In-space cable-driven manipulators exhibit several advantages,such as a large range of motion,high dexterity,and lightweight structure.However,kinematic and dynamic analysis play an essential role in designing a cable...In-space cable-driven manipulators exhibit several advantages,such as a large range of motion,high dexterity,and lightweight structure.However,kinematic and dynamic analysis play an essential role in designing a cable-driven manipulator.In this paper,the kinematic analysis of a type of cable-driven manipulator is performed,and a motion planning scheme is conducted to actuate this manipulator.Moreover,a flexible multi-body dynamic model of a cable-driven manipulator considering the frictional contact between the cables and pulleys is established.To describe properties such as flexibility,vibration,and variable length of the cable,this paper utilizes reducedorder beam elements of the Absolute Nodal Coordinates Formulation(ANCF)in Arbitrary Lagrangian Eulerian(ALE)framework.Additionally,a virtual element is introduced to model the contact segment in the cable-pulley system.A tension decay factor is employed to account for the friction in the contact segment.To validate the proposed method,a semi-analytical model based on D'Alembert's principle is established.Cross-verification is performed to validate the accuracy of both models.The model is further applied to simulate the rotation of the cable-driven manipulator with different structural parameters and frictional factors.The results from the analyses provide valuable guidance for the design and motion control of the in-space cable-driven manipulator.Finally,a prototype of a single module is manufactured and tested.Ground experiments are carried out to verify the kinematic and dynamic models.展开更多
The outbreak of infectious diseases is the result of a combination of various factors,including season,the movement of individuals,non-pharmaceutical interventions(NPIs)and the effectiveness and availability of vaccin...The outbreak of infectious diseases is the result of a combination of various factors,including season,the movement of individuals,non-pharmaceutical interventions(NPIs)and the effectiveness and availability of vaccines.Taking these key elements into consideration,an almost periodic SVEIR warning model in the patch environment is here proposed.First,in terms of reproduction numbers,our results imply that if the effective reproduction numbers are R_(e)<1,then the disease dies out;if R_(e)>1,then the disease spreads and leads to local outbreaks.Second,the relationships between R_(e)and C_(s1),C_(a1)(see Section 2)are given by numerical simulations.The numerical results show that even if all people are vaccinated,NPIs are still needed because of the potentially low efficacy of vaccines.Furthermore,the numerical results suggest that NPIs and the strengthening of the effective rate of vaccination are essential in order to achieve herd immunity.Theories involving this model effectively explain the transmission mechanism of most infectious diseases,and provide a valuable theoretical basis for analyzing new infectious diseases in the future.Moreover,this model is helpful for the prevention and control of infectious diseases and the formulation of public health safety policies.展开更多
To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework ba...To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework based on face-pedestrian joint feature modeling.By constructing a joint tracking model centered on“intra-class independent tracking+cross-category dynamic binding”,designing a multi-modal matching metric with spatio-temporal and appearance constraints,and innovatively introducing a cross-category feature mutual verification mechanism and a dual matching strategy,this work effectively resolves performance degradation in traditional single-category tracking methods caused by short-term occlusion,cross-camera tracking,and crowded environments.Experiments on the Chokepoint_Face_Pedestrian_Track test set demonstrate that in complex scenes,the proposed method improves Face-Pedestrian Matching F1 area under the curve(F1 AUC)by approximately 4 to 43 percentage points compared to several traditional methods.The joint tracking model achieves overall performance metrics of IDF1:85.1825%and MOTA:86.5956%,representing improvements of 0.91 and 0.06 percentage points,respectively,over the baseline model.Ablation studies confirm the effectiveness of key modules such as the Intersection over Area(IoA)/Intersection over Union(IoU)joint metric and dynamic threshold adjustment,validating the significant role of the cross-category identity matching mechanism in enhancing tracking stability.Our_model shows a 16.7%frame per second(FPS)drop vs.fairness of detection and re-identification in multiple object tracking(FairMOT),with its cross-category binding module adding aboute 10%overhead,yet maintains near-real-time performance for essential face-pedestrian tracking at small resolutions.展开更多
The Balkhash Lake Basin(BLB),a vital Central Asian watershed,faces hydrological uncertainty under climate warming.This study integrated multi-source remote sensing data(Sentinel-1 snow depth,Randolph Glacier Inventory...The Balkhash Lake Basin(BLB),a vital Central Asian watershed,faces hydrological uncertainty under climate warming.This study integrated multi-source remote sensing data(Sentinel-1 snow depth,Randolph Glacier Inventory(RGI)v.7.0 glacier inventory,and Advanced Spaceborne Thermal Emission and Reflection Radiometer(ASTER)mass balance)with a degree-day model to reconstruct decadal snow and ice dynamics across 13 sub-basins and analyzed their hydrological impacts from 1950 to 2014.The results showed that:(1)while flows from the downstream river of the BLB decreased from 1950 to 1982 due to land surface changes,runoff increased significantly after 1982 in the Ili River(18.0%)and moderately increased in most rivers in the east(1.3%–8.3%),driven by increased precipitation and glacier melt.Runoff in the Ayaguz catchment(no glaciers with the highest climate warming)declined(10.5%);(2)climate warming reduced precipitation falling as snow caused snow melt water to decline(0.03–0.22 mm/a)across the BLB,leading to downward shifts in runoff and runoff coefficient,especially in the rivers in the east.However,snow melt during April–June positively correlated with runoff coefficient,contributing to an upward shift in the Ili River Basin;and(3)meltwater from glacierized areas(<5.0%of basin area)contributed to 14.3%of total ablation water.Net glacier melt provided substantial excess flows(11.6 m3/s in the Ili River and<1.0 m3/s in the rivers in the east),generally counterbalancing the negative effect of rising potential evaporation at decadal scales and positively correlating with the runoff coefficient.Therefore,water stress in the BLB may be more severe in the future due to the accelerating glacier melt after the abrupt increase in air temperature in 2000,the continuing decline in snow melt,and the significant inter-annual variations in precipitation.展开更多
This paper introduces a novel fractional-order model based on the Caputo-Fabrizio(CF)derivative for analyzing computer virus propagation in networked environments.The model partitions the computer population into four...This paper introduces a novel fractional-order model based on the Caputo-Fabrizio(CF)derivative for analyzing computer virus propagation in networked environments.The model partitions the computer population into four compartments:susceptible,latently infected,breaking-out,and antivirus-capable systems.By employing the CF derivative—which uses a nonsingular exponential kernel—the framework effectively captures memory-dependent and nonlocal characteristics intrinsic to cyber systems,aspects inadequately represented by traditional integer-order models.Under Lipschitz continuity and boundedness assumptions,the existence and uniqueness of solutions are rigorously established via fixed-point theory.We develop a tailored two-step Adams-Bashforth numerical scheme for the CF framework and prove its second-order accuracy.Extensive numerical simulations across various fractional orders reveal that memory effects significantly influence virus transmission and control dynamics;smaller fractional orders produce more pronounced memory effects,delaying both infection spread and antivirus activation.Further theoretical analysis,including Hyers-Ulam stability and sensitivity assessments,reinforces the model’s robustness and identifies key parameters governing virus dynamics.The study also extends the framework to incorporate stochastic effects through a stochastic CF formulation.These results underscore fractional-order modeling as a powerful analytical tool for developing robust and effective cybersecurity strategies.展开更多
Neuromyelitis optica spectrum disorder-related optic neuritis involves various cellular responses to inflammation and degeneration.In most patients,the primary mechanism underlying neuromyelitis optica spectrum disord...Neuromyelitis optica spectrum disorder-related optic neuritis involves various cellular responses to inflammation and degeneration.In most patients,the primary mechanism underlying neuromyelitis optica spectrum disorder-related optic neuritis is the interaction of aquaporin-4 antibodies with the aquaporin-4 protein present on astrocytes within posterior optic nerve.This binding subsequently initiates a cascade of events leading to secondary demyelination of the optic nerve,ultimately culminating in optic nerve degeneration.Earlier studies on this disorder primarily used systemic-induced animal models,which often require prior activation of a systemic immune response.This can result in primary demyelination of the optic nerve,complicating the interpretation of experimental results.Such methodologies hinder the ability to isolate immune responses triggered by specific antibodies.Additionally,the lack of a detailed profile of disease progression over time limits our capacity to identify potential intervention windows.Therefore,constructing a targeted optic neuritis animal model induced by specific antibodies and elucidate the disease progression arecrucial for exploring the mechanisms underlying neuromyelitis optica spectrum disorder-related optic neuritis.In this study,specific antibodies against aquaporin-4 were precisely injected into the retrobulbar optic nerve of mice to induce a targeted inflammatory response in the posterior optic nerve,resulting in a more representative mouse model of neuromyelitis optica spectrum disorder-related optic neuritis than current models.The progression of the disease was then dynamically observed from both histological and functional perspectives over the course of 1 month following the induction of inflammation.By the first week,astrocytes were damaged,as evidenced by the loss of aquaporin-4 and glial fibrillary acidic protein,the activation of microglia,and the upregulation of microglia-related cytokines,including tumor necrosis factor,interleukin-6,interleukin-1β,C-X-C motif ligand 10,and brain-derived neurotrophic factor.Starting from the second week,there were signs of optic nerve demyelination and significant damage to axonal fibers and retinal ganglion cell bodies.Visual-evoked potentials and dark adaptation threshold responses in electroretinogram both indicated dysfunction in the visual pathway and retina,while optical coherence tomography revealed thinning of the retinal nerve fiber layer in live mice.In summary,in this study we conducted a dynamic exploration of the occurrence and progression of neuromyelitis optica spectrum disorder-related optic neuritis triggered by specific antibodies.Our results show pathological changes at various stages and correlate histological and molecular alterations with in vivo structural and functional deterioration.The findings from this study lay an important foundation for further research on neuromyelitis optica spectrum disorder-related optic neuritis.展开更多
Reinforced concrete(RC)columns are often subjected to off-central explosion due to the uncertainty of blast locations.However,few studies have focused on the dynamic response of RC columns under offcentral explosions....Reinforced concrete(RC)columns are often subjected to off-central explosion due to the uncertainty of blast locations.However,few studies have focused on the dynamic response of RC columns under offcentral explosions.A field blast experiment was conducted under close-in explosion with varying detonation offset distances(0 m,0.5 m,and 1 m),the overpressure load and dynamic responses of the full-scale RC columns were measured.Compared with the centrally detonated condition,a relative offset distance of 1.67 decreases the maximum and residual deflections of the RC column by 16.8%and 21.4%,respectively,while increasing the maximum and residual support rotations by 24.7%and 17.8%.Based on the experimental results,a theoretical model was proposed that considers the detonation location and charge mass,boundary conditions,axial compression ratio and material properties.The theoretical model exhibited good agreement with the experimental results,with prediction errors below 10%for both maximum and residual deflection.The effects of parameters were analyzed,and it indicated that an increase in offset distance results in decreased maximum and residual deflections but an increased support angle,thereby exacerbating damage.Higher axial load ratio,span-depth ratio,and longitudinal reinforcement ratio reduce both deflections and support angle.Additionally,a rapid method to predict the maximum and residual deflection of RC columns under off-central blast loading was also proposed based on the Generalized Regression Neural Network(GRNN).Eleven features which related to the RC column properties and the blast characteristics were used in the training process of GRNN,and accurate predictions were achieved with prediction errors within 20%.This study fills the gap in predicting the dynamic response of RC columns under off-central explosion,providing valuable references for blast-resistant design.展开更多
The generalized rheological tests on sandstone were conducted under both dynamic stress and seepage fields.The results demonstrate that the rheological strain of the specimen under increased stress conditions is great...The generalized rheological tests on sandstone were conducted under both dynamic stress and seepage fields.The results demonstrate that the rheological strain of the specimen under increased stress conditions is greater than that under creep conditions,indicating that the dynamic stress field significantly influences the rheological behaviours of sandstone.Following the rheological tests,the number of small pores in the sandstone decreased,while the number of medium-sized pores increased,forming new seepage channels.The high initial rheological stress accelerated fracture compression and the closure of seepage channels,resulting in reduction in the permeability of sandstone.Based on the principles of generalized rheology and the experimental findings,a novel rock rheological constitutive model incorporating both the dynamic stress field and seepage properties has been developed.Numerical simulations of surrounding rock deformation in geotechnical engineering were carried out using a secondary development version of this model,which confirmed the applicability of the generalized rheological numerical simulation method.These results provide theoretical support for the long-term stability evaluation of engineering rock masses and for predicting the deformation of surrounding rock.展开更多
In the era of digital economy,business education lags behind the rapid iteration of industrial technology,which has become the core contradiction hindering industrial development.In order to solve the key problem of t...In the era of digital economy,business education lags behind the rapid iteration of industrial technology,which has become the core contradiction hindering industrial development.In order to solve the key problem of the disconnection between education supply and industrial demand,this paper proposes the“government,industry,academia,research and dynamic iteration”education ecological framework based on the ecological niche theory and the collaborative innovation theory,and adopts the combination of model construction and case study verification research method.The framework designs a four-dimensional collaborative nurturing mechanism that includes the linkage of multiple subjects and a double-cycle dynamic adjustment model based on feedback optimization,and constructs three major systems of technical support,resource integration and quality assurance.The research effectively breaks through the traditional linear cultivation paradigm,and the validation shows that the framework can significantly improve the matching degree and dynamic adaptability of talent cultivation and industrial demand.This paper not only provides a systematic theoretical model for the construction of a new business education system adapted to the needs of the digital economy,but also contributes an operable practical path,which is of great theoretical value and practical reference significance for promoting the digital transformation of business education.展开更多
Partial least squares (PLS) model maximizes the covariance between process variables and quality variables,making it widely used in quality-related fault detection.However,traditional PLS methods focus primarily on li...Partial least squares (PLS) model maximizes the covariance between process variables and quality variables,making it widely used in quality-related fault detection.However,traditional PLS methods focus primarily on linear processes,leading to poor performance in dynamic nonlinear processes.In this paper,a novel quality-related fault detection method,named DiCAE-PLS,is developed by combining dynamic-inner convolutional autoencoder with PLS.In the proposed DiCAE-PLS method,latent features are first extracted through dynamic-inner convolutional autoencoder (DiCAE) to capture process dynamics and nonlinearity from process variables.Then,a PLS model is established to build the relationship between the extracted latent features and the final product quality.To detect quality-related faults,Hotelling's T^(2) statistic is employed.The developed quality-related fault detection is applied to the widely used industrial benchmark of the Tennessee.展开更多
The coal dynamic characteristic stress identification under dynamic load is important for guiding underground mineral mining and predicting underground dynamic disasters.In this article,the dynamic compression test of...The coal dynamic characteristic stress identification under dynamic load is important for guiding underground mineral mining and predicting underground dynamic disasters.In this article,the dynamic compression test of anthracite under five strain rates is carried out,the evolution law of three kinds of crack characteristic stress is analyzed,and a prediction model of the crack characteristic stress threshold considering the strain rate effect is established.Then,the rationality of crack characteristic stress under dynamic loading is discussed from the damage evolution standpoint,and the crack extension response mechanism during dynamic compression of anthracite is discussed.The result shows that the crack characteristic stress threshold is significantly influenced by the strain rate.The three characteristic stress thresholds are positively correlated with the strain rate,but the ratios to the crest stress gradually decrease.The increase in the strain rate strongly contributes to the crack extension behavior of anthracite.In the crack unstable extension phase,because of the increase of the strain rate,anthracite shows more energy dissipation under the same deformation in association with the stress concentration effect and the dynamic strength enhancement effect.The crack propagation rate is increased,the crack propagation path of the section is more complex,and more severe damage occurs before the dynamic failure of anthracite,which leads to even more severe damage.展开更多
Objective:The current pathological diagnosis of lymph node metastasis is time-consuming,labor-intensive,and dependent on sectioning of paraffin blocks.Herein,in a prospective cohort of patients with breast cancer,we v...Objective:The current pathological diagnosis of lymph node metastasis is time-consuming,labor-intensive,and dependent on sectioning of paraffin blocks.Herein,in a prospective cohort of patients with breast cancer,we validated dynamic full-field optical coherence tomography(D-FFOCT),a virtual pathology tool integrating deep learning for nodal metastasis detection,and offering rapid and label-free histologic approximations of fresh tissues.Methods:In a prospective dual-center cohort of 155 patients with breast cancer,747 freshly bisected lymph node slides were obtained via D-FFOCT.Surgeons interpreted each slide with histopathology as the gold standard.A deep learning model was trained on 28,911 patches(corresponding to 590 slides)and tested on 7,736 patches(corresponding to 157 slides).The results were mapped to the slide level for potential intraoperative evaluation.Results:D-FFOCT strongly correlated with hematoxylin and eosin(H&E)-stained histological images.Surgeons achieved 97.10%specificity in nodal diagnosis with D-FFOCT.The performance of the artificial intelligence(AI)model was not inferior to that of human experts and had a sensitivity/specificity of 87.88%/91.94%and an area under the receiver operating characteristic curve of 0.899 at the slide level.The human–AI collaborative system reduced labor requirements by 75%and increased the specificity by 6.5%,to 98.39%.Conclusions:D-FFOCT has excellent potential as a tool for assessing lymph node metastatic status without tissue preparation or consumption.The integration of D-FFOCT with deep learning decreases labor demands and maintains high accuracy,thereby enabling streamlined nodal prediction independent of routine pathology procedures.展开更多
This paper addresses urban sustainability challenges amid global urbanization, emphasizing the need for innova tive approaches aligned with the Sustainable Development Goals. While traditional tools and linear models ...This paper addresses urban sustainability challenges amid global urbanization, emphasizing the need for innova tive approaches aligned with the Sustainable Development Goals. While traditional tools and linear models offer insights, they fall short in presenting a holistic view of complex urban challenges. System dynamics (SD) models that are often utilized to provide holistic, systematic understanding of a research subject, like the urban system, emerge as valuable tools, but data scarcity and theoretical inadequacy pose challenges. The research reviews relevant papers on recent SD model applications in urban sustainability since 2018, categorizing them based on nine key indicators. Among the reviewed papers, data limitations and model assumptions were identified as ma jor challenges in applying SD models to urban sustainability. This led to exploring the transformative potential of big data analytics, a rare approach in this field as identified by this study, to enhance SD models’ empirical foundation. Integrating big data could provide data-driven calibration, potentially improving predictive accuracy and reducing reliance on simplified assumptions. The paper concludes by advocating for new approaches that reduce assumptions and promote real-time applicable models, contributing to a comprehensive understanding of urban sustainability through the synergy of big data and SD models.展开更多
This paper investigates the capabilities of large language models(LLMs)to leverage,learn and create knowledge in solving computational fluid dynamics(CFD)problems through three categories of baseline problems.These ca...This paper investigates the capabilities of large language models(LLMs)to leverage,learn and create knowledge in solving computational fluid dynamics(CFD)problems through three categories of baseline problems.These categories include(1)conventional CFD problems that can be solved using existing numerical methods in LLMs,such as lid-driven cavity flow and the Sod shock tube problem;(2)problems that require new numerical methods beyond those available in LLMs,such as the recently developed Chien-physics-informed neural networks for singularly perturbed convection-diffusion equations;and(3)problems that cannot be solved using existing numerical methods in LLMs,such as the ill-conditioned Hilbert linear algebraic systems.The evaluations indicate that reasoning LLMs overall outperform non-reasoning models in four test cases.Reasoning LLMs show excellent performance for CFD problems according to the tailored prompts,but their current capability in autonomous knowledge exploration and creation needs to be enhanced.展开更多
Currently,there are a limited number of dynamic models available for braided composite plates with large overall motions,despite the incorporation of three-dimensional(3D)braided composites into rotating blade compone...Currently,there are a limited number of dynamic models available for braided composite plates with large overall motions,despite the incorporation of three-dimensional(3D)braided composites into rotating blade components.In this paper,a dynamic model of 3D 4-directional braided composite thin plates considering braiding directions is established.Based on Kirchhoff's plate assumptions,the displacement variables of the plate are expressed.By incorporating the braiding directions into the constitutive equation of the braided composites,the dynamic model of the plate considering braiding directions is obtained.The effects of the speeds,braiding directions,and braided angles on the responses of the plate with fixed-axis rotation and translational motion,respectively,are investigated.This paper presents a dynamic theory for calculating the deformation of 3D braided composite structures undergoing both translational and rotational motions.It also provides a simulation method for investigating the dynamic behavior of non-isotropic material plates in various applications.展开更多
To reveal the deterioration mechanism of coal-rock assemblages under chemical corrosion and dynamic loading,chemical corrosion and dynamic impact experiments were conducted.Under different chemical corrosion condition...To reveal the deterioration mechanism of coal-rock assemblages under chemical corrosion and dynamic loading,chemical corrosion and dynamic impact experiments were conducted.Under different chemical corrosion conditions,the weakening characteristics,observable characteristics,softening characteristics of the dynamic parameters,dynamic failure characteristics,dynamic failure forms and dynamic microscopic characteristics were analyzed.Under each corrosion condition,the dynamic elastic modulus,dynamic deformation modulus and dynamic peak intensity tended to decrease with immersing time.The dynamic elastic modulus,dynamic deformation modulus and dynamic peak intensity exhibited an inverted U-shaped trend.Under dynamic impact,the failure process of acidly corroded samples can be divided into the following stages:the initial stage,elastic energy accumulation stage,local failure of coal and secondary rock crack expansion stage,coal fragment ejection stage,rock spalling stage and complete instability stage.Under dynamic impact,failure modes exist:coal crushing failure,rock fragmenting failure,rock splitting failure and full splitting failure.After impact failure,sample fragments are distributed in powder,granular,cone and block forms.Based on Zhu-Wang-Tang nonlinear viscoelastic properties,a model considering chemical corrosion and impact damage was proposed.The combined effects of chemical and impact-induced damage on the dynamic mechanical properties of coal-rock assemblages were systematically analyzed.展开更多
Concrete materials are employed extensively in a variety of large-scale structures due to their economic viability and superior mechanical properties.During the service life of concrete structures,they are inevitably ...Concrete materials are employed extensively in a variety of large-scale structures due to their economic viability and superior mechanical properties.During the service life of concrete structures,they are inevitably subjected to damage from impact loading from natural disasters,such as earthquakes and storms.In recent years,the phasefield model has demonstrated exceptional capability in predicting the stochastic initiation,propagation,and bifurcation of cracks in materials.This study employs a phase-field model to focus on the rate dependency and failure response of concrete under impact deformation.A viscosity coefficient is introduced within the phase-field model to characterize the viscous behavior of dynamic crack propagation in concrete.The rate-dependent cohesive strength is defined within the yield function of concrete,where the rate sensitivity of cohesive strength facilitates the accumulation of the plastic driving force in the phase-field model.This process effectively captures the impact failure response of concrete.The applicability of the model was validated through unit cell experiments and numerical simulations of concrete under impact compression.Furthermore,the mechanical response and damage evolution mechanisms of concrete under impact loading were analyzed.It was observed that crack propagation in concrete initiates at material defects and,with increasing load,eventually develops in a direction perpendicular to the loading axis.展开更多
This paper presents a dynamic modeling method to test and examine the minimum mass of pressurized pore-gas for triggering landslides in stable gentle soil slopes.A stable gentle soil slope model is constructed with a ...This paper presents a dynamic modeling method to test and examine the minimum mass of pressurized pore-gas for triggering landslides in stable gentle soil slopes.A stable gentle soil slope model is constructed with a dry cement powder core,a saturated clay middle layer,and a dry sand upper layer.The test injects H_(2)O_(2)solution into the cement core to produce new pore-gas.The model test includes three identical H_(2)O_(2)injections.The small mass of generated oxygen gas(0.07%of slope soil mass and landslide body)from the first injection can build sufficient pore-gas pressure to cause soil upheaval and slide.Meanwhile,despite the first injection causing leak paths in the clay layer,the generated small mass of gas from the second and third injections can further trigger the landslide.A dynamic theoretical analysis of the slope failure is carried out and the required minimum pore-gas pressure for the landslide is calculated.The mass and pressure of generated gas in the model test are also estimated based on the calibration test for oxygen generation from H_(2)O_(2)solution in cement powder.The results indicate that the minimum mass of the generated gas for triggering the landslide is 2 ppm to 0.07%of the landslide body.Furthermore,the small mass of gas can provide sufficient pressure to cause soil upheaval and soil sliding in dynamic analysis.展开更多
Data-driven reduced-order modeling opens new avenues of understanding,predicting,controlling,and optimizing system behavior.Simple systems may have state spaces in which sparse human-interpretable dynamical systems ca...Data-driven reduced-order modeling opens new avenues of understanding,predicting,controlling,and optimizing system behavior.Simple systems may have state spaces in which sparse human-interpretable dynamical systems can be identified.This approach has been pioneered by Brunton et al.(2016,PNAS)with sparse identification of nonlinear dynamics.Complex systems,however,cannot be expected to benefit from such simple analytical descriptions.Yet,smoothness may be exploited by analytical local descriptions.In this paper,we identify a clusterwise polynomial dynamics from time-resolved snapshot data.The full state space is partitioned into clusters with a reduced-order polynomial description for each cluster and a global patching strategy.The resulting clusterwise modeling is entirely data-driven and requires no prior knowledge of the system dynamics.We illustrate the approach on the well-known chaotic Lorenz and Rössler systems,on the more challenging chaotic fluid flow dynamics of higher state-space dimensions,on a noisy electrocardiogram signal,and finally on the time evolution of the monthly sunspot number.Clusterwise modeling offers a powerful and interpretable paradigm for dynamical modeling.Nonlinear dynamics can be approximated by assembling many simple local models of different resolutions,opening new paths to understand and control intricate nonlinearities.展开更多
The high-temperature deformation and dynamic recrystallization(DRX)behaviors of GH4698 superalloy were investigated via hot compression tests,and an improved unified dislocation density-based constitutive model was es...The high-temperature deformation and dynamic recrystallization(DRX)behaviors of GH4698 superalloy were investigated via hot compression tests,and an improved unified dislocation density-based constitutive model was established.The results indicate that with the temperature decreasing or the strain rate increasing,the flow stress increases and the DRX fraction decreases.However,as the strain rate increases from 1 to 10 s^(-1),rapid dislocation multiplication and deformation heat accelerate the DRX nucleation,which further increases the DRX fraction.Discontinuous DRX nucleation is the dominant DRX nucleation mechanism,and continuous DRX nucleation mainly occurs under low strain rates.For the developed improved unified dislocation density-based constitutive model,the correlation coefficient,average absolute relative error,and root mean square error between the measured and predicted stresses are 0.994,7.32%and 10.8 MPa,respectively.Meanwhile,the correlation coefficient between the measured and predicted DRX fractions is 0.976.These indicate that the developed model exhibits high accuracy in predicting the high-temperature deformation and DRX behaviors of GH4698 superalloy.展开更多
基金co-supported by the National Natural Science Foundation of China(Nos.12102034 and 12125201)the Open Fund of State Key Laboratory of Robotics and Systems(HIT),China。
文摘In-space cable-driven manipulators exhibit several advantages,such as a large range of motion,high dexterity,and lightweight structure.However,kinematic and dynamic analysis play an essential role in designing a cable-driven manipulator.In this paper,the kinematic analysis of a type of cable-driven manipulator is performed,and a motion planning scheme is conducted to actuate this manipulator.Moreover,a flexible multi-body dynamic model of a cable-driven manipulator considering the frictional contact between the cables and pulleys is established.To describe properties such as flexibility,vibration,and variable length of the cable,this paper utilizes reducedorder beam elements of the Absolute Nodal Coordinates Formulation(ANCF)in Arbitrary Lagrangian Eulerian(ALE)framework.Additionally,a virtual element is introduced to model the contact segment in the cable-pulley system.A tension decay factor is employed to account for the friction in the contact segment.To validate the proposed method,a semi-analytical model based on D'Alembert's principle is established.Cross-verification is performed to validate the accuracy of both models.The model is further applied to simulate the rotation of the cable-driven manipulator with different structural parameters and frictional factors.The results from the analyses provide valuable guidance for the design and motion control of the in-space cable-driven manipulator.Finally,a prototype of a single module is manufactured and tested.Ground experiments are carried out to verify the kinematic and dynamic models.
基金supported by the NSFC(11501269)and the Natural Science Foundation of Gansu Province(23JRRA1041).
文摘The outbreak of infectious diseases is the result of a combination of various factors,including season,the movement of individuals,non-pharmaceutical interventions(NPIs)and the effectiveness and availability of vaccines.Taking these key elements into consideration,an almost periodic SVEIR warning model in the patch environment is here proposed.First,in terms of reproduction numbers,our results imply that if the effective reproduction numbers are R_(e)<1,then the disease dies out;if R_(e)>1,then the disease spreads and leads to local outbreaks.Second,the relationships between R_(e)and C_(s1),C_(a1)(see Section 2)are given by numerical simulations.The numerical results show that even if all people are vaccinated,NPIs are still needed because of the potentially low efficacy of vaccines.Furthermore,the numerical results suggest that NPIs and the strengthening of the effective rate of vaccination are essential in order to achieve herd immunity.Theories involving this model effectively explain the transmission mechanism of most infectious diseases,and provide a valuable theoretical basis for analyzing new infectious diseases in the future.Moreover,this model is helpful for the prevention and control of infectious diseases and the formulation of public health safety policies.
基金supported by the confidential research grant No.a8317。
文摘To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework based on face-pedestrian joint feature modeling.By constructing a joint tracking model centered on“intra-class independent tracking+cross-category dynamic binding”,designing a multi-modal matching metric with spatio-temporal and appearance constraints,and innovatively introducing a cross-category feature mutual verification mechanism and a dual matching strategy,this work effectively resolves performance degradation in traditional single-category tracking methods caused by short-term occlusion,cross-camera tracking,and crowded environments.Experiments on the Chokepoint_Face_Pedestrian_Track test set demonstrate that in complex scenes,the proposed method improves Face-Pedestrian Matching F1 area under the curve(F1 AUC)by approximately 4 to 43 percentage points compared to several traditional methods.The joint tracking model achieves overall performance metrics of IDF1:85.1825%and MOTA:86.5956%,representing improvements of 0.91 and 0.06 percentage points,respectively,over the baseline model.Ablation studies confirm the effectiveness of key modules such as the Intersection over Area(IoA)/Intersection over Union(IoU)joint metric and dynamic threshold adjustment,validating the significant role of the cross-category identity matching mechanism in enhancing tracking stability.Our_model shows a 16.7%frame per second(FPS)drop vs.fairness of detection and re-identification in multiple object tracking(FairMOT),with its cross-category binding module adding aboute 10%overhead,yet maintains near-real-time performance for essential face-pedestrian tracking at small resolutions.
基金supported by the National Natural Science Foundation of China(U2003202,42071054)the Key Research and Development Program of Jiangxi Province,China(20223BBG74003)the Science and Technology Planning Project of Nanjing Institute of Geography and Limnology(NIGLAS2022GS09).
文摘The Balkhash Lake Basin(BLB),a vital Central Asian watershed,faces hydrological uncertainty under climate warming.This study integrated multi-source remote sensing data(Sentinel-1 snow depth,Randolph Glacier Inventory(RGI)v.7.0 glacier inventory,and Advanced Spaceborne Thermal Emission and Reflection Radiometer(ASTER)mass balance)with a degree-day model to reconstruct decadal snow and ice dynamics across 13 sub-basins and analyzed their hydrological impacts from 1950 to 2014.The results showed that:(1)while flows from the downstream river of the BLB decreased from 1950 to 1982 due to land surface changes,runoff increased significantly after 1982 in the Ili River(18.0%)and moderately increased in most rivers in the east(1.3%–8.3%),driven by increased precipitation and glacier melt.Runoff in the Ayaguz catchment(no glaciers with the highest climate warming)declined(10.5%);(2)climate warming reduced precipitation falling as snow caused snow melt water to decline(0.03–0.22 mm/a)across the BLB,leading to downward shifts in runoff and runoff coefficient,especially in the rivers in the east.However,snow melt during April–June positively correlated with runoff coefficient,contributing to an upward shift in the Ili River Basin;and(3)meltwater from glacierized areas(<5.0%of basin area)contributed to 14.3%of total ablation water.Net glacier melt provided substantial excess flows(11.6 m3/s in the Ili River and<1.0 m3/s in the rivers in the east),generally counterbalancing the negative effect of rising potential evaporation at decadal scales and positively correlating with the runoff coefficient.Therefore,water stress in the BLB may be more severe in the future due to the accelerating glacier melt after the abrupt increase in air temperature in 2000,the continuing decline in snow melt,and the significant inter-annual variations in precipitation.
基金supported and funded by the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University(IMSIU)(grant number IMSIU-DDRSP2601).
文摘This paper introduces a novel fractional-order model based on the Caputo-Fabrizio(CF)derivative for analyzing computer virus propagation in networked environments.The model partitions the computer population into four compartments:susceptible,latently infected,breaking-out,and antivirus-capable systems.By employing the CF derivative—which uses a nonsingular exponential kernel—the framework effectively captures memory-dependent and nonlocal characteristics intrinsic to cyber systems,aspects inadequately represented by traditional integer-order models.Under Lipschitz continuity and boundedness assumptions,the existence and uniqueness of solutions are rigorously established via fixed-point theory.We develop a tailored two-step Adams-Bashforth numerical scheme for the CF framework and prove its second-order accuracy.Extensive numerical simulations across various fractional orders reveal that memory effects significantly influence virus transmission and control dynamics;smaller fractional orders produce more pronounced memory effects,delaying both infection spread and antivirus activation.Further theoretical analysis,including Hyers-Ulam stability and sensitivity assessments,reinforces the model’s robustness and identifies key parameters governing virus dynamics.The study also extends the framework to incorporate stochastic effects through a stochastic CF formulation.These results underscore fractional-order modeling as a powerful analytical tool for developing robust and effective cybersecurity strategies.
基金The study was partially supported by the General Research Fund(GRF)from the Research Grants Council(RGC)of the Hong Kong Special Administrative Region,China,No.15103522(to ST)the Internal Research Grant from the Hong Kong Polytechnic University 2021-23,No.P0035512(to ST)and P0035375(to HHLC)+1 种基金the Innovation and Technology Commission of the Hong Kong Special Administrative Region(ITC InnoHK CEVR Project)The Hong Kong Polytechnics University Research Center for Sharp Vision,No.P0039595.
文摘Neuromyelitis optica spectrum disorder-related optic neuritis involves various cellular responses to inflammation and degeneration.In most patients,the primary mechanism underlying neuromyelitis optica spectrum disorder-related optic neuritis is the interaction of aquaporin-4 antibodies with the aquaporin-4 protein present on astrocytes within posterior optic nerve.This binding subsequently initiates a cascade of events leading to secondary demyelination of the optic nerve,ultimately culminating in optic nerve degeneration.Earlier studies on this disorder primarily used systemic-induced animal models,which often require prior activation of a systemic immune response.This can result in primary demyelination of the optic nerve,complicating the interpretation of experimental results.Such methodologies hinder the ability to isolate immune responses triggered by specific antibodies.Additionally,the lack of a detailed profile of disease progression over time limits our capacity to identify potential intervention windows.Therefore,constructing a targeted optic neuritis animal model induced by specific antibodies and elucidate the disease progression arecrucial for exploring the mechanisms underlying neuromyelitis optica spectrum disorder-related optic neuritis.In this study,specific antibodies against aquaporin-4 were precisely injected into the retrobulbar optic nerve of mice to induce a targeted inflammatory response in the posterior optic nerve,resulting in a more representative mouse model of neuromyelitis optica spectrum disorder-related optic neuritis than current models.The progression of the disease was then dynamically observed from both histological and functional perspectives over the course of 1 month following the induction of inflammation.By the first week,astrocytes were damaged,as evidenced by the loss of aquaporin-4 and glial fibrillary acidic protein,the activation of microglia,and the upregulation of microglia-related cytokines,including tumor necrosis factor,interleukin-6,interleukin-1β,C-X-C motif ligand 10,and brain-derived neurotrophic factor.Starting from the second week,there were signs of optic nerve demyelination and significant damage to axonal fibers and retinal ganglion cell bodies.Visual-evoked potentials and dark adaptation threshold responses in electroretinogram both indicated dysfunction in the visual pathway and retina,while optical coherence tomography revealed thinning of the retinal nerve fiber layer in live mice.In summary,in this study we conducted a dynamic exploration of the occurrence and progression of neuromyelitis optica spectrum disorder-related optic neuritis triggered by specific antibodies.Our results show pathological changes at various stages and correlate histological and molecular alterations with in vivo structural and functional deterioration.The findings from this study lay an important foundation for further research on neuromyelitis optica spectrum disorder-related optic neuritis.
基金financially supported by the National Natural Science Foundation of China(Grants No.12472399)。
文摘Reinforced concrete(RC)columns are often subjected to off-central explosion due to the uncertainty of blast locations.However,few studies have focused on the dynamic response of RC columns under offcentral explosions.A field blast experiment was conducted under close-in explosion with varying detonation offset distances(0 m,0.5 m,and 1 m),the overpressure load and dynamic responses of the full-scale RC columns were measured.Compared with the centrally detonated condition,a relative offset distance of 1.67 decreases the maximum and residual deflections of the RC column by 16.8%and 21.4%,respectively,while increasing the maximum and residual support rotations by 24.7%and 17.8%.Based on the experimental results,a theoretical model was proposed that considers the detonation location and charge mass,boundary conditions,axial compression ratio and material properties.The theoretical model exhibited good agreement with the experimental results,with prediction errors below 10%for both maximum and residual deflection.The effects of parameters were analyzed,and it indicated that an increase in offset distance results in decreased maximum and residual deflections but an increased support angle,thereby exacerbating damage.Higher axial load ratio,span-depth ratio,and longitudinal reinforcement ratio reduce both deflections and support angle.Additionally,a rapid method to predict the maximum and residual deflection of RC columns under off-central blast loading was also proposed based on the Generalized Regression Neural Network(GRNN).Eleven features which related to the RC column properties and the blast characteristics were used in the training process of GRNN,and accurate predictions were achieved with prediction errors within 20%.This study fills the gap in predicting the dynamic response of RC columns under off-central explosion,providing valuable references for blast-resistant design.
基金supported and financed by Scientific Research Foundation for High-level Talents of Anhui University of Science and Technology (No.2024yjrc96)Anhui Provincial University Excellent Research and Innovation Team Support Project (No.2022AH010053)+2 种基金National Key Research and Development Program of China (Nos.2023YFC2907602 and 2022YFF1303302)Anhui Provincial Major Science and Technology Project (No.202203a07020011)Open Foundation of Joint National-Local Engineering Research Centre for Safe and Precise Coal Mining (No.EC2023020)。
文摘The generalized rheological tests on sandstone were conducted under both dynamic stress and seepage fields.The results demonstrate that the rheological strain of the specimen under increased stress conditions is greater than that under creep conditions,indicating that the dynamic stress field significantly influences the rheological behaviours of sandstone.Following the rheological tests,the number of small pores in the sandstone decreased,while the number of medium-sized pores increased,forming new seepage channels.The high initial rheological stress accelerated fracture compression and the closure of seepage channels,resulting in reduction in the permeability of sandstone.Based on the principles of generalized rheology and the experimental findings,a novel rock rheological constitutive model incorporating both the dynamic stress field and seepage properties has been developed.Numerical simulations of surrounding rock deformation in geotechnical engineering were carried out using a secondary development version of this model,which confirmed the applicability of the generalized rheological numerical simulation method.These results provide theoretical support for the long-term stability evaluation of engineering rock masses and for predicting the deformation of surrounding rock.
基金supported by Fujian Provincial Vocational Education Research Project(ZJGB2024038)Fujian Provincial Education Science Planning Project(FJJKGZ24-081)Fujian Provincial Social Science Planning Project(FJ2025C048).
文摘In the era of digital economy,business education lags behind the rapid iteration of industrial technology,which has become the core contradiction hindering industrial development.In order to solve the key problem of the disconnection between education supply and industrial demand,this paper proposes the“government,industry,academia,research and dynamic iteration”education ecological framework based on the ecological niche theory and the collaborative innovation theory,and adopts the combination of model construction and case study verification research method.The framework designs a four-dimensional collaborative nurturing mechanism that includes the linkage of multiple subjects and a double-cycle dynamic adjustment model based on feedback optimization,and constructs three major systems of technical support,resource integration and quality assurance.The research effectively breaks through the traditional linear cultivation paradigm,and the validation shows that the framework can significantly improve the matching degree and dynamic adaptability of talent cultivation and industrial demand.This paper not only provides a systematic theoretical model for the construction of a new business education system adapted to the needs of the digital economy,but also contributes an operable practical path,which is of great theoretical value and practical reference significance for promoting the digital transformation of business education.
基金supported in part by the National Natural Science Foundation of China(62573387)the Natural Science Foundation of Zhejiang province,China(LY24F030004)the Fundamental Research Funds of Zhejiang Sci-Tech University(25222139-Y).
文摘Partial least squares (PLS) model maximizes the covariance between process variables and quality variables,making it widely used in quality-related fault detection.However,traditional PLS methods focus primarily on linear processes,leading to poor performance in dynamic nonlinear processes.In this paper,a novel quality-related fault detection method,named DiCAE-PLS,is developed by combining dynamic-inner convolutional autoencoder with PLS.In the proposed DiCAE-PLS method,latent features are first extracted through dynamic-inner convolutional autoencoder (DiCAE) to capture process dynamics and nonlinearity from process variables.Then,a PLS model is established to build the relationship between the extracted latent features and the final product quality.To detect quality-related faults,Hotelling's T^(2) statistic is employed.The developed quality-related fault detection is applied to the widely used industrial benchmark of the Tennessee.
基金National Natural Science Foundation of China,Grant/Award Numbers:12072363,12372373,51934007,52104234,52174091。
文摘The coal dynamic characteristic stress identification under dynamic load is important for guiding underground mineral mining and predicting underground dynamic disasters.In this article,the dynamic compression test of anthracite under five strain rates is carried out,the evolution law of three kinds of crack characteristic stress is analyzed,and a prediction model of the crack characteristic stress threshold considering the strain rate effect is established.Then,the rationality of crack characteristic stress under dynamic loading is discussed from the damage evolution standpoint,and the crack extension response mechanism during dynamic compression of anthracite is discussed.The result shows that the crack characteristic stress threshold is significantly influenced by the strain rate.The three characteristic stress thresholds are positively correlated with the strain rate,but the ratios to the crest stress gradually decrease.The increase in the strain rate strongly contributes to the crack extension behavior of anthracite.In the crack unstable extension phase,because of the increase of the strain rate,anthracite shows more energy dissipation under the same deformation in association with the stress concentration effect and the dynamic strength enhancement effect.The crack propagation rate is increased,the crack propagation path of the section is more complex,and more severe damage occurs before the dynamic failure of anthracite,which leads to even more severe damage.
基金supported by grants from the National Key Research and Development Program of China(Grant No.2024YFC3405303)Beijing Natural Science Foundation(Grant No.7242281 and 7244427)Research and Development Fund of Peking University People’s Hospital(Grant No.RDZH2024-03 and RDEB2025-25).
文摘Objective:The current pathological diagnosis of lymph node metastasis is time-consuming,labor-intensive,and dependent on sectioning of paraffin blocks.Herein,in a prospective cohort of patients with breast cancer,we validated dynamic full-field optical coherence tomography(D-FFOCT),a virtual pathology tool integrating deep learning for nodal metastasis detection,and offering rapid and label-free histologic approximations of fresh tissues.Methods:In a prospective dual-center cohort of 155 patients with breast cancer,747 freshly bisected lymph node slides were obtained via D-FFOCT.Surgeons interpreted each slide with histopathology as the gold standard.A deep learning model was trained on 28,911 patches(corresponding to 590 slides)and tested on 7,736 patches(corresponding to 157 slides).The results were mapped to the slide level for potential intraoperative evaluation.Results:D-FFOCT strongly correlated with hematoxylin and eosin(H&E)-stained histological images.Surgeons achieved 97.10%specificity in nodal diagnosis with D-FFOCT.The performance of the artificial intelligence(AI)model was not inferior to that of human experts and had a sensitivity/specificity of 87.88%/91.94%and an area under the receiver operating characteristic curve of 0.899 at the slide level.The human–AI collaborative system reduced labor requirements by 75%and increased the specificity by 6.5%,to 98.39%.Conclusions:D-FFOCT has excellent potential as a tool for assessing lymph node metastatic status without tissue preparation or consumption.The integration of D-FFOCT with deep learning decreases labor demands and maintains high accuracy,thereby enabling streamlined nodal prediction independent of routine pathology procedures.
基金sponsored by the U.S.Department of Housing and Urban Development(Grant No.NJLTS0027-22)The opinions expressed in this study are the authors alone,and do not represent the U.S.Depart-ment of HUD’s opinions.
文摘This paper addresses urban sustainability challenges amid global urbanization, emphasizing the need for innova tive approaches aligned with the Sustainable Development Goals. While traditional tools and linear models offer insights, they fall short in presenting a holistic view of complex urban challenges. System dynamics (SD) models that are often utilized to provide holistic, systematic understanding of a research subject, like the urban system, emerge as valuable tools, but data scarcity and theoretical inadequacy pose challenges. The research reviews relevant papers on recent SD model applications in urban sustainability since 2018, categorizing them based on nine key indicators. Among the reviewed papers, data limitations and model assumptions were identified as ma jor challenges in applying SD models to urban sustainability. This led to exploring the transformative potential of big data analytics, a rare approach in this field as identified by this study, to enhance SD models’ empirical foundation. Integrating big data could provide data-driven calibration, potentially improving predictive accuracy and reducing reliance on simplified assumptions. The paper concludes by advocating for new approaches that reduce assumptions and promote real-time applicable models, contributing to a comprehensive understanding of urban sustainability through the synergy of big data and SD models.
基金supported by the National Natural Science Foundation of China Basic Science Center Program for“Multiscale Problems in Nonlinear Mechanics”(Grant No.11988102)the National Natural Science Foundation of China(Grant No.12202451).
文摘This paper investigates the capabilities of large language models(LLMs)to leverage,learn and create knowledge in solving computational fluid dynamics(CFD)problems through three categories of baseline problems.These categories include(1)conventional CFD problems that can be solved using existing numerical methods in LLMs,such as lid-driven cavity flow and the Sod shock tube problem;(2)problems that require new numerical methods beyond those available in LLMs,such as the recently developed Chien-physics-informed neural networks for singularly perturbed convection-diffusion equations;and(3)problems that cannot be solved using existing numerical methods in LLMs,such as the ill-conditioned Hilbert linear algebraic systems.The evaluations indicate that reasoning LLMs overall outperform non-reasoning models in four test cases.Reasoning LLMs show excellent performance for CFD problems according to the tailored prompts,but their current capability in autonomous knowledge exploration and creation needs to be enhanced.
基金Project supported by the National Natural Science Foundation of China(Nos.12372071 and 12372070)the Aeronautical Science Fund of China(No.2022Z055052001)the Foundation of China Scholarship Council(No.202306830079)。
文摘Currently,there are a limited number of dynamic models available for braided composite plates with large overall motions,despite the incorporation of three-dimensional(3D)braided composites into rotating blade components.In this paper,a dynamic model of 3D 4-directional braided composite thin plates considering braiding directions is established.Based on Kirchhoff's plate assumptions,the displacement variables of the plate are expressed.By incorporating the braiding directions into the constitutive equation of the braided composites,the dynamic model of the plate considering braiding directions is obtained.The effects of the speeds,braiding directions,and braided angles on the responses of the plate with fixed-axis rotation and translational motion,respectively,are investigated.This paper presents a dynamic theory for calculating the deformation of 3D braided composite structures undergoing both translational and rotational motions.It also provides a simulation method for investigating the dynamic behavior of non-isotropic material plates in various applications.
基金supported by the National Natural Science Foundation of China(Nos.52034009 and 52174093)the Fundamental Research Funds for the Central Universities(Nos.2024ZKPYNY01,2023ZKPYNY03,and 2023YQTD02).
文摘To reveal the deterioration mechanism of coal-rock assemblages under chemical corrosion and dynamic loading,chemical corrosion and dynamic impact experiments were conducted.Under different chemical corrosion conditions,the weakening characteristics,observable characteristics,softening characteristics of the dynamic parameters,dynamic failure characteristics,dynamic failure forms and dynamic microscopic characteristics were analyzed.Under each corrosion condition,the dynamic elastic modulus,dynamic deformation modulus and dynamic peak intensity tended to decrease with immersing time.The dynamic elastic modulus,dynamic deformation modulus and dynamic peak intensity exhibited an inverted U-shaped trend.Under dynamic impact,the failure process of acidly corroded samples can be divided into the following stages:the initial stage,elastic energy accumulation stage,local failure of coal and secondary rock crack expansion stage,coal fragment ejection stage,rock spalling stage and complete instability stage.Under dynamic impact,failure modes exist:coal crushing failure,rock fragmenting failure,rock splitting failure and full splitting failure.After impact failure,sample fragments are distributed in powder,granular,cone and block forms.Based on Zhu-Wang-Tang nonlinear viscoelastic properties,a model considering chemical corrosion and impact damage was proposed.The combined effects of chemical and impact-induced damage on the dynamic mechanical properties of coal-rock assemblages were systematically analyzed.
文摘Concrete materials are employed extensively in a variety of large-scale structures due to their economic viability and superior mechanical properties.During the service life of concrete structures,they are inevitably subjected to damage from impact loading from natural disasters,such as earthquakes and storms.In recent years,the phasefield model has demonstrated exceptional capability in predicting the stochastic initiation,propagation,and bifurcation of cracks in materials.This study employs a phase-field model to focus on the rate dependency and failure response of concrete under impact deformation.A viscosity coefficient is introduced within the phase-field model to characterize the viscous behavior of dynamic crack propagation in concrete.The rate-dependent cohesive strength is defined within the yield function of concrete,where the rate sensitivity of cohesive strength facilitates the accumulation of the plastic driving force in the phase-field model.This process effectively captures the impact failure response of concrete.The applicability of the model was validated through unit cell experiments and numerical simulations of concrete under impact compression.Furthermore,the mechanical response and damage evolution mechanisms of concrete under impact loading were analyzed.It was observed that crack propagation in concrete initiates at material defects and,with increasing load,eventually develops in a direction perpendicular to the loading axis.
基金supported by grants from the Research Grant Council of the Hong Kong Special Administrative Region,China(Project No.HKU 17207518).
文摘This paper presents a dynamic modeling method to test and examine the minimum mass of pressurized pore-gas for triggering landslides in stable gentle soil slopes.A stable gentle soil slope model is constructed with a dry cement powder core,a saturated clay middle layer,and a dry sand upper layer.The test injects H_(2)O_(2)solution into the cement core to produce new pore-gas.The model test includes three identical H_(2)O_(2)injections.The small mass of generated oxygen gas(0.07%of slope soil mass and landslide body)from the first injection can build sufficient pore-gas pressure to cause soil upheaval and slide.Meanwhile,despite the first injection causing leak paths in the clay layer,the generated small mass of gas from the second and third injections can further trigger the landslide.A dynamic theoretical analysis of the slope failure is carried out and the required minimum pore-gas pressure for the landslide is calculated.The mass and pressure of generated gas in the model test are also estimated based on the calibration test for oxygen generation from H_(2)O_(2)solution in cement powder.The results indicate that the minimum mass of the generated gas for triggering the landslide is 2 ppm to 0.07%of the landslide body.Furthermore,the small mass of gas can provide sufficient pressure to cause soil upheaval and soil sliding in dynamic analysis.
基金supported by the National Natural Science Foundation of China(Grant Nos.12172109,12202121,and 12302293)the China Postdoctoral Science Foundation(Grant Nos.2023M730866 and 2023T160166)+1 种基金the Guangdong Basic and Applied Basic Research Foundation(Grant No.2022A1515011492)the Shenzhen Science and Technology Program(Grant Nos.JCYJ20220531095605012,KJZD20230923115210021,and 29853MKCJ202300205).
文摘Data-driven reduced-order modeling opens new avenues of understanding,predicting,controlling,and optimizing system behavior.Simple systems may have state spaces in which sparse human-interpretable dynamical systems can be identified.This approach has been pioneered by Brunton et al.(2016,PNAS)with sparse identification of nonlinear dynamics.Complex systems,however,cannot be expected to benefit from such simple analytical descriptions.Yet,smoothness may be exploited by analytical local descriptions.In this paper,we identify a clusterwise polynomial dynamics from time-resolved snapshot data.The full state space is partitioned into clusters with a reduced-order polynomial description for each cluster and a global patching strategy.The resulting clusterwise modeling is entirely data-driven and requires no prior knowledge of the system dynamics.We illustrate the approach on the well-known chaotic Lorenz and Rössler systems,on the more challenging chaotic fluid flow dynamics of higher state-space dimensions,on a noisy electrocardiogram signal,and finally on the time evolution of the monthly sunspot number.Clusterwise modeling offers a powerful and interpretable paradigm for dynamical modeling.Nonlinear dynamics can be approximated by assembling many simple local models of different resolutions,opening new paths to understand and control intricate nonlinearities.
基金supported by the National Natural Science Foundation of China(No.52375337)the Key Research and Development Program of Hubei Province,China(No.2022BAA024)the Fundamental Research Funds for the Central Universities,China(No.2019kfyXJJS001).
文摘The high-temperature deformation and dynamic recrystallization(DRX)behaviors of GH4698 superalloy were investigated via hot compression tests,and an improved unified dislocation density-based constitutive model was established.The results indicate that with the temperature decreasing or the strain rate increasing,the flow stress increases and the DRX fraction decreases.However,as the strain rate increases from 1 to 10 s^(-1),rapid dislocation multiplication and deformation heat accelerate the DRX nucleation,which further increases the DRX fraction.Discontinuous DRX nucleation is the dominant DRX nucleation mechanism,and continuous DRX nucleation mainly occurs under low strain rates.For the developed improved unified dislocation density-based constitutive model,the correlation coefficient,average absolute relative error,and root mean square error between the measured and predicted stresses are 0.994,7.32%and 10.8 MPa,respectively.Meanwhile,the correlation coefficient between the measured and predicted DRX fractions is 0.976.These indicate that the developed model exhibits high accuracy in predicting the high-temperature deformation and DRX behaviors of GH4698 superalloy.
