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We introduce Dynamic Constrained Grid (DCGrid), a hierarchical and adaptive grid structure for fluid simulation combined with a scheme for effectively managing the grid adaptations. DCGrid is designed to be implemented on the GPU and used in high-performance simulations. Specifically, it allows us to efficiently vary and adjust the grid resolution across the spatial domain and to rapidly evaluate local stencils and individual cells in a GPU implementation. A special feature of DCGrid is that the control of the grid adaption is modeled as an optimization under a constraint on the maximum available memory, which addresses the memory limitations in GPU-based simulation. To further advance the use of DCGrid in high-performance simulations, we complement DCGrid with an efficient scheme for approximating collisions between fluids and static solids on cells with different resolutions. We demonstrate the effectiveness of DCGrid for smoke flows and complex cloud simulations in which terrain-atmosphere interaction requires working with cells of varying resolution and rapidly changing conditions. Finally, we compare the performance of DCGrid to that of alternative adaptive grid structures.

A magnetic actuated capsule microrobotic system (MACMS) is proposed to control the microrobot to complete specific medical tasks, such as medical diagnosis or drug delivery. The structure design and control of the microrobot are optimized. By establishing the dynamic model of the microrobot with spiral structure, the optimal structure parameters are analyzed, and the fluid simulation of the propulsive force and the resistance of the microrobot are carried out by the finite element analysis software to obtain the optimal performance. During the experiment, the peristaltic pump was used for imitating the environment of the gastrointestinal tract, because the human intestinal tract is constantly peristaltic at random speeds. The experimental results indicated that by adjusting the rotational velocity and frequency of the rotating magnetic field, the magnetic actuated spiral jet microrobot could move flexibly in the pipeline where the fluid’s peristaltic velocity is constantly changing medical functions at the desired area for diagnosis. The proposed microrobot and its optimization method make it possible for microrobot to be applied in medical practice.

International audience; Predicting the fine and intricate details of a turbulent flow field in both space and time from a coarse input remains a major challenge despite the availability of modern machine learning tools. In this paper, we present a simple and effective dictionary-based approach to spatio-temporal upsampling of fluid simulation. We demonstrate that our neural network approach can reproduce the visual complexity of turbulent flows from spatially and temporally coarse velocity fields even when using a generic training set. Moreover, since our method generates finer spatial and/or temporal details through embarrassingly-parallel upsampling of small local patches, it can efficiently predict high-resolution turbulence details across a variety of grid resolutions. As a consequence, our method offers a whole range of applications varying from fluid flow upsampling to fluid data compression. We demonstrate the efficiency and generalizability of our method for synthesizing turbulent flows on a series of complex examples, highlighting dramatically better results in spatio-temporal upsampling and flow data compression than existing methods as assessed by both qualitative and quantitative comparisons.

The detection of methane has always been an important part of coal mine safety. In order to improve the methane measurement accuracy in coal mines and to determine the influence of environmental interference factors on the measurement results, we designed a spherical, experimental chamber simulating the on-site environment of an underground coal mine containing methane, in which various environmental interference factors can be superimposed. The simulation chamber can generate a uniform and controllable dust environment, a controllable methane environment with concentrations below that which would trigger an alarm, controllable humidity, and environments characterized by other interference factors. Based on computational simulations of the experimental chamber with varying dust-particle-concentration distributions using a single particle size, an optimal design for the chamber has been realized in terms of the rapid mixing of dust and the flow field. Finally, we constructed an underground methane concentration measurement system for coal mines and assessed the influences of different dust concentrations and relative humidity values on the performance of methane measurements, providing a means for improving the measurement accuracy of underground coal mine, spectral, absorption-type methane sensors.

The field of fluid simulation is developing rapidly, and data-driven methods provide many frameworks and techniques for fluid simulation. This paper presents a survey of data-driven methods used in fluid simulation in computer graphics in recent years. First, we provide a brief introduction of physicalbased fluid simulation methods based on their spatial discretization, including Lagrangian, Eulerian, and hybrid methods. The characteristics of these underlying structures and their inherent connection with datadriven methodologies are then analyzed. Subsequently, we review studies pertaining to a wide range of applications, including data-driven solvers, detail enhancement, animation synthesis, fluid control, and differentiable simulation. Finally, we discuss some related issues and potential directions in data-driven fluid simulation. We conclude that the fluid simulation combined with data-driven methods has some advantages, such as higher simulation efficiency, rich details and different pattern styles, compared with traditional methods under the same parameters. It can be seen that the data-driven fluid simulation is feasible and has broad prospects.

Background In the smoothed particle hydrodynamics (SPH) fluid simulation method, thesmoothing length affects not only the process of neighbor search but also the calculation accuracy of the pressure solver. Therefore, it plays a crucial role in ensuring the accuracy and stability of SPH. Methods In this study, an adaptive SPH fluid simulation method with a variable smoothing length is designed. In this method, the smoothing length is adaptively adjusted according to the ratio of the particle density to the weighted average of the density of the neighboring particles. Additionally, a neighbor search scheme and kernel function scheme are designed to solve the asymmetry problems caused by the variable smoothing length. Results The simulation efficiency of the proposed algorithm is comparable to that of some classical methods, and the variance of the number of neighboring particles is reduced. Thus, the visual effect is more similar to the corresponding physical reality. Conclusions The precision of the interpolation calculation performed in the SPH algorithm is improved using the adaptive-smoothing length scheme; thus, the stability of the algorithm is enhanced, and a larger timestep is possible.

Background The interaction of gas and liquid can produce many interesting phenomena, such as bubbles rising from the bottom of the liquid. The simulation of two-phase fluids is a challenging topic in computer graphics. To animate the interaction of a gas and liquid, MultiFLIP samples the two types of particles, and a Euler grid is used to track the interface of the liquid and gas. However, MultiFLIP uses the fluid implicit particle (FLIP) method to interpolate the velocities of particles into the Euler grid, which suffer from additional noise and instability. Methods To solve the problem caused by fluid implicit particles (FLIP), we present a novel velocity transport technique for two individual particles based on the affine particle-in-cell (APIC) method. First, we design a weighed coupling method for interpolating the velocities of liquid and gas particles to the Euler grid such that we can apply the APIC method to the simulation of a two-phase fluid. Second, we introduce a narrowband method to our system because MultiFLIP is a time-consuming approach owing to the large number of particles. Results Experiments show that our method is well integrated with the APIC method and provides a visually credible two-phase fluid animation. Conclusions The proposed method can successfully handle the simulation of a twophase fluid.

The many-body dissipative particle dynamics (mDPD) is a prominent mesoscopic multiphase model for fluid transport in mesoconfinement. However, it has been a long-standing challenge for mDPD (and ot...

The technical project details the creation of a graphical hair simulation through an exploration of existing fluid and hair simulations. The science, technology, and society (STS) research section seeks to provide insight into the racial biases built into animation and graphics technology, the historical context that these biases are rooted in, and their future implications. Closer inspection of current graphics literature reveals that patterns of racial bias are found embedded in the discipline, from sample images presented in publications to the technical language itself. These biases are especially visible in research surrounding the animation, simulation, and rendering of humans and human features that can be characteristic of certain races, such as hair, which is the focus of the technical portion of this thesis. As such, it is crucial to approach even seemingly purely technical problems with an awareness of the implicit biases that are endemic to the field. The complexity of simulating human hair movement can be attributed to its structural complexity, which involves the interactions between hundreds of thousands of thin strands. One of the many issues that needs to be resolved in order to simulate hair is how to efficiently handle collisions between strands, as naïve approaches such as checking each segment of each strand for collisions with other strands at every time step are often highly impractical. A fluid-based method for simulating hair, comprising the embedding of strands into a particle-based fluid simulation in order to implicitly resolve internal collisions, was explored. Several different fluid simulation approaches and collision resolution strategies were also investigated. Technology carries with it the values and biases of the society it was created in. In this paper, we discuss this phenomenon in the context of computer graphics technology and racial diversity to answer the following research questions: What racial biases are present in computer graphics and animation technology and the media created with this technology, and how have these biases been sustained and molded by technology? What are their implications on the stories told through computer generated media? This paper expands on previous studies addressing the lack of representation of racially diverse features in computer graphics research and the implications of this lack by means of documentary research and discourse analysis. This paper employs the STS framework of co-production in the analysis of the relationship between graphics technology and historical and social values, with a focus on how this relationship forms and upholds identities, institutions, discourse, and representation. Evidence concerning the presence of the issue is found through surveying prominent research papers in the graphics field, existing documentation and software add-ons for popular animation tools, and open-source software packages meant for hobbyist creators. By tracking the development of broader media technology, as well as analyzing the quantity and quality of diversity in film over time both in front and behind the camera, a narrative of the historical context of these biases is built. Finally, we discuss the social implications of our findings in terms of what stories are ultimately told through the animated medium and who is given the ability to tell those stories. Working on both of these projects in tandem has revealed how racial biases have been perpetuated in graphics and animation media and technology. The research performed to complete the technical project provided critical background knowledge for an informed survey of graphics literature in the STS research project. Additionally, the technical challenges unearthed while implementing a hair simulation for a relatively non-complex hair type (straight strands) highlighted the necessity for focused research for other hair types, as the long-held assumption that simulations that work for one type will deliver similar quality results for other types can easily be incorrect. Such faulty assumptions lead to the simulation of some elements being given greater priority while others are pushed to the sidelines. When these elements are human features characteristic to different races, the result is research that contains certain biases which then causes these biases to be further disseminated into technological tools that reach the broader public through popular media. In order for inclusive technology and storytelling, it is essential for researchers, developers, and users alike to become better informed of the biases present in their tools and work, and to include members of diverse social groups when creating narratives of those social groups.

Being aware of global pandemics, this research focused on the potential infection routes in building drainage systems. Case studies have found that dysfunctional building drainage systems not only failed to block contaminants but also potentially became a route for the spreading of viruses. Several fluid simulations in pipelines were conducted in this research using COMSOL Multiphysics. In particular, virus transmission from one patient’s room to other uninfected residential units through pipelines was visualized. A 12-story building, which is commonly seen in the local area, was designed as a simulation model to visualize the transmission and analyze its hazards. Furthermore, five environmental factors were filtered out for discussion: distance, time span, pressure, initial concentration, and environment temperature. By manipulating these factors, the relationship between the factors and the behavior of the contaminant could be explored. In addition, a simulation with a different pipeline arrangement was included to observe the virus diffusion behavior under different scenarios. The visualized simulation concluded that the contaminant would spread through the drainage system and arrive at the neighboring four floors within an hour under the circumstances of a 12-story building with broken seals and constant pressure and contaminant supply on the seventh floor. Meanwhile, the whole building would be exposed to infection risks by the continuous virus spreading through a drainage system. Distance, time span, and pressure were considered critical factors that affected indoor contamination in the system. On the other hand, initial concentration and environmental temperature did not have significant roles. Visualizing the behavior of viruses provides a glimpse of what happens behind walls, paving the way for recognizing the importance of maintaining functional drainage systems for individuals’ health.

International audience; It is notoriously difficult for artists to control liquids while generating plausible animations. We introduce a new liquid control tool that allows users to load, transform, and apply precomputed liquid simulation templates in a scene in order to control a particle-based simulation. Each template instance generates control forces that drive the global simulated liquid to locally reproduce the templated liquid behavior. Our system is augmented with a variable proportion of temporary particles to help efficiently reproduce the templated liquid density, with fewer requirements on the surrounding environment. The resulting control strategy adds only a small computational overhead, leading to quick visual feedback for resolutions allowing interactive simulation. We demonstrate the robustness and ease of use of our method on various examples in 2D and 3D.

Particle techniques mainly deal with physically-based particle variations for phenomena and shapes in computer animation and geometric modeling. Typical particle techniques include smoothed particle hydrodynamics (SPH) simulation for animation and particle systems for shape modeling. SPH simulation and particle systems are meshfree methods and have been widely applied in engineering and applied sciences. Here, we provide a comprehensive survey on the recent developments, achievements, and future expectations of SPH and particle systems, with a detailed description of the classification and methods used in the field. Particularly, it has not only summarized the cutting-edge research of SPH methods and the particle systems, with a description of basic theories behind the particle system and method of the structuring mode for stimulating the irregular mode, but also proposed measures to improve the particle system. These applied methods mainly include the Lagrangian method, for simulating fluid phenomena, such as smoke, fire, explosion, wave, bubble, and free surface, which have been the focus of little attention in the past. Finally, future research directions and expectations are thoroughly discussed with the detail, acceleration, and control techniques used to meet the pressing real demand for real-time performance and flexibility.

We present sharpness-aware minimization (SAM) for fluid dynamics which can efficiently learn the plausible dynamics of liquid splashes. Due to its ability to achieve robust and generalizing solutions, SAM efficiently converges to a parameter set that predicts plausible dynamics of elusive liquid splashes. Our training scheme requires 6 times smaller number of epochs to converge and, 4 times shorter wall-clock time. Our result shows that sharpness of loss function has a close connection to the plausibility of fluid dynamics and suggests further applicability of SAM to machine learning based fluid simulation., Posters, Vishrut Jetly, Hikaru Ibayashi, and Aiichiro Nakano

The highly automated world of manufacturing industry offers new possibilities for the application of adhesives which are not fully utilized yet. In addition to the classical static stress and strength related topics, a more global view on adhesive bonding is needed. This includes the consideration of adhesive flow during application and joining of the substrates with all the information about initial application pattern and the resulting adhesive distribution contained after joining, and thus benefit from the modern manufacturing possibilities. To do so, research which addresses this issue is needed in the first place to elaborate innovative approaches on how to design and develop adhesive application pattern which minimize adhesive spillage and waste while achieving a bond without any air enclosures or other imperfections. This paper systematically investigates different phenomena which can occur during the joining process, such as the formation of air pockets and how they behave once formed. Furthermore, optimized application pattern and the merging behaviour of different flow fronts are considered. In total, four different adhesive application patterns were investigated experimentally and analysed using Particle Image Velocimetry. The investigations were complemented by a numerical simulation of the corresponding squeeze flow experiments - which achieved a high level of agreement. It was found that during the joining process, existing air pockets can reform due to the phenomenon of viscous fingering and subsequently cure into flat cavities, which are more critical in terms of bonding strength than spherical ones.

Micro-scale fluids are tiny droplets that adhere to the surface of an object as a result of rainfall, perspiration, etc. Micro-scale fluid simulation is widely used in fields such as film and games. The existing state-of-the-art simulation methods are not suitable for simulating water droplets moving on a surface due to the fact that the water droplets cannot leave the texture space and their movements always depend on the continuous UV region. In this study, a novel method for simulating water droplets moving on a surface is proposed. We divide the droplets into two types: (1) two-dimensional droplets and (2) three-dimensional droplets and we implement the transformation between two-dimensional droplets in the texture space and three-dimensional droplets in the physical space. In the preprocessing phase, jump textures, coordinate transform textures and force field textures are generated in the non-continuous UV regions on a 3D object’s surface. In the process of simulation, water droplets are treated as rigid particles. The Velocity-Verlet-based method is adopted to solve the motion trajectory equation, and the boundary droplet transport algorithm is implemented based on jump texture. In the process of rendering, the height map is generated according to the simulation in the texture space and then the liquid bridge phenomenon between the droplets is simulated based on the Gaussian blur and the color rank algorithm. Finally, they are converted into normal texture-rendering droplets. The experimental result shows that the proposed method works well when simulating the movements of water droplets on a surface in a real-time manner, and it makes the movement simulation of dimension-reducing water droplets no longer depend on the continuous surface and continuous UV region. Moreover, the simulation efficiency of the proposed method is two times higher than that of the Smoothed Particle Hydrodynamics (SPH) method.

Hadal seafloor organisms live under ultra-high pressure, in low temperatures, and other environments for a long time, which puts higher requirements on the structural design of deep-sea biological samplers. In this paper, we present a full-ocean-depth hydraulic suction macroorganism pressure-retaining sampling method, which actively samples seafloor macroorganisms by pumping and stabilizing the pressure inside the sampler using a pressure compensator. Firstly, the structure and working principle of the hydraulic suction macroorganism pressure-retaining sampler (HSMPS) were introduced. Then the flow field of the HSMPS sampling process was analyzed, and the velocity and pressure distribution of the flow field at different locations of the HSMPS were obtained. In response to the problem of the low viability of samples collected by deep-sea biological samplers, the changes in radial velocity and pressure at different positions of the sampler under different pumping flows were analyzed. Finally, the appropriate suction flow rate was selected based on the analysis results, and HSMPS suction tests and simulated sampling tests, under a 110 MPa high-pressure environment, were carried out using the developed HSMPS engineering prototype. The test results verify the feasibility of the HSMPS design, which will provide strong support for the deep abyssal seafloor sampling operation of the full-ocean-depth manned submersible.

Fractionating columns are used for most of all technical distillation processes. The fundamental understanding of the principles of these critical components is often only provided in theory or in small-scaled laboratory setups.

We present a fast and flexible technique for creating Pyro simulations directly from and coupled with FLIP simulations for fuel. A typical Pyro simulation involves numerous ways to generate fuel but mostly as an input exclusively into the Pyro simulation not as a coupled partner into the simulation. None of the characteristics of the fuel and specifically the reaction of the fuel consumption is considered in a traditional Pyro simulation. We strived to create this relationship in a coupled simulation. This introduced shared fuel, divergence, and velocity data. All this sharing creates a more realistic simulation with little artificial initial velocity.

We present a method for intelligently resizing fluid simulation data using seam carving methods. While advances in post-processing techniques have allowed artists greater control over content late in the production process, this technology has largely remained confined to image processing. Our fluid carving system allows fluid simulation post-processing by performing content-aware non-uniform scaling on baked-out fluid simulation data. Specifically, we extend video seam carving techniques to 4-dimensional animated fluid volume data with a graph cut energy function based on mean curvature and kinetic energy. To reduce the complexity of performing graph cuts on 4D data, we provide a new graph construction formulation that greatly reduces the run-time and memory consumption, which are otherwise prohibitively expensive. We demonstrate that our system is useful for post-production fluid simulation changes and editable fluid FX libraries.

In physically-based simulation, it is essential to choose appropriate material parameters to generate desirable simulation results. In many cases, however, choosing appropriate material parameters is very challenging, and often tedious trial-and-error parameter tuning steps are inevitable. In this paper, we propose a real-to-virtual parameter transfer framework that identifies material parameters of viscous fluids with example video data captured from real-world phenomena. Our method first extracts positional data of fluids and then uses the extracted data as a reference to identify the viscosity parameters, combining forward viscous fluid simulations and parameter optimization in an iterative process. We evaluate our method with a range of synthetic and real-world example data, and demonstrate that our method can identify the hidden physical variables and viscosity parameters. This set of recovered physical variables and parameters can then be effectively used in novel scenarios to generate viscous fluid behaviors visually consistent with the example videos.

Chemically driven colloidal motors capable of implementing different movements under a common environment are of great importance for various complex tasks. However, the key parameters underlying different motion behaviors are incompletely understood. Here, we demonstrate that carbonaceous nanoflask (CNF) motors move spontaneously in glucose powered by the cascade reaction of glucose oxidase and catalase, and their directional propulsion can be premeditated by controlling the surface wettability of nanomotors. The hydrophilic CNF motors move from the round-bottom to the opening neck (backward), whereas the hydrophobic CNF motors swim from the opening neck to the round-bottom (forward). We demonstrate that the backward motion of the hydrophilic CNF motors is driven by the local glucose gradient due to self-diffusiophoresis, and the forward movement of the hydrophobic CNF motors is caused by the locally produced glucose acid gradient. The fluid simulation reveals that the hydrophilic and hydrophobic CNF motors correspond to the puller and pusher models, respectively. Our study offers a minimal strategy to manipulate the direction of motion of motors for specific applications and to change the hydrodynamic behaviors of glucose-powered motors.

This paper instructs the working principle of the well washing device and its parameter optimization in practical applications. A fluent fluid engineering simulation software was used to establish the calculation model of the bottom flow field. The fluid area inside the well washing device with different orifice diameters at 30, 40, 50, and 60 degrees was simulated, and the gas‐solid two‐phase distribution cloud map and corresponding data were obtained. The results show that the cleaning effect is optimal and with no dead angle when θ = 30° and d = 4 mm. Moreover, the optimization design using simulation technology is reliable and simple. Based on this conclusion, a patent for a cyclone reverse circulation well washing device was invented. Under the same conditions, the above results were also verified by comparison with ordinary washing devices.

In this paper, lattice Boltzmann method is used for the simulation of two-dimensional flow over an immersed solid body using external boundary force. Fluid simulation is performed using the Euleria...

In swimming virtual creatures, there is often a disparity between the level of detail in simulating a swimmer’s body and that of the fluid it moves in. In order to address this disparity, we have developed a new approach to modelling swimming virtual creatures using pseudo-soft bodies and particle-based fluids, which has sufficient realism to investigate a larger range of body-environment interactions than are usually included. As this comes with increased computational costs, which may be severe, we have also developed a means of reducing the volume of fluid that must be simulated.

We present a strong fluid-rigid coupling for Smoothed Particle Hydrodynamics (SPH) fluids and rigid bodies with particle-sampled surfaces. The approach interlinks the iterative pressure update at fluid particles with a second SPH solver that computes artificial pressure at rigid-body particles. The introduced SPH rigid-body solver models rigid-rigid contacts as artificial density deviations at rigid-body particles. The corresponding pressure is iteratively computed by solving a global formulation that is particularly useful for large numbers of rigid-rigid contacts. Compared to previous SPH coupling methods, the proposed concept stabilizes the fluid-rigid interface handling. It significantly reduces the computation times of SPH fluid simulations by enabling larger time steps. Performance gain factors of up to 58 compared to previous methods are presented. We illustrate the flexibility of the presented fluid-rigid coupling by integrating it into DFSPH, IISPH, and a recent SPH solver for highly viscous fluids. We further show its applicability to a recent SPH solver for elastic objects. Large scenarios with up to 90 M particles of various interacting materials and complex contact geometries with up to 90 k rigid-rigid contacts are shown. We demonstrate the competitiveness of our proposed rigid-body solver by comparing it to Bullet.

Maxillomandibular advancement surgery is useful for treatment of sleep apnea. However, preoperative analysis and evaluation to facilitate decision-making regarding the direction and distance of maxillomandibular movement has primarily consisted of morphological analysis; physiological function is not evaluated. To improve preoperative prediction, this study used fluid simulation to investigate the characteristics and effects of airway changes associated with maxillomandibular movement. A one-dimensional model with general applicability was thus developed. Actual measurements of flow in patients were used in this fluid simulation, thus achieving an analysis closer to clinical conditions. The simulation results were qualitatively consistent with the actual measurements, which confirmed the usefulness of the simulation. In addition, the results of the one-dimensional model were within the error ranges of the actual measurements. The present results establish a foundation for using accumulating preoperative measurement data for more-precise prediction of postoperative outcomes.

Computational fluid dynamics (CFD) numerical simulations play an important role in many research fields, including hydrological basins, rivers, floods, and dam breaks. Currently, much research mainly pursues accuracy, efficiency, scale, dimensions, etc. In most models, the influencing parameters are adjusted manually, and only one constant is designed in a calculation area, resulting in a lack of heterogeneity in the variable space. In this article, using the idea of spatial interpolation by designing some control points along the river, a spatial design of the Manning coefficient is proposed in the CFD numerical simulation, and an adaptive correction model considering the different correction logic is researched to calibrate the model. Finally, the model is proven to be correct and effective, and it is converged with the Malpasset Dam-breaking case. It can help reduce the artificial calibration and improve simulation accuracy by designing the spatial adaptive correction parameter.

Fluid simulation using meshless methods has increasingly become a robust way to solve mechanics problems that require dealing with large deformations and has become very popular in many applications such as naval engineering, mechanical engineering, movies, and games. The current challenge is to simulate and render the fluid in real time. This works contributions are: a GPU implementation of the SPH method, which provided an average speedup of 11.55 in comparison to the reference multicore CPU implementation, being able to simulate 1M particles at, approximately, 3 fps; also, a Ray Tracing based rendering solution that can be used to render any particle based fluid simulation method is proposed, which is able to render a large number of particles in interactive rates, for instance, 2M particles at 2.7 fps for a resolution of 1920 x 1920 pixels.

Adaptive data structures have become of interest for processing large amounts of information, mainly due to their ability to automatically model the data format. We introduced a new approach in the liquid simulation that combines the pressure projection method with the Particle-In-Cell (PIC) method. The solver relies on a generalized version of the Finite Difference (FD) method to approximate the pressure field and its gradients in tree-based grid discretizations, possibly non-graded. In our approach, FD stencils are computed using mesh-free interpolations provided by a variant of Radial Basis Function (RBF), known as RBF-Finite-Difference (RBF-FD). This mesh-free version of the FD produces differentiation weights on scattered nodes with high-order accuracy. Our method adapts a quadtree/octree dynamically in a narrow-band around the liquid interface, providing an adaptive particle sampling for the PIC advection step. Furthermore, RBF affords an accurate scheme for velocity transfer between the grid and particles, keeping the systems stability and avoiding numerical dissipation. We also present a data structure that connects the spatial subdivision of a quadtree/octree with the topology of its corresponding dual-graph. Our data structure makes the setup of stencils straightforward, allowing its updating without the need to rebuild it from scratch at each time-step. We show our solvers effectiveness and accuracy by simulating incompressible inviscid fluids and comparing results with regular PIC-based solvers available in the literature. Estruturas de dados adaptativas têm se tornado de interesse para processamento de grandes quantidades de informações, principalmente pela sua capacidade de se modelar automaticamente ao formato dos dados. Em se tratando de simulação de líquidos, introduzimos uma nova abordagem que combina o método de projeção da pressão com o método Particle-In-Cell (PIC). O método se baseia em uma versão generalizada do método de diferenças finitas (FD) para aproximar o campo de pressão e seus gradientes em discretizações de malha baseadas em árvore, possivelmente não balanceada. Em nossa abordagem, os pontos de amostra para diferenças finitas são usados para calcular as interpolações sem malha, fornecidas por uma variante da técnica de Funções de Base Radial (RBF), conhecida como RBF-Finite-Difference (RBF-FD). Esta versão sem malha produz pesos de diferenciação em nós espalhados com alta precisão. Nosso método adapta um quadtree/octree dinamicamente em uma faixa estreita ao redor da superfície do líquido, fornecendo uma amostra adaptativa de partículas para a etapa de advecção. Além disso, o RBF fornece um esquema preciso para transferência de velocidade entre a grade e as partículas, mantendo a estabilidade do sistema e evitando dissipação numérica. Apresentamos também uma estrutura de dados que conecta a subdivisão espacial de uma quadtree/octree com a topologia de seu grafo dual correspondente. A estrutura de dados apresentada torna a configuração stencils simples, permitindo sua atualização sem a necessidade de reconstruí-los do zero a cada passo de tempo. Os resultados obtidos mostram a eficácia e a precisão de nosso solver ao simulat fluidos invíscidos incompressíveis e comparando os resultados com métodos que utilizam malha regular, também baseados em PIC, disponíveis na literatura.

This paper analyzes the correlation between the maximum safe driving speed of vehicles on the main body of the whole bridge and the typhoon series based on different wind directions. Firstly, the joint probability density model of typhoon wind level and wind direction is constructed. Secondly, the mathematical model for safe driving of vehicles is constructed based on the aerodynamic six component force. The circular curve, up and down ramp and combined alignment are selected as the representative road routes of bridge, tunnel and castle. The 1:1 light vehicle is set up with different wind speed levels for fluid simulation. Finally, it is concluded that there is a negative correlation between the maximum safe driving speed range of vehicles on the main body of the whole bridge and the typhoon series of 1-16.

Surface reconstruction for particle-based fluid simulation is a computational challenge on par with the simula- tion itself. In real-time applications, splatting-style rendering approaches based on forward rendering of particle impostors are prevalent, but they suffer from noticeable artifacts. In this paper, we present a technique that combines forward rendering simulated features with deep-learning image manipulation to improve the rendering quality of splatting-style approaches to be perceptually similar to ray tracing solutions, circumventing the cost, complexity, and limitations of exact fluid surface rendering by replacing it with the flat cost of a neural network pass. Our solution is based on the idea of training generative deep neural networks with image pairs consisting of cheap particle impostor renders and ground truth high quality ray-traced images.

We performed one-dimensional fluid simulation to study the evolution and characteristics of ion acoustic solitary waves (IASWs) in a plasma comprised of hot inertial ions, superthermal electrons and positrons. The initial density perturbations in the equilibrium ion density are used to excite the IASW pulses in e–p–i plasma. This simulation illustrates the evolution of IASWs in presence of superthermal electrons and positrons. The main focus of this paper is to understand the role of positrons in the nonlinear evolution of the IASWs under the influence of ion thermal pressure. We noticed that the positron density, ion thermal pressure, superthermal index of electrons and positrons play pivotal role in the formation of IASWs. These results will be helpful in understanding the characteristics of IASWs in space/astrophysical plasmas, especially in the active galactic nucleus regions and interstellar medium where superthermal electron–positron pairs are prevalent.

In this paper, a novel method is proposed for data-driven high frequency components generation of velocity fields in fluid simulation. It targets on fluid simulation based on N-S Equation which may suffer from details missing because of low simulation grid resolution and other reasons causing energy dissipation. A frequency transfer model structured with deep learning methods is designed to generate high frequency components with low frequency components as inputs. Considering that high frequency components cannot be inferred from lower ones exactly, our model provides another freedom to adjust the ratio of low frequency and high frequency components in velocity fields to obtain results with diversity and reality. A series of evaluations and results are presented to show our model’s effectiveness in generating high frequency components from low frequency components without improving grid simulation to alleviating energy and dissipation and reconstruct details in fluid simulation.