Two methods based on a slight modification of the regular traffic assignmentalgorithms are proposed to directly compute turn flows instead of estimating them from link flows orobtaining them by expanding the networks....Two methods based on a slight modification of the regular traffic assignmentalgorithms are proposed to directly compute turn flows instead of estimating them from link flows orobtaining them by expanding the networks. The first one is designed on the path-turn incidencerelationship, and it is similar to the computational procedure of link flows. It applies to thetraffic assignment algorithms that can provide detailed path structures. The second utilizes thelink-turn incidence relationship and the conservation of flow on links, a law deriving from thisrelationship. It is actually an improved version of Dial's logit assignment algorithm. The proposedapproaches can avoid the shortcomings both of the estimation methods, e. g. Furness's model andFrator's model, and of the network-expanding method in precision, stability and computation scale.Finally, they are validated by numerical examples.展开更多
Discrete element method can effectively simulate the discontinuity,inhomogeneity and large deformation and failure of rock and soil.Based on the innovative matrix computing of the discrete element method,the highperfo...Discrete element method can effectively simulate the discontinuity,inhomogeneity and large deformation and failure of rock and soil.Based on the innovative matrix computing of the discrete element method,the highperformance discrete element software MatDEM may handle millions of elements in one computer,and enables the discrete element simulation at the engineering scale.It supports heat calculation,multi-field and fluidsolid coupling numerical simulations.Furthermore,the software integrates pre-processing,solver,postprocessing,and powerful secondary development,allowing recompiling new discrete element software.The basic principles of the DEM,the implement and development of the MatDEM software,and its applications are introduced in this paper.The software and sample source code are available online(http://matdem.com).展开更多
To fundamentally alleviate the excavation chamber clogging during slurry tunnel boring machine(TBM)advancing in hard rock,large-diameter short screw conveyor was adopted to slurry TBM of Qingdao Jiaozhou Bay Second Un...To fundamentally alleviate the excavation chamber clogging during slurry tunnel boring machine(TBM)advancing in hard rock,large-diameter short screw conveyor was adopted to slurry TBM of Qingdao Jiaozhou Bay Second Undersea Tunnel.To evaluate the discharging performance of short screw conveyor in different cases,the full-scale transient slurry-rock two-phase model for a short screw conveyor actively discharging rocks was established using computational fluid dynamics-discrete element method(CFD-DEM)coupling approach.In the fluid domain of coupling model,the sliding mesh technology was utilized to describe the rotations of the atmospheric composite cutterhead and the short screw conveyor.In the particle domain of coupling model,the dynamic particle factories were established to produce rock particles with the rotation of the cutterhead.And the accuracy and reliability of the CFD-DEM simulation results were validated via the field test and model test.Furthermore,a comprehensive parameter analysis was conducted to examine the effects of TBM operating parameters,the geometric design of screw conveyor and the size of rocks on the discharging performance of short screw conveyor.Accordingly,a reasonable rotational speed of screw conveyor was suggested and applied to Jiaozhou Bay Second Undersea Tunnel project.The findings in this paper could provide valuable references for addressing the excavation chamber clogging during ultra-large-diameter slurry TBM tunneling in hard rock for similar future.展开更多
For the advancement of fast-charging sodium-ion batteries(SIBs),the synthesis of cutting-edge cathode materials with superior structural stability and enhanced Na+diffusion kinetics is imperative.Multiphase layered tr...For the advancement of fast-charging sodium-ion batteries(SIBs),the synthesis of cutting-edge cathode materials with superior structural stability and enhanced Na+diffusion kinetics is imperative.Multiphase layered transition metal oxides(LTMOs),which leverage the synergistic properties of two distinct monophasic LTMOs,have garnered significant attention;however,their efficacy under fast-charging conditions remains underexplored.In this study,we developed a high-throughput computational screening framework to identify optimal dopants that maximize the electrochemical performance of LTMOs.Specifically,we evaluated the efficacy of 32 dopants based on P2/O3-type Mn/Fe-based Na_(x)Mn_(0.5)Fe_(0.5)O_(2)(NMFO)cathode material.Multiphase LTMOs satisfying criteria for thermodynamic and structural stability,minimized phase transitions,and enhanced Na^(+)diffusion were systematically screened for their suitability in fast-charging applications.The analysis identified two dopants,Ti and Zr,which met all predefined screening criteria.Furthermore,we ranked and scored dopants based on their alignment with these criteria,establishing a comprehensive dopant performance database.These findings provide a robust foundation for experimental exploration and offer detailed guidelines for tailoring dopants to optimize fast-charging SIBs.展开更多
Numerical simulation is dominant in solving partial differential equations(PDEs),but balancing fine-grained grids with low computational costs is challenging.Recently,solving PDEs with neural networks(NNs)has gained i...Numerical simulation is dominant in solving partial differential equations(PDEs),but balancing fine-grained grids with low computational costs is challenging.Recently,solving PDEs with neural networks(NNs)has gained interest,yet cost-effectiveness and high accuracy remain a challenge.This work introduces a novel paradigm for solving PDEs,called multi-scale neural computing(MSNC),considering spectral bias of NNs and local approximation properties in the finite difference method(FDM).The MSNC decomposes the solution with a NN for efficient capture of global scale and the FDM for detailed description of local scale,aiming to balance costs and accuracy.Demonstrated advantages include higher accuracy(10 times for 1D PDEs,20 times for 2D PDEs)and lower costs(4 times for 1D PDEs,16 times for 2D PDEs)than the standard FDM.The MSNC also exhibits stable convergence and rigorous boundary condition satisfaction,showcasing the potential for hybrid of NN and numerical method.展开更多
The computational methods of a typical dynamic mathematical model that can describe the differential element and the inertial element for the system simulation are researched. The stability of numerical solutions of t...The computational methods of a typical dynamic mathematical model that can describe the differential element and the inertial element for the system simulation are researched. The stability of numerical solutions of the dynamic mathematical model is researched. By means of theoretical analysis, the error formulas, the error sign criteria and the error relationship criterion of the implicit Euler method and the trapezoidal method are given, the dynamic factor affecting the computational accuracy has been found, the formula and the methods of computing the dynamic factor are given. The computational accuracy of the dynamic mathematical model like this can be improved by use of the dynamic factor.展开更多
A two-phase wedge-sliding model is developed based on the micro-cellular structure and minimum entropy theory of a stable system, and it is used to describe the ingredient distribution of a mixed fluid in a non-unifor...A two-phase wedge-sliding model is developed based on the micro-cellular structure and minimum entropy theory of a stable system, and it is used to describe the ingredient distribution of a mixed fluid in a non-uniform stress field and to analyse its phase drift phenomenon. In the model, the drift-inhibition angle and the expansion-inhibition angle are also deduced and used as evaluating indexes to describe the drifting trend of different ingredients among the mixed fluids. For solving above two indexes of the model, a new calculation method is developed and used to compute the phase distributions of multiphase fluid at peak stress and gradient area stress, respectively. As an example, the flow process of grease in a pipe is analysed by simulation method and used to verify the validity of the model.展开更多
Attempting to find a fast computing method to DHT （distinguished hyperbolic trajectory）, this study first proves that the errors of the stable DHT can be ignored in normal direction when they are computed as the tra...Attempting to find a fast computing method to DHT （distinguished hyperbolic trajectory）, this study first proves that the errors of the stable DHT can be ignored in normal direction when they are computed as the trajectories extend. This conclusion means that the stable flow with perturbation will approach to the real trajectory as it extends over time. Based on this theory and combined with the improved DHT computing method, this paper reports a new fast computing method to DHT, which magnifies the DHT computing speed without decreasing its accuracy.展开更多
Geo-engineering problems are known for their complexity and high uncertainty levels,requiring precise defini-tions,past experiences,logical reasoning,mathematical analysis,and practical insight to address them effecti...Geo-engineering problems are known for their complexity and high uncertainty levels,requiring precise defini-tions,past experiences,logical reasoning,mathematical analysis,and practical insight to address them effectively.Soft Computing(SC)methods have gained popularity in engineering disciplines such as mining and civil engineering due to computer hardware and machine learning advancements.Unlike traditional hard computing approaches,SC models use soft values and fuzzy sets to navigate uncertain environments.This study focuses on the application of SC methods to predict backbreak,a common issue in blasting operations within mining and civil projects.Backbreak,which refers to the unintended fracturing of rock beyond the desired blast perimeter,can significantly impact project timelines and costs.This study aims to explore how SC methods can be effectively employed to anticipate and mitigate the undesirable consequences of blasting operations,specifically focusing on backbreak prediction.The research explores the complexities of backbreak prediction and highlights the potential benefits of utilizing SC methods to address this challenging issue in geo-engineering projects.展开更多
Although many computing algorithms have been developed to analyze the relationship between land use pattern and driving forces (RLPDF), little has been done to assess and reduce the uncertainty of predictions. In this...Although many computing algorithms have been developed to analyze the relationship between land use pattern and driving forces (RLPDF), little has been done to assess and reduce the uncertainty of predictions. In this study, we investigated RLPDF based on 1990, 2005 and 2012 datasets at two spatial scales using eight state-of-the-art single computing algorithms and four consensus methods in Jinjing rive catchment in Hunan Province, China. At the entire catchment scale, the mean AUC values were between 0.715 (ANN) and 0.948 (RF) for the single-algorithms, and from 0.764 to 0.962 for the consensus methods. At the subcatchment scale, the mean AUC values between 0.624 (CTA) and 0.972 (RF) for the single-algorithms, and from 0.758 to 0.979 for the consensus methods. At the subcatchment scale, the mean AUC values were between 0.624 (CTA) and 0.972 (RF) for the single-algorithms, and from 0.758 to 0.979 for the consensus methods. The result suggested that among the eight single computing algorithms, RF performed the best overall for woodland and paddy field;consensus method showed higher predictive performance for woodland and paddy field models than the single computing algorithms. We compared the simulation results of the best - and worst-performing algorithms for the entire catchment in 2012, and found that approximately 72.5% of woodland and 72.4% of paddy field had probabilities of occurrence of less than 0.1, and 3.6% of woodland and 14.5% of paddy field had probabilities of occurrence of more than 0.5. In other words, the simulation errors associated with using different computing algorithms can be up to 14.5% if a probability level of 0.5 is set as the threshold. The results of this study showed that the choice of modeling approaches can greatly affect the accuracy of RLPDF prediction. The computing algorithms for specific RLPDF tasks in specific regions have to be localized and optimized.展开更多
Three-dimensional(3 D)reconstruction of icosahedral viruses has played a crucial role in the development of cryoelectron microscopy single-particle reconstruction,with many cryo-electron microscopy techniques first es...Three-dimensional(3 D)reconstruction of icosahedral viruses has played a crucial role in the development of cryoelectron microscopy single-particle reconstruction,with many cryo-electron microscopy techniques first established for structural studies of icosahedral viruses,owing to their high symmetry and large mass.This review summarizes the computational methods for icosahedral and symmetry-mismatch reconstruction of viruses,as well as the likely challenges and bottlenecks in virus reconstruction,such as symmetry mismatch reconstruction,contrast transformation function(CTF)correction,and particle distortion.展开更多
The numerous photos captured by low-price Internet of Things(IoT)sensors are frequently affected by meteorological factors,especially rainfall.It causes varying sizes of white streaks on the image,destroying the image...The numerous photos captured by low-price Internet of Things(IoT)sensors are frequently affected by meteorological factors,especially rainfall.It causes varying sizes of white streaks on the image,destroying the image texture and ruining the performance of the outdoor computer vision system.Existing methods utilise training with pairs of images,which is difficult to cover all scenes and leads to domain gaps.In addition,the network structures adopt deep learning to map rain images to rain-free images,failing to use prior knowledge effectively.To solve these problems,we introduce a single image derain model in edge computing that combines prior knowledge of rain patterns with the learning capability of the neural network.Specifically,the algorithm first uses Residue Channel Prior to filter out the rainfall textural features then it uses the Feature Fusion Module to fuse the original image with the background feature information.This results in a pre-processed image which is fed into Half Instance Net(HINet)to recover a high-quality rain-free image with a clear and accurate structure,and the model does not rely on any rainfall assumptions.Experimental results on synthetic and real-world datasets show that the average peak signal-to-noise ratio of the model decreases by 0.37 dB on the synthetic dataset and increases by 0.43 dB on the real-world dataset,demonstrating that a combined model reduces the gap between synthetic data and natural rain scenes,improves the generalization ability of the derain network,and alleviates the overfitting problem.展开更多
Soft computing techniques are becoming even more popular and particularly amenable to model the complex behaviors of most geotechnical engineering systems since they have demonstrated superior predictive capacity,comp...Soft computing techniques are becoming even more popular and particularly amenable to model the complex behaviors of most geotechnical engineering systems since they have demonstrated superior predictive capacity,compared to the traditional methods.This paper presents an overview of some soft computing techniques as well as their applications in underground excavations.A case study is adopted to compare the predictive performances of soft computing techniques including eXtreme Gradient Boosting(XGBoost),Multivariate Adaptive Regression Splines(MARS),Artificial Neural Networks(ANN),and Support Vector Machine(SVM) in estimating the maximum lateral wall deflection induced by braced excavation.This study also discusses the merits and the limitations of some soft computing techniques,compared with the conventional approaches available.展开更多
Based on reasonable assumptions that simplified the calculational model,a simple and practical method was proposed to calculate the post-construction settlement of high-speed railway bridge pile foundation by using th...Based on reasonable assumptions that simplified the calculational model,a simple and practical method was proposed to calculate the post-construction settlement of high-speed railway bridge pile foundation by using the Mesri creep model to describe the soil characteristics and the Mindlin-Geddes method considering pile diameter to calculate the vertical additional stress of pile bottom.A program named CPPS was designed for this method to calculate the post-construction settlement of a high-speed railway bridge pile foundation.The result indicates that the post-construction settlement in 100 years meets the requirements of the engineering specifications,and in the first two decades,the post-construction settlement is about 80% of its total settlement,while the settlement in the rest eighty years tends to be stable.Compared with the measured settlement after laying railway tracks,the calculational result is closed to that of the measured,and the results are conservative with a high computational accuracy.It is noted that the method can be used to calculate the post-construction settlement for the preliminary design of high-speed railway bridge pile foundation.展开更多
This paper presents a simple nonparametric regression approach to data-driven computing in elasticity. We apply the kernel regression to the material data set, and formulate a system of nonlinear equations solved to o...This paper presents a simple nonparametric regression approach to data-driven computing in elasticity. We apply the kernel regression to the material data set, and formulate a system of nonlinear equations solved to obtain a static equilibrium state of an elastic structure. Preliminary numerical experiments illustrate that, compared with existing methods, the proposed method finds a reasonable solution even if data points distribute coarsely in a given material data set.展开更多
This paper elucidates the effectiveness of combining the Poincare-Lighthill-Kuo method (PLK method, for short) and symbolic computation. Firstly, the idea and history of the PLK method are briefly introduced. Then, th...This paper elucidates the effectiveness of combining the Poincare-Lighthill-Kuo method (PLK method, for short) and symbolic computation. Firstly, the idea and history of the PLK method are briefly introduced. Then, the difficulty of intermediate expression swell, often encountered in symbolic computation, is outlined. For overcoming the difficulty, a semi-inverse algorithm was proposed by the author, with which the lengthy ports of intermediate expressions are first frozen in the form of symbols till the Fnal stage of seeking perturbation solutions. Tn discuss the applications of the above algorithm, the related work of the author and his research group on nonlinear oscillations and waves is concisely reviewed. The computer-extended perturbation solution of the Duffing equation shows that the asymptotic solution obtained with the PLK method possesses the convergence radius of 1 and thus the range of validity of the solution is considerably enlarged. The studies on internal solitary waves in stratified fluid and on the head-on collision between two solitary waves in a hyperelastic rod indicate that by means of the presented methods, very complicated manipulation, unconceivable in hand calculation, can be conducted and thus result in higher-order evolution equations and asymptotic solutions. The examples illustrate that the algorithm helps to realize the symbolic computation on micro-commputers. Finally, it is concluded that,vith the aid of symbolic computation, the vitality of the PLK method is greatly. Strengthened and at least for the solutions to conservative systems of oscillations and waves, it is a powerful tool.展开更多
Vehicular Edge Computing(VEC)is a promising technique to accommodate the computation-intensive and delaysensitive tasks through offloading the tasks to the RoadSide-Unit(RSU)equipped with edge computing servers or nei...Vehicular Edge Computing(VEC)is a promising technique to accommodate the computation-intensive and delaysensitive tasks through offloading the tasks to the RoadSide-Unit(RSU)equipped with edge computing servers or neighboring vehicles.Nevertheless,the limited computation resources of edge computing servers and the mobility of vehicles make the offloading policy design very challenging.In this context,through considering the potential transmission gains brought by the mobility of vehicles,we propose an efficient computation offloading and resource allocation scheme in VEC networks with two kinds of offloading modes,i.e.,Vehicle to Vehicle(V2V)and Vehicle to RSU(V2R).We define a new cost function for vehicular users by incorporating the vehicles’offloading delay,energy consumption,and expenses with a differentiated pricing strategy,as well as the transmission gain.An optimization problem is formulated to minimize the average cost of all the task vehicles under the latency and computation capacity constraints.A distributed iterative algorithm is proposed by decoupling the problem into two subproblems for the offloading mode selection and the resource allocation.Matching theorybased and Lagrangian-based algorithms are proposed to solve the two subproblems,respectively.Simulation results show the proposed algorithm achieves low complexity and significantly improves the system performance compared with three benchmark schemes.展开更多
The globally increasing concentrations of greenhouse gases in atmosphere after combustion of coal-or petroleum-based fuels give rise to tremendous interest in searching for porous materials to efficiently capture carb...The globally increasing concentrations of greenhouse gases in atmosphere after combustion of coal-or petroleum-based fuels give rise to tremendous interest in searching for porous materials to efficiently capture carbon dioxide(CO_2) and store methane(CH4), where the latter is a kind of clean energy source with abundant reserves and lower CO_2 emission. Hundreds of thousands of porous materials can be enrolled on the candidate list, but how to quickly identify the really promising ones, or even evolve materials(namely, rational design high-performing candidates) based on the large database of present porous materials? In this context, high-throughput computational techniques, which have emerged in the past few years as powerful tools, make the targets of fast evaluation of adsorbents and evolving materials for CO_2 capture and CH_4 storage feasible. This review provides an overview of the recent computational efforts on such related topics and discusses the further development in this field.展开更多
A PLU-SGS method based on a time-derivative preconditioning algorithm and LU-SGS method is developed in order to calculate the Navier-Stokes equations at all speeds. The equations were discretized using A USMPW scheme...A PLU-SGS method based on a time-derivative preconditioning algorithm and LU-SGS method is developed in order to calculate the Navier-Stokes equations at all speeds. The equations were discretized using A USMPW scheme in conjunction with the third-order MUSCL scheme with Van Leer limiter. The present method was applied to solve the multidimensional compressible Navier-Stokes equations in curvilinear coordinates. Characteristic boundary conditions based on the eigensystem of the preconditioned equations were employed. In order to examine the performance of present method, driven-cavity flow at various Reynolds numbers and viscous flow through a convergent-divergent nozzle at supersonic were selected to rest this method. The computed results were compared with the experimental data or the other numerical results available in literature and good agreements between them are obtained. The results show that the present method is accurate, self-adaptive and stable for a wide range of flow conditions from low speed to supersonic flows.展开更多
文摘Two methods based on a slight modification of the regular traffic assignmentalgorithms are proposed to directly compute turn flows instead of estimating them from link flows orobtaining them by expanding the networks. The first one is designed on the path-turn incidencerelationship, and it is similar to the computational procedure of link flows. It applies to thetraffic assignment algorithms that can provide detailed path structures. The second utilizes thelink-turn incidence relationship and the conservation of flow on links, a law deriving from thisrelationship. It is actually an improved version of Dial's logit assignment algorithm. The proposedapproaches can avoid the shortcomings both of the estimation methods, e. g. Furness's model andFrator's model, and of the network-expanding method in precision, stability and computation scale.Finally, they are validated by numerical examples.
基金Financial supports from the Natural Science Foundation of China(41761134089,41977218)Six Talent Peaks Project of Jiangsu Province(RJFW-003)the Fundamental Research Funds for the Central Universities(14380103)are gratefully acknowledged.
文摘Discrete element method can effectively simulate the discontinuity,inhomogeneity and large deformation and failure of rock and soil.Based on the innovative matrix computing of the discrete element method,the highperformance discrete element software MatDEM may handle millions of elements in one computer,and enables the discrete element simulation at the engineering scale.It supports heat calculation,multi-field and fluidsolid coupling numerical simulations.Furthermore,the software integrates pre-processing,solver,postprocessing,and powerful secondary development,allowing recompiling new discrete element software.The basic principles of the DEM,the implement and development of the MatDEM software,and its applications are introduced in this paper.The software and sample source code are available online(http://matdem.com).
基金supported by the Fundamental Research Funds for the Central Universities(Grant No.2023YJS053)the National Natural Science Foundation of China(Grant No.52278386).
文摘To fundamentally alleviate the excavation chamber clogging during slurry tunnel boring machine(TBM)advancing in hard rock,large-diameter short screw conveyor was adopted to slurry TBM of Qingdao Jiaozhou Bay Second Undersea Tunnel.To evaluate the discharging performance of short screw conveyor in different cases,the full-scale transient slurry-rock two-phase model for a short screw conveyor actively discharging rocks was established using computational fluid dynamics-discrete element method(CFD-DEM)coupling approach.In the fluid domain of coupling model,the sliding mesh technology was utilized to describe the rotations of the atmospheric composite cutterhead and the short screw conveyor.In the particle domain of coupling model,the dynamic particle factories were established to produce rock particles with the rotation of the cutterhead.And the accuracy and reliability of the CFD-DEM simulation results were validated via the field test and model test.Furthermore,a comprehensive parameter analysis was conducted to examine the effects of TBM operating parameters,the geometric design of screw conveyor and the size of rocks on the discharging performance of short screw conveyor.Accordingly,a reasonable rotational speed of screw conveyor was suggested and applied to Jiaozhou Bay Second Undersea Tunnel project.The findings in this paper could provide valuable references for addressing the excavation chamber clogging during ultra-large-diameter slurry TBM tunneling in hard rock for similar future.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korean government(MSIT)(No.2022R1F1A1074339)。
文摘For the advancement of fast-charging sodium-ion batteries(SIBs),the synthesis of cutting-edge cathode materials with superior structural stability and enhanced Na+diffusion kinetics is imperative.Multiphase layered transition metal oxides(LTMOs),which leverage the synergistic properties of two distinct monophasic LTMOs,have garnered significant attention;however,their efficacy under fast-charging conditions remains underexplored.In this study,we developed a high-throughput computational screening framework to identify optimal dopants that maximize the electrochemical performance of LTMOs.Specifically,we evaluated the efficacy of 32 dopants based on P2/O3-type Mn/Fe-based Na_(x)Mn_(0.5)Fe_(0.5)O_(2)(NMFO)cathode material.Multiphase LTMOs satisfying criteria for thermodynamic and structural stability,minimized phase transitions,and enhanced Na^(+)diffusion were systematically screened for their suitability in fast-charging applications.The analysis identified two dopants,Ti and Zr,which met all predefined screening criteria.Furthermore,we ranked and scored dopants based on their alignment with these criteria,establishing a comprehensive dopant performance database.These findings provide a robust foundation for experimental exploration and offer detailed guidelines for tailoring dopants to optimize fast-charging SIBs.
基金supported by the National Natural Science Foundation of China(Grant No.92152301).
文摘Numerical simulation is dominant in solving partial differential equations(PDEs),but balancing fine-grained grids with low computational costs is challenging.Recently,solving PDEs with neural networks(NNs)has gained interest,yet cost-effectiveness and high accuracy remain a challenge.This work introduces a novel paradigm for solving PDEs,called multi-scale neural computing(MSNC),considering spectral bias of NNs and local approximation properties in the finite difference method(FDM).The MSNC decomposes the solution with a NN for efficient capture of global scale and the FDM for detailed description of local scale,aiming to balance costs and accuracy.Demonstrated advantages include higher accuracy(10 times for 1D PDEs,20 times for 2D PDEs)and lower costs(4 times for 1D PDEs,16 times for 2D PDEs)than the standard FDM.The MSNC also exhibits stable convergence and rigorous boundary condition satisfaction,showcasing the potential for hybrid of NN and numerical method.
文摘The computational methods of a typical dynamic mathematical model that can describe the differential element and the inertial element for the system simulation are researched. The stability of numerical solutions of the dynamic mathematical model is researched. By means of theoretical analysis, the error formulas, the error sign criteria and the error relationship criterion of the implicit Euler method and the trapezoidal method are given, the dynamic factor affecting the computational accuracy has been found, the formula and the methods of computing the dynamic factor are given. The computational accuracy of the dynamic mathematical model like this can be improved by use of the dynamic factor.
基金Project supported by the National Natural Science Foundation of China (Grant No. 51075311)
文摘A two-phase wedge-sliding model is developed based on the micro-cellular structure and minimum entropy theory of a stable system, and it is used to describe the ingredient distribution of a mixed fluid in a non-uniform stress field and to analyse its phase drift phenomenon. In the model, the drift-inhibition angle and the expansion-inhibition angle are also deduced and used as evaluating indexes to describe the drifting trend of different ingredients among the mixed fluids. For solving above two indexes of the model, a new calculation method is developed and used to compute the phase distributions of multiphase fluid at peak stress and gradient area stress, respectively. As an example, the flow process of grease in a pipe is analysed by simulation method and used to verify the validity of the model.
基金supported by the National Natural Science Foundation of China (Grant No. 60872159)
文摘Attempting to find a fast computing method to DHT （distinguished hyperbolic trajectory）, this study first proves that the errors of the stable DHT can be ignored in normal direction when they are computed as the trajectories extend. This conclusion means that the stable flow with perturbation will approach to the real trajectory as it extends over time. Based on this theory and combined with the improved DHT computing method, this paper reports a new fast computing method to DHT, which magnifies the DHT computing speed without decreasing its accuracy.
文摘Geo-engineering problems are known for their complexity and high uncertainty levels,requiring precise defini-tions,past experiences,logical reasoning,mathematical analysis,and practical insight to address them effectively.Soft Computing(SC)methods have gained popularity in engineering disciplines such as mining and civil engineering due to computer hardware and machine learning advancements.Unlike traditional hard computing approaches,SC models use soft values and fuzzy sets to navigate uncertain environments.This study focuses on the application of SC methods to predict backbreak,a common issue in blasting operations within mining and civil projects.Backbreak,which refers to the unintended fracturing of rock beyond the desired blast perimeter,can significantly impact project timelines and costs.This study aims to explore how SC methods can be effectively employed to anticipate and mitigate the undesirable consequences of blasting operations,specifically focusing on backbreak prediction.The research explores the complexities of backbreak prediction and highlights the potential benefits of utilizing SC methods to address this challenging issue in geo-engineering projects.
文摘Although many computing algorithms have been developed to analyze the relationship between land use pattern and driving forces (RLPDF), little has been done to assess and reduce the uncertainty of predictions. In this study, we investigated RLPDF based on 1990, 2005 and 2012 datasets at two spatial scales using eight state-of-the-art single computing algorithms and four consensus methods in Jinjing rive catchment in Hunan Province, China. At the entire catchment scale, the mean AUC values were between 0.715 (ANN) and 0.948 (RF) for the single-algorithms, and from 0.764 to 0.962 for the consensus methods. At the subcatchment scale, the mean AUC values between 0.624 (CTA) and 0.972 (RF) for the single-algorithms, and from 0.758 to 0.979 for the consensus methods. At the subcatchment scale, the mean AUC values were between 0.624 (CTA) and 0.972 (RF) for the single-algorithms, and from 0.758 to 0.979 for the consensus methods. The result suggested that among the eight single computing algorithms, RF performed the best overall for woodland and paddy field;consensus method showed higher predictive performance for woodland and paddy field models than the single computing algorithms. We compared the simulation results of the best - and worst-performing algorithms for the entire catchment in 2012, and found that approximately 72.5% of woodland and 72.4% of paddy field had probabilities of occurrence of less than 0.1, and 3.6% of woodland and 14.5% of paddy field had probabilities of occurrence of more than 0.5. In other words, the simulation errors associated with using different computing algorithms can be up to 14.5% if a probability level of 0.5 is set as the threshold. The results of this study showed that the choice of modeling approaches can greatly affect the accuracy of RLPDF prediction. The computing algorithms for specific RLPDF tasks in specific regions have to be localized and optimized.
基金Project supported by the National Key R&D Program of China(Grant No.2016YFA0501100)the National Natural Science Foundation of China(Grant Nos.91530321,31570742,and 31570727)Science and Technology Planning Project of Hunan Province,China(Grant No.2017RS3033)
文摘Three-dimensional(3 D)reconstruction of icosahedral viruses has played a crucial role in the development of cryoelectron microscopy single-particle reconstruction,with many cryo-electron microscopy techniques first established for structural studies of icosahedral viruses,owing to their high symmetry and large mass.This review summarizes the computational methods for icosahedral and symmetry-mismatch reconstruction of viruses,as well as the likely challenges and bottlenecks in virus reconstruction,such as symmetry mismatch reconstruction,contrast transformation function(CTF)correction,and particle distortion.
基金supported by the National Natural Science Foundation of China under Grant no.41975183,and Grant no.41875184 and Supported by a grant from State Key Laboratory of Resources and Environmental Information System.
文摘The numerous photos captured by low-price Internet of Things(IoT)sensors are frequently affected by meteorological factors,especially rainfall.It causes varying sizes of white streaks on the image,destroying the image texture and ruining the performance of the outdoor computer vision system.Existing methods utilise training with pairs of images,which is difficult to cover all scenes and leads to domain gaps.In addition,the network structures adopt deep learning to map rain images to rain-free images,failing to use prior knowledge effectively.To solve these problems,we introduce a single image derain model in edge computing that combines prior knowledge of rain patterns with the learning capability of the neural network.Specifically,the algorithm first uses Residue Channel Prior to filter out the rainfall textural features then it uses the Feature Fusion Module to fuse the original image with the background feature information.This results in a pre-processed image which is fed into Half Instance Net(HINet)to recover a high-quality rain-free image with a clear and accurate structure,and the model does not rely on any rainfall assumptions.Experimental results on synthetic and real-world datasets show that the average peak signal-to-noise ratio of the model decreases by 0.37 dB on the synthetic dataset and increases by 0.43 dB on the real-world dataset,demonstrating that a combined model reduces the gap between synthetic data and natural rain scenes,improves the generalization ability of the derain network,and alleviates the overfitting problem.
基金supported by High-end Foreign Expert Introduction program (No.G20190022002)Chongqing Construction Science and Technology Plan Project (2019-0045)
文摘Soft computing techniques are becoming even more popular and particularly amenable to model the complex behaviors of most geotechnical engineering systems since they have demonstrated superior predictive capacity,compared to the traditional methods.This paper presents an overview of some soft computing techniques as well as their applications in underground excavations.A case study is adopted to compare the predictive performances of soft computing techniques including eXtreme Gradient Boosting(XGBoost),Multivariate Adaptive Regression Splines(MARS),Artificial Neural Networks(ANN),and Support Vector Machine(SVM) in estimating the maximum lateral wall deflection induced by braced excavation.This study also discusses the merits and the limitations of some soft computing techniques,compared with the conventional approaches available.
基金Projects(2009G008-B,2010G018-E-3) supported by Key Projects of China Railway Ministry Science and Technology Research and Development ProgramProject(CX2013B076) supported by Hunan Provincial Innovation Foundation For Postgraduate,China
文摘Based on reasonable assumptions that simplified the calculational model,a simple and practical method was proposed to calculate the post-construction settlement of high-speed railway bridge pile foundation by using the Mesri creep model to describe the soil characteristics and the Mindlin-Geddes method considering pile diameter to calculate the vertical additional stress of pile bottom.A program named CPPS was designed for this method to calculate the post-construction settlement of a high-speed railway bridge pile foundation.The result indicates that the post-construction settlement in 100 years meets the requirements of the engineering specifications,and in the first two decades,the post-construction settlement is about 80% of its total settlement,while the settlement in the rest eighty years tends to be stable.Compared with the measured settlement after laying railway tracks,the calculational result is closed to that of the measured,and the results are conservative with a high computational accuracy.It is noted that the method can be used to calculate the post-construction settlement for the preliminary design of high-speed railway bridge pile foundation.
基金supported by JSPS KAKENHI (Grants 17K06633 and 18K18898)
文摘This paper presents a simple nonparametric regression approach to data-driven computing in elasticity. We apply the kernel regression to the material data set, and formulate a system of nonlinear equations solved to obtain a static equilibrium state of an elastic structure. Preliminary numerical experiments illustrate that, compared with existing methods, the proposed method finds a reasonable solution even if data points distribute coarsely in a given material data set.
文摘This paper elucidates the effectiveness of combining the Poincare-Lighthill-Kuo method (PLK method, for short) and symbolic computation. Firstly, the idea and history of the PLK method are briefly introduced. Then, the difficulty of intermediate expression swell, often encountered in symbolic computation, is outlined. For overcoming the difficulty, a semi-inverse algorithm was proposed by the author, with which the lengthy ports of intermediate expressions are first frozen in the form of symbols till the Fnal stage of seeking perturbation solutions. Tn discuss the applications of the above algorithm, the related work of the author and his research group on nonlinear oscillations and waves is concisely reviewed. The computer-extended perturbation solution of the Duffing equation shows that the asymptotic solution obtained with the PLK method possesses the convergence radius of 1 and thus the range of validity of the solution is considerably enlarged. The studies on internal solitary waves in stratified fluid and on the head-on collision between two solitary waves in a hyperelastic rod indicate that by means of the presented methods, very complicated manipulation, unconceivable in hand calculation, can be conducted and thus result in higher-order evolution equations and asymptotic solutions. The examples illustrate that the algorithm helps to realize the symbolic computation on micro-commputers. Finally, it is concluded that,vith the aid of symbolic computation, the vitality of the PLK method is greatly. Strengthened and at least for the solutions to conservative systems of oscillations and waves, it is a powerful tool.
基金The work was supported in part by the National Natural Science Foundation of China(No.62271295,U22A2003,62201329)Shandong Provincial Natural Science Foundation(ZR2020QF002,ZR2022QF002).
文摘Vehicular Edge Computing(VEC)is a promising technique to accommodate the computation-intensive and delaysensitive tasks through offloading the tasks to the RoadSide-Unit(RSU)equipped with edge computing servers or neighboring vehicles.Nevertheless,the limited computation resources of edge computing servers and the mobility of vehicles make the offloading policy design very challenging.In this context,through considering the potential transmission gains brought by the mobility of vehicles,we propose an efficient computation offloading and resource allocation scheme in VEC networks with two kinds of offloading modes,i.e.,Vehicle to Vehicle(V2V)and Vehicle to RSU(V2R).We define a new cost function for vehicular users by incorporating the vehicles’offloading delay,energy consumption,and expenses with a differentiated pricing strategy,as well as the transmission gain.An optimization problem is formulated to minimize the average cost of all the task vehicles under the latency and computation capacity constraints.A distributed iterative algorithm is proposed by decoupling the problem into two subproblems for the offloading mode selection and the resource allocation.Matching theorybased and Lagrangian-based algorithms are proposed to solve the two subproblems,respectively.Simulation results show the proposed algorithm achieves low complexity and significantly improves the system performance compared with three benchmark schemes.
基金supported by the Natural Science Foundation of China (Nos.21706106,21536001 and 21322603)the National Key Basic Research Program of China ("973") (No.2013CB733503)+1 种基金the Natural Science Foundation of Jiangsu Normal University(16XLR011)Priority Academic Program Development of Jiangsu Higher Education Institutions
文摘The globally increasing concentrations of greenhouse gases in atmosphere after combustion of coal-or petroleum-based fuels give rise to tremendous interest in searching for porous materials to efficiently capture carbon dioxide(CO_2) and store methane(CH4), where the latter is a kind of clean energy source with abundant reserves and lower CO_2 emission. Hundreds of thousands of porous materials can be enrolled on the candidate list, but how to quickly identify the really promising ones, or even evolve materials(namely, rational design high-performing candidates) based on the large database of present porous materials? In this context, high-throughput computational techniques, which have emerged in the past few years as powerful tools, make the targets of fast evaluation of adsorbents and evolving materials for CO_2 capture and CH_4 storage feasible. This review provides an overview of the recent computational efforts on such related topics and discusses the further development in this field.
文摘A PLU-SGS method based on a time-derivative preconditioning algorithm and LU-SGS method is developed in order to calculate the Navier-Stokes equations at all speeds. The equations were discretized using A USMPW scheme in conjunction with the third-order MUSCL scheme with Van Leer limiter. The present method was applied to solve the multidimensional compressible Navier-Stokes equations in curvilinear coordinates. Characteristic boundary conditions based on the eigensystem of the preconditioned equations were employed. In order to examine the performance of present method, driven-cavity flow at various Reynolds numbers and viscous flow through a convergent-divergent nozzle at supersonic were selected to rest this method. The computed results were compared with the experimental data or the other numerical results available in literature and good agreements between them are obtained. The results show that the present method is accurate, self-adaptive and stable for a wide range of flow conditions from low speed to supersonic flows.
