<div>The rate effect of fiber-matrix interfacial debonding behavior of SC-15 epoxy and various fiber reinforcements was studied via in-situ visualization of the debonding event. Special focus has been placed on the dynamic transverse debonding of single fiber reinforced polymer composites. In this study, the debonding force history, debonding initiation, debonding crack velocity, and crack geometry were characterized using a quasi-static load frame and a modified tension Kolsky bar at loading velocities of 0.25 mm/s and 2.5 m/s. Cruciform-shaped specimens were used for interfacial transverse debonding between SC-15 epoxy matrix and various fiber reinforcements including S-2 glass, Kevlar® KM2, and tungsten fiber materials. The load history and high-speed images of the debonding event were simultaneously recorded. A major increase was observed for the average peak debonding force and a minor increase was observed for the average crack velocity with increasing loading velocity. The crack geometry of the cruciform specimens under both loading velocities was also tracked. Scanning electron microscopy of the recovered specimens revealed the debonding direction along the fiber-matrix interface through angled patterns on the failure surface.</div><div><br></div><div>The dynamic shear debonding of single fiber reinforced plastic composites were also studied via the real-time visualization with the fiber pull-out method. The interfacial shear debonding was studied between SC-15 epoxy and fiber reinforcements including S-2 glass, tungsten, steel, and carbon composite Z-pin fiber materials at 2.5 m/s and 5.0 m/s. Both S-2 glass fiber and Z-pin experienced catastrophic interfacial debonding whereas tungsten and steel wire experienced both catastrophic debonding and stick-slip behavior. Scanning electron microscope imaging of recovered epoxy beads revealed a snap-back behavior around the meniscus region of the bead for S-2 glass, tungsten, and steel fiber materials at 5.0 m/s whereas those at 2.5 m/s exhibited no snap-back behavior.</div>

<div><p>Carbon fibre reinforced polymers (CFRPs) are extensively used in aerospace, automotive and other weight-conscious applications for their high strength-to-weight ratio. Utilization of these lightweight materials unfortunately also involves dealing with damages unlike those seen in traditional monolithic materials. This includes invisible, below-the-surface damages such as matrix cracking, delaminations, fibre breakage, etc. that are difficult to spot outwardly in their early stages. Robust methods of damage detection and health monitoring are hence important. With the intention of avoiding weight addition to the structure to monitor its usability, it would be desirable to utilize an inherent property of these materials, such as its electrical conductivity, as an indicator of damage to render the material as self-sensing.</p> <p>To this end, electrical impedance tomography (EIT) has been explored for damage detection and health monitoring in self-sensing materials due to its ability to spatially localize damage via non-invasive electrical measurements.</p> <p>Presently, EIT has been applied mainly to materials possessing lesser electrical anisotropy than is encountered in CFRPs (e.g. nanofiller-modified polymers and cements), with experimental setups involving electrodes placed at the edges of plates. The inability of EIT to effectively tackle electrical anisotropy limits its usage in CFRP structures. Moreover, most real structures of complex geometries lack well-defined edges on which electrodes can be placed. Therefore, in this thesis, we confront these limitations by presenting a study into the effect of EIT sensitivity matrix formulation and surface-mounted electrodes on damage detection and localization in CFRPs.</p> <p>In this work, the conductivity is modeled as being anisotropic, and the sensitivity matrix is formed using three approaches – with respect to i) a scalar multiple of the conductivity tensor, ii) the in-plane conductivity, and iii) the through-thickness conductivity. It was found that through-hole damages can be adeptly identified with a combination of surface-mounted electrodes and a sensitivity matrix formed with respect to either a scalar multiple of the conductivity tensor or the in-plane conductivity. This theory was first validated on a CFRP plate to detect a single through-hole damage. Furthermore, EIT was also used to successfully detect both through-hole and impact damages on a non-planar airfoil shaped structure.</p> <p>Singular value decomposition (SVD) analysis revealed that the rank of the sensitivity matrix is not affected by the conductivity term with respect to which the sensitivity matrix is formed. The results presented here are an important step towards the transition of EIT based diagnostics to real-life CFRP structures.</p><p></p></div><div><div><br></div></div>

<p dir="ltr">Ceramic/metal composites are being explored as potential replacements for conventional metal alloys in high-temperature components used in aerospace and power generation applications. Co-continuous ceramic/metal composites can offer attractive combinations of properties, such as improved mechanical toughness and thermal conductivity (relative to monolithic ceramics) and enhanced stiffness and corrosion/erosion resistance (relative to monolithic metals). However, development of cost-effective and scalable manufacturing routes to dense, complex-shaped ceramic/metal composites is a non-trivial challenge.</p><p dir="ltr">Chapter 1 of this dissertation is focused on the fabrication of WC/Cu composites using pressureless Cu liquid infiltration. The microstructure, density, porosity, phase content and properties of the resulting WC/Cu composites have been investigated. Mechanical properties, such as flexural strength and Vickers hardness have been evaluated, and the thermal cycling behavior of the WC/Cu composites have been examined. This study successfully demonstrates the fabrication of near-net-shape WC/Cu composites and provides insights into potential applications for such composites.</p><p dir="ltr">In Chapter 2, the limitations of metal alloy-based heat exchangers are discussed, leading to the exploration of alternative materials such as composite of zirconium carbide (ZrC) and tungsten (W). The favorable properties of ZrC/W composites, such as chemical compatibility, low vapor pressure, high thermal conductivity, stiffness, and thermal cyclability are highlighted. The fabrication of ZrC/W composites using reactive infiltration processes, emphasizing the importance of scalable fabrication methods, is also demonstrated.</p><p dir="ltr">Chapter 3 is focused on the fabrication and characterization of functionally graded ZrC/W – WC/Cu composites. These composites have been prepared by immersing WC/Cu preforms in Zr – Cu liquid at different temperatures, and the microstructures and phase distributions have been evaluated. It is observed with the same immersion time, the thickness of the ZrC/W reaction zone decreases with increasing immersion temperature due to the rapid reaction between WC and Zr at higher temperatures. Additionally, a model has been developed to describe the thermal conductivity of the composites as a function of the distance from the external surface. These findings provide insights into the fabrication and properties of functionally-graded composites for potential heat dissipation applications.</p><p dir="ltr">In Chapter 4, the development of a Ti-bearing, Ni-based active metal braze for joining Al₂O₃/Cr composites to Ni-based alloys is discussed. Joining ceramic components to metal parts poses challenges due to material property mismatches and ceramic brittleness. Conventional brazing materials often suffer from oxidation at high temperatures in air which compromises joint integrity. The focus of this chapter is the evaluation of the oxidation behavior of the developed brazing material to assess the suitability of this braze for reliable joining of ceramic-based composites to Ni-based alloys for use in air at high temperatures. Differential scanning calorimetry (DSC) has also been used to evaluate the solidus and liquidus temperatures of the Ni-19Cr-10Si and Ni-18Cr-10Si-4Ti alloys.</p><p><br></p>

<p>Composite materials have become widely used for high-performance applications, particularly in the aerospace industry where annual production volumes are low and a higher part cost can be supported. During the last decades composite materials are beginning to see use in a broader range of applications, including the automotive and sports equipment industries. Simultaneously, there is increasing demand from consumers and regulatory bodies to make cars more fuel efficient and in the case of EV’s longer drive range, which can be accomplished by reducing vehicle weight. Composite materials have high specific stiffnesses and strengths, resulting in weight savings when they are used to replace traditionally metal components. However, in order for widespread adoption of composite parts to be viable for the automotive industry, high-rate manufacturing must be realized to reach the required production volumes and part costs.</p> <p>Toward this goal, advanced composite manufacturing techniques have been developed. These techniques typically combine high automation with careful material selection, which can include fast-curing resins and thermoplastics with adapted melt viscosities and thermomechanical properties. They also allow for complex part geometries to be produced in a single step, reducing the need for additional assembly time. Further, they can be used to easily create multi-material components, which can result in parts that benefit from the desirable mechanical properties of the constituent materials without sacrificing performance.</p> <p>This thesis develops a framework for the design and high-rate manufacture of multi-material components. First, a critical literature review is conducted to develop a clear understanding of existing research into combinations of dissimilar materials, including epoxy/polyamide, thermoplastic elastomer/polyamide, and aluminum/thermoplastic. It is shown that, for all material combinations studied, interfacial delamination and subsequent deformation are the primary energy absorption mechanisms and that manufacturing conditions may affect interfacial bond strength. Based on this foundation, adhesion testing is performed on devoted sample configurations fabricated under controlled molding conditions. For these material combinations, interfacial adhesion can be significantly improved with carefully selected processing temperatures, even to the extent that adhesive bond between dissimilar materials can be stronger than the cohesive bond in the constituent materials. Next, impact and quasi-static indentation testing were performed to determine the effects of interfacial adhesion and part design on crash performance. The materials tested all benefit from the placement of a more ductile material on the impacted side of the sample (top surface), indicating a more favorable dissipation of the contact stresses from the impactor, and a higher strength material on the bottom surface where it can withstand tensile stresses imposed by impact-induced bending. </p> <p> Finally, a complex part consisting of a unidirectional polyamide/carbon fiber preform and a thermoplastic overmold is manufactured via a hybrid overmolding process. Interfacial temperature during overmolding is varied to confirm if the same improvements in interfacial bond strength seen in the compression molding test samples are attainable under realistic high-rate manufacture conditions. Additionally, the preform volume is varied to examine the effect of the preform reinforcement on a part’s bending performance. For this system, varying the preform temperature had no effect on interfacial bond strength. A predictive technical cost model is also used to determine the effect of manufacturing changes on part costs. Increasing the tow volume three-fold increased the absorbed energy by more than 30% and requires an increased cost of only 3.8%. </p> <p>This thesis proves that a tough, multi-material part can be rapidly produced via hybrid overmolding. It was demonstrated that a complex shaped part could be produced at a complete line cycle time of approximately 90 secondsmaking it a viable method to produce high-performance, low-cost components. </p>

Micro-mechanical Raman spectroscopy is an excellent tool for direct stress measurements in the structure. The presence of mechanical stress changes the Raman frequency of each Raman modes compared to the Raman frequencies in absence of stress. This difference in Raman frequency is linearly related to stress induced and can be calibrated to stress by uniaxial or biaxial tension/compression experiments. This relationship is not generally linear for non-linear behavior of the materials which limits its use to experimentally study flow stress and plastic deformation behavior of the material. In this work strontium titanate ceramic particles dispersed inside epoxy resin matrix were used to measure stress in epoxy resin matrix with non-linear material behavior around it. The stress concentration factor between stress induced inside ceramic particles and epoxy resin matrix was obtained by non-linear constitutive finite element model. The results of finite element model were used for training a machine learning model to predict stress in epoxy resin matrix based on stress inside ceramic particles. By measuring stress inside ceramic particles using micro-mechanical Raman spectroscopy, the stress inside epoxy matrix was obtained by pre-determined stress concentration factor.

<p>Composite materials have been successfully applied in various industries, such as aerospace, automobile, and wind turbines, etc. Although the material properties of composites are desirable, the behaviors of composites are complicated. Many efforts have been made to model the constitutive behavior and failure of composites, but a complete and validated methodology has not been completely achieved yet. Recently, machine learning techniques have attracted many researchers from the mechanics field, who are seeking to construct surrogate models with machine learning, such as deep neural networks (DNN), to improve the computational speed or employ machine learning to discover unknown governing laws to improve the accuracy. Currently, the majority of studies mainly focus on improving computational speed. Few works focus on applying machine learning to discover unknown governing laws from experimental data.  In this study, we will demonstrate the implementation of machine learning to discover unknown governing laws of composites. Additionally, we will also present an application of machine learning to accelerate the design optimization of a composite rotor blade.</p> <p><br></p> <p>To enable the machine learning model to discover constitutive laws directly from experimental data, we proposed a framework to couple finite element (FE) with DNN to form a fully coupled mechanics system FE-DNN. The proposed framework enables data communication between FE and DNN, which takes advantage of the powerful learning ability of DNN and the versatile problem-solving ability of FE. To implement the framework to composites, we introduced positive definite deep neural network (PDNN) to the framework to form FE-PDNN, which solves the convergence robustness issue of learning the constitutive law of a severely damaged material. In addition, the lamination theory is introduced to the FE-PDNN mechanics system to enable FE-PDNN to discover the lamina constitutive law based on the structural level responses.</p> <p><br></p> <p>We also developed a framework that combines sparse regression with compressed sensing, which leveraging advances in sparsity techniques and machine learning, to discover the failure criterion of composites from experimental data. One advantage of the proposed approach is that this framework does not need Bigdata to train the model. This feature satisfies the current failure data size constraint. Unlike the traditional curve fitting techniques, which results in a solution with nonzero coefficients in all the candidate functions. This framework can identify the most significant features that govern the dataset. Besides, we have conducted a comparison between sparse regression and DNN to show the superiority of sparse regression under limited dataset. Additionally, we used an optimization approach to enforce a constraint to the discovered criterion so that the predicted data to be more conservative than the experimental data. This modification can yield a conservative failure criterion to satisfy the design needs.</p> <p><br></p> <p>Finally, we demonstrated employing machine learning to accelerate the planform design of a composite rotor blade with strength consideration. The composite rotor blade planform design focuses on optimizing planform parameters to achieve higher performance. However, the strength of the material is rarely considered in the planform design, as the physic-based strength analysis is expensive since millions of load cases can be accumulated during the optimization. Ignoring strength analysis may result in the blade working in an unsafe or low safety factor region since composite materials are anisotropic and susceptible to failure. To reduce the computational cost of the blade cross-section strength analysis, we proposed to construct a surrogate model using the artificial neural network (ANN) for beam level failure criterion to replace the physics-based strength analysis. The surrogate model is constructed based on the Timoshenko beam model, where the mapping is between blade loads and the strength ratios of the cross-section. The results showed that the surrogate model constraint using machine learning can achieve the same accuracy as the physics-based simulation while the computing time is significantly reduced. </p>

<p>When a composite laminate is transversely impacted by a projectile at the ballistic limit, its failure mode transits from global conical deformation to localized perforation. This Ph.D. dissertation aims to reveal the fundamental material failure mechanism at the ballistic limit to control perforation. First, transverse impact experiments were designed on composite strips to isolate the interaction between plies and tows. Three failure modes were identified, divided by no, partial, and complete failure before the transverse wave deformed the entire composite strip. The failure phenomenon and critical velocity region can differ with the fiber type and projectile nose geometry and dimension. In most impact events, the composite strips all failed in tension in the front of the projectiles, although they failed at different positions as the projectile nose geometry and fiber type changed. A special failure phenomenon was uncovered when the composite strips were impacted onto razor blades above the upper limit of the critical velocity region: the composite strips seemed to be cut through completely by the razor blades. To further investigate the failure by razor blade, a microscopic method was developed to cut a single fiber extracted from the composite strip and simultaneously image the failure process inside a Scanning Electron Microscope (SEM). The experiments revealed that the razor blade cannot cut through the inorganic S-2 glass fibers while can partially incision the aramid Kevlar^®KM2 Plus fibers and completely shear through the ultra-high-molecular-weight polyethylene (UHMWPE) Dyneema^® SK76 fibers. Further investigations on the fiber’s failure under dynamic cut revealed that there was no variation in the failure mode when the cut speed was increased from 1.67 μm/s to ~5.34 m/s. To record the local dynamic failure inside the composite strips and single fibers at high-velocity impact, an advanced imaging technique, high-speed synchrotron X-ray phase-contrast imaging, was introduced, which allows to capture the composite’s internal failure with a resolution of up to 1.6 μm/pixel and at a time interval 0.1 μs. Integrated with a reverse impact technique, such an advanced imaging technique is believed to be capable of revealing the mechanism involved in the impact-induced cut in single fibers, yarns, and composite strips. The relevant studies will be the extended work of this Ph.D. dissertation and published in the future.</p>

<p dir="ltr">During atmospheric re-entry, the hypersonic leading edges can experience enormous heat fluxes, with surface temperatures greater than 1600℃ expected. While carbon/carbon (C/C) is a candidate material for leading edge structures, it is prone to oxidation and ablation damage above 500℃. Ablation-resistant coatings can protect the C/C, while emissivity can be engineered to lower the leading-edge surface temperature via radiative cooling. In this dissertation, a novel bilayer coating system and a multilayer coating system based on individual layers consisting of ultra-high temperature ceramics (borides, carbides), refractory oxides (zirconia), and rare-earth oxide as emissivity modifiers were applied to a C/C surface via pack cementation and plasma spray. Ablation tests were performed to evaluate the efficacy of the multilayer coatings in simulated high heat flux environments. <a href="" target="_blank">The spectral emittance of the rare-earth modified topcoat ZrO₂ was measured at high temperatures up to 1200</a>℃ using a benchtop emissometer. ZrO₂ stabilized with 6 mol% Sm₂O₃ demonstrated a maximum spectral emissivity of 0.99 at λ = 12.5 µm proving its effectiveness in cooling the leading edge surface through enhanced thermal radiation.</p><p dir="ltr"><a href="" target="_blank">The bilayer coating system comprised of Sm₂O₃-stabilized ZrO₂ topcoat layer and SiC intermediate sublayer on C/C. </a><a href="" target="_blank">This coating significantly improved the ablation resistance of C/C by reducing the mass ablation rate by ~71%. Despite a significant thermal expansion coefficient mismatch between the substrate and the coating, a well-defined mechanical adhesion characterized by the anchors was observed in pre- and post-ablated coating microstructures, indicating their influence on improving ablation resistance.</a></p><p dir="ltr"><a href="" target="_blank">The multilayer coating architecture consisted of SiC, ZrB₂-SiC, ZrC-ZrO₂ sublayers and a Sm₂O₃-ZrO₂ topcoat. The as-sprayed coating microstructure demonstrated well-defined adhesion between the layers and the substrate without forming major voids or cracks. The multilayer coating with optimized</a> sublayer thickness demonstrated excellent ablation and mass erosion resistance as they reduced the mass ablation rate of C/C by ~90% after being subjected to an aggressive oxyacetylene torch heating for 60 s. During testing, the Sm₂O₃-stabilized ZrO₂ topcoat acted as oxygen and thermal barrier, protecting the underlying sublayers from oxidation-induced damage while maintaining a constant surface temperature of ~2100 ℃. Additionally, the high spectral emittance of topcoat material contributed to efficient outward heat transfer via thermal radiation from the external surface while maintaining a constant temperature.</p>

<p>For many applications within the defense, aerospace, and electricity-producing industries, available material choices for high-performance devices that fulfill necessary requirements are limited. Choosing a metallic material or a ceramic material may be optimal for only some of the required properties. For instance, choosing a metal may optimize ductility but compromise oxidation resistance, yield strength, or creep resistance. Of potential interest, ceramic-metal (cermet) composites can address several fundamental concerns such as high temperature mechanical toughness and stiffness and oxidation/corrosion resistance. However, cost-effective, scalable manufacturing of complex-shaped, high-temperature cermets can be challenging.</p> <p>A cermet of interest is niobium and yttrium oxide, Y2O3. Both materials exhibit high melting points with similar coefficients of thermal expansion. Basic thermodynamic calculations suggest that these materials are chemically compatible, and that Y2O3/Nb cermets may be generated by reactive melt infiltration using the patented Displacive Compensation of Porosity (DCP) process. With the DCP process, a liquid fills a porous perform, and a displacement reaction occurs to produce products of larger solid volume. This reaction yields the cermet of interest, formed in a reduced-stress condition, while maintaining a generally near net shape and high relative density.</p> <p>In order to get to the point of designing cermet components for various applications, a focus of this work has been to create a Y2O3/Nb composite by hot pressing powders at high temperatures at the predicted stoichiometric ratios, and then characterizing the thermal and mechanical properties. The reduction reaction between liquid yttrium and solid niobium (IV) oxide (NbO2) was then characterized to evaluate kinetic mechanisms affecting the reaction rate which is necessary for future DCP-based cermet component manufacturing.</p> <p>Lastly, the mechanical behavior of this cermet was modeled and compared to another cermet processed using liquid metal infiltration using a temperature-dependent elasto-visco-plastic self-consistent model. The effects of cooling from processing temperatures, as well as thermally cycling of these cermets, were quantified. As high temperature experiments can be time intensive with high costs, it is advantageous to have a computationally efficient, desktop design tool to quantify the impacts of changing processing and use conditions on material performance.</p>

<p>Obtaining full-field \emph{dynamic} material state awareness would have profound and wide-ranging implications across many fields and disciplines. For example, achieving dynamic state awareness in soft tissues could lead to the early detection of pathophysiological conditions. Applications in geology and seismology could enhance the accuracy of locating mineral and hydrocarbon resources for extraction or unstable subsurface formations. Ensuring safe interaction at the human-machine interfaces in soft robotic applications is another example. And as a final representative example, knowing real-time material dynamics in safety-critical structures and infrastructure can mitigate catastrophic failures. Because many materials (e.g., carbon fiber-reinforced polymers composites, ceramic matrix composites, biological tissues, cementitious and geological materials, and nanocomposites) exhibit coupling between their mechanical state and electrical transport characteristics, self-sensing via the piezoresistive effect is a potential gateway to these capabilities. While piezoresistivity has been mostly explored in static and quasi-static conditions, using piezoresistivity to achieve dynamic material state awareness is comparatively unstudied. Herein lies the significant gap in the state of the art: the piezoresistive effect has yet to be studied for in-situ dynamic sensing.</p> <p><br></p> <p>In this thesis, the gap in the state of the art is addressed by studying the piezoresistive effect of carbon nanocomposites subject to high-rate and transient elastic loading. Nanocomposites were chosen merely as a representative self-sensing material in this study because of their ease of manufacturability and our good understanding of their electro-mechanical coupling. Slender rods were manufactured using epoxy, modified with a small weight fraction of nanofillers such as carbon black (CB), carbon nanofibers (CNFs), and multi-walled carbon nanotubes (MWCNTs), and subject to loading states such as steady-state vibration at structural frequencies ($10^2-10^4$ Hz), controlled wave packet excitation, and high-strain rate impact loading in a split-Hopkinson pressure bar. This work discovers foundational principles for dynamic material state awareness through piezoresistivity. </p> <p><br></p> <p>Three major scholarly contributions are made in this dissertation. First, an investigation was pursued to establish dynamic, high-strain rate sensing. This investigation clearly demonstrated the ability of piezoresistivity to accurately track rapid and spatially-varying deformation for strain rates up to $10^2$ s$^{-1}$. Second, piezoresistivity was used to detect steady-state vibrations common at structural frequencies. Utilizing simple signal processing techniques, it was possible to extract the excitation frequency embedded into the collected electrical measurements. The third contribution examined the dynamic piezoresistive effect through an array of surface-mounted electrodes on CNF/epoxy rods subject to highly-controlled wave packet excitation. Electrode-spacing adjustments were found to induce artificial signal filtering by containing larger portions of the injected wave packets. The strain state in the rod was found after employing an inverse conductivity-to-mechanics model, thereby demonstrating the possibility of deducing actual in-situ strains via this technique. A digital twin in ABAQUS was constructed, and an elastodynamic simulation was conducted using identical dynamic loading, the results of which showed very good agreement with the piezo-inverted strains. </p> <p><br></p> <p>This work creates the first intellectual pathway to full-field dynamic embedded sensing. This work has far-reaching potential applications in many fields, as numerous materials exhibit self-sensing characteristics through deformation-dependent changes to electrical properties. Therefore, \emph{piezoresistive elastodynamics} has the incredible potential to be applied not just in structural applications but in other potentially innovated applications where measuring dynamic behavior through self-sensing materials is possible.  </p>