Solving of Two‐Dimensional Unsteady Inverse Heat Conduction Problems Based on Boundary Element Method and Sequential Function Specification Method

Wang, Shoubin; Deng, Yuanzheng; Sun, Xuepeng

doi:10.1155/2018/6741632

Cited by 6 publications

(3 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The temperature values are used as input to invert the boundary heat flux q 1 (t) and q 2 (t). The results are compared with those obtained by the sequential function specification method (SFSM) to verify the effectiveness of the algorithm [24].…”

Section: Verification Of Algorithm Validitymentioning

confidence: 99%

Research on Unsteady Inverse Heat Conduction Based on Dynamic Matrix Control

Huang

Liu

2023

Energies

View full text Add to dashboard Cite

For the unsteady multi-boundary inverse heat conduction problem, a real-time solution method for boundary heat flux based on dynamic matrix control is proposed in the paper. The method solves the heat flux at the boundary in real-time by measuring the temperature information at the measurement points of the heat transfer system. A two-dimensional direct heat conduction model of the heat transfer system is established in the paper, and is solved by the finite difference method to obtain the temperature information of the measurement points under any heat flux boundary. Then, the correspondence between the heat flux of boundary and the temperature information is presented by means of a step-response model. The regularization parameters are introduced into the method to improve the stability of the inversion process, and the effect of real-time inversion on the heat flux of the boundary is achieved through rolling optimization. The experimental results show that the proposed method can achieve real-time inversion of the heat fluxes of the two-dimensional boundary with good accuracy.

show abstract

Section: Verification Of Algorithm Validitymentioning

confidence: 99%

Research on Unsteady Inverse Heat Conduction Based on Dynamic Matrix Control

Huang

Liu

2023

Energies

View full text Add to dashboard Cite

show abstract

“…Suitable for linear systems, the method can be also applied to the non-linear IHCP; however, iterative procedure is necessary [36] [37]. The method has been successfully used with the multidimensional problems [38][39] [40]. A similar sequential method is available known as the conjugate gradient method with the adjoint equation (CGMAE).…”

Section: Introductionmentioning

confidence: 99%

Sequential Inverse Heat Conduction Problem in OpenFOAM

et al. 2021

View full text Add to dashboard Cite

The solution of the inverse heat conduction problem (IHCP) is commonly found with the sequential algorithm known as the function specification method with explicit updating formulas and sensitivity coefficients of heat flux. This paper presents a different approach namely a direct mathematical optimization of minimizing the least squares norm between experimental data and simulation. A CFD open-source code OpenFOAM is used together with NLOPT and DLIB optimization libraries. To guarantee credibility of the simulation tool developed herein, real experimental data is used from spray cooling of a fast-moving hot steel plate. As the IHCP is inherently an ill-posed problem, the proposed sequential algorithm is stabilized using future time stepping and thereof the optimal number is explained. An assumption about the profile of thermal boundary condition during future steps must be made. It is shown that assuming a linear change of the heat transfer coefficient during each sequence of future time steps yields more accurate results than setting a constant value. For the problem size considered with less than 10k cells, the preconditioned conjugate gradient (FDIC) linear solver converges faster than the multigrid solver (GAMG). However, the latter performs better as the accuracy is concerned. Concerning the best choice of minimizer, the BOBYQA algorithm (quadratic approximation) is found superior to other methods. The proposed IHCP solver is compared with the well-established one.

show abstract

“…The Inverse Heat Conduction Problem is able to retrieve the unknown parameters such as boundary conditions, material thermophysical parameters [1][2][3], internal heat sources, and boundary geometry by measuring the temperature information at the boundary or at some point in the heattransfer system [4,5]. The research of inverse heat conduction problem has a very wide application background.…”

Section: Introductionmentioning

confidence: 99%

Solving of Two‐Dimensional Unsteady‐State Heat‐Transfer Inverse Problem Using Finite Difference Method and Model Prediction Control Method

Wang

2019

Complexity

Self Cite

View full text Add to dashboard Cite

The Inverse Heat Conduction Problem (IHCP) refers to the inversion of the internal characteristics or thermal boundary conditions of a heat transfer system by using other known conditions of the system and according to some information that the system can observe. It has been extensively applied in the fields of engineering related to heat-transfer measurement, such as the aerospace, atomic energy technology, mechanical engineering, and metallurgy. The paper adopts Finite Difference Method (FDM) and Model Predictive Control Method (MPCM) to study the inverse problem in the third-type boundary heat-transfer coefficient involved in the two-dimensional unsteady heat conduction system. The residual principle is introduced to estimate the optimized regularization parameter in the model prediction control method, thereby obtaining a more precise inversion result. Finite difference method (FDM) is adopted for direct problem to calculate the temperature value in various time quanta of needed discrete point as well as the temperature field verification by time quantum, while inverse problem discusses the impact of different measurement errors and measurement point positions on the inverse result. As demonstrated by empirical analysis, the proposed method remains highly precise despite the presence of measurement errors or the close distance of measurement point position from the boundary angular point angle.

show abstract

Solving of Two‐Dimensional Unsteady Inverse Heat Conduction Problems Based on Boundary Element Method and Sequential Function Specification Method

Cited by 6 publications

References 22 publications

Research on Unsteady Inverse Heat Conduction Based on Dynamic Matrix Control

Research on Unsteady Inverse Heat Conduction Based on Dynamic Matrix Control

Sequential Inverse Heat Conduction Problem in OpenFOAM

Solving of Two‐Dimensional Unsteady‐State Heat‐Transfer Inverse Problem Using Finite Difference Method and Model Prediction Control Method

Contact Info

Product

Resources

About