Matching Items (37)
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- All Subjects: Mechanical Engineering
- Genre: Doctoral Dissertation
- Creators: Liu, Yongming
Description
Locomotion of microorganisms is commonly observed in nature and some aspects of their motion can be replicated by synthetic motors. Synthetic motors rely on a variety of propulsion mechanisms including auto-diffusiophoresis, auto-electrophoresis, and bubble generation. Regardless of the source of the locomotion, the motion of any motor can be characterized by the translational and rotational velocity and effective diffusivity. In a uniform environment the long-time motion of a motor can be fully characterized by the effective diffusivity. In this work it is shown that when motors possess both translational and rotational velocity the motor transitions from a short-time diffusivity to a long-time diffusivity at a time of pi/w. The short-time diffusivities are two to three orders of magnitude larger than the diffusivity of a Brownian sphere of the same size, increase linearly with concentration, and scale as v^2/2w. The measured long-time diffusivities are five times lower than the short-time diffusivities, scale as v^2/{2Dr [1 + (w/Dr )^2]}, and exhibit a maximum as a function of concentration. The variation of a colloid's velocity and effective diffusivity to its local environment (e.g. fuel concentration) suggests that the motors can accumulate in a bounded system, analogous to biological chemokinesis. Chemokinesis of organisms is the non-uniform equilibrium concentration that arises from a bounded random walk of swimming organisms in a chemical concentration gradient. In non-swimming organisms we term this response diffusiokinesis. We show that particles that migrate only by Brownian thermal motion are capable of achieving non-uniform pseudo equilibrium distribution in a diffusivity gradient. The concentration is a result of a bounded random-walk process where at any given time a larger percentage of particles can be found in the regions of low diffusivity than in regions of high diffusivity. Individual particles are not trapped in any given region but at equilibrium the net flux between regions is zero. For Brownian particles the gradient in diffusivity is achieved by creating a viscosity gradient in a microfluidic device. The distribution of the particles is described by the Fokker-Planck equation for variable diffusivity. The strength of the probe concentration gradient is proportional to the strength of the diffusivity gradient and inversely proportional to the mean probe diffusivity in the channel in accordance with the no flux condition at steady state. This suggests that Brownian colloids, natural or synthetic, will concentrate in a bounded system in response to a gradient in diffusivity and that the magnitude of the response is proportional to the magnitude of the gradient in diffusivity divided by the mean diffusivity in the channel.
ContributorsMarine, Nathan Arasmus (Author) / Posner, Jonathan D (Thesis advisor) / Adrian, Ronald J (Committee member) / Frakes, David (Committee member) / Phelan, Patrick E (Committee member) / Santos, Veronica J (Committee member) / Arizona State University (Publisher)
Created2013
Description
Structural features of canonical wall-bounded turbulent flows are described using several techniques, including proper orthogonal decomposition (POD). The canonical wall-bounded turbulent flows of channels, pipes, and flat-plate boundary layers include physics important to a wide variety of practical fluid flows with a minimum of geometric complications. Yet, significant questions remain for their turbulent motions' form, organization to compose very long motions, and relationship to vortical structures. POD extracts highly energetic structures from flow fields and is one tool to further understand the turbulence physics. A variety of direct numerical simulations provide velocity fields suitable for detailed analysis. Since POD modes require significant interpretation, this study begins with wall-normal, one-dimensional POD for a set of turbulent channel flows. Important features of the modes and their scaling are interpreted in light of flow physics, also leading to a method of synthesizing one-dimensional POD modes. Properties of a pipe flow simulation are then studied via several methods. The presence of very long streamwise motions is assessed using a number of statistical quantities, including energy spectra, which are compared to experiments. Further properties of energy spectra, including their relation to fictitious forces associated with mean Reynolds stress, are considered in depth. After reviewing salient features of turbulent structures previously observed in relevant experiments, structures in the pipe flow are examined in greater detail. A variety of methods reveal organization patterns of structures in instantaneous fields and their associated vortical structures. Properties of POD modes for a boundary layer flow are considered. Finally, very wide modes that occur when computing POD modes in all three canonical flows are compared. The results demonstrate that POD extracts structures relevant to characterizing wall-bounded turbulent flows. However, significant care is necessary in interpreting POD results, for which modes can be categorized according to their self-similarity. Additional analysis techniques reveal the organization of smaller motions in characteristic patterns to compose very long motions in pipe flows. The very large scale motions are observed to contribute large fractions of turbulent kinetic energy and Reynolds stress. The associated vortical structures possess characteristics of hairpins, but are commonly distorted from pristine hairpin geometries.
ContributorsBaltzer, Jon Ronald (Author) / Adrian, Ronald J (Thesis advisor) / Calhoun, Ronald (Committee member) / Gelb, Anne (Committee member) / Herrmann, Marcus (Committee member) / Squires, Kyle D (Committee member) / Arizona State University (Publisher)
Created2012
Description
The objective of this research is to develop robust, accurate, and adaptive algorithms in the framework of the extended finite element method (XFEM) for fracture analysis of highly heterogeneous materials with complex internal geometries. A key contribution of this work is the creation of novel methods designed to automate the incorporation of high-resolution data, e.g. from X-ray tomography, that can be used to better interpret the enormous volume of data generated in modern in-situ experimental testing. Thus new algorithms were developed for automating analysis of complex microstructures characterized by segmented tomographic images.
A centrality-based geometry segmentation algorithm was developed to accurately identify discrete inclusions and particles in composite materials where limitations in imaging resolution leads to spurious connections between particles in close contact.To allow for this algorithm to successfully segment geometry independently of particle size and shape, a relative centrality metric was defined to allow for a threshold centrality criterion for removal of voxels that spuriously connect distinct geometries.
To automate incorporation of microstructural information from high-resolution images, two methods were developed that initialize signed distance fields on adaptively-refined finite element meshes. The first method utilizes a level set evolution equation that is directly solved on the finite element mesh through Galerkins method. The evolution equation is formulated to produce a signed distance field that matches geometry defined by a set of voxels segmented from tomographic images. The method achieves optimal convergence for the order of elements used. In a second approach, the fast marching method is employed to initialize a distance field on a uniform grid which is then projected by least squares onto a finite element mesh. This latter approach is shown to be superior in speed and accuracy.
Lastly, extended finite element method simulations are performed for the analysis of particle fracture in metal matrix composites with realistic particle geometries initialized from X-ray tomographic data. In the simulations, particles fracture probabilistically through a Weibull strength distribution. The model is verified through comparisons with the experimentally-measured stress-strain response of the material as well as analysis of the fracture. Further, simulations are then performed to analyze the effect of mesh sensitivity, the effect of fracture of particles on their neighbors, and the role of a particles shape on its fracture probability.
A centrality-based geometry segmentation algorithm was developed to accurately identify discrete inclusions and particles in composite materials where limitations in imaging resolution leads to spurious connections between particles in close contact.To allow for this algorithm to successfully segment geometry independently of particle size and shape, a relative centrality metric was defined to allow for a threshold centrality criterion for removal of voxels that spuriously connect distinct geometries.
To automate incorporation of microstructural information from high-resolution images, two methods were developed that initialize signed distance fields on adaptively-refined finite element meshes. The first method utilizes a level set evolution equation that is directly solved on the finite element mesh through Galerkins method. The evolution equation is formulated to produce a signed distance field that matches geometry defined by a set of voxels segmented from tomographic images. The method achieves optimal convergence for the order of elements used. In a second approach, the fast marching method is employed to initialize a distance field on a uniform grid which is then projected by least squares onto a finite element mesh. This latter approach is shown to be superior in speed and accuracy.
Lastly, extended finite element method simulations are performed for the analysis of particle fracture in metal matrix composites with realistic particle geometries initialized from X-ray tomographic data. In the simulations, particles fracture probabilistically through a Weibull strength distribution. The model is verified through comparisons with the experimentally-measured stress-strain response of the material as well as analysis of the fracture. Further, simulations are then performed to analyze the effect of mesh sensitivity, the effect of fracture of particles on their neighbors, and the role of a particles shape on its fracture probability.
ContributorsYuan, Rui (Author) / Oswald, Jay (Thesis advisor) / Chawla, Nikhilesh (Committee member) / Liu, Yongming (Committee member) / Solanki, Kiran (Committee member) / Chen, Kangping (Committee member) / Arizona State University (Publisher)
Created2015
Description
Hydrogen embrittlement (HE) is a phenomenon that affects both the physical and chemical properties of several intrinsically ductile metals. Consequently, understanding the mechanisms behind HE has been of particular interest in both experimental and modeling research. Discrepancies between experimental observations and modeling results have led to various proposals for HE mechanisms. Therefore, to gain insights into HE mechanisms in iron, this dissertation aims to investigate several key issues involving HE such as: a) the incipient crack tip events; b) the cohesive strength of grain boundaries (GBs); c) the dislocation-GB interactions and d) the dislocation mobility.
The crack tip, which presents a preferential trap site for hydrogen segregation, was examined using atomistic methods and the continuum based Rice-Thompson criterion as sufficient concentration of hydrogen can alter the crack tip deformation mechanism. Results suggest that there is a plausible co-existence of the adsorption induced dislocation emission and hydrogen enhanced decohesion mechanisms. In the case of GB-hydrogen interaction, we observed that the segregation of hydrogen along the interface leads to a reduction in cohesive strength resulting in intergranular failure. A methodology was further developed to quantify the role of the GB structure on this behavior.
GBs play a fundamental role in determining the strengthening mechanisms acting as an impediment to the dislocation motion; however, the presence of an unsurmountable barrier for a dislocation can generate slip localization that could further lead to intergranular crack initiation. It was found that the presence of hydrogen increases the strain energy stored within the GB which could lead to a transition in failure mode. Finally, in the case of body centered cubic metals, understanding the complex screw dislocation motion is critical to the development of an accurate continuum description of the plastic behavior. Further, the presence of hydrogen has been shown to drastically alter the plastic deformation, but the precise role of hydrogen is still unclear. Thus, the role of hydrogen on the dislocation mobility was examined using density functional theory and atomistic simulations. Overall, this dissertation provides a novel atomic-scale understanding of the HE mechanism and development of multiscale tools for future endeavors.
The crack tip, which presents a preferential trap site for hydrogen segregation, was examined using atomistic methods and the continuum based Rice-Thompson criterion as sufficient concentration of hydrogen can alter the crack tip deformation mechanism. Results suggest that there is a plausible co-existence of the adsorption induced dislocation emission and hydrogen enhanced decohesion mechanisms. In the case of GB-hydrogen interaction, we observed that the segregation of hydrogen along the interface leads to a reduction in cohesive strength resulting in intergranular failure. A methodology was further developed to quantify the role of the GB structure on this behavior.
GBs play a fundamental role in determining the strengthening mechanisms acting as an impediment to the dislocation motion; however, the presence of an unsurmountable barrier for a dislocation can generate slip localization that could further lead to intergranular crack initiation. It was found that the presence of hydrogen increases the strain energy stored within the GB which could lead to a transition in failure mode. Finally, in the case of body centered cubic metals, understanding the complex screw dislocation motion is critical to the development of an accurate continuum description of the plastic behavior. Further, the presence of hydrogen has been shown to drastically alter the plastic deformation, but the precise role of hydrogen is still unclear. Thus, the role of hydrogen on the dislocation mobility was examined using density functional theory and atomistic simulations. Overall, this dissertation provides a novel atomic-scale understanding of the HE mechanism and development of multiscale tools for future endeavors.
ContributorsAdlakha, Ilaksh (Author) / Solanki, Kiran (Thesis advisor) / Mignolet, Marc (Committee member) / Chawla, Nikhilesh (Committee member) / Jiang, Hanqing (Committee member) / Liu, Yongming (Committee member) / Arizona State University (Publisher)
Created2015
Corrosion and corrosion-fatigue behavior of 7075 aluminum alloys studied by in situ X-ray tomography
Description
7XXX Aluminum alloys have high strength to weight ratio and low cost. They are used in many critical structural applications including automotive and aerospace components. These applications frequently subject the alloys to static and cyclic loading in service. Additionally, the alloys are often subjected to aggressive corrosive environments such as saltwater spray. These chemical and mechanical exposures have been known to cause premature failure in critical applications. Hence, the microstructural behavior of the alloys under combined chemical attack and mechanical loading must be characterized further. Most studies to date have analyzed the microstructure of the 7XXX alloys using two dimensional (2D) techniques. While 2D studies yield valuable insights about the properties of the alloys, they do not provide sufficiently accurate results because the microstructure is three dimensional and hence its response to external stimuli is also three dimensional (3D). Relevant features of the alloys include the grains, subgrains, intermetallic inclusion particles, and intermetallic precipitate particles. The effects of microstructural features on corrosion pitting and corrosion fatigue of aluminum alloys has primarily been studied using 2D techniques such as scanning electron microscopy (SEM) surface analysis along with post-mortem SEM fracture surface analysis to estimate the corrosion pit size and fatigue crack initiation site. These studies often limited the corrosion-fatigue testing to samples in air or specialized solutions, because samples tested in NaCl solution typically have fracture surfaces covered in corrosion product. Recent technological advancements allow observation of the microstructure, corrosion and crack behavior of aluminum alloys in solution in three dimensions over time (4D). In situ synchrotron X-Ray microtomography was used to analyze the corrosion and cracking behavior of the alloy in four dimensions to elucidate crack initiation at corrosion pits for samples of multiple aging conditions and impurity concentrations. Additionally, chemical reactions between the 3.5 wt% NaCl solution and the crack surfaces were quantified by observing the evolution of hydrogen bubbles from the crack. The effects of the impurity particles and age-hardening particles on the corrosion and fatigue properties were examined in 4D.
ContributorsStannard, Tyler (Author) / Chawla, Nikhilesh (Thesis advisor) / Solanki, Kiran N (Committee member) / Goswami, Ramasis (Committee member) / Liu, Yongming (Committee member) / Arizona State University (Publisher)
Created2017
Description
Interstitial impurity atoms can significantly alter the chemical and physical properties of the host material. Oxygen impurity in HCP titanium is known to have a considerable strengthening effect mainly through interactions with dislocations. To better understand such an effect, first the role of oxygen on various slip planes in titanium is examined using generalized stacking fault energies (GSFE) computed by the first principles calculations. It is shown that oxygen can significantly increase the energy barrier to dislocation motion on most of the studied slip planes. Then the Peierls-Nabbaro model is utilized in conjunction with the GSFE to estimate the Peierls stress ratios for different slip systems. Using such information along with a set of tension and compression experiments, the parameters of a continuum scale crystal plasticity model, namely CRSS values, are calibrated. Effect of oxygen content on the macroscopic stress-strain response is further investigated through experiments on oxygen-boosted samples at room temperature. It is demonstrated that the crystal plasticity model can very well capture the effect of oxygen content on the global response of the samples. It is also revealed that oxygen promotes the slip activity on the pyramidal planes.
The effect of oxygen impurity on titanium is further investigated under high cycle fatigue loading. For that purpose, a two-step hierarchical crystal plasticity for fatigue predictions is presented. Fatigue indicator parameter is used as the main driving force in an energy-based crack nucleation model. To calculate the FIPs, high-resolution full-field crystal plasticity simulations are carried out using a spectral solver. A nucleation model is proposed and calibrated by the fatigue experimental data for notched titanium samples with different oxygen contents and under two load ratios. Overall, it is shown that the presented approach is capable of predicting the high cycle fatigue nucleation time. Moreover, qualitative predictions of microstructurally small crack growth rates are provided. The multi-scale methodology presented here can be extended to other material systems to facilitate a better understanding of the fundamental deformation mechanisms, and to effectively implement such knowledge in mesoscale-macroscale investigations.
The effect of oxygen impurity on titanium is further investigated under high cycle fatigue loading. For that purpose, a two-step hierarchical crystal plasticity for fatigue predictions is presented. Fatigue indicator parameter is used as the main driving force in an energy-based crack nucleation model. To calculate the FIPs, high-resolution full-field crystal plasticity simulations are carried out using a spectral solver. A nucleation model is proposed and calibrated by the fatigue experimental data for notched titanium samples with different oxygen contents and under two load ratios. Overall, it is shown that the presented approach is capable of predicting the high cycle fatigue nucleation time. Moreover, qualitative predictions of microstructurally small crack growth rates are provided. The multi-scale methodology presented here can be extended to other material systems to facilitate a better understanding of the fundamental deformation mechanisms, and to effectively implement such knowledge in mesoscale-macroscale investigations.
ContributorsGholami Bazehhour, Benyamin (Author) / Solanki, Kiran N (Thesis advisor) / Liu, Yongming (Committee member) / Oswald, Jay J (Committee member) / Rajagopalan, Jagannathan (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2018
Description
Multiaxial mechanical fatigue of heterogeneous materials has been a significant cause of concern in the aerospace, civil and automobile industries for decades, limiting the service life of structural components while increasing time and costs associated with inspection and maintenance. Fiber reinforced composites and light-weight aluminum alloys are widely used in aerospace structures that require high specific strength and fatigue resistance. However, studying the fundamental crack growth behavior at the micro- and macroscale as a function of loading history is essential to accurately predict the residual fatigue life of components and achieve damage tolerant designs. The issue of mechanical fatigue can be tackled by developing reliable in-situ damage quantification methodologies and by comprehensively understanding fatigue damage mechanisms under a variety of complex loading conditions. Although a multitude of uniaxial fatigue loading studies have been conducted on light-weight metallic materials and composites, many service failures occur from components being subjected to variable amplitude, mixed-mode multiaxial fatigue loadings. In this research, a systematic approach is undertaken to address the issue of fatigue damage evolution in aerospace materials by:
(i) Comprehensive investigation of micro- and macroscale crack growth behavior in aerospace grade Al 7075 T651 alloy under complex biaxial fatigue loading conditions. The effects of variable amplitude biaxial loading on crack growth characteristics such as crack acceleration and retardation were studied in detail by exclusively analyzing the influence of individual mode-I, mixed-mode and mode-II overload and underload fatigue cycles in an otherwise constant amplitude mode-I baseline load spectrum. The micromechanisms governing crack growth behavior under the complex biaxial loading conditions were identified and correlated with the crack growth behavior and fracture surface morphology through quantitative fractography.
(ii) Development of novel multifunctional nanocomposite materials with improved fatigue resistance and in-situ fatigue damage detection and quantification capabilities. A state-of-the-art processing method was developed for producing sizable carbon nanotube (CNT) membranes for multifunctional composites. The CNT membranes were embedded in glass fiber laminates and in-situ strain sensing and damage quantification was achieved by exploiting the piezoresistive property of the CNT membrane. In addition, improved resistance to fatigue crack growth was observed due to the embedded CNT membrane.
(i) Comprehensive investigation of micro- and macroscale crack growth behavior in aerospace grade Al 7075 T651 alloy under complex biaxial fatigue loading conditions. The effects of variable amplitude biaxial loading on crack growth characteristics such as crack acceleration and retardation were studied in detail by exclusively analyzing the influence of individual mode-I, mixed-mode and mode-II overload and underload fatigue cycles in an otherwise constant amplitude mode-I baseline load spectrum. The micromechanisms governing crack growth behavior under the complex biaxial loading conditions were identified and correlated with the crack growth behavior and fracture surface morphology through quantitative fractography.
(ii) Development of novel multifunctional nanocomposite materials with improved fatigue resistance and in-situ fatigue damage detection and quantification capabilities. A state-of-the-art processing method was developed for producing sizable carbon nanotube (CNT) membranes for multifunctional composites. The CNT membranes were embedded in glass fiber laminates and in-situ strain sensing and damage quantification was achieved by exploiting the piezoresistive property of the CNT membrane. In addition, improved resistance to fatigue crack growth was observed due to the embedded CNT membrane.
ContributorsDatta, Siddhant (Author) / Chattopadhyay, Aditi (Thesis advisor) / Liu, Yongming (Committee member) / Jiang, Hanqing (Committee member) / Marvi, Hamidreza (Committee member) / Tang, Pingbo (Committee member) / Yekani Fard, Masoud (Committee member) / Iyyer, Nagaraja (Committee member) / Arizona State University (Publisher)
Created2018
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
Rapid expansion of dense beds of fine, spherical particles subjected to rapid depressurization is studied in a vertical shock tube. As the particle bed is unloaded, a high-speed video camera captures the dramatic evolution of the particle bed structure. Pressure transducers are used to measure the dynamic pressure changes during the particle bed expansion process. Image processing, signal processing, and Particle Image Velocimetry techniques, are used to examine the relationships between particle size, initial bed height, bed expansion rate, and gas velocities.
The gas-particle interface and the particle bed as a whole expand and evolve in stages. First, the bed swells nearly homogeneously for a very brief period of time (< 2ms). Shortly afterward, the interface begins to develop instabilities as it continues to rise, with particles nearest the wall rising more quickly. Meanwhile, the bed fractures into layers and then breaks down further into cellular-like structures. The rate at which the structural evolution occurs is shown to be dependent on particle size. Additionally, the rate of the overall bed expansion is shown to be dependent on particle size and initial bed height.
Taller particle beds and beds composed of smaller-diameter particles are found to be associated with faster bed-expansion rates, as measured by the velocity of the gas-particle interface. However, the expansion wave travels more slowly through these same beds. It was also found that higher gas velocities above the the gas-particle interface measured \textit{via} Particle Image Velocimetry or PIV, were associated with particle beds composed of larger-diameter particles. The gas dilation between the shocktube diaphragm and the particle bed interface is more dramatic when the distance between the gas-particle interface and the diaphragm is decreased-as is the case for taller beds.
To further elucidate the complexities of this multiphase compressible flow, simple OpenFOAM (Weller, 1998) simulations of the shocktube experiment were performed and compared to bed expansion rates, pressure fluctuations, and gas velocities. In all cases, the trends and relationships between bed height, particle diameter, with expansion rates, pressure fluctuations and gas velocities matched well between experiments and simulations. In most cases, the experimentally-measured bed rise rates and the simulated bed rise rates matched reasonably well in early times. The trends and overall values of the pressure fluctuations and gas velocities matched well between the experiments and simulations; shedding light on the effects each parameter has on the overall flow.
The gas-particle interface and the particle bed as a whole expand and evolve in stages. First, the bed swells nearly homogeneously for a very brief period of time (< 2ms). Shortly afterward, the interface begins to develop instabilities as it continues to rise, with particles nearest the wall rising more quickly. Meanwhile, the bed fractures into layers and then breaks down further into cellular-like structures. The rate at which the structural evolution occurs is shown to be dependent on particle size. Additionally, the rate of the overall bed expansion is shown to be dependent on particle size and initial bed height.
Taller particle beds and beds composed of smaller-diameter particles are found to be associated with faster bed-expansion rates, as measured by the velocity of the gas-particle interface. However, the expansion wave travels more slowly through these same beds. It was also found that higher gas velocities above the the gas-particle interface measured \textit{via} Particle Image Velocimetry or PIV, were associated with particle beds composed of larger-diameter particles. The gas dilation between the shocktube diaphragm and the particle bed interface is more dramatic when the distance between the gas-particle interface and the diaphragm is decreased-as is the case for taller beds.
To further elucidate the complexities of this multiphase compressible flow, simple OpenFOAM (Weller, 1998) simulations of the shocktube experiment were performed and compared to bed expansion rates, pressure fluctuations, and gas velocities. In all cases, the trends and relationships between bed height, particle diameter, with expansion rates, pressure fluctuations and gas velocities matched well between experiments and simulations. In most cases, the experimentally-measured bed rise rates and the simulated bed rise rates matched reasonably well in early times. The trends and overall values of the pressure fluctuations and gas velocities matched well between the experiments and simulations; shedding light on the effects each parameter has on the overall flow.
ContributorsZunino, Heather (Author) / Adrian, Ronald J (Thesis advisor) / Clarke, Amanda (Committee member) / Chen, Kangping (Committee member) / Herrmann, Marcus (Committee member) / Huang, Huei-Ping (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