Theses and Dissertations
This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students.
Displaying 21 - 30 of 95
Description
In this research, a new cutting edge wear estimator for micro-endmilling is developed and the reliabillity of the estimator is evaluated. The main concept of this estimator is the minimum chip thickness effect. This estimator predicts the cutting edge radius by detecting the drop in the chip production rate as the cutting edge of a micro- endmill slips over the workpiece when the minimum chip thickness becomes larger than the uncut chip thickness, thus transitioning from the shearing to the ploughing dominant regime. The chip production rate is investigated through simulation and experiment. The simulation and the experiment show that the chip production rate decreases when the minimum chip thickness becomes larger than the uncut chip thickness. Also, the reliability of this estimator is evaluated. The probability of correct estimation of the cutting edge radius is more than 80%. This cutting edge wear estimator could be applied to an online tool wear estimation system. Then, a large number of cutting edge wear data could be obtained. From the data, a cutting edge wear model could be developed in terms of the machine control parameters so that the optimum control parameters could be applied to increase the tool life and the machining quality as well by minimizing the cutting edge wear rate.
In addition, in order to find the stable condition of the machining, the stabillity lobe of the system is created by measuring the dynamic parameters. This process is needed prior to the cutting edge wear estimation since the chatter would affect the cutting edge wear and the chip production rate. In this research, a new experimental set-up for measuring the dynamic parameters is developed by using a high speed camera with microscope lens and a loadcell. The loadcell is used to measure the stiffness of the tool-holder assembly of the machine and the high speed camera is used to measure the natural frequency and the damping ratio. From the measured data, a stability lobe is created. Even though this new method needs further research, it could be more cost-effective than the conventional methods in the future.
In addition, in order to find the stable condition of the machining, the stabillity lobe of the system is created by measuring the dynamic parameters. This process is needed prior to the cutting edge wear estimation since the chatter would affect the cutting edge wear and the chip production rate. In this research, a new experimental set-up for measuring the dynamic parameters is developed by using a high speed camera with microscope lens and a loadcell. The loadcell is used to measure the stiffness of the tool-holder assembly of the machine and the high speed camera is used to measure the natural frequency and the damping ratio. From the measured data, a stability lobe is created. Even though this new method needs further research, it could be more cost-effective than the conventional methods in the future.
ContributorsLee, Jue-Hyun (Author) / SODEMANN, ANGELA A (Thesis advisor) / Shuaib, Abdelrahman (Committee member) / Hsu, Keng (Committee member) / Artemiadis, Panagiotis (Committee member) / Liu, Yongming (Committee member) / Arizona State University (Publisher)
Created2019
Description
This investigation focuses on the development of uncertainty modeling methods applicable to both the structural and thermal models of heated structures as part of an effort to enable the design under uncertainty of hypersonic vehicles. The maximum entropy-based nonparametric stochastic modeling approach is used within the context of coupled structural-thermal Reduced Order Models (ROMs). Not only does this strategy allow for a computationally efficient generation of samples of the structural and thermal responses but the maximum entropy approach allows to introduce both aleatoric and some epistemic uncertainty into the system.
While the nonparametric approach has a long history of applications to structural models, the present investigation was the first one to consider it for the heat conduction problem. In this process, it was recognized that the nonparametric approach had to be modified to maintain the localization of the temperature near the heat source, which was successfully achieved.
The introduction of uncertainty in coupled structural-thermal ROMs of heated structures was addressed next. It was first recognized that the structural stiffness coefficients (linear, quadratic, and cubic) and the parameters quantifying the effects of the temperature distribution on the structural response can be regrouped into a matrix that is symmetric and positive definite. The nonparametric approach was then applied to this matrix allowing the assessment of the effects of uncertainty on the resulting temperature distributions and structural response.
The third part of this document focuses on introducing uncertainty using the Maximum Entropy Method at the level of finite element by randomizing elemental matrices, for instance, elemental stiffness, mass and conductance matrices. This approach brings some epistemic uncertainty not present in the parametric approach (e.g., by randomizing the elasticity tensor) while retaining more local character than the operation in ROM level.
The last part of this document focuses on the development of “reduced ROMs” (RROMs) which are reduced order models with small bases constructed in a data-driven process from a “full” ROM with a much larger basis. The development of the RROM methodology is motivated by the desire to optimally reduce the computational cost especially in multi-physics situations where a lack of prior understanding/knowledge of the solution typically leads to the selection of ROM bases that are excessively broad to ensure the necessary accuracy in representing the response. It is additionally emphasized that the ROM reduction process can be carried out adaptively, i.e., differently over different ranges of loading conditions.
While the nonparametric approach has a long history of applications to structural models, the present investigation was the first one to consider it for the heat conduction problem. In this process, it was recognized that the nonparametric approach had to be modified to maintain the localization of the temperature near the heat source, which was successfully achieved.
The introduction of uncertainty in coupled structural-thermal ROMs of heated structures was addressed next. It was first recognized that the structural stiffness coefficients (linear, quadratic, and cubic) and the parameters quantifying the effects of the temperature distribution on the structural response can be regrouped into a matrix that is symmetric and positive definite. The nonparametric approach was then applied to this matrix allowing the assessment of the effects of uncertainty on the resulting temperature distributions and structural response.
The third part of this document focuses on introducing uncertainty using the Maximum Entropy Method at the level of finite element by randomizing elemental matrices, for instance, elemental stiffness, mass and conductance matrices. This approach brings some epistemic uncertainty not present in the parametric approach (e.g., by randomizing the elasticity tensor) while retaining more local character than the operation in ROM level.
The last part of this document focuses on the development of “reduced ROMs” (RROMs) which are reduced order models with small bases constructed in a data-driven process from a “full” ROM with a much larger basis. The development of the RROM methodology is motivated by the desire to optimally reduce the computational cost especially in multi-physics situations where a lack of prior understanding/knowledge of the solution typically leads to the selection of ROM bases that are excessively broad to ensure the necessary accuracy in representing the response. It is additionally emphasized that the ROM reduction process can be carried out adaptively, i.e., differently over different ranges of loading conditions.
ContributorsSong, Pengchao (Author) / Mignolet, Marc P (Thesis advisor) / Smarslok, Benjamin (Committee member) / Chattopadhyay, Aditi (Committee member) / Liu, Yongming (Committee member) / Jiang, Hanqing (Committee member) / Berman, Spring (Committee member) / Arizona State University (Publisher)
Created2019
Description
Advanced material systems refer to materials that are comprised of multiple traditional constituents but complex microstructure morphologies, which lead to their superior properties over conventional materials. This dissertation is motivated by the grand challenge in accelerating the design of advanced material systems through systematic optimization with respect to material microstructures or processing settings. While optimization techniques have mature applications to a large range of engineering systems, their application to material design meets unique challenges due to the high dimensionality of microstructures and the high costs in computing process-structure-property (PSP) mappings. The key to addressing these challenges is the learning of material representations and predictive PSP mappings while managing a small data acquisition budget. This dissertation thus focuses on developing learning mechanisms that leverage context-specific meta-data and physics-based theories. Two research tasks will be conducted: In the first, we develop a statistical generative model that learns to characterize high-dimensional microstructure samples using low-dimensional features. We improve the data efficiency of a variational autoencoder by introducing a morphology loss to the training. We demonstrate that the resultant microstructure generator is morphology-aware when trained on a small set of material samples, and can effectively constrain the microstructure space during material design. In the second task, we investigate an active learning mechanism where new samples are acquired based on their violation to a theory-driven constraint on the physics-based model. We demonstrate using a topology optimization case that while data acquisition through the physics-based model is often expensive (e.g., obtaining microstructures through simulation or optimization processes), the evaluation of the constraint can be far more affordable (e.g., checking whether a solution is optimal or equilibrium). We show that this theory-driven learning algorithm can lead to much improved learning efficiency and generalization performance when such constraints can be derived. The outcomes of this research is a better understanding of how physics knowledge about material systems can be integrated into machine learning frameworks, in order to achieve more cost-effective and reliable learning of material representations and predictive models, which are essential to accelerate computational material design.
ContributorsCang, Ruijin (Author) / Ren, Yi (Thesis advisor) / Liu, Yongming (Committee member) / Jiao, Yang (Committee member) / Nian, Qiong (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2018
Description
Measuring the dynamic strength of a material based on stress and strain data is challenging due to the diculty in recording strain and stress under the short times and large loads typical of dynamic events, such as impact and shock loading. The research involved in this study aims to perform nite element simulations for a new experimental method that can provide information on material dynamic strength, which is crucial for many engineering applications. In this method, a shock wave is applied to a metallic sample with a perturbed surface, i.e, one with periodic ripples machined or etched on the surface. The speed and magnitude of the change of am- plitude of the ripples are recorded. It is known that these parameters are functions of both geometry and material strength. The experimental data are compared with the simulation results produced. The dynamic yield strength of a material is taken to be the same as the strength used in simulations when a close match is found. The simulations have produced results that closely matched the experimental data and predicted the dynamic yield strength of metallic samples and have led to the discov- ery of a new experimental technique to lower the impact velocity required to induce amplitude changes in surface perturbations under shock loading. Thus, shock experi- ments to measure strength using surface perturbations will become easier to conduct and span a wider range of conditions. However, the existing simulation models are not adequate to examine the relations among hardening behavior and the change of amplitude and velocity on the sample surface. Thus, the models should be further modied to study dierent material hardening behaviors under dynamic loadings.
ContributorsChen, Yan (Author) / Peralta, Pedro (Thesis director) / Oswald, Jay (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2014-12
Description
Understanding damage evolution, particularly as it relates to local nucleation and growth kinetics of spall failure in metallic materials subjected to shock loading, is critical to national security. This work uses computational modeling to elucidate what characteristics have the highest impact on damage localization at the microstructural level in metallic materials, since knowledge of these characteristics is critical to improve these materials. The numerical framework consists of a user-defined material model implemented in a user subroutine run in ABAQUS/Explicit that takes into account crystal plasticity, grain boundary effects, void nucleation and initial growth, and both isotropic and kinematic hardening to model incipient spall. Finite element simulations were performed on copper bicrystal models to isolate the boundary effects between two grains. Two types of simulations were performed in this work: experimentally verified cases in order to validate the constitutive model as well as idealized cases in an attempt to determine the microstructural characteristic that define weakest links in terms of spall damage. Grain boundary effects on damage localization were studied by varying grain boundary orientation in respect to the shock direction and the crystallographic properties of each grain in the bicrystal. Varying these parameters resulted in a mismatch in Taylor factor across the grain boundary and along the shock direction. The experimentally verified cases are models of specific damage sites found from flyer plate impact tests on copper multicrystals in which the Taylor factor mismatch across the grain boundary and along the shock direction are both high or both low. For the idealized cases, grain boundary orientation and crystallography of the grains are chosen such that the Taylor factor mismatch in the grain boundary normal and along the shock direction are maximized or minimized. A perpendicular grain boundary orientation in respect to the shock direction maximizes Taylor factor mismatch, while a parallel grain boundary minimizes the mismatch. Furthermore, it is known that <1 1 1> crystals have the highest Taylor factor, while <0 0 1> has nearly the lowest Taylor factor. The permutation of these extremes for mismatch in the grain boundary normal and along the shock direction results in four idealized cases that were studied for this work. Results of the simulations demonstrate that the material model is capable of predicting damage localization, as it has been able to reproduce damage sites found experimentally. However, these results are qualitative since further calibration is still required to produce quantitatively accurate results. Moreover, comparisons of results for void nucleation rate and void growth rate suggests that void nucleation is more influential in the total void volume fraction for bicrystals with high property mismatch across the interface, suggesting that nucleation is the dominant characteristic in the propagation of damage in the material. Further work in recalibrating the simulation parameters and modeling different bicrystal orientations must be done to verify these results.
ContributorsVo, Johnathan Hiep (Author) / Peralta, Pedro (Thesis director) / Oswald, Jay (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2014-12
DescriptionHydrogen diffusion causes brittleness and cracking at stresses below the yield strength of susceptible metals. The effects of hydrostatic loading on the rate of hydrogen diffusion is relatively unknown. A study of these effects will provide a better understanding in the design process for accounting for the resulting hydrogen embrittlement.
ContributorsWalker, Jordan Scot (Author) / Solanki, Kiran (Thesis director) / Oswald, Jay (Committee member) / Adlakha, Ilaksh (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2013-05
Description
Advanced aerospace materials, including fiber reinforced polymer and ceramic matrix composites, are increasingly being used in critical and demanding applications, challenging the current damage prediction, detection, and quantification methodologies. Multiscale computational models offer key advantages over traditional analysis techniques and can provide the necessary capabilities for the development of a comprehensive virtual structural health monitoring (SHM) framework. Virtual SHM has the potential to drastically improve the design and analysis of aerospace components through coupling the complementary capabilities of models able to predict the initiation and propagation of damage under a wide range of loading and environmental scenarios, simulate interrogation methods for damage detection and quantification, and assess the health of a structure. A major component of the virtual SHM framework involves having micromechanics-based multiscale composite models that can provide the elastic, inelastic, and damage behavior of composite material systems under mechanical and thermal loading conditions and in the presence of microstructural complexity and variability. Quantification of the role geometric and architectural variability in the composite microstructure plays in the local and global composite behavior is essential to the development of appropriate scale-dependent unit cells and boundary conditions for the multiscale model. Once the composite behavior is predicted and variability effects assessed, wave-based SHM simulation models serve to provide knowledge on the probability of detection and characterization accuracy of damage present in the composite. The research presented in this dissertation provides the foundation for a comprehensive SHM framework for advanced aerospace materials. The developed models enhance the prediction of damage formation as a result of ceramic matrix composite processing, improve the understanding of the effects of architectural and geometric variability in polymer matrix composites, and provide an accurate and computational efficient modeling scheme for simulating guided wave excitation, propagation, interaction with damage, and sensing in a range of materials. The methodologies presented in this research represent substantial progress toward the development of an accurate and generalized virtual SHM framework.
ContributorsBorkowski, Luke (Author) / Chattopadhyay, Aditi (Thesis advisor) / Liu, Yongming (Committee member) / Mignolet, Marc (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Rajadas, John (Committee member) / Arizona State University (Publisher)
Created2015
Description
Fracture phenomena have been extensively studied in the last several decades. Continuum mechanics-based approaches, such as finite element methods and extended finite element methods, are widely used for fracture simulation. One well-known issue of these approaches is the stress singularity resulted from the spatial discontinuity at the crack tip/front. The requirement of guiding criteria for various cracking behaviors, such as initiation, propagation, and branching, also poses some challenges. Comparing to the continuum based formulation, the discrete approaches, such as lattice spring method, discrete element method, and peridynamics, have certain advantages when modeling various fracture problems due to their intrinsic characteristics in modeling discontinuities.
A novel, alternative, and systematic framework based on a nonlocal lattice particle model is proposed in this study. The uniqueness of the proposed model is the inclusion of both pair-wise local and multi-body nonlocal potentials in the formulation. First, the basic ideas of the proposed framework for 2D isotropic solid are presented. Derivations for triangular and square lattice structure are discussed in detail. Both mechanical deformation and fracture process are simulated and model verification and validation are performed with existing analytical solutions and experimental observations. Following this, the extension to general 3D isotropic solids based on the proposed local and nonlocal potentials is given. Three cubic lattice structures are discussed in detail. Failure predictions using the 3D simulation are compared with experimental testing results and very good agreement is observed. Next, a lattice rotation scheme is proposed to account for the material orientation in modeling anisotropic solids. The consistency and difference compared to the classical material tangent stiffness transformation method are discussed in detail. The implicit and explicit solution methods for the proposed lattice particle model are also discussed. Finally, some conclusions and discussions based on the current study are drawn at the end.
A novel, alternative, and systematic framework based on a nonlocal lattice particle model is proposed in this study. The uniqueness of the proposed model is the inclusion of both pair-wise local and multi-body nonlocal potentials in the formulation. First, the basic ideas of the proposed framework for 2D isotropic solid are presented. Derivations for triangular and square lattice structure are discussed in detail. Both mechanical deformation and fracture process are simulated and model verification and validation are performed with existing analytical solutions and experimental observations. Following this, the extension to general 3D isotropic solids based on the proposed local and nonlocal potentials is given. Three cubic lattice structures are discussed in detail. Failure predictions using the 3D simulation are compared with experimental testing results and very good agreement is observed. Next, a lattice rotation scheme is proposed to account for the material orientation in modeling anisotropic solids. The consistency and difference compared to the classical material tangent stiffness transformation method are discussed in detail. The implicit and explicit solution methods for the proposed lattice particle model are also discussed. Finally, some conclusions and discussions based on the current study are drawn at the end.
ContributorsChen, Hailong (Author) / Liu, Yongming (Thesis advisor) / Jiao, Yang (Committee member) / Mignolet, Marc (Committee member) / Oswald, Jay (Committee member) / Solanki, Kiran (Committee member) / Arizona State University (Publisher)
Created2015
Description
In this thesis, a FORTRAN code is rewritten in C++ with an object oriented ap-
proach. There are several reasons for this purpose. The first reason is to establish
the basis of a GPU programming. To write programs that utilize GPU hardware,
CUDA or OpenCL is used which only support C and C++. FORTRAN has a feature
that lets its programs to call C/C++ functions. FORTRAN sends relevant data to
C/C++, which in turn sends that data to OpenCL. Although this approach works,
it makes the code messy and bulky and in the end more difficult to deal with. More-
over, there is a slight performance decrease from the additional data copy. This is
the motivation to have the code entirely written in C++ to make it more uniform,
efficient and clean. The second reason is the object oriented feature of the C++. The
“abstraction”, “inheritance” and “run-time polymorphism” features of C++ provide
some form of classes and objects, the ability to build new abstractions, and some
form of run-time binding, respectively. In recent years, some of popular codes has
been rewritten in C++ which were initially in FORTRAN. One of these softwares is
LAMMPS.
In this code the level set equation is solved by RLSG method to track the interface in
two phase flow. In gas/fluid flows, the surface tension is important and only exists at
the interface. Therefore, the location and some geometric features of interface need
to be evaluated which can be achieved by solving the level set equation.
proach. There are several reasons for this purpose. The first reason is to establish
the basis of a GPU programming. To write programs that utilize GPU hardware,
CUDA or OpenCL is used which only support C and C++. FORTRAN has a feature
that lets its programs to call C/C++ functions. FORTRAN sends relevant data to
C/C++, which in turn sends that data to OpenCL. Although this approach works,
it makes the code messy and bulky and in the end more difficult to deal with. More-
over, there is a slight performance decrease from the additional data copy. This is
the motivation to have the code entirely written in C++ to make it more uniform,
efficient and clean. The second reason is the object oriented feature of the C++. The
“abstraction”, “inheritance” and “run-time polymorphism” features of C++ provide
some form of classes and objects, the ability to build new abstractions, and some
form of run-time binding, respectively. In recent years, some of popular codes has
been rewritten in C++ which were initially in FORTRAN. One of these softwares is
LAMMPS.
In this code the level set equation is solved by RLSG method to track the interface in
two phase flow. In gas/fluid flows, the surface tension is important and only exists at
the interface. Therefore, the location and some geometric features of interface need
to be evaluated which can be achieved by solving the level set equation.
ContributorsSafarkhani, Salar (Author) / Herrmann, Mrcus (Thesis advisor) / Oswald, Jay (Committee member) / Rykczewski, Konrad (Committee member) / Arizona State University (Publisher)
Created2015
Description
Polymer matrix composites (PMCs) are attractive structural materials due to their high stiffness to low weight ratio. However, unidirectional PMCs have low shear strength and failure can occur along kink bands that develop on compression due to plastic microbuckling that carry strains large enough to induce nonlinear matrix deformation. Reviewing the literature, a large fraction of the existing work is for uniaxial compression, and the effects of stress gradients, such as those present during bending, have not been as well explored, and these effects are bound to make difference in terms of kink band nucleation and growth. Furthermore, reports on experimental measurements of strain fields leading to and developing inside these bands in the presence of stress gradients are also scarce and need to be addressed to gain a full understanding of their behavior when UDCs are used under bending and other spatially complex stress states.
In a light to bridge the aforementioned gaps, the primary focus of this work is to understand mechanisms for kink band evolution under an influence of stress-gradients induced during bending. Digital image correlation (DIC) is used to measure strains inside and around the kink bands during 3-point bending of samples with 0°/90° stacking made of Ultra-High Molecular Weight Polyethylene Fibers. Measurements indicate bands nucleate at the compression side and propagate into the sample carrying a mixture of large shear and normal strains (~33%), while also decreasing its bending stiffness. Failure was produced by a combination of plastic microbuckling and axial splitting. The microstructure of the kink bands was studied and used in a microstructurally explicit finite element model (FEM) to analyze stresses and strains at ply level in the samples during kink band evolution, using cohesive zone elements to represent the interfaces between plies. Cohesive element properties were deduced by a combination of delamination, fracture and three-point bending tests used to calibrate the FEMs. Modeling results show that the band morphology is sensitive to the shear and opening properties of the interfaces between the plies.
In a light to bridge the aforementioned gaps, the primary focus of this work is to understand mechanisms for kink band evolution under an influence of stress-gradients induced during bending. Digital image correlation (DIC) is used to measure strains inside and around the kink bands during 3-point bending of samples with 0°/90° stacking made of Ultra-High Molecular Weight Polyethylene Fibers. Measurements indicate bands nucleate at the compression side and propagate into the sample carrying a mixture of large shear and normal strains (~33%), while also decreasing its bending stiffness. Failure was produced by a combination of plastic microbuckling and axial splitting. The microstructure of the kink bands was studied and used in a microstructurally explicit finite element model (FEM) to analyze stresses and strains at ply level in the samples during kink band evolution, using cohesive zone elements to represent the interfaces between plies. Cohesive element properties were deduced by a combination of delamination, fracture and three-point bending tests used to calibrate the FEMs. Modeling results show that the band morphology is sensitive to the shear and opening properties of the interfaces between the plies.
ContributorsPatel, Jay K (Author) / Peralta, Pedro D (Thesis advisor) / Oswald, Jay (Committee member) / Jiang, Hanqing (Committee member) / Solanki, Kiran (Committee member) / Ayyar, Adarsh (Committee member) / Arizona State University (Publisher)
Created2016