In the smoothed particle hydrodynamics (SPH) method, a meshless interpolation scheme is needed for the unknown function in order to discretize the governing equation.A particle approximation method has so far been use...In the smoothed particle hydrodynamics (SPH) method, a meshless interpolation scheme is needed for the unknown function in order to discretize the governing equation.A particle approximation method has so far been used for this purpose.Traditional particle interpolation (TPI) is simple and easy to do, but its low accuracy has become an obstacle to its wider application.This can be seen in the cases of particle disorder arrangements and derivative calculations.There are many different methods to improve accuracy, with the moving least square (MLS) method one of the most important meshless interpolation methods.Unfortunately, it requires complex matrix computing and so is quite time-consuming.The authors developed a simpler scheme, called higher-order particle interpolation (HPI).This scheme can get more accurate derivatives than the MLS method, and its function value and derivatives can be obtained simultaneously.Although this scheme was developed for the SPH method, it has been found useful for other meshless methods.展开更多
In this paper, we present an acceleration strategy for Smoothed Particle Hydrodynamics （SPH） on multi-GPU platform. For single-GPU, we first use a neighborhood search algorithm of compacting cell index combined with...In this paper, we present an acceleration strategy for Smoothed Particle Hydrodynamics （SPH） on multi-GPU platform. For single-GPU, we first use a neighborhood search algorithm of compacting cell index combined with spatial domain characteristics For multi-GPU, we focus on the changing patterns of SPH＇s computational time. Simple dynamic load balancing algorithm works well because the computational time of each time step changes slowly compared to previous time step. By further optimizing dynamic load balancing algorithm and the communication strategy among GPUs, a nearly linear speedup is achieved in different scenarios with a scale of millions particles. The quality and efficiency of our methods are demonstrated using multiple scenes with different particle numbers.展开更多
Normally large amounts of particles are required to accurately simulate the metal cutting process,which consumes a lot of computing time and storage.Adaptive techniques can help decrease the number of particles,hence ...Normally large amounts of particles are required to accurately simulate the metal cutting process,which consumes a lot of computing time and storage.Adaptive techniques can help decrease the number of particles,hence reducing the runtime.This paper presents a novel adaptive smoothed particle hydrodynamics(SPH)method for the metal cutting simulation.The spatial resolution changes adaptively according to the distance to the tool tip by the particle splitting and merging.More particles are selected in the region where the workpiece and the tool are in contact.Since the contact region constantly changes during the cutting process,two quadrilateral frames are adopted in the adaptive algorithm to dynamically change the distribution of particles.One frame for the refinement,the other for the coarsening.These frames move at the same speed as the tool.To test the computational efficiency,the metal cutting process is simulated by using SPH with three different adaptive approaches.Numerical results show that the proposed adaptive algorithm with dynamic refinement and coarsening can significantly optimize the runtime.展开更多
基金Supported by the National Natural Science Foundation of China under Grant No.10572041,50779008Doctoral Fund of Ministry of Education of China under Grant No.20060217009
文摘In the smoothed particle hydrodynamics (SPH) method, a meshless interpolation scheme is needed for the unknown function in order to discretize the governing equation.A particle approximation method has so far been used for this purpose.Traditional particle interpolation (TPI) is simple and easy to do, but its low accuracy has become an obstacle to its wider application.This can be seen in the cases of particle disorder arrangements and derivative calculations.There are many different methods to improve accuracy, with the moving least square (MLS) method one of the most important meshless interpolation methods.Unfortunately, it requires complex matrix computing and so is quite time-consuming.The authors developed a simpler scheme, called higher-order particle interpolation (HPI).This scheme can get more accurate derivatives than the MLS method, and its function value and derivatives can be obtained simultaneously.Although this scheme was developed for the SPH method, it has been found useful for other meshless methods.
文摘In this paper, we present an acceleration strategy for Smoothed Particle Hydrodynamics （SPH） on multi-GPU platform. For single-GPU, we first use a neighborhood search algorithm of compacting cell index combined with spatial domain characteristics For multi-GPU, we focus on the changing patterns of SPH＇s computational time. Simple dynamic load balancing algorithm works well because the computational time of each time step changes slowly compared to previous time step. By further optimizing dynamic load balancing algorithm and the communication strategy among GPUs, a nearly linear speedup is achieved in different scenarios with a scale of millions particles. The quality and efficiency of our methods are demonstrated using multiple scenes with different particle numbers.
基金the National Natural Science Foundation of China(Grant Nos.12002290 and 11772274).
文摘Normally large amounts of particles are required to accurately simulate the metal cutting process,which consumes a lot of computing time and storage.Adaptive techniques can help decrease the number of particles,hence reducing the runtime.This paper presents a novel adaptive smoothed particle hydrodynamics(SPH)method for the metal cutting simulation.The spatial resolution changes adaptively according to the distance to the tool tip by the particle splitting and merging.More particles are selected in the region where the workpiece and the tool are in contact.Since the contact region constantly changes during the cutting process,two quadrilateral frames are adopted in the adaptive algorithm to dynamically change the distribution of particles.One frame for the refinement,the other for the coarsening.These frames move at the same speed as the tool.To test the computational efficiency,the metal cutting process is simulated by using SPH with three different adaptive approaches.Numerical results show that the proposed adaptive algorithm with dynamic refinement and coarsening can significantly optimize the runtime.
