This work presents findings in the combined experimental and computational study of the effects of anisotropy and microstructure on the behavior of HMX-based energetic materials. Large single crystal samples of β-HMX were meticulously created by solvent evaporation for experimental purposes, and respective orientations were identified via x-ray diffraction. Indentation modulus and hardness values were obtained for different orientations of β-HMX via nanoindentation experiments. Small-scale dynamic impact experiments were performed, and a viscoplastic power law model fit, to describe the anisotropic viscoplastic properties of the crystal. The anisotropic fracture toughness and surface energy of β-HMX were calculated by studying indentation-nucleated crack system formations and fitting the corresponding data to two different models, developed by Lawn and Laugier. It was found that the {011} and {110} planes had the highest and lowest fracture toughnesses, respectively. Drop hammer impact tests were performed to investigate effects of morphology on the impact-induced thermal response of HMX. Finally, the anisotropic properties obtained in this work were applied in a cohesive finite element simulation involving the impact of a sample of PBX containing HMX crystals with varying orientations. Cohesive finite element models were generated of separate microstructure containing either anisotropic (locally isotropic) or global isotropic properties of HMX particle. In comparison, the isotropic model appeared to be more deformation resistant.

<div>Polymer matrices present in composite materials are prone to have time-dependent behavior very sensitive to changes in temperature. The modeling of thermoviscoelasticity is fundamental for capturing the performance of anisotropic viscoelastic materials subjected to both mechanical and thermal loads, or for manufacturing simulation of composites. In addition, improved plate/shell and beam models are required to efficiently design and simulate large anisotropic composite structures. Numerical models have been extensively used to capture the linear viscoelasticity in composites, which can be generalized in integral or differential forms. The hereditary integral constitutive form has been adopted by many researchers to be implemented into finite element codes, but its formulation is complex and time consuming as it is function of the time history. The differential formulation provides faster computation times, but its applicability has been limited to capture the behavior of three-dimensional thermoviscoelastic orthotropic materials.</div><div><br></div><div>This work extends mechanics of structure genome (MSG) to construct linear thermoviscoelastic solid, plate/shell and beam models for multiscale constitutive modeling of three-dimensional heterogeneous materials made of time and temperature dependent constituents. The formulation derives the transient strain energy based on integral formulation for thermorheologically simple materials subject to finite temperature changes. The reduced time parameter is introduced to relate the time-temperature dependency of the anisotropic material by means of master curves at reference conditions. The thermal expansion creep is treated as inherent material behavior. Exact three-dimensional thermoviscoelastic homogenization solutions are also formulated for laminates modeled as an equivalent, homogeneous, anisotropic solid. The new model is implemented in SwiftComp, a general-purpose multiscale constitutive modeling code based on MSG, to handle real heterogeneous materials with arbitrary microstructures, mesostructures or cross-sectional shapes.</div><div><br></div><div>Three-dimensional representative volume element (RVE) analyses and direct numerical simulations using a commercial finite element software are conducted to verify the accuracy of the MSG-based constitutive modeling. Additionally, MSG-based plate/shell results are validated against thin-ply high-strain composites experimental data showing good agreement. Numerical cases with uniform and nonuniform cross-sectional temperature distributions are studied. The results showed that unlike MSG, the RVE method exhibits limitations to properly capture the long-term behavior of effective coefficients of thermal expansion (CTEs) when time-dependent constituent CTEs are considered. The analyses of the homogenized properties also revealed that despite the heterogeneous nature of the composite material, from a multiscale analysis perspective, the temperature dependencies of the effective stiffness and thermal stress properties are governed by the same shift factor as the polymer matrix. This conclusion remains the same for MSG-based solid, plate/shell and beam models with uniform temperature distributions.</div>

<div>Structural health monitoring (SHM) has immense potential to improve the safety of aerospace, mechanical, and civil structures because it allows for continuous, real-time damage prognostication. However, conventional SHM methodologies are limited by factors such as the need for extensive external sensor arrays, inadequate sensitivity to small-sized damage, and poor spatial damage localization. As such, widespread implementation of SHM in engineering structures has been severely restricted. These limitations can be overcome through the use of multi-functional materials with intrinsic self-sensing capabilities. In this area, composite materials with nanofiller-modified polymer matrices have received considerable research interest. The electrical conductivity of these materials is affected by mechanical stimuli such as strain and damage. This is known as the piezoresistive effect and it has been leveraged extensively for SHM in self-sensing materials. However, prevailing conductivity-based SHM modalities suffer from two critical limitations. The first limitation is that the mechanical state of the structure must be indirectly inferred from conductivity changes. Since conductivity is not a structurally relevant property, it would be much more beneficial to know the displacements, strains, and stresses as these can be used to predict the onset of damage and failure. The second limitation is that the precise shape and size of damage cannot be accurately determined from conductivity changes. From a SHM point of view, knowing the precise shape and size of damage would greatly aid in-service inspection and nondestructive evaluation (NDE) of safety-critical structures. The underlying cause of these limitations is that recovering precise mechanics from conductivity presents an under determined and multi-modal inverse problem. Therefore, commonly used inversion schemes such as gradient-based optimization methods fail to produce physically meaningful solutions. Instead, metaheuristic search algorithms must be used in conjunction with physics-based damage models and realistic constraints on the solution search space. To that end, the overarching goal of this research is to address the limitations of conductivity-based SHM by developing metaheuristic algorithm-enabled methodologies for recovering precise mechanics from conductivity changes in self-sensing composites.</div><div><div><br></div><div>Three major scholarly contributions are made in this thesis. First, a piezoresistive inversion methodology is developed for recovering displacements, strains, and stresses in an elastically deformed self-sensing composite based on observed conductivity changes. For this, a genetic algorithm (GA) is integrated with an analytical piezoresistivity model and physics-based constraints on the search space. Using a simple stress based failure criterion, it is demonstrated that this approach can be used to accurately predict material failure. Second, the feasibility of using other widely used metaheuristic algorithms for piezoresistive inversion is explored. Specifically, simulated annealing (SA) and particle swarm optimization (PSO) are used and their performances are compared to the performance of the GA. It is concluded that while SA and PSO can certainly be used to solve the piezoresistive inversion problem, the GA is the best algorithm based on solution accuracy, consistency, and efficiency. Third, a novel methodology is developed for precisely determining damage shape and size from observed conductivity changes in self-sensing composites. For this, a GA is integrated with physics-based geometric models for damage and suitable constraints on the search space. By considering two specific damage modes —through-holes and delaminations —it is shown that this method can be used to precisely reconstruct the shape and size of damage. </div><div><br></div><div>In achieving these goals, this thesis advances the state of the art by addressing critical limitations of conductivity-based SHM. The methodologies developed herein can enable unprecedented NDE capabilities by providing real-time information about the precise mechanical state (displacements, strains, and stresses) and damage shape in self-sensing composites. This has incredible potential to improve the safety of structures in a myriad of engineering venues.</div></div>

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