To enhance the computational efficiency of spatio-temporally discretized phase-field models,we present a high-speed solver specifically designed for the Poisson equations,a component frequently used in the numerical c...To enhance the computational efficiency of spatio-temporally discretized phase-field models,we present a high-speed solver specifically designed for the Poisson equations,a component frequently used in the numerical computation of such models.This efficient solver employs algorithms based on discrete cosine transformations(DCT)or discrete sine transformations(DST)and is not restricted by any spatio-temporal schemes.Our proposed methodology is appropriate for a variety of phase-field models and is especially efficient when combined with flow field systems.Meanwhile,this study has conducted an extensive numerical comparison and found that employing DCT and DST techniques not only yields results comparable to those obtained via the Multigrid(MG)method,a conventional approach used in the resolution of the Poisson equations,but also enhances computational efficiency by over 90%.展开更多
Rock burst is a kind of geological disaster in rock excavation of high stress areas.To evaluate intensity of rock burst,the maximum shear stress,uniaxial compressive strength,uniaxial tensile strength and rock elastic...Rock burst is a kind of geological disaster in rock excavation of high stress areas.To evaluate intensity of rock burst,the maximum shear stress,uniaxial compressive strength,uniaxial tensile strength and rock elastic energy index were selected as input factors,and burst pit depth as output factor.The rock burst prediction model was proposed according to the genetic algorithms and extreme learning machine.The effect of structural surface was taken into consideration.Based on the engineering examples of tunnels,the observed and collected data were divided into the training set,validation set and prediction set.The training set and validation set were used to train and optimize the model.Parameter optimization results are presented.The hidden layer node was450,and the fitness of the predictions was 0.0197 under the optimal combination of the input weight and offset vector.Then,the optimized model is tested with the prediction set.Results show that the proposed model is effective.The maximum relative error is4.71%,and the average relative error is 3.20%,which proves that the model has practical value in the relative engineering.展开更多
In order to improve the trajectory tracking precision and reduce the synchronization error of a 6-DOF lightweight robot, nonlinear proportion-deviation （N-PD） cross-coupling synchronization control strategy based on...In order to improve the trajectory tracking precision and reduce the synchronization error of a 6-DOF lightweight robot, nonlinear proportion-deviation （N-PD） cross-coupling synchronization control strategy based on adjacent coupling error analysis is presented. The mathematical models of the robot, including kinematic model, dynamic model and spline trajectory planing, are established and verified. Since it is difficult to describe the real-time contour error of the robot for complex trajectory, the adjacent coupling error is analyzed to solve the problem. Combined with nonlinear control and coupling performance of the robot, N-PD cross-coupling synchronization controller is designed and validated by simulation analysis. A servo control experimental system which mainly consists of laser tracking system, the robot mechanical system and EtherCAT based servo control system is constructed. The synchronization error is significantly decreased and the maximum trajectory error is reduced from 0.33 mm to 0.1 mm. The effectiveness of the control algorithm is validated by the experimental results, thus the control strategy can improve the robot＇s trajectory tracking precision significantly.展开更多
基金Supported by Shanxi Province Natural Science Research(202203021212249)Special/Youth Foundation of Taiyuan University of Technology(2022QN101)+3 种基金National Natural Science Foundation of China(12301556)Research Project Supported by Shanxi Scholarship Council of China(2021-029)International Cooperation Base and Platform Project of Shanxi Province(202104041101019)Basic Research Plan of Shanxi Province(202203021211129)。
文摘To enhance the computational efficiency of spatio-temporally discretized phase-field models,we present a high-speed solver specifically designed for the Poisson equations,a component frequently used in the numerical computation of such models.This efficient solver employs algorithms based on discrete cosine transformations(DCT)or discrete sine transformations(DST)and is not restricted by any spatio-temporal schemes.Our proposed methodology is appropriate for a variety of phase-field models and is especially efficient when combined with flow field systems.Meanwhile,this study has conducted an extensive numerical comparison and found that employing DCT and DST techniques not only yields results comparable to those obtained via the Multigrid(MG)method,a conventional approach used in the resolution of the Poisson equations,but also enhances computational efficiency by over 90%.
基金Project(2013CB036004)supported by the National Basic Research Program of ChinaProject(51378510)supported by the National Natural Science Foundation of China
文摘Rock burst is a kind of geological disaster in rock excavation of high stress areas.To evaluate intensity of rock burst,the maximum shear stress,uniaxial compressive strength,uniaxial tensile strength and rock elastic energy index were selected as input factors,and burst pit depth as output factor.The rock burst prediction model was proposed according to the genetic algorithms and extreme learning machine.The effect of structural surface was taken into consideration.Based on the engineering examples of tunnels,the observed and collected data were divided into the training set,validation set and prediction set.The training set and validation set were used to train and optimize the model.Parameter optimization results are presented.The hidden layer node was450,and the fitness of the predictions was 0.0197 under the optimal combination of the input weight and offset vector.Then,the optimized model is tested with the prediction set.Results show that the proposed model is effective.The maximum relative error is4.71%,and the average relative error is 3.20%,which proves that the model has practical value in the relative engineering.
基金Project(2015AA043003)supported by National High-technology Research and Development Program of ChinaProject(GY2016ZB0068)supported by Application Technology Research and Development Program of Heilongjiang Province,ChinaProject(SKLR201301A03)supported by Self-planned Task of State Key Laboratory of Robotics and System(Harbin Institute of Technology),China
文摘In order to improve the trajectory tracking precision and reduce the synchronization error of a 6-DOF lightweight robot, nonlinear proportion-deviation （N-PD） cross-coupling synchronization control strategy based on adjacent coupling error analysis is presented. The mathematical models of the robot, including kinematic model, dynamic model and spline trajectory planing, are established and verified. Since it is difficult to describe the real-time contour error of the robot for complex trajectory, the adjacent coupling error is analyzed to solve the problem. Combined with nonlinear control and coupling performance of the robot, N-PD cross-coupling synchronization controller is designed and validated by simulation analysis. A servo control experimental system which mainly consists of laser tracking system, the robot mechanical system and EtherCAT based servo control system is constructed. The synchronization error is significantly decreased and the maximum trajectory error is reduced from 0.33 mm to 0.1 mm. The effectiveness of the control algorithm is validated by the experimental results, thus the control strategy can improve the robot＇s trajectory tracking precision significantly.
