Livermore Software Technology Corporation

Tushar Goel

Willem J Roux

Improved methods and systems for a neighborhood determination in computer aided engineering analysis are disclosed. According to one aspect, a list of neighbor elements is created for a base element of a grid model representing a structure or an engineering product. The representative node's coordinates of the base element are calculated using corner nodes of the base element. A characteristic length is assigned to the base element. The characteristic length can be determined by users of the computer aided analysis, or be calculated using geometry of the base element. The characteristic length and the representative node collectively define a surface boundary that divides elements in the grid model into two groups. The first group contains potential neighbors, while the second group contains non-neighbors. Only elements in the first group are further processed using traditional procedures to determine whether each of them is indeed a neighbor element according to one of the neighborhood determination criteria.

Neighborhood determination methods and systems in computer aided engineering analysis

Improved topology optimization for engineering product design is disclosed. An engineering product including a design domain to be optimized is defined. Design domain can be a portion or the entire engineering product. Design objective and optional constraint are defined such that optimization goal is achieved. Additionally, initial configuration of the design domain is represented by a finite element analysis (FEA) mesh. Each element or element group is associated with a design variable. A set of discrete material models is created from the baseline material used for the design domain. The set of discrete material models is configured to cover entire range of the design variable and each discrete material model represents a non-overlapping portion. Each element representing the design domain is associated with an appropriate discrete material model according to the design variable. Structure response is obtained via FEA to evaluate design objective and update design variable.

Topology optimization for designing engineering product

Systems and methods of obtaining a set of better converged and diversified Pareto optimal solutions in an engineering design optimization of a product (e.g., automobile, cellular phone, etc.) are disclosed. According to one aspect, a plurality of MOEA based engineering optimizations of a product is conducted independently. Each of the independently conducted optimizations differs from others with parameters such as initial generation and/or evolutionary algorithm. For example, populations (design alternatives) of initial generation can be created randomly from different seed of a random or pseudo-random number generator. In another, each optimization employs a particular revolutionary algorithm including, but not limited to, Nondominated Sorting Genetic Algorithm (NSGA-II), strength Pareto evolutionary algorithm (SPEA), etc. Furthermore, each independently conducted optimization's Pareto optimal solutions are combined to create a set of better converged and diversified solutions. Combinations can be performed at one or more predefined checkpoints during evolution process of the optimization.

Multi-objective evolutionary algorithm based engineering design optimization

The present invention discloses systems and methods of conducting multi-objective evolutionary algorithm (MOEA) based engineering design optimization of a product (e.g., automobile, cellular phone, etc.). Particularly, the present invention discloses an archive configured for monitoring the progress and characterizing the performance of the MOEA based optimization. Further, an optimization performance indicator is created using the archive's update history. The optimization performance indicator is used as a metric of the current state of the optimization. Finally, a stopping or termination criterion for the MOEA based optimization is determined using a measurement derived from the optimization performance indicators. For example, a confirmation of a 'knee' formation has developed in the optimization performance indicators. The optimization performance indicators include, but are not limited to, consolidation ratio, improvement ratio, hypervolume.

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Livermore, CA, United States of America

Tushar Goel