Matching Items (17)
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- All Subjects: Materials Science
- All Subjects: Composites
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Description
Intelligent engineering designs require an accurate understanding of material behavior, since any uncertainties or gaps in knowledge must be counterbalanced with heightened factors of safety, leading to overdesign. Therefore, building better structures and pushing the performance of new components requires an improved understanding of the thermomechanical response of advanced materials under service conditions. This dissertation provides fundamental investigations of several advanced materials: thermoset polymers, a common matrix material for fiber-reinforced composites and nanocomposites; aluminum alloy 7075-T6 (AA7075-T6), a high-performance aerospace material; and ceramic matrix composites (CMCs), an advanced composite for extreme-temperature applications. To understand matrix interactions with various interfaces and nanoinclusions at their fundamental scale, the properties of thermoset polymers are studied at the atomistic scale. An improved proximity-based molecular dynamics (MD) technique for modeling the crosslinking of thermoset polymers is carefully established, enabling realistic curing simulations through its ability to dynamically and probabilistically perform complex topology transformations. The proximity-based MD curing methodology is then used to explore damage initiation and the local anisotropic evolution of mechanical properties in thermoset polymers under uniaxial tension with an emphasis on changes in stiffness through a series of tensile loading, unloading, and reloading experiments. Aluminum alloys in aerospace applications often require a fatigue life of over 109 cycles, which is well over the number of cycles that can be practically tested using conventional fatigue testing equipment. In order to study these high-life regimes, a detailed ultrasonic cycle fatigue study is presented for AA7075-T6 under fully reversed tension-compression loading. The geometric sensitivity, frequency effects, size effects, surface roughness effects, and the corresponding failure mechanisms for ultrasonic fatigue across different fatigue regimes are investigated. Finally, because CMCs are utilized in extreme environments, oxidation plays an important role in their degradation. A multiphysics modeling methodology is thus developed to address the complex coupling between oxidation, mechanical stress, and oxygen diffusion in heterogeneous carbon fiber-reinforced CMC microstructures.
ContributorsSchichtel, Jacob (Author) / Chattopadhyay, Aditi (Thesis advisor) / Dai, Lenore (Committee member) / Ghoshal, Anindya (Committee member) / Huang, Huei-Ping (Committee member) / Jiao, Yang (Committee member) / Oswald, Jay (Committee member) / Arizona State University (Publisher)
Created2022
Description
Advanced fibrous composite materials exhibit outstanding thermomechanical performance under extreme environments, which make them ideal for structural components that are used in a wide range of aerospace, nuclear, and defense applications. The integrity and residual useful life of these components, however, are strongly influenced by their inherent material flaws and defects resulting from the complex fabrication processes. These defects exist across multiple length scales and govern several scale-dependent inelastic deformation mechanisms of each of the constituents as well as their composite damage anisotropy. Tailoring structural components for optimal performance requires addressing the knowledge gap regarding the microstructural material morphology that governs the structural scale damage and failure response. Therefore, there is a need for a high-fidelity multiscale modeling framework and scale-specific in-situ experimental characterization that can capture complex inelastic mechanisms, including damage initiation and propagation across multiple length scales. This dissertation presents a novel multiscale computational framework that accounts for experimental information pertinent to microstructure morphology and architectural variabilities to investigate the response of ceramic matrix composites (CMCs) with manufacturing-induced defects. First, a three-dimensional orthotropic viscoplasticity creep formulation is developed to capture the complex temperature- and time-dependent constituent load transfer mechanisms in different CMC material systems. The framework also accounts for a reformulated fracture mechanics-informed matrix damage model and the Curtin progressive fiber damage model to capture the complex scale-dependent damage and failure mechanisms through crack kinetics and porosity growth. Next, in-situ experiments using digital image correlation (DIC) are performed to capture the damage and failure mechanisms in CMCs and to validate the high-fidelity modeling results.
The dissertation also presents an exhaustive experimental investigation into the effects of temperature and manufacturing-induced defects on toughened epoxy adhesives and hybrid composite-metallic bonded joints. Nondestructive evaluation techniques are utilized to characterize the inherent defects morphology of the bulk adhesives and bonded interface. This is followed by quasi-static tensile tests conducted at extreme hot and cold temperature conditions. The damage mechanisms and failure modes are investigated using in-situ DIC and a high-resolution camera. The information from the morphology characterization studies is used to reconstruct high-fidelity geometries of the test specimens for finite element analysis.
ContributorsKhafagy, Khaled Hassan Abdo (Author) / Chattopadhyay, Aditi (Thesis advisor) / Fard, Masoud Y. (Committee member) / Milcarek, Ryan (Committee member) / Stoumbos, Tom (Committee member) / Borkowski, Luke (Committee member) / Arizona State University (Publisher)
Created2022
Description
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.
ContributorsSkinner, Travis Dale (Author) / Chattopadhyay, Aditi (Thesis advisor) / Hall, Asha (Committee member) / Liu, Yongming (Committee member) / Jiao, Yang (Committee member) / Yekani-Fard, Masoud (Committee member) / Arizona State University (Publisher)
Created2021
Description
While understanding of failure mechanisms for polymeric composites have improved vastly over recent decades, the ability to successfully monitor early failure and subsequent prevention has come of much interest in recent years. One such method to detect these failures involves the use of mechanochemistry, a field of chemistry in which chemical reactions are initiated by deforming highly-strained bonds present in certain moieties. Mechanochemistry is utilized in polymeric composites as a means of stress-sensing, utilizing weak and force-responsive chemical bonds to activate signals when embedded in a composite material. These signals can then be detected to determine the amount of stress applied to a composite and subsequent potential damage that has occurred due to the stress. Among mechanophores, the cinnamoyl moiety is capable of stress response through fluorescent signal under mechanical load. The cinnamoyl group is fluorescent in its initial state and capable of undergoing photocycloaddition in the presence of ultraviolet (UV) light, followed by subsequent reversion when under mechanical load. Signal generation before the yield point of the material provides a form of damage precursor detection.This dissertation explores the implementation of mechanophores in novel approaches to overcome some of the many challenges within the mechanochemistry field. First, new methods of mechanophore detection were developed through utilization of Fourier transform infrared (FTIR) spectroscopy signals and in-situ stress sensing. Developing an in-situ testing method provided a two-fold advantage of higher resolution and more time efficiency over current methods involving image analysis with a fluorescent microscope. Second, bonding mechanophores covalently into the backbone of an epoxy matrix mitigated property loss due to mechanophore incorporation. This approach was accomplished through functionalizing either the resin or hardener component of the matrix. Finally, surface functionalization of fibers was performed and allowed for unaltered fabrication procedures of composite layups as well as provided increased adhesion at the fiber-matrix interphase. The developed materials could enable a simple, non-invasive, and non-detrimental structural health monitoring approach.
ContributorsGunckel, Ryan Patrick (Author) / Dai, Lenore (Thesis advisor) / Chattopadhyay, Aditi (Thesis advisor) / Lind Thomas, Mary Laura (Committee member) / Liu, Yongming (Committee member) / Forzani, Erica (Committee member) / Arizona State University (Publisher)
Created2021
Description
Extensive efforts have been devoted to understanding material failure in the last several decades. A suitable numerical method and specific failure criteria are required for failure simulation. The finite element method (FEM) is the most widely used approach for material mechanical modelling. Since FEM is based on partial differential equations, it is hard to solve problems involving spatial discontinuities, such as fracture and material interface. Due to their intrinsic characteristics of integro-differential governing equations, discontinuous approaches are more suitable for problems involving spatial discontinuities, such as lattice spring method, discrete element method, and peridynamics. A recently proposed lattice particle method is shown to have no restriction of Poisson’s ratio, which is very common in discontinuous methods. In this study, the lattice particle method is adopted to study failure problems. In addition of numerical method, failure criterion is essential for failure simulations. In this study, multiaxial fatigue failure is investigated and then applied to the adopted method. Another critical issue of failure simulation is that the simulation process is time-consuming. To reduce computational cost, the lattice particle method can be partly replaced by neural network model.First, the development of a nonlocal maximum distortion energy criterion in the framework of a Lattice Particle Model (LPM) is presented for modeling of elastoplastic materials. The basic idea is to decompose the energy of a discrete material point into dilatational and distortional components, and plastic yielding of bonds associated with this material point is assumed to occur only when the distortional component reaches a critical value. Then, two multiaxial fatigue models are proposed for random loading and biaxial tension-tension loading, respectively. Following this, fatigue cracking in homogeneous and composite materials is studied using the lattice particle method and the proposed multiaxial fatigue model. Bi-phase material fatigue crack simulation is performed. Next, an integration of an efficient deep learning model and the lattice particle method is presented to predict fracture pattern for arbitrary microstructure and loading conditions. With this integration, computational accuracy and efficiency are both considered. Finally, some conclusion and discussion based on this study are drawn.
ContributorsWei, Haoyang (Author) / Liu, Yongming (Thesis advisor) / Chattopadhyay, Aditi (Committee member) / Jiang, Hanqing (Committee member) / Jiao, Yang (Committee member) / Oswald, Jay (Committee member) / Arizona State University (Publisher)
Created2021
Description
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.
ContributorsVenkatesan, Karthik Rajan (Author) / Chattopadhyay, Aditi (Thesis advisor) / Liu, Yongming (Committee member) / Jiao, Yang (Committee member) / Yekani Fard, Masoud (Committee member) / Stoumbos, Tom (Committee member) / Arizona State University (Publisher)
Created2021
Description
Non-Destructive Testing (NDT) is integral to preserving the structural health of materials. Techniques that fall under the NDT category are able to evaluate integrity and condition of a material without permanently altering any property of the material. Additionally, they can typically be used while the material is in active use instead of needing downtime for inspection.
The two general categories of structural health monitoring (SHM) systems include passive and active monitoring. Active SHM systems utilize an input of energy to monitor the health of a structure (such as sound waves in ultrasonics), while passive systems do not. As such, passive SHM tends to be more desirable. A system could be permanently fixed to a critical location, passively accepting signals until it records a damage event, then localize and characterize the damage. This is the goal of acoustic emissions testing.
When certain types of damage occur, such as matrix cracking or delamination in composites, the corresponding release of energy creates sound waves, or acoustic emissions, that propagate through the material. Audio sensors fixed to the surface can pick up data from both the time and frequency domains of the wave. With proper data analysis, a time of arrival (TOA) can be calculated for each sensor allowing for localization of the damage event. The frequency data can be used to characterize the damage.
In traditional acoustic emissions testing, the TOA combined with wave velocity and information about signal attenuation in the material is used to localize events. However, in instances of complex geometries or anisotropic materials (such as carbon fibre composites), velocity and attenuation can vary wildly based on the direction of interest. In these cases, localization can be based off of the time of arrival distances for each sensor pair. This technique is called Delta T mapping, and is the main focus of this study.
The two general categories of structural health monitoring (SHM) systems include passive and active monitoring. Active SHM systems utilize an input of energy to monitor the health of a structure (such as sound waves in ultrasonics), while passive systems do not. As such, passive SHM tends to be more desirable. A system could be permanently fixed to a critical location, passively accepting signals until it records a damage event, then localize and characterize the damage. This is the goal of acoustic emissions testing.
When certain types of damage occur, such as matrix cracking or delamination in composites, the corresponding release of energy creates sound waves, or acoustic emissions, that propagate through the material. Audio sensors fixed to the surface can pick up data from both the time and frequency domains of the wave. With proper data analysis, a time of arrival (TOA) can be calculated for each sensor allowing for localization of the damage event. The frequency data can be used to characterize the damage.
In traditional acoustic emissions testing, the TOA combined with wave velocity and information about signal attenuation in the material is used to localize events. However, in instances of complex geometries or anisotropic materials (such as carbon fibre composites), velocity and attenuation can vary wildly based on the direction of interest. In these cases, localization can be based off of the time of arrival distances for each sensor pair. This technique is called Delta T mapping, and is the main focus of this study.
ContributorsBriggs, Nathaniel (Author) / Chattopadhyay, Aditi (Thesis director) / Papandreou-Suppappola, Antonia (Committee member) / Skinner, Travis (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05