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Abstract To realistic and efficient capture microscopic features of fluid surface, we proposed a novel method for creating small-scale surface details. In this paper, we introduced a surface tension and adhesion model to simulate surface details, which refined the cohesion term and area minimization term. It modified the calculation of surface tension and adhesion and enlarged the support length for cohesion, which makes the microscopic characteristics of surface details more visible. In addition, we integrated this model with a Divergence-free SPH method which fulfills constant density condition and divergence-free condition simultaneously. The experimental results show that our method can well simulate small-scale details of fluid surface in various scenarios meanwhile improves the computational stability and efficiency. [ABSTRACT FROM AUTHOR]

Energy is of great theoretical and practical importance in flotation. Some progress has been achieved in recent years. However, the study of energy consumed in the flotation process is still not fully developed. In this review, we analyse the energy generation, energy detection, and influence of the energy level on the flotation effect, which remains a popular research category in flotation energy research. A theoretical model of flotation energy transmission and transformation is proposed. The techniques for measuring energy consumption in the flotation process are systematically summarized. The flow-field simulation method is confined to two-phase flows and is not fully suitable for three-phase flows. The motor power measurement method and dissipative structure theory analysis method are used to analyse the flotation process on the macroscopic level, while the Extended Derjaguin-landau-Verwey-Overbeek(EDLVO) theory and the flow-field test method can be used to study the microprocesses of flotation. This review provides more insight into the future research of flotation energy, and optimizes the flotation process and equipment. It is necessary to further develop flotation energy measurement technology, especially for microprocesses, in order to reveal the turbulent energy transfer efficiency in the flotation process. [ABSTRACT FROM AUTHOR]

This study aims to develop a novel method by which visually to simulate water flow paths on building façades. Rainwater runoff affects the designs of façades in terms of safety and aesthetics because runoff leaves dirt and stains on an aesthetic façade. The first step is to review flow simulation algorithms and identify its limitations in fluid visualization research on flow path simulations. The second step is to review an existing CFD program to identify its limitations, and then establish the goals of the newly proposed method. The third step is to identify the properties and behaviors of water on a surface, including basic fluid mechanics to establish the mechanical relationship between the water and the façade material. The fourth step involves an experiment with water flows to reveal their characteristics based on the literature. The fifth step is to develop an algorithm which visually simulates water flows on a building façade. As a result, “Rainflow01” and “Rainflow02” are developed based on the open-source Grasshopper component “Drainage Polysurface” and Rhino. Rainflow01 and Rainflow02, which work based on the angle variation and critical sliding angle of the water path, present an innovative approach for predictions of water paths over a façade. [ABSTRACT FROM AUTHOR]

We introduce a new advection scheme for fluid animation. Our main contribution is the use of long-term temporal changes in pressure to extend the commonly used semi-Lagrangian scheme further back along the time axis. Our algorithm starts by tracing sample points along a trajectory following the velocity field backwards in time for many steps. During this backtracing process, the pressure gradient along the path is integrated to correct the velocity of the current time step. We show that our method effectively suppresses numerical diffusion, retains small-scale vorticity, and provides better long-term kinetic energy preservation. [ABSTRACT FROM AUTHOR]

We propose a temporally coherent generative model addressing the super-resolution problem for fluid flows. Our work represents a first approach to synthesize four-dimensional physics fields with neural networks. Based on a conditional generative adversarial network that is designed for the inference of three-dimensional volumetric data, our model generates consistent and detailed results by using a novel temporal discriminator, in addition to the commonly used spatial one. Our experiments show that the generator is able to infer more realistic high-resolution details by using additional physical quantities, such as low-resolution velocities or vorticities. Besides improvements in the training process and in the generated outputs, these inputs offer means for artistic control as well. We additionally employ a physics-aware data augmentation step, which is crucial to avoid overfitting and to reduce memory requirements. In this way, our network learns to generate adverted quantities with highly detailed, realistic, and temporally coherent features. Our method works instantaneously, using only a single time-step of low-resolution fluid data. We demonstrate the abilities of our method using a variety of complex inputs and applications in two and three dimensions. [ABSTRACT FROM AUTHOR]

We present a data-driven technique to instantly predict how fluid flows around various three-dimensional objects. Such simulation is useful for computational fabrication and engineering, but is usually computationally expensive since it requires solving the Navier-Stokes equation for many time steps. To accelerate the process, we propose a machine learning framework which predicts aerodynamic forces and velocity and pressure fields given a three-dimensional shape input. Handling detailed free-form three-dimensional shapes in a data-driven framework is challenging because machine learning approaches usually require a consistent parametrization of input and output. We present a novel PolyCube maps-based parametrization that can be computed for three-dimensional shapes at interactive rates. This allows us to efficiently learn the nonlinear response of the flow using a Gaussian process regression. We demonstrate the effectiveness of our approach for the interactive design and optimization of a car body. [ABSTRACT FROM AUTHOR]

The Laplacian Eigenfunction method for fluid simulation, which we refer to as Eigenfluids, introduced an elegant new way to capture intricate fluid flows with near-zero viscosity. However, the approach does not scale well, as the memory cost grows prohibitively with the number of eigenfunctions. The method also lacks generality, because the dynamics are constrained to a closed box with Dirichlet boundaries, while open, Neumann boundaries are also needed in most practical scenarios. To address these limitations, we present a set of analytic eigenfunctions that supports uniform Neumann and Dirichlet conditions along each domain boundary, and show that by carefully applying the discrete sine and cosine transforms, the storage costs of the eigenfunctions can be made completely negligible. The resulting algorithm is both faster and more memory-efficient than previous approaches, and able to achieve lower viscosities than similar pseudo-spectral methods. We are able to surpass the scalability of the original Laplacian Eigenfunction approach by over two orders of magnitude when simulating rectangular domains. Finally, we show that the formulation allows forward scattering to be directed in a way that is not possible with any other method. [ABSTRACT FROM AUTHOR]

Advection-projection methods for fluid animation are widely appreciated for their stability and efficiency. However, the projection step dissipates energy from the system, leading to artificial viscosity and suppression of small-scale details. We propose an alternative approach for detail-preserving fluid animation that is surprisingly simple and effective. We replace the energy-dissipating projection operator applied at the end of a simulation step by an energy-preserving reflection operator applied at mid-step. We show that doing so leads to two orders of magnitude reduction in energy loss, which in turn yields vastly improved detail-preservation. We evaluate our reflection solver on a set of 2D and 3D numerical experiments and show that it compares favorably to state-of-the-art methods. Finally, our method integrates seamlessly with existing projection-advection solvers and requires very little additional implementation. [ABSTRACT FROM AUTHOR]

Generating realistic fluid simulations remains computationally expensive, and animators can expend enormous effort trying to achieve a desired motion. To reduce such costs, several methods have been developed in which high-resolution turbulence is synthesized as a post process. Since global motion can then be obtained using a fast, low-resolution simulation, less effort is needed to create a realistic animation with the desired behavior. While much research has focused on accelerating the low-resolution simulation, the problem controlling the behavior of the turbulent, high-resolution motion has received little attention. In this paper, we show that style transfer methods from image editing can be adapted to transfer the turbulent style of an existing fluid simulation onto a new one. We do this by extending example-based image synthesis methods to handle velocity fields using a combination of patch-based and optimization-based texture synthesis. This approach allows us to take into account the incompressibility condition, which we have found to be a important factor during synthesis. Using our method, a user can easily and intuitively create high-resolution fluid animations that have a desired turbulent motion. [ABSTRACT FROM AUTHOR]

Optimized water resource management depends on reliable and detailed information which can be described in virtual waterscape simulation. Addressing virtual lake-waterscape reality is important for a water resource management system. Many researchers use the same methodology as being used in ocean simulation for lake simulation. However, there is a big difference between the real lake and the effect of lack simulation. This paper is aimed at using random noise to improve large-scale lake simulation. The procedures are going to be taken as follows: first, using Perlin noise to model lake waves. Second, in order to create appropriate dense mesh, mesh points generated in screen space are going to be projected into world space. Third, using efficient parallel computing power of the CUDA to calculate height field generation, vertex transformation and rendering in graphics processing unit. The rendering result shows that the CUDA method can reduce the computational complexity, meeting the requirements of real-time simulation. [ABSTRACT FROM AUTHOR]

Aiming at reproducing plasma detachment states with a three‐dimensional fluid code, we are developing the Lagrange–Monte Carlo (LG‐MC) scheme. It integrates two schemes, namely a Lagrange scheme for the convective part and a Monte Carlo scheme for the diffusive part. One advantage of the scheme is the semi‐implicit treatment of the pressure gradient term in the convective part, which is essential to solve pure convective problems. As a first step, several one‐dimensional (1D) test calculations have been carried out so far. In this paper, results of the two preliminary tests are presented: (a) a test for the Lagrange scheme solving convective equations, and (b) a test for the integrated LG‐MC scheme solving a convection–conduction equation. These tests confirm the conservative property of the Lagrange scheme and the reliability of the integrated LG‐MC scheme. [ABSTRACT FROM AUTHOR]

Traditional Eulerian-based fluid simulations require much time and computational resources to solve the projection step, especially the large linear system produced by the Poisson equation. In this paper, we propose an adaptive machine-learning-based projection method combining deep neural network and incremental learning technique. We provide two modes: Fast Mode and Normal Mode to solve the most time-consuming projection step and deal with various simulation scenes largely different from the training data set. We introduce patch-based feature vectors to represent the whole velocity field and a loss function to keep the divergence-free constraint. We have demonstrated the acceleration and extrapolation ability of our method by testing various smoke scenes far different from our training data set. [ABSTRACT FROM AUTHOR]

Hybrid approaches such as combining video data with pure physics-based simulation have been popular in the recent decade for computer graphics. The key motivation is to clearly retain salient advantages from both data-driven method and model-centric numerical simulation, while overcoming certain difficulties of both. The Eulerian method, which has been widely employed in flow simulation, stores variables such as velocity and density on regular Cartesian grids, thereby it could be associated with (volumetric) video data on the same domain. This paper proposes a novel method for flow simulation, which is tightly coupling video-based reconstruction with physically-based simulation and making use of meaningful physical attributes during re-simulation. First, we reconstruct the density field from a single-view video. Second, we estimate the velocity field using the reconstructed density field as prior. In the iterative process, the pressure projection can be treated as a physical constraint and the results of each step are corrected by obtained velocity field in the Eulerian framework. Third, we use the reconstructed density field and velocity field to guide the Eulerian simulation with anticipated new results. Through the guidance of video data, we can produce new flows that closely match with the real scene exhibited in data acquisition. Moreover, in the multigrid Eulerian simulation, we can generate new visual effects which cannot be created from raw video acquisition, with a goal of easily producing many more visually interesting results and respecting true physical attributes at the same time. We demonstrate salient advantages of our hybrid method with a variety of animation examples. [ABSTRACT FROM AUTHOR]

This paper presents a method for nested fluid simulation based on smoothed particle hydrodynamics. Given suitable background flow information of an “external flow” as it evolves in time, our method simulates the motion of particles only within a local material region. In order to perform the simulation, the background physical quantities need to be transferred to the local fluid particles. We employ ghost particles to carry the given physical quantities to the nested fluid. We also solve the problem of density computation appropriately for the ghost particles. Our numerical tests show that accurate local fluid motion can be obtained in such a nested volume of fluid particles. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abstract: We studied the role of electron physics in 3‐D two‐fluid 10‐moment simulation of Ganymede's magnetosphere. The model captures nonideal physics like the Hall effect, electron inertia, and anisotropic, nongyrotropic pressure effects. A series of analyses were carried out: (1) The resulting magnetic field topology and electron and ion convection patterns were investigated. The magnetic fields were shown to agree reasonably well with in situ measurements by the Galileo satellite. (2) The physics of collisionless magnetic reconnection were carefully examined in terms of the current sheet formation and decomposition of generalized Ohm's law. The importance of pressure anisotropy and nongyrotropy in supporting the reconnection electric field is confirmed. (3) We compared surface “brightness” morphology, represented by surface electron and ion pressure contours, with oxygen emission observed by the Hubble Space Telescope. The correlation between the observed emission morphology and spatial variability in electron/ion pressure was demonstrated. Potential extension to multi‐ion species in the context of Ganymede and other magnetospheric systems is also discussed. [ABSTRACT FROM AUTHOR]

Abstract: A novel unified particle‐based method is proposed for real‐time dissolution simulation that is fast, predictable, independent of sampling resolution, and visually plausible. The dissolution model is derived from collision theory and integrated into a smoothed particle hydrodynamics fluid solver. Dissolution occurs when a solute is submerged in solvent. Physical laws govern the local excitation of solute particles based on kinetic energy: when the local excitation energy exceeds a user‐specified threshold (activation energy), the particle will be dislodged from the solid. Solute separation during dissolution is handled using a new Graphics Processing Unit (GPU)‐based region growing method. The use of smoothed particle hydrodynamics sampling for both solute and solvent guarantees a predictable and smooth dissolution process and provides user control of the volume change during the phase transition. A mathematical relationship between the activation energy and dissolution time allows for intuitive artistic control over the global dissolution rate. We demonstrate this method using a number of practical examples, including antacid pills dissolving in water, hydraulic erosion of nonhomogeneous terrains, and melting. [ABSTRACT FROM AUTHOR]

A packed bed dielectric barrier discharge (DBD) is widely used for plasma catalysis applications, but the exact plasma characteristics in between the packing beads are far from understood. Therefore, we study here these plasma characteristics by means of fluid modelling and experimental observations using ICCD imaging, for packing materials with different dielectric constants. Our study reveals that a packed bed DBD reactor in dry air at atmospheric pressure may show three types of discharges, i.e. positive restrikes, filamentary microdischarges, which can also be localized between two packing beads, and surface discharges (so-called surface ionization waves). Restrikes between the dielectric surfaces result in the formation of filamentary microdischarges, while surface charging creates electric field components parallel to the dielectric surfaces, leading to the formation of surface discharges. A transition in discharge mode occurs from surface discharges to local filamentary discharges between the packing beads when the dielectric constant of the packing rises from 5 to 1000. This may have implications for the efficiency of plasma catalytic gas treatment, because the catalyst activation may be limited by constraining the discharge to the contact points of the beads. The production of reactive species occurs most in the positive restrikes, the surface discharges and the local microdischarges in between the beads, and is less significant in the longer filamentary microdischarges. The faster streamer propagation and discharge development with higher dielectric constant of the packing beads leads to a faster production of reactive species. This study is of great interest for plasma catalysis, where packing beads with different dielectric constants are often used as supports for the catalytic materials. It allows us to better understand how different packing materials can influence the performance of packed bed plasma reactors for environmental applications. [ABSTRACT FROM AUTHOR]

We present a novel adaptive stepping scheme for SPH fluids, in which particles have their own time steps determined from local conditions, e.g. courant condition. These individual time steps are constrained for global convergence and stability. Fluid particles are then updated asynchronously. The approach naturally allocates computing resources to visually complex regions, e.g. regions with intense collisions, thereby reducing the overall computational time. The experiments show that our approach is more efficient than the standard method and the method with globally adaptive time steps, especially in highly dynamic scenes. [ABSTRACT FROM AUTHOR]

Computing the forces acting from a surrounding air phase onto a particle-based fluid or rigid object is challenging. Simulating the air phase and modeling the interactions using a multiphase approach is computationally expensive. Furthermore, stability issues may arise in such multiphase simulations. In contrast, the effects from the air can be approximated efficiently by employing a drag equation. Here, for plausible effects, the parameterization is important but challenging. We present a drag force discretization based on the drag equation that acts on each particle separately. It is used to compute the effects of air onto particle-based fluids and rigid objects. Our presented approach calculates the exposed surface area and drag coefficient of each particle. For fluid particles, we approximate their deformation to improve the drag coefficient estimation. The resulting effects are validated by comparing them to the results of multiphase SPH simulations. We further show the practicality of our approach by combining it with different types of SPH fluid solvers and by simulating multiple, complex scenes. [ABSTRACT FROM AUTHOR]

We apply a novel optimization scheme from the image processing and machine learning areas, a fast Primal-Dual method, to achieve controllable and realistic fluid simulations. While our method is generally applicable to many problems in fluid simulations, we focus on the two topics of fluid guiding and separating solid-wall boundary conditions. Each problem is posed as an optimization problem and solved using our method, which contains acceleration schemes tailored to each problem. In fluid guiding, we are interested in partially guiding fluid motion to exert control while preserving fluid characteristics. With our method, we achieve explicit control over both large-scale motions and small-scale details which is valuable for many applications, such as level-of-detail adjustment (after running the coarse simulation), spatially varying guiding strength, domain modification, and resimulation with different fluid parameters. For the separating solid-wall boundary conditions problem, our method effectively eliminates unrealistic artefacts of fluid crawling up solid walls and sticking to ceilings, requiring few changes to existing implementations. We demonstrate the fast convergence of our Primal-Dual method with a variety of test cases for both model problems. [ABSTRACT FROM AUTHOR]

Fast and vivid fluid simulation and visualization is a challenge topic of study in recent years. Particle-based simulation method has been widely used in the art animation modeling and multimedia field. However, the requirements of huge numerical calculation and high quality of visualization usually result in a poor computing efficiency. In this work, in order to improve those issues, we present a fast framework for 3D fluid fast constructing and visualization which parallelizes the fluid algorithm based on the GPU computing framework and designs a direct surface visualization method for particle-based fluid data such as WCSPH, IISPH, and PCISPH. Considering on conventional polygonization or adaptive mesh methods may incur high computing costs and detail losses, an improved particle-based method is provided for real-time fluid surface rendering with the screen-space technology and the utilities of the modern graphics hardware to achieve the high performance rendering; meanwhile, it effectively protects fluid details. Furthermore, to realize the fast construction of scenes, an optimized design of parallel framework and interface is also discussed in our paper. Our method is convenient to enforce, and the results demonstrate a significant improvement in the performance and efficiency by being compared with several examples. [ABSTRACT FROM AUTHOR]

The multigrid method has been widely used in computational fluid dynamics (CFD) numerical calculations because of its strong convergence. To achieve real-time simulation of a fluid in computer graphics (CG), the operation efficiency is also a significant factor to consider except for operational accuracy. For this problem, we introduced two multigrid cycling schemes, V-Cycle and full multigrid (FMG). Moreover, we have proposed a simple geometric multigrid method (GMG), and compared with the existing wide application of algebraic multigrid (AMG). All the calculations are the solution of parallel computing of GPU in this paper. The results showed that our approaches have improved the algorithm's computational speed and convergence time, which prominently enhanced the efficiency of the fluid simulation. [ABSTRACT FROM AUTHOR]

A continuous-flow output mode of a rotary blood pump reduces the fluctuation range of arterial blood pressure and easily causes complications. For a centrifugal rotary blood pump, sinusoidal and pulsatile speed patterns are designed using the impeller speed modulation. This study aimed to analyze the hemodynamic characteristics and hemolysis of different speed patterns of a blood pump in patients with heart failure using computational fluid dynamics (CFD) and the lumped parameter model (LPM). The results showed that the impeller with three speed patterns (including the constant speed pattern) met the normal blood demand of the human body. The pulsating flow generated by the impeller speed modulation effectively increased the maximum pulse pressure (PP) to 12.7 mm Hg, but the hemolysis index (HI) in the sinusoidal and pulsatile speed patterns was higher than that in the constant speed pattern, which was about 2.1 × 10−5. The flow path of the pulsating flow field in the spiral groove of the hydrodynamic suspension bearing was uniform, but the alternating high shear stress (0~157 Pa) was caused by the impeller speed modulation, causing blood damage. Therefore, the rational modulation of the impeller speed and the structural optimization of a blood pump are important for improving hydrodynamic characteristics and hemolysis.

Multiple-phase fluids’ simulation and 3D visualization comprise an important cooperative visualization subject between fluid dynamics and computer animation. Interactions between different fluids have been widely studied in both physics and computer graphics. To further the study in both areas, cooperative research has been carried out; hence, a more authentic fluid simulation method is required. The key to a better multiphase fluid simulation result is surface extraction. Previous works usually have problems in extracting surfaces with unnatural fluctuations or detail missing. Gaps between different phases also hinder the reality of simulation. In this paper, we propose a unified surface extraction approach integrated with a modified density model for the particle-based multiphase fluid simulation. We refine the original asymmetric smoothing kernel used in the color field and address a binary tree scheme for surface extraction. Besides, we employ a multiphase fluid framework with modified density to eliminate density deviation between different fluids. With the methods mentioned above, our approach can effectively reconstruct the fluid surface for particle-based multiphase fluid simulation. It can also resolve the issue of overlaps and gaps between different fluids, which has widely existed in former methods for a long time. The experiments carried out in this paper show that our approach is able to have an ideal fluid surface condition and have good interaction effects.

In order to capture stable and realistic microscopic features of fluid surface, a surface tension and adhesion method based on implicit incompressible SPH (smoothed particle hydrodynamics) is presented in this paper. It gives a steady and fast tension model and can solve the problem of not considering adhesion. Molecular cohesion and surface minimization are considered for surface tension, and adhesion is added to show the microscopic characteristics of the surface. To simulate surface tension and adhesion stably and efficiently, the surface tension and adhesion model is integrated to an implicit incompressible SPH method. The experimental results show that the method can better simulate surface features in a variety of scenarios compared with previous methods and meanwhile ensure stability and efficiency. [ABSTRACT FROM AUTHOR]

High-performance and low-power computation is required for large-scale fluid dynamics simulation. Due to the inefficient architecture and structure of CPUs and GPUs, they now have a difficulty in improving power efficiency for the target application. Although FPGAs become promising alternatives for power-efficient and high-performance computation due to their new architecture having floating-point (FP) DSP blocks, their relatively narrow memory bandwidth requires an appropriate way to fully exploit the advantage. This paper presents an architecture and design for scalable fluid simulation based on data-flow computing with a state-of-the-art FPGA. To exploit available hardware resources including FP DSPs, we introduce spatial and temporal parallelism to further scale the performance by adding more stream processing elements (SPEs) in an array. Performance modeling and prototype implementation allow us to explore the design space for both the existing Altera Arria10 and the upcoming Intel Stratix10 FPGAs. We demonstrate that Arria10 10AX115 FPGA achieves 519 GFlops at 9.67 GFlops/W only with a stream bandwidth of 9.0 GB/s, which is 97.9 percent of the peak performance of 18 implemented SPEs. We also estimate that Stratix10 FPGA can scale up to 6844 GFlops by combining spatial and temporal parallelism adequately. [ABSTRACT FROM PUBLISHER]

In this paper, we present a novel pairwise-force smoothed particle hydrodynamics (PF-SPH) model to enable simulation of various interactions at interfaces in real time. Realistic capture of interactions at interfaces is a challenging problem for SPH-based simulations, especially for scenarios involving multiple interactions at different interfaces. Our PF-SPH model can readily handle multiple types of interactions simultaneously in a single simulation; its basis is to use a larger support radius than that used in standard SPH. We adopt a novel anisotropic filtering term to further improve the performance of interaction forces. The proposed model is stable; furthermore, it avoids the particle clustering problem which commonly occurs at the free surface. We show how our model can be used to capture various interactions. We also consider the close connection between droplets and bubbles, and show how to animate bubbles rising in liquid as well as bubbles in air. Our method is versatile, physically plausible and easy-to-implement. Examples are provided to demonstrate the capabilities and effectiveness of our approach. [ABSTRACT FROM AUTHOR]