Livermore Software Technology Corporation

Other

Nielen Stander

Katharina Witowski

Anirban Basudhar

A reference curve representing measured stress-strain data obtained in a material test of a specimen is received. FEA model is created to represent the specimen which is associated with numerical material properties defined by a formula having a set of adjustable coefficients. Multiple computed curves are obtained each defined with multiple nodes of computed stress-strain values by conducting a time-marching simulation of the material test using the FEA model with a set of unique coefficients. Respective curve difference measurement parameters are calculated between each computed curve and the reference curve using a similarity measure technique that includes trimming off excess end portion of each computed curve so as to match the reference curve. Optimal values of the adjustable coefficients are determined by estimating a minimum of the curve difference measurement parameters according to an optimization technique.

Systems and methods of determining a numerical material model that optimally emulates physical material test results

Systems and methods of selecting sampling points (product designs) in a multi-objective engineering design optimization of a product are disclosed. The method comprises (a) receiving a description of the product to be optimized, (b) selecting an initial set of sampling points in a design variable space of the product, (c) obtaining numerically-simulated structural responses of each of the current set, (d) deriving a set of approximate POPs from optimization using metamodels constructed from numerically-simulated structural responses, (e) establishing subregions around POF kernels that are selected from approximate POPs using 'Piercing' procedure, (f) creating a set of Diversity Basis Points by populating the subregions with a space filling criterion, (g) selecting another set of sampling points from a combined group of the Diversity Basis Points and POF kernels using 'Piercing' procedure, (h) reducing the subregion size, and (i) repeating (c)-(h) until a termination condition has been reached.

Multi-objective engineering design optimization using sequential adaptive sampling in the pareto optimal region

Methods and systems for matching a computed curve to a target curve to enable realistic engineering simulations are disclosed. Discrepancies between computed curve and the target curve are measured, and based on the discrepancies, decisions on how to adjust parametric inputs can be made to achieve an optimal result of simulation. Optimization of parameter identification is achieved by adjusting the parametric inputs of a simulation model such that the discrepancy between the two curves is minimized. Because the points on the two curves to be matched are paired, matching of any two open curves, including hysteretic curves, can be handled. Curves that are complete set apart in their original coordinates can be merged to a common coordinate system for parameter identification without the computational instability problems.

Curve matching for parameter identification

Methods and systems for matching a computed curve to a target curve to enable realistic engineering simulations are disclosed. Optimization of parameter identification is achieved by adjusting the parametric inputs of a simulation model such that the discrepancy between the two curves is minimized. Because the points on the two curves to be matched are paired, matching of any two open curves, including hysteretic curves, can be handled. Curves that are completely set apart in their original coordinates can be merged to a common coordinate system for parameter identification without the computational instability problems. A partial matching scheme is used for mapping points defining the shorter one of the two curves to a set of mapped points on the longer one. One or more offsets from the first point of the longer curve are used for multiple attempts to find a best fit.

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Pleasanton, CA, United States of America

Nielen Stander