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ASME Conference Presenter Attendance Policy and Archival Proceedings

2018;():V013T00A001. doi:10.1115/IMECE2018-NS13.
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This online compilation of papers from the ASME 2018 International Mechanical Engineering Congress and Exposition (IMECE2018) represents the archival version of the Conference Proceedings. According to ASME’s conference presenter attendance policy, if a paper is not presented at the Conference by an author of the paper, the paper will not be published in the official archival Proceedings, which are registered with the Library of Congress and are submitted for abstracting and indexing. The paper also will not be published in The ASME Digital Collection and may not be cited as a published paper.

Commentary by Dr. Valentin Fuster

Design, Reliability, Safety, and Risk: CAD, CAM, and CAE Design

2018;():V013T05A001. doi:10.1115/IMECE2018-86287.

A nitinol-based arch wedge support (AWS) was designed using computational approach. Finite element analysis (FEA) was performed to on this design to assess the influence of loading, boundary conditions, and thickness on the mechanical response of the computer-aid design (CAD) model. Five loading conditions caused by different human movements, two boundary conditions, and three thicknesses are involved in this computational study. FEA results showed that the presented AWS design can resist forces caused by different human motions without generating any permanent deformation. The study features the first time to design and evaluate a thin-walled nitinol AWS model. The results of this study form the background of prototyping and experimental testing of the design in the next phase.

Commentary by Dr. Valentin Fuster
2018;():V013T05A002. doi:10.1115/IMECE2018-86988.

In order to complete the mating and demating operations of the electrical connectors for underwater applications in the deep water environment, the pressure-balanced oil-filled (PBOF) structures are designed to compensate the huge water pressure. This paper focuses on the sealing performance of three sealing systems used in connectors, including the O-ring seals, rectangular seals, and U-cup seals. A method coupled the finite element analysis and elastohy-drodynamic lubrication (EHL) numerical model is presented to describe the issue. Results show that the rectangular seals perform best in fluid leakage, and O-ring seals are better in reducing the friction force. The oil leakages of the seals increase with the speed while the seawater leakages remain roughly constant. And the oil leakages of all the seals are larger than the seawater leakage. Types of seal rings, fluid viscosity and operation speed of connector can all influence the sealing performance of wet-mate connectors.

Commentary by Dr. Valentin Fuster
2018;():V013T05A003. doi:10.1115/IMECE2018-86996.

In this paper, a new algorithm for similar 3D CAD model difference examination based on geometric matching is presented. Firstly, using the boundary representation (B-rep) method, the two 3D models are decomposed into two sets of surfaces, each with an attributed adjacency graph (AAG) which is established using adjacency relationship of corresponding surfaces. The vertices of the AAG are set as the geometric information about surfaces (i.e. surface type, area). The edges of the AAG present the adjacency between surfaces, and the attribute information (i.e. the type and length of edges, the angle between two adjacent surfaces) is also stored in the AAG. Secondly, the surface similarity between two models is calculated according to their types, areas, composition edges and topological relationships. At the same time, the similarity matrix which stores the surface similarity coefficients is generated to find the geometric and topological optimal matching surfaces. Then, in the AAG, with the corresponding vertices of the optimal matching surface pair as the center, the remaining surfaces of two models are quickly and optimally matched according to the topological connections and similarity coefficients while the unmatchable ones are defined as added or deleted surfaces. Finally, differences between the two models are evaluated by analyzing and comparing the geometric attribute information about the matched surfaces.

In order to validate the effectiveness and feasibility of the proposed algorithm, a software prototype for similar model difference examination has been developed. The effectiveness and feasibility of the algorithm have been verified by engineering applications through the industrial needs. The results show that this algorithm can effectively compare the differences among different design iterations and demonstrate its potentials for a wide range of engineering design iterations examination problems.

Commentary by Dr. Valentin Fuster
2018;():V013T05A004. doi:10.1115/IMECE2018-87404.

Design reusability largely depends on the parametric quality of its associated digital product data. In this regard, the quality of the master model (typically a history-based parametric model) is crucial. However, no quantitative metrics exist that can provide an accurate assessment of parametric complexity and model reusability. In this paper, a set of 370 parametric 3D CAD models of various geometric complexities were analyzed to assess their robustness when undergoing alteration. Three indicators for estimating the modification ability of the model are proposed: Ratio for Exhaustive Modification, Ratio for Selective Exhaustive Modification, and Ratio for Weighted Exhaustive Modification. Correlations between these indicators as well as other geometric complexity metrics are studied. The geometric complexity metrics considered in our study include number of faces, surface area to volume ratio, sphericity, and convexity. Our experimental results with the proposed indicators provide new insights on the quantitative assessment of parametric complexity and support their use as reliable indicators of CAD model reusability.

Commentary by Dr. Valentin Fuster
2018;():V013T05A005. doi:10.1115/IMECE2018-87531.

Using a wheelchair can be a challenging task for people with reduced force and control of muscles of abdomen or lower back. Spinal cord injured (SCI) people are the majority of those who are spending most of the day on a wheelchair and a proper training and chair setup is mandatory to reach a good level of functionality and to avoid harms and side effects. In order to assess the complex motion of a person self-pushing a wheelchair, a motion capture (Mocap) system has been arranged and a group of SCI patients has been acquired in a hospital gym. The Mocap system uses three Microsoft Kinect RGB-D sensors and iPisoft to perform the recording of the 3D motion. The main goal of the research is to provide therapists with a quantitative method to define a preliminary configuration in an objective way once is given the user’s medical conditions and his/her way of using the wheelchair. Working side by side with physiotherapists, the main parameters to be evaluated (e.g. pushing angles) have been identified and algorithms have been identified to automatically extract them from the 3D digital avatar model data coming from the Mocap system. The performance of the patients is then analyzed taking into account the wheelchair setup (e.g. position and inclination of the seat and of the back). The influence of geometric parameters on patients’ motion is analyzed so that design guidelines for configuration can be found. The overall outcome is to maximize performance and minimize side effects and fatigue, providing users with a better experience on the wheelchair.

Topics: Wheelchairs
Commentary by Dr. Valentin Fuster
2018;():V013T05A006. doi:10.1115/IMECE2018-88421.

In vehicle design modeling and simulation, surrogate model is commonly used to replace the high fidelity Finite Element (FE) model. A lot of simulation data from the high-fidelity FE model are utilized to construct an accurate surrogate model requires. However, computational time of FE model increases significantly with the growing complexities of vehicle engineering systems. In order to attain a surrogate model with satisfactory accuracy as well as acceptable computational time, this paper presents a model updated strategy based on multi-fidelity surrogate models. Based on a high-fidelity FE model and a low-fidelity FE model, an accurate multi-fidelity surrogate model is modeled. Firstly, the original full vehicle FE model is simplified to get a sub-model with acceptable accuracy, and it is able to capture the essential behaviors in the vehicle side impact simulations. Next, a primary response surface model (RSM) is built based on the simplified sub-model simulation data. Bayesian inference based bias term is modeled using the difference between the high-fidelity full vehicle FE model simulation data and the primary RSM running results. The bias is then incorporated to update the original RSM. This method can enhance the precision of surrogate model while saving computational time. A real-world side impact vehicle design case is utilized to demonstrate the validity of the proposed strategy.

Commentary by Dr. Valentin Fuster

Design, Reliability, Safety, and Risk: Crashworthiness, Occupant Protection, and Biomechanics

2018;():V013T05A007. doi:10.1115/IMECE2018-86521.

Metal-polymer hybrid (MPH) materials can integrate the excellent mechanical properties of metal and complex geometry formability of polymer into a single component, which has become an effective way of reducing the weight of automotive semi-structural components. For example, the hybrid steel/thermoplastic polymer has been applied in automotive front-end modules, bumper cross-beams and B-pillars due to its light weight, excellent strength and stiffness, good corrosion resistance and recycling, high integration and reasonable cost. These components are usually subjected to impact or crash loads and the strain rate effect should be taken into account.

This paper aims to experimentally and numerically study the dynamic behavior of MPH materials at different strain rates and provide an accurate and efficient numerical model for crash simulation of vehicles with MPH components.

Firstly, MPH specimens with high strength steel (HSS) and glass fiber-reinforced thermoplastic polymer (GFRTP) were fabricated by direct injection molding adhesion (DIMA) process. Then, the dynamic mechanical properties of MPH specimens under strain rates from 800 s−1 to 2000 s−1 were investigated by Split Hopkinson Pressure Bar (SHPB) experiments. Finally, a strain rate-dependent numerical model was established in ABAQUS software to simulate the dynamic behavior of MPH specimens and validated by experimental results. Three numerical approaches for modeling the interface between the two discrete material phases were considered and compared to examine the level of interaction between two constitute materials. Cohesive zone modeling technique at the interface which saved modeling and characterization time and showed adequate predictive capability proved to be generally applicable to the evaluation of structural concepts in an early vehicle development stage.

This study provides a foundation for the future engineering application of HSS/GFRP hybrid materials and numerical models for automotive crash simulation.

Commentary by Dr. Valentin Fuster
2018;():V013T05A008. doi:10.1115/IMECE2018-86684.

Crash test results have shown that vehicles which receive good ratings in existing co-linear consumer information tests still may require structural modifications for good performance in NHTSA’s frontal oblique test procedure. The purpose of this study was to determine incremental vehicle structural change requirements and their associated mass and cost to significantly reduce occupant compartment intrusion. An available finite element model of a mid-size sedan was updated and validated using data from a 2015 Toyota Camry. The generated baseline model correlated well with the New Car Assessment Program (NCAP) full overlap test, NHTSA’s left and right oblique impact tests, and with the IIHS small and moderate overlap crash configurations. An iterative optimization process was used to develop necessary countermeasures to reduce occupant compartment intrusion according to defined design goals for the left and right oblique impact configuration. No unintended consequences, i.e. no considerable increase of vehicle pulse for oblique and co-linear load cases were observed. The associated added mass was 10.8kg and the associated cost was $30. Occupant risk analysis was not part of this study. Additional research in concert with restraint systems and occupants would ensure that the optimized structure does not adversely affect the measured occupant injury predictions.

Topics: Countermeasures
Commentary by Dr. Valentin Fuster
2018;():V013T05A009. doi:10.1115/IMECE2018-86793.

Polymethylmethacrylate (PMMA) has been widely utilized to manufacture the covers of aircraft cockpits, naval vessels, car windows and so on, due to their high transmittance, low density, easy processing formability, high corrosion resistance and excellent mechanical properties. Under special conditions such as ejection lifesaving, the PMMA plate needs to be split precisely by explosion cutting technology. Hence, an accurate numerical simulation of PMMA structures is significantly important in engineering application. This paper aims to study the cutting behavior of PMMA plate numerically and investigate the influencing factors on cutting performance of PMMA plates. First of all, the simulation of explosion cutting process of PMMA plate is carried out by a non-linear explicit solver in LS-DYNA software using the fluid-solid coupling method. Jones-Wilkins-Lee (JWL) equation of state is used to simulate the relationship between the transient pressure and specific volume of explosives during explosion. The material model considering failure behaviors is used in the simulation. Additionally, the influence of explosive dosage as well as explosive type on the cutting performance of PMMA plate is investigated. Furthermore, the effect of PMMA geometry size on cutting performance is discussed. This study contributes to the knowledge for the design of PMMA structures which needs explosion cutting and the selection of explosive dosage and explosive type.

Topics: Explosions , Cutting
Commentary by Dr. Valentin Fuster
2018;():V013T05A010. doi:10.1115/IMECE2018-87700.

The U.S. Department of Transportation (DOT) Federal Railroad Administration (FRA) began promulgating regulations for the structural crashworthiness of passenger rail equipment at 49 Code of Federal Regulations (CFR) Part 238 on May 12, 1999. These Passenger Equipment Safety Standards (PESS) [1] include requirements affecting the designs of sidewall structures on passenger rail equipment. The FRA’s Office of Research, Development and Technology and the DOT’s Volpe National Transportation Systems Center are conducting research to evaluate the side impact strength of Tier I passenger rail equipment designs that have been constructed according to the current side structure regulations in §238.215 and §238.217.

Following a fatal 2011 accident in which a highway semitrailer truck impacted the side of a passenger train that was transiting a grade crossing in Miriam, NV, the National Transportation Safety Board (NTSB) recommended that the FRA “develop side impact crashworthiness standards (including performance validation) for passenger railcars that provide a measurable improvement compared to the current regulation for minimizing encroachment to and loss of railcar occupant survival space” [2].

This paper describes the status of the current FRA research related to side structure integrity and describes the planned next stage of the research program which will include analyzing the performance of generalized passenger railcar structures in side impact collision scenarios. A discussion of the technical challenges associated with analyzing side impacts on passenger rail equipment is also presented.

Topics: Rails
Commentary by Dr. Valentin Fuster
2018;():V013T05A011. doi:10.1115/IMECE2018-87736.

The Hybrid-III Rail Safety (H3-RS) anthropomorphic test device (ATD), also known as a crash test dummy, was developed by the Rail Safety and Standards Board (RSSB), DeltaRail (now Resonate Group Ltd.), and the Transport Research Laboratory (TRL) in the United Kingdom between 2002 and 2005 for passenger rail safety applications [1]. The H3-RS is a modification of the standard Hybrid-III 50th percentile male (H3-50M) ATD with additional features in the chest and abdomen to increase its biofidelity and eight sensors to measure deflection. The H3-RS features bilateral (left and right) deflection sensors in the upper and lower chest and in the upper and lower abdomen; whereas, the standard H3-50M only features a single unilateral (center) deflection sensor in the chest with no deflection sensors located in the abdomen.

Additional H3-RS research was performed by the Volpe National Transportation Systems Center (Volpe Center) under the direction of the U.S. Department of Transportation, Federal Railroad Administration (FRA) Office of Research, Development, and Technology. The Volpe Center contracted with TRL to conduct a series of dynamic pendulum impact tests [2]. The goal of testing the abdomen response of the H3-RS ATD was to develop data to refine an abdomen design that produces biofidelic and repeatable results under various impact conditions with respect to impactor geometry, vertical impact height, and velocity.

In this study, the abdominal response of the H3-RS finite element (FE) model that TRL developed is validated using the results from pendulum impact tests [2]. Results from the pendulum impact tests and corresponding H3-RS FE simulations are compared using the longitudinal relative deflection measurements from the internal sensors in the chest and abdomen as well as the longitudinal accelerometer readings from the impactor. The abdominal response of the H3-RS FE model correlated well with the physical ATD as the impactor geometry, vertical impact height, and velocity were changed. There were limitations with lumbar positioning of the H3-RS FE model as well as the material definition for the relaxation rate of the foam in the abdomen that can be improved in future work.

The main goal of validating the abdominal response of the dummy model is to enable its use in assessing injury potential in dynamic sled testing of crashworthy workstation tables, the results of which are presented in a companion paper [3]. The authors used the model of the H3-RS ATD to study the 8G sled test specified in the American Public Transportation Association (APTA) workstation table safety standard [4]. The 8G sled test is intended to simulate the longitudinal crash accleration in a severe train-to-train collision involving U.S. passenger equipment. Analyses of the dynamic sled test are useful for studying the sensitivity of the sled test to factors such as table height, table force-crush behavior, seat pitch, etc., which help to inform discussions on revisions to the test requirements eventually leading to safer seating environments for passengers.

Commentary by Dr. Valentin Fuster
2018;():V013T05A012. doi:10.1115/IMECE2018-87751.

Fixed workstation tables in passenger rail coaches can pose a potential injury hazard for passengers seated at them during an accident. Tables designed to absorb impact energy while minimizing contact forces can reduce the risk of serious injury, while helping to compartmentalize occupants during a train collision. The Rail Safety and Standards Board (RSSB) in the U.K. issued safety requirement GM/RT2100, Issue 5 [1] and the American Public Transportation Association (APTA) in the U.S. issued safety standard APTA PR-CS-S-018-13, Rev. 1 [2] with the goals of setting design and performance requirements for energy-absorbing workstation tables.

The U.S. Department of Transportation, Federal Railroad Administration (FRA) Office of Research, Development and Technology directed the Volpe National Transportation Systems Center (Volpe Center) to evaluate the performance of the Hybrid-III Rail Safety (H3-RS) anthropomorphic test device (ATD), also known as a test dummy, in the APTA sled test in order to incorporate a reference to the H3-RS in the safety standard. The Volpe Center contracted with the manufacturer of the H3-RS, Transport Research Laboratory (TRL), in the U.K. to conduct a series of sled tests [3] with energy-absorbing tables, donated by various table manufacturers. The tables were either already compliant with the RSSB table standard or were being developed to comply with the APTA table standard.

The sled test specified in Option A of the APTA table standard involves the use of two different 50th percentile male frontal impact ATDs. The H3-RS and the standard Hybrid-III (H3-50M) ATDs performed as expected. The H3-RS, which features bilateral deflection sensors in the chest and abdomen, was able to measure abdomen deflections while the H3-50M, which features a single sensor measuring chest compression, was not equipped to measure abdomen deflection.

This study attempts to validate a finite element (FE) model of the APTA 8G sled test with respect to the thorax response of the H3-RS and H3-50M. The model uses a simplified rigid body-spring representation of one of the energy absorbing tables tested by TRL. The FE models of the H3-RS ATD and the H3-50M ATD were provided by TRL and LSTC, respectively. Results from the sled tests and FE simulations are compared using data obtained from the chest accelerometer, the chest and abdomen deflection sensors, and the femur load cells. Using video analysis, the gross motion of the dummies and table are also compared. Technical challenges related to model validation of the 8G sled test are also discussed.

This study builds on previous analyses conducted to validate the abdomen response of the H3-RS FE model, which are presented in a companion paper [4].

Commentary by Dr. Valentin Fuster
2018;():V013T05A013. doi:10.1115/IMECE2018-87904.

Car-pedestrian collision fatalities have been reported for a significant number of roadside accidents around the world. In order to reduce the lower extremity injuries in car-pedestrian collisions, it is important to determine the impact forces on the pedestrian and conditions that the car frontal side impacts on the lower extremities of the pedestrian. The Working Group 17 (WG17) of the European Enhanced Vehicle-safety Committee (EEVC) has developed a legform subsystem impactor and procedure for assessing pedestrian collisions and potential injuries. This research describes a methodology for the evaluation of the legform impactor kinematics after a collision utilizing finite element (FE) models of the legform and cars and comparing the simulation results with the ones from a multi-body legform model as well as a 50th percentile male human pedestrian model responses.

Two approaches are carried out in the process. First, the collision strike simulations with the FE model using an FE lower legform is considered and validated against the EVVC/WG17 regulation criteria. Secondly, the collision strike simulations with a multi-body legform and an ellipsoidal multi-body car model are conducted to compare the responses from the FE model and the multi-body model. The results from the impact simulations of FE legform and the multi-body legform are also compared with the ones from a full-size pedestrian model at constant speeds. All the models and simulation in this are using the LS-DYNA nonlinear FE code, while the multibody legform, car, and full-sized pedestrian models are developed and evaluated in MADYMO.

The results from this study demonstrate the differences between the subsystem legform and the full-size pedestrian responses as well as suitability of various FE and multibody models related to pedestrian impact responses. Different workbenches comparisons with finite model and ellipsoidal models gives more better correlation to this research.

Commentary by Dr. Valentin Fuster
2018;():V013T05A014. doi:10.1115/IMECE2018-88398.

The mesh morphing method is widely applied in building subject-specific human finite element models. However, there are many problems yet to be resolved when applying the mesh morphing method in subject-specific modeling, such as calculation difficulties and low morphing accuracy. To solve these problems above, an efficient peak-selection RBF mesh morphing method is proposed in the paper. Firstly, by comparing different types of radial basis functions, an optimal kernel function is selected to improve morphing accuracy. Secondly, the landmarks are reduced by selecting multiple peak nodes from the object surfaces, so as to reduce iteration steps and improve the mesh generation efficiency. The proposed peak-selection Radial Basis Function (RBF) mesh morphing method is further demonstrated through a subject-specific child finite element modeling problem. This mesh morphing method has important significance for analyzing the occupant injury of different body features in motor vehicle crashes.

Topics: Modeling
Commentary by Dr. Valentin Fuster

Design, Reliability, Safety, and Risk: Failure and Forensic Analysis

2018;():V013T05A015. doi:10.1115/IMECE2018-86042.

The spindle system of machine tool produces a huge amounts of process data when it works. These data directly reflect the running state of spindle system but are seldom used to perform early fault warning. This paper proposes a novel early fault warning method adaptive weighted fuzzy Petri-net. Firstly, the long short-term memory (LSTM) is put forward to predict the time-series of future state for spindle system. Then, in order to design a reasoning framework for dynamic knowledge which can adapt to changes in the area of knowledge, an adaptive weighted fuzzy petri-net (AWFPN) is brought up to perform fault diagnosis. Finally, the effectiveness and feasibility of proposed method are verified by simulations and experiments. Results show that the proposed early fault warning method could effectively help to find potential fault information in the manufacturing process and provide the useful advice for maintenance.

Commentary by Dr. Valentin Fuster
2018;():V013T05A016. doi:10.1115/IMECE2018-87609.

The effects of reduced kingpin offset distance at the ground (scrub radius) and speed were evaluated under controlled test conditions simulating front tire tread detachment drag. While driving in a straight line at target speeds of 50, 60, or 70 mph with the steering wheel locked, the drag of a tire tread detachment was simulated by applying the left front brake with a pneumatic actuator. The test vehicle was a 2001 dual rear wheel four-wheel-drive Ford F350 pickup truck with an 11,500 lb. GVWR. The scrub radius was tested at the OEM distance of 125 mm (Δ = 0) and at reduced distances of 49 mm (Δ = −76) and 11 mm (Δ = −114). The average steady state responses at 70 mph with the OEM scrub radius were: steering torque = −24.5 in-lb; slip angle = −3.8 deg; lateral acceleration = −0.47 g; yaw rate = −8.9 deg/sec; lateral displacement after 0.75 seconds = 3.1 ft and lateral displacement after 1.5 seconds = 13.1 ft. At the OEM scrub radius, responses that increased linearly with speed included: slip angle (R2 = 0.84); lateral acceleration (R2 = 0.93); yaw rate (R2 = 0.73) and lateral displacement (R2 = 0.59 and R2 = 0.87, respectively). At the OEM scrub radius, steer torque decreased linearly with speed (R2 = 0.76) and longitudinal acceleration had no linear relationship with speed (R2 = 0.09). At 60 mph and 70 mph for both scrub radius reductions, statistically significant decreases (CI ≥ 95%) occurred in average responses of steer torque, slip angle, lateral acceleration, yaw rate, and lateral displacement. At 50 mph, reducing the OEM scrub radius to 11 mm resulted in statistically significant decreases (CI ≥ 95%) in average responses of steer torque, lateral acceleration, yaw rate and lateral displacement. At 50 mph the average slip angle response decreased (CI = 87%) when the OEM scrub radius was reduced to 11 mm.

Commentary by Dr. Valentin Fuster

Design, Reliability, Safety, and Risk: General Topics on Risk, Safety, and Reliability

2018;():V013T05A017. doi:10.1115/IMECE2018-86678.

Renewable energy and natural gas are displacing coal and nuclear power in many parts of the world as sources of electricity. While, the environmental benefits of such changes seem clear, the impact on worker safety, especially in developed nations is less clear. Coal mining is a relatively dangerous occupation, though one that has grown significantly safer in recent decades. Manufacturing and installation of solar photovoltaic (PV) power may pose less risk to workers on a per hour basis, but the number of worker hours necessary to generate a Megawatt-hour of electricity is currently higher for solar PV than it is for coal-generated power. The implications for the overall occupational burden of accidental deaths and injuries has not been previously detailed. This paper presents the results of a Monte Carlo sensitivity analysis for changes in total worker injuries and injury rates under different assumptions for the future energy mix in developed nations. Projections from the Energy Information Agency (EIA) and other organizations together with documented productivity gains for the various energy industries provide test cases for this analysis. The analysis indicates that future occupational fatality and injury burden of the energy sector is highly dependent on improvements in safety in the expanding industries, while specific projections on the share of specific technologies is less critical. This result highlights the need to invest in occupational risk mitigation in these industries.

Commentary by Dr. Valentin Fuster
2018;():V013T05A018. doi:10.1115/IMECE2018-87156.

A challenge for greyhound racing is optimizing the tracks to minimize the risk of injuries. The effects of different track design variables on greyhound injury rates has not been explored sufficiently. The purpose of this paper is to present some preliminary findings on the effect of greyhound racetrack design variables such as the track curvature and lure alignment. An analysis was carried out of two years of greyhound racing injury data from three different tracks in New South Wales, Australia. The data from before and after an intervention was introduced were compared. Variables in the study, which may affect\ the analysis were investigated to minimize the errors. The analysis showed that there is a reduction in injury rates for a longer lure arm in the tracks with short or no straight section.

To verify the effect of track design variables on the greyhound dynamics a kinematic simulation of greyhound center of gravity was created. The simulation considered fundamental variables correlating directly with kinematics between the greyhound and the track. The simulation data showed that the rate of change in the rotation of the greyhound heading direction decreases when the track running path has a more gradual curvature. The result of the simulation showed excellent agreement with that of injury data analysis.

Commentary by Dr. Valentin Fuster
2018;():V013T05A019. doi:10.1115/IMECE2018-87623.

Rolling element bearings are very important and highly utilized in many industries. Their catastrophic failure due to fluctuating working conditions leads to unscheduled breakdown and increases accidental economical losses. Thus these issues have triggered a need for reliable and automatic prognostics methodology which will prevent a potentially expensive maintenance program. Accordingly, Remaining Useful Life (RUL) prediction based on artificial intelligence is an attractive methodology for several researchers. In this study, data-driven condition monitoring approach is implemented for predicting RUL of bearing under a certain load and speed. The approach demonstrates the use of ensemble regression techniques like Random Forest and Gradient Boosting for prediction of RUL with time-domain features which are extracted from given vibration signals. The extracted features are ranked using Decision Tree (DT) based ranking technique and training and testing feature vectors are produced and fed as an input to ensemble technique. Hyper-parameters are tuned for these models by using exhaustive parameter search and performance of these models is further verified by plotting respective learning curves. For the present work FEMTO bearing data-set provided by IEEE PHM Data Challenge 2012 is used. Weibull Hazard Rate Function for each bearing from learning data set is used to find target values i.e. projected RUL of the bearings. Results of proposed models are compared with well-established data-driven approaches from literature and are found to be better than all the models applied on this data-set, thereby demonstrating the reliability of the proposed model.

Commentary by Dr. Valentin Fuster
2018;():V013T05A020. doi:10.1115/IMECE2018-87875.

In the United States, approximately 44 children under the age of five years old drown each year after gaining unauthorized access to above-ground pools via pool ladders. Approximately 704 additional children sustain submersion-related injuries after gaining unauthorized access to above-ground pools via pool ladders. In many cases, these events occurred during brief lapses of adult supervision. The societal cost associated with these deaths and injuries ranges from 134 to 342 million dollars per year. In addition to societal costs, there is also a significant loss in quality of life for near-drowning victims and their families.

Since the 1960’s, several medical studies have been published that discuss children under the age of five accessing above-ground pools and drowning. Several of these medical studies propose solutions to reduce the likelihood of drowning. Despite the proposed solutions in these studies, the rate of such drownings in above-ground pools has not decreased. However, the medical studies do not address how proper and safe engineering design of pool ladders can and should be used to prevent such occurrences.

This paper adds engineering science to these medical studies by including safety engineering principles that can be used to prevent young children from gaining unauthorized access to above-ground pools via pool ladders. Specifically, this paper addresses, hazard and risk assessment, passive safety systems that can be added to pool ladders to prevent drowning incidences, and the economic and technological feasibility of such passive safety systems. This paper shows that the benefits associated with the reduction in societal costs of drowning or near-drowning outweigh the cost of adding passive safety systems to pool ladders.

Commentary by Dr. Valentin Fuster
2018;():V013T05A021. doi:10.1115/IMECE2018-87888.

Engineering decisions that have the greatest effect on worker and public safety occur early in the design process. During these decisions, engineers rely on their experience and intuition to estimate the severity and likelihood of undesired future events like failures, equipment damage, injuries, or environmental harm. These initial estimates can then form the basis of investment of limited project resources in mitigating those risks. Behavioral economics suggests that most people make significant and predictable errors when considering high consequence, low probability events. These biases have not previously been studied quantitatively in the context of engineering decisions, however. This paper describes preliminary results from a set of computerized experiments with engineering students estimating, prioritizing, and making design decisions related to risk. The undergraduate students included in this experiment were more likely to underestimate than overestimate the risk of failure. They were also more optimistic of the effects of efforts to mitigate risk than the evidence suggested. These results suggest that considerably more effort is needed to understand the characteristics and qualities of these biases in risk estimation, and understand what kinds of intervention might best ameliorate these biases and enable engineers to more effectively identify and manage the risks of technology.

Commentary by Dr. Valentin Fuster
2018;():V013T05A022. doi:10.1115/IMECE2018-87889.

Escalators are common mechanical vertical transportation systems that move an estimated 245 million people daily in the U.S. on the more than 33,000 escalators [1]. It has been estimated that about 10,000 escalator-related injuries per year result in an emergency department treatment in the U.S. [2]. A study of escalator injuries published in 2001 concluded that injuries were primarily the result of falls or entrapment at the bottom or top of an escalator or between a moving stair and escalator sidewall [3]. Regarding sidewall entrapment, the 2000 edition of the ASME A17.1, “Safety Code for Elevators and Escalators,” introduced periodic tests for both new and existing escalators to evaluate the potential for sidewall entrapment [4]. The development history of the step/skirt performance index is presented and current requirements in the ASME A17.1 and A17.2, “Guide for Inspection of Elevators, Escalators and Moving Walkways,” codes regarding the index are reviewed. Injury data from the U.S. Consumer Product Safety Commission (CPSC) for escalator riders are analyzed from the timeframe of 1998 to 2017 to seek trends in escalator entrapments during the time period between the introduction of the index and the present.

Topics: Safety , Escalators , Risk
Commentary by Dr. Valentin Fuster

Design, Reliability, Safety, and Risk: Product and Process Design

2018;():V013T05A023. doi:10.1115/IMECE2018-86292.

Currently, pressure vessels that operate in hydrogen service and subjected to fatigue must be designed using a defect tolerant design procedure. This means that first the fracture mechanics properties of the material being considered must be measured in hydrogen at the maximum service pressure. The properties are fatigue crack propagation properties and threshold stress intensity factor for hydrogen embrittlement (KIHE). With these properties, a fatigue crack propagation life can be estimated assuming an initial crack size and geometry and growing this defect to failure. The property measurements are costly and can only be performed at a few laboratories. Furthermore, the resulting lives are usually very short because of the assumed initial crack size. These things limit the application of this design method to lower cycle or static loading applications. This work introduces a cost-effective method of design and construction of pressure vessels for high cycle use in hydrogen service at pressures below 40,000 psi that eliminates the need for determining fracture mechanics properties in hydrogen environment. The method uses shrink fit construction of a liner inside a jacket. The method requires that when the pressure is applied, the magnitude of the resultant stress at the pressure boundary of the liner is more compressive than the magnitude of the applied pressure and the maximum allowed size of defect in the jacket at the interface between the jacket and the liner is such that when the cyclic stress is applied the resultant fatigue loading of that defect at that location to be less than the threshold value for growth of that defect.

Commentary by Dr. Valentin Fuster
2018;():V013T05A024. doi:10.1115/IMECE2018-86551.

In our group, we are developing flexure hinge based manipulators made of nitinol for minimally invasive surgery. On the one hand, sufficient flexibility is required from flexure hinges to be able to cover the surgical workspace. On the other hand, the bending amount of the flexure hinges has to be limited below the yielding point to ensure a safe operation. As a result of these considerations, it has to be questioned how much bending angle a nitinol flexure hinge with given geometric dimensions can provide without being subject to plastic deformation. Due to the nonlinearities resulting from large deflections and the material itself, the applicability of the suggested approaches in the literature regarding compliance modeling of flexure hinges is doubtful. Therefore, a series of experiments was conducted in order to characterize the rectangular cross section nitinol flexure hinges regarding the flexibility-strength trade-off. The nitinol flexure hinge samples were fabricated by wire electrical discharge machining in varying thicknesses while keeping the length constant and in varying lengths while keeping the thickness constant. The samples were loaded and unloaded incrementally until deflections beyond visible plastic deformation occured. Each pose in loaded and unloaded states was recorded by means of a digital microscope. The deflection angles yielding to permanent set values corresponding to 0.1% strain were measured and considered as elastic limit. A quasilinear correlation between maximum elastic deflection angle and length-to-thickness ratio was identified. Based on this correlation, a minimal model was determined to be a limit for a secure design. The proposed guideline was verified by additional measurements with additional samples of random dimensions and finite element analysis.

Commentary by Dr. Valentin Fuster
2018;():V013T05A025. doi:10.1115/IMECE2018-86572.

The pitting resistance of straight bevel gears, like other gears, is commonly assessed on the basis of the contact stress in a gear mesh. A new contact stress model for straight bevel gears is used to estimate the contact stress in some gearset designs and compared with predictions from ISO 10300 bevel gear standards. In the cases considered, the new model contact stresses defer from the ISO values in the range of 13% to 33%, with the ISO predictions generally on the higher side. These deviations appear to be somewhat high but not unreasonable because of obvious differences in the two models. The ISO standard uses the mid facewidth cone radius in its contact stress model while the new model uses the cone backend radius which is larger than the mid facewidth cone radius. Another contributing factor is that the load service factor values evaluated from ISO methods are generally higher than those of the new model values, based largely on American Gear Manufacturers Association (AGMA) methods. It should be noted that the power ratings for all the design cases studied are below 10 kW.

Topics: Stress , Bevel gears
Commentary by Dr. Valentin Fuster
2018;():V013T05A026. doi:10.1115/IMECE2018-86573.

A simple but accurate combined computationaland graphical method for creating drawings and solid models of standard involute gears is presented. The method is predicated on the fact that the gear tooth angle at the base circle is fixed for a gear of specified module or size. As the contact point moves along the involute curve from the base circle point through the pitch point to the addendum circle point; the involute and gear tooth contact angles change continuously but their sum is fixed at the value it was at the base circle. This allows the coordinates of points on the involute curve to be generated analytically without employing the roll angle as current available methods. The generated data can be implemented in any computer design drafting (CDD) package platform to create an accurate gear tooth profile. The computations are done with Microsoft Excel which generates the graphical data for the gear tooth profile that are used in the CDD package. The required inputs to the Excel spreadsheet are the gear module size, the pressure angle, the number of teeth and the radial number of steps. A gearset example is considered and created with this method. The solid model of the example gearset in mesh and 2D drawing of the pinion are presented.

Topics: Gear teeth
Commentary by Dr. Valentin Fuster
2018;():V013T05A027. doi:10.1115/IMECE2018-86711.

This paper establishes the baseline for incorporating the Internet of Things (IoT) into the Reliability-Risk model. The authors developed the original Reliability-Risk model as a “trade-off” tool for ranking conceptual designs as a function of reliability. We summarize the original Reliability-Risk model and algorithm and discuss the process of updating the standard Integration Definition Function Modeling (IDEF0) technique with the IoT. Inserting the updated IDEF0 into the Reliability-Risk modeling framework creates a dynamic closed-loop system. We identified a concept for using a probabilistic workflow to automate the new closed-loop system and discuss a Reliability-Risk sensitivity approach.

The Reliability-Risk model ranked five conceptual packaging designs against 17 criteria for incorporation into the supply chain. The authors use a Multi-Criteria-Decision System (MCDS) to establish the rankings. The paper re-visits the original example to include data (the IoT) such as shock, temperature, and humidity obtained from various nodes in the logistics cycle. After the sensor data are incorporated, updated systems specification and reliability models resulted in a new ranking. We will discuss the results of the rankings.

Current research in developing the Digital Twin and Digital Thread are lacking in the area of logistics modeling. The incorporation of Discrete Event Simulation models to simulate transportation, handling, and storage shows promise to address these shortcomings. Therefore, we will briefly discuss our approach on incorporating Discrete Event Simulation modeling into the Reliability-Risk-IoT model to create a “logistics twin.”

Commentary by Dr. Valentin Fuster
2018;():V013T05A028. doi:10.1115/IMECE2018-86715.

In the sport of basketball, it is important to practice shooting the ball to develop the skill of making the shot in the basket at a high efficiency. Making shots at a high efficiency allows the player to succeed at a high level in the sport. The main focus of the paper describes the design and development of an automatic basketball rebound (ABR) system. The developed ABR provides a system that will launch the ball back to the player at any position on the court within a 50-foot radius. This is accomplished by a variable spring loaded launching mechanism that will compress a spring, depending on the players location, to generate the appropriate force required to launch the ball back to the player. The novel launching mechanism developed is mounted to a rotary table that ensures the launching mechanism is in the correct orientation with the player once the ball is launched. The player is outfitted with an inertial measurement unit to track their position using a method known as dead reckoning. This information is relayed back to a microcontroller that determines the system response. The ABR system is made from lightweight materials and is compact such that it is easy to move around compared to its predecessors.

Commentary by Dr. Valentin Fuster
2018;():V013T05A029. doi:10.1115/IMECE2018-86748.

This work presents the novel design of a smart hydrodynamic journal bearing with adjustable radial clearance. The dynamic behavior of this bearing was mathematically modeled and examined. Finite Element Analyses were conducted to determine the effort needed to change and maintain a desired value for the radial clearance. First, the bearing set was modelled as a two-degrees-of-freedom dynamic system. For an initial value of a radial clearance of c = 0.0508 mm, the bearing set exhibited an unstable behavior under its postulated operating condition. A Generic Algorithm (GA) was used to define an objective function so that an optimum value of c could be determined in order to ring the bearing into a stable operating condition. The GA determined the value of radial clearance of c = 0.0051 mm for this purpose. Second, a Jeffcott rotor was modeled as an eight-degrees-of-freedom vibratory stem supported by two identical smart bearings. For an initial value of c = 0.025 mm, the disk’s peak-to-peak vibrations amplitude was determined to be 8 × 10−5 meter and 8.5 × 10−5 m along two orthogonal axes of a reference frame respectively. The GA was used to determine a new value for the radial clearance of the supporting bearings in order to reduce the disk’s vibration level. A new value of radial clearance c was determined to be 0.095 mm which in turn reduced the vibrations of the dick from 8 × 10−5 and 8.5 × 10−5 meter to 3.5 × 10−5 and 2.5 × 10−5 m respectively.

Commentary by Dr. Valentin Fuster
2018;():V013T05A030. doi:10.1115/IMECE2018-86888.

Engineering design is typically a team effort. Design teams frequently need to push technical boundaries to solve the most relevant challenges faced by our society. A significant area of research across multiple fields of investigation, including engineering, is the understanding and use of an individual’s cognitive attributes in the process of assembling productive teams. This research proposes an approach to assembling an engineering design team by first defining the desirable cognitive attributes in the team members. Subsequently, based on individual cognitive profile assessments along these attributes, an exhaustive list of possible design teams is investigated based on their cumulative attribute level. We compare the performance of two teams predicted to perform at different levels, and our results verify the differences between the observations of team interactions and the quality of designs produced. In addition to self-assessments, we also investigate the brain activity of the respondents using electroencephalography (EEG) to evaluate performance in an individual and a team setting. This analysis intends to highlight the characteristics of an individuals’ brain activity under different circumstances to reveal if these characteristics contribute to the success of a design team. EEG data revealed observations such as correlation between raw amplitude and level of team contribution, a higher variation in the channel power spectral density during individual versus team tasks, and a degradation of alpha activity moving from individual to group work. The results of this research can guide organizations to form teams with the necessary cognitive attributes to achieve the optimum design solution.

Topics: Design , Teams
Commentary by Dr. Valentin Fuster
2018;():V013T05A031. doi:10.1115/IMECE2018-86997.

In hot summer, the sun rays strike the roof surface and heat up the enclosed attic. Passive vents (Soffit or Gable) allow some circulation of fresh air. Presently, in India, passive Whirlybird is predominantly used for ventilation purposes, which spins and sucks up the warm air and forces it out upwards through the vent on the roof. Since it depends mainly on the natural wind velocity, it’s efficiency to cost ratio is very low. Also, the accumulation of dust particles has a deleterious effect on the performance and life of the unit. Hence, in this work, a roof top solar ventilator has been designed and developed at low cost to address the above-mentioned problems. This unit has a high-performance brushless DC motor, an adjustable solar panel to achieve optimal solar exposure and it blends seamlessly into roof. The solar panel powers the fan through the motor, thereby increasing the air circulation through the vent. This increased air circulation provides the required pressure to force the hot air out from the attic. During hot summer, the difference in temperature between the floor and the ceiling can reach 10–15 °C, leading to a constant heat pile up in the attic and this system can limit the temperature of the attic to 40°C. In winter season, moist air present inside the house warms up, rises and collides with the cold air entering through the roof. This provides a mixed circulation that prevents the cold air from entering the roof and also reduces freezing of snow on the roof surface. Further, it keeps the inside space cooler and drier. Since this ventilator operates on renewable energy source, it is a simple and feasible solution that is environmentally friendly at low-cost. This provides healthy, energy efficient homes and work spaces as it reduces the usage of air conditions and heaters. A comparative study on the performance, life and cost of both the existing and the newly developed ventilators has been made and the same is reported.

Topics: Design , Solar energy , Roofs
Commentary by Dr. Valentin Fuster
2018;():V013T05A032. doi:10.1115/IMECE2018-87180.

Small-scale spill detection and removal represents a fundamental concern for a wide variety of industries such as food production plants. Often these spills are detected and cleaned manually resulting in slower operations and less productivity. In this design project, a robotic solution, including detection of the spill and removal of it, is presented to maintain high productivity and operations standards in a given organization. The design consists of a plastic structure including acrylic and polylactide (PLA), a vacuum motor, spill detection electronics using image processing and control apparatus. For initial testing purposes, the robotic attachment was mounted to iRobot Create 2 as a movement platform. Testing methods consisted of rounds of spill cleaning for a variety of materials including oil and syrup. As a result of those tests, the design can be scaled to different industries such as Oil and Gas, Energy, Supermarket and Warehouses. Results show improved spill detection and removal compared to manual methods.

Topics: Robotics
Commentary by Dr. Valentin Fuster
2018;():V013T05A033. doi:10.1115/IMECE2018-87608.

Given the current trend in manufacturing to decrease part variability, and in order to increase product quality, dimensional tolerances are becoming more exacting. With this in mind, and with the decreased time allotted for components to progress from design to manufacture, it has become more critical that accurate models of the manufacturing process are developed. This paper investigates the changes in cross sectional area when a prismatic bar is plastically deformed into a ring of constant diameter. Through further processing, these rings are transformed into components that function to secure mechanical components, such as bearings, into assemblies. Failure of the ring can cause significant damage, or failure of the assembly. Typical thickness tolerances are on the order of +/−.002” (0.05 mm), but can be as small as +/−.0002” (0.005 mm). Also, a growing trend in manufacturing is for the final ring to have a specified thickness on the inner and outer edge within this tolerance band. The rings are produced in various metallic materials with different mechanical properties by continuously coiling prismatic bars to a specific diameter. An analytic model based on small strain theory was developed for the simple cross sections of rectangular and trapezoidal geometries. This model was then extended to include the effect of a hyperbolic rather than linear stress distribution through this simple section in order to relieve the constraints of small strain theory and adequately model the actual process. An empirical model was developed based on experimental observations. A numerical model was developed using the commercial finite element analysis (FEA) software Abaqus (SIMULIA, Providence, RI) to simulate the manufacturing process. This was compared to the empirical model developed from production parts for validation. Once the finite element model is validated, it could be used to explore the effects of design parameters (initial dimensions of the prismatic bar, material properties etc.) and create efficient designs for manufacturing. The empirical model can then be used in the design process. Additionally, the numerical simulation could be used to model more complex cross sectional areas which cannot be evaluated analytically. There was adequate agreement between the empirical and numerical models to the extent that the numerical model could be used for more complex cross sectional geometries. A further refinement of the analytic model to include finite strain theory should be used to expand on this.

Commentary by Dr. Valentin Fuster
2018;():V013T05A034. doi:10.1115/IMECE2018-87649.

Human kind has always been intrigued by space but what seems to not make sense is why we aren’t just as intrigued about our ocean. As the life blood of all things on earth we need to understand the approximate 71% of water mass that surrounds us [1]. This is the goal of our paper, bringing interest back to the ocean using unmanned underwater vehicles. In this paper we will discuss the functionality, build and deployment of an intelligent unmanned drone. The mission of this underwater vehicle is to explore the ocean to understand complex ocean dynamics and bring forth the wonders of the ocean to the masses. We will systematically break down the design process of our drone circuitry and sensors on board, then see why we chose these components and sensors to successfully achieve our objective of collecting targeted data from the ocean.

Commentary by Dr. Valentin Fuster
2018;():V013T05A035. doi:10.1115/IMECE2018-87720.

Tensile residual stress (RS) peaks near the weld toe accelerate crack generation and propagation stages reducing dramatically the life of welded components. In order to relief RS, components are typically heat-treated. However, heat treatments can affect the microstructure compromising mechanical properties. In addition, their application in big structures is complex due to size limitations. As an alternative, mechanical treatments such as shot peening can be locally applied. Moreover, they generate local compressive stresses in the treated surfaces, which present beneficial effect in the fatigue strength of treated components.

In the present work, the contribution of shot peening in the fatigue strength of multipass welded joints is numerically evaluated. For that purpose, first the RS stress pattern of a 3 pass butt weld of 10mm thick, 50mm length S275JR plates is calculated. Following, the application of shot peening in the tensile RS area is modelled and the evolution of RS pattern is analyzed. Finally, the fatigue strength of treated and non-treated butt welds is evaluated.

Commentary by Dr. Valentin Fuster
2018;():V013T05A036. doi:10.1115/IMECE2018-88091.

User-centered product design (UCPD) and especially its methods and tools offer a lot of benefits to product development. By using specific data of the user group or by including them into the design process, systems with better functionality and usability arise. However, including the users in an optimum manner means to include them over the whole product development process, which is costly and often too time-consuming regarding the ever shorter product life cycles. An extensive application of UCPD methods is therefore usually not practical for industry.

In order to (1) support the user-centered development process in general and (2) support the selection of appropriate UCPD methods, a multi-channel human-system interaction framework is proposed. It is derived from existing human-computer and human-machine interaction models and further includes additional factors influencing the human-system interaction. However, the framework itself needs further and more detailed elaboration and discussion and currently lacks an allocation of UCPD methods.

Topics: Product design
Commentary by Dr. Valentin Fuster
2018;():V013T05A037. doi:10.1115/IMECE2018-88374.

Spent nuclear fuel, after cooling within a pool storage system, is generally stored in stainless steel dry storage casks. Some dry storage casks have been in regular use for decades, causing increasing interest in technologies to inspect these units. This work presents a case study on the design and prototyping challenges of a robotic inspection system known as PRINSE. PRINSE is designed for in-use dry nuclear waste storage casks, and its development was motivated by a recently completed multi-university NEUP study to develop, deploy, and test sensor systems enabling novel inspection capabilities. The field deployment situation presented particular design challenges not commonly seen in robotics for three reasons: geometric constraints to enter the in-situ cask environment, severe operational temperatures within the cask inspection area, and a high-radiation environment requiring stand-off human tele-operation and remote actuation of the robot from outside the cask. From a design standpoint, project hurdles included the teaming across multiple universities, the need to rapidly develop new prototype systems, and the novel design constraints which had to be managed carefully with the technology development process. This paper presents the specific mechanical engineering design challenges related to this complex system built to inspect dry storage casks. Additionally, it presents insights gained during the completion of the project, with specific focus on the challenges and methods used to achieve design coordination across sub-teams. Key experiences from this project are presented in a design-centric analysis of the management of technical constraints and how these constraints were distributed among the sub-teams.

Commentary by Dr. Valentin Fuster
2018;():V013T05A038. doi:10.1115/IMECE2018-88603.

The choke-level is one of the key factors that influence the falling process of the granular materials which is closely related to the crushing efficiency in the cone crusher. In this paper the motion characteristics of the particles near the choke-level have been analyzed and the phenomenon of single particle breakage below the choke level is pointed out. Based on the multi-zone method, an improved particle shape prediction model is established. In this model, the compound breaking behavior which includes the single particle breakage under the choke-level effect and the inter-particles breakage under the fill-feed, the transformation of particle shape and the particle size distribution in each crushing zone are considered. Tests on the PYG-B1735 cone crusher are conducted in order to validate the improved model. The improved model provides a theoretical foundation for the productivity estimation and the performance optimization.

Commentary by Dr. Valentin Fuster

Design, Reliability, Safety, and Risk: Product Optimization

2018;():V013T05A039. doi:10.1115/IMECE2018-86293.

An optimization framework is developed to minimize structural weight of the front-frame of heavy-duty trucks while satisfying stress constraint. The shape of the frame is defined by a number of design parameters (which define the shape of the side-rail, position and width of the internal brackets, and width of the flanges). In addition, the thickness of the engine-mount, the side-rails, inner-brackets, radiator mount, shock absorber and cab-mount connector are also considered as design variables. Aluminum Alloy, 6013-T6 is chosen as the material and the maximum allowable stress is the yield stress (320 MPa). A quantity known as ‘Violation’ is defined as the ratio of area in the front-end module where stress constraint is violated to the total area of the frame is introduced to implement stress constraints. For optimization, the penalty method is used where the objective is to minimize the total weight while keeping the value of the ‘Violation’ parameter less than 0.1 %. The Particle Swarm Optimization Algorithm is implemented using parallel computation for optimizing the structure. Commercial FEA software MSC.PATRAN is used for creating the geometry and the mesh whereas MSC.NASTRAN is used to perform static analysis. Six design load conditions, each corresponding to a road condition are used for the problem.

Commentary by Dr. Valentin Fuster
2018;():V013T05A040. doi:10.1115/IMECE2018-86952.

The advanced development of additive manufacturing (AM) has greatly promoted the research and application of variable density porous structures. Meanwhile, AM constraints highlight the significance of design for AM (DFAM). The structural performance of existing topology optimization (TO) based design methods is limited and AM constraints are little considered. In this paper, we propose a novel optimization design method of AM oriented porous structures which allows the existence of void. A novel density filter is designed to achieve multi-interval TO for better structural performance and satisfy the minimum feature size constraint. Meanwhile, another customized density filter is designed to obtained support-free porous structure for the buildability constraint of AM. FEA results demonstrate that optimized porous structure designed by proposed method has better stiffness performance and adaptability to AM constraints, compared with existing methods.

Commentary by Dr. Valentin Fuster
2018;():V013T05A041. doi:10.1115/IMECE2018-87057.

Measurement of the reaction forces and moments (general wrench) are instrumental in the development stage of a product. Currently available measurement setups have varying ranges in different directions. The range of the device is limited to least stiff direction. The optimal use of load cell for predicted force/moment bounds is based on utilizing the system efficiently in different directions. We have presented a methodology to optimize the measurement setup based on directional stiffness behavior. The technique is coupled to design of load cell based on the characteristic structure of “Stewart platform”. The optimization function proposed allows the designer to design a measurement setup for a bound of the reaction force/moment. Additionally, the nonlinearities like friction and issue of loose joints due to relative motion at the passive joints are avoided. The improvement comes from replacement of the mechanical joints by kinematically constrained flexures.

Commentary by Dr. Valentin Fuster
2018;():V013T05A042. doi:10.1115/IMECE2018-87728.

This paper presents a novel design methodology, which combines topology and shape optimization to define material distribution in the structural design of a truss. Firstly, in order to identify the best layout, the topology optimization process in the design domain is carried out by applying the BESO (Bidirectional Evolutionary Structural Optimization) method. In this approach, the low energy elements are eliminated from an initial mesh, and a new geometry is constructed. This new geometry consists of a set of elements with a higher elastic energy. This results in a new division of material providing different zones, some subjected to higher stress and others containing less elastic energy. Moreover, the elements of the final mesh are re-arranged and modified, considering the distribution of tension. This new arrangement is constructed by aligning and rotating the original mesh elements coherently to the principal directions. In the Shape Optimization stage, the resulting TO (Topology Optimization) geometry is refined. A process of replacing the tabular mesh is performed by rearranging the remaining elements. The vertices of the mesh are set as control polygon vertices and used as reference to define the NURBS (Non-Uniform Rational B-Spline) curves. This provides a parametric representation of the boundaries, outlining the high elastic energy zones. The final stage is the optimization of the continuous and analytically defined NURBS curve outlining the solid material domain. The Shape Optimization is carried out applying a gradient-based optimization method.

Commentary by Dr. Valentin Fuster
2018;():V013T05A043. doi:10.1115/IMECE2018-87769.

Even though the power transformers are electrical machines, their design includes several important steps with strong emphasis on mechanical engineering topics, such as the design of welded metallic structures. Indeed, the tank and its cover are typically manufactured from steel sheets or plates to which a group of stiffeners are added, with the objective of reducing the bending stress, transverse displacements and/or buckling.

The current communication presents and discusses several incremental innovations in the structural design and simulation of tanks for Core type power transformers, including: (i) optimization of the stiffeners design and welding bead volume reduction; (ii) optimization of panels curvature; (iii) simulation of the transformer tank loaded by both hydrostatic pressure and vacuum conditions; and (iv) inclusion of non-linear behavior to more accurately simulate representative structures.

Achieved numerical results are compared with obtained experimental data, to evaluate the design procedures and the potential of virtual testing of new solutions.

Commentary by Dr. Valentin Fuster
2018;():V013T05A044. doi:10.1115/IMECE2018-87926.

Spring operated pressure relief valves (SOPRVs) are essential components of technical systems. As parts of safety systems, they protect people and the environment from technological hazards. Their ability to open at a predefined pressure is considered the most important feature. The reliability of this function depends on numerous operational and design factors.

In this paper, we examine the effects of design measures on the mechanical loads in seat seals of SOPRVs. In particular, we evaluate the applicability of the principle of non-uniform system stiffness in order to systematically control the mechanical loads in seat seals for an exemplary case of a flat faced soft seated SOPRV. We systematically vary design parameters and accurately estimate the contact stresses as well as the set pressure by performing non-linear finite element analyses. We focus on the quasi-static case of a closed seal, since dynamic effects of the opening and closing processes are not within the scope of this work. In our contribution, we show that the application of these design measures can significantly influence both the initial contact stresses and the set pressure at a constant spring force. In particular, the effects of the taper angle are analyzed and discussed.

Commentary by Dr. Valentin Fuster
2018;():V013T05A045. doi:10.1115/IMECE2018-88180.

While the nonuniformity of the diameter of a shaft can be optimized to reduce damaging stress concentrations at the ends of the contact region that are typically found in interference fits between uniform diameter shafts and hubs, the resulting shape changes may adversely affect the joint strength. A more robust design may be achieved if the surface profile is optimized under both interference fit and functional loads. A novel gradientless structural shape optimization method is applied in this work with a unique multiobjective formulation that includes the contact interactions and their effects on the shaft. The method incorporates surface-averaged based optimization goals, which consider both local and global variations, so that the optimization of the entire contacting region can be readily achieved. The formulation has no system-dependent parameters, weighting factors, or stopping criterion, allowing for its broad application to design and compare systems of varying geometries, loads, and meshes. The method was used to attain design goals specific to contacting interfaces subjected to interference, axial, and torsional loads, achieving a 50% improvement in the stress state uniformity over the entire contract region in all cases. Through the presented method, the relative influence of each optimization goal on the resulting shape is demonstrated.

Commentary by Dr. Valentin Fuster

Design, Reliability, Safety, and Risk: Reliability and Risk in Energy Systems

2018;():V013T05A046. doi:10.1115/IMECE2018-87417.

Fault detection and diagnosis schemes based on data-driven statistical modelling are highly dependent on an accurate and exhaustive feature extraction procedure to deliver a superior performance as a monitoring strategy. Otherwise conducted, a deficient feature extraction procedure leads to a monitoring structure widely deviated from normal operating conditions. If an operating state is not identified as it, an increment in false alarm rate would be evidenced whenever the process shifts towards that condition and the monitoring scheme triggers the abnormal condition warning. On the other hand, if two similar operating conditions could not be individualized i.e. to be identified as a single operating state, a lack of sensitivity for minor — yet typical — deviations would render a monitoring strategy with prominent misdetection rates.

Although Multimode Operational Mapping requires the proper identification of a finite set of normal process states, it is a challenging task especially for large-scale systems. Its complexity derives from a broad universe of monitoring variables, highly interactuating process units integrated over very dynamic network systems, among others. This is the case of natural gas transmission infrastructure, as it deals with variable upstream production rates, diverse consumption trends from customers, internal processes constrains, merged in a stringent operating scheme.

This paper proposes a novel strategy to address the identification and feature extraction of normal conditions on multimode operation systems. The proposed framework uses a segmentation approach based on operator’s knowledge, the Takagi-Sugeno-Kang fuzzy engine and k-means algorithm to characterize the normal operation states of the system. The results show an improvement in the performance of Principal Component Analysis during abnormal conditions detection, in addition an increase on the sensitivity of Hotelling and Q statistics.

Commentary by Dr. Valentin Fuster
2018;():V013T05A047. doi:10.1115/IMECE2018-87677.

The U.S. Nuclear Regulatory Commission (NRC) promulgated Part 50.69 to Title 10 of the Code of Federal Regulations (CFR), “Risk-informed categorization and treatment of structures, systems and components for nuclear power reactors,” in November 2004 (hereafter referred to as 10 CFR 50.69). The rule provides a voluntary alternative to compliance with many regulations which require “special treatment,” or regulatory requirements which go beyond industrial controls, including: specific inspection, testing, qualification, and reporting requirements. The voluntary alternative includes a process for categorization of structures, systems, and components (SSCs) as having either low safety significance (LSS) or high safety significance (HSS). The categorization process can result in increased requirements for HSS SSCs which were previously treated as non-safety-related, and reduced requirements for LSS SSCs which were previously treated as safety-related.

The categorization process includes plant-specific risk analyses which are used in combination with an integrated decision-making panel (IDP) to determine whether the SSC has a low or high safety significance. Seismic probabilistic risk assessment (SPRA) is one of the risk analyses options to account for the seismic risk contribution. Because the 10 CFR 50.69 rule has currently not been implemented widely, the significance of various SPRA assumptions and sources of uncertainty to the categorization process has had limited evaluation for a broad spectrum of U.S. nuclear power plants.

This paper will assess the importance of certain aspects of the seismic risk contribution to the categorization process. NRC Standardized Plant Analysis Risk (SPAR) models will be used to perform sensitivity studies to quantify the impact of various assumptions and sources of uncertainty on the outcome of the categorization process.

Commentary by Dr. Valentin Fuster
2018;():V013T05A048. doi:10.1115/IMECE2018-87883.

Gas turbines are the most important components in thermal power plants, and these components such as turbine has been studied carefully. Gas turbine components operate predominantly under elevated temperature and high stress, and consequently gradual deformation becomes temporally inevitable. In turbine blades, creep is common failure mechanism, and it is an important factor for design assessment. The gas turbine blade is a component operating at high elevated temperatures, requiring a cooling systems to reduce the temperature. Common power enhancement approach is to spray water into compressor, and it is how humidity becomes an important factor in creep failure mechanism. The humidity variability results in temperature level change during the turbine operation, potentially affecting the blades creep life. In this paper, first different creep life prediction models were classified, and then a new model is proposed for creep life considering humidity based on Arrhenius equation. In our study, failure criterion is rupture. As a case study, the creep life of Nimonic-90 alloy turbine blade was predicted using proposed method and compared with FEA results which collected by literature surveys. Proposed model is capable of predicting creep life with only knowing dry temperature (WAR = 0), and there is no need to measure blade temperature variation during operation. The influence of humidity (%WAR) were studied on turbine blades creep life, and results show that creep life of turbine blade increase with increasing humidity percentage.

Commentary by Dr. Valentin Fuster
2018;():V013T05A049. doi:10.1115/IMECE2018-88508.

Rigid wet cooling media is a key component of direct and indirect evaporative cooling systems. Evaporation is the process of a substance in a liquid state changing to a gaseous state. When water evaporates only water molecules get evaporated and the other chemicals in the water are left behind on the surface as residue. Many studies have been conducted on how the change in air flow velocity, media depth, porosity and water distribution affect performance of the cooling system. The operational efficiency of the cooling media varies over its life cycle and depends primarily on temperature and speed of inlet air, water distribution system, type of pad and dimension of the pad.

Although evaporative cooling when implemented with air-side economization enables efficiency gains, a trade-off between the system maintenance and its operational efficiency exists. In this study, the primary objective is to determine how calcium scale affects the overall performance of the cooling pad and the water system. Areas of the pad that are not wetted effectively allow air to pass through without being cooled and the edges between wetted and dry surface establish sites for scale formation. An Accelerated Degradation Testing (ADT) by rapid wetting and drying on the media pads at elevated levels of calcium is designed and conducted on the cellulose wet cooling media pad. This research focuses on monitoring the degradation that occurs over its usage and establish a key maintenance parameter for water used in media pad.

As a novel study, preliminary tests were mandatory because there were no established standards for media pad degradation testing. Sump water conductivity is identified as the key maintenance parameter for monitoring sump replenishing and draining cycles which will result in reduced water usage. The average water conductivity in the sump during wetting cycles increases monotonically when ADT was performed on a new media pad. An empirical relationship between sump water conductivity and number of wetting cycles is proposed. This information will be very helpful for the manufacturers to guide their customers for maintenance of the media pad and sump water drain cycles.

Topics: Cooling , Testing
Commentary by Dr. Valentin Fuster

Design, Reliability, Safety, and Risk: Reliability Methods

2018;():V013T05A050. doi:10.1115/IMECE2018-86130.

In reliability-based mechanical design, reliability replaces the traditional factor of safety as the measurement index of the safety of mechanical components. More than 90% of metal components under cyclic fatigue loadings in industries fail because of fatigue. The P-S-N curve fatigue theory (Probability - Stress level - Number of cycles) is one of the current important fatigue theories. It is very important to know how to determine the reliability of components under different loading-induced cyclic stresses for reliability-based mechanical design. The Monte Carlo method is a powerful numerical simulation in almost every field such as optimization, numerical integration, and generating draws from a probability distribution. Literature reviews show the Monte Carlo method is successfully implemented to estimate the reliability of components under single loading-induced cyclic stress. However, there is little literature about implementing the Monte Carlo method to estimate the reliability of components under multiple loading-induced cyclic stress by using the P-S-N curve fatigue theory. The purpose of this paper is to develop a new Monte Carlo computational algorithm to calculate the reliability of components under several cyclic loadings using the P-S-N curve fatigue theory. Two key concepts in the widely-accepted Miner rule in fatigue theory are that fatigue damage is linear cumulative and the fatigue damage because of different cyclic stress is independent. Based on these two key concepts, this paper has successfully developed a new Monte Carlo computational algorithm to calculate the reliability of components under multiple loading-induced cyclic stresses using the P-S-N curve fatigue theory. The results obtained by the developed computational algorithm is validated by results obtained from two published methods. The results by the developed computational algorithm is again validated by the K-D probabilistic model. Based on validation studies, the relative differences in the results between the proposed method and the published methods are in the range of 0.66% to 2.98%. Therefore, the developed Monte Carlo computational algorithm is validated and can provide an acceptable estimation of the reliability of components under several cyclic fatigue loadings using the P-S-N curve fatigue theory.

Commentary by Dr. Valentin Fuster
2018;():V013T05A051. doi:10.1115/IMECE2018-87015.

In this paper, a new model is proposed for system degradation evaluation under sliding wear failure mechanism. This model estimates the material loss by progression of sliding distance. This model is generated by considering physical and geometrical aspects of system under wear mechanism. Several sets of experimental data are used for validation of the presented model. These experimental data are related to pin-on-disc test of Tungsten Carbide pins. These sets of data include initially conformal and non-conformal contacts. One set of data of pin-on-disc test by ASTM-G99 standard is used for additional validation of the model and for investigation of normal load effects on the parameters of presented model. Finally, uncertainty analysis is done by Monte-Carlo simulation to determine the variations of the predicted wear caused material loss.

Topics: Wear , Uncertainty
Commentary by Dr. Valentin Fuster
2018;():V013T05A052. doi:10.1115/IMECE2018-87040.

For long-term operation, blades start to show some defects with increasing operating hours, such as fouling, erosion, corrosion, damage and tip clearance. As the basic unit components of gas turbines, the health conditions of blades directly affect the energy conversation efficiency and service life of the whole equipment. The process from first installation to scrap is blades’ whole operation life cycle. It is an effective way to establish the whole operation life cycle model of blades for real-time monitoring, troubleshooting and prevention, so as to improve the management of equipment. The current research on the whole operation life cycle model is mostly limited to a single subject, such as thermal effects or stress effects. It lacks a profound analysis of this issue from the multi-disciplinary perspective. Meanwhile, the deterioration of blades influence on geometry variation of the blade surface is not taken into consideration in detail. Therefore, the current blade life model is not accurate enough to represent the actual situation. In this paper, the typical gas path deterioration is characterized by blade profile parameters, including the increment of the blade leading edge thickness, the increment of the blade trailing edge, and the change of the blade surface roughness in the whole operation life cycle model of blades. The influencing factors of aerodynamics and strain are synthetically characterized through the study of their multi-disciplinary influence mechanism. And the relationship between the corresponding influencing factors and the variation of blade profile parameters is established. Thus, the numerical simulation model under multi-physics is built to reveal its distribution and trends of the flow field and stress in the gas path. The result shows that it can protect the blades, ensure safe and stable operation, and reduce the deterioration rate.

Commentary by Dr. Valentin Fuster
2018;():V013T05A053. doi:10.1115/IMECE2018-88139.

This paper proposes reliability-based optimal design of a micro-grid system under service disruptions due to natural disasters. The objective is to determine the minimum number of generators and their distributions in the micro-grid so that the system’s recoverability (or resilience) and operation efficiency can be guaranteed under random failure scenarios of the power transmission lines. Power flow analysis combing with the Monte Carlo simulation (MCS) are used for uncertainty propagation analysis to quantify the system’s recoverability distribution and the transmission efficiency distribution under random failure scenarios of the transmission lines. The optimal allocation of the generators is much more reliable compared to the deterministic solutions without considering various uncertainties in the system. The proposed work is demonstrated through a 12-bus power system.

Commentary by Dr. Valentin Fuster

Design, Reliability, Safety, and Risk: Safety in Transportation, Agriculture, and Off-Road Vehicles

2018;():V013T05A054. doi:10.1115/IMECE2018-86277.

This paper presents the design and implementation of a low-cost and reliable wireless motion control system for conventional electric wheelchairs. The presented work aims to enhance the mobility of handicapped and elderly wheelchair users by utilizing a mobile application to control the motion of their unattained wheelchairs. The designed system takes into consideration cost, weight, a range of operation, ease of use, and implementation. The conventional electric wheelchair is equipped with a motorized front wheel steering mechanism. In addition, it is equipped with a Wi-Fi module to support remote motion control via a specially designed Android mobile application called “Android Application For NavigAtioN”; AAFNAN for short. Experimental testing of the prototype showed successful remote motion control and ease of use.

Commentary by Dr. Valentin Fuster
2018;():V013T05A055. doi:10.1115/IMECE2018-86594.

Automobile Braking System is one of the most important sub systems of the vehicle. It is the primary safety system since the stopping of the vehicle is majorly dependent on this system. This system utilises the frictional force between the tire and the road to stop the vehicle. The braking force required by the vehicle is governed by two factors. One of them is the coefficient of friction between the tire and the road surface, the other one is the load on the vehicle. Thus, required braking force to halt the vehicle with the minimum possible stopping distance varies with the load in the vehicle. If the applied braking force is greater than the required brake force, wheel gets locked which results in increased stopping distance. In order to prevent the wheel lock at low load conditions, a variable braking force system is developed. In Motorcycles, the pillion load majorly contributes to the overall weight. Thus, the amount of braking force required to stop with minimum stopping distance also varies drastically with respect to pillion load condition. Hence, the amount of braking force developed between the road surface and the tire is varied in the variable braking force system. In this project, variable brake force system is achieved by varying the effective disc radius. The maximum braking force developed between the ground and the tire is controlled based on the pillion load on the motor cycle, if friction is present between the tire and the ground. Two calipers are mounted on the brake disc of which one is fixed at a constant distance (constant effective disc radius – 67mm) and the other is movable depending on the load on the motorcycle. The movable caliper slides upwards and downwards such that the effective disc radius is varied based on the pillion load. Using a load cell, the load of the vehicle is determined. A microcontroller is programmed to move the caliper with the help of a stepper motor based on the load on the motorcycle. This way, the effective disc radius is varied for various loads on the motorcycle.

Topics: Braking
Commentary by Dr. Valentin Fuster
2018;():V013T05A056. doi:10.1115/IMECE2018-86775.

Drum brakes have dominated the braking industry for many years due to their low cost and adequate operating performance. In this paper, the authors present the first example of studying the sensitivity analysis of a magnetorheological fluid (MRF) and a conventional frictional brake by using first order Tayler series expansion. Nondimensional analyses are carried out to generalize the analyses for every brake configuration. This paper seeks to step away from the complexity of the numerical models for these brakes. Taylor series expansion is used to examine the effects of perturbing dimensionless design parameters on the braking torque. In addition, Taguchi approach is applied for the brakes to study the contribution of the design parameters on the braking torque and to obtain the optimal design. It is shown in this paper that braking torque for magnetorheological fluid brake is dependent on seven dimensionless groups while the frictional brake is dependent upon only four dimensionless groups. Four groups of the MRF brake and two groups for the frictional brake dominate the physics of braking. The sensitivity analysis has identified the key parameters that must be adjusted in order to increase braking torque. Furthermore, Taguchi approach has showed the how the variations of input variables affect the variations of the output variable and stated the optimal levels of the design parameters that achieve the optimal design.

Commentary by Dr. Valentin Fuster
2018;():V013T05A057. doi:10.1115/IMECE2018-86863.

With the degradation of metrorail facilities and the increase in network size, it is urgently needed to perform vulnerability assessment to ensure the safe operation of the metro system. In this paper, a link-weighted network model is proposed by considering the physical interval length between neighboring metro stations as link weight factor. Firstly, the metro network was essentially mapped into a bipartite topological diagram that consists of nodes denoting metro stations and links representing metro routes including any tunnels or bridges. After analyzing the network for its complexity level, it was revealed that the metro network topology can be appropriately constructed by using the Space L method. On this basis, multiple characteristic indexes of the network were calculated to characterize network topology structural features. We then tested the state of Shanghai metro network under different failure scenarios by removing a fraction of nodes from the network. Quantitative vulnerability analyses were conducted according to the change in the topological structure of Shanghai metro network and the change in the corresponding global network efficiency due to disruptions. Finally, both the network efficiency of link-weighted and unweighted Shanghai metro network topology were calculated and compared. This study has identified the vulnerable metro stations, which could provide support for the reasonable resource allocation of maintenance work and the decision-making in emergency treatment after failure. In order to increase the adaptability to emergencies and improve the operational efficiency, it was proposed that during the planning, construction, and operation of the metro system, the management and protection of the vulnerable stations should be given increased attention.

Commentary by Dr. Valentin Fuster
2018;():V013T05A058. doi:10.1115/IMECE2018-87071.

A data acquisition system along with a sensor package was designed and installed on an existing mechanically-controlled cargo tractor to gather more data on their usage patterns. The data collected through the developed system include GPS route, vehicle speed and acceleration, engine state, transmission state, seat occupancy, fuel level, and video recording. The sensor package was designed and integrated in a way that does not interfere with the driver’s operation of the cargo tractor. Cellular network connectivity was employed to retrieve sensor data so as to minimize human effort and maintain typical usage patterns of the outfitted cargo tractors. Testing and validation results showed that the developed system can correctly and effectively record data necessary for further analysis and optimization. A fuel usage analysis was then completed using a chassis dynamometer based on the collected data. The collected data will significantly promote cargo tractor activity simulations in order to facilitate optimizing work flow at large industrial facilities and improving energy efficiency.

Commentary by Dr. Valentin Fuster
2018;():V013T05A059. doi:10.1115/IMECE2018-87230.

This work proposes a method to simulate wheel lock of a Heavy Commercial Road Vehicle (HCRV) using pneumatic brake circuit on a brake dynamometer. The proposed methodology lumps the effects of wheel slip and load transfer during straight-line braking into ‘equivalent inertia’ on the wheels. This inertia profile could then be imported on a dynamometer interface and realized using suitable inertia discs and an electric motor. Equivalent inertia was computed from test datasets obtained from a Hardware-in-Loop (HiL) experimental system consisting of an air brake system and IPG TruckMaker®, a vehicle dynamic simulation software. These datasets were obtained for various road, vehicle load and braking conditions. This framework would facilitate the evaluation of wheel slip regulation algorithms using a brake dynamometer by capturing necessary dynamics of HCRVs during braking. It is expected that such testing can be placed between HiL and on-road tests, and would provide greater confidence in Active Safety Systems (ASSs) before their deployment on vehicles.

Commentary by Dr. Valentin Fuster
2018;():V013T05A060. doi:10.1115/IMECE2018-87471.

Metro-Rail transit systems are large-scale networks in numerous modern urban areas that play prominent direct and supportive roles in providing efficient mobility for sustaining communities and local economies. Any event leading to failure of a metro-rail network could have serious societal consequences, such as dramatic effect on the safety and wellbeing of commuters in addition to direct and indirect costs from its diminished performance that lead to resilience loss. Potential performance losses might exhibit complexity and pose a challenge for measurement and prediction. Hence, measuring the resilience of such a network enables its efficient enhancement in a cost-effective manner. Enhancing resilience highly depends on identifying recovery strategies with special attention not only to restoring connectedness but also on reducing associated failure and recovery costs. An effective recovery strategy must demonstrate rapid optimal restoration of a disrupted system while minimizing the cost of the disruption. The objective of this paper is to identify effective recovery strategies to reduce the performance loss and to minimize the total cost of a network during and after a disruptive event, using Washington D.C. Metro with its 91 stations and 140 links as a case study. Method of measuring performance loss in this paper, illustrates that the best recovery sequence typically reflects the order of components ranked based on their degree of vulnerability in the network. Also, the proposed cost model provides a basis to decision makers to identify an optimal recovery strategy according to both paramount recovery sequence and minimum cost consideration.

Topics: Failure
Commentary by Dr. Valentin Fuster
2018;():V013T05A061. doi:10.1115/IMECE2018-87825.

This research proposes an analytical vehicle KANO model, called V-KANO Model, which will be able to improve vehicle technical characteristics and performance target setting more precisely at the early stage during vehicle design and development process. A vehicle needs to be designed to satisfy the wants of the customers, the key is to truthfully and accurately interpret customers’ wants into engineering specifications; in other words, to translate customers’ voices into vehicle’s technical characteristics and design targets correctly. In this research, the KANO model originally introduced by Japanese quality expert Dr. Noriaki Kano is improved and modified for vehicle’s technical characteristics and performance design targets setting. The conventional KANO model was only a qualitative-based general model lack of precision and detailed information, the new innovatively developed V-KANO Model modifies and improves it into a quantitative-based mathematical model which correlates the customers’ satisfaction degree of vehicle performance with the professional trained engineers’ evaluation index closely to successfully derive an analytical vehicle KANO model, which can be adopted to guide a new vehicle system technical characteristics and performance design targets setting and development at the early stages of vehicle design process.

Commentary by Dr. Valentin Fuster

Design, Reliability, Safety, and Risk: Safety, Risk, and Reliability of Emerging Technologies

2018;():V013T05A062. doi:10.1115/IMECE2018-86769.

The use of automobile lightweight is an effective measure to reduce energy consumption and vehicle emissions. The utilization of high-performance composite materials is an important way to achieve lightweight vehicles technically. The advantages of using thermoplastic composite wheels are: easy to form, high manufacturing efficiency, low cost and easy to recycle. This leads to broader application prospects. Taking composite anisotropy into consideration, the mechanical performance of a wheel made of long glass fiber reinforced thermoplastic (LGFT), is analysed using the finite element method (FEM). This is done by placing the wheel under a bending fatigue load simulation. According to the simulation results, the sample database is established by orthogonal experimental method on the Isight platform, and the approximate model is established by the Response Surface Methodology (RSM). Based on this model, uncertainty optimization analysis is then conducted on the wheel’s design using Sigma Principle whereby the optimization target is the mass minimization. The maximum deformation of the wheel and the stress on both sides of the spoke will serve as constraint conditions and the key dimension parameters of the wheel model will be taken as the design variables. The uncertainty optimization is based on the Sigma criterion, taking into consideration the wheel’s geometry and property-fluctuation materials. The feasibility of design schemes is then verified after comparison analysis between the optimization results and the simulation results obtained. The result shows that compared with deterministic optimization, though the weight of the wheel has slightly increased, the uncertainty optimization based on the Sigma criterion is much more robust and the reliabilities of the three constraints are all above 6 Sigma. The resulting optimized LGFT wheel weighs 5.28kg, which has a 5.5% more loss in weight than the initial target and is also 25.6% lighter than the counterpart wheel which is made of aluminum alloy. The desired design results is now achieved with this lightweight effect.

Commentary by Dr. Valentin Fuster
2018;():V013T05A063. doi:10.1115/IMECE2018-87431.

Experimental toxicology studies for the purposes of setting occupational exposure limits for aerosols have drawbacks including excessive time and cost which could be overcome or limited by the development of computational approaches. A quantitative, analytical relationship between the characteristics of emerging nanomaterials and related toxicity is desired to better assist in the subsequent mitigation of toxicity by design. Quantitative structure activity relationships (QSAR’s) and meta-analyses are popular methods used to develop predictive toxicity models. A meta-analysis for investigation of the dose-response and recovery relationship in a variety of engineered nanoparticles was performed using a clustering-based approach. The primary objective of the clustering is to categorize groups of similarly behaving nanoparticles leading to the identification of any physicochemical differences between the various clusters and evaluate their contributions to toxicity. The studies are grouped together based on their similarity of their dose-response and recovery relationship, the algorithm utilizes hierarchical clustering to classify the different nanoparticles. The algorithm uses the Akaike information criterion (AIC) as the performance metric to ensure there is no overfitting in the clusters. The results from the clustering analysis of 2 types of engineered nanoparticles namely Carbon nanotubes (CNTs) and Metal oxide nanoparticles (MONPs) for 5 response variables revealed that there are at least 4 or more toxicologically distinct groups present among the nanoparticles on the basis of similarity of dose-response. Analysis of the attributes of the clusters reveals that they also differ on the basis of their length, diameter and impurity content. The analysis was further extended to derive no-observed-adverse-effect-levels (NOAEL’s) for the clusters. The NOAELs for the “Long and Thin” variety of CNTs were found to be the lowest, indicating that those CNTs showed the earliest signs of adverse effects.

Topics: Nanoparticles
Commentary by Dr. Valentin Fuster
2018;():V013T05A064. doi:10.1115/IMECE2018-88004.

Pipe bends are critical components in piping systems where their failure modes are quite different from straight pipes. The objective of the present work is to investigate the limit loads of pipe bends with actual As-fabricated shape obtained from pipe bending process as compared to bends with Ideal and Assumed imperfect shapes. The present work is conducted by using nonlinear finite element analysis and is performed in two steps. The first step is achieved by simulating rotary pipe bending process with ball mandrel to obtain the actual as-fabricated shape of the 90° pipe bend. The process simulation was verified against published experimental data. In the second step, the pipe bend is subjected to different combinations of simultaneous loads consisting of internal pressure and In-plane closing bending moment. Results are provided for limit load curves for pipe bends with as-fabricated geometries and bends with ideal shape and assumed geometrical imperfections.

Topics: Pressure , Stress , Pipe bends
Commentary by Dr. Valentin Fuster

Design, Reliability, Safety, and Risk: Social Context Aware Design

2018;():V013T05A065. doi:10.1115/IMECE2018-87163.

Environmental simulations through rendering has an important role to play in the design process of and communication regarding the built environment. Technological advances allow for widely used printed renders with 360° panoramic representations to be displayed through head-mounted devices (HMD). However, the adoption of this technology should be done with caution, due to the possible effects of the user’s context relative to his or her expertise and geographic–cultural level. This study compared printed and 360° HMD-render setup capacities for experts and nonexperts in Architecture, from different geographic–cultural contexts of Mexico and Spain. To tackle this, a broad spectrum of 15 components addressing aspects of utility, spatial representation, and the emotional and general capabilities of environmental simulations were assessed using bipolar scales by a total of 120 participants. Analyses showed differences in all aspects for all contexts of the study. The greatest differences were general, with non-experts of an indistinct geographic–cultural context showing the least perception of the capabilities. This indicates a strong conditioning, generated by experience acquired in different geographical–cultural contexts, supporting the idea of incorporating context–aware reasoning into the representation of novel rendering. Hence, our results will have interest for both professionals and instructors.

Topics: Rendering
Commentary by Dr. Valentin Fuster
2018;():V013T05A066. doi:10.1115/IMECE2018-87865.

Quantitative approaches to estimating user demand provide a powerful tool for engineering designers. We hypothesized that estimating binomial distribution parameters n (user population size) and p (user population product affinity) from historical user data can predict demand in new situations. This approach applied to a major Bike Sharing System (BSS) expansion. BSS Operators must make key decisions when adding additional docking stations. Binomial Parameter estimation approaches are briefly discussed, followed by evidence that BSSs supply an amiable case for parameter estimation. Parameter plots reveal a continuous surface over the BSS area. These surfaces allow prediction of overall ridership levels at new station locations distinctly and more accurately from approaches currently utilized. Utilizing spearman’s Rho as a comparison benchmark, our approach yields a stronger correlation between our prediction and the observed new station utilization (rho = .830, stations = 46, p < .01) than the order implemented by the BSS operator (rho = .596, stations = 46, p < .01). Finally, this approach is mathematically straightforward, indicating potential as a mainstream BSS tool for BSS operators planning future station expansions. The results validate our approach of using current user data to determine target population characteristics, informing decisions about new design situations.

Topics: Design , Bicycles
Commentary by Dr. Valentin Fuster
2018;():V013T05A067. doi:10.1115/IMECE2018-87900.

Current trends in product development process highlight the increasing adoption of digital data and virtual processes. Nowadays, a huge amount of product data are collected without a clear management strategy and, oftentimes, they dont even cover the whole product development process. A global and integrated planning about information needed to sustain product design process is not a trivial task and, usually, companies underrates this issue. From the perspective of virtualization of processes, and then their automation, the lack of structured knowledge is certainly awful. This paper aims at making a critical analysis how product data evolve throughout the product design or configuration process and how they impact the product development activities. Efficient digital product twin allows companies to virtualize processes and leverage their automation, but it is important to understand how the knowledge management should be carried out. Three case studies, directly experienced by the authors, have been investigated analyzing digital data and virtual tools that allow companies to automate the design process, each one bringing a peculiar perspective of the problem.

Topics: Design
Commentary by Dr. Valentin Fuster
2018;():V013T05A068. doi:10.1115/IMECE2018-88441.

The interaction between technology and people is characterized by sociotechnical models. In the context of design, these types of systems are analyzed to increase productivity. The level of productivity is expected to increase as the technology evolves. Still, a lack of focus on adaptive design hinders the success of sociotechnical systems. The problem is evident in the relationship between microgrid technology and the residents of developing communities. An analysis of this type of sociotechnical system is analyzed in this paper. Rural villages in the developing world often lack access to the power grid. However, microgrids can provide electrical power in these locations. Power can be harnessed from renewable resources such as wind, solar, geothermal, and hydropower. Large batteries are used to store energy and buffer the electrical supply with the demand. The system powers security lighting, water pumps, and purification systems. Microgrids also power small machines that sustain agriculture in developing communities. The access to energy uplifts the developing community socially and economically. Still, as the community evolves, energy demand increases and the microgrid is unable to provide sufficient energy. A challenge in microgrid design involves the scalability of the system. Currently, there is no method for adapting the microgrid system to the increases in demand that occur over time. Accordingly, a mathematical framework is needed to support design decisions that could otherwise support adaptability. A demand model to predict the energy use for a composite rural village is presented. The predicted demand requirements are configured using a design optimization simulation model. These configurations are studied, and adaptive design techniques are devised through the process. The outcome of this study identifies a basic design methodology for microgrid design that is cognizant of scalability. Moreover, it identifies key attributes and relationships for the mathematical framework that supports the overarching goal of adaptable design.

Topics: Design , Microgrids
Commentary by Dr. Valentin Fuster

Design, Reliability, Safety, and Risk: Testing for Product Reliability and Safety

2018;():V013T05A069. doi:10.1115/IMECE2018-86340.

Diamond sawblade is an efficient tool to building renovation or demolition. Concrete used in construction is a typical composite material with random distribution, which is difficult to accurately identify and predict even under the same processing conditions, and tool life of diamond sawblade is difficult to control.

In this paper, by cutting out single component of the hard and soft aggregate separately from concrete, the single component and concrete experiments were carried out to understand the sawing characteristics of different components. The wavelet decomposition was used to analyze the characteristic of each frequency band of the different components sawing force and vibration signals, and the sensitive frequency bands after correlation coefficient and energy ratio variation of each wavelet layer were extracted to judge the bluntness status of sawblade. By taking the Root-Mean-Square (RMS) value, the energy ratio of d2 and d5 wavelet layers and the standard deviation of sawing force and vibration signal as the characteristic values of the sawblade, a neural network optimized by bat algorithm was established to analyze the concrete processing signals and predict the working state of the sawblade. Evidence theory was adopted to combine the prediction results of sawing force and vibration samples to increase the overall prediction accuracy and reliability. The test sample showed that this method can correct inconsistent individual sensor predictions while being as close to the actual status value as possible. It provides an effective tool life prediction way of the diamond sawblade and a theoretical method for the monitoring of non-metallic materials with inhomogeneous components.

Topics: Concretes , Sawing , Diamonds
Commentary by Dr. Valentin Fuster
2018;():V013T05A070. doi:10.1115/IMECE2018-87685.

The emergence of a global economy has proposed new challenges for the product design engineer and provided new risks for the consumer. While the design and manufacturing processes have changed, the objective of providing a consumer product that is safe for public use still remains. This task becomes challenging for the product design engineer since the ability to oversee all aspects of the design, manufacture, and use is very limited and yet the mentality of “if you build it, you will be sued” is ever present. This paper considers three very different consumer products and all suffered a failure which resulted in harm done to the user. The first product is a multipurpose tool that, even though abuse was observed, contained a concealed danger as a result of poor design and/or manufacture that resulted in the injury. Second is a hanging chair that fell from the supporting fastener causing injury. Analysis and testing were unable to repeat the failure, thus severe abuse by the user proved to be the causal factor. Finally, a wine bottle opener caused injury as the user attempted to remove a part of the device from the packaging. In this case, the product itself was adequately designed to prevent injury for its intended use, but the packaging containing the product suffered from a faulty design. These cases exhibit different scenarios in which a consumer product caused injury to an end user and shows the varying entities that can bear the burden of negligence.

Commentary by Dr. Valentin Fuster
2018;():V013T05A071. doi:10.1115/IMECE2018-87857.

In oil and gas industry, machineries and mechanical components are designed with high reliability to meet the demand of the oil field. Rotating machinery is a widely used equipment and any failure of critical components within the machinery could lead to delays and large expenses. Failure of rotary seal is one of the foremost causes of breakdown in rotary machinery and such a failure can affect the other process operations in oil and gas plants. Assessing seal degradation and severity estimation are very important for maintenance decision-making. Extracting meaningful and sensitive features that can show seal degradation from raw signals is a challenging task of degradation assessment. However, no extensive works are dedicated in this area of seals. In this paper, we perform accelerated aging and testing to capture the behavior of seals through their cycle of operation and demonstrated a statistical time domain feature based approach for extracting the sensitive features that can show seal degradation. Out of eleven statistical features extracted, seven extracted features such as mean, RMS, maximum, squared mean rooted absolute amplitude, impulse factor, crest factor, margin factor are found to be significant factors which have a potential to differentiate severity levels in seals. The findings from our work show that our approach has a potential to assess the severity in seals. As a possible extension, extracted features can be used to build a classification model to classify severity in seals which could be of great interest to the users and manufacturers of rotary seals.

Commentary by Dr. Valentin Fuster
2018;():V013T05A072. doi:10.1115/IMECE2018-87952.

In 2008, the Mine Safety and Health Administration (MSHA) published a final rule on Refuge Alternatives (RAs) for Underground Coal Mines. The rule states that RAs shall be capable of sustaining trapped miners for 96 hours and that RAs can also be used to facilitate escape by sustaining trapped miners until they receive communications regarding escape options. As of 2014, there were three types of coal mine RAs manufactured by 10 different companies and at least 13 different communications systems approved for use underground. However, there is no specific guidance on how to determine if such a wide variety of systems will facilitate successful communication in an emergency. Examples in this study detail one representative example of each of the three types of RAs. Each example RA was tested underground in an experimental coal mine by researchers from the National Institute for Occupational Safety and Health (NIOSH). The purpose of the testing was to determine a representative signal attenuation caused by a specific RA’s wall material and entrance door. For each RA type, the signal loss was investigated using comparative measurements. Test results showed an average difference of 3 decibel milliwatts (dBm) for a tent type RA, 15 dBm for a metal RA and 14 dBm for a Built-in-Place RA for a frequency range of 150 to 3000 MHz. These results can be used in calculating the available link budget for a communication system to determine if a signal will reach the inside of the RA.

Commentary by Dr. Valentin Fuster

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