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The assignment:Determination of crack propogation direction for CT specimen using different theories such as MTS,MTPS,Del-criteria,T-criteria,Ip theory

using ansys multiphysics

1) What are the boundry condition to be used for above criteria

2) How to take care of mixed mode loading

A PhD opportunity in the field of computational and applied mechanics is available in the department of Civil and Environmental engineering at the University of Illinois at Urbana-Champaign.

Qualifying candidates must have a strong background in mechanics and mathematics. Familiarity with scientific computing in one of the widely used programming languages (e.g. Fortran, C++ or Python)is required.

hello, everybody 



    I've made a 3D multi-story frame and shear-wall model in Abaqus. So far, I wanna get the equivalent story mass, story stiffness and story modal displacement. how to extract the story mass and story displacement in Abaqus?   or how to make an equivalent multi-mass point system from original 3D multi-story model? 



Thanks in advance 



Best Regards, 

Shelton 

A major oil and gas service company in Houston, TX is hiring a mechanical engineer, please see below descriptions for detail. If you are interested in this position, please email your resume to ComponentME [at] gmail.com (ComponentME[at]gmail[dot]com).

How to include water buoyancies effect in analysis for an abaqus model. The abaqus model is developed using shell and solid elements

Shannon-type expected information gain can be used to evaluate the
relevance of a proposed experiment subjected to uncertainty. The
estimation of such gain, however, relies on a double-loop integration.
Moreover, its numerical integration in multi-dimensional cases, e.g.,
when using Monte Carlo sampling methods, is therefore computationally
too expensive for realistic physical models, especially for those
involving the solution of partial differential equations. In this work,
we present a new methodology, based on the Laplace approximation for the
integration of the posterior probability density function (pdf), to
accelerate the estimation of the expected information gains in the model
parameters and predictive quantities of interest. We obtain a