Sequential Regularization Method for the Identification of Mold Heat Flux during Continuous Casting Using Inverse Problem Solutions Techniques

被引:2
|
作者
Zhang, Haihui [1 ]
Zou, Jiawei [1 ]
Xiao, Pengcheng [2 ]
机构
[1] Jiangxi Univ Sci & Technol, Fac Mat Met & Chem, Ganzhou 341000, Peoples R China
[2] North China Univ Sci & Technol, Coll Met & Energy, Tangshan 063210, Peoples R China
关键词
continuous casting; heat transfer; inverse problem; accuracy; sequential regularization method; INITIAL SOLIDIFICATION; TRANSFER COEFFICIENTS; SLAG INFILTRATION; MOLTEN STEEL; AIR-GAP; PART II; SIMULATOR; OSCILLATION; BILLET; DECOMPOSITION;
D O I
10.3390/met13101685
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
A two-dimensional transient inverse heat-conduction problem (2DIHCP) was established to determine the mold heat flux using observed temperatures. The sequential regularization method (SRM) was used with zeroth-, first-, and second-order spatial regularization to solve the 2DIHCP. The accuracy of the 2DIHCP was investigated under two strict test conditions (Case 1: heat flux with time-spatial periodically varying, and Case 2: that with sharp variations). The effects of the number of future time steps, regularization parameters, order of regularization, discrete grids, and time step size on the accuracy of the 2DIHCP were analyzed. The results showed that the minimum relative error (epred) of the predicted Case 1 heat flux is 5.05%, 5.39%, and 5.88% for zeroth-, first-, and second-order spatial regularization, respectively. The corresponding values for the predicted Case 2 heat flux are 6.31%, 6.30%, and 6.36%. Notably, zeroth- and first-order spatial regularization had higher accuracy than second-order spatial regularization, while zeroth-order spatial regularization was comparable to first-order. Additionally, first-order spatial regularization was more accurate in reconstructing heat flux containing sharp spatial variations. The CPU time of the predicted Case 2 heat flux is 1.71, 1.71, and 1.70 s for zeroth-, first-, and second-order spatial regularization, respectively. The corresponding values for the predicted Case 1 heat flux are 6.18, 6.15, and 6.17 s. It is noteworthy that the choice of spatial regularization order does not significantly impact the required computing time. Lastly, the minimum epred of Case 2 heat flux with zeroth-order spatial regularization is 7.96%, 6.42%, and 7.87% for time step sizes of 1/fs, 1/2fs, and 1/5fs, respectively. The accuracy of the inverse analysis displays an initial improvement followed by degradation as the time step size decreases. A recommended time step size is 1/2fs, where fs denotes the temperature-sampling rate.
引用
收藏
页数:24
相关论文
共 47 条
  • [31] Influence of mold heat flux on longitudinal surface cracks during high-speed continuous casting of steel slab
    Nakajima, Keiji
    Hiraki, Sei
    Kawamoto, Masayuki
    Kanazawa, Takashi
    Sumitomo Search, 1994, (55): : 32 - 39
  • [32] Determination of Time-Spatial Varying Mold Heat Flux During Continuous Casting from Fast Response Thermocouples
    Zhang, Haihui
    Xiao, Pengcheng
    METALLURGICAL AND MATERIALS TRANSACTIONS B-PROCESS METALLURGY AND MATERIALS PROCESSING SCIENCE, 2023, 54 (06): : 3462 - 3484
  • [33] Accurate heat flux estimation in continuous casting Molds via MH-MCMC Bayesian Inverse Method
    Kumar, Suraj
    Siddiqui, Mohammad Tabish
    Ganguly, Suvankar
    Talukdar, Prabal
    APPLIED THERMAL ENGINEERING, 2024, 257
  • [34] SEQUENTIAL BOUNDARY HEAT FLUX ESTIMATION USING THE METHOD OF FUNDAMENTAL SOLUTIONS AND BAYESIAN FILTERS
    Polatschek Kopperschmidt, Carlos Eduardo
    Marques Margotto, Bruno Henrique
    Rambalducci Dalla, Carlos Eduardo
    Colaco, Marcelo Jose
    da Silva, Wellington Betencurte
    Sampaio Dutra, Julio Cesar
    PROCEEDINGS OF CHT-21 ICHMT INTERNATIONAL SYMPOSIUM ON ADVANCES IN COMPUTATIONAL HEAT TRANSFER, 2021, 2021,
  • [35] HEAT FLUX CHARACTERIZATION FROM A BAND HEATER TO PIPE USING INVERSE HEAT CONDUCTION PROBLEM METHOD
    da Silva, Ramon Peruchi Pacheco
    Woodbury, Keith
    Samadi, Forooza
    Carpenter, Joseph
    PROCEEDINGS OF ASME 2023 HEAT TRANSFER SUMMER CONFERENCE, HT2023, 2023,
  • [36] Note on using radial basis functions and Tikhonov regularization method to solve an inverse heat conduction problem
    Shidfar, A.
    Darooghehgimofrad, Z.
    Garshasbi, M.
    ENGINEERING ANALYSIS WITH BOUNDARY ELEMENTS, 2009, 33 (10) : 1236 - 1238
  • [37] Estimation of heat flux entering the bone during the drilling process using the inverse heat transfer method
    Farahani, Somayeh Davoodabadi
    Tahmasebi, Vahid
    Toghraie, Davood
    INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER, 2024, 154
  • [38] Thermal analysis during continuous casting process using effective heat capacity method
    Amin, MR
    JOURNAL OF THERMOPHYSICS AND HEAT TRANSFER, 2000, 14 (02) : 170 - 176
  • [39] Experimental disc heat flux identification on a reduced scale braking system using the inverse heat conduction method
    Meresse, D.
    Harmand, S.
    Siroux, M.
    Watremez, M.
    Dubar, L.
    APPLIED THERMAL ENGINEERING, 2012, 48 : 202 - 210
  • [40] On-line heat flux estimation of a nonlinear heat conduction system with complex geometry using a sequential inverse method and artificial neural network
    Huang, Shuwen
    Tao, Bo
    Li, Jindang
    Yin, Zhouping
    INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER, 2019, 143