GOALI/Collaborative Research: Topology Optimization for Additively Manufactured Metal Castings
GOALI/Collaborative Research: Topology Optimization for Additively Manufactured Metal Castings
批准号:
1462089
负责人:
Christopher Williams
金额:
$24.27万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-06-01 至 2019-05-31
中文摘要
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英文摘要
This Grant Opportunity for Academic Liaison with Industry (GOALI) Program collaborative research award will develop an integrated design-manufacture framework by coupling topology optimization design methods with additive manufacturing processes. Topology optimization is a systematic, computational tool for designing high performance devices and components. Topology-optimized designs, however, are often geometrically complex and thus difficult, if not impossible, to fabricate with traditional manufacturing processes. Additive manufacturing is arising as a potential means for overcoming this obstacle, as its layer-wise fabrication approach enables the creation of geometrically complex components without negatively affecting production cost or throughput. However, despite this natural synergy, additive manufacturing and topology optimization approaches have not yet been integrated into a comprehensive design-manufacture framework. Without this integration, topology-optimized designs may be incompatible with additive manufacturing and require tedious and potentially deleterious post-process alterations to conform to manufacturing restrictions. The primary goal of this research is thus to optimize parts for as-built conditions by (i) identifying, characterizing, and understanding the aspects of an additive manufacturing process that impose constraints on part geometry and (ii) advancing topology optimization methods to incorporate these constraints. Thus the work will substantially improve both the efficiency of the engineering design process and the efficacy of the resultant engineered artifacts. The integrated design-manufacture optimization capability will be of considerable benefit to a broad range of industries, including automotive, agricultural, and aerospace where (for example) the realization of lightweight large-scale components could lead to substantial energy savings. The multidisciplinary research team will also create integrated educational modules and provide research opportunities for underrepresented groups.As manufacturing constraints are specific to each additive manufacturing process, the research team will focus on designing components to be manufactured via the 3D sand printing process in which metal parts are made by casting molten metal into 3D printed sand molds. The team will identify, characterize, and quantify the aspects of this additive manufacturing and metal casting process chain that impose constraints on component geometry and mathematically incorporate these constraints into the topology optimization method. The topology optimization approach will have roots in projection-based algorithms where manufacturing design variables are coupled to the physical and analysis spaces to naturally achieve manufacturability. Maintaining rigor in the design framework will facilitate extension to other
materials and additive manufacturing processes. The team will design, fabricate, and experimentally test an engineered component for a case-study (provided by the industrial partner) to validate the developed design-manufacture framework.
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Constructions and properties of p-adic L-functions for GL(n)
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Computational Design of Graphene-Based Materials for Challenging Nuclear Decommissioning Applications
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UNS: Selective Catalytic Conversion of Syngas-Derived Dimethyl Oxalate to Ethylene Glycol: Mechanistic Insights from In-Situ Surface Vibrational Spectroscopy
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EAGER/Collaborative Research/Cybermanufacturing: Just Make It: Integrating Cybermanufacturing into Design Studios to Enable Innovation
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财政年份:2015
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Collaborative Research/Workshop: Educational Needs and Opportunities in Additive Manufacturing; Arlington, Virginia; April 10-11, 2014
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IGERT: Functional Nanomaterials for Sustainable Energy Solutions
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批准号:1250052
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资助金额:$300.0万
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财政年份:2013
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CAREER: Additive Manufacture of Copper Cellular Materials
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财政年份:2013
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RET Site: Innovation-based Manufacturing
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批准号:1200221
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Advancing Personalized Engineering Learning Via an Adaptive Concept Map
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BGP Capacity Building Grant Proposal
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REU SITE: Sustainable Energy in Chemical Engineering
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Carbon Dioxide and Water Flux Responses to Extreme Weather and Climate Anomalies: A Fluxnet Synthesis
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海外基金