Matching Items (170)
Filtering by
- Genre: Academic theses
- Creators: Huang, Huei-Ping
- Status: Published
Description
It is well known that radiative heat transfer rate can exceed that between two blackbodies by several orders of magnitude due to the coupling of evanescent waves. One promising application of near-field thermal radiation is thermophotovoltaic (TPV) devices, which convert thermal energy to electricity. Recently, different types of metamaterials with excitations of surface plasmon polaritons (SPPs)/surface phonon polaritons (SPhPs), magnetic polaritons (MP), and hyperbolic modes (HM), have been studied to further improve near-field radiative heat flux and conversion efficiency. On the other hand, near-field experimental demonstration between planar surfaces has been limited due to the extreme challenge in the vacuum gap control as well as the parallelism.
The main objective of this work is to experimentally study the near-field radiative transfer and the excitation of resonance modes by designing nanostructured thin films separated by nanometer vacuum gaps. In particular, the near-field radiative heat transfer between two parallel plates of intrinsic silicon wafers coated with a thin film of aluminum nanostructure is investigated. In addition, theoretical studies about the effects of different physical mechanisms such as SPhP/SPP, MPs, and HM on near-field radiative transfer in various nanostructured metamaterials are conducted particularly for near-field TPV applications. Numerical simulations are performed by using multilayer transfer matrix method, rigorous coupled wave analysis, and finite difference time domain techniques incorporated with fluctuational electrodynamics. The understanding gained here will undoubtedly benefit the spectral control of near-field thermal radiation for energy-harvesting applications like thermophotovoltaic energy conversion and radiation-based thermal management.
The main objective of this work is to experimentally study the near-field radiative transfer and the excitation of resonance modes by designing nanostructured thin films separated by nanometer vacuum gaps. In particular, the near-field radiative heat transfer between two parallel plates of intrinsic silicon wafers coated with a thin film of aluminum nanostructure is investigated. In addition, theoretical studies about the effects of different physical mechanisms such as SPhP/SPP, MPs, and HM on near-field radiative transfer in various nanostructured metamaterials are conducted particularly for near-field TPV applications. Numerical simulations are performed by using multilayer transfer matrix method, rigorous coupled wave analysis, and finite difference time domain techniques incorporated with fluctuational electrodynamics. The understanding gained here will undoubtedly benefit the spectral control of near-field thermal radiation for energy-harvesting applications like thermophotovoltaic energy conversion and radiation-based thermal management.
ContributorsSabbaghi, Payam (Author) / Wang, Liping (Thesis advisor) / Phelan, Patrick (Committee member) / Huang, Huei-Ping (Committee member) / Wang, Robert (Committee member) / Yu, Hongbin (Committee member) / Arizona State University (Publisher)
Created2019
Description
Phononic crystals are artificially engineered materials that can forbid phonon propagation in a specific frequency range that is referred to as a “phononic band gap.” Phononic crystals that have band gaps in the GHz to THz range can potentially enable sophisticated control over thermal transport with “phononic devices”. Calculations of the phononic band diagram are the standard method of determining if a given phononic crystal structure has a band gap. However, calculating the phononic band diagram is a computationally expensive and time-consuming process that can require sophisticated modeling and coding. In addition to this computational burden, the inverse process of designing a phononic crystal with a specific band gap center frequency and width is a challenging problem that requires extensive trial-and-error work.
In this dissertation, I first present colloidal nanocrystal superlattices as a new class of three-dimensional phononic crystals with periodicity in the sub-20 nm size regime using the plane wave expansion method. These calculations show that colloidal nanocrystal superlattices possess phononic band gaps with center frequencies in the 102 GHz range and widths in the 101 GHz range. Varying the colloidal nanocrystal size and composition provides additional opportunities to fine-tune the phononic band gap. This suggests that colloidal nanocrystal superlattices are a promising platform for the creation of high frequency phononic crystals.
For the next topic, I explore opportunities to use supervised machine learning for expedited discovery of phononic band gap presence, center frequency and width for over 14,000 two-dimensional phononic crystal structures. The best trained model predicts band gap formation, center frequencies and band gap widths, with 94% accuracy and coefficients of determination (R2) values of 0.66 and 0.83, respectively.
Lastly, I expand the above machine learning approach to use machine learning to design a phononic crystal for a given set of phononic band gap properties. The best model could predict elastic modulus of host and inclusion, density of host and inclusion, and diameter-to-lattice constant ratio for target center and width frequencies with coefficients of determinations of 0.94, 0.98, 0.94, 0.71, and 0.94 respectively. The high values coefficients of determination represents great opportunity for phononic crystal design.
In this dissertation, I first present colloidal nanocrystal superlattices as a new class of three-dimensional phononic crystals with periodicity in the sub-20 nm size regime using the plane wave expansion method. These calculations show that colloidal nanocrystal superlattices possess phononic band gaps with center frequencies in the 102 GHz range and widths in the 101 GHz range. Varying the colloidal nanocrystal size and composition provides additional opportunities to fine-tune the phononic band gap. This suggests that colloidal nanocrystal superlattices are a promising platform for the creation of high frequency phononic crystals.
For the next topic, I explore opportunities to use supervised machine learning for expedited discovery of phononic band gap presence, center frequency and width for over 14,000 two-dimensional phononic crystal structures. The best trained model predicts band gap formation, center frequencies and band gap widths, with 94% accuracy and coefficients of determination (R2) values of 0.66 and 0.83, respectively.
Lastly, I expand the above machine learning approach to use machine learning to design a phononic crystal for a given set of phononic band gap properties. The best model could predict elastic modulus of host and inclusion, density of host and inclusion, and diameter-to-lattice constant ratio for target center and width frequencies with coefficients of determinations of 0.94, 0.98, 0.94, 0.71, and 0.94 respectively. The high values coefficients of determination represents great opportunity for phononic crystal design.
ContributorsSadat, Seid Mohamadali (Author) / Wang, Robert Y (Thesis advisor) / Huang, Huei-Ping (Committee member) / Ankit, Kumar (Committee member) / Wang, Liping (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2020
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
Flexible conducting materials have been in the forefront of a rapidly transforming electronics industry, focusing on wearable devices for a variety of applications in recent times. Over the past few decades, bulky, rigid devices have been replaced with a surging demand for thin, flexible, light weight, ultra-portable yet high performance electronics. The interconnects available in the market today only satisfy a few of the desirable characteristics, making it necessary to compromise one feature over another. In this thesis, a method to prepare a thin, flexible, and stretchable inter-connect is presented with improved conductivity compared to previous achievements. It satisfies most mechanical and electrical conditions desired in the wearable electronics industry. The conducting composite, prepared with the widely available, low cost silicon-based organic polymer - polydimethylsiloxane (PDMS) and silver (Ag), is sandwiched between two cured PDMS layers. These protective layers improve the mechanical stability of the inter-connect. The structure can be stretched up to 120% of its original length which can further be enhanced to over 250% by cutting it into a serpentine shape without compromising its electrical stability. The inter-connect, around 500 µm thick, can be integrated into thin electronic packaging. The synthesis process of the composite material, along with its electrical and mechanical and properties are presented in detail. Testing methods and results for mechanical and electrical stability are also illustrated over extensive flexing and stretching cycles. The materials put into test, along with conductive silver (Ag) - polydimethylsiloxane (PDMS) composite in a sandwich structure, are copper foils, copper coated polyimide (PI) and aluminum (Al) coated polyethylene terephthalate (PET).
ContributorsNandy, Mayukh (Author) / Yu, Hongbin (Thesis advisor) / Chan, Candace (Committee member) / Jiang, Hanqing (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
Description
Drainage flow of a viscous compressible gas from a semi-sealed narrow conduit is a pore-scale model for studying the fundamental flow physics of fluid recovery from a porous reservoir without using fluid injection. Thermal effect has been routinely neglected for these flows in the traditional petroleum engineering literature. Since the motion is entirely driven by volumetric expansion, temperature change always accompanies the density change. This thesis examines such thermal effects on the drainage flow.
Thermal drainage flow is first studied by simultaneously solving the linearized continuity, momentum and energy equations for adiabatic walls. It is shown that even in the absence of an imposed temperature drop, gas expansion induces a transient temperature decrease inside the channel, which slows down the drainage process compared to the isothermal model and Lighthill’s model. For a given density drop, gas drains out faster as the initial-to-final temperature ratio increases; and the transient density can undershoot the final equilibrium value. A parametric study is then carried out to explore the influence of various thermal boundary conditions on drainage flow. It is found that as the wall transitions from adiabatic to isothermal condition, the excess density changes from a plane wave solution to a non-plane wave solution and the drainage rate increases. It is shown that when the exit is also cooled and the wall is non-adiabatic, the total recovered fluid mass exceeds the amount based on the isothermal theory which is determined by the initial and final density difference alone. Finally, a full numerical simulation is conducted to mimic the channel-reservoir system using the finite volume method. The Ghost-Cell Navier-Stokes Characteristic Boundary Condition technique is applied at the far end of the truncated reservoir, which is an open boundary. The results confirm the conclusions of the linear theory.
Thermal drainage flow is first studied by simultaneously solving the linearized continuity, momentum and energy equations for adiabatic walls. It is shown that even in the absence of an imposed temperature drop, gas expansion induces a transient temperature decrease inside the channel, which slows down the drainage process compared to the isothermal model and Lighthill’s model. For a given density drop, gas drains out faster as the initial-to-final temperature ratio increases; and the transient density can undershoot the final equilibrium value. A parametric study is then carried out to explore the influence of various thermal boundary conditions on drainage flow. It is found that as the wall transitions from adiabatic to isothermal condition, the excess density changes from a plane wave solution to a non-plane wave solution and the drainage rate increases. It is shown that when the exit is also cooled and the wall is non-adiabatic, the total recovered fluid mass exceeds the amount based on the isothermal theory which is determined by the initial and final density difference alone. Finally, a full numerical simulation is conducted to mimic the channel-reservoir system using the finite volume method. The Ghost-Cell Navier-Stokes Characteristic Boundary Condition technique is applied at the far end of the truncated reservoir, which is an open boundary. The results confirm the conclusions of the linear theory.
ContributorsHuang, Wei (Author) / Chen, Kangping (Thesis advisor) / Huang, Huei-Ping (Committee member) / Herrmann, Marcus (Committee member) / Calhoun, Ronald (Committee member) / Baer, Steven (Committee member) / Arizona State University (Publisher)
Created2020
Description
The focus of this dissertation is first on understanding the difficulties involved in constructing reduced order models of structures that exhibit a strong nonlinearity/strongly nonlinear events such as snap-through, buckling (local or global), mode switching, symmetry breaking. Next, based on this understanding, it is desired to modify/extend the current Nonlinear Reduced Order Modeling (NLROM) methodology, basis selection and/or identification methodology, to obtain reliable reduced order models of these structures. Focusing on these goals, the work carried out addressed more specifically the following issues:
i) optimization of the basis to capture at best the response in the smallest number of modes,
ii) improved identification of the reduced order model stiffness coefficients,
iii) detection of strongly nonlinear events using NLROM.
For the first issue, an approach was proposed to rotate a limited number of linear modes to become more dominant in the response of the structure. This step was achieved through a proper orthogonal decomposition of the projection on these linear modes of a series of representative nonlinear displacements. This rotation does not expand the modal space but renders that part of the basis more efficient, the identification of stiffness coefficients more reliable, and the selection of dual modes more compact. In fact, a separate approach was also proposed for an independent optimization of the duals. Regarding the second issue, two tuning approaches of the stiffness coefficients were proposed to improve the identification of a limited set of critical coefficients based on independent response data of the structure. Both approaches led to a significant improvement of the static prediction for the clamped-clamped curved beam model. Extensive validations of the NLROMs based on the above novel approaches was carried out by comparisons with full finite element response data. The third issue, the detection of nonlinear events, was finally addressed by building connections between the eigenvalues of the finite element software (Nastran here) and NLROM tangent stiffness matrices and the occurrence of the ‘events’ which is further extended to the assessment of the accuracy with which the NLROM captures the full finite element behavior after the event has occurred.
i) optimization of the basis to capture at best the response in the smallest number of modes,
ii) improved identification of the reduced order model stiffness coefficients,
iii) detection of strongly nonlinear events using NLROM.
For the first issue, an approach was proposed to rotate a limited number of linear modes to become more dominant in the response of the structure. This step was achieved through a proper orthogonal decomposition of the projection on these linear modes of a series of representative nonlinear displacements. This rotation does not expand the modal space but renders that part of the basis more efficient, the identification of stiffness coefficients more reliable, and the selection of dual modes more compact. In fact, a separate approach was also proposed for an independent optimization of the duals. Regarding the second issue, two tuning approaches of the stiffness coefficients were proposed to improve the identification of a limited set of critical coefficients based on independent response data of the structure. Both approaches led to a significant improvement of the static prediction for the clamped-clamped curved beam model. Extensive validations of the NLROMs based on the above novel approaches was carried out by comparisons with full finite element response data. The third issue, the detection of nonlinear events, was finally addressed by building connections between the eigenvalues of the finite element software (Nastran here) and NLROM tangent stiffness matrices and the occurrence of the ‘events’ which is further extended to the assessment of the accuracy with which the NLROM captures the full finite element behavior after the event has occurred.
ContributorsLin, Jinshan (Author) / Mignolet, Marc (Thesis advisor) / Jiang, Hanqing (Committee member) / Oswald, Jay (Committee member) / Spottswood, Stephen (Committee member) / Rajan, Subramaniam D. (Committee member) / Arizona State University (Publisher)
Created2020
Description
Compressible fluid flows involving multiple physical states of matter occur in both nature and technical applications such as underwater explosions and implosions, cavitation-induced bubble collapse in naval applications and Richtmyer-Meshkov type instabilities in inertial confinement fusion. Of particular interest is the atomization of fuels that enable shock-induced mixing of fuel and oxidizer in supersonic combustors. Due to low residence times and varying length scales, providing insight through physical experiments is both technically challenging and sometimes unfeasible. Numerical simulations can help provide detailed insight and aid in the engineering design of devices that can harness these physical phenomena.
In this research, computational methods were developed to accurately simulate phase interfaces in compressible fluid flows with a focus on targeting primary atomization. Novel numerical methods which treat the phase interface as a discontinuity, and as a smeared region were developed using low-dissipation, high-order schemes. The resulting methods account for the effects of compressibility, surface tension and viscosity. To aid with the varying length scales and high-resolution requirements found in atomization applications, an adaptive mesh refinement (AMR) framework is used to provide high-resolution only in regions of interest. The developed methods were verified with test cases involving strong shocks, high density ratios, surface tension effects and jumps in the equations of state, in one-, two- and three dimensions, obtaining good agreement with theoretical and experimental results. An application case of the primary atomization of a liquid jet injected into a Mach 2 supersonic crossflow of air is performed with the methods developed.
In this research, computational methods were developed to accurately simulate phase interfaces in compressible fluid flows with a focus on targeting primary atomization. Novel numerical methods which treat the phase interface as a discontinuity, and as a smeared region were developed using low-dissipation, high-order schemes. The resulting methods account for the effects of compressibility, surface tension and viscosity. To aid with the varying length scales and high-resolution requirements found in atomization applications, an adaptive mesh refinement (AMR) framework is used to provide high-resolution only in regions of interest. The developed methods were verified with test cases involving strong shocks, high density ratios, surface tension effects and jumps in the equations of state, in one-, two- and three dimensions, obtaining good agreement with theoretical and experimental results. An application case of the primary atomization of a liquid jet injected into a Mach 2 supersonic crossflow of air is performed with the methods developed.
ContributorsKannan, Karthik (Author) / Herrmann, Marcus (Thesis advisor) / Huang, Huei-Ping (Committee member) / Lopez, Juan (Committee member) / Peet, Yulia (Committee member) / Wang, Liping (Committee member) / Arizona State University (Publisher)
Created2020
Description
Realistic engineering, physical and biological systems are very complex in nature, and their response and performance are governed by multitude of interacting processes. In computational modeling of these systems, the interactive response is most often ignored, and simplifications are made to model one or a few relevant phenomena as opposed to a complete set of interacting processes due to a complexity of integrative analysis. In this thesis, I will develop new high-order computational approaches that reduce the amount of simplifications and model the full response of a complex system by accounting for the interaction between different physical processes as required for an accurate description of the global system behavior. Specifically, I will develop multi-physics coupling techniques based on spectral-element methods for the simulations of such systems. I focus on three specific applications: fluid-structure interaction, conjugate heat transfer, and modeling of acoustic wave propagation in non-uniform media. Fluid-structure interaction illustrates a complex system between a fluid and a solid, where a movable and deformable structure is surrounded by fluid flow, and its deformation caused by fluid affects the fluid flow interactively. To simulate this system, two coupling schemes are developed: 1) iterative implicit coupling, and 2) explicit coupling based on Robin-Neumann boundary conditions. A comprehensive verification strategy of the developed methodology is presented, including a comparison with benchmark flow solutions, h-, p- and temporal refinement studies. Simulation of a turbulent flow in a channel interacting with a compliant wall is attempted as well. Another problem I consider is when a solid is stationary, but a heat transfer occurs on the fluid-solid interface. To model this problem, a conjugate heat transfer framework is introduced. Validation of the framework, as well as studies of an interior thermal environment in a building regulated by an HVAC system with an on/off control model with precooling and multi-zone precooling strategies are presented. The final part of this thesis is devoted to modeling an interaction of acoustic waves with the fluid flow. The development of a spectral-element methodology for solution of Lighthill’s equation, and its application to a problem of leak detection in water pipes is presented.
ContributorsXu, Yiqin (Author) / Peet, Yulia (Thesis advisor) / Huang, Huei-Ping (Committee member) / Herrmann, Marcus (Committee member) / Adrian, Ronald (Committee member) / Baer, Steven (Committee member) / Arizona State University (Publisher)
Created2021