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Design Optimization of Networks of Cooling Passages

[+] Author Affiliations
Nenad Jelisavcic, Ramon J. Moral, Debasis Sahoo, George S. Dulikravich, Maickel Gonzalez

Florida International University

Thomas J. Martin

Pratt & Whitney Engine Company

Paper No. IMECE2005-79175, pp. 399-410; 12 pages
doi:10.1115/IMECE2005-79175
From:
  • ASME 2005 International Mechanical Engineering Congress and Exposition
  • Heat Transfer, Part B
  • Orlando, Florida, USA, November 5 – 11, 2005
  • Conference Sponsors: Heat Transfer Division
  • ISBN: 0-7918-4222-3 | eISBN: 0-7918-3769-6
  • Copyright © 2005 by ASME

abstract

A one-dimensional thermo-fluid flow network analysis program COOLNET was developed to predict coolant flow rates, total coolant pressures, bulk coolant total temperatures, and internal heat transfer coefficient distributions, inside internally cooled objects. The coolant passages were allowed to be an arbitrary network of one-dimensional fluid elements or tubes. Geometric parameters of each passage were optimized using a hybrid multi-objective optimization algorithm. For the chosen Pratt & Whitney gas turbine the cross-sectional areas, hydraulic diameters, ribs’ heights and angles in each passage were optimized in order to minimize coolant flow rate, coolant total pressure loss, and total heat removed by coolant from the system. Validation of the hybrid multi-objective optimizer was performed with various test functions. Also, validation of the COOLNET was done with existing Pratt & Whitney gas turbine blade. Program OBJ was written to connect hybrid multi-objective optimizer and COOLNET. Optimization process was visualized using Tecplot (commercial software). Program PLOT was written to write input file for Tecplot, purpose of PLOT was to visualize initial and optimized results. Analysis for the best optimal result is given. The resulting COOLNET analysis provided coolant flow rates, total and static pressures and temperatures, and the heat transfer coefficient of each fluid element. The COOLNET analysis algorithm would typically converge in 50 iterations requiring about 5 seconds of CPU time on a 3.0 GHz processor. Results demonstrated that in case of an internally cooled gas turbine blade an improvement in overall performance is possible. A typical design optimization required between 500-1,000 iterations with a population of 30 designs. Thus, total number of configurations analyzed was approximately 15,000-30,000.

Copyright © 2005 by ASME

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