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     COLLOQUIUM OF THE COMPUTATIONAL MATERIALS SCIENCE CENTER
AND THE SCHOOL OF PHYSICS, ASTRONOMY, & COMPUTATIONAL SCIENCES
                            (CSI 898-Sec 001)
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       TOWARDS  DATA AND SPECIFICATION DRIVEN INVERSE MULITSCALE 
                            DESIGN OF MATERIALS

                           John G. Michopoulos
Computational Multiphysics System Lab., Center of Computational Materials Science
                      Naval Research Laboratory, Washington DC

    We are presenting an overview of a framework for treating material behavior
and material properties as design models and variables respectively, in the
context of designing materials that need to perform such as they satisfy
specific data- and specification-driven performance requirements. 
After an overview of the general principles and strategies two examples will
be presented at the opposite ends of the length scale spectrum. 
In the atomistic scale level we demonstrate the determination of the
Lenard-Jones (L-J) potential parameters that govern the dynamics of a problem
of fracture such that a specific load history of the associated medium is
realized. The approach followed is that of an inverse problem. A global Monte
Carlo optimizer along with a legacy molecular dynamics code are implemented on
Graphical Process Unit computational infrastructure, to compute the design
variables of the problem that in this case are the L-J constants.
    In the macro scale we demonstrate the determination of a general set of
material parameters that define the elastic and inelastic (with damage)
constitutive response of the general anisotropic medium applicable for
fiber-epoxy composite material laminates. The specification requirements to be
satisfied are those of a set of data representing load-displacement histories
in the full 6-dimensional kinematic space collected via a custom-made
multiaxial robotic testing machine..  The problem is also approached from an
inverse problem perspective. The determination of the best suitable
constitutive theory and the design (material) constants is achieved by
minimizing objective functions such as the difference between experimentally
measured and analytically computed system responses as described by strain
fields and surface strain energy densities. Finally, examples based actual
data demonstrate the successful application of design optimization for
constitutive characterization.

                          November 26, 2012
                               4:30 pm
                    Room 301, Research I, Fairfax Campus

Refreshments will be served at 4:15 PM.
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Find the schedule at http://www.cmasc.gmu.edu/seminars.htm