Computer-Aided Engineering and Design Commons^™

Universal Systems Simulation Via Constraint Hypergraphs With Applications To Digital Twins, John Morris

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The characterization of systems encompasses a variety of modeling frameworks designed to capture specific behaviors and components of various system domains. Whatever the framework, the core elements of a system representation are the information of the system and a description of how that information is related. The relations in deterministic systems are functions, which, when composed to form executable processes, can be used to simulate system data. A declarative modeling framework is one that encodes mechanisms for preparing these simulations within the model structure, allowing an external agent to form the execution processes required for a given context. To date, …

Neural Operator And Physics-Informed Deep Learning Approaches For Inverse Design Of Composites And Manufacturing Processes, Minglei Lu

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In this dissertation, artificial intelligence (AI) models are designed and used to accelerate inverse design of composites and manufacturing processes. The critical bottlenecks in machine learning (ML) including data availability, data quality, model generalization and adaptation, interpretability, physical consistency, and the ’black box’ nature of models for the inverse design are addressed. And the proposed AI models are tested under different engineering scenarios. Firstly, a fast deep neural operator (DNO) structure was developed to significantly reduce training time. This model was tested in the context of additive manufacturing, a transformative industrial technology that allows for the creation of materials with …

An Efficient Computational Frameworks For Design And Analysis Of Metamaterials, Raj Pradip Khawale

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Advancement in additive manufacturing helps in building artificial lattice structures with unique properties that are not available in naturally occurring materials or in continuum structures. Specifically, beam-based lattices are well known for producing lightweight structures with very high strength, auxetic behavior, and energy absorption capabilities. In recent years, numerous research studies have been conducted on generating algorithms and frameworks to obtain unusual properties based on the variation in the cell geometry and material properties. However, the exploration of the full design space is hampered in practice primarily due to restrictions on cell tiling variation. Additionally, the lattices are very intricate, …

Linear And Nonlinear Topology Optimization With Morphing Beam Networks, Andrew S. Montalbano

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Topology optimization (TO) is an engineering design discipline dedicated to optimizing material distribution within a given domain. In traditional gradient-based topology optimization, the solid domain is discretized into small volumetric elements. Using finite element analysis (FEA) of the structure, the gradient of the objective function with respect to the design variables (the pseudo densities) is computed, and these design variables are updated iteratively until convergence is achieved. Although gradient-based TO methods are well-established, sensitivity analyses of objective functions and constraints can be both mathematically complex and computationally intensive. The nonconvex nature of most TO problems often complicates efficient convergence. Furthermore, …

A Manufacturing-To-Response Pathway For Manufacturing Optimization Of Carbon Fiber Reinforced Polymer Composite Structures, Madhura Limaye

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Over the past decade, there has been an increased adoption of thermoplastic and thermoset based continuous carbon fiber reinforced polymer (CFRP) composites for structural applications in several industries. Among the different manufacturing methods, thermoforming process for thermoplastic based continuous CFRP’s offer a major advantage in reducing cycle times for large scale productions. Similarly, out-of-autoclave curing process for thermoset based continuous CFRP’s using heated tooling enables production of large composite structures. However, these manufacturing processes can have a significant impact on the structural performance of parts by inducing undesirable effects. These effects include inhomogeneous fiber orientations, thickness variations, and residual stresses …

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 …

Multiscale Topology Optimization With A Strong Dependence On Complementary Energy, Dustin Dean Bielecki

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A discrete approach introduces a novel deep learning approach for generating fine resolution structures that preserve all the information from the topology optimization (TO). The proposed approach utilizes neural networks (NNs) that map the desired engineering properties to seed for determining optimized structure. This framework relies on utilizing parameters such as density and nodal deflections to predict optimized topologies. A three-stage NN framework is employed for the discrete approach to reduce computational runtime while maintaining physics constraints.

A continuous representation that uses complementary energy (CE) methods to solve a representative element's homogenized properties consists of an embedded structure that is …

Multiple Heat Exchanger Cooling System For Automotive Applications – Design, Mathematical Modeling, And Experimental Observations, Zaker Syed

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The design of the automotive cooling systems has slowly evolved from engine-driven mechanical to computer-controlled electro-mechanical components. With the addition of computer-controlled variable speed actuators, cooling system architectures have been updated to maximize performance and efficiency. By switching from one large radiator to multiple smaller radiators with individual flow control valves, the heat rejection requirements may be precisely adjusted. The combination of computer regulated thermal management system should reduce power consumption while satisfying temperature control objectives. This research focuses on developing and analyzing a multi-radiator system architecture for implementation in ground transportation applications. The premise is to use a single …

Development Of A Reverse Engineered, Parameterized, And Structurally Validated Computational Model To Identify Design Parameters That Influence American Football Faceguard Performance, William Ferriell

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Traumatic brain injury (TBI) continues to have the greatest incidence among athletes participating in American football. The headgear design research community has focused on developing accurate computational and experimental analysis techniques to better assess the ability of headgear technology to attenuate impacts and protect athletes from TBI. Despite efforts to innovate the headgear system, minimal progress has been made to innovate the faceguard. Although the faceguard is not the primary component of the headgear system that contributes to impact attenuation, faceguard performance metrics, such as weight, structural stiffness, and visual field occlusions, have been linked to athlete safety. To improve …

Characterization Of Friction Element Welding Using Finite Element Modeling, Ankit Varma

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Friction element welding (FEW) has been advocated as a solution to weld different materials together, with the ability to join high-strength materials for a range of thicknesses with low input energy and a short processing time. This work develops a coupled thermal-mechanical finite element model to better understand the physical mechanisms involved in the process and to predict temperature and material flow during the process. Furthermore, microstructural analysis is performed for the steel layer using a scanning electron microscope and Vickers microhardness tester to understand the variation in its grain structure and hardness. Results from the finite element model and …

Mechanical Interfacial Locking And Multiscale Modeling Of Reinforced Thermoplastic Composites For Structural Applications, Anmol Kothari

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The ever-growing pressure of reducing the adverse impact of transportation systems on environment has pushed industries towards fuel-efficient and sustainable solutions. While several approaches have been used to improve fuel efficiency, the light-weighting of structural components has proven broadly effective. In this regard, reinforced thermoplastic composites (RTPC), owing to their high recyclability, higher impact strength and fast cycle times, have become competitive candidates at an industrial scale. However, to implement RTPC toward large scale structural applications several challenges pertaining to material design and manufacturing effects need to be addressed. To this end, a computational study is carried out to address …