1,665 research outputs found

    Wall Temperature and Leading-Edge Bluntness Effects in Hypersonic Laminar Separation

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    This thesis considers wall-temperature and leading-edge bluntness effects on hypersonic laminar separation, using both the interactive boundary layer theory and Computational Fluid Dynamics. Firstly, we studied the effect of wall temperature and leading-edge bluntness on hypersonic laminar separation induced by a finite-span compression corner. The flow conditions were: Mach number 9.66; Reynolds number 1.34 × 106 per metre; and stagnation temperature 3150 K. The wall-to-stagnation temperature ratio varied from 0.095 to 0.333. Two leading-edge bluntnesses of 40 μm and 200 μm were used in the investigation. Numerical solutions were obtained using a compressible Navier-Stokes solver, and compared with the triple-deck theory using the numerical method of Ruban (1978) and Cassel et al. (1995). Separation was induced by ramp angles of 10◦ and 20◦ , which produced incipient and large separations, respectively. The corresponding scale angles were not sufficient to induce secondary separation. Two regimes of shock intereference were identified depending on the wall temperature ratio. Increasing both the wall temperature ratio and blunting increased the separation length. The corner instability in the form of a stationary wave-packet identified by Cassel et al. (1995) for scale angles α ≥ 3.9 was investigated but was shown to be a numerical artefact of the algorithm rather than having any physical basis. We attempted to solve the steady-state triple-deck equations using the method of Bos & Ruban (2000) for supersonic flow past a compression corner. This was motivated by the fact that in their above paper they show solutions for scale angles up to 8, the highest obtained so far in the literature. However, we encountered a stationary wave-packet at the corner for scale angles 1.82 and 1.96, depending on the values of stretching factors. Our solutions are then compared with the steady-state solutions produced using the method of Logue et al. (2014), which do not show such wave-packets. These wave-packets do not appear to be the result of flow instability, as flow instabilities should only appear with unsteady equations (Cassel et al., 1995). It is therefore suggested that the method of Bos & Ruban (2000) produces these spurious wave-packets as a consequence of their numerical method. This has important implications in the interpretation of triple-deck solutions. We discuss a relationship between wave-packets and discontinuities encountered in the numerical solution of unsteady, supersonic triple-deck equations. Large gradients at the corner are found to compromise the stability of the algorithm of Cassel et al. (1995) as the scale angle increases. Two numerical methods have been developed to deal with such gradients. The first method is a time-splitting explicit method with a first-order approximation of the pressure derivative (FOM). This improves the stability of the algorithm at the cost of added numerical diffusion. The range of solutions obtained was extended from 3.7 by Cassel et al. (1995) to 6.5. The diffusivity of this method is quantified by comparing with the steady state solutions of Korolev et al. (2002) and Logue et al. (2014). The appearance of a spike just prior to the second minimum in shear stress also seen by some previous researchers is elucidated. The second method, which is new, is the Haar Wavelet Method (HWM) applied to unsteady triple-deck equations. This method is found to be stable and accurate, but computationally very expensive. Finally, our results are analysed in terms of the maximum pressure gradient prior to reattachment and the second shear stress minimum as defined and discussed in Smith & Khorrami (1991). Finally, we also considered an axisymmetric compression corner, using the interactive boundary layer theory. The problem of axisymmetric supersonic laminar separation over a compression corner has not been considered within the framework of triple-deck theory for several decades, despite significant advances in both theoretical methods and numerical techniques. We revisited the problem considered by Gittler & Kluwick (1987), using two numerical methods; the method of Ruban (1978) and Cassel et al. (1995), termed Ruban-Cassel Method (RCM); and the Haar Wavelet Method (HWM). The solution for both numerical methods shows good agreement for both shear-stress and pressure values. At a scale angle 6.8, the Ruban-Cassel Method produces a wave-packet similar to that encountered by Cassel et al. (1995). Using the Haar Wavelet Method, wave have been able to show results for scale angles up to 10 without encountering such a wave-packet. Incipient secondary separation is shown to occur for a scale angle of 10. Secondary separation was not observed by Gittler & Kluwick (1987) for scale angles as high as 9. It is suggested that this is possibly due to the Reyhner & Flügge-Lotz (1968) approximation used in their calculations, which neglects the convective term in the reverse flow

    Numerical resolution of the Navier-Stokes equations with parallel programming for the analysis of heat and mass transfer phenomena.

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    Aquesta tesi analitza mètodes numèrics per resoldre les equacions de Navier-Stokes en dinàmica de fluids computacional (CFD, per les sigles en anglès). La investigació es centra a des- envolupar una visió profunda de diferents mètodes numèrics i la seva aplicació a diversos fenòmens de transport. S’aplica una metodologia pas a pas, que abarca l’anàlisi de volums fi- nits i mètodes espectrals, la validació de models i la verificació de codis a través de l’anàlisi de casos d’estudi de convecció-difusió, flux de fluids i turbulència. La investigació revela l’efecte de diferents esquemes d’aproximació a la solució numèrica i emfatitza la importància d’una representació física precisa juntament amb la solidesa matemàtica. S’examina la convergència del mètode de resolució d’equacions iteratiu pel que fa a la naturalesa de la física de l’estudi, i cal destacar la necessitat de tècniques de relaxació apropiades. A més, s’explora el mètode de passos fraccionats per resoldre el fort acoblament de pressió-velocitat a les equacions de Navier-Stokes, mentre es considera l’addició d’altres fenòmens de transport. L’anàlisi de fluxes turbulents mostra la cascada d’energia a l’espai de Fourier i l’efecte del truncament a causa de la discretització espacial o espectral, abordat per l’aplicació de models simplificats, com ara Large Eddy Simulation (LES), aconseguint una solució aproximada amb un menor cost computacional. A més, s’analitza la implementació de la computació en paral·lel utilitzant l’estàndard MPI, emfatitzant-ne l’escalabilitat i el potencial per abordar les demandes creixents de l’anàlisi CFD en els camps de l’enginyeria. En general, aquesta recerca proporciona informació valuosa sobre els mètodes numèrics per a les equacions de Navier-Stokes, la seva aplicació a CFD i les implicacions pràctiques per als processos d’enginyeriaEsta tesis analiza métodos numéricos para resolver las ecuaciones de Navier-Stokes en dinámica de fluidos computacional (CFD, por sus siglas en Inglés). La investigación se centra en desarrollar una visión profunda de distintos métodos numéricos y su aplicación a diversos fenómenos de transporte. Se aplica una metodología paso a paso, que abarca el análisis de volúmenes finitos y métodos espectrales, validación de modelos y verificación de códigos a través del analisis de casos de estudio de convección-difusión, flujo de fluidos y turbulencia. La investigación revela el efecto de diferentes esquemas de aproximación en la solución numérica y enfatiza la importancia de una representación física precisa junto con la solidez matemática. Se examina la convergencia del método de resolución de equaciones iterativo con respecto a la naturaleza de la física del estudio, destacando la necesidad de técnicas de relajación apropiadas. Además, se explora el método de pasos fraccionados para resolver el fuerte acoplamiento de presión-velocidad en las ecuaciones de Navier-Stokes, mientras se considera la adición de otros fenómenos de transporte. El análisis de flujos turbulentos muestra la cascada de energía en el espacio de Fourier y el efecto del truncamiento debido a la discretización espacial o espectral, abordado por la aplicación de modelos simplificados, como Large Eddy Simulation (LES), logrando una solución aproximada con un menor costo computacional. Además, se analiza la implementación de la computación en paralelo utilizando el estándar MPI, enfatizando su escalabilidad y potencial para abordar las crecientes demandas del análisis CFD en los campos de la ingeniería. En general, esta investigación proporciona información valiosa sobre los métodos numéricos para las ecuaciones de Navier-Stokes, su aplicación a CFD y sus implicaciones prácticas para los procesos de ingenieríaThis thesis analyzes numerical methods for solving the Navier-Stokes equations in computational fluid dynamics (CFD). The research focuses on developing a deep insight into different numerical techniques and their application to various transport phenomena. A step-by-step methodology is applied, encompassing the analysis of finite volume and spectral methods, model validation, and code verification with the study of convection-diffusion, fluid flow, and turbulence study cases. The investigation reveals the effect of different approximation schemes on the numerical solution and emphasizes the importance of accurate physics representation alongside mathematical robustness. The convergence of the numerical solver is examined concerning the nature of the studied physics, highlighting the need for appropriate relaxation techniques. Additionally, the fractional step method is explored to solve the strong pressure-velocity coupling in the Navier-Stokes equations while considering the addition of other transport phenomena. The analysis of turbulent flows showcases the energy cascade in the Fourier space and its truncation effect due to spatial or spectral discretization, addressed by the application of simplified models, such as Large Eddy Simulation (LES), capable of approximating the solution with reduced computational cost. Furthermore, the implementation of parallel computing using the MPI standard is discussed, emphasizing its scalability and potential for addressing the growing demands of CFD analysis in engineering fields. Overall, this research provides valuable insights into numerical methods for the Navier-Stokes equations, their application to CFD, and their practical implications for engineering processe

    Development, Implementation, and Optimization of a Modern, Subsonic/Supersonic Panel Method

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    In the early stages of aircraft design, engineers consider many different design concepts, examining the trade-offs between different component arrangements and sizes, thrust and power requirements, etc. Because so many different designs are considered, it is best in the early stages of design to use simulation tools that are fast; accuracy is secondary. A common simulation tool for early design and analysis is the panel method. Panel methods were first developed in the 1950s and 1960s with the advent of modern computers. Despite being reasonably accurate and very fast, their development was abandoned in the late 1980s in favor of more complex and accurate simulation methods. The panel methods developed in the 1980s are still in use by aircraft designers today because of their accuracy and speed. However, they are cumbersome to use and limited in applicability. The purpose of this work is to reexamine panel methods in a modern context. In particular, this work focuses on the application of panel methods to supersonic aircraft (a supersonic aircraft is one that flies faster than the speed of sound). Various aspects of the panel method, including the distributions of the unknown flow variables on the surface of the aircraft and efficiently solving for these unknowns, are discussed. Trade-offs between alternative formulations are examined and recommendations given. This work also serves to bring together, clarify, and condense much of the literature previously published regarding panel methods so as to assist future developers of panel methods

    A simple and general framework for the construction of thermodynamically compatible schemes for computational fluid and solid mechanics

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    We introduce a simple and general framework for the construction of thermodynamically compatible schemes for the numerical solution of overdetermined hyperbolic PDE systems that satisfy an extra conservation law. As a particular example in this paper, we consider the general Godunov-Peshkov-Romenski (GPR) model of continuum mechanics that describes the dynamics of nonlinear solids and viscous fluids in one single unified mathematical formalism. A main peculiarity of the new algorithms presented in this manuscript is that the entropy inequality is solved as a primary evolution equation instead of the usual total energy conservation law, unlike in most traditional schemes for hyperbolic PDE. Instead, total energy conservation is obtained as a mere consequence of the proposed thermodynamically compatible discretization. The approach is based on the general framework introduced in Abgrall (2018) [1]. In order to show the universality of the concept proposed in this paper, we apply our new formalism to the construction of three different numerical methods. First, we construct a thermodynamically compatible finite volume (FV) scheme on collocated Cartesian grids, where discrete thermodynamic compatibility is achieved via an edge/face-based correction that makes the numerical flux thermodynamically compatible. Second, we design a first type of high order accurate and thermodynamically compatible discontinuous Galerkin (DG) schemes that employs the same edge/face-based numerical fluxes that were already used inside the finite volume schemes. And third, we introduce a second type of thermodynamically compatible DG schemes, in which thermodynamic compatibility is achieved via an element-wise correction, instead of the edge/face-based corrections that were used within the compatible numerical fluxes of the former two methods. All methods proposed in this paper can be proven to be nonlinearly stable in the energy norm and they all satisfy a discrete entropy inequality by construction. We present numerical results obtained with the new thermodynamically compatible schemes in one and two space dimensions for a large set of benchmark problems, including inviscid and viscous fluids as well as solids. An interesting finding made in this paper is that, in numerical experiments, one can observe that for smooth isentropic flows the particular formulation of the new schemes in terms of entropy density, instead of total energy density, as primary state variable leads to approximately twice the convergence rate of high order DG schemes for the entropy density

    Transition Physics and Boundary-Layer Stability: Computational Modeling in Compressible Flow

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    Laminar-to-turbulent transition of boundary layers remains a critical subject of study in aerodynamics. The differences in surface friction and heating between laminar and turbulent flows can be nearly an order of magnitude. Accurate prediction of the transition region between these two regimes is essential for design applications. The objective of this work is to advance simplified approaches to representing the laminar boundary layer and perturbation dynamics that usher flows to turbulence. A versatile boundary-layer solver called DEKAF including thermochemical effects has been created, and the in-house nonlinear parabolized stability equation technique called EPIC has been advanced, including an approach to reduce divergent growth associated with the inclusion of the mean-flow distortion. The simplified approaches are then applied to advance studies in improving aircraft energy efficiency. Under the auspices of a NASA University Leadership Initiative, the transformative technology of a swept, slotted, natural-laminar-flow wing is leveraged to maintain laminar flow over large extents of the wing surface, thereby increasing energy efficiency. From an aircraft performance perspective, sweep is beneficial as it reduces the experienced wave drag. From a boundary-layer transition perspective, though, sweep introduces several physical complications, spawned by the crossflow instability mechanism. As sweep is increased, the crossflow mechanism becomes increasingly unstable, and can lead to an early transition to turbulence. The overarching goal of the present analysis then is to address the question, how much sweep can be applied to this wing while maintaining the benefits of the slotted, natural-laminar-flow design? Linear and nonlinear stability analyses will be presented to assess various pathways to turbulence. In addition, companion computations are presented to accompany the risk-reduction experiment run in the Klebanoff-Saric Wind Tunnel at Texas A&M University. Linear analyses assess a wide range of various configurations to inform experimentalists where relevant unstable content resides. A comparison between simulation and experimental measurements is presented, for which there is a good agreement

    Investigation of entropy generation and thermohydraulics of forced and mixed convection of Al₂O₃-Cu/water in a parabolic trough receiver tube

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    Heat transfer has long been a vital part of human life. Many sources have focused on increased heat transfer. Various industries, such as solar water heating systems, solar chemistry, solar desalination plants, and concentrating solar power plants, food processing plants, petrochemical plants, refrigeration systems and air conditioning equipment, and condensing central heating exchangers, etc., face the challenges of effective utilisation, conservation, and recovery of heat. In modern times, increasing the rate of heat transfer in concentrating solar collectors such as parabolic troughs by using various passive approaches have proven to be very effective. When passive approaches are used, more pumping power is needed to move the fluid through the receiver. Manufacturing of parabolic trough receiver tubes requires a significant financial commitment due to the high expenses of both capital and operation. Therefore, it is essential to develop parabolic trough receivers that are efficient. Several methods, such as heat transfer enhancement and minimisation of entropy generation, are used to do this. The current investigation makes use of tube insert technology and nanoparticle flow to achieve optimal thermohydraulic and thermodynamic designs. Previous research on fluid flow and heat transfer in a regular pipe (PT) and a pipe equipped with an elliptical-cut twisted tape insert (TECT) and a traditional twisted tape insert (TPT) has not been conducted, particularly emphasizing the utilization of hybrid nanofluid as the working medium. However, previous works on water and nanofluid do exist. In addition, the Bejan number and the generation of total entropy are not examined on tubes supplied with an elliptical-cut and classical twisted tape insert for different fluids. Hence, in this study, heat transfer and entropy generation in a turbulent flow of an Alâ‚‚O₃-Cu/water hybrid nanofluid in a plain tube with classical and elliptical-cut twisted tape inserts are investigated numerically. The current study focuses on the heat transmission augmentation and thermodynamic irreversibility of steady and unsteady turbulent flows through pipes with elliptical-cut and classical twisted tape introduced under uniform or non-uniform well heat flux for water, hybrid-nanofluids (Alâ‚‚O₃-Cu/water), and nanofluids (CuO/water). This work uses Star-CCM+ for numerical simulations. The realizable k-ℇ model is employed to simulate the turbulent flow computationally. The findings are utilised to determine which type of tube and fluid provides the highest performance by quantifying gains in steady state (friction factor, heat transfer, and thermal performance factor) and unsteady state (transient heat transfer). The total entropy generation has been examined in this PhD study to determine the type of tube and fluid that reduces entropy generation. The results indicate that the heat transfer augmentation and thermal performance factor provided by the tube fitted with elliptical-cut twisted tape are greater than those provided by the tube supplied with classical twisted tape and the ordinary tube. This is because the pipe supplied with elliptical-cut twisted tape mixes the fluids better than the tube supplied with traditional twisted tape and the ordinary tube. Also, when the number of nanoparticles increases, heat transmission and thermal performance factors increase. Furthermore, TECT, hybrid nanofluids, and mass concentrations of nanoparticles affect the rate of total entropy production. The mixed convection of Alâ‚‚O₃-Cu/water hybrid nanofluid is also investigated in a vertical pipe supplied with elliptical-cut twisted tape inserts. Further, the local and total entropy production as well as Bejan number of the system are calculated. The results clearly demonstrate the effect of mixed convection on heat transfer, thermal performance factor, and entropy production. Where the factor of thermal performance and the rate of heat transfer increase of pipe systems under mixed convection exceed those under forced convection. Moreover, mixed convection has a significant impact on the minimisation of the total entropy production

    Numerical Analysis of Lithium-ion Battery Thermal Management System Towards Fire Safety Improvement

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    The development of alternative energy sources aims to tackle the energy crisis and climate change. Due to the intermittent nature of renewable energy, energy storage systems find antidotes to the current flaws for ensuring a stable and consistent power supply and reducing our reliance on fossil fuels. Lithium-ion batteries are the most used energy storage unit and have been applied in many fields, such as portable devices, building infrastructure, automotive industries, etc. Nevertheless, there remain significant safety concerns and fire risks. Thus, this has created much interest particularly in developing a comprehensive numerical tool to effectively assess the thermal behaviour and safety performance of battery thermal management systems (BTMs). In this thesis, a modelling framework was built by integrating the artificial neural network model with the computational fluid dynamics analysis. This includes (i) a comparison of natural ventilation and forced air cooling under various ambient pressures; (ii) an analysis of thermal behaviour and cooling performance with different ambient temperatures and ventilation velocities; and (iii) optimisation of battery pack layout for enhancing the cooling efficiency and reducing the risks of thermal runaway and fire outbreak. The optimal battery design achieved a 1.9% decrease in maximum temperature and a 4.5% drop in temperature difference. Moreover, this thesis delivered an overall review of BTMs employing machine learning (ML) techniques and the application of various ML models in battery fire diagnosis and early warning, which brings new insights into BTMs design and anticipates further smart battery systems. In addition, the battery thermal propagation effect under various abnormal heat generation locations was demonstrated to investigate several stipulating thermal propagation scenarios for enhancing battery thermal performances. The results indicated that various abnormal heat locations disperse heat to the surrounding coolant and other cells, affecting the cooling performance of the battery pack. The feasibility of compiling all pertinent information, including battery parameters and operation conditions, was studied in this thesis since ML models can build non-related factors relationships. The integrated numerical model offers a promising and efficient tool for simultaneously optimising multiple factors in battery design and facilitates a constructive understanding of battery performance and potential risks

    Hemodynamic Quantifications By Contrast-Enhanced Ultrasound:From In-Vitro Modelling To Clinical Validation

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    Synergies between Numerical Methods for Kinetic Equations and Neural Networks

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    The overarching theme of this work is the efficient computation of large-scale systems. Here we deal with two types of mathematical challenges, which are quite different at first glance but offer similar opportunities and challenges upon closer examination. Physical descriptions of phenomena and their mathematical modeling are performed on diverse scales, ranging from nano-scale interactions of single atoms to the macroscopic dynamics of the earth\u27s atmosphere. We consider such systems of interacting particles and explore methods to simulate them efficiently and accurately, with a focus on the kinetic and macroscopic description of interacting particle systems. Macroscopic governing equations describe the time evolution of a system in time and space, whereas the more fine-grained kinetic description additionally takes the particle velocity into account. The study of discretizing kinetic equations that depend on space, time, and velocity variables is a challenge due to the need to preserve physical solution bounds, e.g. positivity, avoiding spurious artifacts and computational efficiency. In the pursuit of overcoming the challenge of computability in both kinetic and multi-scale modeling, a wide variety of approximative methods have been established in the realm of reduced order and surrogate modeling, and model compression. For kinetic models, this may manifest in hybrid numerical solvers, that switch between macroscopic and mesoscopic simulation, asymptotic preserving schemes, that bridge the gap between both physical resolution levels, or surrogate models that operate on a kinetic level but replace computationally heavy operations of the simulation by fast approximations. Thus, for the simulation of kinetic and multi-scale systems with a high spatial resolution and long temporal horizon, the quote by Paul Dirac is as relevant as it was almost a century ago. The first goal of the dissertation is therefore the development of acceleration strategies for kinetic discretization methods, that preserve the structure of their governing equations. Particularly, we investigate the use of convex neural networks, to accelerate the minimal entropy closure method. Further, we develop a neural network-based hybrid solver for multi-scale systems, where kinetic and macroscopic methods are chosen based on local flow conditions. Furthermore, we deal with the compression and efficient computation of neural networks. In the meantime, neural networks are successfully used in different forms in countless scientific works and technical systems, with well-known applications in image recognition, and computer-aided language translation, but also as surrogate models for numerical mathematics. Although the first neural networks were already presented in the 1950s, the scientific discipline has enjoyed increasing popularity mainly during the last 15 years, since only now sufficient computing capacity is available. Remarkably, the increasing availability of computing resources is accompanied by a hunger for larger models, fueled by the common conception of machine learning practitioners and researchers that more trainable parameters equal higher performance and better generalization capabilities. The increase in model size exceeds the growth of available computing resources by orders of magnitude. Since 20122012, the computational resources used in the largest neural network models doubled every 3.43.4 months\footnote{\url{https://openai.com/blog/ai-and-compute/}}, opposed to Moore\u27s Law that proposes a 22-year doubling period in available computing power. To some extent, Dirac\u27s statement also applies to the recent computational challenges in the machine-learning community. The desire to evaluate and train on resource-limited devices sparked interest in model compression, where neural networks are sparsified or factorized, typically after training. The second goal of this dissertation is thus a low-rank method, originating from numerical methods for kinetic equations, to compress neural networks already during training by low-rank factorization. This dissertation thus considers synergies between kinetic models, neural networks, and numerical methods in both disciplines to develop time-, memory- and energy-efficient computational methods for both research areas

    Analysis, Design and Fabrication of Micromixers, Volume II

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    Micromixers are an important component in micrototal analysis systems and lab-on-a-chip platforms which are widely used for sample preparation and analysis, drug delivery, and biological and chemical synthesis. The Special Issue "Analysis, Design and Fabrication of Micromixers II" published in Micromachines covers new mechanisms, numerical and/or experimental mixing analysis, design, and fabrication of various micromixers. This reprint includes an editorial, two review papers, and eleven research papers reporting on five active and six passive micromixers. Three of the active micromixers have electrokinetic driving force, but the other two are activated by mechanical mechanism and acoustic streaming. Three studies employs non-Newtonian working fluids, one of which deals with nano-non-Newtonian fluids. Most of the cases investigated micromixer design
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