TY - JOUR
T1 - Topology optimization of an airfoil fin microchannel heat exchanger using artificial intelligence
AU - Guillen, Donna Post
AU - Abboud, Alexander W.
AU - Bennink, James
N1 - Funding Information:
This work was supported by the U.S. Department of Energy, Office of Nuclear Energy under the Advanced Reactor Technology portfolio’s Microreactor Program and authored by Battelle Energy Alliance, LLC, under Contract No. DE-AC07-05-ID14517 with the U.S. Department of Energy, Office of Nuclear Energy. This work was supported in part by the U.S. Department of Energy, Office of Science, Office of Workforce Development for Teachers and Scientists (WDTS) under the Science Undergraduate Laboratory Internships Program (SULI). Mahmoud Ramadan and Jack Holiman contributed to the initial computational fluid dynamic studies. Ting-Leung Sham and Xiaodong Sun provided helpful insight regarding the thermal stress analysis and the application of the ASME Code. This research made use Idaho National Laboratory computing resources which are supported by the Office of Nuclear Energy of the U.S. Department of Energy and the Nuclear Science User Facilities under Contract No. DE-AC07-05ID14517. The content represents ongoing efforts by the Microreactor Program to enable accelerated development and demonstration of microreactor technology.
Publisher Copyright:
© 2022 Elsevier B.V.
PY - 2022/5
Y1 - 2022/5
N2 - High-performance microchannel heat exchangers are needed to supply heat for power conversion for nuclear microreactors. An airfoil fin microchannel design, constructed of Alloy 617 with helium as the working fluid, is analyzed and optimized using a design of experiments with artificial intelligence techniques. The use of airfoil fins offers the potential to reduce pressure drop across the heat exchanger, as compared to other types of channel configurations. A framework for topology optimization of airfoil fin printed circuit heat exchangers (PCHEs) has been developed that can be readily extended to different fin sizes and shapes, as well as different inlet and operating conditions, materials of construction, and working fluids. An optimization procedure is developed that employs computational fluid dynamics for a set of design points identified using Latin hypercube sampling. Computational fluid dynamics is used to analyze a simplified two-channel configuration where five design parameters are varied – inlet angle, fin scale, extent of staggering, transverse and longitudinal pitches. Two methods (a 5D polynomial and a regression neural network) are compared for generating surrogate models and the resulting response surface approximation is input to a genetic algorithm that is used to identify a set of optimal parameters. The optimal geometries are found across six channel Reynolds numbers ranging from 1000 to 5000, since inlet conditions affect flow through the heat exchanger. A set of optimal designs that maximizes heat transfer and minimizes pressure drop is identified, and a thermal stress analysis is performed on the optimal design. Correlations for the Nusselt number and Darcy friction factor are developed that can be useful for thermal hydraulic analyses using system codes. Thermal stresses are analyzed and a brief discussion of the status of code cases of PCHEs for nuclear applications is given. Testing and thermomechanical modeling is needed to facilitate future code compliance of PCHEs for high pressure and high temperature applications.
AB - High-performance microchannel heat exchangers are needed to supply heat for power conversion for nuclear microreactors. An airfoil fin microchannel design, constructed of Alloy 617 with helium as the working fluid, is analyzed and optimized using a design of experiments with artificial intelligence techniques. The use of airfoil fins offers the potential to reduce pressure drop across the heat exchanger, as compared to other types of channel configurations. A framework for topology optimization of airfoil fin printed circuit heat exchangers (PCHEs) has been developed that can be readily extended to different fin sizes and shapes, as well as different inlet and operating conditions, materials of construction, and working fluids. An optimization procedure is developed that employs computational fluid dynamics for a set of design points identified using Latin hypercube sampling. Computational fluid dynamics is used to analyze a simplified two-channel configuration where five design parameters are varied – inlet angle, fin scale, extent of staggering, transverse and longitudinal pitches. Two methods (a 5D polynomial and a regression neural network) are compared for generating surrogate models and the resulting response surface approximation is input to a genetic algorithm that is used to identify a set of optimal parameters. The optimal geometries are found across six channel Reynolds numbers ranging from 1000 to 5000, since inlet conditions affect flow through the heat exchanger. A set of optimal designs that maximizes heat transfer and minimizes pressure drop is identified, and a thermal stress analysis is performed on the optimal design. Correlations for the Nusselt number and Darcy friction factor are developed that can be useful for thermal hydraulic analyses using system codes. Thermal stresses are analyzed and a brief discussion of the status of code cases of PCHEs for nuclear applications is given. Testing and thermomechanical modeling is needed to facilitate future code compliance of PCHEs for high pressure and high temperature applications.
KW - Airfoil fin
KW - Computational fluid dynamics
KW - Genetic algorithm
KW - Latin hypercube sampling
KW - Microchannel heat exchanger
KW - Topology optimization
UR - https://www.scopus.com/pages/publications/85126727000
UR - https://www.mendeley.com/catalogue/e801fff1-9674-3d18-8269-34b23a21b1d0/
U2 - 10.1016/j.nucengdes.2022.111737
DO - 10.1016/j.nucengdes.2022.111737
M3 - Article
AN - SCOPUS:85126727000
SN - 0029-5493
VL - 391
JO - Nuclear Engineering and Design
JF - Nuclear Engineering and Design
M1 - 111737
ER -