2007
DOI: 10.1016/j.ijheatmasstransfer.2006.11.022
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Inverse estimation of heat flux and temperature in multi-layer gun barrel

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Cited by 44 publications
(14 citation statements)
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“…For the validation, the present model was compared with a reference model employing the finite element method (FEM) along with the Kalman filter and recursive least-squares algorithm. The details of the reference model can be found elsewhere [22]. For both models, the initial temperature was T 0 = 298.15 K, the number of node elements was E = 25, the sampling interval was Dt = 0.001 s, and the exact transient heat flux profile was given as follows.…”
Section: Resultsmentioning
confidence: 99%
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“…For the validation, the present model was compared with a reference model employing the finite element method (FEM) along with the Kalman filter and recursive least-squares algorithm. The details of the reference model can be found elsewhere [22]. For both models, the initial temperature was T 0 = 298.15 K, the number of node elements was E = 25, the sampling interval was Dt = 0.001 s, and the exact transient heat flux profile was given as follows.…”
Section: Resultsmentioning
confidence: 99%
“…The details of the description and derivation of this algorithm can be found elsewhere [19,22]. The calculation process of the Kalman filter was expressed as follows.…”
Section: Kalman Filter and Recursive Least-squares Algorithmmentioning
confidence: 99%
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“…However, the inverse heat conduction problems (IHCP) can predict these parameters by utilizing measured temperature on or in the structures and have been applied widely [1][2][3][4][5][6].…”
Section: Introductionmentioning
confidence: 99%
“…The maximum entropy method [6] is applied to estimate the surface temperature by Kim et al The inverse heat conduction problem is reformulated for MEM and a three-phase solution method using the successive quadratic programming. Chen et al [7] presents an input estimation method to estimate the time-varying heat flux and the temperature of the inner wall in the chamber recursively. Their simulated results show that the proposed method exhibits a good estimation performance and promotes a practical implementation highly.…”
Section: Introductionmentioning
confidence: 99%