Full Content is available to subscribers

Subscribe/Learn More  >

Combination of Elementary Processes to Form a General Energy System Configuration

[+] Author Affiliations
A. Toffolo

Luleå University of Technology, Luleå, Sweden

S. Rech, A. Lazzaretto

University of Padova, Padova, Italy

Paper No. IMECE2017-71653, pp. V006T08A015; 14 pages
  • ASME 2017 International Mechanical Engineering Congress and Exposition
  • Volume 6: Energy
  • Tampa, Florida, USA, November 3–9, 2017
  • Conference Sponsors: ASME
  • ISBN: 978-0-7918-5841-7
  • Copyright © 2017 by ASME


The fundamental challenge in the synthesis/design optimization of energy conversion systems is the definition of the system configuration and design parameters. The traditional way to operate in system engineering practice is to follow the previous experience, starting from design solutions that already exist. A more advanced strategy consists in the preliminary identification of a superstructure that should include all the possible solutions to the synthesis/design optimization problem, and in the selection of the system configuration starting from this superstructure through a design parameter optimization. This top-down approach cannot guarantee that all possible configurations could be predicted in advance and that all the configurations derived from the superstructure are really feasible.

To solve the general problem of the synthesis/design of complex energy systems a new bottom-up methodology is proposed, based on the original idea that the fundamental nucleus in the construction of any energy system configuration is the elementary thermodynamic cycle (compression, heat transfer with the hot source, expansion, heat transfer with the cold source). So, any configuration can be built by generating, according to a rigorous set of rules, all the combinations of the elementary thermodynamic cycles operated by different working fluids that can be identified within the system, and selecting the best resulting configuration through an optimization procedure.

In this paper a deep analysis of the major features of the methodology is presented to show, through different examples of applications, how an artificial intelligence is able to generate system configurations of various complexity using preset logical rules without any “ad hoc” expertise.

Copyright © 2017 by ASME



Interactive Graphics


Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In