Simulation of Cavitating Water Flow in High Energy Spillways

2012 ◽  
Author(s):  
Piroz Zamankhan
Keyword(s):  
Gpu Computing ◽  
Graphics Processing Unit ◽  
Three Dimensional ◽  
High Energy ◽  
Cfd Modeling ◽  
Processing Unit ◽  
Water Mixture ◽  
Ocean Engineering ◽  
Eddy Simulation ◽  
Simulation Techniques

The air-water mixture from an artificially aerated spillway flowing down to a canyon may create major erosion and damage to both the spillway’s surface and the environment. In this case, the location of an aerator to prevent cavitation scour and decrease the energy head of the flow, its geometry and the aeration flow rate would be important factors in designing an environmental friendly high energy spillway. In this work, an analysis of the problem based on physical and computational fluid dynamics (CFD) modeling is presented. The numerical modelling is a large-eddy simulation technique (LES) combined with a discrete element method. Three-dimensional simulations of a spillway are performed on a graphics processing unit (GPU). The result of this analysis in the form of design suggestions intend to diminish the hazards associated with cavitation and may minimize canyon erosion. This promising effort in GPU computing could pave the way for developing advanced simulation techniques for the study of waterways and ports, as well as coastal and ocean engineering in the future.

scholarly journals Simulation of Cavitation Water Flows

2015 ◽  
Vol 2015 ◽  
pp. 1-16 ◽  
Author(s):  
Piroz Zamankhan
Keyword(s):  
Graphics Processing Unit ◽  
Three Dimensional ◽  
High Energy ◽  
Cfd Modeling ◽  
Processing Unit ◽  
Water Mixture ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Computational Fluid Dynamics Cfd ◽  
Graphics Processing

The air-water mixture from an artificially aerated spillway flowing down to a canyon may cause serious erosion and damage to both the spillway surface and the environment. The location of an aerator, its geometry, and the aeration flow rate are important factors in the design of an environmentally friendly high-energy spillway. In this work, an analysis of the problem based on physical and computational fluid dynamics (CFD) modeling is presented. The numerical modeling used was a large eddy simulation technique (LES) combined with a discrete element method. Three-dimensional simulations of a spillway were performed on a graphics processing unit (GPU). The result of this analysis in the form of design suggestions may help diminishing the hazards associated with cavitation.

A Real-Time Photogrammetric System for Acquisition and Monitoring of Three-Dimensional Human Body Kinematics

2021 ◽  
Vol 87 (5) ◽  
pp. 363-373
Author(s):  
Long Chen ◽  
Bo Wu ◽  
Yao Zhao ◽  
Yuan Li
Keyword(s):  
Real Time ◽  
Human Body ◽  
Graphics Processing Unit ◽  
Three Dimensional ◽  
Stereo Pair ◽  
Processing Unit ◽  
Detection Distance ◽  
Human Kinematics ◽  
Graphics Processing ◽  
Time Acquisition

Real-time acquisition and analysis of three-dimensional (3D) human body kinematics are essential in many applications. In this paper, we present a real-time photogrammetric system consisting of a stereo pair of red-green-blue (RGB) cameras. The system incorporates a multi-threaded and graphics processing unit (GPU)-accelerated solution for real-time extraction of 3D human kinematics. A deep learning approach is adopted to automatically extract two-dimensional (2D) human body features, which are then converted to 3D features based on photogrammetric processing, including dense image matching and triangulation. The multi-threading scheme and GPU-acceleration enable real-time acquisition and monitoring of 3D human body kinematics. Experimental analysis verified that the system processing rate reached ∼18 frames per second. The effective detection distance reached 15 m, with a geometric accuracy of better than 1% of the distance within a range of 12 m. The real-time measurement accuracy for human body kinematics ranged from 0.8% to 7.5%. The results suggest that the proposed system is capable of real-time acquisition and monitoring of 3D human kinematics with favorable performance, showing great potential for various applications.

scholarly journals Prediction of Residual Stresses in a Multipass Pipe Weld by a Novel 3D Finite Element Approach

2018 ◽  
Author(s):  
Hui Huang ◽  
Jian Chen ◽  
Blair Carlson ◽  
Hui-Ping Wang ◽  
Paul Crooker ◽  
...  
Keyword(s):  
Finite Element ◽  
Residual Stresses ◽  
High Performance ◽  
Large Scale ◽  
Graphics Processing Unit ◽  
Computational Cost ◽  
Three Dimensional ◽  
Processing Unit ◽  
Girth Welds ◽  
Welding Processes

Due to enormous computation cost, current residual stress simulation of multipass girth welds are mostly performed using two-dimensional (2D) axisymmetric models. The 2D model can only provide limited estimation on the residual stresses by assuming its axisymmetric distribution. In this study, a highly efficient thermal-mechanical finite element code for three dimensional (3D) model has been developed based on high performance Graphics Processing Unit (GPU) computers. Our code is further accelerated by considering the unique physics associated with welding processes that are characterized by steep temperature gradient and a moving arc heat source. It is capable of modeling large-scale welding problems that cannot be easily handled by the existing commercial simulation tools. To demonstrate the accuracy and efficiency, our code was compared with a commercial software by simulating a 3D multi-pass girth weld model with over 1 million elements. Our code achieved comparable solution accuracy with respect to the commercial one but with over 100 times saving on computational cost. Moreover, the three-dimensional analysis demonstrated more realistic stress distribution that is not axisymmetric in hoop direction.

scholarly journals Real-Time Computer Simulation of Three Dimensional Elastostatics Using the Finite Point Method

2011 ◽  
Vol 110-116 ◽  
pp. 2740-2745
Author(s):  
Kirana Kumara P. ◽  
Ashitava Ghosal
Keyword(s):  
Real Time ◽  
Graphics Processing Unit ◽  
Numerical Technique ◽  
Three Dimensional ◽  
Point Method ◽  
Processing Unit ◽  
Finite Point ◽  
Deformable Solids ◽  
Finite Point Method ◽  
Linear Elastostatics

Real-time simulation of deformable solids is essential for some applications such as biological organ simulations for surgical simulators. In this work, deformable solids are approximated to be linear elastic, and an easy and straight forward numerical technique, the Finite Point Method (FPM), is used to model three dimensional linear elastostatics. Graphics Processing Unit (GPU) is used to accelerate computations. Results show that the Finite Point Method, together with GPU, can compute three dimensional linear elastostatic responses of solids at rates suitable for real-time graphics, for solids represented by reasonable number of points.

scholarly journals Machine Learning in Python: Main Developments and Technology Trends in Data Science, Machine Learning, and Artificial Intelligence

Information ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 193 ◽  
Author(s):  
Sebastian Raschka ◽  
Joshua Patterson ◽  
Corey Nolet
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Data Science ◽  
Gpu Computing ◽  
Graphics Processing Unit ◽  
General Purpose ◽  
Processing Unit ◽  
The Core ◽  
Critical Components ◽  
High Level

Smarter applications are making better use of the insights gleaned from data, having an impact on every industry and research discipline. At the core of this revolution lies the tools and the methods that are driving it, from processing the massive piles of data generated each day to learning from and taking useful action. Deep neural networks, along with advancements in classical machine learning and scalable general-purpose graphics processing unit (GPU) computing, have become critical components of artificial intelligence, enabling many of these astounding breakthroughs and lowering the barrier to adoption. Python continues to be the most preferred language for scientific computing, data science, and machine learning, boosting both performance and productivity by enabling the use of low-level libraries and clean high-level APIs. This survey offers insight into the field of machine learning with Python, taking a tour through important topics to identify some of the core hardware and software paradigms that have enabled it. We cover widely-used libraries and concepts, collected together for holistic comparison, with the goal of educating the reader and driving the field of Python machine learning forward.

scholarly journals A Multi-GPU Parallel Algorithm in Hypersonic Flow Computations

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Jianqi Lai ◽  
Hua Li ◽  
Zhengyu Tian ◽  
Ye Zhang
Keyword(s):  
Parallel Algorithm ◽  
Hypersonic Flow ◽  
Stokes Equations ◽  
Programming Model ◽  
Graphics Processing Unit ◽  
Three Dimensional ◽  
Flow Characteristics ◽  
Time Discretization ◽  
Processing Unit ◽  
Complex Flow

Computational fluid dynamics (CFD) plays an important role in the optimal design of aircraft and the analysis of complex flow mechanisms in the aerospace domain. The graphics processing unit (GPU) has a strong floating-point operation capability and a high memory bandwidth in data parallelism, which brings great opportunities for CFD. A cell-centred finite volume method is applied to solve three-dimensional compressible Navier–Stokes equations on structured meshes with an upwind AUSM+UP numerical scheme for space discretization, and four-stage Runge–Kutta method is used for time discretization. Compute unified device architecture (CUDA) is used as a parallel computing platform and programming model for GPUs, which reduces the complexity of programming. The main purpose of this paper is to design an extremely efficient multi-GPU parallel algorithm based on MPI+CUDA to study the hypersonic flow characteristics. Solutions of hypersonic flow over an aerospace plane model are provided at different Mach numbers. The agreement between numerical computations and experimental measurements is favourable. Acceleration performance of the parallel platform is studied with single GPU, two GPUs, and four GPUs. For single GPU implementation, the speedup reaches 63 for the coarser mesh and 78 for the finest mesh. GPUs are better suited for compute-intensive tasks than traditional CPUs. For multi-GPU parallelization, the speedup of four GPUs reaches 77 for the coarser mesh and 147 for the finest mesh; this is far greater than the acceleration achieved by single GPU and two GPUs. It is prospective to apply the multi-GPU parallel algorithm to hypersonic flow computations.

A Survey of General Purpose Computation of GPU for Computational Fluid Dynamics

2013 ◽  
Vol 753-755 ◽  
pp. 2731-2735
Author(s):  
Wei Cao ◽  
Zheng Hua Wang ◽  
Chuan Fu Xu
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
High Performance ◽  
Stokes Equations ◽  
Gpu Computing ◽  
Graphics Processing Unit ◽  
General Purpose ◽  
Navier Stokes ◽  
Processing Unit ◽  
Gpgpu Computing

The graphics processing unit (GPU) has evolved from configurable graphics processor to a powerful engine for high performance computer. In this paper, we describe the graphics pipeline of GPU, and introduce the history and evolution of GPU architecture. We also provide a summary of software environments used on GPU, from graphics APIs to non-graphics APIs. At last, we present the GPU computing in computational fluid dynamics applications, including the GPGPU computing for Navier-Stokes equations methods and the GPGPU computing for Lattice Boltzmann method.

scholarly journals THREE-DIMENSIONAL MODELING OF LONG-WAVE RUNUP: SIMULATION OF TSUNAMI INUNDATION WITH GPU-SPHYSICS

2011 ◽  
Vol 1 (32) ◽  
pp. 8 ◽  
Author(s):  
Robert Weiss ◽  
Andrew James Munoz ◽  
Robert A. Dalrymple ◽  
Alexis Herault ◽  
Giuseppe Bilotta
Keyword(s):  
Assessment Tool ◽  
Graphics Processing Unit ◽  
Laboratory Data ◽  
Three Dimensional ◽  
Processing Unit ◽  
Wave Runup ◽  
Tsunami Inundation ◽  
Three Dimensional Modeling ◽  
Particle Hydrodynamics ◽  
Graphics Processing

Tsunamis need to be studied more carefully and quantitatively to fully understand their destructive impact on coastal areas. Numerical modeling provides an accurate and useful method to model tsunami inundations on a coastline. However, models must undergo a detailed verification and validation process to be used as an accurate hazard assessment tool. Using standards and procedures given by NOAA, a new code in hydrodynamic modeling called GPU-SPHysics can be verified and validated for use as a tsunami inundation model. GPU-SPHysics is a meshless, Lagrangian code that utilizes the computing power of the Graphics Processing Unit (GPU) to calculate high resolution hydrodynamic simulations using the equations given by Smooth Particle Hydrodynamics (SPH). GPU-SPHysics has proven to be an accurate tool in modeling complex tsunami inundations, such as the inundation on a conical island, when tested against extensive laboratory data.

Clearance Measurement of 3D Objects Using Accessibility Cone

2019 ◽  
Author(s):  
Masatomo Inui ◽  
Kouhei Nishimiya ◽  
Nobuyuki Umezu
Keyword(s):  
Graphics Processing Unit ◽  
Three Dimensional ◽  
Computation Time ◽  
Depth Information ◽  
Computation Method ◽  
Processing Unit ◽  
Three Dimensional Objects ◽  
Mechanical Products ◽  
Definition Of ◽  
Graphics Processing

Abstract Clearance is a basic parameter in the design of mechanical products, generally specified as the distance between two shape elements, for example, the width of a slot. This definition is unsuitable for evaluating the clearance during assembly or manufacturing tasks, where the depth information is also critical. In this paper, we propose a novel definition of clearance for the surface of three-dimensional objects. Unlike the typical methods used to define clearance, the proposed method can simultaneously handle the relationship between the width and depth in the clearance, and thus, obtain an intuitive understanding regarding the assembly and manufacturing capability of a product. Our definition is based on the accessibility cone of a point on the object’s surface; further, the peak angle of the accessibility cone corresponds to the clearance at this point. A computation method of the clearance is presented and the results of its application are demonstrated. Our method uses the rendering function of a graphics processing unit to compute the clearance. A large computation time necessary for the analysis is considered as a problem regarding the practical use of this clearance definition.

scholarly journals Efficient Parallel Algorithms for 3D Laplacian Smoothing on the GPU

2019 ◽  
Vol 9 (24) ◽  
pp. 5437
Author(s):  
Lei Xiao ◽  
Guoxiang Yang ◽  
Kunyang Zhao ◽  
Gang Mei
Keyword(s):  
Large Scale ◽  
Graphics Processing Unit ◽  
Parallel Implementation ◽  
Three Dimensional ◽  
Smoothing Method ◽  
Three Dimensions ◽  
Processing Unit ◽  
Mesh Quality ◽  
Mesh Smoothing ◽  
Laplacian Smoothing

In numerical modeling, mesh quality is one of the decisive factors that strongly affects the accuracy of calculations and the convergence of iterations. To improve mesh quality, the Laplacian mesh smoothing method, which repositions nodes to the barycenter of adjacent nodes without changing the mesh topology, has been widely used. However, smoothing a large-scale three dimensional mesh is quite computationally expensive, and few studies have focused on accelerating the Laplacian mesh smoothing method by utilizing the graphics processing unit (GPU). This paper presents a GPU-accelerated parallel algorithm for Laplacian smoothing in three dimensions by considering the influence of different data layouts and iteration forms. To evaluate the efficiency of the GPU implementation, the parallel solution is compared with the original serial solution. Experimental results show that our parallel implementation is up to 46 times faster than the serial version.

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