Wear modelling and simulation in moving geometries

The aim of this thesis is to describe the new wear modelling framework for the numerical simulation of fully coupled multiphase flows with dynamic boundary motion in response to wear. The framework considers the combination of coupling fluid flow, particle motion, wear modelling and boundary movement within a single model which has not yet been achieved in research. This is of significance in the minerals processing industry from both economical and safety aspects due to the degradation of components as a result of wear from the abrasive nature of slurry flows. The wear modelling framework uses a hybrid Eulerian-Lagrangian modelling approach which tracks particle trajectory with representative Lagrangian particles, with particle-particle interactions modelled statistically through the use of the kinetic theory of granular flow. This approach allows for full coupling of the phases with particle trajectory information required for wear modelling whilst remaining computationally feasible through the use of representative particles. Boundary movement in response to wear uses an anisotropic unstructured adap tive mesh approach which allows the mesh to move in response to a specified grid velocity and also optimised in order to provide resolution in areas important to the chosen fields and decrease in areas not required at specified time steps. The wear modelling framework takes place between a Python based Lagrangian particle module coupled with a computational fluid dynamics framework developed within Imperial College London called Fluidity. The framework can be applied to the study of component wear when subject to solid particles entrained in fluids. Component wear is a key consideration in many industries working with particle-laden flow as the study of wear through experimentation or in the field is time consuming and expensive. Simulation of jet impingement in two dimensions confirms the behaviour of boundary deformation in response to wear. A comprehensive study of Coriolis tester arm simulations are conducted to understand the effects of physical parameters on the wear profile obtained. Results are compared with experimental data from Weir Minerals and numerical simulations using the wear modelling framework are able to accurately capture the key characteristics of the wear profile and the behaviour of the particles.Open Acces

Parallel Processing of Eulerian-Lagrangian, Cell-based Adaptive Method for moving Boundary Problems.

In this study, issues and techniques related to the parallel processing of the Eulerian-Lagrangian method for multi-scale moving boundary computation are investigated. The scope of the study consists of the Eulerian approach for field equations, explicit interface-tracking, Lagrangian interface modification and reconstruction algorithms, and a cell-based unstructured adaptive mesh refinement (AMR) in a distributed-memory computation framework. We decomposed the Eulerian domain spatially along with AMR to balance the computational load of solving field equations, which is a primary cost of the entire solver. The Lagrangian domain is partitioned based on marker vicinities with respect to the Eulerian partitions to minimize inter-processor communication. Overall, the performance of an Eulerian task peaks at 10,000-20,000 cells per processor, and it is the upper bound of the performance of the Eulerian- Lagrangian method. Moreover, the load imbalance of the Lagrangian task is not as influential as the communication overhead of the Eulerian-Lagrangian tasks on the overall performance. To assess the parallel processing capabilities, a high Weber number drop collision is simulated. The high convective to viscous length scale ratios result in disparate length scale distributions; together with the moving and topologically irregular interfaces, the computational tasks require temporally and spatially resolved treatment adaptively. The techniques presented enable us to perform original studies to meet such computational requirements. Coalescence, stretch, and break-up of satellite droplets due xvii to the interfacial instability are observed in current study, and the history of interface evolution is in good agreement with the experimental data. The competing mechanisms of the primary and secondary droplet break up, along with the gas-liquid interfacial dynamics are systematically investigated. This study shows that Rayleigh-Taylor instability on the edge of an extruding sheet can be profound at the initial stage of collision, and Rayleigh-Plateau instability dominates the longitudinal disturbance on the fringe of the liquid sheet at a long time, which eventually results in primary breakups.PHDAerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/99988/1/ckkuan_1.pd

DEEP-LEARNING-ENHANCED MULTIPHYSICS FLOW COMPUTATIONS FOR PROPULSION APPLICATIONS

Numerical simulation is a critical part of research into and development of engineering systems. Engineers often use simulation to explore design settings both analytically and numerically before prototypes are built and tested. Even with the most advanced high performance computing facility, however, high-fidelity numerical simulations are extremely costly in time and resources. For example, a survey of the design parameter space for a single-element injector for a propulsion application (such as the RD-170 rocket engine) using the large eddy simulation technique may require several tens of millions of CPU-hours on a major computer cluster. This is because the flowfields can only be fully characterized by resolving a multitude of strongly coupled fluid dynamic, thermodynamic, transport, multiphase, and combustion processes. The cost is further increased by grid resolution requirements and by the effects of turbulence and high-pressure phenomena, which require treatment of real-fluid physics at supercritical conditions. If such models are used for statistical analysis or design optimization, the total computation time and resource requirements may render the work unfeasible. Recent developments in deep learning techniques offer the possibility of significant advances in dealing with these challenges and significant shortening of the time-to-solution. The general scope of this thesis research is to set the foundations for new paradigms in modeling, simulation, and design by applying deep learning techniques to recent developments in computational science. More specifically, the research aims at developing an integrated suite of data-driven surrogate modeling approaches and software for large-scale simulation problems. The techniques to be put into practice include: (1) deep neural networks for function approximation and solver acceleration, (2) deep autoencoders for nonlinear dimensionality reduction, and (3) spatiotemporal emulators based on multi-level neural networks for simulator approximation and rapid exploration of design spaces. A hierarchy of benchmark cases has been studied to generate databases to enable and support the development and verification of the proposed approaches. Emphasis is placed on canonical examples, as well as on engineering problems for aerospace and automotive applications, including supercritical turbulent flows in a rocket-engine swirl injector, and multiphase cavitating flows in a diesel engine injector.Ph.D

DEVELOPMENT OF A COMPUTATIONAL MODEL FOR A SIMULTANEOUS SIMULATION OF INTERNAL FLOW AND SPRAY BREAK-UP OF THE DIESEL INJECTION PROCESS

El proceso de atomización desde una vena o lámina líquida hasta multitud de gotas dispersas en un medio gaseoso ha sido un fenómeno de interés desde hace varias décadas, especialmente en el campo de los motores de combustión interna alternativos. Multitud de estudios experimentales han sido publicados al respecto, pues una buena mezcla de aire-combustible asegura una evaporación y combustión mucho más eficientes, aumentando la potencia del motor y reduciendo la cantidad de contaminantes emitidos. Con el auge de las técnicas computacionales, muchos modelos han sido desarrollados para estudiar este proceso de atomización y mezcla. Uno de los últimos modelos que han aparecido es el llamado ELSA (Eulerian-Lagrangian Spray Atomization), que utiliza un modelo Euleriano para la parte densa del chorro y cambia a un modelo Lagrangiano cuando la concentración de líquido es suficientemente pequeña, aprovechando de esta manera las ventajas de ambos. En el presente trabajo se ha desarrollado un modelo puramente Euleriano para estudiar la influencia de la geometría interna de la tobera de inyección en el proceso de atomización y mezcla. Se ha estudiado únicamente el proceso de inyección diésel. Este modelo permite resolver en un único dominio el flujo interno y el externo, evitando así las comunes simplificaciones y limitaciones de la interpolación entre ambos dominios resueltos por separado. Los resultados actuales son prometedores, el modelo predice con un error aceptable la penetración del chorro, el flujo másico y de cantidad de movimiento, los perfiles de velocidad y concentración, así como otros parámetros característicos del chorro.Martí Gómez-Aldaraví, P. (2014). DEVELOPMENT OF A COMPUTATIONAL MODEL FOR A SIMULTANEOUS SIMULATION OF INTERNAL FLOW AND SPRAY BREAK-UP OF THE DIESEL INJECTION PROCESS [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/43719TESISPremios Extraordinarios de tesis doctorale

High-Fidelity Modeling of Buoyancy-Driven Diffusion Flames Towards Fire Suppression

Buoyancy-driven diffusion flames have been widely studied as a canonical fire configuration due to practical and scientific interests. Numerical investigations are conducted in this dissertation to improve understandings of interactions and couplings among turbulence, chemistry, soot, and multiphase radiation in buoyancy-driven diffusion flames. A high-fidelity modeling framework based on OpenFOAM-5.x, including detailed models for chemistry, radiation, and soot, is developed to improve the numerical accuracy and the computational efficiency with scale-resolved simulations. A Monte Carlo ray tracing (MCRT) based radiation solver coupled with line-by-line databases is developed to describe gas and soot radiation. Detailed and efficient radiation models for water mists are developed and coupled with the MCRT solver. An adaptive hybrid integration chemistry solver is implemented to speed up finite-rate chemistry integration. A semi-empirical two-equation soot model is incorporated to describe soot dynamics. The developed multi-physical platform is systematically verified through a series of combustion-radiation systems including a laminar ethylene diffusion flame and four laminar methane diffusion flames with good agreement. The developed platform is subsequently employed to investigate a laboratory-scale turbulent pool fire. Good agreement with experiments on radiative heat fluxes, and with theories on flame temperature, velocity and puffing frequency, is achieved. Detailed investigations on interactions among chemistry, soot, radiation, and turbulence are performed to gain physical insights on modeling chemistry, soot and radiation. Drawn on the database from high-fidelity pool fire simulations, three physics-based reduced-order models including a flamelet model considering re-absorption, an optimized two-step mechanism for chemistry, and a simple soot model based on the laminar smoke point concept, are developed. Encouraging results are obtained using the reduced-order models with considerable savings in computational cost. Finally, to investigate radiative attenuation of water mists in fire suppression, a radiation model considering anisotropic scattering for water mists is developed and validated against theoretical values, and is adopted to obtain benchmark results for development of reduced-order radiation models

Advances in Modeling of Fluid Dynamics

This book contains twelve chapters detailing significant advances and applications in fluid dynamics modeling with focus on biomedical, bioengineering, chemical, civil and environmental engineering, aeronautics, astronautics, and automotive. We hope this book can be a useful resource to scientists and engineers who are interested in fundamentals and applications of fluid dynamics

Aeronautical engineering: A continuing bibliography with indexes (supplement 254)

This bibliography lists 538 reports, articles, and other documents introduced into the NASA scientific and technical information system in June 1990. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

MS FT-2-2 7 Orthogonal polynomials and quadrature: Theory, computation, and applications

Quadrature rules find many applications in science and engineering. Their analysis is a classical area of applied mathematics and continues to attract considerable attention. This seminar brings together speakers with expertise in a large variety of quadrature rules. It is the aim of the seminar to provide an overview of recent developments in the analysis of quadrature rules. The computation of error estimates and novel applications also are described