Particle Modeling of Fuel Plate Melting during Coolant Flow Blockage in HFIR

Cooling channel inlet flow blockage has damaged fuel in plate fueled reactors and contributes significantly to the probability of fuel damage based on Probabilistic Risk Assessment. A Smoothed Particle Hydrodynamics (SPH) model for fuel melt from inlet flow blockage for the High Flux Isotope Reactor is created. The model is coded for high throughput graphics processing unit (GPU) calculations. This modeling approach allows movement toward quantification of the uncertainty in fuel coolant flow blockage consequence assessment. The SPH modeling approach is convenient for following movement of fuel and coolant during melt progression and provides a tool for capturing the interactions of fuel melting into the coolant. The development of this new model is presented. The implementation of the model for GPU simulation is described. The model is compared against analytical solutions. Modeling of a scaled fuel melt progression is simulated for different conditions showing the sensitivities of melting fuel to conditions in the coolant channel

Petascale turbulence simulation using a highly parallel fast multipole method on GPUs

This paper reports large-scale direct numerical simulations of homogeneous-isotropic fluid turbulence, achieving sustained performance of 1.08 petaflop/s on gpu hardware using single precision. The simulations use a vortex particle method to solve the Navier-Stokes equations, with a highly parallel fast multipole method (FMM) as numerical engine, and match the current record in mesh size for this application, a cube of 4096^3 computational points solved with a spectral method. The standard numerical approach used in this field is the pseudo-spectral method, relying on the FFT algorithm as numerical engine. The particle-based simulations presented in this paper quantitatively match the kinetic energy spectrum obtained with a pseudo-spectral method, using a trusted code. In terms of parallel performance, weak scaling results show the fmm-based vortex method achieving 74% parallel efficiency on 4096 processes (one gpu per mpi process, 3 gpus per node of the TSUBAME-2.0 system). The FFT-based spectral method is able to achieve just 14% parallel efficiency on the same number of mpi processes (using only cpu cores), due to the all-to-all communication pattern of the FFT algorithm. The calculation time for one time step was 108 seconds for the vortex method and 154 seconds for the spectral method, under these conditions. Computing with 69 billion particles, this work exceeds by an order of magnitude the largest vortex method calculations to date

Real-time fluid simulations under smoothed particle hydrodynamics for coupled kinematic modelling in robotic applications

Although solids and fluids can be conceived as continuum media, applications of solid and fluid dynamics differ greatly from each other in their theoretical models and their physical behavior. That is why the computer simulators of each turn to be very disparate and case-oriented. The aim of this research work, captured in this thesis book, is to find a fluid dynamics model that can be implemented in near real-time with GPU processing and that can be adapted to typically large scales found in robotic devices in action with fluid media. More specifically, the objective is to develop these fast fluid simulations, comprising different solid body dynamics, to find a viable time kinematic solution for robotics. The tested cases are: i) the case of a fluid in a closed channel flowing across a cylinder, ii) the case of a fluid flowing across a controlled profile, and iii), the case of a free surface fluid control during pouring. The implementation of the former cases settles the formulations and constraints to the latter applications. The results will allow the reader not only to sustain the implemented models but also to break down the software implementation concepts for better comprehension. A fast GPU-based fluid dynamics simulation is detailed in the main implementation. The results show that it can be used in real-time to allow robotics to perform a blind pouring task with a conventional controller and no special sensing systems nor knowledge-driven prediction models would be necessary.Aunque los sólidos y los fluidos pueden concebirse como medios continuos, las aplicaciones de la dinámica de sólidos y fluidos difieren mucho entre sí en sus modelos teóricos y su comportamiento físico. Es por eso que los simuladores por computadora de cada uno son muy dispares y están orientados al caso de su aplicación. El objetivo de este trabajo de investigación, capturado en este libro de tesis, es encontrar un modelo de dinámica de fluidos que se pueda implementar cercano al tiempo real con procesamiento GPU y que se pueda adaptar a escalas típicamente grandes que se encuentran en dispositivos robóticos en acción con medios fluidos. Específicamente, el propósito es desarrollar estas simulaciones de fluidos rápidos, que comprenden diferentes dinámicas de cuerpos sólidos, para encontrar una solución cinemática viable para robótica. Los casos probados son: i) el caso de un fluido en canal cerrado que fluye a través de un cilindro, ii) el caso de un fluido que fluye a través de un alabe controlado, y iii), el caso del control de un fluido de superficie libre durante el vertido. La implementación de estos primeros casos establece las formulaciones y limitaciones de aplicaciones futuras. Los resultados permitirán al lector no solo sostener los modelos implementados sino también desglosar los conceptos de la implementación en software para una mejor comprensión. En la implementación principal se consigue una simulación rápida de dinámica de fluidos basada en GPU. Los resultados muestran que esta implementación se puede utilizar en tiempo real para permitir que la robótica realice una tarea de vertido ciego con un controlador convencional sin que sea necesario algún sistema de sensado especial ni algún modelo predictivo basados en el conocimiento.Programa de Doctorado en Ingeniería Eléctrica, Electrónica y Automática por la Universidad Carlos III de MadridPresidente: Carmen Martínez Arévalo.- Secretario: Luis Santiago Garrido Bullón.- Vocal: Benjamín Hernández Arreguí

Working With Incremental Spatial Data During Parallel (GPU) Computation

Central to many complex systems, spatial actors require an awareness of their local environment to enable behaviours such as communication and navigation. Complex system simulations represent this behaviour with Fixed Radius Near Neighbours (FRNN) search. This algorithm allows actors to store data at spatial locations and then query the data structure to find all data stored within a fixed radius of the search origin. The work within this thesis answers the question: What techniques can be used for improving the performance of FRNN searches during complex system simulations on Graphics Processing Units (GPUs)? It is generally agreed that Uniform Spatial Partitioning (USP) is the most suitable data structure for providing FRNN search on GPUs. However, due to the architectural complexities of GPUs, the performance is constrained such that FRNN search remains one of the most expensive common stages between complex systems models. Existing innovations to USP highlight a need to take advantage of recent GPU advances, reducing the levels of divergence and limiting redundant memory accesses as viable routes to improve the performance of FRNN search. This thesis addresses these with three separate optimisations that can be used simultaneously. Experiments have assessed the impact of optimisations to the general case of FRNN search found within complex system simulations and demonstrated their impact in practice when applied to full complex system models. Results presented show the performance of the construction and query stages of FRNN search can be improved by over 2x and 1.3x respectively. These improvements allow complex system simulations to be executed faster, enabling increases in scale and model complexity

Combined SPH-DEM modeling of solid-fluid interactions

Evaluation of Solid-Fluid interaction is of high significance in all engineering fields. In this paper, the Smoothed Particle Hydrodynamics (SPH) and the Discrete Element Method (DEM) were employed to simulate solids and fluids, respectively. As for the simulation of water behavior, first, a single-phase “dam break” experiment is modeled by the SPH. In this model, variable smoothing length and an almost novel boundary method were utilized which resulted in a tremendous boost in its resemblance to the experiment. To couple these methods (SPH and DEM), three approaches were proposed and validated against a famous experimental test named “dam break with an elastic gate test”. Finally, to be sure of the correctness of these approaches, an elastic plate under a water column in the hydrostatic condition was simulated and the error was 2 percent in comparison with the analytical solution. In pursuit of having short run-times, parallel computing on GPU (CUDA) was employed, and a robust nearest neighbor search (NNS) algorithm was modified and developed

Numerical modelling of interaction between aluminium structure and explosion in soil

In this paper, a graphics processing unit-accelerated smoothed particle hydrodynamics solver is presented to simulate the three-dimensional explosions in soils and their damage to aluminium structures. To achieve this objective, a number of equations of state and constitutive models required to close the governing equations are incorporated into the proposed smoothed particle hydrodynamics framework, including the Jones-Wilkins-Lee equation of state for explosive materials, the Grüneisen equation of state for metals, the elastic-perfectly plastic constitutive model for metals, and the elastoplastic and elasto-viscoplastic constitutive models for soils. The proposed smoothed particle hydrodynamics methodology was implemented using the Compute Unified Device Architecture programming interface on an NVIDIA graphics processing unit in order to improve the computational efficiency. The various components of the proposed methodology were validated using four test cases, namely, a C4 detonation and an aluminium bar expanded by denotation to validate the modelling of explosion, a cylindrical Taylor bar impact test case to validate the modelling of large deformation in metals, a sand collapse test for the modelling of soils. Following the validation, the proposed method was used to simulate the detonation of an explosive material (C4) in soil and the concomitant deformation of an aluminium plate resulting from this explosion. The predicted results of this simulation are shown to be in good conformance with available experimental data. Finally, it is shown that the proposed graphics processing unit-accelerated SPH solver is able to model interaction problems involving millions of particles in a reasonable time. © 2021 The Author

Interstitial-Scale Modeling of Packed-Bed Reactors

Packed-beds are common to adsorption scrubbers, packed bed reactors, and trickle-bed reactors widely used across the petroleum, petrochemical, and chemical industries. The micro structure of these packed beds is generally very complex and has tremendous influence on heat, mass, and momentum transport phenomena on the micro and macro length scales within the bed. On a reactor scale, bed geometry strongly influences overall pressure drop, residence time distribution, and conversion of species through domain-fluid interactions. On the interstitial scale, particle boundary layer formation, fluid to particle mass transfer, and local mixing are controlled by turbulence and dissipation existing around packed particles. In the present research, a CFD model is developed using OpenFOAM: www.openfoam.org) to directly resolve momentum and scalar transport in both laminar and turbulent flow-fields, where the interstitial velocity field is resolved using the Navier-Stokes equations: i.e. no pseudo-continuum based assumptions. A discussion detailing the process of generating the complex domain using a Monte-Carlo packing algorithm is provided, along with relevant details required to generate an arbitrary polyhedral mesh describing the packed-bed. Lastly, an algorithm coupling OpenFOAM with a linear system solver using the graphics processing unit: GPU) computing paradigm was developed and will be discussed in detail