The aging of operational reactors leads to increased mechanical vibrations in the reactor interior.The vibration of the incore sensors near their nominal locations is a new problem for neutronic field reconstruction.C...The aging of operational reactors leads to increased mechanical vibrations in the reactor interior.The vibration of the incore sensors near their nominal locations is a new problem for neutronic field reconstruction.Current field-reconstruction methods fail to handle spatially moving sensors.In this study,we propose a Voronoi tessellation technique in combination with convolutional neural networks to handle this challenge.Observations from movable in-core sensors were projected onto the same global field structure using Voronoi tessellation,holding the magnitude and location information of the sensors.General convolutional neural networks were used to learn maps from observations to the global field.The proposed method reconstructed multi-physics fields(including fast flux,thermal flux,and power rate)using observations from a single field(such as thermal flux).Numerical tests based on the IAEA benchmark demonstrated the potential of the proposed method in practical engineering applications,particularly within an amplitude of 5 cm around the nominal locations,which led to average relative errors below 5% and 10% in the L_(2) and L_(∞)norms,respectively.展开更多
The Voronoi grain-based breakable block model(VGBBM)based on the combined finite-discrete element method(FDEM)was proposed to explicitly characterize the failure mechanism and predict the deformation behavior of hard-...The Voronoi grain-based breakable block model(VGBBM)based on the combined finite-discrete element method(FDEM)was proposed to explicitly characterize the failure mechanism and predict the deformation behavior of hard-rock mine pillars.The influence of the microscopic parameters on the macroscopic mechanical behavior was investigated using laboratory-scale models.The field-scale pillar models(width-to-height,W/H=1,2 and 3)were calibrated based on the empirically predicted stress-strain curves of Creighton mine pillars.The results indicated that as the W/H ratios increased,the VGBBM effectively predicted the transition from strain-softening to pseudo-ductile behavior in pillars,and explicitly captured the separated rock slabs and the V-shaped damage zones on both sides of pillars and conjugate shear bands in core zones of pillars.The volumetric strain field revealed significant compressional deformation in core zones of pillars.While the peak strains of W/H=1 and 2 pillars were relatively consistent,there were significant differences in the strain energy storage and release mechanism.W/H was the primary factor influencing the deformation and strain energy in the pillar core.The friction coefficient of the structural plane was also an important factor affecting the pillar strength and the weakest discontinuity angle.The fracture surface was controlled by the discontinuity angle and the friction coefficient.This study demonstrated the capability of the VGBBM in predicting the strengths and deformation behavior of hard-rock pillars in deep mine design.展开更多
This work proposes an online collaborative hunting strategy for multi-robot systems based on obstacle-avoiding Voronoi cells in a complex dynamic environment. This involves firstly designing the construction method us...This work proposes an online collaborative hunting strategy for multi-robot systems based on obstacle-avoiding Voronoi cells in a complex dynamic environment. This involves firstly designing the construction method using a support vector machine(SVM) based on the definition of buffered Voronoi cells(BVCs). Based on the safe collision-free region of the robots, the boundary weights between the robots and the obstacles are dynamically updated such that the robots are tangent to the buffered Voronoi safety areas without intersecting with the obstacles. Then, the robots are controlled to move within their own buffered Voronoi safety area to achieve collision-avoidance with other robots and obstacles. The next step involves proposing a hunting method that optimizes collaboration between the pursuers and evaders. Some hunting points are generated and distributed evenly around a circle. Next, the pursuers are assigned to match the optimal points based on the Hungarian algorithm.Then, a hunting controller is designed to improve the containment capability and minimize containment time based on collision risk. Finally, simulation results have demonstrated that the proposed cooperative hunting method is more competitive in terms of time and travel distance.展开更多
Storm surge is often the marine disaster that poses the greatest threat to life and property in coastal areas.Accurate and timely issuance of storm surge warnings to take appropriate countermeasures is an important me...Storm surge is often the marine disaster that poses the greatest threat to life and property in coastal areas.Accurate and timely issuance of storm surge warnings to take appropriate countermeasures is an important means to reduce storm surge-related losses.Storm surge numerical models are important for storm surge forecasting.To further improve the performance of the storm surge forecast models,we developed a numerical storm surge forecast model based on an unstructured spherical centroidal Voronoi tessellation(SCVT)grid.The model is based on shallow water equations in vector-invariant form,and is discretized by Arakawa C grid.The SCVT grid can not only better describe the coastline information but also avoid rigid transitions,and it has a better global consistency by generating high-resolution grids in the key areas through transition refinement.In addition,the simulation speed of the model is accelerated by using the openACC-based GPU acceleration technology to meet the timeliness requirements of operational ensemble forecast.It only takes 37 s to simulate a day in the coastal waters of China.The newly developed storm surge model was applied to simulate typhoon-induced storm surges in the coastal waters of China.The hindcast experiments on the selected representative typhoon-induced storm surge processes indicate that the model can reasonably simulate the distribution characteristics of storm surges.The simulated maximum storm surges and their occurrence times are consistent with the observed data at the representative tide gauge stations,and the mean absolute errors are 3.5 cm and 0.6 h respectively,showing high accuracy and application prospects.展开更多
基金partially supported by the Natural Science Foundation of Shanghai(No.23ZR1429300)the Innovation Fund of CNNC(Lingchuang Fund)+1 种基金EP/T000414/1 PREdictive Modeling with QuantIfication of UncERtainty for MultiphasE Systems(PREMIERE)the Leverhulme Centre for Wildfires,Environment,and Society through the Leverhulme Trust(No.RC-2018-023).
文摘The aging of operational reactors leads to increased mechanical vibrations in the reactor interior.The vibration of the incore sensors near their nominal locations is a new problem for neutronic field reconstruction.Current field-reconstruction methods fail to handle spatially moving sensors.In this study,we propose a Voronoi tessellation technique in combination with convolutional neural networks to handle this challenge.Observations from movable in-core sensors were projected onto the same global field structure using Voronoi tessellation,holding the magnitude and location information of the sensors.General convolutional neural networks were used to learn maps from observations to the global field.The proposed method reconstructed multi-physics fields(including fast flux,thermal flux,and power rate)using observations from a single field(such as thermal flux).Numerical tests based on the IAEA benchmark demonstrated the potential of the proposed method in practical engineering applications,particularly within an amplitude of 5 cm around the nominal locations,which led to average relative errors below 5% and 10% in the L_(2) and L_(∞)norms,respectively.
基金the National Natural Science Foundation of China(No.42377172)the National Key Research and Development Plan Project of China(No.2023YFC2907204).
文摘The Voronoi grain-based breakable block model(VGBBM)based on the combined finite-discrete element method(FDEM)was proposed to explicitly characterize the failure mechanism and predict the deformation behavior of hard-rock mine pillars.The influence of the microscopic parameters on the macroscopic mechanical behavior was investigated using laboratory-scale models.The field-scale pillar models(width-to-height,W/H=1,2 and 3)were calibrated based on the empirically predicted stress-strain curves of Creighton mine pillars.The results indicated that as the W/H ratios increased,the VGBBM effectively predicted the transition from strain-softening to pseudo-ductile behavior in pillars,and explicitly captured the separated rock slabs and the V-shaped damage zones on both sides of pillars and conjugate shear bands in core zones of pillars.The volumetric strain field revealed significant compressional deformation in core zones of pillars.While the peak strains of W/H=1 and 2 pillars were relatively consistent,there were significant differences in the strain energy storage and release mechanism.W/H was the primary factor influencing the deformation and strain energy in the pillar core.The friction coefficient of the structural plane was also an important factor affecting the pillar strength and the weakest discontinuity angle.The fracture surface was controlled by the discontinuity angle and the friction coefficient.This study demonstrated the capability of the VGBBM in predicting the strengths and deformation behavior of hard-rock pillars in deep mine design.
基金supported by the National Natural Science Foundation of China (62273007,61973023)Project of Cultivation for Young Top-motch Talents of Beijing Municipal Institutions (BPHR202203032)。
文摘This work proposes an online collaborative hunting strategy for multi-robot systems based on obstacle-avoiding Voronoi cells in a complex dynamic environment. This involves firstly designing the construction method using a support vector machine(SVM) based on the definition of buffered Voronoi cells(BVCs). Based on the safe collision-free region of the robots, the boundary weights between the robots and the obstacles are dynamically updated such that the robots are tangent to the buffered Voronoi safety areas without intersecting with the obstacles. Then, the robots are controlled to move within their own buffered Voronoi safety area to achieve collision-avoidance with other robots and obstacles. The next step involves proposing a hunting method that optimizes collaboration between the pursuers and evaders. Some hunting points are generated and distributed evenly around a circle. Next, the pursuers are assigned to match the optimal points based on the Hungarian algorithm.Then, a hunting controller is designed to improve the containment capability and minimize containment time based on collision risk. Finally, simulation results have demonstrated that the proposed cooperative hunting method is more competitive in terms of time and travel distance.
基金The National Natural Science Foundation of China under contract No.42076214.
文摘Storm surge is often the marine disaster that poses the greatest threat to life and property in coastal areas.Accurate and timely issuance of storm surge warnings to take appropriate countermeasures is an important means to reduce storm surge-related losses.Storm surge numerical models are important for storm surge forecasting.To further improve the performance of the storm surge forecast models,we developed a numerical storm surge forecast model based on an unstructured spherical centroidal Voronoi tessellation(SCVT)grid.The model is based on shallow water equations in vector-invariant form,and is discretized by Arakawa C grid.The SCVT grid can not only better describe the coastline information but also avoid rigid transitions,and it has a better global consistency by generating high-resolution grids in the key areas through transition refinement.In addition,the simulation speed of the model is accelerated by using the openACC-based GPU acceleration technology to meet the timeliness requirements of operational ensemble forecast.It only takes 37 s to simulate a day in the coastal waters of China.The newly developed storm surge model was applied to simulate typhoon-induced storm surges in the coastal waters of China.The hindcast experiments on the selected representative typhoon-induced storm surge processes indicate that the model can reasonably simulate the distribution characteristics of storm surges.The simulated maximum storm surges and their occurrence times are consistent with the observed data at the representative tide gauge stations,and the mean absolute errors are 3.5 cm and 0.6 h respectively,showing high accuracy and application prospects.
