Parallel adaptive fluid-structure interaction simulations of explosions impacting on building structures

We pursue a level set approach to couple an Eulerian shock-capturing fluid solver with space–time refinement to an explicit solid dynamics solver for large deformations and fracture. The coupling algorithms considering recursively finer fluid time steps as well as overlapping solver updates are discussed. Our ideas are implemented in the AMROC adaptive fluid solver framework and are used for effective fluid–structure coupling to the general purpose solid dynamics code DYNA3D. Beside simulations verifying the coupled fluid–structure solver and assessing its parallel scalability, the detailed structural analysis of a reinforced concrete column under blast loading and the simulation of a prototypical blast explosion in a realistic multistory building are presented

Dynamical separation of spherical bodies in supersonic flow

An experimental and computational investigation of the unsteady separation behaviour of two spheres in Mach-4 flow is carried out. The spherical bodies, initially contiguous, are released with negligible relative velocity and thereafter fly freely according to the aerodynamic forces experienced. In experiments performed in a supersonic Ludwieg tube, nylon spheres are initially suspended in the test section by weak threads which are detached by the arrival of the flow. The subsequent sphere motions and unsteady flow structures are recorded using high-speed (13 kHz) focused shadowgraphy. The qualitative separation behaviour and the final lateral velocity of the smaller sphere are found to vary strongly with both the radius ratio and the initial alignment angle of the two spheres. More disparate radii and initial configurations in which the smaller sphere centre lies downstream of the larger sphere centre each increases the tendency for the smaller sphere to be entrained within the flow region bounded by the bow shock of the larger body, rather than expelled from this region. At a critical angle for a given radius ratio (or a critical radius ratio for a given angle), transition from entrainment to expulsion occurs; at this critical value, the final lateral velocity is close to maximum due to the same ‘surfing’ effect noted by Laurence & Deiterding (J. Fluid Mech., vol. 676, 2011, pp. 396–431) at hypersonic Mach numbers. A visualization-based tracking algorithm is used to provide quantitative comparisons between the experiments and high-resolution inviscid numerical simulations, with generally favourable agreement

The Peano software---parallel, automaton-based, dynamically adaptive grid traversals

We discuss the design decisions, design alternatives, and rationale behind the third generation of Peano, a framework for dynamically adaptive Cartesian meshes derived from spacetrees. Peano ties the mesh traversal to the mesh storage and supports only one element-wise traversal order resulting from space-filling curves. The user is not free to choose a traversal order herself. The traversal can exploit regular grid subregions and shared memory as well as distributed memory systems with almost no modifications to a serial application code. We formalize the software design by means of two interacting automata—one automaton for the multiscale grid traversal and one for the application-specific algorithmic steps. This yields a callback-based programming paradigm. We further sketch the supported application types and the two data storage schemes realized before we detail high-performance computing aspects and lessons learned. Special emphasis is put on observations regarding the used programming idioms and algorithmic concepts. This transforms our report from a “one way to implement things” code description into a generic discussion and summary of some alternatives, rationale, and design decisions to be made for any tree-based adaptive mesh refinement software

Dynamically adaptive data-driven simulation of extreme hydrological flows

Hydrological hazards such as storm surges, tsunamis, and rainfall-induced flooding are physically complex events that are costly in loss of human life and economic productivity. Many such disasters could be mitigated through improved emergency evacuation in real-time and through the development of resilient infrastructure based on knowledge of how systems respond to extreme events. Datadriven computational modeling is a critical technology underpinning these efforts. This investigation focuses on the novel combination of methodologies in forward simulation and data assimilation. The forward geophysical model utilizes adaptive mesh refinement (AMR), a process by which a computational mesh can adapt in time and space based on the current state of a simulation. The forward solution is combined with ensemble based data assimilation methods, whereby observations from an event are assimilated into the forward simulation to improve the veracity of the solution, or used to invert for uncertain physical parameters. The novelty in our approach is the tight two-way coupling of AMR and ensemble filtering techniques. The data assimilation system is implemented on various test cases that delve into the aspects of ensemble based assimilation filters. Additionally, data assimilation on tsunami models is analyzed and a methodology to map the uncertainties in the seabed deformation due to the associated earthquake to the water surface elevation forecast has been presented. Further, using other simulated environments such as the Chile tsunami event of February 2010, a systematic way to calibrate the assimilation system is presented. Finally, the technology is tested by assimilating actual gauge data from the Tohoku tsunami event. These advances offer the promise of significantly transforming data-driven, real-time modeling of hydrological hazards, with potentially broader applications in other science domains.Engineering Mechanic

Doctor of Philosophy

dissertationSolutions to Partial Di erential Equations (PDEs) are often computed by discretizing the domain into a collection of computational elements referred to as a mesh. This solution is an approximation with an error that decreases as the mesh spacing decreases. However, decreasing the mesh spacing also increases the computational requirements. Adaptive mesh re nement (AMR) attempts to reduce the error while limiting the increase in computational requirements by re ning the mesh locally in regions of the domain that have large error while maintaining a coarse mesh in other portions of the domain. This approach often provides a solution that is as accurate as that obtained from a much larger xed mesh simulation, thus saving on both computational time and memory. However, historically, these AMR operations often limit the overall scalability of the application. Adapting the mesh at runtime necessitates scalable regridding and load balancing algorithms. This dissertation analyzes the performance bottlenecks for a widely used regridding algorithm and presents two new algorithms which exhibit ideal scalability. In addition, a scalable space- lling curve generation algorithm for dynamic load balancing is also presented. The performance of these algorithms is analyzed by determining their theoretical complexity, deriving performance models, and comparing the observed performance to those performance models. The models are then used to predict performance on larger numbers of processors. This analysis demonstrates the necessity of these algorithms at larger numbers of processors. This dissertation also investigates methods to more accurately predict workloads based on measurements taken at runtime. While the methods used are not new, the application of these methods to the load balancing process is. These methods are shown to be highly accurate and able to predict the workload within 3% error. By improving the accuracy of these estimations, the load imbalance of the simulation can be reduced, thereby increasing the overall performance

Optimisation and analysis of injector geometry on a centre-bodiless continuous rotating detonation rocket engine

Rotating Detonation Engines (RDEs) provide a means of improving the efficiency of combustion engines at a time when reducing emissions is paramount. The key to their operation are RDE injectors, the two main injector design methodologies being the Semi-Impinging Injector (SII) method and Pintle injector method. In this thesis, the SII method was modified to add an additional degree of freedom (DOF) perpendicular to the two DOFs present in the SII method to develop the Modified Semi-Impinging Injector (MSII) method. This was done with the goal of improving the optimisation, implementation, and performance of the injector. The MSII and SII methods were compared where it was found that the injector flows could be categorised into two stages, the mixing phase where the mixing efficiency rose rapidly and the dampening phase where the mixing efficiency value stabilise over the length of the flow. The stabilised flow was found to remain relatively constant over the DOF ranges explored. Therefore, to determine the optimal injector, given that the speed of mixing is key to RDE performance, the characteristic length measurement was developed. The characteristic length is defined as the length required to meet 63.2% of the final stabilised value, with the lower the length, the faster the mixing. It was discovered that the mixing efficiency was the most relevant performance characteristic and that applying the characteristic length to the mixing efficiency allowed the mixing speed to be measured. It was found that the MSII injectors outperformed the SII injectors in mixing speed. The MSII method was then applied to a numerically simulated RDE and compared to a comparable Pintle injector method RDE. The two injector designs were simulated using Ansys Fluent by a detailed and simplified simulation method. It was found that the Ansys software had issues simulating RDEs resulting in only short runs of the engines, where the results were inconclusive and often contradictory. It was recommended that the MSII and SII methods be first empirically validated before more numerical simulations are conducted, and that with the information currently available, that the Pintle injector method is the best currently in use

Numerical modelling of inhomogeneous Liquefied Natural Gas (LNG) vapour cloud explosions

The main hazard of Liquified Natural Gas (LNG) is the flammable vapour cloud, which can extend to kilometres as a greenhouse gas or be ignited resulting in fire and explosions. This work aims to carry out a safety study on the vapour cloud explosion of LNG. Since most of the experimental research works are available for Hydrogen/Air mixture, in this present work, the first goal is to extend the existing physical understanding of deflagration-to-detonation transition (DDT), in hydrogen/air mixtures with transverse concentration gradients in closed channels. Explosions in homogenous (uniform) reactive mixtures have been widely investigated, both experimentally and numerically. However, in real accident scenarios, mixtures are usually inhomogeneous due to the localised nature of most fuel releases, buoyancy effects and the finite time between release and ignition. It is imperative to determine whether mixture inhomogeneity can increase the explosion hazard beyond what is known for homogeneous mixtures. Hence, extensive knowledge on these processes has been built up over decades for homogeneous mixtures. The approach is to identify similarities and differences caused by concentration gradients compared to homogenous mixtures with equal average hydrogen concentration. The dynamics of deflagration to detonation transition (DDT), and explosion modelling, have been studied using the newly assembled density-based solvers (VCEFoam) within the frame of OpenFOAM CFD toolbox. In order to evaluate the convective fluxes contribution, Harten–Lax–van Leer–Contact (HLLC) scheme is used for accurate shock capturing. The numerical code is initially verified by four sets of verification test cases. In addition to shock capturing verification, the capability of the current numerical code in capturing the detonation cellular structure has been examined. The CFD results have been compared against both quantitatively and qualitatively with the other previous works as well as an experimental observation. Then, numerical studies have been conducted to investigate flame acceleration and transition to detonation in both homogeneous and inhomogeneous hydrogen-air mixtures in obstructed and unobstructed channel configurations (in medium scale). The developed VCEFoam solver has been used within OpenFOAM, for these simulations. For the considered experiment (Boeck et al., 2016), different sets of configurations and fuel concentration have been studied. Three different geometry configuration such as BR00 (0% Blockage ratio, smooth channel), BR30 (30 % blockage ratio), and BR60 (60% blockage ratio), have been considered in this study. Also, in order to study the effect of a concentration gradient, different mixture concentrations have been investigated in both homogenous and inhomogeneous mixtures. A total of 17 conditions were simulated for different hydrogen concentrations in both homogeneous and inhomogeneous mixtures with and without obstructions. A high resolution grid is provided by using adaptive mesh refinement (AMR) method, which leads to 30 grid points per half reaction length (HRL). The numerical predictions were compared against previous experiments. Overall, the predicted flame tip velocities, overpressures, and locations of detonation onset are in good reasonably agreement with the measurements. It is found that, the transverse concentration gradients can either strengthen or weaken flame acceleration, depending on average hydrogen concentration and channel obstruction. The role of hydrodynamic instabilities and the effect of baroclinic torque and Richtmyer Meshkov (RM) instability have also been studied. The results support that RM instability is the primary source of turbulence generation in the present case. Then vapour cloud explosion study has been carried out for industrial scale scenarios (very large scale). A robust CFD methodology has been presented for modelling very large scale, vapour cloud explosions scenarios. A specific model has been considered for modelling the impact of flame-instabilities, particularly the thermal diffusive instabilities, and Darrieus Landau (DL) instabilities in large-scale models. The numerical model has initially been validated with the largest ever conducted indoor DDT and explosion experiments in the RUT facilities. Good qualitative agreement between the numerical prediction results and experimental measurements of RUT facilities has achieved. After demonstrating the code verification, LNG vapour cloud explosion scenarios, generated from the release of an evaporated liquefied natural gas have been studied. Two different possible incidents in LNG VCE have been studied; explosion modelling in onshore LNG plant and offshore LNG shipping. For the onshore LNG explosion study; an LNG plant has been considered to have fuel leakage from one of its storage tanks. In both onshore and offshore scenarios, the maximum recorded overpressure was below 1.2 bar, which is far below the CJ detonation limit (CJ detonation pressure, for stoichiometric methane/air mixtures, is 16.6 bar). Therefore, in this scenario, LNG flame acceleration was not enough to cause a detonation, and only a flame deflagration has been noticed. The results of the current study can be used in the context of safety to assess the potential risks of explosions in the energy industry

Local Mesh Refinement in COM3D for Combustion Simulation (KIT Scientific Reports ; 7670)

Conflict between resolution and total computational effort is a long term issue challenging scientists who are committed to develop computational tools with concerns of both accuracy and efficiency. The work is to implement the robust and effective LMR in the solution of Euler equations, the solution of Navier-Stokes equations and the simulation of detonation

Detonation Structure Simulation with AMROC

Numerical simulations can be the key to the thorough understanding of the multi-dimensional nature of transient detonation waves. But th