Ultrasonic-Assisted Grinding(UAG)is a novel manufacturing technology that shows promising promise for use in processing Ceramic Matrix Composites(CMCs).Nevertheless,analyzing the material removal process of CMCs with ...Ultrasonic-Assisted Grinding(UAG)is a novel manufacturing technology that shows promising promise for use in processing Ceramic Matrix Composites(CMCs).Nevertheless,analyzing the material removal process of CMCs with multidirectional structure during UAG is challenging,impeding the progress and improvement of the UAG process.This work examined the impact of ultrasonic vibration on the dynamic mechanical characteristics during processing.Additionally,we experimentally elucidated the material removal mechanism of CMCs during the scratching process under the influence of vertical vibration.The results indicate that the introduction of ultrasonic vibration causes a strain rate effect,resulting in a modification of the material removal mechanism,subsequently impacting the processing quality.Ultrasonic vibration increases the dynamic strength and brittleness of the fibers in CMCs,leading to more cracks at fracture,which changes from the original bending fracture to shear fracture.In addition,ultrasonic vibration can effectively inhibit the impact of scratching depth and anisotropy on the removal mechanism of CMCs,resulting in a more uniform surface of CMCs after processing.展开更多
The multi-satellite electromagnetic formation flight system is nonlinear and strongly coupled,which makes modeling and optimization challenging.To simplify electromagnetic force evaluation and dynamics modeling,we int...The multi-satellite electromagnetic formation flight system is nonlinear and strongly coupled,which makes modeling and optimization challenging.To simplify electromagnetic force evaluation and dynamics modeling,we introduce a reference frame consistent with each satellite body frame,in which the electromagnetic dipoles and electromagnetic forces are represented as two-dimensional vectors.Then,the maneuver time is divided into time intervals,and different satellite sets are activated in each interval,converting the multi-satellite formation reconfiguration problem into an optimal trajectory problem of each two-satellite subsystem.To this end,a token-based dynamic programming method with a switching penalty of active satellite sets is proposed to determine the sequence of satellite sets participating in each time interval,thereby enabling all satellites to reach their desired states.For the two-satellite subsystem with the objectives of minimizing maneuver time and energy consumption,the Gauss pseudo-spectral method is employed to generate the optimal reconfiguration trajectory.Numerical simulations verify the effectiveness of the proposed optimization method.展开更多
Gas wells often encounter blockages in gas recovery channels owing to fluid accumulation during the later stages of extraction,which adversely affects subsequent recovery efforts.These undesirable conditions(e.g.,high...Gas wells often encounter blockages in gas recovery channels owing to fluid accumulation during the later stages of extraction,which adversely affects subsequent recovery efforts.These undesirable conditions(e.g.,high condensate content,high temperature,and high salinity)often affect foaming agent performance.In this study,surfactants were screened using an airflow method that closely resembles field treatment method.Notably,alcohol ether sulfates(AE_(n)S)with various polyoxyethylene(EO)units demonstrated exceptional performance in terms of liquid unloading efficiency and foam stability.At 80℃,the unloading efficiency of AE_(n)S with two EO units(AE_(2)S)in a high NaCl mass concentration(up to 200 g/L)and high condensate volume fraction(up to 20%)reached 84%.The dynamic surface tension and interfacial tension measured at the same temperature were used to analyze the influence of the diffusion rate and interfacial characteristics on the AE_(n)S foam,while the viscosity and liquid film thickness measurements reflected the mechanical strength and liquid-carrying capacity.In addition,transmission electron microscopy(TEM)revealed that AE_(2)S formed“dendritic”micellar aggregates at a high NaCl mass concentration,which significantly enhanced the viscosity and stability of the foam.The interactions among AE_(n)S,NaCl,and H2O were analyzed using molecular dynamics,and it was confirmed from a molecular mechanics perspective that a stable structure can form among the three,contributing to the foam stability.These findings demonstrate the significant potential of the AE_(2)S foam for gas well deliquification.展开更多
Railway noise barriers are an essential piece of infrastructure for reducing noise propagation.However,these barriers experience aerodynamic loads generated by high-speed trains,leading to dynamic effects that may com...Railway noise barriers are an essential piece of infrastructure for reducing noise propagation.However,these barriers experience aerodynamic loads generated by high-speed trains,leading to dynamic effects that may compromise their fatigue capacity.The most common structural design for railway noise barriers consists of vertical configurations of posts and panels.However,there have been few dynamic analyses of steel post/wood panel noise barriers under train-induced aerodynamic loads.This study used dynamic finite element analysis to assess the dynamic behavior of such noise barriers.Analysis of a 40-m-long noise barrier model and a triangular simplified load model,the latter of which effectively represented the detailed aerodynamic load,were first used to establish the model and input of the moving load during dynamic simulation.Then,the effects of different parameters on the dynamic response of the noise barrier were evaluated,including the damping ratio,the profile of the steel post,the span length of the panel,the barrier height,and the train speed.Gray relational analysis indicated that barrier height exhibited the highest correlations with the dynamic responses,followed by train speed,post profile,span length,and damping ratio.A reduction in the natural frequency and an increase in the train speed result in a higher peak response and more pronounced fluctuations between the nose and tail waves.The dynamic amplification factor(DAF)was found to be related to both the natural frequency and train speed.A model was proposed showing that the DAF significantly increases as the square of the natural frequency decreases and the cube of the train speed rises.展开更多
In multi-modal emotion recognition,excessive reliance on historical context often impedes the detection of emotional shifts,while modality heterogeneity and unimodal noise limit recognition performance.Existing method...In multi-modal emotion recognition,excessive reliance on historical context often impedes the detection of emotional shifts,while modality heterogeneity and unimodal noise limit recognition performance.Existing methods struggle to dynamically adjust cross-modal complementary strength to optimize fusion quality and lack effective mechanisms to model the dynamic evolution of emotions.To address these issues,we propose a multi-level dynamic gating and emotion transfer framework for multi-modal emotion recognition.A dynamic gating mechanism is applied across unimodal encoding,cross-modal alignment,and emotion transfer modeling,substantially improving noise robustness and feature alignment.First,we construct a unimodal encoder based on gated recurrent units and feature-selection gating to suppress intra-modal noise and enhance contextual representation.Second,we design a gated-attention crossmodal encoder that dynamically calibrates the complementary contributions of visual and audio modalities to the dominant textual features and eliminates redundant information.Finally,we introduce a gated enhanced emotion transfer module that explicitly models the temporal dependence of emotional evolution in dialogues via transfer gating and optimizes continuity modeling with a comparative learning loss.Experimental results demonstrate that the proposed method outperforms state-of-the-art models on the public MELD and IEMOCAP datasets.展开更多
With the rapid development of intelligent navigation technology,efficient and safe path planning for mobile robots has become a core requirement.To address the challenges of complex dynamic environments,this paper pro...With the rapid development of intelligent navigation technology,efficient and safe path planning for mobile robots has become a core requirement.To address the challenges of complex dynamic environments,this paper proposes an intelligent path planning framework based on grid map modeling.First,an improved Safe and Smooth A*(SSA*)algorithm is employed for global path planning.By incorporating obstacle expansion and cornerpoint optimization,the proposed SSA*enhances the safety and smoothness of the planned path.Then,a Partitioned Dynamic Window Approach(PDWA)is integrated for local planning,which is triggered when dynamic or sudden static obstacles appear,enabling real-time obstacle avoidance and path adjustment.A unified objective function is constructed,considering path length,safety,and smoothness comprehensively.Multiple simulation experiments are conducted on typical port grid maps.The results demonstrate that the improved SSA*significantly reduces the number of expanded nodes and computation time in static environmentswhile generating smoother and safer paths.Meanwhile,the PDWA exhibits strong real-time performance and robustness in dynamic scenarios,achieving shorter paths and lower planning times compared to other graph search algorithms.The proposedmethodmaintains stable performance across maps of different scales and various port scenarios,verifying its practicality and potential for wider application.展开更多
A safe and reliable path planning algorithm is fundamental for unmanned surface vehicles(USVs)to perform autonomous navigation tasks.However,a single global or local planning strategy cannot fully meet the requirement...A safe and reliable path planning algorithm is fundamental for unmanned surface vehicles(USVs)to perform autonomous navigation tasks.However,a single global or local planning strategy cannot fully meet the requirements of complex maritime environments.Global planning alone cannot effectively handle dynamic obstacles,while local planning alone may fall into local optima.To address these issues,this paper proposes a multi-dynamic-obstacle avoidance path planning method that integrates an improved A^(*)algorithm with the dynamic window approach(DWA).The traditional A^(*)algorithm often generates paths that are too close to obstacle boundaries and contain excessive turning points,whereas the traditional DWA tends to skirt densely clustered obstacles,resulting in longer routes and insufficient dynamic obstacle avoidance.To overcome these limitations,improved versions of both algorithms are developed.Key points extracted from the optimized A^(*)path are used as intermediate start-destination pairs for the improved DWA,and the weights of the DWA evaluation function are adjusted to achieve effective fusion.Furthermore,a multi-dynamic-obstacle avoidance strategy is designed for complex navigation scenarios.Simulation results demonstrate that the USV can adaptively switch between dynamic obstacle avoidance and path tracking based on obstacle distribution,validating the effectiveness of the proposed method.展开更多
To address the key scientific challenge of monitoring the dynamic fracturing of surrounding rock in deep roadways,this study systematically investigates the quantitative relationship between stress and charge signals ...To address the key scientific challenge of monitoring the dynamic fracturing of surrounding rock in deep roadways,this study systematically investigates the quantitative relationship between stress and charge signals during coal mass loading.By integrating innovative analytical approaches,introducing quantitative evaluation indices,and developing a charge–stress inversion model,and incorporating underground monitoring practices,significant progress has been achieved in elucidating the correlation between stress variations and charge signals throughout the entire coal mass fracturing process.First,in the field of stress–charge correlation analysis,empirical mode decomposition(EMD)was combined with wavelet coherence analysis for the first time,enabling the removal of slow-varying stress trends while retaining high-frequency fluctuations.This approach allowed for the quantitative characterization of the evolution of coherence between stress variations and charge fluctuations across multiple time scales.Second,coherence skewness and the proportion of high-coherence intervals were innovatively introduced to examine the influence of time scale selection on correlation results.On this basis,a criterion for determining the near-optimal observation scale of charge signals was proposed,providing a quantitative reference for time scale selection in similar signal analyses.Finally,by correlating charge signals with coal damage factors and stress states,a charge-based damage evolution equation was established to achieve effective stress inversion.Combined with in situ monitoring of stress and charge in roadway surrounding rock,this approach revealed the correlation characteristics of stress and charge intensity responses during the dynamic fracturing process.The results indicate,first,that charge signals are not significantly correlated with the absolute stress level of coal but are directly associated with stress variations following coal damage and failure,with the amplitude of charge fluctuations increasing alongside stress fluctuations.Second,coherence between stress and charge signals varies markedly across time scales,with excessively small or large scales leading to distortion,and the scale corresponding to the peak proportion of intervals with coherence>0.8 was identified as the near-optimal observation scale.Third,charge signals can effectively characterize coal damage factors,and the established damage evolution equation can effectively invert stress variation trends.Fourth,in underground roadways,zones of dynamic fracturing in surrounding rock are commonly located in areas where stress concentration overlaps with regions of high charge intensity,further confirming the strong consistency between charge and stress variations.These findings improve the theoretical framework of charge signal responses in loaded coal and provide a scientific basis for precise“stress-charge”monitoring of dynamic disasters,offering practical potential for engineering applications.展开更多
Photo-responsive supramolecular assembly especially supramolecular hydrogels with tunable luminescence show a promising application potential in writable information recording and display materials.Herein,we report ph...Photo-responsive supramolecular assembly especially supramolecular hydrogels with tunable luminescence show a promising application potential in writable information recording and display materials.Herein,we report photo-responsive reversible multicolor supramolecular hydrogel with near-infrared emission,which is constructed by cucurbit[7]uril(CB[7]),cyanostilbene derivative(DAC)and Laponite XLG(LP)via supramolecular cascade assembly.Compared with the free vip molecule DAC,the confinement of macrocycle CB[7]achieve effective near-infrared fluorescence in the aqueous phase from scratch,and the subsequent cascade assembly with LP further restrict the molecular rotation of the DAC,which not only result in a substantial enhancement of the fluorescence intensity,but is also endowed with light-controlled fluorescence on/off both in the solution and hydrogel states.Further,8-hydroxy-1,3,6-pyrenetrisulfonic acid trisodium salt(HPTS)is introduced in the cascade assembly to fabricated photocontrollable reversible multicolor luminescence supramolecular hydrogel between red and green induced by Förster resonance energy transfer,which is successfully employed in reversible multiple information encryption.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
Amid the increasing demand for data sharing,the need for flexible,secure,and auditable access control mechanisms has garnered significant attention in the academic community.However,blockchain-based ciphertextpolicy a...Amid the increasing demand for data sharing,the need for flexible,secure,and auditable access control mechanisms has garnered significant attention in the academic community.However,blockchain-based ciphertextpolicy attribute-based encryption(CP-ABE)schemes still face cumbersome ciphertext re-encryption and insufficient oversight when handling dynamic attribute changes and cross-chain collaboration.To address these issues,we propose a dynamic permission attribute-encryption scheme for multi-chain collaboration.This scheme incorporates a multiauthority architecture for distributed attribute management and integrates an attribute revocation and granting mechanism that eliminates the need for ciphertext re-encryption,effectively reducing both computational and communication overhead.It leverages the InterPlanetary File System(IPFS)for off-chain data storage and constructs a cross-chain regulatory framework—comprising a Hyperledger Fabric business chain and a FISCO BCOS regulatory chain—to record changes in decryption privileges and access behaviors in an auditable manner.Security analysis shows selective indistinguishability under chosen-plaintext attack(sIND-CPA)security under the decisional q-Parallel Bilinear Diffie-Hellman Exponent Assumption(q-PBDHE).In the performance and experimental evaluations,we compared the proposed scheme with several advanced schemes.The results show that,while preserving security,the proposed scheme achieves higher encryption/decryption efficiency and lower storage overhead for ciphertexts and keys.展开更多
Defining science and demarcating it from pseudoscience are longstanding core issues in the philosophy of science.Hilbert’s traditional axiomatic standards(consistency,completeness,independence)struggle with modern co...Defining science and demarcating it from pseudoscience are longstanding core issues in the philosophy of science.Hilbert’s traditional axiomatic standards(consistency,completeness,independence)struggle with modern complex systems,while existing demarcation criteria like replicability and Popper’s falsificationism have practical limitations.Analyzing incompatibilities in complex systems,this paper proposes a revised framework:modified Hilbert axiomatic standards(clearly defined concepts,logical consistency,unrefuted axioms)and dynamic demarcation criteria.Abandoning unattainable traditional requirements of completeness and independence,it emphasizes conceptual clarity,openness,and progressiveness,offering an operational,self-consistent basis for judging scientificity.展开更多
Recycling of waste rubber(WR)is crucial for the sustainable development of the rubber industry.The enhancement of interfacial interactions is the main strategy for waste polymer recycling.However,there is a lack of me...Recycling of waste rubber(WR)is crucial for the sustainable development of the rubber industry.The enhancement of interfacial interactions is the main strategy for waste polymer recycling.However,there is a lack of methods for enhancing the interfacial interactions for WR recycling because WR contains abundant inert C―H bonds.Herein,we designed thioctic acid inverse vulcanization copolymers to endow recycled WR with dynamic disulfide interfacial interactions,significantly improving the mechanical properties of recycled WR.These disulfide interfacial interactions among the recycled WR tend to exchange,which dramatically increases the fractocohesive length and prevents stress concentration near the crack tips.When recycled WR is subjected to external stress,the loads are redistributed across a broad region of adjacent regions instead of being concentrated on a limited length scale,which resists crack propagation.This work effectively recycled WR,providing a strategy for solvent-free reaction-derived inverse vulcanization copolymers to improve the toughness of WR recycling.展开更多
The space gravitational wave detection aims to detect gravitational waves in the mHz band in order to study supermassive black hole mergers,galaxy evolution and the structure of the early universe.One of its core payl...The space gravitational wave detection aims to detect gravitational waves in the mHz band in order to study supermassive black hole mergers,galaxy evolution and the structure of the early universe.One of its core payloads is a transponder-type interstellar laser interferometer,designed to measure relative displacement changes at the pico-meter level.Among its components,phasemeter is tasked with extracting the phase and frequency of the interference signal.Currently,phase-locked loop(PLL)phasemeters are commonly employed.However,the second harmonic signal generated by the mixer can restrict both the dynamic range and phase measurement accuracy of the phasemeter.This paper analyzes the interstellar laser interferometer and the impact of the second harmonic signal on the phasemeter's performance.To address these challenges,a phasemeter incorporating a second harmonic signal filter is proposed.This new design mitigates second harmonic disturbances within the phasemeter's bandwidth by dynamically adjusting the filter's cutoff frequency to track the input signal frequency,thereby suppressing the second harmonic signal in real time.Theoretical and simulation analyses demonstrate that the proposed phasemeter with a second harmonic filter significantly enhances the dynamic range.Finally,experimental results verify that the phasemeter can achieve the tracking of sudden frequency changes up to4.8 MHz.展开更多
Drilling and blasting tunneling is a cyclic process in which tunnel rock undergoes repeated blast loading,affecting its dynamic characteristics,energy evolution,and damage progression.To explore the dynamic mechanical...Drilling and blasting tunneling is a cyclic process in which tunnel rock undergoes repeated blast loading,affecting its dynamic characteristics,energy evolution,and damage progression.To explore the dynamic mechanical properties and damage mechanisms of carbonaceous slate under cyclic impact loads of varying intensities,cyclic dynamic tests are conducted using a triaxial split Hopkinson pressure bar.This study analyzes the stress-strain relationship,energy damage evolution,and macro-to-micro failure characteristics.The results show that peak stress and strain are significantly influenced by impact intensity and the number of impacts.The initial dynamic stress is positively correlated with the impact intensity,but with more impact,the dynamic stress decreases while the peak strain increases.Energy evolution follows a pattern of"slow growthfluctuating growthrapid growth,"with the crack initiation stress and its proportion decreasing.CT and SEM analyses reveal that as the impact intensity increases,failure becomes more chaotic,the fracture volume increases,and the fracture mode shifts from interlayer and intergranular to through-layer and trans-granular fractures.These findings provide an experimental basis for soft rock tunnel stability analysis.展开更多
With the recent increase in data volume and diversity,traditional text representation techniques are struggling to capture context,particularly in environments with sparse data.To address these challenges,this study p...With the recent increase in data volume and diversity,traditional text representation techniques are struggling to capture context,particularly in environments with sparse data.To address these challenges,this study proposes a new model,the Masked Joint Representation Model(MJRM).MJRM approximates the original hypothesis by leveraging multiple elements in a limited context.It dynamically adapts to changes in characteristics based on data distribution through three main components.First,masking-based representation learning,termed selective dynamic masking,integrates topic modeling and sentiment clustering to generate and train multiple instances across different data subsets,whose predictions are then aggregated with optimized weights.This design alleviates sparsity,suppresses noise,and preserves contextual structures.Second,regularization-based improvements are applied.Third,techniques for addressing sparse data are used to perform final inference.As a result,MJRM improves performance by up to 4%compared to existing AI techniques.In our experiments,we analyzed the contribution of each factor,demonstrating that masking,dynamic learning,and aggregating multiple instances complement each other to improve performance.This demonstrates that a masking-based multi-learning strategy is effective for context-aware sparse text classification,and can be useful even in challenging situations such as data shortage or data distribution variations.We expect that the approach can be extended to diverse fields such as sentiment analysis,spam filtering,and domain-specific document classification.展开更多
基金supported by the National Science Foundation for Distinguished Young Scholars of China(No.52325506)the Fundamental Research Funds for the Central Universities(No.DUT22LAB501)。
文摘Ultrasonic-Assisted Grinding(UAG)is a novel manufacturing technology that shows promising promise for use in processing Ceramic Matrix Composites(CMCs).Nevertheless,analyzing the material removal process of CMCs with multidirectional structure during UAG is challenging,impeding the progress and improvement of the UAG process.This work examined the impact of ultrasonic vibration on the dynamic mechanical characteristics during processing.Additionally,we experimentally elucidated the material removal mechanism of CMCs during the scratching process under the influence of vertical vibration.The results indicate that the introduction of ultrasonic vibration causes a strain rate effect,resulting in a modification of the material removal mechanism,subsequently impacting the processing quality.Ultrasonic vibration increases the dynamic strength and brittleness of the fibers in CMCs,leading to more cracks at fracture,which changes from the original bending fracture to shear fracture.In addition,ultrasonic vibration can effectively inhibit the impact of scratching depth and anisotropy on the removal mechanism of CMCs,resulting in a more uniform surface of CMCs after processing.
文摘The multi-satellite electromagnetic formation flight system is nonlinear and strongly coupled,which makes modeling and optimization challenging.To simplify electromagnetic force evaluation and dynamics modeling,we introduce a reference frame consistent with each satellite body frame,in which the electromagnetic dipoles and electromagnetic forces are represented as two-dimensional vectors.Then,the maneuver time is divided into time intervals,and different satellite sets are activated in each interval,converting the multi-satellite formation reconfiguration problem into an optimal trajectory problem of each two-satellite subsystem.To this end,a token-based dynamic programming method with a switching penalty of active satellite sets is proposed to determine the sequence of satellite sets participating in each time interval,thereby enabling all satellites to reach their desired states.For the two-satellite subsystem with the objectives of minimizing maneuver time and energy consumption,the Gauss pseudo-spectral method is employed to generate the optimal reconfiguration trajectory.Numerical simulations verify the effectiveness of the proposed optimization method.
文摘Gas wells often encounter blockages in gas recovery channels owing to fluid accumulation during the later stages of extraction,which adversely affects subsequent recovery efforts.These undesirable conditions(e.g.,high condensate content,high temperature,and high salinity)often affect foaming agent performance.In this study,surfactants were screened using an airflow method that closely resembles field treatment method.Notably,alcohol ether sulfates(AE_(n)S)with various polyoxyethylene(EO)units demonstrated exceptional performance in terms of liquid unloading efficiency and foam stability.At 80℃,the unloading efficiency of AE_(n)S with two EO units(AE_(2)S)in a high NaCl mass concentration(up to 200 g/L)and high condensate volume fraction(up to 20%)reached 84%.The dynamic surface tension and interfacial tension measured at the same temperature were used to analyze the influence of the diffusion rate and interfacial characteristics on the AE_(n)S foam,while the viscosity and liquid film thickness measurements reflected the mechanical strength and liquid-carrying capacity.In addition,transmission electron microscopy(TEM)revealed that AE_(2)S formed“dendritic”micellar aggregates at a high NaCl mass concentration,which significantly enhanced the viscosity and stability of the foam.The interactions among AE_(n)S,NaCl,and H2O were analyzed using molecular dynamics,and it was confirmed from a molecular mechanics perspective that a stable structure can form among the three,contributing to the foam stability.These findings demonstrate the significant potential of the AE_(2)S foam for gas well deliquification.
基金financially supported by the Swedish Transport Administration(Trafikverket)through the“Excellence Area 4”and FOI-BBT program(Grant Nos.BBT-2019-022 and BBT-TRV 2024/132497).
文摘Railway noise barriers are an essential piece of infrastructure for reducing noise propagation.However,these barriers experience aerodynamic loads generated by high-speed trains,leading to dynamic effects that may compromise their fatigue capacity.The most common structural design for railway noise barriers consists of vertical configurations of posts and panels.However,there have been few dynamic analyses of steel post/wood panel noise barriers under train-induced aerodynamic loads.This study used dynamic finite element analysis to assess the dynamic behavior of such noise barriers.Analysis of a 40-m-long noise barrier model and a triangular simplified load model,the latter of which effectively represented the detailed aerodynamic load,were first used to establish the model and input of the moving load during dynamic simulation.Then,the effects of different parameters on the dynamic response of the noise barrier were evaluated,including the damping ratio,the profile of the steel post,the span length of the panel,the barrier height,and the train speed.Gray relational analysis indicated that barrier height exhibited the highest correlations with the dynamic responses,followed by train speed,post profile,span length,and damping ratio.A reduction in the natural frequency and an increase in the train speed result in a higher peak response and more pronounced fluctuations between the nose and tail waves.The dynamic amplification factor(DAF)was found to be related to both the natural frequency and train speed.A model was proposed showing that the DAF significantly increases as the square of the natural frequency decreases and the cube of the train speed rises.
基金funded by“the Fanying Special Program of the National Natural Science Foundation of China,grant number 62341307”“the Scientific research project of Jiangxi Provincial Department of Education,grant number GJJ200839”“theDoctoral startup fund of JiangxiUniversity of Technology,grant number 205200100402”.
文摘In multi-modal emotion recognition,excessive reliance on historical context often impedes the detection of emotional shifts,while modality heterogeneity and unimodal noise limit recognition performance.Existing methods struggle to dynamically adjust cross-modal complementary strength to optimize fusion quality and lack effective mechanisms to model the dynamic evolution of emotions.To address these issues,we propose a multi-level dynamic gating and emotion transfer framework for multi-modal emotion recognition.A dynamic gating mechanism is applied across unimodal encoding,cross-modal alignment,and emotion transfer modeling,substantially improving noise robustness and feature alignment.First,we construct a unimodal encoder based on gated recurrent units and feature-selection gating to suppress intra-modal noise and enhance contextual representation.Second,we design a gated-attention crossmodal encoder that dynamically calibrates the complementary contributions of visual and audio modalities to the dominant textual features and eliminates redundant information.Finally,we introduce a gated enhanced emotion transfer module that explicitly models the temporal dependence of emotional evolution in dialogues via transfer gating and optimizes continuity modeling with a comparative learning loss.Experimental results demonstrate that the proposed method outperforms state-of-the-art models on the public MELD and IEMOCAP datasets.
文摘With the rapid development of intelligent navigation technology,efficient and safe path planning for mobile robots has become a core requirement.To address the challenges of complex dynamic environments,this paper proposes an intelligent path planning framework based on grid map modeling.First,an improved Safe and Smooth A*(SSA*)algorithm is employed for global path planning.By incorporating obstacle expansion and cornerpoint optimization,the proposed SSA*enhances the safety and smoothness of the planned path.Then,a Partitioned Dynamic Window Approach(PDWA)is integrated for local planning,which is triggered when dynamic or sudden static obstacles appear,enabling real-time obstacle avoidance and path adjustment.A unified objective function is constructed,considering path length,safety,and smoothness comprehensively.Multiple simulation experiments are conducted on typical port grid maps.The results demonstrate that the improved SSA*significantly reduces the number of expanded nodes and computation time in static environmentswhile generating smoother and safer paths.Meanwhile,the PDWA exhibits strong real-time performance and robustness in dynamic scenarios,achieving shorter paths and lower planning times compared to other graph search algorithms.The proposedmethodmaintains stable performance across maps of different scales and various port scenarios,verifying its practicality and potential for wider application.
基金supported by the National Nature Science Foundation of China(62203299,62373246,62388101)the Research Fund of State Key Laboratory of Deep-Sea Manned Vehicles(2024SKLDMV04)+1 种基金the Oceanic Interdisciplinary Program of Shanghai Jiao Tong University(SL2023MS007)the Startup Fund for Young Faculty at SJTU(24X010502929)。
文摘A safe and reliable path planning algorithm is fundamental for unmanned surface vehicles(USVs)to perform autonomous navigation tasks.However,a single global or local planning strategy cannot fully meet the requirements of complex maritime environments.Global planning alone cannot effectively handle dynamic obstacles,while local planning alone may fall into local optima.To address these issues,this paper proposes a multi-dynamic-obstacle avoidance path planning method that integrates an improved A^(*)algorithm with the dynamic window approach(DWA).The traditional A^(*)algorithm often generates paths that are too close to obstacle boundaries and contain excessive turning points,whereas the traditional DWA tends to skirt densely clustered obstacles,resulting in longer routes and insufficient dynamic obstacle avoidance.To overcome these limitations,improved versions of both algorithms are developed.Key points extracted from the optimized A^(*)path are used as intermediate start-destination pairs for the improved DWA,and the weights of the DWA evaluation function are adjusted to achieve effective fusion.Furthermore,a multi-dynamic-obstacle avoidance strategy is designed for complex navigation scenarios.Simulation results demonstrate that the USV can adaptively switch between dynamic obstacle avoidance and path tracking based on obstacle distribution,validating the effectiveness of the proposed method.
基金supported by the Research Fund of the National Natural Science Foundation of China(No.52374205)the Fundamental Research Project of the Educational Department of Liaoning Province(No.JYTMS20230793)the Research Fund of the State Key Laboratory of Coal Resources and Safe Mining,CUMT(No.YJY-XD-2024-A-016).
文摘To address the key scientific challenge of monitoring the dynamic fracturing of surrounding rock in deep roadways,this study systematically investigates the quantitative relationship between stress and charge signals during coal mass loading.By integrating innovative analytical approaches,introducing quantitative evaluation indices,and developing a charge–stress inversion model,and incorporating underground monitoring practices,significant progress has been achieved in elucidating the correlation between stress variations and charge signals throughout the entire coal mass fracturing process.First,in the field of stress–charge correlation analysis,empirical mode decomposition(EMD)was combined with wavelet coherence analysis for the first time,enabling the removal of slow-varying stress trends while retaining high-frequency fluctuations.This approach allowed for the quantitative characterization of the evolution of coherence between stress variations and charge fluctuations across multiple time scales.Second,coherence skewness and the proportion of high-coherence intervals were innovatively introduced to examine the influence of time scale selection on correlation results.On this basis,a criterion for determining the near-optimal observation scale of charge signals was proposed,providing a quantitative reference for time scale selection in similar signal analyses.Finally,by correlating charge signals with coal damage factors and stress states,a charge-based damage evolution equation was established to achieve effective stress inversion.Combined with in situ monitoring of stress and charge in roadway surrounding rock,this approach revealed the correlation characteristics of stress and charge intensity responses during the dynamic fracturing process.The results indicate,first,that charge signals are not significantly correlated with the absolute stress level of coal but are directly associated with stress variations following coal damage and failure,with the amplitude of charge fluctuations increasing alongside stress fluctuations.Second,coherence between stress and charge signals varies markedly across time scales,with excessively small or large scales leading to distortion,and the scale corresponding to the peak proportion of intervals with coherence>0.8 was identified as the near-optimal observation scale.Third,charge signals can effectively characterize coal damage factors,and the established damage evolution equation can effectively invert stress variation trends.Fourth,in underground roadways,zones of dynamic fracturing in surrounding rock are commonly located in areas where stress concentration overlaps with regions of high charge intensity,further confirming the strong consistency between charge and stress variations.These findings improve the theoretical framework of charge signal responses in loaded coal and provide a scientific basis for precise“stress-charge”monitoring of dynamic disasters,offering practical potential for engineering applications.
基金National Natural Science Foundation of China (NSFC) (No.22131008)the Haihe Laboratory of Sustainable Chemical Transformations for financial support。
文摘Photo-responsive supramolecular assembly especially supramolecular hydrogels with tunable luminescence show a promising application potential in writable information recording and display materials.Herein,we report photo-responsive reversible multicolor supramolecular hydrogel with near-infrared emission,which is constructed by cucurbit[7]uril(CB[7]),cyanostilbene derivative(DAC)and Laponite XLG(LP)via supramolecular cascade assembly.Compared with the free vip molecule DAC,the confinement of macrocycle CB[7]achieve effective near-infrared fluorescence in the aqueous phase from scratch,and the subsequent cascade assembly with LP further restrict the molecular rotation of the DAC,which not only result in a substantial enhancement of the fluorescence intensity,but is also endowed with light-controlled fluorescence on/off both in the solution and hydrogel states.Further,8-hydroxy-1,3,6-pyrenetrisulfonic acid trisodium salt(HPTS)is introduced in the cascade assembly to fabricated photocontrollable reversible multicolor luminescence supramolecular hydrogel between red and green induced by Förster resonance energy transfer,which is successfully employed in reversible multiple information encryption.
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.
文摘Amid the increasing demand for data sharing,the need for flexible,secure,and auditable access control mechanisms has garnered significant attention in the academic community.However,blockchain-based ciphertextpolicy attribute-based encryption(CP-ABE)schemes still face cumbersome ciphertext re-encryption and insufficient oversight when handling dynamic attribute changes and cross-chain collaboration.To address these issues,we propose a dynamic permission attribute-encryption scheme for multi-chain collaboration.This scheme incorporates a multiauthority architecture for distributed attribute management and integrates an attribute revocation and granting mechanism that eliminates the need for ciphertext re-encryption,effectively reducing both computational and communication overhead.It leverages the InterPlanetary File System(IPFS)for off-chain data storage and constructs a cross-chain regulatory framework—comprising a Hyperledger Fabric business chain and a FISCO BCOS regulatory chain—to record changes in decryption privileges and access behaviors in an auditable manner.Security analysis shows selective indistinguishability under chosen-plaintext attack(sIND-CPA)security under the decisional q-Parallel Bilinear Diffie-Hellman Exponent Assumption(q-PBDHE).In the performance and experimental evaluations,we compared the proposed scheme with several advanced schemes.The results show that,while preserving security,the proposed scheme achieves higher encryption/decryption efficiency and lower storage overhead for ciphertexts and keys.
基金supported by the start-up funding from Westlake University under Grant Number 041030150118 and the scientific research project of Westlake University“Theoretical Research and Demonstration Application of Complex Systems and Deep-Sea Technology(Phase I)”under Grant Number WU2025A006.
文摘Defining science and demarcating it from pseudoscience are longstanding core issues in the philosophy of science.Hilbert’s traditional axiomatic standards(consistency,completeness,independence)struggle with modern complex systems,while existing demarcation criteria like replicability and Popper’s falsificationism have practical limitations.Analyzing incompatibilities in complex systems,this paper proposes a revised framework:modified Hilbert axiomatic standards(clearly defined concepts,logical consistency,unrefuted axioms)and dynamic demarcation criteria.Abandoning unattainable traditional requirements of completeness and independence,it emphasizes conceptual clarity,openness,and progressiveness,offering an operational,self-consistent basis for judging scientificity.
基金financially supported by the National Natural Science Foundation of China(No.52363007)。
文摘Recycling of waste rubber(WR)is crucial for the sustainable development of the rubber industry.The enhancement of interfacial interactions is the main strategy for waste polymer recycling.However,there is a lack of methods for enhancing the interfacial interactions for WR recycling because WR contains abundant inert C―H bonds.Herein,we designed thioctic acid inverse vulcanization copolymers to endow recycled WR with dynamic disulfide interfacial interactions,significantly improving the mechanical properties of recycled WR.These disulfide interfacial interactions among the recycled WR tend to exchange,which dramatically increases the fractocohesive length and prevents stress concentration near the crack tips.When recycled WR is subjected to external stress,the loads are redistributed across a broad region of adjacent regions instead of being concentrated on a limited length scale,which resists crack propagation.This work effectively recycled WR,providing a strategy for solvent-free reaction-derived inverse vulcanization copolymers to improve the toughness of WR recycling.
基金the National Key Research&Development Program of China(Grant No.2022YFC2203901)the State Key Laboratory of Spatial Datum(Grant No.SKLSD2025-KF-03)+1 种基金Fundamental Research Funds for the Central UniversitiesSun Yat-sen University for the support。
文摘The space gravitational wave detection aims to detect gravitational waves in the mHz band in order to study supermassive black hole mergers,galaxy evolution and the structure of the early universe.One of its core payloads is a transponder-type interstellar laser interferometer,designed to measure relative displacement changes at the pico-meter level.Among its components,phasemeter is tasked with extracting the phase and frequency of the interference signal.Currently,phase-locked loop(PLL)phasemeters are commonly employed.However,the second harmonic signal generated by the mixer can restrict both the dynamic range and phase measurement accuracy of the phasemeter.This paper analyzes the interstellar laser interferometer and the impact of the second harmonic signal on the phasemeter's performance.To address these challenges,a phasemeter incorporating a second harmonic signal filter is proposed.This new design mitigates second harmonic disturbances within the phasemeter's bandwidth by dynamically adjusting the filter's cutoff frequency to track the input signal frequency,thereby suppressing the second harmonic signal in real time.Theoretical and simulation analyses demonstrate that the proposed phasemeter with a second harmonic filter significantly enhances the dynamic range.Finally,experimental results verify that the phasemeter can achieve the tracking of sudden frequency changes up to4.8 MHz.
基金support from the Joint Funds of the National Natural Science Foundation of China(Grant No.U23A2060)the National Natural Science Foundation of China(Grant Nos.42177143 and 52474150).
文摘Drilling and blasting tunneling is a cyclic process in which tunnel rock undergoes repeated blast loading,affecting its dynamic characteristics,energy evolution,and damage progression.To explore the dynamic mechanical properties and damage mechanisms of carbonaceous slate under cyclic impact loads of varying intensities,cyclic dynamic tests are conducted using a triaxial split Hopkinson pressure bar.This study analyzes the stress-strain relationship,energy damage evolution,and macro-to-micro failure characteristics.The results show that peak stress and strain are significantly influenced by impact intensity and the number of impacts.The initial dynamic stress is positively correlated with the impact intensity,but with more impact,the dynamic stress decreases while the peak strain increases.Energy evolution follows a pattern of"slow growthfluctuating growthrapid growth,"with the crack initiation stress and its proportion decreasing.CT and SEM analyses reveal that as the impact intensity increases,failure becomes more chaotic,the fracture volume increases,and the fracture mode shifts from interlayer and intergranular to through-layer and trans-granular fractures.These findings provide an experimental basis for soft rock tunnel stability analysis.
基金supported by the SungKyunKwan University and the BK21 FOUR(Graduate School Innovation)funded by the Ministry of Education(MOE,Korea)and National Research Foundation of Korea(NRF).
文摘With the recent increase in data volume and diversity,traditional text representation techniques are struggling to capture context,particularly in environments with sparse data.To address these challenges,this study proposes a new model,the Masked Joint Representation Model(MJRM).MJRM approximates the original hypothesis by leveraging multiple elements in a limited context.It dynamically adapts to changes in characteristics based on data distribution through three main components.First,masking-based representation learning,termed selective dynamic masking,integrates topic modeling and sentiment clustering to generate and train multiple instances across different data subsets,whose predictions are then aggregated with optimized weights.This design alleviates sparsity,suppresses noise,and preserves contextual structures.Second,regularization-based improvements are applied.Third,techniques for addressing sparse data are used to perform final inference.As a result,MJRM improves performance by up to 4%compared to existing AI techniques.In our experiments,we analyzed the contribution of each factor,demonstrating that masking,dynamic learning,and aggregating multiple instances complement each other to improve performance.This demonstrates that a masking-based multi-learning strategy is effective for context-aware sparse text classification,and can be useful even in challenging situations such as data shortage or data distribution variations.We expect that the approach can be extended to diverse fields such as sentiment analysis,spam filtering,and domain-specific document classification.
