Robust model for optimization of forming process for metallic bipolar plates of cleaner energy production system
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gp-bibliography.bib Revision:1.8098
- @Article{HUANG:2018:IJHE,
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author = "Yuhao Huang and Akhil Garg and Saeed Asghari and
Xiongbin Peng and My Loan Phung Le",
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title = "Robust model for optimization of forming process for
metallic bipolar plates of cleaner energy production
system",
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journal = "International Journal of Hydrogen Energy",
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volume = "43",
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number = "1",
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pages = "341--353",
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year = "2018",
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keywords = "genetic algorithms, genetic programming,
Proton-exchange membrane fuel cell(PEMFC), Rubber pad
forming(RPF), Genetic programming(GP), Factorial design
method",
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ISSN = "0360-3199",
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DOI = "doi:10.1016/j.ijhydene.2017.11.043",
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URL = "http://www.sciencedirect.com/science/article/pii/S0360319917343604",
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abstract = "Energy production systems such as proton-exchange
membrane fuel cell (PEMFC) has a promising future in
the cleaner energy market due to zero emissions. Rubber
pad forming (RPF) process of metallic bipolar plates of
PEMFCs is gaining attention among the researchers.
Studies based on design of experiments have been
conducted to find the crucial parameters of the forming
process. These methods are based on the assumptions of
the model structure, correlated residuals, etc., which
can cause uncertainty in estimation ability of the
model on unseen data. Therefore, the present study
focuses on the design of robust models of these
parameters for PEMFCs using an optimization approach of
genetic programming (GP). The inputs from the
experiments considered in GP are radius, the friction
coefficient, the filling factor and the minimum
thickness. Experiments on PEMFCs validates the
performance of the GP models. Further, the
relationships between the two inputs and the three
outputs for PEMFCs are generated as well as the
contributions of each input to each of the output.
Optimization of the models generated by GP can further
determine the forming quality of metallic bipolar
plates of PEMFCs by an appropriate setting of the two
inputs",
- }
Genetic Programming entries for
Yuhao Huang
Akhil Garg
Saeed Asghari
Xiongbin Peng
My Loan Phung Le
Citations