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Heuristics applying stochastic information as tools for thermoacoustic standing-wave engine optimization

Nowak I.

Computer Assisted Methods in Engineering and Science

2018

Vol. 25, no. 1

3--19

In this article, two numerical methods for solving engineering problems defined as multicriteria optimiza-tion and inverse problem are presented. In particular, thisstudy deals with the optimization of the designof thermoacoustic engine in the frame in which both types of tasks are solved. The first proposed heuristicserves to find many p-optimal solutions simultaneously, which represents a compromise between usuallymutually contradictory goals at work. Based on them, the full Pareto front is approximated. The inverseproblem solution reproduces parameters for solutions located on a designated front but those that arenot found in multicriteria optimization. In this article, the RACO heuristics are proposed for determiningp-optimal solutions and the Bayesian approach is introduced as a method for solving ill-conditioned inverseproblems. Optimization of the construction of the thermoacoustic engine is aimed at verifying proposedmethodology and present the possibility of using both methods in engineering problems. The problemdiscussed in this article is formulated and the numerical methods used in the solution are presented indetails.