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

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 Ng 这项研究的目的是：1）通过 MRI（磁共振成像）非侵入性地可视化适当质量的颗粒材料的内部和行为，以及 2）验证通过 DEM（离散元）获得的微观观察结果方法）模拟。 其他人产生的随机椭球阵列的宏观 DEM 结果非常有希望。 它们为各种应变、排水和不排水载荷以及静态和循环载荷提供了定性正确的结果和一些良好的定量预测。 然而，需要 3D 观察来验证。 随着 MRI 的出现，这项研究是可行的。 研究结果将为模拟粒状土的本构关系提供通用的理论框架。 *** 9505340 Nakakawa 这项研究的目的是：1) 通过 MRI（磁共振成像）非侵入性地可视化适当质量的颗粒材料的内部和行为，以及 2) 验证 DEM 获得的显微观察结果（离散元法）模拟。 其他人产生的随机椭球阵列的宏观 DEM 结果非常有希望。 它们为各种应变、排水和不排水载荷以及静态和循环载荷提供了定性正确的结果和一些良好的定量预测。 然而，需要 3D 观察来验证。 随着 MRI 的出现，这项研究是可行的。 研究结果将为模拟粒状土的本构关系提供通用的理论框架。 *** 9503462 Ghaboussi 将开发一种新方法，直接根据土壤测试结果确定土壤本构模型。 主要目标是开发并通过实验验证这种测定方法，并将结果应用于根据现场试验和新型实验室试验的结果确定土壤的本构特性。 在利用神经网络对行为进行建模并使用有限元开发适当的计算方面后，将进行一系列实验来模拟现场测试。 与传统的土壤测试不同，在所提出的方法中，样品必须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不同应力路径。 新的土壤测试，包括相对简单的冲压测试，将在实验室中开发和测试。 这些结果将用于训练神经网络。 方法论和计算方面的开发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，直接根据土壤测试结果确定土壤本构模型。 主要目标是开发并通过实验验证这种测定方法，并将结果应用于根据现场试验和新型实验室试验的结果确定土壤的本构特性。 在利用神经网络对行为进行建模并使用有限元开发适当的计算方面后，将进行一系列实验来模拟现场测试。 与传统的土壤测试不同，在所提出的方法中，样品必须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不同应力路径。 新的土壤测试，包括相对简单的冲压测试，将在实验室中开发和测试。 这些结果将用于训练神经网络。 方法论和计算方面的开发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。 ***