BP neural network regularized by wall temperature characteristics to reduce the ill-posedness of two-dimensional inverse heat transfer problems in rotating disk cavities
Changchun Deng , Tian Qiu , Peng Liu , Shuiting Ding , Xiang Luo
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引用次数: 0
Abstract
In the two-dimensional heat transfer experiments of aero-engine rotating disk cavities, the inverse heat transfer problem method can be used to obtain the wall heat flux numerically, which uses the two-dimensional measured wall temperature to solve the rotating disk heat conduction equation. A back propagation (BP) neural network data approximation method is proposed to reduce the ill-posedness of the two-dimensional inverse heat transfer problems in rotating disk cavities in this paper. The priori knowledge of wall temperature characteristics expressed by two-dimensional wall temperature first-order radial partial derivative distribution is used for BP neural networks’ regularization. The distribution characteristics of the wall temperature first-order radial partial derivative in a typical preswirl rotating disk cavity were investigated by the flow-thermal coupling numerical simulation. Based on these characteristics, the BP neural network construction and training method with uncertain regularization coefficient is adopted. The numerical experiment results show that compared with the traditional polynomial fitting methods, the BP neural network approximation methods in this paper show significant advantages in data processing performance and stability; The fluctuation amplitude of the wall heat flux relative error on the disk surface can be reduced by 1–3 orders of magnitude, reducing the relative error of wall heat flux in most areas of the disk to within 20 % of the original value; The maximum wall heat flux relative error suppression area where |δqr,cal/δqr,mea × 100 %| < 100 % of BP neural network approximation method can reach 1.93 times that of the traditional fitting method, and 3.18 times for the area where |δqr,cal/δqr,mea × 100 %| < 30 % in the current study.
期刊介绍:
The International Journal of Thermal Sciences is a journal devoted to the publication of fundamental studies on the physics of transfer processes in general, with an emphasis on thermal aspects and also applied research on various processes, energy systems and the environment. Articles are published in English and French, and are subject to peer review.
The fundamental subjects considered within the scope of the journal are:
* Heat and relevant mass transfer at all scales (nano, micro and macro) and in all types of material (heterogeneous, composites, biological,...) and fluid flow
* Forced, natural or mixed convection in reactive or non-reactive media
* Single or multi–phase fluid flow with or without phase change
* Near–and far–field radiative heat transfer
* Combined modes of heat transfer in complex systems (for example, plasmas, biological, geological,...)
* Multiscale modelling
The applied research topics include:
* Heat exchangers, heat pipes, cooling processes
* Transport phenomena taking place in industrial processes (chemical, food and agricultural, metallurgical, space and aeronautical, automobile industries)
* Nano–and micro–technology for energy, space, biosystems and devices
* Heat transport analysis in advanced systems
* Impact of energy–related processes on environment, and emerging energy systems
The study of thermophysical properties of materials and fluids, thermal measurement techniques, inverse methods, and the developments of experimental methods are within the scope of the International Journal of Thermal Sciences which also covers the modelling, and numerical methods applied to thermal transfer.