Publications

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How does a structure fail in an explosion? Is there an engineering design opportunity to mitigate the effects of a blast? These are questions that may be addressed with simulation; however, a computational simulation capability to answer these questions must include developments in material physics modeling and numerical algorithms that we believe are possible, but do not yet exist. This LDRD project proposes to develop the physics models and computational approaches to create a computational simulation approach to answer these physics and engineering questions.

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Computational simulation of structures subjected to blast loadings requires integration of computational shock-physics for blast, and structural response with potential for pervasive failure. Current methodologies for this problem space are problematic in terms of efficiency and solution quality. This report details the development of several coupling algorithms for thin shells, with an emphasis on rigorous verification where possible and comparisons to existing methodologies in use at Sandia.

This paper describes an approach that seeks to parallelize the spatial search associated with computational contact mechanics. In contact mechanics, the purpose of the spatial search is to find “nearest neighbors,” which is the prelude to an imprinting search that resolves the interactions between the external surfaces of contacting bodies. In particular, we are interested in the contact global search portion of the spatial search associated with this operation on domain-decomposition-based meshes. Specifically, we describe an implementation that combines standard domain-decomposition-based MPI-parallel spatial search with thread-level parallelism (MPI-X) available on advanced computer architectures (those with GPU coprocessors). Our goal is to demonstrate the efficacy of the MPI-X paradigm in the overall contact search. Standard MPI-parallel implementations typically use a domain decomposition of the external surfaces of bodies within the domain in an attempt to efficiently distribute computational work. This decomposition may or may not be the same as the volume decomposition associated with the host physics. The parallel contact global search phase is then employed to find and distribute surface entities (nodes and faces) that are needed to compute contact constraints between entities owned by different MPI ranks without further inter-rank communication. Key steps of the contact global search include computing bounding boxes, building surface entity (node and face) search trees and finding and distributing entities required to complete on-rank (local) spatial searches. To enable source-code portability and performance across a variety of different computer architectures, we implemented the algorithm using the Kokkos hardware abstraction library. While we targeted development towards machines with a GPU accelerator per MPI rank, we also report performance results for OpenMP with a conventional multi-core compute node per rank. Results here demonstrate a 47 % decrease in the time spent within the global search algorithm, comparing the reference ACME algorithm with the GPU implementation, on an 18M face problem using four MPI ranks. While further work remains to maximize performance on the GPU, this result illustrates the potential of the proposed implementation.

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This document compares the finite element shell formulations in the Sierra Solid Mechanics code. These are finite elements either currently in the Sierra simulation codes Presto and Adagio, or expected to be added to them in time. The list of elements are divided into traditional two-dimensional, plane stress shell finite elements, and three-dimensional solid finite elements that contain either modifications or additional terms designed to represent the bending stiffness expected to be found in shell formulations. These particular finite elements are formulated for finite deformation and inelastic material response, and, as such, are not based on some of the elegant formulations that can be found in an elastic, infinitesimal finite element setting. Each shell element is subjected to a series of 12 verification and validation test problems. The underlying purpose of the tests here is to identify the quality of both the spatially discrete finite element gradient operator and the spatially discrete finite element divergence operator. If the derivation of the finite element is proper, the discrete divergence operator is the transpose of the discrete gradient operator. An overall summary is provided from which one can rank, at least in an average sense, how well the individual formulations can be expected to perform in applications encountered year in and year out. A letter grade has been assigned albeit sometimes subjectively for each shell element and each test problem result. The number of A's, B's, C's, et cetera assigned have been totaled, and a grade point average (GPA) has been computed, based on a 4.0-system. These grades, combined with a comparison between the test problems and the application problem, can be used to guide an analyst to select the element with the best shell formulation.

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Model-based computer simulations have revolutionized product development in the last 10 to 15 years. Technologies that have existed for many decades or even centuries have been improved with the aid of computer simulations. Everything from low-tech consumer goods such as detergents, lubricants and light bulb filaments to the most advanced high-tech products such as airplane wings, wireless communication technologies and pharmaceuticals is engineered with the aid of computer simulations today. In this paper, we present a framework for describing computational tools and their application within the context of product engineering. We examine a few cases of product development that integrate numerical computer simulations into the development stage. We will discuss how the simulations were integrated into the development process, what features made the simulations useful, the level of knowledge and experience that was necessary to run meaningful simulations and other details of the process. Based on this discussion, recommendations for the incorporation of simulations and computational tools into product development will be made.