Optimization-based Design for Manufacturing
This report provides detailed documentation of the algorithms that where developed and implemented in the Plato software over the course of the Optimization-based Design for Manufacturing LDRD project.
This report provides detailed documentation of the algorithms that where developed and implemented in the Plato software over the course of the Optimization-based Design for Manufacturing LDRD project.
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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Conference Proceedings of the Society for Experimental Mechanics Series
Engineering designers are responsible for designing parts, components, and systems that perform required functions in their intended field environment. To determine if their design will meet its requirements, the engineer must run a qualification test. For shock and vibration environments, the component or unit under test is connected to a shaker table or shock apparatus and is imparted with a load to simulate the mechanical stress from vibration. A difficulty in this approach is when the stresses in the unit under test cannot be generated by a fixed base boundary condition. A fixed base boundary condition is the approximate boundary condition when the unit under test is affixed to a stiff test fixture and shaker table. To aid in correcting for this error, a flexible fixture needs to be designed to account for the stresses that the unit under test will experience in the field. This paper will use topology optimization to design a test fixture that will minimize the difference between the mechanical impedance of the next level of assembly and the test fixture. The optimized fixture will be compared to the rigid fixture with respect to the test’s ability to produce the field stresses.
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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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Scripta Materialia
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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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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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.
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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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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Proceedings - ASPE 2015 Spring Topical Meeting: Achieving Precision Tolerances in Additive Manufacturing
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