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Understanding plasticity and fracture in aluminum alloys and their composites by 3D X-ray synchrotron tomography and microdiffraction

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Aluminum alloys and their composites are attractive materials for applications requiring high strength-to-weight ratios and reasonable cost. Many of these applications, such as those in the aerospace industry, undergo fatigue loading. An understanding of the microstructural damage that occurs in

Aluminum alloys and their composites are attractive materials for applications requiring high strength-to-weight ratios and reasonable cost. Many of these applications, such as those in the aerospace industry, undergo fatigue loading. An understanding of the microstructural damage that occurs in these materials is critical in assessing their fatigue resistance. Two distinct experimental studies were performed to further the understanding of fatigue damage mechanisms in aluminum alloys and their composites, specifically fracture and plasticity. Fatigue resistance of metal matrix composites (MMCs) depends on many aspects of composite microstructure. Fatigue crack growth behavior is particularly dependent on the reinforcement characteristics and matrix microstructure. The goal of this work was to obtain a fundamental understanding of fatigue crack growth behavior in SiC particle-reinforced 2080 Al alloy composites. In situ X-ray synchrotron tomography was performed on two samples at low (R=0.1) and at high (R=0.6) R-ratios. The resulting reconstructed images were used to obtain three-dimensional (3D) rendering of the particles and fatigue crack. Behaviors of the particles and crack, as well as their interaction, were analyzed and quantified. Four-dimensional (4D) visual representations were constructed to aid in the overall understanding of damage evolution. During fatigue crack growth in ductile materials, a plastic zone is created in the region surrounding the crack tip. Knowledge of the plastic zone is important for the understanding of fatigue crack formation as well as subsequent growth behavior. The goal of this work was to quantify the 3D size and shape of the plastic zone in 7075 Al alloys. X-ray synchrotron tomography and Laue microdiffraction were used to non-destructively characterize the volume surrounding a fatigue crack tip. The precise 3D crack profile was segmented from the reconstructed tomography data. Depth-resolved Laue patterns were obtained using differential-aperture X-ray structural microscopy (DAXM), from which peak-broadening characteristics were quantified. Plasticity, as determined by the broadening of diffracted peaks, was mapped in 3D. Two-dimensional (2D) maps of plasticity were directly compared to the corresponding tomography slices. A 3D representation of the plastic zone surrounding the fatigue crack was generated by superimposing the mapped plasticity on the 3D crack profile.

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2014

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Structural characteristics and applications of hard-particle packings via event-driven molecular dynamics simulations

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In this dissertation, the results of our comprehensive computational studies of disordered jammed (i.e., mechanically stable) packings of hard particles are presented, including the family of superdisks in 2D and ellipsoids in 3D Euclidean space. Following a very brief introduction

In this dissertation, the results of our comprehensive computational studies of disordered jammed (i.e., mechanically stable) packings of hard particles are presented, including the family of superdisks in 2D and ellipsoids in 3D Euclidean space. Following a very brief introduction to the hard-particle systems, the event driven molecular dynamics (EDMD) employed to generate the packing ensembles will be discussed. A large number of 2D packing configurations of superdisks are subsequently analyzed, through which a relatively accurate theoretical scheme for packing-fraction prediction based on local particle contact configurations is proposed and validated via additional numerical simulations. Moreover, the studies on binary ellipsoid packing in 3D are briefly discussed and the effects of different geometrical parameters on the final packing fraction are analyzed.

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2014

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A novel nonlocal lattice particle framework for modeling of solids

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Fracture phenomena have been extensively studied in the last several decades. Continuum mechanics-based approaches, such as finite element methods and extended finite element methods, are widely used for fracture simulation. One well-known issue of these approaches is the stress singularity

Fracture phenomena have been extensively studied in the last several decades. Continuum mechanics-based approaches, such as finite element methods and extended finite element methods, are widely used for fracture simulation. One well-known issue of these approaches is the stress singularity resulted from the spatial discontinuity at the crack tip/front. The requirement of guiding criteria for various cracking behaviors, such as initiation, propagation, and branching, also poses some challenges. Comparing to the continuum based formulation, the discrete approaches, such as lattice spring method, discrete element method, and peridynamics, have certain advantages when modeling various fracture problems due to their intrinsic characteristics in modeling discontinuities.

A novel, alternative, and systematic framework based on a nonlocal lattice particle model is proposed in this study. The uniqueness of the proposed model is the inclusion of both pair-wise local and multi-body nonlocal potentials in the formulation. First, the basic ideas of the proposed framework for 2D isotropic solid are presented. Derivations for triangular and square lattice structure are discussed in detail. Both mechanical deformation and fracture process are simulated and model verification and validation are performed with existing analytical solutions and experimental observations. Following this, the extension to general 3D isotropic solids based on the proposed local and nonlocal potentials is given. Three cubic lattice structures are discussed in detail. Failure predictions using the 3D simulation are compared with experimental testing results and very good agreement is observed. Next, a lattice rotation scheme is proposed to account for the material orientation in modeling anisotropic solids. The consistency and difference compared to the classical material tangent stiffness transformation method are discussed in detail. The implicit and explicit solution methods for the proposed lattice particle model are also discussed. Finally, some conclusions and discussions based on the current study are drawn at the end.

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2015

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Probabilistic fatigue damage localization at unknown temperatures using guided wave methods

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This research examines the current challenges of using Lamb wave interrogation methods to localize fatigue crack damage in a complex metallic structural component subjected to unknown temperatures. The goal of this work is to improve damage localization results for a

This research examines the current challenges of using Lamb wave interrogation methods to localize fatigue crack damage in a complex metallic structural component subjected to unknown temperatures. The goal of this work is to improve damage localization results for a structural component interrogated at an unknown temperature, by developing a probabilistic and reference-free framework for estimating Lamb wave velocities and the damage location. The methodology for damage localization at unknown temperatures includes the following key elements: i) a model that can describe the change in Lamb wave velocities with temperature; ii) the extension of an advanced time-frequency based signal processing technique for enhanced time-of-flight feature extraction from a dispersive signal; iii) the development of a Bayesian damage localization framework incorporating data association and sensor fusion. The technique requires no additional transducers to be installed on a structure, and allows for the estimation of both the temperature and the wave velocity in the component. Additionally, the framework of the algorithm allows it to function completely in an unsupervised manner by probabilistically accounting for all measurement origin uncertainty. The novel algorithm was experimentally validated using an aluminum lug joint with a growing fatigue crack. The lug joint was interrogated using piezoelectric transducers at multiple fatigue crack lengths, and at temperatures between 20°C and 80°C. The results showed that the algorithm could accurately predict the temperature and wave speed of the lug joint. The localization results for the fatigue damage were found to correlate well with the true locations at long crack lengths, but loss of accuracy was observed in localizing small cracks due to time-of-flight measurement errors. To validate the algorithm across a wider range of temperatures the electromechanically coupled LISA/SIM model was used to simulate the effects of temperatures. The numerical results showed that this approach would be capable of experimentally estimating the temperature and velocity in the lug joint for temperatures from -60°C to 150°C. The velocity estimation algorithm was found to significantly increase the accuracy of localization at temperatures above 120°C when error due to incorrect velocity selection begins to outweigh the error due to time-of-flight measurements.

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2013

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Nonlinear dynamics of uncertain multi-joint structures

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The present investigation is part of a long-term effort focused on the development of a methodology for the computationally efficient prediction of the dynamic response of structures with multiple joints. The first part of this thesis reports on the dynamic

The present investigation is part of a long-term effort focused on the development of a methodology for the computationally efficient prediction of the dynamic response of structures with multiple joints. The first part of this thesis reports on the dynamic response of nominally identical beams with a single lap joint (“Brake-Reuss” beam). The observed impact responses at different levels clearly demonstrate the occurrence of both micro- and macro-slip, which are reflected by increased damping and a lowering of natural frequencies. Significant beam-to-beam variability of impact responses is also observed.

Based on these experimental results, a deterministic 4-parameter Iwan model of the joint was developed. These parameters were randomized following a previous investigation. The randomness in the impact response predicted from this uncertain model was assessed in a Monte Carlo format through a series of time integrations of the response and found to be consistent with the experimental results.

The availability of an uncertain computational model for the Brake-Reuss beam provides a starting point to analyze and model the response of multi-joint structures in the presence of uncertainty/variability. To this end, a 4-beam frame was designed that is composed of three identical Brake-Reuss beams and a fourth, stretched one. The response of that structure to impact was computed and several cases were identified.

The presence of uncertainty implies that an exact prediction of the response of a particular frame cannot be achieved. Rather, the response can only be predicted to lie within a band reflecting the level of uncertainty. In this perspective, the computational model adopted for the frame is only required to provide a good estimate of this uncertainty band. Equivalently, a relaxation of the model complexity, i.e., the introduction of epistemic uncertainty, can be performed as long as it does not affect significantly the uncertainty band of the predictions. Such an approach, which holds significant promise for the efficient computational of the response of structures with many uncertain joints, is assessed here by replacing some joints by linear spring elements. It is found that this simplification of the model is often acceptable at lower excitation/response levels.

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2016

A study of heating and degradation of acrylonitrile-butadiene-styrene/polycarbonate polymer due to ultraviolet lasers illumination during localized pre-deposition heating for fused filament fabrication 3D printing

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With the growing popularity of 3d printing in recreational, research, and commercial enterprises new techniques and processes are being developed to improve the quality of parts created. Even so, the anisotropic properties is still a major hindrance of parts manufactured

With the growing popularity of 3d printing in recreational, research, and commercial enterprises new techniques and processes are being developed to improve the quality of parts created. Even so, the anisotropic properties is still a major hindrance of parts manufactured in this method. The goal is to produce parts that mimic the strength characteristics of a comparable part of the same design and materials created using injection molding. In achieving this goal the production cost can be reduced by eliminating the initial investment needed for the creation of expensive tooling. This initial investment reduction will allow for a wider variant of products in smaller batch runs to be made available. This thesis implements the use of ultraviolet (UV) illumination for an in-process laser local pre-deposition heating (LLPH). By comparing samples with and without the LLPH process it is determined that applied energy that is absorbed by the polymer is converted to an increase in the interlayer temperature, and resulting in an observed increase in tensile strength over the baseline test samples. The increase in interlayer bonding thus can be considered the dominating factor over polymer degradation.

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2017

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Safety Enhanced Designs in UAS Risk Monitoring and Collision Resolution

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Collision-free path planning is also a major challenge in managing unmanned aerial vehicles (UAVs) fleets, especially in uncertain environments. The design of UAV routing policies using multi-agent reinforcement learning has been considered, and propose a Multi-resolution, Multi-agent, Mean-field reinforcement learning

Collision-free path planning is also a major challenge in managing unmanned aerial vehicles (UAVs) fleets, especially in uncertain environments. The design of UAV routing policies using multi-agent reinforcement learning has been considered, and propose a Multi-resolution, Multi-agent, Mean-field reinforcement learning algorithm, named 3M-RL, for flight planning, where multiple vehicles need to avoid collisions with each other while moving towards their destinations. In this system, each UAV makes decisions based on local observations, and does not communicate with other UAVs. The algorithm trains a routing policy using an Actor-Critic neural network with multi-resolution observations, including detailed local information and aggregated global information based on mean-field. The algorithm tackles the curse-of-dimensionality problem in multi-agent reinforcement learning and provides a scalable solution. The proposed algorithm is tested in different complex scenarios in both 2D and 3D space and the simulation results show that 3M-RL result in good routing policies. Also as a compliment, dynamic data communications between UAVs and a control center has also been studied, where the control center needs to monitor the safety state of each UAV in the system in real time, where the transition of risk level is simply considered as a Markov process. Given limited communication bandwidth, it is impossible for the control center to communicate with all UAVs at the same time. A dynamic learning problem with limited communication bandwidth is also discussed in this paper where the objective is to minimize the total information entropy in real-time risk level tracking. The simulations also demonstrate that the algorithm outperforms policies such as a Round & Robin policy.

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2021

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Phase Change Materials in Infrastructural Concrete and Buildings: Material Design and Performance

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Phase change materials (PCMs) are combined sensible-and-latent thermal energy storage materials that can be used to store and dissipate energy in the form of heat. PCMs incorporated into wall-element systems have been well-studied with respect to energy efficiency of building

Phase change materials (PCMs) are combined sensible-and-latent thermal energy storage materials that can be used to store and dissipate energy in the form of heat. PCMs incorporated into wall-element systems have been well-studied with respect to energy efficiency of building envelopes. New applications of PCMs in infrastructural concrete, e.g., for mitigating early-age cracking and freeze-and-thaw induced damage, have also been proposed. Hence, the focus of this dissertation is to develop a detailed understanding of the physic-chemical and thermo-mechanical characteristics of cementitious systems and novel coating systems for wall-elements containing PCM. The initial phase of this work assesses the influence of interface properties and inter-inclusion interactions between microencapsulated PCM, macroencapsulated PCM, and the cementitious matrix. The fact that these inclusions within the composites are by themselves heterogeneous, and contain multiple components necessitate careful application of models to predict the thermal properties. The next phase observes the influence of PCM inclusions on the fracture and fatigue behavior of PCM-cementitious composites. The compliant nature of the inclusion creates less variability in the fatigue life for these composites subjected to cyclic loading. The incorporation of small amounts of PCM is found to slightly improve the fracture properties compared to PCM free cementitious composites. Inelastic deformations at the crack-tip in the direction of crack opening are influenced by the microscale PCM inclusions. After initial laboratory characterization of the microstructure and evaluation of the thermo-mechanical performance of these systems, field scale applicability and performance were evaluated. Wireless temperature and strain sensors for smart monitoring were embedded within a conventional portland cement concrete pavement (PCCP) and a thermal control smart concrete pavement (TCSCP) containing PCM. The TCSCP exhibited enhanced thermal performance over multiple heating and cooling cycles. PCCP showed significant shrinkage behavior as a result of compressive strains in the reinforcement that were twice that of the TCSCP. For building applications, novel PCM-composites coatings were developed to improve and extend the thermal efficiency. These coatings demonstrated a delay in temperature by up to four hours and were found to be more cost-effective than traditional building insulating materials.

The results of this work prove the feasibility of PCMs as a temperature-regulating technology. Not only do PCMs reduce and control the temperature within cementitious systems without affecting the rate of early property development but they can also be used as an auto-adaptive technology capable of improving the thermal performance of building envelopes.

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2018

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Characteristics of distributed cracking for analysis and design of strain hardening cement based composites

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As the demand of sustainable construction materials increases, use of fibers and textiles as partial or full reinforcement in concrete members present a tremendous opportunity. Proper characterization techniques and design guides for hybrid materials are therefore needed. This dissertation presents

As the demand of sustainable construction materials increases, use of fibers and textiles as partial or full reinforcement in concrete members present a tremendous opportunity. Proper characterization techniques and design guides for hybrid materials are therefore needed. This dissertation presents a comprehensive study on serviceability-based design of strain softening and strain hardening materials. Multiple experimental procedures are developed to document the nature of single crack localization and multiple cracking mechanisms in various fiber and fabric reinforced cement-based composites. In addition, strain rate effects on the mechanical properties are examined using a high speed servo-hydraulic tension test equipment.

Significant hardening and degradation parameters such as stiffness, crack spacing, crack width, localized zone size are obtained from tensile tests using digital image correlation (DIC) technique. A tension stiffening model is used to simulate the tensile response that addresses the cracking and localization mechanisms. The model is also modified to simulate the sequential cracking in joint-free slabs on grade reinforced by steel fibers, where the lateral stiffness of slab and grade interface and stress-crack width response are the most important model parameters.

Parametric tensile and compressive material models are used to formulate generalized analytical solutions for flexural behaviors of hybrid reinforced concrete (HRC) that contains both rebars and fibers. Design recommendations on moment capacity, minimum reinforcement ratio etc. are obtained using analytical equations. The role of fiber in reducing the amount of conventional reinforcement is revealed. The approach is extended to T-sections and used to model Ultra High Performance Concrete (UHPC) beams and girders.

The analytical models are extended to structural members subjected to combined axial and bending actions. Analytical equations to address the P-M diagrams are derived. Closed-form equations that generate the interaction diagram of HRC section are presented which may be used in the design of multiple types of applications.

The theoretical models are verified by independent experimental results from literature. Reliability analysis using Monte Carlo simulation (MCS) is conducted for few design problems on ultimate state design. The proposed methodologies enable one to simulate the experiments to obtain material parameters and design structural members using generalized formulations.

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2016

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Modeling Complex Material Systems Using Stochastic Reconstruction and Lattice Particle Simulation

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In this dissertation, three complex material systems including a novel class of hyperuniform composite materials, cellularized collagen gel and low melting point alloy (LMPA) composite are investigated, using statistical pattern characterization, stochastic microstructure reconstruction and micromechanical analysis. In Chapter 1,

In this dissertation, three complex material systems including a novel class of hyperuniform composite materials, cellularized collagen gel and low melting point alloy (LMPA) composite are investigated, using statistical pattern characterization, stochastic microstructure reconstruction and micromechanical analysis. In Chapter 1, an introduction of this report is provided, in which a brief review is made about these three material systems. In Chapter 2, detailed discussion of the statistical morphological descriptors and a stochastic optimization approach for microstructure reconstruction is presented. In Chapter 3, the lattice particle method for micromechanical analysis of complex heterogeneous materials is introduced. In Chapter 4, a new class of hyperuniform heterogeneous material with superior mechanical properties is investigated. In Chapter 5, a bio-material system, i.e., cellularized collagen gel is modeled using correlation functions and stochastic reconstruction to study the collective dynamic behavior of the embed tumor cells. In chapter 6, LMPA soft robotic system is generated by generalizing the correlation functions and the rigidity tunability of this smart composite is discussed. In Chapter 7, a future work plan is presented.

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2018