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首页> 外文期刊>Bulletin of the Polish Academy of Sciences. Technical Sciences >Some aspects of application of artificial neural network for numerical modeling in civil engineering
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Some aspects of application of artificial neural network for numerical modeling in civil engineering

机译:人工神经网络在土木工程数值建模中的一些应用

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In order to obtain reliable results of computations in civil engineering, the numerical procedures that are used at the stage of design should be calibrated by comparison of the theoretical results with an observed behavior of previously modeled and then executed structures. The hybrid Finite Element code with an Artificial Neural Network inserted as a representation of a constitutive law, offers a possibility to adjust not only parameters of the constitutive relationships but also its qualitative form. Because of this, the representation of constitutive law by the ANN is presented in this paper. The constitutive data should be calibrated to fit well the observable values, measured in experiments. If the constitutive law is expressed by ANN, the inverse problem can be reduce to a training of the ANN inserted into the Finite Element code. An example of a solution of the inverse problem in calibration of constitutive law is presented. An identification of parameters of flow of pollutant in soils is described as another example of application of ANN in engineering.
机译:为了在土木工程中获得可靠的计算结果,在设计阶段使用的数字程序应通过将理论结果与先前建模然后执行的结构的观察到的行为进行比较来进行校准。带有人工神经网络的混合有限元代码插入,作为本构定律的表示,不仅可以调整本构关系的参数,而且可以调整其定性形式。因此,本文提出了用ANN表示本构法。本构数据应进行校准,以使其与实验中测得的可观察值相吻合。如果本构定律由ANN表示,则反问题可以简化为对插入有限元代码中的ANN的训练。给出了解决本构定律反问题的一个例子。 ANN在工程中的另一个应用实例是对土壤污染物流向参数的识别。

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