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Concurrent Shape and Topology Optimization

Robbins, Joshua; Alberdi, Ryan; Clark, Brett W.

The typical topology optimization workflow uses a design domain that does not change during the optimization process. Consequently, features of the design domain, such as the location of loads and constraints, must be determined in advance and are not optimizable. A method is proposed herein that allows the design domain to be optimized along with the topology. This approach uses topology and shape derivatives to guide nested optimizers to the optimal topology and design domain. The details of the method are discussed, and examples are provided that demonstrate the utility of this approach.

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TYPE SAND Report YEAR 2021
DOIOSTI

Scalable Geometric Modeler for Overlap Detection and Resolution (ASC IC L2 Milestone 7181 FY2020 Final Review)

Clark, Brett W.; Foulk, James W.; Moore, Jacquelyn R.; Kensek, Ronald P.; Hoffman, Edward L.; Ibanez-Granados, Daniel A.

The final review for the FY20 Advanced Simulation and Computing (ASC) Integrated Codes (IC) L2 Milestone #7181 was conducted on August 31, 2020 at Sandia National Laboratories in Albuquerque, New Mexico. The review panel unanimously agreed that the milestone has been successfully completed. Roshan Quadros (1543) led the milestone team and various members from the team presented the results. The review panel was comprised of staff from Sandia National Laboratories Albuquerque and California that are involved with computational engineering modeling and analysis. The panel consisted of experts in the fields of solid modeling, discretization, meshing, simulation workflows, and computational analysis including personnel Brett Clark (1543, Chair); Jay Foulk (8363); Jackie Moore (1553); Ron Kensek (1341); Ed Hoffman (8753); Dan Ibanez (1443). The presentation documented the technical approach of the team and summarized the results with sufficient detail to demonstrate both the value and the completion of the milestone. A separate SAND report was also generated with more detail to supplement the presentation. The purpose of the milestone was to advance capabilities for automatically finding, displaying, and resolving geometric overlaps in CAD models.

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TYPE Other Report YEAR 2020
DOIOSTI

Improve Replication of In-service Mechanical Environments

Schoenherr, Tyler F.; Clark, Brett W.; Coffin, Peter

Structural dynamic testing is a common method for determining if the design of a component of a system will mechanically fail when deployed into its field environment. To satisfy the test's goal, the mechanical stresses must be replicated. Structural dynamic testing is commonly executed on a shaker table or a shock apparatus such as a drop table or a resonant plate. These apparatus impart a force or load on the component through a test fixture that connects the unit under test to the apparatus. Because the test fixture is directly connected to the unit under test, the fixture modifies the structural dynamics of the system, thus varying the locations and relative levels of stress on the unit under test. This may lead to a false positive or negative indication if the unit under test will fail in its field environment depending on the environment and the test fixture. This body of research utilizes topology optimization using the Plato software to design a test fixture that attaches to the unit under test that matches the dynamic impedance of the next level of assembly. The optimization's objective function is the difference between the field configuration and the laboratory configuration's frequency response functions. It was found that this objective function had many local minima and posed difficulties in converging to an acceptable solution. A case study is presented that uses this objective function and although the results are not perfect, they are quantifiably better than the current method of using a sufficiently stiff fixture.

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TYPE SAND Report YEAR 2018
DOIOSTI

Additive manufacturing: Toward holistic design

Scripta Materialia

Jared, Bradley H.; Valentin, Miguel A.; Beghini, Lauren L.; Boyce, Brad L.; Clark, Brett W.; Cook, Adam; Kaehr, Bryan J.; Robbins, Joshua

Additive manufacturing offers unprecedented opportunities to design complex structures optimized for performance envelopes inaccessible under conventional manufacturing constraints. Additive processes also promote realization of engineered materials with microstructures and properties that are impossible via traditional synthesis techniques. Enthused by these capabilities, optimization design tools have experienced a recent revival. The current capabilities of additive processes and optimization tools are summarized briefly, while an emerging opportunity is discussed to achieve a holistic design paradigm whereby computational tools are integrated with stochastic process and material awareness to enable the concurrent optimization of design topologies, material constructs and fabrication processes.

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TYPE Journal Article YEAR 2017
DOIOSTIScopus

CUBIT Geometry and Mesh Generation Toolkit 15.2 User Documentation

Blacker, Teddy D.; Owen, Steven J.; Staten, Matthew L.; Quadros, William; Hanks, Byron; Clark, Brett W.; Meyers, Ray J.; Ernst, Corey; Merkley, Karl; Morris, Randy; Mcbride, Corey; Stimpson, Clinton; Plooster, Michael; Showman, Sam

Welcome to CUBIT, the Sandia National Laboratory automated mesh generation toolkit. CUBIT is a full-featured software toolkit for robust generation of two- and three-dimensional finite element meshes (grids) and geometry preparation. Its main goal is to reduce the time to generate meshes, particularly large hex meshes of complicated, interlocking assemblies. It is a solidmodeler based preprocessor that meshes volumes and surfaces for finite element analysis.

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TYPE Other Report YEAR 2016
DOIOSTI

CUBIT: Geometry and Mesh Generation Toolkit (15.1 User Documentation)

Blacker, Teddy D.; Owen, Steven J.; Staten, Matthew L.; Quadros, William; Hanks, Byron; Clark, Brett W.; Meyers, Ray J.; Ernst, Corey; Merkley, Karl; Morris, Randy; Mcbride, Corey; Stimpson, Clinton J.; Plooster, Michael; Showman, Sam

CUBIT is a full-featured software toolkit for robust generation of two- and three-dimensional finite element meshes (grids) and geometry preparation. Its main goal is to reduce the time to generate meshes, particularly large hex meshes of complicated, interlocking assemblies. It is a solid-modeler based preprocessor that meshes volumes and surfaces for finite element analysis. Mesh generation algorithms include quadrilateral and triangular paving, 2D and 3D mapping, hex sweeping and multi-sweeping, tetrahedral meshing, and various special purpose primitives. CUBIT contains many algorithms for controlling and automating much of the meshing process, such as automatic scheme selection, interval matching, sweep grouping, and also includes state-of-the-art smoothing algorithms.

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TYPE Other Report YEAR 2016
DOIOSTI

Topology Optimization of Cellular Structure

Additive manufacturing

Robbins, Joshua; Owen, Steven J.; Clark, Brett W.; Voth, Thomas E.

This paper presents an end-to-end design process for compliance minimization based topological optimization of cellular structures through to the realization of a final printed product. Homogenization is used to derive properties representative of these structures through direct numerical simulation of unit cell models of the underlying periodic structure. The resulting homogenized properties are then used assuming uniform distribution of the cellular structure to compute the final macro-scale structure. A new method is then presented for generating an STL representation of the final optimized part that is suitable for printing on typical industrial machines. Quite fine cellular structures are shown to be possible using this method as compared to other approaches that use nurb based CAD representations of the geometry. Finally, results are presented that illustrate the fine-scale stresses developed in the final macro-scale optimized part and suggestions are made as to incorporate these features into the overall optimization process.

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TYPE Journal Article YEAR 2015
OSTI

Solving the Big Data (BD) Problem in Advanced Manufacturing (Subcategory for work done at Georgia Tech. Study Process and Design Factors for Additive Manufacturing Improvement)

Clark, Brett W.; Diaz, Kimberly A.; Ochiobi, Chinaza D.; Paynabar, Kamran

3D printing originally known as additive manufacturing is a process of making 3 dimensional solid objects from a CAD file. This ground breaking technology is widely used for industrial and biomedical purposes such as building objects, tools, body parts and cosmetics. An important benefit of 3D printing is the cost reduction and manufacturing flexibility; complex parts are built at the fraction of the price. However, layer by layer printing of complex shapes adds error due to the surface roughness. Any such error results in poor quality products with inaccurate dimensions. The main purpose of this research is to measure the amount of printing errors for parts with different geometric shapes and to analyze them for finding optimal printing settings to minimize the error. We use a Design of Experiments framework, and focus on studying parts with cone and ellipsoid shapes. We found that the orientation and the shape of geometric shapes have significant effect on the printing error. From our analysis, we also determined the optimal orientation that gives the least printing error.

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TYPE Other Report YEAR 2015
DOIOSTI

Removing small features with real CAD operations

Proceedings of the 16th International Meshing Roundtable, IMR 2007

Clark, Brett W.

Preparing Computer Aided Design models for successful mesh generation continues to be a crucial part of the design to analysis process. A common problem in CAD models is features that are very small compared to the desired mesh size. Small features exist for a variety of reasons and can require an excessive amount of elements or inhibit mesh generation all together. Many of the tools for removing small features modify only the topology of the model (often in a secondary topological representation of the model) leaving the underlying geometry as is. The availability of tools that actually modify the topology and underlying geometry in the boundary representation (B-rep) model is much more limited regardless of the inherent advantages of this approach. This paper presents a process for removing small featrues from a B-rep model using almost solely functionality provided by the underlying solid modeling kernel. The process cuts out the old topology and reconstructs new topology and geometry to close the volume. The process is quite general and can be applied to complex configurations of unwanted topology.

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TYPE Conference YEAR 2008
OSTIScopus
66 Results
66 Results