Fatigue fracture is one of the most common types of mechanical failures seen in structures. Considering that fatigue failures usually initiate on surfaces, it is accepted that surface roughness has a detrimental effect on the fatigue life of components. Irregularities on the surface cause stress concentrations and form nucleation sites for cracks. As surface conditions are not always satisfactory, particularly for additively manufactured components, it is necessary to develop a reliable model for fatigue life estimation considering surface roughness effects and assure structural integrity. This research study focuses on extending a previously developed subcycle fatigue crack growth model to include the effects of surface roughness. Unlike other models that consider surface irregularities as series of cracks, the proposed model is unique in the way that it treats the peaks and valleys of surface texture as a single equivalent notch. First, an equivalent stress concentration factor for the roughness was estimated and introduced into an asymptotic interpolation method for notches. Later, a concept called equivalent initial flaw size was incorporated along with linear elastic fracture mechanics to predict the fatigue life of Ti-6Al-4V alloy with different levels of roughness under uniaxial and multiaxial loading conditions. The predicted results were validated using the available literature data. The developed model can also handle variable amplitude loading conditions, which is suggested for future work.

Applications such as heat exchangers, surface-based cellular structures, rotating blades, and waveguides rely on thin metal walls as crucial constituent elements of the structure. The design freedom enabled by laser powder bed fusion has led to an interest in exploiting this technology to further the performance of these components, many of which retain their as-built surface morphologies on account of their design complexity. However, there is limited understanding of how and why mechanical properties vary by wall thickness for specimens that are additively manufactured and maintain an as-printed surface finish. Critically, the contributions of microstructure and morphology to the mechanical behavior of thin wall laser powder bed fusion structures have yet to be systematically identified and decoupled. This work focuses on elucidating the room temperature quasi-static tensile and high cycle fatigue properties of as-printed, thin-wall Inconel 718 fabricated using laser powder bed fusion, with the aim of addressing this critical gap in the literature. Wall thicknesses studied range from 0.3 - 2.0 mm, and the effects of Hot Isostatic Pressing are also examined, with sheet metal specimens used as a baseline for comparison. Statistical analyses are conducted to identify the significance of the dependence of properties on wall thickness and Hot Isostatic Pressing, as well as to examine correlations of these properties to section area, porosity, and surface roughness. A thorough microstructural study is complemented with a first-of-its-kind study of surface morphology to decouple their contributions and identify underlying causes for observed changes in mechanical properties. This thesis finds that mechanical properties in the quasi-static and fatigue framework do not see appreciable declines until specimen thickness is under 0.75 mm in thickness. The added Hot Isostatic Pressing heat treatment effectively closed pores, recrystallized the grain structure, and provided a more homogenous microstructure that benefits the modulus, tensile strength, elongation, and fatigue performance at higher stresses. Stress heterogeneities, primarily caused by surface defects, negatively affected the thinner specimens disproportionately. Without the use of the Hot Isostatic Pressing, the grain structure remained much more refined and benefitted the yield strength and fatigue endurance limit.

With the abundance of increasingly large datasets, the ability to predict the phase of high-entropy alloys (HEAs) based solely on elemental composition could become a reliable tool for the discovery of new HEAs. However, as the amount of data expands so does the computational time and resources required to train predictive classical machine learning models. Quantum computers, which use quantum bits (qubits), could be the solution to overcoming these demands. Their ability to use quantum superposition and interference to perform calculations could be the key to handling large amounts of data. In this work, a hybrid quantum-classical machine learning algorithm is implemented on both quantum simulators and quantum processors to perform the supervised machine learning task. Their feasibility as a future tool for HEA discovery is evaluated based on the algorithm’s performance. An artificial neural network (ANN), run by classical computers, is also trained on the same data for performance comparison. The accuracy of the quantum-classical model was found to be comparable to the accuracy achieved by the classical ANN with a slight decrease in accuracy when ran on quantum hardware due to qubit susceptibility to decoherence. Future developments in the applied quantum machine learning method are discussed.

Disordered many-body systems are ubiquitous in condensed matter physics, materials science and biological systems. Examples include amorphous and glassy states of matter, granular materials, and tissues composed of packings of cells in the extra-cellular matrix (ECM). Understanding the collective emergent properties in these systems is crucial to improving the capability for controlling, engineering and optimizing their behaviors, yet it is extremely challenging due to their complexity and disordered nature. The main theme of the thesis is to address this challenge by characterizing and understanding a variety of disordered many-body systems via unique statistical geometrical and topological tools and the state-of-the-art simulation methods. Two major topics of the thesis are modeling ECM-mediated multicellular dynamics and understanding hyperuniformity in 2D material systems. Collective migration is an important mode of cell movement for several biological processes, and it has been the focus of a large number of studies over the past decades. Hyperuniform (HU) state is a critical state in a many-particle system, an exotic property of condensed matter discovered recently. The main focus of this thesis is to study the mechanisms underlying collective cell migration behaviors by developing theoretical/phenomenological models that capture the features of ECM-mediated mechanical communications in vitro and investigate general conditions that can be imposed on hyperuniformity-preserving and hyperuniformity-generating operations, as well as to understand how various novel transport physical properties arise from the unique hyperuniform long-range correlations.

Cellular metamaterials arouse broad scientific interests due to the combination of host material and structure together to achieve a wide range of physical properties rarely found in nature. Stochastic foam as one subset has been considered as a competitive candidate for versatile applications including heat exchangers, battery electrodes, automotive, catalyst devices, magnetic shielding, etc. For the engineering of the cellular foam architectures, closed-form models that can be used to predict the mechanical and thermal properties of foams are highly desired especially for the recently developed ultralight weight shellular architectures. Herein, for the first time, a novel packing three-dimensional (3D) hollow pentagonal dodecahedron (HPD) model is proposed to simulate the cellular architecture with hollow struts. An electrochemical deposition process is utilized to manufacture the metallic hollow foam architecture. Mechanical and thermal testing of the as-manufactured foams are carried out to compare with the HPD model. Timoshenko beam theory is utilized to verify and explain the derived power coefficient relation. Our HPD model is proved to accurately capture both the topology and the physical properties of hollow stochastic foam. Understanding how the novel HPD model packing helps break the conventional impression that 3D pentagonal topology cannot fulfill the space as a representative volume element. Moreover, the developed HPD model can predict the mechanical and thermal properties of the manufactured hollow metallic foams and elucidating of how the inevitable manufacturing defects affect the physical properties of the hollow metallic foams. Despite of the macro-scale stochastic foam architecture, nano gradient gyroid lattices are studied using Molecular Dynamics (MD) simulation. The simulation result reveals that, unlike homogeneous architecture, gradient gyroid not only shows novel layer-by-layer deformation behavior, but also processes significantly better energy absorption ability. The deformation behavior and energy absorption are predictable and designable, which demonstrate its highly programmable potential.

Ultra-fast 2D/3D material microstructure reconstruction and quantitative structure-property mapping are crucial components of integrated computational material engineering (ICME). It is particularly challenging for modeling random heterogeneous materials such as alloys, composites, polymers, porous media, and granular matters, which exhibit strong randomness and variations of their material properties due to the hierarchical uncertainties associated with their complex microstructure at different length scales. Such uncertainties also exist in disordered hyperuniform systems that are statistically isotropic and possess no Bragg peaks like liquids and glasses, yet they suppress large-scale density fluctuations in a similar manner as in perfect crystals. The unique hyperuniform long-range order in these systems endow them with nearly optimal transport, electronic and mechanical properties. The concept of hyperuniformity was originally introduced for many-particle systems and has subsequently been generalized to heterogeneous materials such as porous media, composites, polymers, and biological tissues for unconventional property discovery. An explicit mixture random field (MRF) model is proposed to characterize and reconstruct multi-phase stochastic material property and microstructure simultaneously, where no additional tuning step nor iteration is needed compared with other stochastic optimization approaches such as the simulated annealing. The proposed method is shown to have ultra-high computational efficiency and only requires minimal imaging and property input data. Considering microscale uncertainties, the material reliability will face the challenge of high dimensionality. To deal with the so-called “curse of dimensionality”, efficient material reliability analysis methods are developed. Then, the explicit hierarchical uncertainty quantification model and efficient material reliability solvers are applied to reliability-based topology optimization to pursue the lightweight under reliability constraint defined based on structural mechanical responses. Efficient and accurate methods for high-resolution microstructure and hyperuniform microstructure reconstruction, high-dimensional material reliability analysis, and reliability-based topology optimization are developed. The proposed framework can be readily incorporated into ICME for probabilistic analysis, discovery of novel disordered hyperuniform materials, material design and optimization.

In this dissertation, two types of passive air freshener products from Henkel, the wick-based air freshener and gel-based air freshener, are studied for their wicking mechanisms and evaporation performances.The fibrous pad of the wick-based air freshener is a porous medium that absorbs fragrance by capillary force and releases the fragrance into the ambient air. To investigate the wicking process, a two-dimensional multiphase flow numerical model using COMSOL Multiphysics is built. Saturation and liquid pressure inside the pad are solved. Comparison between the simulation results and experiments shows that evaporation occurs simultaneously with the wicking process. The evaporation performance on the surface of the wicking pad is analyzed based on the kinetic theory, from which the mass flow rate of molecules passing the interface of each pore of the porous medium is obtained. A 3D model coupling the evaporation model and dynamic wicking on the evaporation pad is built to simulate the entire performance of the air freshener to the environment for a long period of time. Diffusion and natural convection effects are included in the simulation. The simulation results match well with the experiments for both the air fresheners placed in a chamber and in the absent of a chamber, the latter of which is subject to indoor airflow. The gel-based air freshener can be constructed as a porous medium in which the solid network of particles spans the volume of the fragrance liquid. To predict the evaporation performance of the gel, two approaches are tested for gel samples in hemispheric shape. The first approach is the sessile drop model commonly used for the drying process of a pure liquid droplet. It can be used to estimate the weight loss rate and time duration of the evaporation. Another approach is to simulate the concentration profile outside the gel and estimate the evaporation rate from the surface of the gel using the kinetic theory. The evaporation area is updated based on the change of pore size. A 3D simulation using the same analysis is further applied to the cylindrical gel sample. The simulation results match the experimental data well.

Damage and failure of advanced composite materials and structures are often manifestations of nonlinear deformation that involve multiple mechanisms and their interactions at the constituent length scale. The presence and interactions of inelastic microscale constituents strongly influence the macroscopic damage anisotropy and useful residual life. The mechano-chemical interactions between constituents at the atomistic length scale play a more critical role with nanoengineered composites. Therefore, it is desirable to link composite behavior to specific microscopic constituent properties explicitly and lower length scale features using high-fidelity multiscale modeling techniques.In the research presented in this dissertation, an atomistically-informed multiscale modeling framework is developed to investigate damage evolution and failure in composites with radially-grown carbon nanotube (CNT) architecture. A continuum damage mechanics (CDM) model for the radially-grown CNT interphase region is developed with evolution equations derived using atomistic simulations. The developed model is integrated within a high-fidelity generalized method of cells (HFGMC) micromechanics theory and is used to parametrically investigate the influence of various input micro and nanoscale parameters on the mechanical properties, such as elastic stiffness, strength, and toughness. In addition, the inter-fiber stresses and the onset of damage in the presence of the interphase region are investigated to better understand the energy dissipation mechanisms that attribute to the enhancement in the macroscopic out-of-plane strength and toughness. Note that the HFGMC theory relies heavily on the description of microscale features and requires many internal variables, leading to high computational costs. Therefore, a novel reduced-order model (ROM) is also developed to surrogate full-field nonlinear HFGMC simulations and decrease the computational time and memory requirements of concurrent multiscale simulations significantly. The accurate prediction of composite sandwich materials' thermal stability and durability remains a challenge due to the variability of thermal-related material coefficients at different temperatures and the extensive use of bonded fittings. Consequently, the dissertation also investigates the thermomechanical performance of a complex composite sandwich space structure subject to thermal cycling. Computational finite element (FE) simulations are used to investigate the intrinsic failure mechanisms and damage precursors in honeycomb core composite sandwich structures with adhesively bonded fittings.

Atmospheric water extraction (AWE) is an emerging technology to tackle water resource shortage challenges. One such approach to provide fresh water utilizes stimuli-responsive hydrogel-based desiccants to capture the moisture from the air and release it into the liquid form. Typical gel desiccants are composed of a hygroscopic agent for capturing and a hydrophilic gel matrix for storage. The desorption process can be completed by elevating the temperature above the upper or lower critical solution temperature point to initiate the volume phase transition of either thermo-responsive or photothermal types. This thesis focuses on investigating the structural effect of hydrogels on moisture uptake. Firstly, the main matrix of gel desiccant, poly(N-isopropylacrylamide) hydrogel, was optimized via tuning synthesis temperature and initial monomer concentration. Secondly, a series of hydrogel-based desiccants consisting of a hygroscopic material, vinyl imidazole, and optimized poly(N-isopropylacrylamide) gel matrix were synthesized with different network structures. The moisture uptake result showed that the gel desiccant with an interpenetrating polymeric network (IPN) resulted in the best-performing moisture capturing. The gel desiccant with the best performance will be used as a primary structural unit to evaluate the feasibility of developing a light-responsive gel desiccant to materialize light-trigger moisture desorption for AWE technology in the future.

Fiber reinforced composites are rapidly replacing conventional metallic or polymeric materials as materials of choice in a myriad of applications across a wide range of industries. The relatively low weight, high strength, high stiffness, and a variety of thermal and mechanical environmental and loading capabilities are in part what make composite materials so appealing to material experts and design engineers. Additionally, fiber reinforced composites are highly tailorable and customized composite materials and structures can be readily designed for specific applications including those requiring particular directional material properties, fatigue resistance, damage tolerance, high temperature capabilities, or resistance to environmental degradation due to humidity and oxidation. The desirable properties of fiber reinforced composites arise from the strategic combination of multiple constituents to form a new composite material. However, the significant material anisotropy that occurs as a result of combining multiple constituents, each with different directional thermal and mechanical properties, complicates material analysis and remains a major impediment to fully understanding composite deformation and damage behavior. As a result, composite materials, especially specialized composites such as ceramic matrix composites and various multifunctional composites, are not utilized to their fullest potential. In the research presented in this dissertation, the deformation and damage behavior of several fiber reinforced composite systems were investigated. The damage accumulation and propagation behavior of carbon fiber reinforced polymer (CFRP) composites under complex in-phase biaxial fatigue loading conditions was investigated and the early stage damage and microscale damage were correlated to the eventual fatigue failure behavior and macroscale damage mechanisms. The temperature-dependent deformation and damage response of woven ceramic matrix composites (CMCs) reinforced with carbon and silicon carbide fibers was also studied. A fracture mechanics-informed continuum damage model was developed to capture the brittle damage behavior of the ceramic matrix. A multiscale thermomechanical simulation framework, consisting of cooldown simulations to capture a realistic material initial state and subsequent mechanical loading simulations to capture the temperature-dependent nonlinear stress-strain behavior, was also developed. The methodologies and results presented in this research represent substantial progress toward increasing understanding of the deformation and damage behavior of some key fiber reinforced composite materials.