We have developed a plasma etching simulator to investigate the evolution of pattern profiles in SiO2 material under different plasma conditions. This model focuses on energy and angular dependent etching yield （phys...We have developed a plasma etching simulator to investigate the evolution of pattern profiles in SiO2 material under different plasma conditions. This model focuses on energy and angular dependent etching yield （physical sputtering in this paper）, neutral and ion angular distributions, and reflection of ions or neutrals on the surface of a photoresist or SiO2. The effect of positive charge accumulation on the surface of insulated mask or SiO2 is studied and the charge accumulation contributes to a deflection of ion trajectory. The wafer profile evolution has been simulated using a cellular-automata-like method under radio-frequency （RF） bias and direct-current （DC） bias, respectively. On the basis of the critical role of angular distribution of ions or neutrals, the wafer profile evolution has been simulated for different variances of angles. Observed microtrenching has been well reproduced in the simulator. The ratio of neutrals to ions has been considered and the result shows that because the neutrals are not accelerated by an electric field, their energy is much lower compared with ions, so they are easily reflected on the surface of SiO2, which makes the trench shallower.展开更多
A major goal of coastal engineering is to develop models for the reliable prediction of short-and longterm near shore evolution.The most successful coastal models are numerical models,which allow flexibility in the ch...A major goal of coastal engineering is to develop models for the reliable prediction of short-and longterm near shore evolution.The most successful coastal models are numerical models,which allow flexibility in the choice of initial and boundary conditions.In the present study,evolutionary algorithms(EAs)are employed for multi-objective Pareto optimum design of group method data handling(GMDH)-type neural networks that have been used for bed evolution modeling in the surf zone for reflective beaches,based on the irregular wave experiments performed at the Hydraulic Laboratory of Imperial College(London,UK).The input parameters used for such modeling are significant wave height,wave period,wave action duration,reflection coefficient,distance from shoreline and sand size.In this way,EAs with an encoding scheme are presented for evolutionary design of the generalized GMDH-type neural networks,in which the connectivity configurations in such networks are not limited to adjacent layers.Also,multi-objective EAs with a diversity preserving mechanism are used for Pareto optimization of such GMDH-type neural networks.The most important objectives of GMDH-type neural networks that are considered in this study are training error(TE),prediction error(PE),and number of neurons(N).Different pairs of these objective functions are selected for two-objective optimization processes.Therefore,optimal Pareto fronts of such models are obtained in each case,which exhibit the trade-offs between the corresponding pair of the objectives and,thus,provide different non-dominated optimal choices of GMDH-type neural network model for beach profile evolution.The results showed that the present model has been successfully used to optimally prediction of beach profile evolution on beaches with seawalls.展开更多
The prediction of the wheel wear is a fundamental problem in heavy haul railway. A numerical methodology is introduced to simulate the wheel wear evolution of heavy haul freight car. The methodology includes the spati...The prediction of the wheel wear is a fundamental problem in heavy haul railway. A numerical methodology is introduced to simulate the wheel wear evolution of heavy haul freight car. The methodology includes the spatial coupling dynamics of vehicle and track, the three-dimensional rolling contact analysis of wheel-rail, the Specht's material wear model, and the strategy for reproducing the actual operation conditions of railway. The freight vehicle is treated as a full 3D rigid multi-body model. Every component is built detailedly and various contact interactions between parts are accurately simulated, taking into account the real clearances. The wheel-rail rolling contact calculation is carried out based on Hertz's theory and Kalker's FASTSIM algorithm. The track model is built based on field measurements. The material loss due to wear is evaluated according to the Specht's model in which the wear coefficient varies with the wear intensity. In order to exactly reproduce the actual operating conditions of railway,dynamic simulations are performed separately for all possible track conditions and running velocities in each iterative step.Dimensionless weight coefficients are introduced that determine the ratios of different cases and are obtained through site survey. For the wheel profile updating, an adaptive step strategy based on the wear depth is introduced, which can effectively improve the reliability and stability of numerical calculation. At last, the wear evolution laws are studied by the numerical model for different wheels of heavy haul freight vehicle running in curves. The results show that the wear of the front wheelset is more serious than that of the rear wheelset for one bogie, and the difference is more obvious for the outer wheels. The wear of the outer wheels is severer than that of the inner wheels. The wear of outer wheels mainly distributes near the flange and the root; while the wear of inner wheels mainly distributes around the nominal rolling circle. For the outer wheel of front wheelset of each bogie, the development of wear is gradually concentrated on the flange and the developing speed increases continually with the increase of traveled distance.展开更多
Microgrooves with diverse cross-sections are required in various fields but remain a significant challenge in precision machining,especially for hard-to-machine materials.Patterned laser ablation offers an avenue for ...Microgrooves with diverse cross-sections are required in various fields but remain a significant challenge in precision machining,especially for hard-to-machine materials.Patterned laser ablation offers an avenue for fabricating microgrooves on any material with notably enhanced shape diversity.However,it is hard to precisely control the grooves'cross-sectional profiles due to the complex ablation process,including the diffraction-induced energy distribution variations away from the focal plane and the inconsistent polarization-related energy absorption.These factors complicate the relationship between beam spot shape and ablated groove shape,making it challenging to design appropriate spot shapes for specific groove requirements.Here,we propose an adaptive beam-shaping method for laser spot design to improve microgrooves'shape accuracy.Combining laser diffraction and polarization effects,a profile evolution model of the laser ablation is established to accurately predict groove shapes,guiding the iterative beam-shaping procedure.The beam spot shape is iteratively fine-tuned until the deviation between the simulated and the target grooves'profile meets the accuracy requirements.The grooves'profile deviations are significantly reduced,with the final profile's root mean square error decreased to less than 0.5μm when processing microgrooves with a width of 10μm.Various microgrooves with precise cross-sections,including triangles,trapezoids,and functionally contoured micro structures,are achieved by patterned laser direct writing assisted with the adaptive beam-shaping method.This method paves the way for laser ablation of microgrooves with high shape accuracy for traditional hard-to-machine materials.展开更多
The geomorphic minimum energy dissipation principle is important in the development of gully evolutionary theory.The impact of debris flows on channels during movement also adheres to this theory.A minimum energy diss...The geomorphic minimum energy dissipation principle is important in the development of gully evolutionary theory.The impact of debris flows on channels during movement also adheres to this theory.A minimum energy dissipation model for debris flows has been obtained from previous studies,which is derived from the flow rules of runoff along a channel under rainfall or ice-snow meltwater conditions.However,the lack of consideration for erosion characteristics has hindered a comprehensive understanding of the movement characteristics of debris flow.In this paper,the phenomenon of volume increase resulting from the entrainment along debris flow movement is considered in order to derive a model for the mean velocity,reflecting the minimum energy dissipation principle.The entire expression of the mean velocity model is determined through 38 typical glacial and rainstorm debris flow cases.To evaluate the reliability of the proposed model,we employed 164 monitoring data from 1995 to 2000 in the Jiangjia gully,Yunnan,China.The results show that the velocity calculated by the proposed model are highly correlated with those obtained from the monitoring data.Additionally,a comparison is made between the mean velocities calculated by the proposed model and those obtained from previous studies,highlighting the exceptional applicability of the proposed model.This study will contribute to reveal the movement laws of debris flow along the channel.展开更多
Particles and fields represent two major modeling paradigms in pure and applied science at all. In this paper a methodology and some of the results for three-dimensional (3D) simulations that include both field and pa...Particles and fields represent two major modeling paradigms in pure and applied science at all. In this paper a methodology and some of the results for three-dimensional (3D) simulations that include both field and particle abstractions are presented. Electromagnetic field calculations used here are based on the discrete differential form representation of the finite elements method, while the Monte Carlo method makes foundation of the particle part of the simulations. The first example is the simulation of the feature profile evolution during SiO2 etching enhanced by Ar + /CF4 non-equilibrium plasma based on the sparse field method for solving level set equations. Second example is devoted to the design of a spiral inflector which is one of the key devices of the axial injection system of the VINCY Cyclotron.展开更多
The study of dynamic networks in computer science has become crucial, given their ever-evolving nature within digital ecosystems. These networks serve as fundamental models for various networked systems, usually chara...The study of dynamic networks in computer science has become crucial, given their ever-evolving nature within digital ecosystems. These networks serve as fundamental models for various networked systems, usually characterized by modular structures. Understanding these structures, also known as communities, and the mechanisms driving their evolution is vital, as changes in one module can impact the entire network. Traditional static network analysis falls short of capturing the full complexity of dynamic networks, prompting a shift toward understanding the underlying mechanisms driving their evolution. Graph Evolution Rules (GERs) have emerged as a promising approach, explaining how subgraphs transform into new configurations. In this paper, we comprehensively explore GERs in dynamic networks from diverse systems with a focus on the rules characterizing the formation and evolution of their modular structures, using EvoMine for GER extraction and the Leiden algorithm for community detection. We characterize network and module evolution through GER profiles, enabling cross-system comparisons. By combining GERs and network communities, we decompose network evolution into regions to uncover insights into global and mesoscopic network evolution patterns. From a mesoscopic standpoint, the evolution patterns characterizing communities emphasize a non-homogeneous nature, with each community, or groups of them, displaying specific evolution patterns, while other networks’ communities follow more uniform evolution patterns. Additionally, closely interconnected sets of communities tend to evolve similarly. Our findings offer valuable insights into the intricate mechanisms governing the growth and development of dynamic networks and their communities, shedding light on the interplay between modular structures and evolving network dynamics.展开更多
基金supported by National Natural Science Foundation of China (Nos.11075029 and 10975030)the Important National Science and Technology Specific Project of China (No.2011ZX02403-001)
文摘We have developed a plasma etching simulator to investigate the evolution of pattern profiles in SiO2 material under different plasma conditions. This model focuses on energy and angular dependent etching yield （physical sputtering in this paper）, neutral and ion angular distributions, and reflection of ions or neutrals on the surface of a photoresist or SiO2. The effect of positive charge accumulation on the surface of insulated mask or SiO2 is studied and the charge accumulation contributes to a deflection of ion trajectory. The wafer profile evolution has been simulated using a cellular-automata-like method under radio-frequency （RF） bias and direct-current （DC） bias, respectively. On the basis of the critical role of angular distribution of ions or neutrals, the wafer profile evolution has been simulated for different variances of angles. Observed microtrenching has been well reproduced in the simulator. The ratio of neutrals to ions has been considered and the result shows that because the neutrals are not accelerated by an electric field, their energy is much lower compared with ions, so they are easily reflected on the surface of SiO2, which makes the trench shallower.
文摘A major goal of coastal engineering is to develop models for the reliable prediction of short-and longterm near shore evolution.The most successful coastal models are numerical models,which allow flexibility in the choice of initial and boundary conditions.In the present study,evolutionary algorithms(EAs)are employed for multi-objective Pareto optimum design of group method data handling(GMDH)-type neural networks that have been used for bed evolution modeling in the surf zone for reflective beaches,based on the irregular wave experiments performed at the Hydraulic Laboratory of Imperial College(London,UK).The input parameters used for such modeling are significant wave height,wave period,wave action duration,reflection coefficient,distance from shoreline and sand size.In this way,EAs with an encoding scheme are presented for evolutionary design of the generalized GMDH-type neural networks,in which the connectivity configurations in such networks are not limited to adjacent layers.Also,multi-objective EAs with a diversity preserving mechanism are used for Pareto optimization of such GMDH-type neural networks.The most important objectives of GMDH-type neural networks that are considered in this study are training error(TE),prediction error(PE),and number of neurons(N).Different pairs of these objective functions are selected for two-objective optimization processes.Therefore,optimal Pareto fronts of such models are obtained in each case,which exhibit the trade-offs between the corresponding pair of the objectives and,thus,provide different non-dominated optimal choices of GMDH-type neural network model for beach profile evolution.The results showed that the present model has been successfully used to optimally prediction of beach profile evolution on beaches with seawalls.
基金Project(U1234211)supported of the National Natural Science Foundation of ChinaProject(20120009110020)supported by the Specialized Research Fund for Ph.D. Programs of Foundation of Ministry of Education of ChinaProject(SHGF-11-32)supported the Scientific and Technological Innovation Project of China Shenhua Energy Company Limited
文摘The prediction of the wheel wear is a fundamental problem in heavy haul railway. A numerical methodology is introduced to simulate the wheel wear evolution of heavy haul freight car. The methodology includes the spatial coupling dynamics of vehicle and track, the three-dimensional rolling contact analysis of wheel-rail, the Specht's material wear model, and the strategy for reproducing the actual operation conditions of railway. The freight vehicle is treated as a full 3D rigid multi-body model. Every component is built detailedly and various contact interactions between parts are accurately simulated, taking into account the real clearances. The wheel-rail rolling contact calculation is carried out based on Hertz's theory and Kalker's FASTSIM algorithm. The track model is built based on field measurements. The material loss due to wear is evaluated according to the Specht's model in which the wear coefficient varies with the wear intensity. In order to exactly reproduce the actual operating conditions of railway,dynamic simulations are performed separately for all possible track conditions and running velocities in each iterative step.Dimensionless weight coefficients are introduced that determine the ratios of different cases and are obtained through site survey. For the wheel profile updating, an adaptive step strategy based on the wear depth is introduced, which can effectively improve the reliability and stability of numerical calculation. At last, the wear evolution laws are studied by the numerical model for different wheels of heavy haul freight vehicle running in curves. The results show that the wear of the front wheelset is more serious than that of the rear wheelset for one bogie, and the difference is more obvious for the outer wheels. The wear of the outer wheels is severer than that of the inner wheels. The wear of outer wheels mainly distributes near the flange and the root; while the wear of inner wheels mainly distributes around the nominal rolling circle. For the outer wheel of front wheelset of each bogie, the development of wear is gradually concentrated on the flange and the developing speed increases continually with the increase of traveled distance.
基金financially supported by the National Natural Science Foundation of China(Grant No.52375438)the Guangdong Talent Project(Grant No.2023TQ07Z453)+1 种基金the Shenzhen Science and Technology Programs(Grant Nos.JCYJ20220818100408019 and JSGG20220831101401003)Jiangyin-SUSTech Innovation Fund。
文摘Microgrooves with diverse cross-sections are required in various fields but remain a significant challenge in precision machining,especially for hard-to-machine materials.Patterned laser ablation offers an avenue for fabricating microgrooves on any material with notably enhanced shape diversity.However,it is hard to precisely control the grooves'cross-sectional profiles due to the complex ablation process,including the diffraction-induced energy distribution variations away from the focal plane and the inconsistent polarization-related energy absorption.These factors complicate the relationship between beam spot shape and ablated groove shape,making it challenging to design appropriate spot shapes for specific groove requirements.Here,we propose an adaptive beam-shaping method for laser spot design to improve microgrooves'shape accuracy.Combining laser diffraction and polarization effects,a profile evolution model of the laser ablation is established to accurately predict groove shapes,guiding the iterative beam-shaping procedure.The beam spot shape is iteratively fine-tuned until the deviation between the simulated and the target grooves'profile meets the accuracy requirements.The grooves'profile deviations are significantly reduced,with the final profile's root mean square error decreased to less than 0.5μm when processing microgrooves with a width of 10μm.Various microgrooves with precise cross-sections,including triangles,trapezoids,and functionally contoured micro structures,are achieved by patterned laser direct writing assisted with the adaptive beam-shaping method.This method paves the way for laser ablation of microgrooves with high shape accuracy for traditional hard-to-machine materials.
基金supported by the National Natural Science Foundation of China(Grant No.41925030)the Nyingchi National Sustainable Development Experimental Zone Project(2023-SYQ-007)+1 种基金the Chinese Academy of Sciences Light of West China Programthe Science and Technology Research Program of Institute of Mountain Hazards and Environment,Chinese Academy of Sciences(Grant No.IMHE-ZDRW-02).
文摘The geomorphic minimum energy dissipation principle is important in the development of gully evolutionary theory.The impact of debris flows on channels during movement also adheres to this theory.A minimum energy dissipation model for debris flows has been obtained from previous studies,which is derived from the flow rules of runoff along a channel under rainfall or ice-snow meltwater conditions.However,the lack of consideration for erosion characteristics has hindered a comprehensive understanding of the movement characteristics of debris flow.In this paper,the phenomenon of volume increase resulting from the entrainment along debris flow movement is considered in order to derive a model for the mean velocity,reflecting the minimum energy dissipation principle.The entire expression of the mean velocity model is determined through 38 typical glacial and rainstorm debris flow cases.To evaluate the reliability of the proposed model,we employed 164 monitoring data from 1995 to 2000 in the Jiangjia gully,Yunnan,China.The results show that the velocity calculated by the proposed model are highly correlated with those obtained from the monitoring data.Additionally,a comparison is made between the mean velocities calculated by the proposed model and those obtained from previous studies,highlighting the exceptional applicability of the proposed model.This study will contribute to reveal the movement laws of debris flow along the channel.
基金supported by O171037,Ⅲ 41011 and Ⅲ45006 Projects of Ministry of Education and Science,Serbia.
文摘Particles and fields represent two major modeling paradigms in pure and applied science at all. In this paper a methodology and some of the results for three-dimensional (3D) simulations that include both field and particle abstractions are presented. Electromagnetic field calculations used here are based on the discrete differential form representation of the finite elements method, while the Monte Carlo method makes foundation of the particle part of the simulations. The first example is the simulation of the feature profile evolution during SiO2 etching enhanced by Ar + /CF4 non-equilibrium plasma based on the sparse field method for solving level set equations. Second example is devoted to the design of a spiral inflector which is one of the key devices of the axial injection system of the VINCY Cyclotron.
基金supported by the Italian Ministry of University and Research(MUR)and the European Union–NextGenerationEU in the framework of the PRIN 2022 project“AWESOME:Analysis framework for WEb3 SOcial MEdia”–CUP:I53D23003680006.
文摘The study of dynamic networks in computer science has become crucial, given their ever-evolving nature within digital ecosystems. These networks serve as fundamental models for various networked systems, usually characterized by modular structures. Understanding these structures, also known as communities, and the mechanisms driving their evolution is vital, as changes in one module can impact the entire network. Traditional static network analysis falls short of capturing the full complexity of dynamic networks, prompting a shift toward understanding the underlying mechanisms driving their evolution. Graph Evolution Rules (GERs) have emerged as a promising approach, explaining how subgraphs transform into new configurations. In this paper, we comprehensively explore GERs in dynamic networks from diverse systems with a focus on the rules characterizing the formation and evolution of their modular structures, using EvoMine for GER extraction and the Leiden algorithm for community detection. We characterize network and module evolution through GER profiles, enabling cross-system comparisons. By combining GERs and network communities, we decompose network evolution into regions to uncover insights into global and mesoscopic network evolution patterns. From a mesoscopic standpoint, the evolution patterns characterizing communities emphasize a non-homogeneous nature, with each community, or groups of them, displaying specific evolution patterns, while other networks’ communities follow more uniform evolution patterns. Additionally, closely interconnected sets of communities tend to evolve similarly. Our findings offer valuable insights into the intricate mechanisms governing the growth and development of dynamic networks and their communities, shedding light on the interplay between modular structures and evolving network dynamics.
