Open AccessEstimation of Heat Flux in Inverse Heat Conduction Problems Using Quantum-Behaved Particle Swarm Optimization
Author(s) -
Naishuo Tian,
Wenbo Xu,
Jun Sun,
Lai Chen
Publication year - 2010
Publication title -
journal of algorithms and computational technology
Language(s) - English
Resource type - Journals
eISSN - 1748-3026
pISSN - 1748-3018
DOI - 10.1260/1748-3018.4.1.25
Subject(s) - particle swarm optimization , inverse problem , conjugate gradient method , heat flux , transient (computer programming) , thermal conduction , mathematical optimization , multi swarm optimization , quantum , stability (learning theory) , inverse , mathematics , computer science , heat transfer , physics , mechanics , mathematical analysis , thermodynamics , geometry , quantum mechanics , machine learning , operating system
An inverse optimization algorithm based on Quantum-Behaved Particle Swarm Optimization (QPSO) is examined and applied to estimate the unknown transient heat flux applied to certain boundaries in transient heat conduction problems. Results demonstrate the accuracy, stability and validity of the QPSO method in inverse estimation of the heat flux without prior knowledge of the functional form of the unknown quantities. This paper also addresses the high computational costs of QPSO and proposes a hybrid method to reduce the computational costs by combining the advantages of a gradient method and a stochastic method. Finally comparison of the proposed hybrid method and Conjugate Gradient Method (CGM) is also included.