Geometrically and materially nonlinear analysis using material point method
Date
2022
Authors
Asiri, Abdullah N., author
Heyliger, Paul, advisor
van de Lindt, John, committee member
Chen, Suren, committee member
Cheney, Margaret, committee member
Journal Title
Journal ISSN
Volume Title
Abstract
Computational engineering has become an effective tool for different engineering aspects. It provides suitable simulation models for complex problems. Also, the computational models are strongly recommended as alternatives to experiments due to the consumed cost and time. In addition, because this field has gotten attention earlier, the accuracy of computational models has been improved. The finite element method (FEM) is one of the famous computer simulations that has been adopted widely in scientific and technical fields. It considers an excellent tool for different engineering analyses; however, for the large deformation behavior, the FEM cannot withstand due to the finite discretization of the systems in which the accuracy would be lost as a result of the large distortion that occurred for the model. Thereby, the mesh-less methods are appropriate models for such problems. The material point method (MPM) is one of the improved mesh-less methods, which is an extension of the Particle In Cell (PIC) method used for fluid mechanics modeling. Both static and dynamic applications are intended to simulate the two-dimensional material point method model. The main objective here is to simulate and validate the material point method with the analytical solutions for different solid mechanics applications. Further, to examine the formulation of the nonlinear behavior using the MPM. The research can be achieved by studying two hypotheses: 1) Beam mechanics analysis using the material point method and 2) Damage mechanics analysis using the material point method. Both hypotheses consider different assumptions of the geometry and material constants. Material point simulation of the two hypotheses will be conducted through RMACC Summit Supercomputer using FORTRAN and MATLAB languages.