New Method of Experimentation and Constitutive Modelling Using Neural Networks

9505338 Ng本研究的目的是：1）通过MRI（磁共振成像）非侵入性地可视化颗粒材料的内部和行为，以及2）验证通过DEM（离散元素方法）模拟获得的显微观察结果。 现有的宏观DEM结果的随机阵列的椭球体产生的其他是非常有前途的。 他们提供了定性正确的结果和一些很好的定量预测范围广泛的应变，排水和不排水荷载，以及静态和循环荷载。 但是，需要进行三维观察以进行验证。 在MRI检查的条件下，本研究是可行的。 研究结果将为粒状土本构关系的建模提供一个通用的理论框架。 *** 9505340 Nakagawa本研究的目的是：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（离散元方法）模拟获得的微观观察结果。 现有的宏观DEM结果的随机阵列的椭球体产生的其他是非常有前途的。 他们提供了定性正确的结果和一些很好的定量预测范围广泛的应变，排水和不排水荷载，以及静态和循环荷载。 但是，需要进行三维观察以进行验证。 在MRI检查的条件下，本研究是可行的。 研究结果将为粒状土本构关系的建模提供一个通用的理论框架。 *** 9503462 Ghaboussi将开发一种新的方法来直接从土壤试验的结果确定土壤的本构模型。 主要目的是开发和实验验证这种方法的测定，与应用的结果确定的土的本构特性的结果，在现场试验和新类型的实验室试验。 在开发适当的计算方面，利用神经网络模型的行为和使用有限元，一系列的实验将进行模拟原位测试。 与传统的土壤试验不同，在所提出的方法中，样品必须经受非均匀的应变状态，以便样品内的不同点可以经受尽可能多的不同应力路径。 新的土壤测试，包括相对简单的冲孔测试，将在实验室开发和测试。 这些结果将用于训练神经网络。 方法和计算方面的发展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将开发一种新的方法来直接从土壤试验的结果确定土壤的本构模型。 主要目的是开发和实验验证这种方法的测定，与适用于确定的土壤的本构特性的结果，从原位测试和新型的实验室测试的结果。 在开发适当的计算方面，利用神经网络模型的行为和使用有限元，一系列的实验将进行模拟原位测试。 与传统的土壤试验不同，在所提出的方法中，样品必须经受非均匀的应变状态，以便样品内的不同点可以经受尽可能多的不同应力路径。 新的土壤测试，包括相对简单的冲孔测试，将在实验室开发和测试。 这些结果将用于训练神经网络。 方法和计算方面的发展将在伊利诺伊大学进行。 这项研究的实验部分将在约翰霍普金斯大学进行。 ***

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. ***