A Survey of Ocean Simulation and Rendering Techniques in Computer Graphics

This paper presents a survey of ocean simulation and rendering methods in computer graphics. To model and animate the ocean's surface, these methods mainly rely on two main approaches: on the one hand, those which approximate ocean dynamics with parametric, spectral or hybrid models and use empirical laws from oceanographic research. We will see that this type of methods essentially allows the simulation of ocean scenes in the deep water domain, without breaking waves. On the other hand, physically-based methods use Navier-Stokes Equations (NSE) to represent breaking waves and more generally ocean surface near the shore. We also describe ocean rendering methods in computer graphics, with a special interest in the simulation of phenomena such as foam and spray, and light's interaction with the ocean surface

A GPU-accelerated package for simulation of flow in nanoporous source rocks with many-body dissipative particle dynamics

Mesoscopic simulations of hydrocarbon flow in source shales are challenging, in part due to the heterogeneous shale pores with sizes ranging from a few nanometers to a few micrometers. Additionally, the sub-continuum fluid-fluid and fluid-solid interactions in nano- to micro-scale shale pores, which are physically and chemically sophisticated, must be captured. To address those challenges, we present a GPU-accelerated package for simulation of flow in nano- to micro-pore networks with a many-body dissipative particle dynamics (mDPD) mesoscale model. Based on a fully distributed parallel paradigm, the code offloads all intensive workloads on GPUs. Other advancements, such as smart particle packing and no-slip boundary condition in complex pore geometries, are also implemented for the construction and the simulation of the realistic shale pores from 3D nanometer-resolution stack images. Our code is validated for accuracy and compared against the CPU counterpart for speedup. In our benchmark tests, the code delivers nearly perfect strong scaling and weak scaling (with up to 512 million particles) on up to 512 K20X GPUs on Oak Ridge National Laboratory's (ORNL) Titan supercomputer. Moreover, a single-GPU benchmark on ORNL's SummitDev and IBM's AC922 suggests that the host-to-device NVLink can boost performance over PCIe by a remarkable 40\%. Lastly, we demonstrate, through a flow simulation in realistic shale pores, that the CPU counterpart requires 840 Power9 cores to rival the performance delivered by our package with four V100 GPUs on ORNL's Summit architecture. This simulation package enables quick-turnaround and high-throughput mesoscopic numerical simulations for investigating complex flow phenomena in nano- to micro-porous rocks with realistic pore geometries

Emergent behavior of soil fungal dynamics:influence of soil architecture and water distribution

Macroscopic measurements and observations in two-dimensional soil-thin sections indicate that fungal hyphae invade preferentially the larger, air-filled pores in soils. This suggests that the architecture of soils and the microscale distribution of water are likely to influence significantly the dynamics of fungal growth. Unfortunately, techniques are lacking at present to verify this hypothesis experimentally, and as a result, factors that control fungal growth in soils remain poorly understood. Nevertheless, to design appropriate experiments later on, it is useful to indirectly obtain estimates of the effects involved. Such estimates can be obtained via simulation, based on detailed micron-scale X-ray computed tomography information about the soil pore geometry. In this context, this article reports on a series of simulations resulting from the combination of an individual-based fungal growth model, describing in detail the physiological processes involved in fungal growth, and of a Lattice Boltzmann model used to predict the distribution of air-liquid interfaces in soils. Three soil samples with contrasting properties were used as test cases. Several quantitative parameters, including Minkowski functionals, were used to characterize the geometry of pores, air-water interfaces, and fungal hyphae. Simulation results show that the water distribution in the soils is affected more by the pore size distribution than by the porosity of the soils. The presence of water decreased the colonization efficiency of the fungi, as evinced by a decline in the magnitude of all fungal biomass functional measures, in all three samples. The architecture of the soils and water distribution had an effect on the general morphology of the hyphal network, with a "looped" configuration in one soil, due to growing around water droplets. These morphologic differences are satisfactorily discriminated by the Minkowski functionals, applied to the fungal biomass

Accelerating Eulerian Fluid Simulation With Convolutional Networks

Efficient simulation of the Navier-Stokes equations for fluid flow is a long standing problem in applied mathematics, for which state-of-the-art methods require large compute resources. In this work, we propose a data-driven approach that leverages the approximation power of deep-learning with the precision of standard solvers to obtain fast and highly realistic simulations. Our method solves the incompressible Euler equations using the standard operator splitting method, in which a large sparse linear system with many free parameters must be solved. We use a Convolutional Network with a highly tailored architecture, trained using a novel unsupervised learning framework to solve the linear system. We present real-time 2D and 3D simulations that outperform recently proposed data-driven methods; the obtained results are realistic and show good generalization properties.Comment: Significant revisio

Gray-scale Lattice Boltzmann – an attempt to bridge multiple length scales

Understanding and controlling the flow of fluids through porous media such as rocks, fibres, granular media and paper is of fundamental significance to a variety of industries such as oil and gas, chemical production, health and sanitary products. Numerical modelling of this physical process can be difficult not only because of the complex, three- dimensional topology of the porous medium but also because of computational limitations. For example, shale rocks which is now being intensively investigated for its oil and gas resources have porosity over a wide range of length scales from nano-metres up to millimetres. It has been shown that the micro-porosity is fundamental to the fluid movement through the rock. However, current numerical models, which work off computed tomo- graphical (CT) scans of the rock will be excessively large if they are to fully model all length scales which may span six or more orders of magnitude. Here we consider the development of a lattice Boltzmann (LB) technique which may be able to solve the fluid flow over a wide range of length scales. In the past LB techniques have proven to be ideal to model fluid flow in complex porous media since it can readily import and process digital data from CT scans. Hence the fluid flow field is quickly determined and permeabilities can be predicted. However, when the CT data contains micro- porosity, the conventional LB method is not applicable and a modified LB method needs to be developed. Here we consider a gray-scale LB method which works on voxels which are not fully void or solid but something in between, i.e. each voxel is partially resistant to fluid flow. We firstly outline the model, then validate it on test cases and then demonstrate its applicability on real porous media. We develop models not only for single phase fluid flow, but also multiphase fluid flow (i.e. a gas and a liquid) as well as a temperature model, where the temperature field is advected by the fluid flow. For all these cases the models are developed and validated and then demonstrated on realistic media. It is shown that the gray-scale LB model may be able to solve for fluid flow through multiple length scales – a difficult computational problem which is of increasing significance in many real-world applications

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

Challenges in imaging and predictive modeling of rhizosphere processes

Background Plant-soil interaction is central to human food production and ecosystem function. Thus, it is essential to not only understand, but also to develop predictive mathematical models which can be used to assess how climate and soil management practices will affect these interactions. Scope In this paper we review the current developments in structural and chemical imaging of rhizosphere processes within the context of multiscale mathematical image based modeling. We outline areas that need more research and areas which would benefit from more detailed understanding. Conclusions We conclude that the combination of structural and chemical imaging with modeling is an incredibly powerful tool which is fundamental for understanding how plant roots interact with soil. We emphasize the need for more researchers to be attracted to this area that is so fertile for future discoveries. Finally, model building must go hand in hand with experiments. In particular, there is a real need to integrate rhizosphere structural and chemical imaging with modeling for better understanding of the rhizosphere processes leading to models which explicitly account for pore scale processes