Back analysis on thermal parameters of ship lock head based on BP neural network
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Abstract:
Due to eng ineering constructio n limits, the thermal parameter s of concrete for some lo ck head pr ojects cannot be deter2 mined by the adiabatic temperatur e rising test. In this paper, an inver sion analy sis method w as pr oposed to determine the lock head thermal par ameter s based o n BP neural netw or k. First, the combinatio ns o f co ncr ete thermal par ameters w ere constructed based on the unifo rm desig n theor y and they w ere used to generate a series of training samples using the thermal FEM analysis. Then, the measured temper ature dat a w ere put into the neural netw ork to per form the inv ersio n ana lysis on the thermal parame2 ter s. Finally, t he therma l parameters o btained from the inv er sion ana lysis w ere used to ana lyze and pr edict the temper ature data at certain po ints and compared t hem w ith the actual temperature data. The results show ed the co nv erg ence r ate o f t he BP neural netw or k is improv ed by the t hermal par ameters developed by the unifo rm desig n, and the obtained parameter s meet the eng i2 neering requirements.
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