Yoichiro Kawaguchi

A morphological study of the form of nature

A process of recreating some forms of nature, including shells, horns, tusks, claws, and spiral plants, is herein described. The forms of nature based on spirals and ramification are generated not through the use of object data calculated by measurement, but through the use of an algorithmic structure based on the laws of nature. Although there are a myriad of forms to the shapes of nature, they are represented on the basis of one common principle, which can be expressed by means of the same mathematical expressions. The graphic software which is called “GROWTH” (Growth Rationale Object Work THeorem) has now been designed to create these forms automatically. GROWTH incorporates the rational, common principle of geometrical series which are found in the structute of biological objects.

Sliced data structure for particle-based simulations on GPUs

We present a sliced data structure that is effective for use in neighboring particle search for particle-based simulations. In this method, a grid is dynamically constructed to fit to a particle distribution. Rather than computing the grid to fit perfectly to the particle distribution, it compute a grid with some margin to the distribution. This lowers the computation cost of constructing the data structure. Before storing particle indices on a grid, key values which are used to compute the index of a voxel are calculated. The proposed data structure can be introduced into particle-based simulations that run entirely on the Graphics Processing Unit (GPU) because the construction of this data structure and access to storing values can also be also performed entirely on the GPU. The proposed data structure removes the restriction of a computation region with a fixed grid and makes it possible to simulate particle motions over a larger area. Moreover, the cost of the proposed method is low enough for use in real-time applications. In this paper, we first introduce the sliced data structure and then describe its implementation on the GPU. Finally, we apply the propsed method to particle-based simulations and present its quantitative evaluations.

Smoothed particle hydrodynamics in complex shapes

In this paper, we propose an improved computation model of wall boundary in Smoothed Particle Hydrodynamics, a particle method for fluid simulation. Generally, particle methods calculate a wall boundary by converting it to wall particles. The proposed method uses a distance function calculated from a polygon model as a wall boundary. As a result, fluid motion in complex shapes can be simulated easily. Since the method does not use wall particles, it is able to represent a wall boundary without increasing the particle resolution. When a boundary is represented by wall particles, we have to generate a large number of wall particles. The proportion of the number of wall particles in total number of particles is high. However the proposed method does not need wall particles, it can reduce the total number of particles. After the simulation, surface mesh is usually constructed to visualize a simulation result from particles. However, it is difficult to generate smooth surface from them. We also propose a visualization method which can construct smooth fluid surfaces contacting with a wall boundary.

MimicTile: a variable stiffness deformable user interface for mobile devices

MimicTile is a novel variable stiffness deformable user interface for mobile devices that implements two key features. The first feature is an input interface that accepts a variety of deformation-based gestures, providing a user with several ways of interacting with a small mobile device. The other feature is the ability to provide information to the user through haptic feedback by varying the stiffness of the interface. The features are suitable for enhancing mobile applications. They were implemented using only shape memory alloy (SMA) wires as the actuator. SMA wire is extremely flexible, making it ideal for deformable user interfaces. In MimicTile, SMA wires act as both actuators and external input sensors. The actuator function works by altering stiffness based on user input. This study also discusses ideas for further development of deformable user interfaces.

Real-time Fluid Simulation Coupled with Cloth

This paper presents a real-time simulation method for coupling of cloth and fluids computed by using Smoothed Particle Hydrodynamics (SPH). To compute interaction between cloth consisting of several polygons and fluid particles, the distance between cloth to the particle have to be calculated. It is computationally expensive because we have to compute the distance to the faces, edges and vertices of polygons. Instead of calculating the exact distance to a cloth, we calculate an approximate distance by using the distance to the faces and the gravitational centers of the polygons. This paper also presents techniques to perform the coupled simulation entirely on Graphics Processing Units (GPUs). The computation of interaction forces is divided into fluid-cloth and cloth-fluid forces to implement entire simulation on GPUs. By exploiting the parallelizm of GPUs, we could couple simulations of several tens of thousands of fluid particles and cloth which consists of several thousands of polygons in real-time.

Real-Time Simulation of Granular Materials Using Graphics Hardware

We present a method to compute friction in a particle-based simulation of granular materials on GPUs and its data structure. We use Distinct Element Method to compute the force between particles. There has been a method to accelerate Distinct Element Method using GPUs, but the method does not compute friction. We implemented friction into the DEM simulation on GPUs and this leads to the real-time simulation of granular materials.

Real-time particle-based simulation on GPUs

As physical laws govern the motion of objects around us, a physically-based simulation plays an important role in computer graphics. For instance, the motion of a fluid, which is difficult to generate by hand, can be produced by solving the governing equations. Acceleration of a simulation is one of the most important research themes because the speed and stability of a simulation are essential for real-time applications.

BRDF estimation system for structural colors

In this paper, we provide a shading algorithm for Structural Colors which can appear on micro surfaces. To approach a common algorithm for as many micro surfaces as possible, we modeled them out of polygons which have relative index of refraction. The algorithm calculates a surfaces BRDF for each wevelength by ray tracing considering interference. Interference yield different BRDF between each wavelength, and we perceive it as structural colors. We simulated not only single thin film but also multilayered thin films as typical micro surfaces causing structural colors. We illustrated calculated BRDF in 3D computer graphics using environment mapping. Rendering results in our method indicate that it represent structural colors qualitatively.

Simulating the Coalescence and Separation of Bubble and Foam by Particle Level Set Method

In this paper, we present a physics-based computer graphics technique for simulating and rendering foams and bubbles floating on the calm surface of fluid. We integrate rendering of bubble and foam, fluid simulation and the interactions between them to create the appearance of realistic liquids. As a whole, the animation of bubble that floats on the surface of fluid becomes possible by the technique of this research.

Massive particles: particle-based simulations on multiple GPUs

There is no study using multiple GPUs for particle-based simulation to the best of our knowledge although several researchers have been using a GPU. In this study, a particle-based simulation is parallelized on multiple GPUs. There are several challenges to accomplish it. For example, the simulation should not have serial computations that can be a bottleneck of the simulation. Particle methods cannot assign a fixed computation data to each GPU but the data has to be reassigned each iteration because particles not having any fixed connectivity can move freely. It is difficult for a particle-based simulation to scale the performance to the number of GPUs because the overhead of the parallelization can be high. We overcame these hurdles by employing not a server-client computation model but a peer-to-peer model among GPUs. Each GPU dynamically manages their own computation data without a server. A sliced-grid was used to lower the traffic among GPUs. As a result, the simulation speed scales well to the number of GPUs and the method brings it possible to simulate millions of particles in real-time. Of course, the proposed method is effective not only for a simulation on GPUs but also one on CPUs. The contribution of this study also includes a sorting technique utilizing the coherency between the time steps which was also introduced to increase the performance on a GPU.