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ABSTRACTAs the technology of material science progresses day by
day,the data of material properties are very important to
theapplication of new materials. Material properties may not
beeasy to obtain experimentally without the help of
propermathematical models. It is feasible to use inverse method
inpredicting the thermal properties of material. In this paper,
the conjugate gradient method is used to solve inverse
heattransfer problems to compute the thermal properties.
Conjugate gradient method includes three basic problems:direct
problem, sensitivity problem and adjoint problem.In this method,
a target function J is defined as the differencebetween measured
temperature and computed temperature,which can be obtained from
solving the direct problem.The conjugate gradient method
predicts the thermal propertyby minimizing the target function.
In each iteration, thesensitivity and adjoint problems offer a
corrected amount tomodify the property.With assumed thermal
properties, three numerical experimentsare used to test the
conjugate gradient method. From thecomputational results, it is
found that the method can predictthermal conductivity, heat
capacity and latent heat correctly.However, in the model of
predicting latent heat, there arethree assumptions: (1) Dx must
be small, (2) the casting materialis pure metal, (3) the pouring
temperature is the meltingtemperature. Finally, the measured
temperatures of metal in a(green-sand) casting process is used
to predict the thermalconductivity. Compared with the data
reported in the literature,the average error of the computed
values is 5.6%. From theseresults, it is shown that the
conjugate gradient method can beused to predict thermal
properties simply and accurately.
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