2019
DOI: 10.3390/data4030090
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Database for Research Projects to Solve the Inverse Heat Conduction Problem

Abstract: To achieve the optimal performance of an object to be heat treated, it is necessary to know the value of the Heat Transfer Coefficient (HTC) describing the amount of heat exchange between the work piece and the cooling medium. The prediction of the HTC is a typical Inverse Heat Transfer Problem (IHCP), which cannot be solved by direct numerical methods. Numerous techniques are used to solve the IHCP based on heuristic search algorithms having very high computational demand. As another approach, it would be pos… Show more

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Cited by 3 publications
(1 citation statement)
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“…The effectiveness and accuracy of the estimation were verified by numerical simulation and experiment. Szénási and Felde [20] proposed a database containing the heat transfer coefficient function and the corresponding temperature records for the heat exchange between the work piece and the cooling medium, and designed a simple feedforward dense neural network to solve the IHCP. Zielonka et al [21] proposed a method to solve the inverse problem of alloy solidification in casting mold based on metal shrinkage phenomenon.…”
Section: Introductionmentioning
confidence: 99%
“…The effectiveness and accuracy of the estimation were verified by numerical simulation and experiment. Szénási and Felde [20] proposed a database containing the heat transfer coefficient function and the corresponding temperature records for the heat exchange between the work piece and the cooling medium, and designed a simple feedforward dense neural network to solve the IHCP. Zielonka et al [21] proposed a method to solve the inverse problem of alloy solidification in casting mold based on metal shrinkage phenomenon.…”
Section: Introductionmentioning
confidence: 99%