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- Genre: Doctoral Dissertation
Stochastic multiscale modeling and statistical characterization of complex polymer matrix composites
Description
There are many applications for polymer matrix composite materials in a variety of different industries, but designing and modeling with these materials remains a challenge due to the intricate architecture and damage modes. Multiscale modeling techniques of composite structures subjected to complex loadings are needed in order to address the scale-dependent behavior and failure. The rate dependency and nonlinearity of polymer matrix composite materials further complicates the modeling. Additionally, variability in the material constituents plays an important role in the material behavior and damage. The systematic consideration of uncertainties is as important as having the appropriate structural model, especially during model validation where the total error between physical observation and model prediction must be characterized. It is necessary to quantify the effects of uncertainties at every length scale in order to fully understand their impact on the structural response. Material variability may include variations in fiber volume fraction, fiber dimensions, fiber waviness, pure resin pockets, and void distributions. Therefore, a stochastic modeling framework with scale dependent constitutive laws and an appropriate failure theory is required to simulate the behavior and failure of polymer matrix composite structures subjected to complex loadings. Additionally, the variations in environmental conditions for aerospace applications and the effect of these conditions on the polymer matrix composite material need to be considered. The research presented in this dissertation provides the framework for stochastic multiscale modeling of composites and the characterization data needed to determine the effect of different environmental conditions on the material properties. The developed models extend sectional micromechanics techniques by incorporating 3D progressive damage theories and multiscale failure criteria. The mechanical testing of composites under various environmental conditions demonstrates the degrading effect these conditions have on the elastic and failure properties of the material. The methodologies presented in this research represent substantial progress toward understanding the failure and effect of variability for complex polymer matrix composites.
ContributorsJohnston, Joel Philip (Author) / Chattopadhyay, Aditi (Thesis advisor) / Liu, Yongming (Committee member) / Jiang, Hanqing (Committee member) / Dai, Lenore (Committee member) / Rajadas, John (Committee member) / Arizona State University (Publisher)
Created2016
Description
This investigation develops small-size reduced order models (ROMs) that provide an accurate prediction of the response of only part of a structure, referred to as component-centric ROMs. Four strategies to construct such ROMs are presented, the first two of which are based on the Craig-Bampton Method and start with a set of modes for the component of interest (the β component). The response in the rest of the structure (the α component) induced by these modes is then determined and optimally represented by applying a Proper Orthogonal Decomposition strategy using Singular Value Decomposition. These first two methods are effectively basis reductions techniques of the CB basis. An approach based on the “Global - Local” Method generates the “global” modes by “averaging” the mass property over α and β comp., respectively (to extract a “coarse” model of α and β) and the “local” modes orthogonal to the “global” modes to add back necessary “information” for β. The last approach adopts as basis for the entire structure its linear modes which are dominant in the β component response. Then, the contributions of other modes in this part of the structure are approximated in terms of those of the dominant modes with close natural frequencies and similar mode shapes in the β component. In this manner, the non-dominant modal contributions are “lumped” onto the dominant ones, to reduce the number of modes for a prescribed accuracy. The four approaches are critically assessed on the structural finite element model of a 9-bay panel with the modal lumping-based method leading to the smallest sized ROMs. Therefore, it is extended to the nonlinear geometric situation and first recast as a rotation of the modal basis to achieve unobservable modes. In the linear case, these modes completely disappear from the formulation owing to orthogonality. In the nonlinear case, however, the generalized coordinates of these modes are still present in the nonlinear terms of the observable modes. A closure-type algorithm is then proposed to eliminate the unobserved generalized coordinates. This approach, its accuracy and computational savings, was demonstrated on a simple beam model and the 9-bay panel model.
ContributorsWang, Yuting (Author) / Mignolet, Marc P (Thesis advisor) / Jiang, Hanqing (Committee member) / Liu, Yongming (Committee member) / Oswald, Jay (Committee member) / Rajan, Subramaniam D. (Committee member) / Spottswood, Stephen M (Committee member) / Arizona State University (Publisher)
Created2017
Description
A hybrid molecular dynamics (MD) simulation framework is developed to emulate mechanochemical reaction of mechanophores in epoxy-based nanocomposites. Two different force fields, a classical force field and a bond order based force field are hybridized to mimic the experimental processes from specimen preparation to mechanical loading test. Ultra-violet photodimerization for mechanophore synthesis and epoxy curing for thermoset polymer generation are successfully simulated by developing a numerical covalent bond generation method using the classical force field within the framework. Mechanical loading tests to activate mechanophores are also virtually conducted by deforming the volume of a simulation unit cell. The unit cell deformation leads to covalent bond elongation and subsequent bond breakage, which is captured using the bond order based force field. The outcome of the virtual loading test is used for local work analysis, which enables a quantitative study of mechanophore activation. Through the local work analysis, the onset and evolution of mechanophore activation indicating damage initiation and propagation are estimated; ultimately, the mechanophore sensitivity to external stress is evaluated. The virtual loading tests also provide accurate estimations of mechanical properties such as elastic, shear, bulk modulus, yield strain/strength, and Poisson’s ratio of the system. Experimental studies are performed in conjunction with the simulation work to validate the hybrid MD simulation framework. Less than 2% error in estimations of glass transition temperature (Tg) is observed with experimentally measured Tgs by use of differential scanning calorimetry. Virtual loading tests successfully reproduce the stress-strain curve capturing the effect of mechanophore inclusion on mechanical properties of epoxy polymer; comparable changes in Young’s modulus and yield strength are observed in experiments and simulations. Early damage signal detection, which is identified in experiments by observing increased intensity before the yield strain, is captured in simulations by showing that the critical strain representing the onset of the mechanophore activation occurs before the estimated yield strain. It is anticipated that the experimentally validated hybrid MD framework presented in this dissertation will provide a low-cost alternative to additional experiments that are required for optimizing material design parameters to improve damage sensing capability and mechanical properties.
In addition to the study of mechanochemical reaction analysis, an atomistic model of interphase in carbon fiber reinforced composites is developed. Physical entanglement between semi-crystalline carbon fiber surface and polymer matrix is captured by introducing voids in multiple graphene layers, which allow polymer matrix to intertwine with graphene layers. The hybrid MD framework is used with some modifications to estimate interphase properties that include the effect of the physical entanglement. The results are compared with existing carbon fiber surface models that assume that carbon fiber has a crystalline structure and hence are unable to capture the physical entanglement. Results indicate that the current model shows larger stress gradients across the material interphase. These large stress gradients increase the viscoplasticity and damage effects at the interphase. The results are important for improved prediction of the nonlinear response and damage evolution in composite materials.
In addition to the study of mechanochemical reaction analysis, an atomistic model of interphase in carbon fiber reinforced composites is developed. Physical entanglement between semi-crystalline carbon fiber surface and polymer matrix is captured by introducing voids in multiple graphene layers, which allow polymer matrix to intertwine with graphene layers. The hybrid MD framework is used with some modifications to estimate interphase properties that include the effect of the physical entanglement. The results are compared with existing carbon fiber surface models that assume that carbon fiber has a crystalline structure and hence are unable to capture the physical entanglement. Results indicate that the current model shows larger stress gradients across the material interphase. These large stress gradients increase the viscoplasticity and damage effects at the interphase. The results are important for improved prediction of the nonlinear response and damage evolution in composite materials.
ContributorsKoo, Bonsung (Author) / Chattopadhyay, Aditi (Thesis advisor) / Dai, Lenore (Committee member) / Jiang, Hanqing (Committee member) / Jiao, Yang (Committee member) / Rajadas, John (Committee member) / Arizona State University (Publisher)
Created2017
Description
The Very High Temperature Reactor (VHTR) is one of six conceptual designs proposed for Generation IV nuclear reactors. Alloy 617, a solid solution strengthened Ni-base superalloy, is currently the primary candidate material for the tubing of the Intermediate Heat Exchanger (IHX) in the VHTR design. Steady-state operation of the nuclear power plant at elevated temperatures leads to creep deformation, whereas loading transients including startup and shutdown generate fatigue. A detailed understanding of the creep-fatigue interaction in Alloy 617 is necessary before it can be considered as a material for nuclear construction in ASME Boiler and Pressure Vessel Code. Current design codes for components undergoing creep-fatigue interaction at elevated temperatures require creep-fatigue testing data covering the entire range from fatigue-dominant to creep-dominant loading. Classical strain-controlled tests, which produce stress relaxation during the hold period, show a saturation in cycle life with increasing hold periods due to the rapid stress-relaxation of Alloy 617 at high temperatures. Therefore, applying longer hold time in these tests cannot generate creep-dominated failure. In this study, uniaxial isothermal creep-fatigue tests with non-traditional loading waveforms were designed and performed at 850 and 950°C, with an objective of generating test data in the creep-dominant regime. The new loading waveforms are hybrid strain-controlled and force-controlled testing which avoid stress relaxation during the creep hold. The experimental data showed varying proportions of creep and fatigue damage, and provided evidence for the inadequacy of the widely-used time fraction rule for estimating creep damage under creep-fatigue conditions. Micro-scale damage features in failed test specimens, such as fatigue cracks and creep voids, were quantified using a Scanning Electron Microscope (SEM) to find a correlation between creep and fatigue damage. Quantitative statistical imaging analysis showed that the microstructural damage features (cracks and voids) are correlated with a new mechanical driving force parameter. The results from this image-based damage analysis were used to develop a phenomenological life-prediction methodology called the effective time fraction approach. Finally, the constitutive creep-fatigue response of the material at 950°C was modeled using a unified viscoplastic model coupled with a damage accumulation model. The simulation results were used to validate an energy-based constitutive life-prediction model, as a mechanistic model for potential component and structure level creep-fatigue analysis.
ContributorsTahir, Fraaz (Author) / Liu, Yongming (Thesis advisor) / Jiang, Hanqing (Committee member) / Rajagopalan, Jagannathan (Committee member) / Oswald, Jay (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2017
Description
The focus of this investigation includes three aspects. First, the development of nonlinear reduced order modeling techniques for the prediction of the response of complex structures exhibiting "large" deformations, i.e. a geometrically nonlinear behavior, and modeled within a commercial finite element code. The present investigation builds on a general methodology, successfully validated in recent years on simpler panel structures, by developing a novel identification strategy of the reduced order model parameters, that enables the consideration of the large number of modes needed for complex structures, and by extending an automatic strategy for the selection of the basis functions used to represent accurately the displacement field. These novel developments are successfully validated on the nonlinear static and dynamic responses of a 9-bay panel structure modeled within Nastran. In addition, a multi-scale approach based on Component Mode Synthesis methods is explored. Second, an assessment of the predictive capabilities of nonlinear reduced order models for the prediction of the large displacement and stress fields of panels that have a geometric discontinuity; a flat panel with a notch was used for this assessment. It is demonstrated that the reduced order models of both virgin and notched panels provide a close match of the displacement field obtained from full finite element analyses of the notched panel for moderately large static and dynamic responses. In regards to stresses, it is found that the notched panel reduced order model leads to a close prediction of the stress distribution obtained on the notched panel as computed by the finite element model. Two enrichment techniques, based on superposition of the notch effects on the virgin panel stress field, are proposed to permit a close prediction of the stress distribution of the notched panel from the reduced order model of the virgin one. A very good prediction of the full finite element results is achieved with both enrichments for static and dynamic responses. Finally, computational challenges associated with the solution of the reduced order model equations are discussed. Two alternatives to reduce the computational time for the solution of these problems are explored.
ContributorsPerez, Ricardo Angel (Author) / Mignolet, Marc (Thesis advisor) / Oswald, Jay (Committee member) / Spottswood, Stephen (Committee member) / Peralta, Pedro (Committee member) / Jiang, Hanqing (Committee member) / Arizona State University (Publisher)
Created2012
Description
The rheological properties at liquid-liquid interfaces are important in many industrial processes such as manufacturing foods, pharmaceuticals, cosmetics, and petroleum products. This dissertation focuses on the study of linear viscoelastic properties at liquid-liquid interfaces by tracking the thermal motion of particles confined at the interfaces. The technique of interfacial microrheology is first developed using one- and two-particle tracking, respectively. In one-particle interfacial microrheology, the rheological response at the interface is measured from the motion of individual particles. One-particle interfacial microrheology at polydimethylsiloxane (PDMS) oil-water interfaces depends strongly on the surface chemistry of different tracer particles. In contrast, by tracking the correlated motion of particle pairs, two-particle interfacial microrheology significantly minimizes the effects from tracer particle surface chemistry and particle size. Two-particle interfacial microrheology is further applied to study the linear viscoelastic properties of immiscible polymer-polymer interfaces. The interfacial loss and storage moduli at PDMS-polyethylene glycol (PEG) interfaces are measured over a wide frequency range. The zero-shear interfacial viscosity, estimated from the Cross model, falls between the bulk viscosities of two individual polymers. Surprisingly, the interfacial relaxation time is observed to be an order of magnitude larger than that of the PDMS bulk polymers. To explore the fundamental basis of interfacial nanorheology, molecular dynamics (MD) simulations are employed to investigate the nanoparticle dynamics. The diffusion of single nanoparticles in pure water and low-viscosity PDMS oils is reasonably consistent with the prediction by the Stokes-Einstein equation. To demonstrate the potential of nanorheology based on the motion of nanoparticles, the shear moduli and viscosities of the bulk phases and interfaces are calculated from single-nanoparticle tracking. Finally, the competitive influences of nanoparticles and surfactants on other interfacial properties, such as interfacial thickness and interfacial tension are also studied by MD simulations.
ContributorsSong, Yanmei (Author) / Dai, Lenore L (Thesis advisor) / Jiang, Hanqing (Committee member) / Lin, Jerry Y S (Committee member) / Raupp, Gregory B (Committee member) / Sierks, Michael R (Committee member) / Arizona State University (Publisher)
Created2011
Description
Different environmental factors, such as ultraviolet radiation (UV), relative humidity (RH) and the presence of reducing gases (acetone and ethanol), play an important role in the daily life of human beings. UV is very important in a number of areas, such as astronomy, resin curing of polymeric materials, combustion engineering, water purification, flame detection and biological effects with more recent proposals like early missile plume detection, secure space-to-space communications and pollution monitoring. RH is a very common parameter in the environment. It is essential not only for human comfort, but also for a broad spectrum of industries and technologies. There is a substantial interest in the development of RH sensors for applications in monitoring moisture level at home, in clean rooms, cryogenic processes, medical and food science, and so on. The concentration of acetone and other ketone bodies in the exhaled air can serve as an express noninvasive diagnosis of ketosis. Meanwhile, driving under the influence of alcohol is a serious traffic violation and this kind of deviant behavior causes many accidents and deaths on the highway. Therefore, the detection of ethanol in breath is usually used as a quick and reliable screening method for the sobriety checkpoint. Traditionally, semiconductor metal oxide sensors are the major candidates employed in the sensing applications mentioned above. However, they suffer from the low sensitivity, poor selectivity and huge power consumption. In this dissertation, Zinc Oxide (ZnO) based Film Bulk Acoustic Resonator (FBAR) was developed to monitor UV, RH, acetone and ethanol in the environment. FBAR generally consists of a sputtered piezoelectric thin film (ZnO/AlN) sandwiched between two electrodes. It has been well developed both as filters and as high sensitivity mass sensors in recent years. FBAR offers high sensitivity and excellent selectivity for various environment monitoring applications. As the sensing signal is in the frequency domain, FABR has the potential to be incorporated in a wireless sensor network for remote sensing. This study extended our current knowledge of FBAR and pointed out feasible directions for future exploration.
ContributorsQiu, Xiaotun (Author) / Yu, Hongyu (Thesis advisor) / Christen, Jennifer Blain (Committee member) / Aberle, James T., 1961- (Committee member) / Jiang, Hanqing (Committee member) / Arizona State University (Publisher)
Created2011
Description
Soft materials are matters that can easily deform from their original shapes and structures under thermal or mechanical stresses, and they range across various groups of materials including liquids, foams, gels, colloids, polymers, and biological substances. Although soft materials already have numerous applications with each of their unique characteristics, integrating materials to achieve complementary functionalities is still a growing need for designing advanced applications of complex requirements. This dissertation explores a unique approach of utilizing intermolecular interactions to accomplish not only the multifunctionality from combined materials but also their tailored properties designed for specific tasks. In this work, multifunctional soft materials are explored in two particular directions, ionic liquids (ILs)-based mixtures and interpenetrating polymer network (IPN).
First, ILs-based mixtures were studied to develop liquid electrolytes for molecular electronic transducers (MET) in planetary exploration. For space missions, it is challenging to operate any liquid electrolytes in an extremely low-temperature environment. By tuning intermolecular interactions, the results demonstrated a facile method that has successfully overcome the thermal and transport barriers of ILs-based mixtures at extremely low temperatures. Incorporation of both aqueous and organic solvents in ILs-based electrolyte systems with varying types of intermolecular interactions are investigated, respectively, to yield optimized material properties supporting not only MET sensors but also other electrochemical devices with iodide/triiodide redox couple targeting low temperatures.
Second, an environmentally responsive hydrogel was synthesized via interpenetrating two crosslinked polymer networks. The intermolecular interactions facilitated by such an IPN structure enables not only an upper critical solution temperature (UCST) transition but also a mechanical enhancement of the hydrogel. The incorporation of functional units validates a positive swelling response to visible light and also further improves the mechanical properties. This studied IPN system can serve as a promising route in developing “smart” hydrogels utilizing visible light as a simple, inexpensive, and remotely controllable stimulus.
Over two directions across from ILs to polymeric networks, this work demonstrates an effective strategy of utilizing intermolecular interactions to not only develop multifunctional soft materials for advanced applications but also discover new properties beyond their original boundaries.
First, ILs-based mixtures were studied to develop liquid electrolytes for molecular electronic transducers (MET) in planetary exploration. For space missions, it is challenging to operate any liquid electrolytes in an extremely low-temperature environment. By tuning intermolecular interactions, the results demonstrated a facile method that has successfully overcome the thermal and transport barriers of ILs-based mixtures at extremely low temperatures. Incorporation of both aqueous and organic solvents in ILs-based electrolyte systems with varying types of intermolecular interactions are investigated, respectively, to yield optimized material properties supporting not only MET sensors but also other electrochemical devices with iodide/triiodide redox couple targeting low temperatures.
Second, an environmentally responsive hydrogel was synthesized via interpenetrating two crosslinked polymer networks. The intermolecular interactions facilitated by such an IPN structure enables not only an upper critical solution temperature (UCST) transition but also a mechanical enhancement of the hydrogel. The incorporation of functional units validates a positive swelling response to visible light and also further improves the mechanical properties. This studied IPN system can serve as a promising route in developing “smart” hydrogels utilizing visible light as a simple, inexpensive, and remotely controllable stimulus.
Over two directions across from ILs to polymeric networks, this work demonstrates an effective strategy of utilizing intermolecular interactions to not only develop multifunctional soft materials for advanced applications but also discover new properties beyond their original boundaries.
ContributorsXu, Yifei (Author) / Dai, Lenore L. (Thesis advisor) / Forzani, Erica (Committee member) / Holloway, Julianne (Committee member) / Jiang, Hanqing (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2020
Description
Though a single mode of energy transfer, optical radiation meaningfully interacts with its surrounding environment at over a wide range of physical length scales. For this reason, its reconstruction and measurement are of great importance in remote sensing, as these multi-scale interactions encode a great deal of information about distant objects, surfaces, and physical phenomena. For some remote sensing applications, obtaining a desired quantity of interest does not necessitate the explicit mapping of each point in object space to an image space with lenses or mirrors. Instead, only edge rays or physical boundaries of the sensing instrument are considered, while the spatial intensity distribution of optical energy received from a distant object informs its position, optical characteristics, or physical/chemical state.
Admittedly specialized, the principals and consequences of non-imaging optics are nevertheless applicable to heterogeneous semiconductor integration and automotive light detection and ranging (LiDAR), two important emerging technologies. Indeed, a review of relevant engineering literature finds two under-addressed remote sensing challenges. The semiconductor industry lacks an optical strain metrology with displacement resolution smaller than 100 nanometers capable of measuring strain fields between high-density interconnect lines. Meanwhile, little attention is paid to the per-meter sensing characteristics of scene-illuminating flash LiDAR in the context of automotive applications, despite the technology’s much lower cost. It is here that non-imaging optics offers intriguing instrument design and explanations of observed sensor performance at vastly different length scales.
In this thesis, an effective non-contact technique for mapping nanoscale mechanical strain fields and out-of-plane surface warping via laser diffraction is demonstrated, with application as a novel metrology for next-generation semiconductor packages. Additionally, object detection distance of low-cost automotive flash LiDAR, on the order of tens of meters, is understood though principals of optical energy transfer from the surface of a remote object to an extended multi-segment detector. Such information is of consequence when designing an automotive perception system to recognize various roadway objects in low-light scenarios.
Admittedly specialized, the principals and consequences of non-imaging optics are nevertheless applicable to heterogeneous semiconductor integration and automotive light detection and ranging (LiDAR), two important emerging technologies. Indeed, a review of relevant engineering literature finds two under-addressed remote sensing challenges. The semiconductor industry lacks an optical strain metrology with displacement resolution smaller than 100 nanometers capable of measuring strain fields between high-density interconnect lines. Meanwhile, little attention is paid to the per-meter sensing characteristics of scene-illuminating flash LiDAR in the context of automotive applications, despite the technology’s much lower cost. It is here that non-imaging optics offers intriguing instrument design and explanations of observed sensor performance at vastly different length scales.
In this thesis, an effective non-contact technique for mapping nanoscale mechanical strain fields and out-of-plane surface warping via laser diffraction is demonstrated, with application as a novel metrology for next-generation semiconductor packages. Additionally, object detection distance of low-cost automotive flash LiDAR, on the order of tens of meters, is understood though principals of optical energy transfer from the surface of a remote object to an extended multi-segment detector. Such information is of consequence when designing an automotive perception system to recognize various roadway objects in low-light scenarios.
ContributorsHoughton, Todd Kristopher (Author) / Yu, Hongbin (Thesis advisor) / Jiang, Hanqing (Committee member) / Jayasuriya, Suren (Committee member) / Zhang, Liang (Committee member) / Arizona State University (Publisher)
Created2020
Description
Polyurea is a highly versatile material used in coatings and armor systems to protect against extreme conditions such as ballistic impact, cavitation erosion, and blast loading. However, the relationships between microstructurally-dependent deformation mechanisms and the mechanical properties of polyurea are not yet fully understood, especially under extreme conditions. In this work, multi-scale coarse-grained models are developed to probe molecular dynamics across the wide range of time and length scales that these fundamental deformation mechanisms operate. In the first of these models, a high-resolution coarse-grained model of polyurea is developed, where similar to united-atom models, hydrogen atoms are modeled implicitly. This model was trained using a modified iterative Boltzmann inversion method that dramatically reduces the number of iterations required. Coarse-grained simulations using this model demonstrate that multiblock systems evolve to form a more interconnected hard phase, compared to the more interrupted hard phase composed of distinct ribbon-shaped domains found in diblock systems. Next, a reactive coarse-grained model is developed to simulate the influence of the difference in time scales for step-growth polymerization and phase segregation in polyurea. Analysis of the simulated cured polyurea systems reveals that more rapid reaction rates produce a smaller diameter ligaments in the gyroidal hard phase as well as increased covalent bonding connecting the hard domain ligaments as evidenced by a larger fraction of bridging segments and larger mean radius of gyration of the copolymer chains. The effect that these processing-induced structural variations have on the mechanical properties of the polymer was tested by simulating uniaxial compression, which revealed that the higher degree of hard domain connectivity leads to a 20% increase in the flow stress. A hierarchical multiresolution framework is proposed to fully link coarse-grained molecular simulations across a broader range of time scales, in which a family of coarse-grained models are developed. The models are connected using an incremental reverse–mapping scheme allowing for long time scale dynamics simulated at a highly coarsened resolution to be passed all the way to an atomistic representation.
ContributorsLiu, Minghao (Author) / Oswald, Jay (Thesis advisor) / Muhich, Christopher (Committee member) / Jiang, Hanqing (Committee member) / Peralta, Pedro (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2020