Physically based modeling and animation of tornado

Realistic modeling and rendering of dynamic tornado scene is recognized as a challenging task for researchers of computer graphics. In this paper a new physically based method for simulating and animating tornado scene is presented. We first propose a Two-Fluid model based on the physical theory of tornado, then we simulate the flow of tornado and its interaction with surrounding objects such as debris, etc. Taking the scattering and absorption of light by the participating media into account, the illumination effects of the tornado scene can be generated realistically. With the support of graphics hardware, various kinds of dynamic tornado scenes can be rendered at interactive rates.

A Closure for Isotropic Turbulence Based on Extended Scale Similarity Theory in Physical Space

The closure of a turbulence field is a longstanding fundamental problem, while most closure models are introduced in spectral space. Inspired by Chou＇s quasi-normal closure method in spectral space, we propose an analytical closure model for isotropic turbulence based on the extended scale similarity theory of the velocity structure function in physical space. The assumptions and certain approximations are justified with direct numerical simulation. The asymptotic scaling properties are reproduced by this new closure method, in comparison to the classical Batchelor model.

Physics-Based Active Learning for Design Space Exploration and Surrogate Construction for Multiparametric Optimization

The sampling of the training data is a bottleneck in the development of artificial intelligence(AI)models due to the processing of huge amounts of data or to the difficulty of access to the data in industrial practices.Active learning(AL)approaches are useful in such a context since they maximize the performance of the trained model while minimizing the number of training samples.Such smart sampling methodologies iteratively sample the points that should be labeled and added to the training set based on their informativeness and pertinence.To judge the relevance of a data instance,query rules are defined.In this paper,we propose an AL methodology based on a physics-based query rule.Given some industrial objectives from the physical process where the AI model is implied in,the physics-based AL approach iteratively converges to the data instances fulfilling those objectives while sampling training points.Therefore,the trained surrogate model is accurate where the potentially interesting data instances from the industrial point of view are,while coarse everywhere else where the data instances are of no interest in the industrial context studied.

Evaluation of an erosion-sediment transport model for a hillslope using laboratory flume data

Climate change can escalate rainfall intensity and cause further increase in sediment transport in arid lands which in turn can adversely affect water quality. Hence, there is a strong need to predict the fate of sediments in order to provide measures for sound erosion control and water quality management. The presence of micro- topography on hillslopes influences processes of runoff generation and erosion, which should be taken into account to achieve more accurate modelling results. This study presents a physically based mathematical model for erosion and sediment transport coupled to one-dimensional overland flow equations that simulate rainfall-runoff generation on the rill and interrill areas of a bare hillslope. Modelling effort at such a fine resolution considering the flow con- nection between Jnterrill areas and rills is rarely verified. The developed model was applied on a set of data gath- ered from an experimental setup where a 650 cm×136 cm erosion flume was pre-formed with a longitudinal rill and interrJll having a plane geometry and was equipped with a rainfall simulator that reproduces natural rainfall characteristics. The flume can be given both longitudinal and lateral slope directions. For calibration and validation, the model was applied on the experimental results obtained from the setup of the flume having 5% lateral and 10% longitudinal slope directions under rainfall intensities of 105 and 45 mm/h, respectively. Calibration showed that the model was able to produce good results based on the R2 （0.84） and NSE （0.80） values. The model performance was further tested through validation which also produced good statistics （R2=0.83, NSE=0.72）. Results in terms of the sedigraphs, cumulative mass curves and performance statistics suggest that the model can be a useful and an important step towards verifying and improving mathematical models of erosion and sediment transport.

Application of hydrometeorological coupled European flood forecasting operational real time system in Yellow River Basin

This study evaluated the application of the European flood forecasting operational real time system （EFFORTS） to the Yellow River. An automatic data pre-processing program was developed to provide real-time hydrometeorological data. Various GIS layers were collected and developed to meet the demands of the distributed hydrological model in the EFFORTS. The model parameters were calibrated and validated based on more than ten years of historical hydrometeorological data from the study area. The San-Hua Basin （from the Sanmenxia Reservoir to the Huayuankou Hydrological Station）, the most geographically important area of the Yellow River, was chosen as the study area. The analysis indicates that the EFFORTS enhances the work efficiency, extends the flood forecasting lead time, and attains an acceptable level of forecasting accuracy in the San-Hua Basin, with a mean deterministic coefficient at Huayuankou Station, the basin outlet, of 0.90 in calibration and 0.96 in validation. The analysis also shows that the ;simulation accuracy is better for the southern part than for the northern part of the San-Hua Basin. This implies that, along with the characteristics of the basin and the mechanisms of runoff generation of the hydrological model, the hydrometeorological data play an important role in simulation of hydrological behavior.

Real-Time Simulation of Aeolian Sand Movement and Sand Ripple Evolution: A Method Based on the Physics of Blown Sand

Simulation and visualization of aeolian sand movement and sand ripple evolution are a challenging subject. In this paper, we propose a physically based modeling and simulating method that can be used to synthesize sandy terrain in various patterns. Our method is based on the mechanical behavior of individual sand grains, which are widely studied in the physics of blown sand. We accounted significant mechanisms of sand transportation into the sand model, such as saltation, successive saltation and collapsing, while simplified the vegetation model and wind field model to make the simulation feasible and affordable. We implemented the proposed method on the programming graphics processing unit （GPU） to get real-time simulation and rendering. Finally, we proved that our method can reflect many characteristics of sand ripple evolution through several demonstrations. We also gave several synthesized desert scenes made from the simulated height field to display its significance on application.

Framework and development of data-driven physics based model with application in dimensional accuracy prediction in pocket milling

In the manufacturing of thin wall components for aerospace industry,apart from the side wall contour error,the Remaining Bottom Thickness Error(RBTE)for the thin-wall pocket component(e.g.rocket shell)is of the same importance but overlooked in current research.If the RBTE reduces by 30%,the weight reduction of the entire component will reach up to tens of kilograms while improving the dynamic balance performance of the large component.Current RBTE control requires the off-process measurement of limited discrete points on the component bottom to provide the reference value for compensation.This leads to incompleteness in the remaining bottom thickness control and redundant measurement in manufacturing.In this paper,the framework of data-driven physics based model is proposed and developed for the real-time prediction of critical quality for large components,which enables accurate prediction and compensation of RBTE value for the thin wall components.The physics based model considers the primary root cause,in terms of tool deflection and clamping stiffness induced Axial Material Removal Thickness(AMRT)variation,for the RBTE formation.And to incorporate the dynamic and inherent coupling of the complicated manufacturing system,the multi-feature fusion and machine learning algorithm,i.e.kernel Principal Component Analysis(kPCA)and kernel Support Vector Regression(kSVR),are incorporated with the physics based model.Therefore,the proposed data-driven physics based model combines both process mechanism and the system disturbance to achieve better prediction accuracy.The final verification experiment is implemented to validate the effectiveness of the proposed method for dimensional accuracy prediction in pocket milling,and the prediction accuracy of AMRT achieves 0.014 mm and 0.019 mm for straight and corner milling,respectively.

Robust and Real-Time Guidewire Simulation Based on Kirchhoff Elastic Rod for Vascular Intervention Training

Virtual reality(VR) based vascular intervention training is a fascinating innovation, which helps trainees develop skills in safety remote from patients. The vascular intervention training involves the use of flexible tipped guidewires to advance diagnostic or therapeutic catheters into a patient's vascular anatomy. In this paper, a real-time physically-based modeling approach is proposed to simulate complicated behaviors of guidewires and catheters based on Kirchhoff elastic rod. The slender body of guidewire and catheter is simulated using more efficient special case of naturally straight, isotropic Kirchhoff rods, and the short flexible tip composed of straight or angled design is modeled using more complex generalized Kirchhoff rods. We derive the equations of motion for guidewire and catheter with continuous elastic energy, and then they were discretized using a linear implicit scheme that guarantees stability and robustness. In addition, we apply a fast-projection method to enforce the inextensibility of guidewire and catheter, while an adaptive sampling algorithm is implemented to improve the simulation efficiency without reducing accuracy. Experimental results reveal that our guidewire simulation method is both robust and efficient in a real-time performance.

A Finite Difference Method Modeling for IGBT and Diode in PSPICE

In this paper,a novel modeling approach for both PiN diode and IGBT is presented.In this model,the carrier diffusion equation,which retains the distributed nature of charge dynamics in bipolar power devices,is solved directly by finite difference method in PSPICE.The physical basis of this model and some practical considerations are introduced.Compared with conventional Fourier based IGBT model,the presented model keeps higher simulation speed and comparable high accuracy.These features were also verified by simulations and experiments.

Stable Real-Time Surgical Cutting Simulation of Deformable Objects Embedded with Arbitrary Triangular Meshes

Surgical simulators need to simulate deformation and cutting of deformable objects. Adaptive octree mesh based cutting methods embed the deformable objects into octree meshes that are recursively refined near the cutting tool trajectory. Deformation is only applied to the octree meshes; thus the deformation instability problem caused by degenerated elements is avoided. Biological tissues and organs usually contain complex internal structures that are ignored by previous work. In this paper the deformable objects are modeled as voxels connected by links and embedded inside adaptive octree meshes. Links swept by the cutting tool are disconnected and object surface meshes are reconstructed from disconnected links. Two novel methods for embedding triangular meshes as internal structures are proposed. The surface mesh embedding method is applicable to arbitrary triangular meshes, but these meshes have no physical properties. The material sub-region embedding method associates the interiors enclosed by the triangular meshes with physical properties, but requires that these meshes are watertight, and have no self-intersections, and their smallest features are larger than a voxel. Some local features are constructed in a pre-calculation stage to increase simulation performance. Simulation tests show that our methods can cut embedded structures in a way consistent with the cutting of the deformable objects. Cut fragments can also deform correctly along with the deformable objects.

Inflatable Models

A physically-based model is presented for the simulation of a new type of deformable objects-inflatable objects, such as shaped balloons, which consist of pressurized air enclosed by an elastic surface. These objects have properties inherent in both 3D and 2D elastic bodies, as they demonstrate the behaviour of 3D shapes using 2D formulations. As there is no internal structure in them, their behaviour is substantially different from the behaviour of deformable solid objects. We use one of the few available models for deformable surfaces, and enhance it to include the forces of internal and external pressure. These pressure forces may also incorporate buoyancy forces, to allow objects filled with a low density gas to float in denser media. The obtained models demonstrate rich dynamic behaviour, such as bouncing, floating, deflation and inflation.

Visual Simulation of Multiple Unmixable Fluids

We present a novel grid-based method for simulating multiple unmixable fluids moving and interacting. Unlike previous methods that can only represent the interface between two fluids （usually between liquid and gas）, this method can handle an arbitrary number of fluids through multiple independent level sets coupled with a constrain condition. To capture the fluid surface more accurately, we extend the particle level set method to a multi-fluid version. It shares the advantages of the particle level set method, and has the ability to track the interfaces of multiple fluids. To handle the dynamic behavior of different fluids existing together, we use a multiphase fluid formulation based on a smooth weight function.

A Boundary Element Method for Simulation of Deformable Objects

In this paper, a boundary element method is first applied to real-time animation of deformable objects and to simplify data preparation. Next, the visible external surface of the object in deforming process is represented by B-spline surface, whose control points are embedded in dynamic equations of BEM. Finally, the above method is applied to anatomical simulation. A pituitary model in human brain, which is reconstructed from a set of anatomical sections, is selected to be the deformable object under action of virtual tool such as scalpel or probe. It produces fair graphic realism and high speed performance. The results show that BEM not only has less computational expense than FEM, but also is convenient to combine with the 3D reconstruction and surface modeling as it enables the reduction of the dimensionality of the problem by one.

Modeling of cylindrical surrounding gate MOSFETs including the fringing field effects

A physically based analytical model for surface potential and threshold voltage including the fringing gate capacitances in cylindrical surround gate（CSG） MOSFETs has been developed.Based on this a subthreshold drain current model has also been derived.This model first computes the charge induced in the drain/source region due to the fringing capacitances and considers an effective charge distribution in the cylindrically extended source/drain region for the development of a simple and compact model.The fringing gate capacitances taken into account are outer fringe capacitance,inner fringe capacitance,overlap capacitance,and sidewall capacitance.The model has been verified with the data extracted from 3D TCAD simulations of CSG MOSFETs and was found to be working satisfactorily.

Constitutive Model for the Thermo-viscoplastic Behavior of Hexagonal Close-Packed Metals with Application to Ti-6A1-4V Alloy

In this paper, a new physically based constitutive model is developed for hexagonal close-packed metals, especially the Ti-6Al-4V alloy, subjected to high strain rate and different temperatures based on the microscopic mechanism of plastic deformation and the theory of thermally activated dislocation motion. A global analysis of constitutive parameters based on the Latin Hypercube Sampling method and the Spearman＇s rank correlation method is adopted in order to improve the identification efficiency of parameters. Then, an optimal solution of constitutive parameters as a whole is obtained by using a global genetic algorithm composed of an improved niche genetic algorithm, a global peak determination strategy and the local accurate search techniques. It is concluded that the proposed constitutive modal can accurately describe the Ti-6Al-4V alloy＇s dynamic behavior because the prediction results of the model are in good agreement with the experimental data.

Variance reduction using interframe coherence for animated scenes

In an animated scene,geometry and lighting often change in an unpredictable way. Rendering algorithms based on Monte Carlo methods are usually employed to precisely capture all features of an animated scene. However,Monte Carlo methods typically take a long time to produce a noise-free image. In this paper,we propose a variance reduction technique for Monte Carlo methods which exploits coherence between frames. Firstly,we introduce a dual cone model to measure the incident coherence intersecting camera rays in object space. Secondly,we allocate multiple frame buffers to store image samples from consecutive frames. Finally,the color of a pixel in one frame is computed by borrowing samples from neighboring pixels in current,previous,and subsequent frames. Our experiments show that noise is greatly reduced by our method since the number of effective samples is increased by use of borrowed samples.

Nearshore regional behavior of lightning interaction with wind turbines

The severity of lightning strikes on offshore wind turbines built along coastal and nearshore regions can pose safety concerns that are often overlooked.In this research study the behavior of electrical discharges for wind turbines that might be located in the nearshore regions along the East Coast of China and Sea of Japan were characterized using a physics-based model that accounted for a total of eleven different geometrical and lightning parameters.Utilizing the electrical potential field predicted using this model it was then possible to estimate the frequency of lightning strikes and the distribution of electrical loads utilizing established semi-empirical relationships and available data.The total number of annual lightning strikes on an offshore wind turbine was found to vary with hub elevation,extent of cloud cover,season and geographical location.The annual lightning strike rate on a wind turbine along the nearshore region on the Sea of Japan during the winter season was shown to be moderately larger compared to the lightning strike frequency on a turbine structure on the East Coast of China.Short duration electrical discharges,represented using marginal probability functions,were found to vary with season and geographical location,exhibiting trends consistent with the distribution of the electrical peak current.It was demonstrated that electrical discharges of moderately long duration typically occur in the winter months on the East Coast of China and the summer season along the Sea of Japan.In contrast,severe electrical discharges are typical of summer thunderstorms on the East Coast of China and winter frontal storm systems along the West Coast of Japan.The electrical charge and specific energy dissipated during lightning discharges on an offshore wind turbine was found to vary stochastically,with severe electrical discharges corresponding to large electrical currents of long duration.