Given the growing number of vehicle accidents caused by unintended acceleration and braking failure,verifying Sudden Unintended Acceleration(SUA)incidents has become a persistent challenge.A central issue of debate is...Given the growing number of vehicle accidents caused by unintended acceleration and braking failure,verifying Sudden Unintended Acceleration(SUA)incidents has become a persistent challenge.A central issue of debate is whether such events stem frommechanical malfunctions or driver pedalmisapplications.However,existing verification procedures implemented by vehiclemanufacturers often involve closed tests after vehicle recalls;thus raising ongoing concerns about reliability and transparency.Consequently,there is a growing need for a user-driven framework that enables independent data acquisition and verification.Although previous studies have addressed SUA detection using deep learning,few have explored howclass granularity optimization affects power efficiency and inference performance in real-time Edge AI systems.To address this problem,this work presents a cloud-assisted artificial intelligence(AI)solution for the reliable verification of SUA occurrences.The proposed system integrates multimodal sensor streams including camera-based foot images,On-Board Diagnostics II(OBD-II)signals,and six-axismeasurements to determine whether the brake pedal was actually engaged at themoment of a suspected SUA.Beyond image acquisition,convolutional neural network(CNN)models perform real-time inference to classify the driver’s pedal operation states with the resulting outputs transmitted and archived in the cloud.A dedicated dataset of brake and accelerator pedal images was collected from 15 vehicles produced by 6 domestic and international manufacturers.Using this dataset,transfer learning techniques were applied to compare and analyze model performance and generalization as the CNN class granularity varied from coarse to fine levels.Furthermore,classification performance was evaluated in terms of latency and power efficiency under different class configurations.The experimental results demonstrated that the proposed solution identified the driver’s pedal behavior accurately and promptly,with the two-class model achieving the highest F1-score and accuracy among all granularity settings.展开更多
Granular materials exhibit complex macroscopic mechanical behaviors closely related to their microscalemicrostructural features.Traditional macroscopic phenomenological elasto-plastic models,however,usually have compl...Granular materials exhibit complex macroscopic mechanical behaviors closely related to their microscalemicrostructural features.Traditional macroscopic phenomenological elasto-plastic models,however,usually have complex formulations and lack explicit relations to these microstructural features.To avoid these limitations,this study proposes a micromechanics-based softening hyperelastic model for granular materials,integrating softening hyperelasticity withmicrostructural insights to capture strain softening,critical state,and strain localization behaviors.The model has two key advantages:(1)a clear conceptualization,straightforward formulation,and ease of numerical implementation(via Abaqus UMAT subroutine in this study);(2)explicit incorporation of micro-scale features(e.g.,contact stiffness,particle size,porosity)to reveal their influences on macroscopic responses.An isotropic directional distribution density of contacts and three specific microstructures are considered,and their softening hyperelastic constitutive modulus tensors are explicitly derived.By introducing a softening factor and critical failure energy density,the model can describe geomaterial behaviors,simulating residual strength,X-shaped shear bands,and strain localization evolution.Numerical validations in comparison with themacro-scale hyperelastic model,Abaqus Drucker-Prager model,and the experiment confirm its accuracy.Parametric studies reveal critical dependencies:a normal to tangential contact stiffness ratio of 2-8(depending on stiffness magnitude),an internal length of 2-4 mm to ensure shear band formation,and a critical failure energy density(≤10 kJ/m^(3))to trigger strain softening and localization.Influences of the specific microstructures on strain localization and softening are investigated.The model also shows mesh independence due to the introduction of an internal length.The model’s applicability is further demonstrated by slope stability analysis,capturing slip surface evolution,and load-displacement characteristics.This study develops a robust microstructure-aware hyperelastic framework to describe the mechanical behaviors of granular materials,providing multiscale insights for geotechnical engineering applications.展开更多
Granular flow,such as hopper discharge and debris flows,involves complex multi-scale,multi-phase,and multi-physics coupling,posing significant challenges for numerical simulation.Over the past two decades,methods like...Granular flow,such as hopper discharge and debris flows,involves complex multi-scale,multi-phase,and multi-physics coupling,posing significant challenges for numerical simulation.Over the past two decades,methods like the Discrete Element Method(DEM),Smoothed Particle Hydrodynamics(SPH),and Depth-Averaging Method(DAM),have been developed to address these problems.However,their applicability across different scales remains unclear due to differences in physical assumptions and numerical algorithms.Therefore,a comprehensive evaluation is critically needed.This study selects three typical methods(DEM,SPH,and DAM)to examine their convergence behavior,boundary condition implementation,and limitations in physical and numerical modeling.We numerically studied three extreme deformation flow cases with the three chosen methods.These cases include granular column collapse at the particle scale,flow-structure interaction at the laboratory scale,and reconstruction of the 2015 Shenzhen Guangming landslide at the field scale.By comparing the granular flow dynamics,deposition morphology,and structure interactions,and also the simulation accuracy and computational efficiency,we show the applicability of the three models across different scales.Further,we provide practical guidance for model selection in large-deformation flow problems in a granular system of different scales.展开更多
With the development of carbon electricity,achieving a low-carbon economy has become a prevailing and inevitable trend.Improving low-carbon expansion generation planning is critical for carbon emission mitigation and ...With the development of carbon electricity,achieving a low-carbon economy has become a prevailing and inevitable trend.Improving low-carbon expansion generation planning is critical for carbon emission mitigation and a lowcarbon economy.In this paper,a two-layer low-carbon expansion generation planning approach considering the uncertainty of renewable energy at multiple time scales is proposed.First,renewable energy sequences considering the uncertainty in multiple time scales are generated based on the Copula function and the probability distribution of renewable energy.Second,a two-layer generation planning model considering carbon trading and carbon capture technology is established.Specifically,the upper layer model optimizes the investment decision considering the uncertainty at a monthly scale,and the lower layer one optimizes the scheduling considering the peak shaving at an hourly scale and the flexibility at a 15-minute scale.Finally,the results of different influence factors on low-carbon generation expansion planning are compared in a provincial power grid,which demonstrate the effectiveness of the proposed model.展开更多
In order to investigate the influence of processing parameters on the granularity distribution of superalloy powders during the atomization of plasma rotating electrode processing (PREP), in this paper FGH95 superallo...In order to investigate the influence of processing parameters on the granularity distribution of superalloy powders during the atomization of plasma rotating electrode processing (PREP), in this paper FGH95 superalloy powders is prepared under different processing conditions by PREP and the influence of PREP processing parameters on the granularity distribution of FGH95 superalloy powders is discussed based on fractal geometry theory. The results show that with the increase of rotating velocity of the self-consuming electrode, the fractal dimension of the granularity distribution increases linearly, which results in the increase of the proportion of smaller powders. The change of interval between plasma gun and the self-consuming electrode has a little effect on the granularity distribution, also the fractal dimension of the granularity distribution changed a little correspondingly.展开更多
Bio-inspired computer modelling brings solutions fromthe living phenomena or biological systems to engineering domains.To overcome the obstruction problem of large-scale wind power consumption in Northwest China,this ...Bio-inspired computer modelling brings solutions fromthe living phenomena or biological systems to engineering domains.To overcome the obstruction problem of large-scale wind power consumption in Northwest China,this paper constructs a bio-inspired computer model.It is an optimal wind power consumption dispatching model of multi-time scale demand response that takes into account the involved high-energy load.First,the principle of wind power obstruction with the involvement of a high-energy load is examined in this work.In this step,highenergy load model with different regulation characteristics is established.Then,considering the multi-time scale characteristics of high-energy load and other demand-side resources response speed,a multi-time scale model of coordination optimization is built.An improved bio-inspired model incorporating particle swarm optimization is applied to minimize system operation and wind curtailment costs,as well as to find the most optimal energy configurationwithin the system.Lastly,we take an example of regional power grid in Gansu Province for simulation analysis.Results demonstrate that the suggested scheduling strategy can significantly enhance the wind power consumption level and minimize the system’s operational cost.展开更多
Person re-identification(Re-ID)has achieved great progress in recent years.However,person Re-ID methods are still suffering from body part missing and occlusion problems,which makes the learned representations less re...Person re-identification(Re-ID)has achieved great progress in recent years.However,person Re-ID methods are still suffering from body part missing and occlusion problems,which makes the learned representations less reliable.In this paper,we pro⁃pose a robust coarse granularity part-level network(CGPN)for person Re-ID,which ex⁃tracts robust regional features and integrates supervised global features for pedestrian im⁃ages.CGPN gains two-fold benefit toward higher accuracy for person Re-ID.On one hand,CGPN learns to extract effective regional features for pedestrian images.On the other hand,compared with extracting global features directly by backbone network,CGPN learns to extract more accurate global features with a supervision strategy.The single mod⁃el trained on three Re-ID datasets achieves state-of-the-art performances.Especially on CUHK03,the most challenging Re-ID dataset,we obtain a top result of Rank-1/mean av⁃erage precision(mAP)=87.1%/83.6%without re-ranking.展开更多
Morlet wavelet transformation is used in this paper to analyze the multi time scale characteristics of pre cipitation data series from 1957 to 2005 in Guyuan region.The results showed that(1) the annual precipitation ...Morlet wavelet transformation is used in this paper to analyze the multi time scale characteristics of pre cipitation data series from 1957 to 2005 in Guyuan region.The results showed that(1) the annual precipitation evo lution process had obvious multi time scale variation characteristics of 15 25 years,7 12 years and 3 6 years,and different time scales had different oscillation energy densities;(2) the periods at smaller time scales changed more frequently,which often nested in a biggish quasi periodic oscillations,so the concrete time domain should be ana lyzed if necessary;(3) the precipitation had three main periods(22 year,9 year and 4 year) and the 22 year period was especially outstanding,and the analysis of this main period reveals that the precipitation would be in a relative high water period until about 2012.展开更多
Precise integration methods to solve structural dynamic responses and the corresponding time integration formula are composed of two parts： the multiplication of an exponential matrix with a vector and the integratio...Precise integration methods to solve structural dynamic responses and the corresponding time integration formula are composed of two parts： the multiplication of an exponential matrix with a vector and the integration term. The second term can be solved by the series solution. Two hybrid granularity parallel algorithms are designed, that is, the exponential matrix and the first term are computed by the fine-grained parallel algorithra and the second term is computed by the coarse-grained parallel algorithm. Numerical examples show that these two hybrid granularity parallel algorithms obtain higher speedup and parallel efficiency than two existing parallel algorithms.展开更多
In this paper, some important issues of granularity are discussed mainly in information systems (ISs) based on binary relation. Firstly, the vector representation method of knowledge granules is proposed in an infor-m...In this paper, some important issues of granularity are discussed mainly in information systems (ISs) based on binary relation. Firstly, the vector representation method of knowledge granules is proposed in an infor-mation system based on binary relation to eliminate limitations of set representation method. Secondly, operators among knowledge granularity are introduced and some important properties of them are studied carefully. Thirdly, distance between two knowledge granules is established and granular space is constructed based on it. Fourthly, axiomatic definition of knowledge granularity is investigated, and one can find that some existed knowledge granularities are special cases under the definition. In addition, as an application of knowledge granular space, an example is employed to validate some results in our work.展开更多
Coal is a solid combustible mineral,and coal-bearing strata have important hydrocarbon generation potential and contribute to more than 12%of the global hydrocarbon resources.However,the deposition and hydrocarbon evo...Coal is a solid combustible mineral,and coal-bearing strata have important hydrocarbon generation potential and contribute to more than 12%of the global hydrocarbon resources.However,the deposition and hydrocarbon evolution process of ancient coal-bearing strata is characterized by multiple geological times,leading to obvious distinctions in their hydrocarbon generation potential,geological processes,and production,which affect the evaluation and exploration of hydrocarbon resources derived from coaly source rocks worldwide.This study aimed to identify the differences on oil-generated parent macerals and the production of oil generated from different coaly source rocks and through different oil generation processes.Integrating with the analysis of previous tectonic burial history and hydrocarbon generation history,high-temperature and high-pressure thermal simulation experiments,organic geochemistry,and organic petrology were performed on the Carboniferous-Permian(C-P)coaly source rocks in the Huanghua Depression,Bohai Bay Basin.The oil-generated parent macerals of coal's secondary oil generation process(SOGP)were mainly hydrogen-rich collotelinite,collodetrinite,sporinite,and cutinite,while the oil-generated parent macerals of tertiary oil generation process(TOGP)were the remaining small amount of hydrogen-rich collotelinite,sporinite,and cutinite,as well as dispersed soluble organic matter and unexhausted residual hydrocarbons.Compared with coal,the oil-generated parent macerals of coaly shale SOGP were mostly sporinite and cutinite.And part of hydrogen-poor vitrinite,lacking hydrocarbon-rich macerals,and macerals of the TOGP,in addition to some remaining cutinite and a small amount of crude oil and bitumen from SOGP contributed to the oil yield.The results indicated that the changes in oil yield had a good junction between SOGP and TOGP,both coal and coaly shale had higher SOGP aborted oil yield than TOGP starting yield,and coaly shale TOGP peak oil yield was lower than SOGP peak oil yield.There were significant differences in saturated hydrocarbon and aromatic parameters in coal and coaly shale.Coal SOGP was characterized by a lower Ts/Tm and C31-homohopane22S/(22S+22R)and a higher Pr/n C17compared to coal TOGP,while the aromatic parameter methyl dibenzothiophene ratio(MDR)exhibited coaly shale TOGP was higher than coaly shale SOGP than coaly TOGP than coaly SOGP,and coal trimethylnaphthalene ratio(TNR)was lower than coaly shale TNR.Thus,we established oil generation processes and discriminative plates.In this way,we distinguished the differences between oil generation parent maceral,oil generation time,and oil production of coaly source rocks,and therefore,we provided important support for the evaluation,prediction,and exploration of oil resources from global ancient coaly source rocks.展开更多
To solve the different time delays that exist in the control device installed on spatial structures, in this study, discrete analysis using a 2N precise algorithm was selected to solve the multi-time-delay issue for l...To solve the different time delays that exist in the control device installed on spatial structures, in this study, discrete analysis using a 2N precise algorithm was selected to solve the multi-time-delay issue for long-span structures based on the market-based control （MBC） method. The concept of interval mixed energy was introduced from computational structural mechanics and optimal control research areas, and it translates the design of the MBC multi-time-delay controller into a solution for the segment matrix. This approach transforms the serial algorithm in time to parallel computing in space, greatly improving the solving efficiency and numerical stability. The designed controller is able to consider the issue of time delay with a linear controlling force combination and is especially effective for large time-delay conditions. A numerical example of a long-span structure was selected to demonstrate the effectiveness of the presented controller, and the time delay was found to have a significant impact on the results.展开更多
Dynamic distribution model is one of the best schemes for parallel volume rendering. How- ever, in homogeneous cluster system.since the granularity is traditionally identical, all processors communicate almost simulta...Dynamic distribution model is one of the best schemes for parallel volume rendering. How- ever, in homogeneous cluster system.since the granularity is traditionally identical, all processors communicate almost simultaneously and computation load may lose balance. Due to problems above, a dynamic distribution model with prime granularity for parallel computing is presented. Granularities of each processor are relatively prime, and related theories are introduced. A high parallel performance can be achieved by minimizing network competition and using a load balancing strategy that ensures all processors finish almost simultaneously. Based on Master-Slave-Gleaner ( MSG) scheme, the parallel Splatting Algorithm for volume rendering is used to test the model on IBM Cluster 1350 system. The experimental results show that the model can bring a considerable improvement in performance, including computation efficiency, total execution time, speed, and load balancing.展开更多
This paper proposes an optimal solution to choose the number of enhancement layers in fine granularity scalability (FGS) scheme under the constraint of minimum transmission energy, in which FGS is combined with transm...This paper proposes an optimal solution to choose the number of enhancement layers in fine granularity scalability (FGS) scheme under the constraint of minimum transmission energy, in which FGS is combined with transmission energy control, so that FGS enhancement layer transmission energy is minimized while the distortion guaranteed. By changing the bit-plane level and packet loss rate, minimum transmission energy of enhancement layer is obtained, while the expected distortion is satisfied.展开更多
Rough set philosophy hinges on the granularity of data, which is used to build all its basic concepts, like approximations, dependencies, reduction etc. Genetic Algorithms provides a general frame to optimize problem ...Rough set philosophy hinges on the granularity of data, which is used to build all its basic concepts, like approximations, dependencies, reduction etc. Genetic Algorithms provides a general frame to optimize problem solution of complex system without depending on the domain of problem.It is robust to many kinds of problems.The paper combines Genetic Algorithms and rough sets theory to compute granular of knowledge through an example of information table. The combination enable us to compute granular of knowledge effectively.It is also useful for computer auto-computing and information processing.展开更多
Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a ...Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a multi-time scale optimal scheduling strategy based on model predictive control(MPC)is proposed under the consideration of load optimization.First,load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature,and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost.Second,considering inter-day to intra-day source-load prediction error,an intraday rolling optimal scheduling strategy based on MPC is proposed that dynamically corrects the day-ahead dispatch results to stabilize system power fluctuations and promote photovoltaic consumption.Finally,taking an office building on a summer work day as an example,the effectiveness of the proposed scheduling strategy is verified.The results of the example show that the strategy reduces the total operating cost of the photovoltaic energy storage building system by 17.11%,improves the carbon emission reduction by 7.99%,and the photovoltaic consumption rate reaches 98.57%,improving the system’s low-carbon and economic performance.展开更多
As the proportion of renewable energy increases, the interaction between renewable energy devices and the grid continues to enhance. Therefore, the renewable energy dynamic test in a power system has become more and m...As the proportion of renewable energy increases, the interaction between renewable energy devices and the grid continues to enhance. Therefore, the renewable energy dynamic test in a power system has become more and more important. Traditional dynamic simulation systems and digital-analog hybrid simulation systems are difficult to compromise on the economy, flexibility and accuracy. A multi-time scale test system of doubly fed induction generator based on FPGA+ CPU heterogeneous calculation is proposed in this paper. The proposed test system is based on the ADPSS simulation platform. The power circuit part of the test system is setup up using the EMT(electromagnetic transient simulation) simulation, and the control part uses the actual physical devices. In order to realize the close-loop testing for the physical devices, the power circuit must be simulated in real-time. This paper proposes a multi-time scale simulation algorithm, in which the decoupling component divides the power circuit into a large time scale system and a small time scale system in order to reduce computing effort. This paper also proposes the FPGA+CPU heterogeneous computing architecture for implementing this multitime scale simulation. In FPGA, there is a complete small time-scale EMT engine, which support the flexibly circuit modeling with any topology. Finally, the test system is connected to an DFIG controller based on Labview to verify the feasibility of the test system.展开更多
In this paper, we conduct research on the development trend and general applications of the fuzzy rough granular computing theory. Granular computing is a new concept of general information processing and computing pa...In this paper, we conduct research on the development trend and general applications of the fuzzy rough granular computing theory. Granular computing is a new concept of general information processing and computing paradigm which covers all the granularity the study of the theory, methods, techniques and the tools. In many areas are the basic ideas of granular computing, such as the interval analysis, rough set theory, clustering analysis and information retrieval, machine learning, database, etc. With the theory of domain known division of target concept and rule acquisition, in knowledge discovery, data mining and the pattern recognition is widely used. Under this basis, in this paper, we propose the fuzzy rough theory based computing paradigm that gains ideal performance.展开更多
Based on the content of radioactive elements (U, Th, K) of strata in two drill holes in the Fuzhou basin, and combined with the result of spore_pollen analysis, the relationship between radioactivity and lithology and...Based on the content of radioactive elements (U, Th, K) of strata in two drill holes in the Fuzhou basin, and combined with the result of spore_pollen analysis, the relationship between radioactivity and lithology and deposit environments is discussed and the results show that the content of radioactive substances is related to the granularity and lithology in sediment, and it is higher in argillaceous sediment (e.g. silt and clay), lower in sand sediment and in the middle in gravels between the above two kinds of sediment. The content of radioactive substances is also related to paleoclimate. A warm and humid environment is propitious to the deposition of radioactive substances, while a cool and dry climate is just the reverse.展开更多
In this study,the effects of different salinity gradients and addition of compatible solutes on anaerobic treated effluent water qualities,sludge characteristics and microbial communities were investigated.The increas...In this study,the effects of different salinity gradients and addition of compatible solutes on anaerobic treated effluent water qualities,sludge characteristics and microbial communities were investigated.The increase in salinity resulted in a decrease in particle size of the granular sludge,which was concentrated in the range of 0.5-1.0 mm.The content of EPS(extracellular polymeric substances)in the granular sludge gradually increased with increasing salinity and the addition of betaine(a typical compatible solute).Meanwhile,the microbial community structure was significantly affected by salinity,with high salinity reducing the diversity of bacteria.At higher salinity,Patescibacteria and Proteobacteria gradually became the dominant phylum,with relative abundance increasing to 13.53%and 12.16%at 20 g/L salinity.Desulfobacterota and its subordinate Desulfovibrio,which secrete EPS in large quantities,dominated significantly after betaine addition.Their relative abundance reached 13.65%and 7.86%at phylum level and genus level.The effect of these changes on the treated effluent was shown as the average chemical oxygen demand(COD)removal rate decreased from 82.10%to 79.71%,78.01%,68.51%and 64.55%when the salinity gradually increased from 2 g/L to 6,10,16 and 20 g/L.At the salinity of 20 g/L,average COD removal increased to 71.65%by the addition of 2 mmol/L betaine.The gradient elevated salinity and the exogenous addition of betaine played an important role in achieving stability of the anaerobic system in a highly saline environment,which provided a feasible strategy for anaerobic treatment of organic saline wastewater.展开更多
基金supported by Basic Science Research Program to Research Institute for Basic Sciences(RIBS)of Jeju National University through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(RS-2019-NR040080)This research was also carried out with the support of the Jeju RISE Center,funded by the Ministry of Education and Jeju Special Self-Governing Province in 2025,as part of the“Regional Innovation System&Education(RISE):Glocal University 30”initiative.
文摘Given the growing number of vehicle accidents caused by unintended acceleration and braking failure,verifying Sudden Unintended Acceleration(SUA)incidents has become a persistent challenge.A central issue of debate is whether such events stem frommechanical malfunctions or driver pedalmisapplications.However,existing verification procedures implemented by vehiclemanufacturers often involve closed tests after vehicle recalls;thus raising ongoing concerns about reliability and transparency.Consequently,there is a growing need for a user-driven framework that enables independent data acquisition and verification.Although previous studies have addressed SUA detection using deep learning,few have explored howclass granularity optimization affects power efficiency and inference performance in real-time Edge AI systems.To address this problem,this work presents a cloud-assisted artificial intelligence(AI)solution for the reliable verification of SUA occurrences.The proposed system integrates multimodal sensor streams including camera-based foot images,On-Board Diagnostics II(OBD-II)signals,and six-axismeasurements to determine whether the brake pedal was actually engaged at themoment of a suspected SUA.Beyond image acquisition,convolutional neural network(CNN)models perform real-time inference to classify the driver’s pedal operation states with the resulting outputs transmitted and archived in the cloud.A dedicated dataset of brake and accelerator pedal images was collected from 15 vehicles produced by 6 domestic and international manufacturers.Using this dataset,transfer learning techniques were applied to compare and analyze model performance and generalization as the CNN class granularity varied from coarse to fine levels.Furthermore,classification performance was evaluated in terms of latency and power efficiency under different class configurations.The experimental results demonstrated that the proposed solution identified the driver’s pedal behavior accurately and promptly,with the two-class model achieving the highest F1-score and accuracy among all granularity settings.
基金supported by the National Natural Science Foundation of China through grant numbers 12002245 and 12172263the Science and Technology Research Program of Chongqing Municipal Education Commission through grant number KJQN202300742+1 种基金the National Natural Science Foundation of ChongqingMunicipality through grant number CSTB2025NSCQ-GPX0841Chongqing Jiaotong University through grant number F1220038.
文摘Granular materials exhibit complex macroscopic mechanical behaviors closely related to their microscalemicrostructural features.Traditional macroscopic phenomenological elasto-plastic models,however,usually have complex formulations and lack explicit relations to these microstructural features.To avoid these limitations,this study proposes a micromechanics-based softening hyperelastic model for granular materials,integrating softening hyperelasticity withmicrostructural insights to capture strain softening,critical state,and strain localization behaviors.The model has two key advantages:(1)a clear conceptualization,straightforward formulation,and ease of numerical implementation(via Abaqus UMAT subroutine in this study);(2)explicit incorporation of micro-scale features(e.g.,contact stiffness,particle size,porosity)to reveal their influences on macroscopic responses.An isotropic directional distribution density of contacts and three specific microstructures are considered,and their softening hyperelastic constitutive modulus tensors are explicitly derived.By introducing a softening factor and critical failure energy density,the model can describe geomaterial behaviors,simulating residual strength,X-shaped shear bands,and strain localization evolution.Numerical validations in comparison with themacro-scale hyperelastic model,Abaqus Drucker-Prager model,and the experiment confirm its accuracy.Parametric studies reveal critical dependencies:a normal to tangential contact stiffness ratio of 2-8(depending on stiffness magnitude),an internal length of 2-4 mm to ensure shear band formation,and a critical failure energy density(≤10 kJ/m^(3))to trigger strain softening and localization.Influences of the specific microstructures on strain localization and softening are investigated.The model also shows mesh independence due to the introduction of an internal length.The model’s applicability is further demonstrated by slope stability analysis,capturing slip surface evolution,and load-displacement characteristics.This study develops a robust microstructure-aware hyperelastic framework to describe the mechanical behaviors of granular materials,providing multiscale insights for geotechnical engineering applications.
基金supported by the National Natural Science Foundation of China(Nos.12572465,12032005).
文摘Granular flow,such as hopper discharge and debris flows,involves complex multi-scale,multi-phase,and multi-physics coupling,posing significant challenges for numerical simulation.Over the past two decades,methods like the Discrete Element Method(DEM),Smoothed Particle Hydrodynamics(SPH),and Depth-Averaging Method(DAM),have been developed to address these problems.However,their applicability across different scales remains unclear due to differences in physical assumptions and numerical algorithms.Therefore,a comprehensive evaluation is critically needed.This study selects three typical methods(DEM,SPH,and DAM)to examine their convergence behavior,boundary condition implementation,and limitations in physical and numerical modeling.We numerically studied three extreme deformation flow cases with the three chosen methods.These cases include granular column collapse at the particle scale,flow-structure interaction at the laboratory scale,and reconstruction of the 2015 Shenzhen Guangming landslide at the field scale.By comparing the granular flow dynamics,deposition morphology,and structure interactions,and also the simulation accuracy and computational efficiency,we show the applicability of the three models across different scales.Further,we provide practical guidance for model selection in large-deformation flow problems in a granular system of different scales.
基金supported partly by the National Key R&D Program of China(2018YFA0702200)the Science and Technology Project of State Grid Shandong Electric Power Company(520604190002)。
文摘With the development of carbon electricity,achieving a low-carbon economy has become a prevailing and inevitable trend.Improving low-carbon expansion generation planning is critical for carbon emission mitigation and a lowcarbon economy.In this paper,a two-layer low-carbon expansion generation planning approach considering the uncertainty of renewable energy at multiple time scales is proposed.First,renewable energy sequences considering the uncertainty in multiple time scales are generated based on the Copula function and the probability distribution of renewable energy.Second,a two-layer generation planning model considering carbon trading and carbon capture technology is established.Specifically,the upper layer model optimizes the investment decision considering the uncertainty at a monthly scale,and the lower layer one optimizes the scheduling considering the peak shaving at an hourly scale and the flexibility at a 15-minute scale.Finally,the results of different influence factors on low-carbon generation expansion planning are compared in a provincial power grid,which demonstrate the effectiveness of the proposed model.
文摘In order to investigate the influence of processing parameters on the granularity distribution of superalloy powders during the atomization of plasma rotating electrode processing (PREP), in this paper FGH95 superalloy powders is prepared under different processing conditions by PREP and the influence of PREP processing parameters on the granularity distribution of FGH95 superalloy powders is discussed based on fractal geometry theory. The results show that with the increase of rotating velocity of the self-consuming electrode, the fractal dimension of the granularity distribution increases linearly, which results in the increase of the proportion of smaller powders. The change of interval between plasma gun and the self-consuming electrode has a little effect on the granularity distribution, also the fractal dimension of the granularity distribution changed a little correspondingly.
基金supported by the Program for Innovative Research Team(in Science and Technology)in University of Henan Province(No.22IRTSTHN016)the Hubei Natural Science Foundation(No.2021CFB156)the Japan Society for the Promotion of Science(JSPS)Grants-in-Aid for Scientific Research(KAKENHI)(No.JP21K17737).
文摘Bio-inspired computer modelling brings solutions fromthe living phenomena or biological systems to engineering domains.To overcome the obstruction problem of large-scale wind power consumption in Northwest China,this paper constructs a bio-inspired computer model.It is an optimal wind power consumption dispatching model of multi-time scale demand response that takes into account the involved high-energy load.First,the principle of wind power obstruction with the involvement of a high-energy load is examined in this work.In this step,highenergy load model with different regulation characteristics is established.Then,considering the multi-time scale characteristics of high-energy load and other demand-side resources response speed,a multi-time scale model of coordination optimization is built.An improved bio-inspired model incorporating particle swarm optimization is applied to minimize system operation and wind curtailment costs,as well as to find the most optimal energy configurationwithin the system.Lastly,we take an example of regional power grid in Gansu Province for simulation analysis.Results demonstrate that the suggested scheduling strategy can significantly enhance the wind power consumption level and minimize the system’s operational cost.
文摘Person re-identification(Re-ID)has achieved great progress in recent years.However,person Re-ID methods are still suffering from body part missing and occlusion problems,which makes the learned representations less reliable.In this paper,we pro⁃pose a robust coarse granularity part-level network(CGPN)for person Re-ID,which ex⁃tracts robust regional features and integrates supervised global features for pedestrian im⁃ages.CGPN gains two-fold benefit toward higher accuracy for person Re-ID.On one hand,CGPN learns to extract effective regional features for pedestrian images.On the other hand,compared with extracting global features directly by backbone network,CGPN learns to extract more accurate global features with a supervision strategy.The single mod⁃el trained on three Re-ID datasets achieves state-of-the-art performances.Especially on CUHK03,the most challenging Re-ID dataset,we obtain a top result of Rank-1/mean av⁃erage precision(mAP)=87.1%/83.6%without re-ranking.
基金National Key Project of ScientificTechnical Supporting Programs Funded by Ministry of Science & Technology of China during the 11th Five-Year Plan Period (Grant No. 2006BCA01A07-2).
文摘Morlet wavelet transformation is used in this paper to analyze the multi time scale characteristics of pre cipitation data series from 1957 to 2005 in Guyuan region.The results showed that(1) the annual precipitation evo lution process had obvious multi time scale variation characteristics of 15 25 years,7 12 years and 3 6 years,and different time scales had different oscillation energy densities;(2) the periods at smaller time scales changed more frequently,which often nested in a biggish quasi periodic oscillations,so the concrete time domain should be ana lyzed if necessary;(3) the precipitation had three main periods(22 year,9 year and 4 year) and the 22 year period was especially outstanding,and the analysis of this main period reveals that the precipitation would be in a relative high water period until about 2012.
基金the National Natural Science Foundation of China(No.60273048).
文摘Precise integration methods to solve structural dynamic responses and the corresponding time integration formula are composed of two parts： the multiplication of an exponential matrix with a vector and the integration term. The second term can be solved by the series solution. Two hybrid granularity parallel algorithms are designed, that is, the exponential matrix and the first term are computed by the fine-grained parallel algorithra and the second term is computed by the coarse-grained parallel algorithm. Numerical examples show that these two hybrid granularity parallel algorithms obtain higher speedup and parallel efficiency than two existing parallel algorithms.
文摘In this paper, some important issues of granularity are discussed mainly in information systems (ISs) based on binary relation. Firstly, the vector representation method of knowledge granules is proposed in an infor-mation system based on binary relation to eliminate limitations of set representation method. Secondly, operators among knowledge granularity are introduced and some important properties of them are studied carefully. Thirdly, distance between two knowledge granules is established and granular space is constructed based on it. Fourthly, axiomatic definition of knowledge granularity is investigated, and one can find that some existed knowledge granularities are special cases under the definition. In addition, as an application of knowledge granular space, an example is employed to validate some results in our work.
基金supported by the Certificate of National Science and Technology Major Project of the Ministry of Science and Technology of China(No.2016ZX05006007-004)the National Natural Science Foundation of China(Nos.42172145,42072130)。
文摘Coal is a solid combustible mineral,and coal-bearing strata have important hydrocarbon generation potential and contribute to more than 12%of the global hydrocarbon resources.However,the deposition and hydrocarbon evolution process of ancient coal-bearing strata is characterized by multiple geological times,leading to obvious distinctions in their hydrocarbon generation potential,geological processes,and production,which affect the evaluation and exploration of hydrocarbon resources derived from coaly source rocks worldwide.This study aimed to identify the differences on oil-generated parent macerals and the production of oil generated from different coaly source rocks and through different oil generation processes.Integrating with the analysis of previous tectonic burial history and hydrocarbon generation history,high-temperature and high-pressure thermal simulation experiments,organic geochemistry,and organic petrology were performed on the Carboniferous-Permian(C-P)coaly source rocks in the Huanghua Depression,Bohai Bay Basin.The oil-generated parent macerals of coal's secondary oil generation process(SOGP)were mainly hydrogen-rich collotelinite,collodetrinite,sporinite,and cutinite,while the oil-generated parent macerals of tertiary oil generation process(TOGP)were the remaining small amount of hydrogen-rich collotelinite,sporinite,and cutinite,as well as dispersed soluble organic matter and unexhausted residual hydrocarbons.Compared with coal,the oil-generated parent macerals of coaly shale SOGP were mostly sporinite and cutinite.And part of hydrogen-poor vitrinite,lacking hydrocarbon-rich macerals,and macerals of the TOGP,in addition to some remaining cutinite and a small amount of crude oil and bitumen from SOGP contributed to the oil yield.The results indicated that the changes in oil yield had a good junction between SOGP and TOGP,both coal and coaly shale had higher SOGP aborted oil yield than TOGP starting yield,and coaly shale TOGP peak oil yield was lower than SOGP peak oil yield.There were significant differences in saturated hydrocarbon and aromatic parameters in coal and coaly shale.Coal SOGP was characterized by a lower Ts/Tm and C31-homohopane22S/(22S+22R)and a higher Pr/n C17compared to coal TOGP,while the aromatic parameter methyl dibenzothiophene ratio(MDR)exhibited coaly shale TOGP was higher than coaly shale SOGP than coaly TOGP than coaly SOGP,and coal trimethylnaphthalene ratio(TNR)was lower than coaly shale TNR.Thus,we established oil generation processes and discriminative plates.In this way,we distinguished the differences between oil generation parent maceral,oil generation time,and oil production of coaly source rocks,and therefore,we provided important support for the evaluation,prediction,and exploration of oil resources from global ancient coaly source rocks.
基金provided by the Science Fund for Creative Research Groups of the National Natural Science Foundation of China under Grant Nos.51261120375 and 51421064
文摘To solve the different time delays that exist in the control device installed on spatial structures, in this study, discrete analysis using a 2N precise algorithm was selected to solve the multi-time-delay issue for long-span structures based on the market-based control （MBC） method. The concept of interval mixed energy was introduced from computational structural mechanics and optimal control research areas, and it translates the design of the MBC multi-time-delay controller into a solution for the segment matrix. This approach transforms the serial algorithm in time to parallel computing in space, greatly improving the solving efficiency and numerical stability. The designed controller is able to consider the issue of time delay with a linear controlling force combination and is especially effective for large time-delay conditions. A numerical example of a long-span structure was selected to demonstrate the effectiveness of the presented controller, and the time delay was found to have a significant impact on the results.
基金Supported by Natural Science Foundation of China ( No. 60373061).
文摘Dynamic distribution model is one of the best schemes for parallel volume rendering. How- ever, in homogeneous cluster system.since the granularity is traditionally identical, all processors communicate almost simultaneously and computation load may lose balance. Due to problems above, a dynamic distribution model with prime granularity for parallel computing is presented. Granularities of each processor are relatively prime, and related theories are introduced. A high parallel performance can be achieved by minimizing network competition and using a load balancing strategy that ensures all processors finish almost simultaneously. Based on Master-Slave-Gleaner ( MSG) scheme, the parallel Splatting Algorithm for volume rendering is used to test the model on IBM Cluster 1350 system. The experimental results show that the model can bring a considerable improvement in performance, including computation efficiency, total execution time, speed, and load balancing.
文摘This paper proposes an optimal solution to choose the number of enhancement layers in fine granularity scalability (FGS) scheme under the constraint of minimum transmission energy, in which FGS is combined with transmission energy control, so that FGS enhancement layer transmission energy is minimized while the distortion guaranteed. By changing the bit-plane level and packet loss rate, minimum transmission energy of enhancement layer is obtained, while the expected distortion is satisfied.
文摘Rough set philosophy hinges on the granularity of data, which is used to build all its basic concepts, like approximations, dependencies, reduction etc. Genetic Algorithms provides a general frame to optimize problem solution of complex system without depending on the domain of problem.It is robust to many kinds of problems.The paper combines Genetic Algorithms and rough sets theory to compute granular of knowledge through an example of information table. The combination enable us to compute granular of knowledge effectively.It is also useful for computer auto-computing and information processing.
文摘Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a multi-time scale optimal scheduling strategy based on model predictive control(MPC)is proposed under the consideration of load optimization.First,load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature,and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost.Second,considering inter-day to intra-day source-load prediction error,an intraday rolling optimal scheduling strategy based on MPC is proposed that dynamically corrects the day-ahead dispatch results to stabilize system power fluctuations and promote photovoltaic consumption.Finally,taking an office building on a summer work day as an example,the effectiveness of the proposed scheduling strategy is verified.The results of the example show that the strategy reduces the total operating cost of the photovoltaic energy storage building system by 17.11%,improves the carbon emission reduction by 7.99%,and the photovoltaic consumption rate reaches 98.57%,improving the system’s low-carbon and economic performance.
基金supported by the State Grid Science and Technology Project (Title: Technology Research On Large Scale EMT Real-time simulation customized platform, FX71-17-001)
文摘As the proportion of renewable energy increases, the interaction between renewable energy devices and the grid continues to enhance. Therefore, the renewable energy dynamic test in a power system has become more and more important. Traditional dynamic simulation systems and digital-analog hybrid simulation systems are difficult to compromise on the economy, flexibility and accuracy. A multi-time scale test system of doubly fed induction generator based on FPGA+ CPU heterogeneous calculation is proposed in this paper. The proposed test system is based on the ADPSS simulation platform. The power circuit part of the test system is setup up using the EMT(electromagnetic transient simulation) simulation, and the control part uses the actual physical devices. In order to realize the close-loop testing for the physical devices, the power circuit must be simulated in real-time. This paper proposes a multi-time scale simulation algorithm, in which the decoupling component divides the power circuit into a large time scale system and a small time scale system in order to reduce computing effort. This paper also proposes the FPGA+CPU heterogeneous computing architecture for implementing this multitime scale simulation. In FPGA, there is a complete small time-scale EMT engine, which support the flexibly circuit modeling with any topology. Finally, the test system is connected to an DFIG controller based on Labview to verify the feasibility of the test system.
文摘In this paper, we conduct research on the development trend and general applications of the fuzzy rough granular computing theory. Granular computing is a new concept of general information processing and computing paradigm which covers all the granularity the study of the theory, methods, techniques and the tools. In many areas are the basic ideas of granular computing, such as the interval analysis, rough set theory, clustering analysis and information retrieval, machine learning, database, etc. With the theory of domain known division of target concept and rule acquisition, in knowledge discovery, data mining and the pattern recognition is widely used. Under this basis, in this paper, we propose the fuzzy rough theory based computing paradigm that gains ideal performance.
基金This project was granted bythe National Developmentand Reform Commission.Item Number:20041138
文摘Based on the content of radioactive elements (U, Th, K) of strata in two drill holes in the Fuzhou basin, and combined with the result of spore_pollen analysis, the relationship between radioactivity and lithology and deposit environments is discussed and the results show that the content of radioactive substances is related to the granularity and lithology in sediment, and it is higher in argillaceous sediment (e.g. silt and clay), lower in sand sediment and in the middle in gravels between the above two kinds of sediment. The content of radioactive substances is also related to paleoclimate. A warm and humid environment is propitious to the deposition of radioactive substances, while a cool and dry climate is just the reverse.
基金supported by the Guangdong Special Support ProgramProject(No.2021JC060580)the Foshan Innovation Team Project(No.2130218003140).
文摘In this study,the effects of different salinity gradients and addition of compatible solutes on anaerobic treated effluent water qualities,sludge characteristics and microbial communities were investigated.The increase in salinity resulted in a decrease in particle size of the granular sludge,which was concentrated in the range of 0.5-1.0 mm.The content of EPS(extracellular polymeric substances)in the granular sludge gradually increased with increasing salinity and the addition of betaine(a typical compatible solute).Meanwhile,the microbial community structure was significantly affected by salinity,with high salinity reducing the diversity of bacteria.At higher salinity,Patescibacteria and Proteobacteria gradually became the dominant phylum,with relative abundance increasing to 13.53%and 12.16%at 20 g/L salinity.Desulfobacterota and its subordinate Desulfovibrio,which secrete EPS in large quantities,dominated significantly after betaine addition.Their relative abundance reached 13.65%and 7.86%at phylum level and genus level.The effect of these changes on the treated effluent was shown as the average chemical oxygen demand(COD)removal rate decreased from 82.10%to 79.71%,78.01%,68.51%and 64.55%when the salinity gradually increased from 2 g/L to 6,10,16 and 20 g/L.At the salinity of 20 g/L,average COD removal increased to 71.65%by the addition of 2 mmol/L betaine.The gradient elevated salinity and the exogenous addition of betaine played an important role in achieving stability of the anaerobic system in a highly saline environment,which provided a feasible strategy for anaerobic treatment of organic saline wastewater.
