Parallel fluid dynamics for the film and animation industries

Includes bibliographical references (leaves 142-149).The creation of automated fluid effects for film and media using computer simulations is popular, as artist time is reduced and greater realism can be achieved through the use of numerical simulation of physical equations. The fluid effects in today’s films and animations have large scenes with high detail requirements. With these requirements, the time taken by such automated approaches is large. To solve this, cluster environments making use of hundreds or more CPUs have been used. This overcomes the processing power and memory limitations of a single computer and allows very large scenes to be created. One of the newer methods for fluid simulation is the Lattice Boltzmann Method (LBM). This is a cellular automata type of algorithm, which parallelizes easily. An important part of the process of parallelization is load balancing; the distribution of computation amongst the available computing resources in the cluster. To date, the parallelization of the Lattice Boltzmann method only makes use of static load balancing. Instead, it is possible to make use of dynamic load balancing, which adjusts the computation distribution as the simulation progresses. Here, we investigate the use of the LBM in conjunction with a Volume of Fluid (VOF) surface representation in a parallel environment with the aim of producing large scale scenes for the film and animation industries. The VOF method tracks mass exchange between cells of the LBM. In particular, we implement the new dynamic load balancing algorithm to improve the efficiency of the fluid simulation using this method. Fluid scenes from films and animations have two important requirements: the amount of detail and the spatial resolution of the fluid. These aspects of the VOF LBM are explored by considering the time for scene creation using a single and multi-CPU implementation of the method. The scalability of the method is studied by plotting the run time, speedup and efficiency of scene creation against the number of CPUs. From such plots, an estimate is obtained of the feasibility of creating scenes of a giving level of detail. Such estimates enable the recommendation of architectures for creation of specific scenes. Using a parallel implementation of the VOF LBM method we successfully create large scenes with great detail. In general, considering the significant amounts of communication required for the parallel method, it is shown to scale well, favouring scenes with greater detail. The scalability studies show that the new dynamic load balancing algorithm improves the efficiency of the parallel implementation, but only when using lower number of CPUs. In fact, for larger number of CPUs, the dynamic algorithm reduces the efficiency. We hypothesise the latter effect can be removed by making using of centralized load balancing decision instead of the current decentralized approach. The use of a cluster comprising of 200 CPUs is recommended for the production of large scenes of a grid size 6003 in a reasonable time frame

System Design for Digital Experimentation and Explanation Generation

Experimentation increasingly drives everyday decisions in modern life, as it is considered by some to be the gold standard for determining cause and effect within any system. Digital experiments have expanded the scope and frequency of experiments, which can range in complexity from classic A/B tests to contextual bandits experiments, which share features with reinforcement learning. Although there exists a large body of prior work on estimating treatment effects using experiments, this prior work did not anticipate the new challenges and opportu- nities introduced by digital experimentation. Novel errors and threats to validity arise at the intersection of software and experimentation, especially when experimentation is in service of understanding humans behavior or autonomous black-box agents. We present several novel tools for automating aspects of the experimentation- analysis pipeline. We propose new methods for evaluating online field experimentation, automatically generating corresponding analyses of treatment effects. We then draw the connection between software testing and experimental design and argue that applying software testing techniques to a kind of autonomous agent—a deep reinforcement learning agent—to demonstrate the need for novel testing paradigms when a software stack uses learned components that may have emergent behavior. We show how our system may be used to evaluate claims made about the behavior of autonomous agents and find that some claims do not hold up under test. Finally, we show how to produce explanations of the behavior of black-box software-defined agents interacting with white-box environments via automated experimentation. We show how an automated system can be used for exploratory data analysis, with a human in the loop, to investigate a large space of possible counterfactual explanations

GASFLOW-MPI: A Scalable Computational Fluid Dynamics Code for Gases, Aerosols and Combustion. Band 1 (Theory and Computational Model (Revision 1.0). (KIT Scientific Reports ; 7710)

Karlsruhe Institute of Technology (KIT) is developing the parallel computational fluid dynamics code GASFLOW-MPI as a best-estimate tool for predicting transport, mixing, and combustion of hydrogen and other gases in nuclear reactor containments and other facility buildings. GASFLOW-MPI is a finite-volume code based on proven computational fluid dynamics methodology that solves the compressible Navier-Stokes equations for three-dimensional volumes in Cartesian or cylindrical coordinates

On the Processing of Highly Nonlinear Solitarywaves and Guided Ultrasonic Waves for Structural Health Monitoring and Nondestructive Evaluation

The in-situ measurement of thermal stress in civil and mechanical structures may prevent structural anomalies such as unexpected buckling. In the first half of the dissertation, we present a study where highly nonlinear solitary waves (HNSWs) were utilized to measure axial stress in slender beams. HNSWs are compact non-dispersive waves that can form and travel in nonlinear systems such as one-dimensional chains of particles. The effect of the axial stress acting in a beam on the propagation of HNSWs was studied. We found that certain features of the solitary waves enable the measurement of the stress. In general, most guided ultrasonic waves (GUWs)-based health monitoring approaches for structural waveguides are based on the comparison of testing data to baseline data. In the second half of the dissertation, we present a study where some baseline-free signal processing algorithms were presented and applied to numerical and experimental data for the structural health monitoring (SHM) of underwater or dry structures. The algorithms are based on one or more of the following: continuous wavelet transform, empirical mode decomposition, Hilbert transform, competitive optimization algorithm, probabilistic methods. Moreover, experimental data were also processed to extract some features from the time, frequency, and joint timefrequency domains. These features were then fed to a supervised learning algorithm based on artificial neural networks to classify the types of defect. The methods were validated using the numerical model of a plate and a pipe, and the experimental study of a plate in water. In experiment, the propagation of ultrasonic waves was induced by means of laser pulses or transducer and detected with an array of immersion transducers. The results demonstrated that the algorithms are effective, robust against noise, and able to localize and classify the damage

Vibration, Control and Stability of Dynamical Systems

From Preface: This is the fourteenth time when the conference “Dynamical Systems: Theory and Applications” gathers a numerous group of outstanding scientists and engineers, who deal with widely understood problems of theoretical and applied dynamics. Organization of the conference would not have been possible without a great effort of the staff of the Department of Automation, Biomechanics and Mechatronics. The patronage over the conference has been taken by the Committee of Mechanics of the Polish Academy of Sciences and Ministry of Science and Higher Education of Poland. It is a great pleasure that our invitation has been accepted by recording in the history of our conference number of people, including good colleagues and friends as well as a large group of researchers and scientists, who decided to participate in the conference for the first time. With proud and satisfaction we welcomed over 180 persons from 31 countries all over the world. They decided to share the results of their research and many years experiences in a discipline of dynamical systems by submitting many very interesting papers. This year, the DSTA Conference Proceedings were split into three volumes entitled “Dynamical Systems” with respective subtitles: Vibration, Control and Stability of Dynamical Systems; Mathematical and Numerical Aspects of Dynamical System Analysis and Engineering Dynamics and Life Sciences. Additionally, there will be also published two volumes of Springer Proceedings in Mathematics and Statistics entitled “Dynamical Systems in Theoretical Perspective” and “Dynamical Systems in Applications”

Numerical simulation of slug flow with high viscosity liquid

Slug flow is one of the most common flow patterns in multiphase oil/gas transport in pipelines. Due to its complexity, it poses numerous challenges to model development. Industrial slug flow models are one-dimensional and can give poor predictions in situations where the associated closures and simplifications are no longer valid. Computational Fluid Dynamics (CFD) facilitates high-resolution studies of slug flow dynamics by implementing multi-dimensional models. Understanding the physics of slug flow would help identify the main flow mechanisms to be modelled and enable the development of mechanistic slug flow models for commercial software. In this thesis, a computational approach is developed. The front tracking method (FTM) (Tryggvason et al. 2001) and the phase field method (PFM) (Ding et al. 2007) are used to model long bubbles in slug flows. Results of the validation study show good agreement with DeBisschop et al. (2002), who performed simulations of long bubbles in two-dimensional channels in the creeping-flow limit. Their work is extended here to moderate Archimedes numbers (10 < Ar < 200). The effects of inertia, surface tension, viscosity and inclination angle on the terminal velocity and the shape of a long bubble in different flow conditions are investigated. Furthermore, the FTM is coupled with a discrete bubble tracking method (DBTM), which has resulted in a robust hybrid method to model small and large bubbles simultaneously in an Eulerian-Lagrangian fashion. The method allows the study of the interaction of the small bubbles with a long bubble. The work is extended further to three dimensions using the PFM. The validation study shows good agreement with the present two-dimensional numerical work. The geometry is converted from a square channel to a pipe to facilitate a more realistic simulation of slug flow in pipelines. This work will provide a rigorous basis for developing simplified models.Open Acces

13th Annual Review of Progress in Applied Computational Electromagnetics at the Naval Postgraduate School, Monterey, CA, March 17-21, 1997, Conference Proceedings Volumes I & II

Includes Volumes 1 &