Engineering Commons^™

Deep Reinforcement Learning For The Design Of Structural Topologies, Nathan Brown

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Advances in machine learning algorithms and increased computational efficiencies have given engineers new capabilities and tools for engineering design. The presented work investigates using deep reinforcement learning (DRL), a subset of deep machine learning that teaches an agent to complete a task through accumulating experiences in an interactive environment, to design 2D structural topologies. Three unique structural topology design problems are investigated to validate DRL as a practical design automation tool to produce high-performing designs in structural topology domains.

The first design problem attempts to find a gradient-free alternative to solving the compliance minimization topology optimization problem. In the proposed …

Atomistic And Mesoscale Modeling Of Microstructure Development During Solid-State Sintering, Omar Hussein

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Interfaces are ubiquitous in materials systems, and they influence the processing and properties of nearly all engineering and functional materials. Examples include grain boundaries (GBs) in polycrystalline materials, free surfaces in nanoparticles, and phase boundaries in multiphase materials. Therefore, understanding and controlling interfacial processes is a key aspect of materials design and discovery efforts.

Recent developments in advanced manufacturing and synthesis techniques have enabled the fabrication of materials architectures with intricate nanoscale features. Of particular interest is solid-state sintering, known for creating complex and high-precision geometries with controlled microstructures. While sintering science has been the subject of active research, very …

Atomistic And Mesoscale Modeling Of Microstructure Development During Solid-State Sintering, Omar Marwan Isa Hussein

All Dissertations

Interfaces are ubiquitous in materials systems, and they influence the processing and properties of nearly all engineering and functional materials. Examples include grain boundaries (GBs) in polycrystalline materials, free surfaces in nanoparticles, and phase boundaries in multiphase materials. Therefore, understanding and controlling interfacial processes is a key aspect of materials design and discovery efforts. Recent developments in advanced manufacturing and synthesis techniques have enabled the fabrication of materials architectures with intricate nanoscale features. Of particular interest is solid-state sintering, known for creating complex and high-precision geometries with controlled microstructures. While sintering science has been the subject of active research, very …

Design Of Meta-Materials Outside The Homogenization Limit Using Multiscale Analysis And Topology Optimization, Christopher Czech

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The field of meta-materials engineering has largely expanded mechanical design possibilities over the last two decades; some notable design advances include the systematic engineering of negative Poisson's ratio materials and functionally graded materials, materials designed for optimal electronic and thermo-mechanical performances, and the design of materials under uncertainty. With these innovations, the systematic engineering of materials for design-specific uses is becoming more common in industrial and military uses. The motivation for this body of research is the design of the shear beam for a non-pneumatic wheel. Previously, a design optimization of a finite element model of the non-pneumatic wheel was …