Mine safety have top-five disasters,which including the water,gas,fire,dust and geological dynamic disaster.The coal mine water disaster is one of the important factors which restricted the development of China’s coa...Mine safety have top-five disasters,which including the water,gas,fire,dust and geological dynamic disaster.The coal mine water disaster is one of the important factors which restricted the development of China’s coal production.It is showed by statistics that 60%of mine accidents are affected by groundwater,which not only result in the production losses.展开更多
A modeling tool for simulating three-dimensional land frequency-domain controlled-source electromagnetic surveys,based on a finite-element discretization of the Helmholtz equation for the electric fields,has been deve...A modeling tool for simulating three-dimensional land frequency-domain controlled-source electromagnetic surveys,based on a finite-element discretization of the Helmholtz equation for the electric fields,has been developed.The main difference between our modeling method and those previous works is edge finite-element approach applied to solving the three-dimensional land frequency-domain electromagnetic responses generated by horizontal electric dipole source.Firstly,the edge finite-element equation is formulated through the Galerkin method based on Helmholtz equation of the electric fields.Secondly,in order to check the validity of the modeling code,the numerical results are compared with the analytical solutions for a homogeneous half-space model.Finally,other three models are simulated with three-dimensional electromagnetic responses.The results indicate that the method can be applied for solving three-dimensional electromagnetic responses.The algorithm has been demonstrated,which can be effective to modeling the complex geo-electrical structures.This efficient algorithm will help to study the distribution laws of3-D land frequency-domain controlled-source electromagnetic responses and to setup basis for research of three-dimensional inversion.展开更多
A finite element algorithm combined with divergence condition was presented for computing three-dimensional(3D) magnetotelluric forward modeling. The finite element equation of three-dimensional magnetotelluric forwar...A finite element algorithm combined with divergence condition was presented for computing three-dimensional(3D) magnetotelluric forward modeling. The finite element equation of three-dimensional magnetotelluric forward modeling was derived from Maxwell's equations using general variation principle. The divergence condition was added forcedly to the electric field boundary value problem, which made the solution correct. The system of equation of the finite element algorithm was a large sparse, banded, symmetric, ill-conditioned, non-Hermitian complex matrix equation, which can be solved using the Bi-CGSTAB method. In order to prove correctness of the three-dimensional magnetotelluric forward algorithm, the computed results and analytic results of one-dimensional geo-electrical model were compared. In addition, the three-dimensional magnetotelluric forward algorithm is given a further evaluation by computing COMMEMI model. The forward modeling results show that the algorithm is very efficient, and it has a lot of advantages, such as the high precision, the canonical process of solving problem, meeting the internal boundary condition automatically and adapting to all kinds of distribution of multi-substances.展开更多
The objective of this work is to model the microstructure of asphalt mixture and build virtual test for asphalt mixture by using Particle Flow Code in three dimensions(PFC^(3D))based on three-dimensional discrete elem...The objective of this work is to model the microstructure of asphalt mixture and build virtual test for asphalt mixture by using Particle Flow Code in three dimensions(PFC^(3D))based on three-dimensional discrete element method.A randomly generating algorithm was proposed to capture the three-dimensional irregular shape of coarse aggregate.And then,modeling algorithm and method for graded aggregates were built.Based on the combination of modeling of coarse aggregates,asphalt mastic and air voids,three-dimensional virtual sample of asphalt mixture was modeled by using PFC^(3D).Virtual tests for penetration test of aggregate and uniaxial creep test of asphalt mixture were built and conducted by using PFC^(3D).By comparison of the testing results between virtual tests and actual laboratory tests,the validity of the microstructure modeling and virtual test built in this study was verified.Additionally,compared with laboratory test,the virtual test is easier to conduct and has less variability.It is proved that microstructure modeling and virtual test based on three-dimensional discrete element method is a promising way to conduct research of asphalt mixture.展开更多
A three dimensional finite element program incorporating actually measured vertical tire-pavement contact pressure(TPCP) was utilized for modeling the mechanistic responses in asphalt concrete(AC) layers by simulating...A three dimensional finite element program incorporating actually measured vertical tire-pavement contact pressure(TPCP) was utilized for modeling the mechanistic responses in asphalt concrete(AC) layers by simulating various vehicle motions:stationary and non-stationary(i.e.in acceleration or deceleration mode).Analysis of the results indicated the following items.1) It is critical to use the vertical TPCP as the design control criteria for the tensile strains at the bottom of the AC layer when the base layer modulus is lower in magnitude(e.g.≤400 MPa);however,when the base layer modulus is higher in magnitude(e.g.≥7 000 MPa),the horizontal TPCP and the tensile strains in the X-direction at the surface of the AC layer should also be considered as part of the design response criteria.2) The definition of "overload" needs to be revised to include tire pressure over-inflation,i.e.,a vehicle should be considered to be overloaded if the wheel load exceeds the specification and/or the tire inflation pressure is higher than the specification.3) Light trucks have more structural impact on the strain responses and pavement design when the thickness of the surfacing AC layer is thinner(e.g.≤50 mm).4) The acceleration of a vehicle does not significantly impact the AC surface distresses such as rutting at the top of the upgrade slopes or intersections;however,vehicle deceleration can dramatically induce horizontal shear strains and consequently,aggravate shoving and rutting problems at the highway intersections.Evidently,these factors should be taken into account during mechanistic stress-strain modeling and structural design of asphalt pavements.展开更多
A user-defined micromechanical model was developed to investigate the fracture mechanism of asphalt concrete （AC） using the discrete element method （DEM）. A three-dimensional （3D） AC beam was built using the ＂F...A user-defined micromechanical model was developed to investigate the fracture mechanism of asphalt concrete （AC） using the discrete element method （DEM）. A three-dimensional （3D） AC beam was built using the ＂Fish＂ language provided by PFC3D and was employed to simulate the three-point bending beam test at two temperature levels： -10 ℃ and 15℃. The AC beam was modeled with the consideration of the microstructural features of asphalt mixtures. Uniaxial complex modulus test and indirect tensile strength test were conducted to obtain material input parameters for numerical modeling. The 3D predictions were validated using laboratory experimental measurements of AC beams prepared by the same mixture design. Effects of mastic stiffness, cohesive and adhesive strength on AC fracture behavior were investigated using the DEM model. The results show that the 3D DEM fracture model can accurately predict the fracture patterns of asphalt concrete. The ratio of stress at interfaces to the stress in mastics increases as the mastic stiffness decreases; however, the increase in the cohesive strength or adhesive strength shows no significant influence on the tensile strength.展开更多
Intercepting high-maneuverability hypersonic targets in near-space environments poses significant challenges due to their extreme speeds and evasive capabilities.To address these challenges,this study presents an inte...Intercepting high-maneuverability hypersonic targets in near-space environments poses significant challenges due to their extreme speeds and evasive capabilities.To address these challenges,this study presents an integrated approach that combines a Three-Dimensional Finite-Time Optimal Cooperative Guidance Law(FTOC)with an Information Fusion Anti-saturation Predefined-time Observer(IFAPO).The proposed FTOC guidance law employs a nonlinear,non-quadratic finite-time optimal control strategy designed for rapid convergence within the limited timeframes of near-space interceptions,avoiding the need for remaining flight time estimation or linear decoupling inherent in traditional methods.To complement the guidance strategy,the IFAPO leverages multi-source information fusion theory and incorporates anti-saturation mechanisms to enhance target maneuver estimation.This method ensures accurate and real-time prediction of target acceleration while maintaining predefined convergence performance,even under complex interception conditions.By integrating the FTOC guidance law and IFAPO,the approach optimizes cooperative missile positioning,improves interception success rates,and minimizes fuel consumption,addressing practical constraints in military applications.Simulation results and comparative analyses confirm the effectiveness of the integrated approach,demonstrating its capability to achieve cooperative interception of highly maneuvering targets with enhanced efficiency and reduced economic costs,aligning with realistic combat scenarios.展开更多
This work provides a method to predict the three-dimensional equivalent elastic properties of the filament-wound composites based on the multi-scale homogenization principle.In the meso-scale,a representative volume e...This work provides a method to predict the three-dimensional equivalent elastic properties of the filament-wound composites based on the multi-scale homogenization principle.In the meso-scale,a representative volume element(RVE)is defined and the bridging model is adopted to establish a theoretical predictive model for its three-dimensional equivalent elastic constants.The results obtained through this method for the previous experimental model are compared with the ones gained respectively by experiments and classical laminate theory to verify the reliability of this model.In addition,the effects of some winding parameters,such as winding angle,on the equivalent elastic behavior of the filament-wound composites are analyzed.The rules gained can provide a theoretical reference for the optimum design of filament-wound composites.展开更多
A three-dimensional path-planning approach has been developed to coordinate multiple fixed-wing unmanned aerial vehicles(UAVs)while avoiding collisions.The hierarchical path-planning architecture that divides the path...A three-dimensional path-planning approach has been developed to coordinate multiple fixed-wing unmanned aerial vehicles(UAVs)while avoiding collisions.The hierarchical path-planning architecture that divides the path-planning process into two layers is proposed by designing the velocityobstacle strategy for satisfying timeliness and effectiveness.The upper-level layer focuses on creating an efficient Dubins initial path considering the dynamic constraints of the fixed wing.Subsequently,the lower-level layer detects potential collisions and adjusts its flight paths to avoid collisions by using the threedimensional velocity obstacle method,which describes the maneuvering space of collision avoidance as the intersection space of half space.To further handle the dynamic and collisionavoidance constraints,a priority mechanism is designed to ensure that the adjusted path is still feasible for fixed-wing UAVs.Simulation experiments demonstrate the effectiveness of the proposed method.展开更多
In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of t...In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of the three-dimensional attack area model,restrict their practical applications.To address these issues,an improved backtracking algorithm is proposed to improve calculation efficiency.A significant reduction in solution time and maintenance of accuracy in the three-dimensional attack area are achieved by using the proposed algorithm.Furthermore,the age-layered population structure genetic programming(ALPS-GP)algorithm is introduced to determine an analytical polynomial model of the three-dimensional attack area,considering real-time requirements.The accuracy of the polynomial model is enhanced through the coefficient correction using an improved gradient descent algorithm.The study reveals a remarkable combination of high accuracy and efficient real-time computation,with a mean error of 91.89 m using the analytical polynomial model of the three-dimensional attack area solved in just 10^(-4)s,thus meeting the requirements of real-time combat scenarios.展开更多
Sediment deposition in the pumping station has a huge negative impact on unit operation.The three-dimensional CFD method has been used to simulate inlet structure flow in pumping station based on the Eulerian solid- l...Sediment deposition in the pumping station has a huge negative impact on unit operation.The three-dimensional CFD method has been used to simulate inlet structure flow in pumping station based on the Eulerian solid- liquid two-phase flow model. The numerical results of the preliminary scheme show that sediment deposition occurs in the forebay of pumping station because of poor flow pattern therein. In order to improve hydraulic configuration in the forebay,one modified measure reconstructs water diversion weir shape,and another measure sets a water retaining sill in the approach channel. The simulation results of the modified scheme prove that back flow in the forebay has been eliminated and the sediment deposition region has also been reduced.展开更多
Large visual language models such as CLIP have demonstrated impressive performance on various downstream tasks involving natural images,by leveraging prompt learning.However,these models often falter when applied to t...Large visual language models such as CLIP have demonstrated impressive performance on various downstream tasks involving natural images,by leveraging prompt learning.However,these models often falter when applied to tasks involving medical images.We provide an experimental insight into this phenomenon:CLIP is insensitive to the class names of medical images.For instance,replacing the class name“medulloblastoma”(a type of brain tumor)with“dog”in prompts has minimal impact on performance,a phenomenon not observed with natural images.To realign prompt learning with medical image recognition,we propose a novel prompt learning strategy,termed prompt reverse learning(PeLen).Different from the existing methods that adapt CLIP’s representations to downstream tasks,PeLen adapts task-specific representations to CLIP’s representations.Built upon the insensitivity to the class names of medical images,PeLen designates natural images and their class names to represent a specific class of medical images and class names,e.g.,allowing the image and text of a dog to correspond to the image and text of medulloblastoma.Consequently,PeLen learns prompts to align the representations between the medical images and the visual and textual representations of natural images.Our experiments demonstrate the efficacy of PeLen for medical image recognition.展开更多
Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLM...Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLMs.Therefore,in order to better assess the capability of LLMs in the agricultural domain,Agri-Eval was proposed as a benchmark for assessing the knowledge and reasoning ability of LLMs in agriculture.The assessment dataset used in Agri-Eval covered seven major disciplines in the agricultural domain:crop science,horticulture,plant protection,animal husbandry,forest science,aquaculture science,and grass science,and contained a total of 2283 questions.Among domestic general-purpose LLMs,DeepSeek R1 performed best with an accuracy rate of 75.49%.In the realm of international general-purpose LLMs,Gemini 2.0 pro exp 0205 standed out as the top performer,achieving an accuracy rate of 74.28%.As an LLMs in agriculture vertical,Shennong V2.0 outperformed all the LLMs in China,and the answer accuracy rate of agricultural knowledge exceeded that of all the existing general-purpose LLMs.The launch of Agri-Eval helped the LLM developers to comprehensively evaluate the model's capability in the field of agriculture through a variety of tasks and tests to promote the development of the LLMs in the field of agriculture.展开更多
In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asy...In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asymptotic stability of the trivial solution and the positive periodic solution.Finally,numerical simulations are presented to validate our results.Our results show that age-selective harvesting is more conducive to sustainable population survival than non-age-selective harvesting.展开更多
In this work,100 nm gate-length InP-based high electron mobility transistors(HEMTs)with a composite InGaAs/InAs/InGaAs channel are fabricated.DC measurements indicate that the InAs channel enhances transconductance bu...In this work,100 nm gate-length InP-based high electron mobility transistors(HEMTs)with a composite InGaAs/InAs/InGaAs channel are fabricated.DC measurements indicate that the InAs channel enhances transconductance but shifts the peak point toward lower V_(gs) under high V_(ds) bias.Peak separation analysis reveals the DC transconductance curve is composed of two components:the gate-controlled transconductance and the impact-ionization-induced additional transconductance.Further analysis demonstrates that the anomalous shift originates from the channel impact ionization intensity variation,which is caused by changes in the gate-drain electric field rather than the carrier density in the channel.Two additional current sources are introduced in the small-signal model to characterize the impact-ionization-induced transconductance,and the numerical variation trends of their parameters are consistent with the peak separation results,which validate the mechanism's correctness.RF measurements confirm that the DC transconductance enhancement does not effectively improve RF characteristics,which is attributed to the ionization-induced transconductance having a time constant significantly larger than that of conventional transconductance components.These findings provide a theoretical foundation for controlling the impact-ionization.展开更多
This paper presents an efficient model reduction technique for linear time-varying systems based on shifted Legendre polynomials.The approach constructs approximate low-rank decomposition factors of finite-time Gramia...This paper presents an efficient model reduction technique for linear time-varying systems based on shifted Legendre polynomials.The approach constructs approximate low-rank decomposition factors of finite-time Gramians directly from the expansion coefficients of impulse responses.Leveraging these factors,we develop two model reduction algorithms that integrate the low-rank square root method with dominant subspace projection.Our method is computationally efficient and flexible,requiring only a few matrix-vector operations and a singular value decomposition of a low-dimensional matrix,thereby avoiding the need to solve differential Lyapunov equations.Numerical experiments confirm the effectiveness of the proposed approach.展开更多
Nonlinear classification models are widely used in various fields due to their excellent performance in handling complex problems.This paper investigates the learning performance of nonlinear classification models bas...Nonlinear classification models are widely used in various fields due to their excellent performance in handling complex problems.This paper investigates the learning performance of nonlinear classification models based on Markov sampling,which builds upon the traditional framework using i.i.d.samples.Subsequently,we introduce a ueMC-NL algorithm,tailored specifically for nonlinear classification models,facilitating the production of ueMC samples from a finite dataset.Numerical investigations on the random forest and the MLP model reveal that nonlinear classification models utilizing ueMC samples yield lower misclassification rates compared to i.i.d.samples.展开更多
This paper focused on the modeling of microbial fermentation processes under varying production environments and proposed a novel approach.Considering that the dynamic characteristics of microorganisms differ across g...This paper focused on the modeling of microbial fermentation processes under varying production environments and proposed a novel approach.Considering that the dynamic characteristics of microorganisms differ across growth stages,we introduced the concept of multi-stage sensitivity analysis,in which each stage was investigated separately.The fuzzy C-means(FCM)algorithm was employed to cluster process data under nominal conditions,thereby dividing the penicillin fermentation process into distinct growth stages.Based on this division,the Latin hypercube sampling with partial rank correlation coefficient(LHS-EPRCC)method was applied to conduct sensitivity analysis for each stage,identifying an importance parameter set(IPS)that corresponds to the stage-specific growth characteristics.Re-estimation and correction of the IPS were then performed to enhance the predictive accuracy of the model.In a penicillin fermentation process deviating from nominal conditions,the proposed method was applied for model correction.Simulation results demonstrate that the corrected model aligns well with the actual process,thereby verifying the effectiveness of the proposed multistage sensitivity analysis approach in addressing complex fermentation processes and environmental uncertainties.展开更多
Utilizing finite element analysis,the ballistic protection provided by a combination of perforated D-shaped and base armor plates,collectively referred to as radiator armor,is evaluated.ANSYS Explicit Dynamics is empl...Utilizing finite element analysis,the ballistic protection provided by a combination of perforated D-shaped and base armor plates,collectively referred to as radiator armor,is evaluated.ANSYS Explicit Dynamics is employed to simulate the ballistic impact of 7.62 mm armor-piercing projectiles on Aluminum AA5083-H116 and Steel Secure 500 armors,focusing on the evaluation of material deformation and penetration resistance at varying impact points.While the D-shaped armor plate is penetrated by the armor-piercing projectiles,the combination of the perforated D-shaped and base armor plates successfully halts penetration.A numerical model based on the finite element method is developed using software such as SolidWorks and ANSYS to analyze the interaction between radiator armor and bullet.The perforated design of radiator armor is to maintain airflow for radiator function,with hole sizes smaller than the bullet core diameter to protect radiator assemblies.Predictions are made regarding the brittle fracture resulting from the projectile core′s bending due to asymmetric impact,and the resulting fragments failed to penetrate the perforated base armor plate.Craters are formed on the surface of the perforated D-shaped armor plate due to the impact of projectile fragments.The numerical model accurately predicts hole growth and projectile penetration upon impact with the armor,demonstrating effective protection of the radiator assemblies by the radiator armor.展开更多
Objective The essence of syndrome manifestation recognition in traditional Chinese medicine(TCM)is to infer the body’s latent pathogenesis state from clinical observational information,rather than to perform simple l...Objective The essence of syndrome manifestation recognition in traditional Chinese medicine(TCM)is to infer the body’s latent pathogenesis state from clinical observational information,rather than to perform simple label matching.However,previous studies have largely modeled this task as syndrome pattern classification within a fixed label space,which does not adequately reflect the cognition process of TCM syndrome differentiation centered on pathogenesis reasoning,and is also insufficient to capture the openness,semantic variability,and cross-disease reusability of syndrome manifestation expression.This study aimed to investigate whether introducing pathogenesis reasoning chain-of-thought(PR-CoT)supervision into large language models(LLMs)could improve the quality and cognitive consistency of syndrome manifestation recognition and support cross-disease transfer.Methods Syndrome manifestation recognition was formulated as a conditional generation task under the framework of clinical observational information(X)→pathogenesis structure(Z)→syndrome pattern output(Y),where Z serves as an explicit intermediate structural variable linking the clinical evidence and syndrome judgment.Within this framework,a PR-CoT-supervised dataset for syndrome manifestation recognition was constructed based on medical case records of spleen-stomach disorders.After preprocessing,information extraction,manual proofreading,and data cleaning,the dataset comprised 4800 training cases,400 development cases,and 400 test cases.Each sample was annotated with a structured PR-CoT consisting of three progressive levels:clinical information summarization,comprehensive pathogenesis analysis,and syndrome pattern output.Supervised fine-tuning was conducted on open-source LLMs,with an end-to-end model serving as the baseline.Qwen3-32B was used as the primary experimental model,and Qwen3-14B as the scale comparison model.A progressive multidimensional evaluation framework was further established,comprising a structural parsing level,a semantic similarity level,and an expert blind review level.At the structural parsing level,syndrome pattern expressions were decomposed into structural elements and evaluated using Precision,Recall,F1 score,and Jaccard similarity.At the semantic similarity level,independent LLMs scored the theoretical proximity between predicted and reference syndrome patterns.At the expert blind review level,three TCM experts independently evaluated model outputs on two dimensions:syndrome differentiation consistency and terminology standardization of syndrome patterns.In addition,zero-shot cross-disease transfer evaluation was conducted on gynecological and heart-system disorder test sets.Results At the structural parsing level,PR-CoT supervision did not lead to a stable improvement in the element-wise overlap of syndrome pattern structural components.Compared with the corresponding baselines,neither Qwen3-32B nor Qwen3-14B showed consistent advantages in structural matching metrics after the introduction of PR-CoT supervision.In contrast,at the semantic similarity level,PR-CoT supervision produced stable positive gains across different model scales and evaluation systems.The average semantic score of Qwen3-32B increased from 6.4258 in the baseline model to 6.5850 after PR-CoT supervision,and that of Qwen3-14B increased from 5.8700 to 5.9642.At the expert blind review level,the overall score of Qwen3-32B(PR-CoT)was 7.0260±0.1077,higher than 6.4163±0.2889 for its baseline.In zero-shot cross-disease testing,the PR-CoT model still showed advantages in semantic evaluation and expert evaluation on both gynecological and heart-system disorder test sets,indicating a certain degree of transferability.Conclusion The benefits of PR-CoT supervision are mainly reflected in TCM semantic consistency and clinical plausibility,rather than in improved hard matching of structural elements.These findings support understanding syndrome manifestation recognition as a process of generating and expressing latent pathogenesis structures,rather than as a classification task within a traditional fixed label space.By introducing pathogenesis reasoning as an explicit intermediate structure into the modeling process and combining it with a progressive multidimensional evaluation framework,this study provides a methodological pathway for intelligent TCM syndrome differentiation that integrates theoretical alignment,interpretability,and multi-level evaluation.展开更多
文摘Mine safety have top-five disasters,which including the water,gas,fire,dust and geological dynamic disaster.The coal mine water disaster is one of the important factors which restricted the development of China’s coal production.It is showed by statistics that 60%of mine accidents are affected by groundwater,which not only result in the production losses.
基金Projects(41674080,41674079)supported by the National Natural Science Foundation of China
文摘A modeling tool for simulating three-dimensional land frequency-domain controlled-source electromagnetic surveys,based on a finite-element discretization of the Helmholtz equation for the electric fields,has been developed.The main difference between our modeling method and those previous works is edge finite-element approach applied to solving the three-dimensional land frequency-domain electromagnetic responses generated by horizontal electric dipole source.Firstly,the edge finite-element equation is formulated through the Galerkin method based on Helmholtz equation of the electric fields.Secondly,in order to check the validity of the modeling code,the numerical results are compared with the analytical solutions for a homogeneous half-space model.Finally,other three models are simulated with three-dimensional electromagnetic responses.The results indicate that the method can be applied for solving three-dimensional electromagnetic responses.The algorithm has been demonstrated,which can be effective to modeling the complex geo-electrical structures.This efficient algorithm will help to study the distribution laws of3-D land frequency-domain controlled-source electromagnetic responses and to setup basis for research of three-dimensional inversion.
基金Project(60672042) supported by the National Natural Science Foundation of China
文摘A finite element algorithm combined with divergence condition was presented for computing three-dimensional(3D) magnetotelluric forward modeling. The finite element equation of three-dimensional magnetotelluric forward modeling was derived from Maxwell's equations using general variation principle. The divergence condition was added forcedly to the electric field boundary value problem, which made the solution correct. The system of equation of the finite element algorithm was a large sparse, banded, symmetric, ill-conditioned, non-Hermitian complex matrix equation, which can be solved using the Bi-CGSTAB method. In order to prove correctness of the three-dimensional magnetotelluric forward algorithm, the computed results and analytic results of one-dimensional geo-electrical model were compared. In addition, the three-dimensional magnetotelluric forward algorithm is given a further evaluation by computing COMMEMI model. The forward modeling results show that the algorithm is very efficient, and it has a lot of advantages, such as the high precision, the canonical process of solving problem, meeting the internal boundary condition automatically and adapting to all kinds of distribution of multi-substances.
基金Project(51378006) supported by National Natural Science Foundation of ChinaProject(141076) supported by Huoyingdong Foundation of the Ministry of Education of China+1 种基金Project(2242015R30027) supported by Excellent Young Teacher Program of Southeast University,ChinaProject(BK20140109) supported by the Natural Science Foundation of Jiangsu Province,China
文摘The objective of this work is to model the microstructure of asphalt mixture and build virtual test for asphalt mixture by using Particle Flow Code in three dimensions(PFC^(3D))based on three-dimensional discrete element method.A randomly generating algorithm was proposed to capture the three-dimensional irregular shape of coarse aggregate.And then,modeling algorithm and method for graded aggregates were built.Based on the combination of modeling of coarse aggregates,asphalt mastic and air voids,three-dimensional virtual sample of asphalt mixture was modeled by using PFC^(3D).Virtual tests for penetration test of aggregate and uniaxial creep test of asphalt mixture were built and conducted by using PFC^(3D).By comparison of the testing results between virtual tests and actual laboratory tests,the validity of the microstructure modeling and virtual test built in this study was verified.Additionally,compared with laboratory test,the virtual test is easier to conduct and has less variability.It is proved that microstructure modeling and virtual test based on three-dimensional discrete element method is a promising way to conduct research of asphalt mixture.
文摘A three dimensional finite element program incorporating actually measured vertical tire-pavement contact pressure(TPCP) was utilized for modeling the mechanistic responses in asphalt concrete(AC) layers by simulating various vehicle motions:stationary and non-stationary(i.e.in acceleration or deceleration mode).Analysis of the results indicated the following items.1) It is critical to use the vertical TPCP as the design control criteria for the tensile strains at the bottom of the AC layer when the base layer modulus is lower in magnitude(e.g.≤400 MPa);however,when the base layer modulus is higher in magnitude(e.g.≥7 000 MPa),the horizontal TPCP and the tensile strains in the X-direction at the surface of the AC layer should also be considered as part of the design response criteria.2) The definition of "overload" needs to be revised to include tire pressure over-inflation,i.e.,a vehicle should be considered to be overloaded if the wheel load exceeds the specification and/or the tire inflation pressure is higher than the specification.3) Light trucks have more structural impact on the strain responses and pavement design when the thickness of the surfacing AC layer is thinner(e.g.≤50 mm).4) The acceleration of a vehicle does not significantly impact the AC surface distresses such as rutting at the top of the upgrade slopes or intersections;however,vehicle deceleration can dramatically induce horizontal shear strains and consequently,aggravate shoving and rutting problems at the highway intersections.Evidently,these factors should be taken into account during mechanistic stress-strain modeling and structural design of asphalt pavements.
基金Project(51208178)supported by the National Natural Science Foundation of ChinaProject(2012M520991)supported by China Postdoctoral Science Foundation
文摘A user-defined micromechanical model was developed to investigate the fracture mechanism of asphalt concrete （AC） using the discrete element method （DEM）. A three-dimensional （3D） AC beam was built using the ＂Fish＂ language provided by PFC3D and was employed to simulate the three-point bending beam test at two temperature levels： -10 ℃ and 15℃. The AC beam was modeled with the consideration of the microstructural features of asphalt mixtures. Uniaxial complex modulus test and indirect tensile strength test were conducted to obtain material input parameters for numerical modeling. The 3D predictions were validated using laboratory experimental measurements of AC beams prepared by the same mixture design. Effects of mastic stiffness, cohesive and adhesive strength on AC fracture behavior were investigated using the DEM model. The results show that the 3D DEM fracture model can accurately predict the fracture patterns of asphalt concrete. The ratio of stress at interfaces to the stress in mastics increases as the mastic stiffness decreases; however, the increase in the cohesive strength or adhesive strength shows no significant influence on the tensile strength.
基金supported by the National Natural Science Foundation of China(Grant No.61773142).
文摘Intercepting high-maneuverability hypersonic targets in near-space environments poses significant challenges due to their extreme speeds and evasive capabilities.To address these challenges,this study presents an integrated approach that combines a Three-Dimensional Finite-Time Optimal Cooperative Guidance Law(FTOC)with an Information Fusion Anti-saturation Predefined-time Observer(IFAPO).The proposed FTOC guidance law employs a nonlinear,non-quadratic finite-time optimal control strategy designed for rapid convergence within the limited timeframes of near-space interceptions,avoiding the need for remaining flight time estimation or linear decoupling inherent in traditional methods.To complement the guidance strategy,the IFAPO leverages multi-source information fusion theory and incorporates anti-saturation mechanisms to enhance target maneuver estimation.This method ensures accurate and real-time prediction of target acceleration while maintaining predefined convergence performance,even under complex interception conditions.By integrating the FTOC guidance law and IFAPO,the approach optimizes cooperative missile positioning,improves interception success rates,and minimizes fuel consumption,addressing practical constraints in military applications.Simulation results and comparative analyses confirm the effectiveness of the integrated approach,demonstrating its capability to achieve cooperative interception of highly maneuvering targets with enhanced efficiency and reduced economic costs,aligning with realistic combat scenarios.
文摘This work provides a method to predict the three-dimensional equivalent elastic properties of the filament-wound composites based on the multi-scale homogenization principle.In the meso-scale,a representative volume element(RVE)is defined and the bridging model is adopted to establish a theoretical predictive model for its three-dimensional equivalent elastic constants.The results obtained through this method for the previous experimental model are compared with the ones gained respectively by experiments and classical laminate theory to verify the reliability of this model.In addition,the effects of some winding parameters,such as winding angle,on the equivalent elastic behavior of the filament-wound composites are analyzed.The rules gained can provide a theoretical reference for the optimum design of filament-wound composites.
基金supported by the National Science Fund for Distinguished Young Scholars(52425211)BIT Research Fund Program for Young Scholars(XSQD-202201005).
文摘A three-dimensional path-planning approach has been developed to coordinate multiple fixed-wing unmanned aerial vehicles(UAVs)while avoiding collisions.The hierarchical path-planning architecture that divides the path-planning process into two layers is proposed by designing the velocityobstacle strategy for satisfying timeliness and effectiveness.The upper-level layer focuses on creating an efficient Dubins initial path considering the dynamic constraints of the fixed wing.Subsequently,the lower-level layer detects potential collisions and adjusts its flight paths to avoid collisions by using the threedimensional velocity obstacle method,which describes the maneuvering space of collision avoidance as the intersection space of half space.To further handle the dynamic and collisionavoidance constraints,a priority mechanism is designed to ensure that the adjusted path is still feasible for fixed-wing UAVs.Simulation experiments demonstrate the effectiveness of the proposed method.
基金National Natural Science Foundation of China(62373187)Forward-looking Layout Special Projects(ILA220591A22)。
文摘In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of the three-dimensional attack area model,restrict their practical applications.To address these issues,an improved backtracking algorithm is proposed to improve calculation efficiency.A significant reduction in solution time and maintenance of accuracy in the three-dimensional attack area are achieved by using the proposed algorithm.Furthermore,the age-layered population structure genetic programming(ALPS-GP)algorithm is introduced to determine an analytical polynomial model of the three-dimensional attack area,considering real-time requirements.The accuracy of the polynomial model is enhanced through the coefficient correction using an improved gradient descent algorithm.The study reveals a remarkable combination of high accuracy and efficient real-time computation,with a mean error of 91.89 m using the analytical polynomial model of the three-dimensional attack area solved in just 10^(-4)s,thus meeting the requirements of real-time combat scenarios.
基金Chinese National Foundation of Natural Science-Key Projects(51339005)
文摘Sediment deposition in the pumping station has a huge negative impact on unit operation.The three-dimensional CFD method has been used to simulate inlet structure flow in pumping station based on the Eulerian solid- liquid two-phase flow model. The numerical results of the preliminary scheme show that sediment deposition occurs in the forebay of pumping station because of poor flow pattern therein. In order to improve hydraulic configuration in the forebay,one modified measure reconstructs water diversion weir shape,and another measure sets a water retaining sill in the approach channel. The simulation results of the modified scheme prove that back flow in the forebay has been eliminated and the sediment deposition region has also been reduced.
基金supported by the National Natural Science Foundation of China(62222117).
文摘Large visual language models such as CLIP have demonstrated impressive performance on various downstream tasks involving natural images,by leveraging prompt learning.However,these models often falter when applied to tasks involving medical images.We provide an experimental insight into this phenomenon:CLIP is insensitive to the class names of medical images.For instance,replacing the class name“medulloblastoma”(a type of brain tumor)with“dog”in prompts has minimal impact on performance,a phenomenon not observed with natural images.To realign prompt learning with medical image recognition,we propose a novel prompt learning strategy,termed prompt reverse learning(PeLen).Different from the existing methods that adapt CLIP’s representations to downstream tasks,PeLen adapts task-specific representations to CLIP’s representations.Built upon the insensitivity to the class names of medical images,PeLen designates natural images and their class names to represent a specific class of medical images and class names,e.g.,allowing the image and text of a dog to correspond to the image and text of medulloblastoma.Consequently,PeLen learns prompts to align the representations between the medical images and the visual and textual representations of natural images.Our experiments demonstrate the efficacy of PeLen for medical image recognition.
文摘Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLMs.Therefore,in order to better assess the capability of LLMs in the agricultural domain,Agri-Eval was proposed as a benchmark for assessing the knowledge and reasoning ability of LLMs in agriculture.The assessment dataset used in Agri-Eval covered seven major disciplines in the agricultural domain:crop science,horticulture,plant protection,animal husbandry,forest science,aquaculture science,and grass science,and contained a total of 2283 questions.Among domestic general-purpose LLMs,DeepSeek R1 performed best with an accuracy rate of 75.49%.In the realm of international general-purpose LLMs,Gemini 2.0 pro exp 0205 standed out as the top performer,achieving an accuracy rate of 74.28%.As an LLMs in agriculture vertical,Shennong V2.0 outperformed all the LLMs in China,and the answer accuracy rate of agricultural knowledge exceeded that of all the existing general-purpose LLMs.The launch of Agri-Eval helped the LLM developers to comprehensively evaluate the model's capability in the field of agriculture through a variety of tasks and tests to promote the development of the LLMs in the field of agriculture.
基金Supported by the National Natural Science Foundation of China(12261018)Universities Key Laboratory of Mathematical Modeling and Data Mining in Guizhou Province(2023013)。
文摘In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asymptotic stability of the trivial solution and the positive periodic solution.Finally,numerical simulations are presented to validate our results.Our results show that age-selective harvesting is more conducive to sustainable population survival than non-age-selective harvesting.
基金Supported by the National Natural Science Foundation of China(62474195)。
文摘In this work,100 nm gate-length InP-based high electron mobility transistors(HEMTs)with a composite InGaAs/InAs/InGaAs channel are fabricated.DC measurements indicate that the InAs channel enhances transconductance but shifts the peak point toward lower V_(gs) under high V_(ds) bias.Peak separation analysis reveals the DC transconductance curve is composed of two components:the gate-controlled transconductance and the impact-ionization-induced additional transconductance.Further analysis demonstrates that the anomalous shift originates from the channel impact ionization intensity variation,which is caused by changes in the gate-drain electric field rather than the carrier density in the channel.Two additional current sources are introduced in the small-signal model to characterize the impact-ionization-induced transconductance,and the numerical variation trends of their parameters are consistent with the peak separation results,which validate the mechanism's correctness.RF measurements confirm that the DC transconductance enhancement does not effectively improve RF characteristics,which is attributed to the ionization-induced transconductance having a time constant significantly larger than that of conventional transconductance components.These findings provide a theoretical foundation for controlling the impact-ionization.
文摘This paper presents an efficient model reduction technique for linear time-varying systems based on shifted Legendre polynomials.The approach constructs approximate low-rank decomposition factors of finite-time Gramians directly from the expansion coefficients of impulse responses.Leveraging these factors,we develop two model reduction algorithms that integrate the low-rank square root method with dominant subspace projection.Our method is computationally efficient and flexible,requiring only a few matrix-vector operations and a singular value decomposition of a low-dimensional matrix,thereby avoiding the need to solve differential Lyapunov equations.Numerical experiments confirm the effectiveness of the proposed approach.
文摘Nonlinear classification models are widely used in various fields due to their excellent performance in handling complex problems.This paper investigates the learning performance of nonlinear classification models based on Markov sampling,which builds upon the traditional framework using i.i.d.samples.Subsequently,we introduce a ueMC-NL algorithm,tailored specifically for nonlinear classification models,facilitating the production of ueMC samples from a finite dataset.Numerical investigations on the random forest and the MLP model reveal that nonlinear classification models utilizing ueMC samples yield lower misclassification rates compared to i.i.d.samples.
基金National Natural Science Foundation of China(62471204,62473175,62403215,61833007)Natural Science Foundation of Jiangsu Province(BK20241607,BE2023022-2)Research start-up fund for high-level talent(928201/186)。
文摘This paper focused on the modeling of microbial fermentation processes under varying production environments and proposed a novel approach.Considering that the dynamic characteristics of microorganisms differ across growth stages,we introduced the concept of multi-stage sensitivity analysis,in which each stage was investigated separately.The fuzzy C-means(FCM)algorithm was employed to cluster process data under nominal conditions,thereby dividing the penicillin fermentation process into distinct growth stages.Based on this division,the Latin hypercube sampling with partial rank correlation coefficient(LHS-EPRCC)method was applied to conduct sensitivity analysis for each stage,identifying an importance parameter set(IPS)that corresponds to the stage-specific growth characteristics.Re-estimation and correction of the IPS were then performed to enhance the predictive accuracy of the model.In a penicillin fermentation process deviating from nominal conditions,the proposed method was applied for model correction.Simulation results demonstrate that the corrected model aligns well with the actual process,thereby verifying the effectiveness of the proposed multistage sensitivity analysis approach in addressing complex fermentation processes and environmental uncertainties.
文摘Utilizing finite element analysis,the ballistic protection provided by a combination of perforated D-shaped and base armor plates,collectively referred to as radiator armor,is evaluated.ANSYS Explicit Dynamics is employed to simulate the ballistic impact of 7.62 mm armor-piercing projectiles on Aluminum AA5083-H116 and Steel Secure 500 armors,focusing on the evaluation of material deformation and penetration resistance at varying impact points.While the D-shaped armor plate is penetrated by the armor-piercing projectiles,the combination of the perforated D-shaped and base armor plates successfully halts penetration.A numerical model based on the finite element method is developed using software such as SolidWorks and ANSYS to analyze the interaction between radiator armor and bullet.The perforated design of radiator armor is to maintain airflow for radiator function,with hole sizes smaller than the bullet core diameter to protect radiator assemblies.Predictions are made regarding the brittle fracture resulting from the projectile core′s bending due to asymmetric impact,and the resulting fragments failed to penetrate the perforated base armor plate.Craters are formed on the surface of the perforated D-shaped armor plate due to the impact of projectile fragments.The numerical model accurately predicts hole growth and projectile penetration upon impact with the armor,demonstrating effective protection of the radiator assemblies by the radiator armor.
文摘Objective The essence of syndrome manifestation recognition in traditional Chinese medicine(TCM)is to infer the body’s latent pathogenesis state from clinical observational information,rather than to perform simple label matching.However,previous studies have largely modeled this task as syndrome pattern classification within a fixed label space,which does not adequately reflect the cognition process of TCM syndrome differentiation centered on pathogenesis reasoning,and is also insufficient to capture the openness,semantic variability,and cross-disease reusability of syndrome manifestation expression.This study aimed to investigate whether introducing pathogenesis reasoning chain-of-thought(PR-CoT)supervision into large language models(LLMs)could improve the quality and cognitive consistency of syndrome manifestation recognition and support cross-disease transfer.Methods Syndrome manifestation recognition was formulated as a conditional generation task under the framework of clinical observational information(X)→pathogenesis structure(Z)→syndrome pattern output(Y),where Z serves as an explicit intermediate structural variable linking the clinical evidence and syndrome judgment.Within this framework,a PR-CoT-supervised dataset for syndrome manifestation recognition was constructed based on medical case records of spleen-stomach disorders.After preprocessing,information extraction,manual proofreading,and data cleaning,the dataset comprised 4800 training cases,400 development cases,and 400 test cases.Each sample was annotated with a structured PR-CoT consisting of three progressive levels:clinical information summarization,comprehensive pathogenesis analysis,and syndrome pattern output.Supervised fine-tuning was conducted on open-source LLMs,with an end-to-end model serving as the baseline.Qwen3-32B was used as the primary experimental model,and Qwen3-14B as the scale comparison model.A progressive multidimensional evaluation framework was further established,comprising a structural parsing level,a semantic similarity level,and an expert blind review level.At the structural parsing level,syndrome pattern expressions were decomposed into structural elements and evaluated using Precision,Recall,F1 score,and Jaccard similarity.At the semantic similarity level,independent LLMs scored the theoretical proximity between predicted and reference syndrome patterns.At the expert blind review level,three TCM experts independently evaluated model outputs on two dimensions:syndrome differentiation consistency and terminology standardization of syndrome patterns.In addition,zero-shot cross-disease transfer evaluation was conducted on gynecological and heart-system disorder test sets.Results At the structural parsing level,PR-CoT supervision did not lead to a stable improvement in the element-wise overlap of syndrome pattern structural components.Compared with the corresponding baselines,neither Qwen3-32B nor Qwen3-14B showed consistent advantages in structural matching metrics after the introduction of PR-CoT supervision.In contrast,at the semantic similarity level,PR-CoT supervision produced stable positive gains across different model scales and evaluation systems.The average semantic score of Qwen3-32B increased from 6.4258 in the baseline model to 6.5850 after PR-CoT supervision,and that of Qwen3-14B increased from 5.8700 to 5.9642.At the expert blind review level,the overall score of Qwen3-32B(PR-CoT)was 7.0260±0.1077,higher than 6.4163±0.2889 for its baseline.In zero-shot cross-disease testing,the PR-CoT model still showed advantages in semantic evaluation and expert evaluation on both gynecological and heart-system disorder test sets,indicating a certain degree of transferability.Conclusion The benefits of PR-CoT supervision are mainly reflected in TCM semantic consistency and clinical plausibility,rather than in improved hard matching of structural elements.These findings support understanding syndrome manifestation recognition as a process of generating and expressing latent pathogenesis structures,rather than as a classification task within a traditional fixed label space.By introducing pathogenesis reasoning as an explicit intermediate structure into the modeling process and combining it with a progressive multidimensional evaluation framework,this study provides a methodological pathway for intelligent TCM syndrome differentiation that integrates theoretical alignment,interpretability,and multi-level evaluation.
