Applied Mechanics Commons^™

The Generation Of A Physics Informed Machine Learning Model To Predict Defect Evolution In Materials & On The Thermally Activated Regime Of Dislocation Motion: A Simulation Driven Study On The Mechanical Behavior Of Crystals, Liam Myhill

All Theses

Line defects in crystals, known as dislocations, govern the mechanisms of plastic deformation at the micro-meso scale. The study of dislocations has proliferated the field of materials science and engineering for since the 1950’s, and modern studies show increasing utilization of computational methods to model the evolution of line defects in material systems. In keeping with modern research practice, the studies herewith demonstrate the use of advanced computing to generate models which can be used to better understand the behaviors of dislocations within crystal matrices. An advanced high-throughput model for a physically informed machine learning graph neural network (PIML-GNN) is …

Cfrp Delamination Density Propagation Analysis By Magnetostriction Theory, Brandon Eugene Williams

All Dissertations

While Carbon Fiber Reinforced Polymers (CFRPs) have exceptional mechanical properties concerning their overall weight, their failure profile in demanding high-stress environments raises reliability concerns in structural applications. Two crucial limiting factors in CFRP reliability are low-strain material degradation and low fracture toughness. Due to CFRP’s low strain degradation characteristics, a wide variety of interlaminar damage can be sustained without any appreciable change to the physical structure itself. This damage suffered by the energy transfer from high- stress levels appears in the form of microporosity, crazes, microcracks, and delamination in the matrix material before any severe laminate damage is observed. This …

Physics-Based Machine Learning Methods For Control And Sensing In Fish-Like Robots, Colin Rodwell

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Underwater robots are important for the construction and maintenance of underwater infrastructure, underwater resource extraction, and defense. However, they currently fall far behind biological swimmers such as fish in agility, efficiency, and sensing capabilities. As a result, mimicking the capabilities of biological swimmers has become an area of significant research interest. In this work, we focus specifically on improving the control and sensing capabilities of fish-like robots.

Our control work focuses on using the Chaplygin sleigh, a two-dimensional nonholonomic system which has been used to model fish-like swimming, as part of a curriculum to train a reinforcement learning agent to …

Characterization Of Mechanically Recycled Polylactic Acid (Pla) Filament For 3d-Printing By Evaluating Mechanical, Thermal, And Chemical Properties And Process Performance, Mahsa Shabani Samghabady

All Theses

Polylactic acid (PLA) is a biopolymer made from renewable resources such as sugar and corn. PLA filament is a popular material used in Fused Deposition Modeling (FDM) 3D-printing. While this material has many advantages, all the failed parts, support structures, rafts, nozzle tests, and the many prototype iterations during the 3D-printing process contribute to the plastic pollution and release of greenhouse gases. Although PLA is biodegradable, it can take years to degrade in landfills. Instead of throwing away PLA waste and buying new filaments, PLA can be recycled. Amongst the different recycling technologies, mechanical recycling is the most environmentally friendly. …

Investigation Of Fatigue Response With Analytical And Machine Learning Models And Hygroscopic Analysis Of Asymmetric Bistable Cfrp Composites, Shoab Ahmed Chowdhury

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Asymmetric bistable carbon fibre reinforced plastic (CFRP) composites enable a broad range of applications as they can sustain multiple stable configurations and have small snap-through load requirements. These unique features, coupled with their light strength-to-weight and stiffness-to-weight ratios, have made them preferred options for multifunctional systems. This study investigates the fatigue and hygroscopic response of 2-ply, [0/90] bistable CFRP laminates and proposes predictive modeling approaches for improved performance.

While previous studies widely researched and documented the fatigue of general composites in axial loading, fatigue analysis of asymmetric bistable composites in the out-of-plane snap-through direction is inadequate. This study performs fatigue …

A Predictive Analysis Of The Influence Of Thickness And Length On The Curvature Of Square Bistable Carbon Fiber Reinforced Composite Laminates, Stephan Terry

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This thesis presents a predictive analysis of the stability of square bistable carbon fiber reinforced composite laminates under various loading conditions. The stability of these laminates is essential to their performance and longevity and is influenced by factors such as thickness and length. Analytical and numerical techniques are used to model the behavior of these laminates, and experimental tests are conducted to validate the models. The findings of this research have implications for the design and optimization of square bistable carbon fiber reinforced composites.

The study investigates the relationships between the side length and thickness of square laminates for bistability. …

Modeling, Control And Estimation Of Reconfigurable Cable Driven Parallel Robots, Adhiti Raman Thothathri

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The motivation for this thesis was to develop a cable-driven parallel robot (CDPR) as part of a two-part robotic device for concrete 3D printing. This research addresses specific research questions in this domain, chiefly, to present advantages offered by the addition of kinematic redundancies to CDPRs. Due to the natural actuation redundancy present in a fully constrained CDPR, the addition of internal mobility offers complex challenges in modeling and control that are not often encountered in literature.

This work presents a systematic analysis of modeling such kinematic redundancies through the application of reciprocal screw theory (RST) and Lie algebra while …

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

All Dissertations

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 Objective Function Optimization And Trade Space Analysis, Yifan Xu

All Theses

Optimization can assist in obtaining the best possible solution to a design problem by varying related variables under given constraints. It can be applied in many practical applications, including engineering, during the design process. The design time can be further reduced by the application of automated optimization methods. Since the required resource and desired benefit can be translated to a function of variables, optimization can be viewed as the process of finding the variable values to reach the function maxima or minima. A Multiple Objective Optimization (MOO) problem is when there is more than one desired function that needs to …

Tunable Filtration Of Particles During Dip-Coating, Connor Copeland

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When a solid substrate is withdrawn from a liquid bath a thin coating is deposited whose thickness is given by the Landau-Levich-Derjaguin (LLD) law. We perform an experimental study of dip coating of particle suspensions showing that particles of a given size can become entrained in the meniscus by the competition between viscous and surface tension forces. This is called capillary filtration and can be used as a tunable dynamic filter. For single particle suspensions, filtration can be in terms of either clumps or single particles, with the relevant entrainment points depending upon the rheology of the working fluid, either …

Creep Behavior Of A Ti-Based Multi-Principal Element Alloy, Benjamin Elbrecht

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Abstract

The understanding of microstructural damage mechanisms is the foundation of better understanding existing materials and future material development. There are significant challenges to measuring these damage mechanisms in-situ as continuous observation of the state of the microstructure is difficult or impossible for many experimental setups. This thesis presents a method for measuring grain boundary sliding (GBS) and local strain concentrations in-situ via a Heaviside function based algorithm. GBS is the shearing of two grains along their shared grain boundary and is a common damage mechanism in creep which presents as a discontinuity that can be measured with a Heaviside …

Examining The Different Snap-Through Characteristics Of Bistable Cfrp Composite Laminates, Vishrut Deshpande

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Bistable carbon fiber composites, whose bistability arises from having asymmetric fiber layouts in different layers, have shown immense potential for use in shape morphing and adaptive structure applications. While many studies in this field focus on these composite laminates’ external shapes at the two stable states, their snap-through behavior of shifting from one stable shape to the other remains a critical aspect to be investigated in complete detail. Moreover, symmetric loading conditions have been extensively studied based on the classical lamination theory, but the asymmetric loading conditions received far less attention. Therefore, this study examines an asymmetric, localized point load …

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 …

A Manufacturing-To-Response Pathway For Formed 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 …