Computational fluid dynamics

An overview of computational fluid dynamics (CFD) activities at the Langley Research Center is given. The role of supercomputers in CFD research, algorithm development, multigrid approaches to computational fluid flows, aerodynamics computer programs, computational grid generation, turbulence research, and studies of rarefied gas flows are among the topics that are briefly surveyed

Numerical analysis of conservative unstructured discretisations for low Mach flows

This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving. https://authorservices.wiley.com/author-resources/Journal-Authors/licensing-and-open-access/open-access/self-archiving.htmlUnstructured meshes allow easily representing complex geometries and to refine in regions of interest without adding control volumes in unnecessary regions. However, numerical schemes used on unstructured grids have to be properly defined in order to minimise numerical errors. An assessment of a low-Mach algorithm for laminar and turbulent flows on unstructured meshes using collocated and staggered formulations is presented. For staggered formulations using cell centred velocity reconstructions the standard first-order method is shown to be inaccurate in low Mach flows on unstructured grids. A recently proposed least squares procedure for incompressible flows is extended to the low Mach regime and shown to significantly improve the behaviour of the algorithm. Regarding collocated discretisations, the odd-even pressure decoupling is handled through a kinetic energy conserving flux interpolation scheme. This approach is shown to efficiently handle variable-density flows. Besides, different face interpolations schemes for unstructured meshes are analysed. A kinetic energy preserving scheme is applied to the momentum equations, namely the Symmetry-Preserving (SP) scheme. Furthermore, a new approach to define the far-neighbouring nodes of the QUICK scheme is presented and analysed. The method is suitable for both structured and unstructured grids, either uniform or not. The proposed algorithm and the spatial schemes are assessed against a function reconstruction, a differentially heated cavity and a turbulent self-igniting diffusion flame. It is shown that the proposed algorithm accurately represents unsteady variable-density flows. Furthermore, the QUICK schemes shows close to second order behaviour on unstructured meshes and the SP is reliably used in all computations.Peer ReviewedPostprint (author's final draft

Kinetic Solvers with Adaptive Mesh in Phase Space

An Adaptive Mesh in Phase Space (AMPS) methodology has been developed for solving multi-dimensional kinetic equations by the discrete velocity method. A Cartesian mesh for both configuration (r) and velocity (v) spaces is produced using a tree of trees data structure. The mesh in r-space is automatically generated around embedded boundaries and dynamically adapted to local solution properties. The mesh in v-space is created on-the-fly for each cell in r-space. Mappings between neighboring v-space trees implemented for the advection operator in configuration space. We have developed new algorithms for solving the full Boltzmann and linear Boltzmann equations with AMPS. Several recent innovations were used to calculate the discrete Boltzmann collision integral with dynamically adaptive mesh in velocity space: importance sampling, multi-point projection method, and the variance reduction method. We have developed an efficient algorithm for calculating the linear Boltzmann collision integral for elastic and inelastic collisions in a Lorentz gas. New AMPS technique has been demonstrated for simulations of hypersonic rarefied gas flows, ion and electron kinetics in weakly ionized plasma, radiation and light particle transport through thin films, and electron streaming in semiconductors. We have shown that AMPS allows minimizing the number of cells in phase space to reduce computational cost and memory usage for solving challenging kinetic problems

Partitioning Optimization for Massively Parallel Transport Sweeps on Unstructured Grids

The field of radiation transport studies the distribution of radiation throughout a seven-dimensional phase-space consisting of time, space, energy, and direction. Radiation transport is described by the Boltzmann equation that can be solved stochastically or deterministically. The work presented in this dissertation utilizes the deterministic method known as the transport sweep, a popular technique that has been the subject of a large amount of research. We specifically focus on the parallel implementations of the transport sweep, and predicting the time it takes to sweep across a structured or unstructured mesh given a set of partitioning parameters, achieved through a time-to-solution estimator, written in Python. The time-to-solution estimator is tested against PDT, Texas A&M’s massively deterministic transport code. The time-to-solution estimator’s sweep time is within 10% of PDT’s sweep time for the majority of problems tested. We use the time-to-solution estimator as the objective function in an optimization scheme to attempt to get the partitions that lead to the fastest sweep time for a given problem and partitioning scheme. Two optimization methods are discussed: using a black box tool (scipy’s optimize library) and an intuitive method that prioritizes placing partitions in mesh locations that does not increase the number of cells (which we chose to name the CDF method). The time-to-solution estimator proved to not be smooth enough for a black box tool to work, so the CDF optimization method became the primary method. The CDF method proved effective for the majority of problems run, improving the time to solution over previously used partitioning scheme

Parallel algorithms for computational fluid dynamics on unstructured meshes

La simulació numèrica directa (DNS) de fluxos complexes és actualment una utopia per la majoria d'aplicacions industrials ja que els requeriments computacionals son massa elevats. Donat un flux, la diferència entre els recursos computacionals necessaris i els disponibles és cobreix mitjançant la modelització/simplificació d'alguns termes de les equacions originals que regeixen el seu comportament. El creixement continuat dels recursos computacionals disponibles, principalment en forma de super-ordinadors, contribueix a reduir la part del flux que és necessari aproximar. De totes maneres, obtenir la eficiència esperada dels nous super-ordinadors no és una tasca senzilla i, per aquest motiu, part de la recerca en el camp de la Mecànica de Fluids Computacional es centra en aquest objectiu. En aquest sentit, algunes contribucions s'han presentat en el marc d'aquesta tesis. El primer objectiu va ser el desenvolupament d'un codi de CFD de propòsit general i paral·lel, basat en la metodologia de volums finits en malles no estructurades, per resoldre problemes de multi-física. Aquest codi, anomenat TermoFluids (TF), té un disseny orientat a objectes i pensat per ser usat de forma altament eficient en els super-ordinadors actuals. Amb el temps, ha esdevingut pel grup una eina fonamental en projectes tant de recerca bàsica com d'interès industrial. En el context d'aquesta tesis, el treball s'ha focalitzat en el desenvolupament de dos de les llibreries més bàsiques de TermoFluids: i) La Basics Objects Library (BOL), que es una plataforma de software sobre la qual estan programades la resta de llibreries del codi, i que conté els mètodes algebraics i geomètrics fonamentals per la implementació paral·lela dels algoritmes de discretització, ii) la Linear Solvers Library (LSL), que conté un gran nombre de mètodes per resoldre els sistemes d'equacions lineals derivats de les discretitzacions. El primer capítol d'aquesta tesi conté les principals idees subjacents al disseny i la implementació de la BOL i la LSL, juntament amb alguns exemples i algunes aplicacions industrials. En els capítols posteriors hi ha una explicació detallada de solvers específics per algunes aplicacions concretes. En el segon capítol, es presenta un solver paral·lel i directe per la resolució de l'equació de Poisson per casos en els quals una de les direccions del domini té condicions d'homogeneïtat. En la simulació de fluxos incompressibles, l'equació de Poisson es resol almenys una vegada en cada pas de temps, convertint-se en una de les parts més costoses i difícils de paral·lelitzar del codi. El mètode que proposem és una combinació d'una descomposició directa de Schur (DDS) i una diagonalització de Fourier. La darrera descompon el sistema original en un conjunt de sub-sistemes 2D independents que es resolen mitjançant l'algorisme DDS. Atès que no s'imposen restriccions a les direccions no periòdiques del domini, aquest mètode és aplicable a la resolució de problemes discretitzats mitjançat l'extrusió de malles 2D no estructurades. L'escalabilitat d'aquest mètode ha estat provada amb èxit amb un màxim de 8192 CPU per malles de fins a ~10⁹ volums de control. En el darrer capitol capítol, es presenta un mètode de resolució per l'equació de Transport de Boltzmann (BTE). La estratègia emprada es basa en el mètode d'Ordenades Discretes i pot ser aplicat en discretitzacions no estructurades. El flux per a cada ordenada angular es resol amb un mètode de substitució equivalent a la resolució d'un sistema lineal triangular. La naturalesa seqüencial d'aquest procés fa de la paral·lelització de l'algoritme el principal repte. Diversos algorismes de substitució han estat analitzats, esdevenint una de les heurístiques proposades la millor opció en totes les situacions analitzades, amb excel·lents resultats. Els testos d'eficiència paral·lela s'han realitzat usant fins a 2560 CPU.Direct Numerical Simulation (DNS) of complex flows is currently an utopia for most of industrial applications because computational requirements are too high. For a given flow, the gap between the required and the available computing resources is covered by modeling/simplifying of some terms of the original equations. On the other hand, the continuous growth of the computing power of modern supercomputers contributes to reduce this gap, reducing hence the unresolved physics that need to be attempted with approximated models. This growth, widely relies on parallel computing technologies. However, getting the expected performance from new complex computing systems is becoming more and more difficult, and therefore part of the CFD research is focused on this goal. Regarding to it, some contributions are presented in this thesis. The first objective was to contribute to the development of a general purpose multi-physics CFD code. referred to as TermoFluids (TF). TF is programmed following the object oriented paradigm and designed to run in modern parallel computing systems. It is also intensively involved in many different projects ranging from basic research to industry applications. Besides, one of the strengths of TF is its good parallel performance demonstrated in several supercomputers. In the context of this thesis, the work was focused on the development of two of the most basic libraries that compose TF: I) the Basic Objects Library (BOL), which is a parallel unstructured CFD application programming interface, on the top of which the rest of libraries that compose TF are written, ii) the Linear Solvers Library (LSL) containing many different algorithms to solve the linear systems arising from the discretization of the equations. The first chapter of this thesis contains the main ideas underlying the design and the implementation of the BOL and LSL libraries, together with some examples and some industrial applications. A detailed description of some application-specific linear solvers included in the LSL is carried out in the following chapters. In the second chapter, a parallel direct Poisson solver restricted to problems with one uniform periodic direction is presented. The Poisson equation is solved, at least, once per time-step when modeling incompressible flows, becoming one of the most time consuming and difficult to parallelize parts of the code. The solver here proposed is a combination of a direct Schur-complement based decomposition (DSD) and a Fourier diagonalization. The latter decomposes the original system into a set of mutually independent 2D sub-systems which are solved by means of the DSD algorithm. Since no restrictions are imposed in the non-periodic directions, the overall algorithm is well-suited for solving problems discretized on extruded 2D unstructured meshes. The scalability of the solver has been successfully tested using up to 8192 CPU cores for meshes with up to 10 9 grid points. In the last chapter, a solver for the Boltzmann Transport Equation (BTE) is presented. It can be used to solve radiation phenomena interacting with flows. The solver is based on the Discrete Ordinates Method and can be applied to unstructured discretizations. The flux for each angular ordinate is swept across the computational grid, within a source iteration loop that accounts for the coupling between the different ordinates. The sequential nature of the sweep process makes the parallelization of the overall algorithm the most challenging aspect. Several parallel sweep algorithms, which represent different options of interleaving communications and calculations, are analyzed. One of the heuristics proposed consistently stands out as the best option in all the situations analyzed. With this algorithm, good scalability results have been achieved regarding both weak and strong speedup tests with up to 2560 CPUs