New Method of Experimentation and Constitutive Modelling Using Neural Networks

使用神经网络进行实验和本构建模的新方法

• 批准号: 9503697
• 负责人: Poul Lade
• 金额: $ 11.05万
• 依托单位: Johns Hopkins University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1995
• 资助国家: 美国
• 起止时间: 1995-06-15 至 1999-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9503697&HistoricalAwards=false
• 关键词: New; Method; Experimentation; Constitutive; Modelling; New; Method; Experimentation; Constitutive; Modelling

9505338 Ng The objective of this research is: 1) to non-invasively visualize the interior and the behavior of a suitable mass of granular material by MRI (Magnetic Resonance Imaging), and 2) to verify the microscopic observations obtained by DEM (Discrete Element Method) simulations. Available macroscopic DEM results on random arrays of ellipsoids produced by others are very promising. They provide qualitatively correct results and some good quantitative predictions for a wide range of strains, drained and undrained loading, and static as well as cyclic loading. However, 3-D observations are needed for verification. This research is feasible with the availability of MRI. The results will provide a general theoretical framework for modeling the constitutive relations of granular soils. *** 9505340 Nakagawa The objective of this research is: 1) to non-invasively visualize the interior and the behavior of a suitable mass of granular material by MRI (Magnetic Resonance Imaging), and 2) to verify the microscopic observations obtained by DEM (Discrete Element Method) simulations. Available macroscopic DEM results on random arrays of ellipsoids produced by others are very promising. They provide qualitatively correct results and some good quantitative predictions for a wide range of strains, drained and undrained loading, and static as well as cyclic loading. However, 3-D observations are needed for verification. This research is feasible with the availability of MRI. The results will provide a general theoretical framework for modeling the constitutive relations of granular soils. *** 9503462 Ghaboussi A new method will be developed to determine constitutive models of soils directly from the results of soil tests. The primary objective is to develop and experimentally verify this method of determination, with the results applied to the determination of the constitutive properties of soils from the results of in situ tests and n ew types of laboratory tests. After developing appropriate computational aspects utilizing neural networks to model behavior and using the FEM, a series of experiments will be conducted to simulate the in situ tests. Unlike conventional soils tests, in the proposed method it is essential that the sample be subjected to a non uniform state of strain so that different points within the sample can be subjected to as many different stress paths as possible. New soils tests, including a relatively simple punched test, will be developed and tested in the laboratory. These results will be used to train the neural network. The development of methodology and the computational aspects will be conducted at the University of Illinois. The experimental part of the proposed research will be conducted at the Johns Hopkins University. *** 9503697 Lade A new method will be developed to determine constitutive models of soils directly from the results of soil tests. The primary objective is to develop and experimentally verify this method of determination, with the results applied to the determination of the constitutive properties of soils from the results of in situ tests and new types of laboratory tests. After developing appropriate computational aspects utilizing neural networks to model behavior and using the FEM, a series of experiments will be conducted to simulate the in situ tests. Unlike conventional soils tests, in the proposed method it is essential that the sample be subjected to a non uniform state of strain so that different points within the sample can be subjected to as many different stress paths as possible. New soils tests, including a relatively simple punched test, will be developed and tested in the laboratory. These results will be used to train the neural network. The development of methodology and the computational aspects will be conducted at the University of Illinois. The experimental part of the proposed rese arch will be conducted at the Johns Hopkins University. ***

9505338这项研究的目的是：1）非侵入性地可视化MRI（磁共振成像）和2）验证DEM（离散元素方法）模拟获得的显微镜观察的内部和行为。 对其他人产生的椭圆形随机阵列的可用宏观DEM结果非常有前途。 它们为广泛的应变，排水和不排水的负载以及静态以及循环载荷提供了定性正确的结果和一些良好的定量预测。 但是，需要进行3-D观察以进行验证。 这项研究对于MRI的可用性是可行的。 结果将提供一个一般的理论框架，用于建模颗粒土壤的本构关系。 *** 9505340 Nakagawa这项研究的目的是：1）通过MRI（磁共振成像）和2）非侵入性地可视化合适的颗粒材料的内部和行为，以验证DEM（离散元素方法）模拟获得的显微镜观察结果。 对其他人产生的椭圆形随机阵列的可用宏观DEM结果非常有前途。 它们为广泛的应变，排水和不排水的负载以及静态以及循环载荷提供了定性正确的结果和一些良好的定量预测。 但是，需要进行3-D观察以进行验证。 这项研究对于MRI的可用性是可行的。 结果将提供一个一般的理论框架，用于建模颗粒土壤的本构关系。 *** 9503462 Ghaboussi将开发一种新方法，以直接从土壤测试的结果中确定土壤的本构模型。 主要目标是开发和实验验证这种确定方法，其结果适用于从原位测试和实验室测试类型的NEW类型的结果中确定土壤的本构特性。 在开发了使用神经网络来建模行为并使用FEM的适当计算方面之后，将进行一系列实验以模拟原位测试。 与常规的土壤测试不同，在提出的方法中，必须将样品承受非均匀的应变状态，以便样品内的不同点可以承受尽可能多的应力路径。 将在实验室开发和测试新的土壤测试，包括相对简单的打孔测试。 这些结果将用于训练神经网络。 方法论的发展和计算方面将在伊利诺伊大学进行。 拟议研究的实验部分将在约翰霍普金斯大学进行。 *** 9503697 LADE将开发一种新方法，以直接从土壤测试的结果中确定土壤的组成型模型。 主要目的是开发和实验验证这种确定方法，其结果适用于从原位测试和新类型的实验室测试的结果中确定土壤的本构特性。 在开发了使用神经网络来建模行为并使用FEM的适当计算方面之后，将进行一系列实验以模拟原位测试。 与常规的土壤测试不同，在提出的方法中，必须将样品承受非均匀的应变状态，以便样品内的不同点可以承受尽可能多的应力路径。 将在实验室开发和测试新的土壤测试，包括相对简单的打孔测试。 这些结果将用于训练神经网络。 方法论的发展和计算方面将在伊利诺伊大学进行。 拟议的Rese Arch的实验部分将在约翰霍普金斯大学进行。 ***