Currently,the demand for electromagnetic wave(EMW)absorbing materials with specific functions and capable of withstanding harsh environments is becoming increasingly urgent.Multi-component interface engineering is con...Currently,the demand for electromagnetic wave(EMW)absorbing materials with specific functions and capable of withstanding harsh environments is becoming increasingly urgent.Multi-component interface engineering is considered an effective means to achieve high-efficiency EMW absorption.However,interface modulation engineering has not been fully discussed and has great potential in the field of EMW absorption.In this study,multi-component tin compound fiber composites based on carbon fiber(CF)substrate were prepared by electrospinning,hydrothermal synthesis,and high-temperature thermal reduction.By utilizing the different properties of different substances,rich heterogeneous interfaces are constructed.This effectively promotes charge transfer and enhances interfacial polarization and conduction loss.The prepared SnS/SnS_(2)/SnO_(2)/CF composites with abundant heterogeneous interfaces have and exhibit excellent EMW absorption properties at a loading of 50 wt%in epoxy resin.The minimum reflection loss(RL)is−46.74 dB and the maximum effective absorption bandwidth is 5.28 GHz.Moreover,SnS/SnS_(2)/SnO_(2)/CF epoxy composite coatings exhibited long-term corrosion resistance on Q235 steel surfaces.Therefore,this study provides an effective strategy for the design of high-efficiency EMW absorbing materials in complex and harsh environments.展开更多
Precisely estimating the state of health(SOH)of lithium-ion batteries is essential for battery management systems(BMS),as it plays a key role in ensuring the safe and reliable operation of battery systems.However,curr...Precisely estimating the state of health(SOH)of lithium-ion batteries is essential for battery management systems(BMS),as it plays a key role in ensuring the safe and reliable operation of battery systems.However,current SOH estimation methods often overlook the valuable temperature information that can effectively characterize battery aging during capacity degradation.Additionally,the Elman neural network,which is commonly employed for SOH estimation,exhibits several drawbacks,including slow training speed,a tendency to become trapped in local minima,and the initialization of weights and thresholds using pseudo-random numbers,leading to unstable model performance.To address these issues,this study addresses the challenge of precise and effective SOH detection by proposing a method for estimating the SOH of lithium-ion batteries based on differential thermal voltammetry(DTV)and an SSA-Elman neural network.Firstly,two health features(HFs)considering temperature factors and battery voltage are extracted fromthe differential thermal voltammetry curves and incremental capacity curves.Next,the Sparrow Search Algorithm(SSA)is employed to optimize the initial weights and thresholds of the Elman neural network,forming the SSA-Elman neural network model.To validate the performance,various neural networks,including the proposed SSA-Elman network,are tested using the Oxford battery aging dataset.The experimental results demonstrate that the method developed in this study achieves superior accuracy and robustness,with a mean absolute error(MAE)of less than 0.9%and a rootmean square error(RMSE)below 1.4%.展开更多
Complex network models are frequently employed for simulating and studyingdiverse real-world complex systems.Among these models,scale-free networks typically exhibit greater fragility to malicious attacks.Consequently...Complex network models are frequently employed for simulating and studyingdiverse real-world complex systems.Among these models,scale-free networks typically exhibit greater fragility to malicious attacks.Consequently,enhancing the robustness of scale-free networks has become a pressing issue.To address this problem,this paper proposes a Multi-Granularity Integration Algorithm(MGIA),which aims to improve the robustness of scale-free networks while keeping the initial degree of each node unchanged,ensuring network connectivity and avoiding the generation of multiple edges.The algorithm generates a multi-granularity structure from the initial network to be optimized,then uses different optimization strategies to optimize the networks at various granular layers in this structure,and finally realizes the information exchange between different granular layers,thereby further enhancing the optimization effect.We propose new network refresh,crossover,and mutation operators to ensure that the optimized network satisfies the given constraints.Meanwhile,we propose new network similarity and network dissimilarity evaluation metrics to improve the effectiveness of the optimization operators in the algorithm.In the experiments,the MGIA enhances the robustness of the scale-free network by 67.6%.This improvement is approximately 17.2%higher than the optimization effects achieved by eight currently existing complex network robustness optimization algorithms.展开更多
Accurate short-term wind power forecast technique plays a crucial role in maintaining the safety and economic efficiency of smart grids.Although numerous studies have employed various methods to forecast wind power,th...Accurate short-term wind power forecast technique plays a crucial role in maintaining the safety and economic efficiency of smart grids.Although numerous studies have employed various methods to forecast wind power,there remains a research gap in leveraging swarm intelligence algorithms to optimize the hyperparameters of the Transformer model for wind power prediction.To improve the accuracy of short-term wind power forecast,this paper proposes a hybrid short-term wind power forecast approach named STL-IAOA-iTransformer,which is based on seasonal and trend decomposition using LOESS(STL)and iTransformer model optimized by improved arithmetic optimization algorithm(IAOA).First,to fully extract the power data features,STL is used to decompose the original data into components with less redundant information.The extracted components as well as the weather data are then input into iTransformer for short-term wind power forecast.The final predicted short-term wind power curve is obtained by combining the predicted components.To improve the model accuracy,IAOA is employed to optimize the hyperparameters of iTransformer.The proposed approach is validated using real-generation data from different seasons and different power stations inNorthwest China,and ablation experiments have been conducted.Furthermore,to validate the superiority of the proposed approach under different wind characteristics,real power generation data fromsouthwestChina are utilized for experiments.Thecomparative results with the other six state-of-the-art prediction models in experiments show that the proposed model well fits the true value of generation series and achieves high prediction accuracy.展开更多
The pre-wetting of aggregate surface is a means to improve the interface performance of SBS modified asphalt and aggregate.The effect of pre-wetting technology on the interaction between SBS modified asphalt and aggre...The pre-wetting of aggregate surface is a means to improve the interface performance of SBS modified asphalt and aggregate.The effect of pre-wetting technology on the interaction between SBS modified asphalt and aggregate was analyzed by molecular dynamics simulation.The diffusion coefficient and concentration distribution of SBS modified asphalt on aggregate surface are included.The simulation results show that the diffusion coefficient of the aggregate surface of SBS modified asphalt is increased by 47.6%and 70.5%respectively after 110#asphalt and 130#asphalt are pre-wetted.The concentration distribution of SBS modified asphalt on the aggregate surface after pre-wetting is more uniform.According to the results of interface energy calculation,the interface energy of SBS modified bitumen and aggregate can be increased by about 5%after pre-wetting.According to the results of molecular dynamics simulation,the pre-wetting technology can effectively improve the interface workability of SBS modified bitumen and aggregate,so as to improve the interface performance.展开更多
In disaster relief operations,multiple UAVs can be used to search for trapped people.In recent years,many researchers have proposed machine le arning-based algorithms,sampling-based algorithms,and heuristic algorithms...In disaster relief operations,multiple UAVs can be used to search for trapped people.In recent years,many researchers have proposed machine le arning-based algorithms,sampling-based algorithms,and heuristic algorithms to solve the problem of multi-UAV path planning.The Dung Beetle Optimization(DBO)algorithm has been widely applied due to its diverse search patterns in the above algorithms.However,the update strategies for the rolling and thieving dung beetles of the DBO algorithm are overly simplistic,potentially leading to an inability to fully explore the search space and a tendency to converge to local optima,thereby not guaranteeing the discovery of the optimal path.To address these issues,we propose an improved DBO algorithm guided by the Landmark Operator(LODBO).Specifically,we first use tent mapping to update the population strategy,which enables the algorithm to generate initial solutions with enhanced diversity within the search space.Second,we expand the search range of the rolling ball dung beetle by using the landmark factor.Finally,by using the adaptive factor that changes with the number of iterations.,we improve the global search ability of the stealing dung beetle,making it more likely to escape from local optima.To verify the effectiveness of the proposed method,extensive simulation experiments are conducted,and the result shows that the LODBO algorithm can obtain the optimal path using the shortest time compared with the Genetic Algorithm(GA),the Gray Wolf Optimizer(GWO),the Whale Optimization Algorithm(WOA)and the original DBO algorithm in the disaster search and rescue task set.展开更多
In this paper,we prove that Euclid's algorithm,Bezout's equation and Divi-sion algorithm are equivalent to each other.Our result shows that Euclid has preliminarily established the theory of divisibility and t...In this paper,we prove that Euclid's algorithm,Bezout's equation and Divi-sion algorithm are equivalent to each other.Our result shows that Euclid has preliminarily established the theory of divisibility and the greatest common divisor.We further provided several suggestions for teaching.展开更多
Silicon stands as a key anode material in lithium-ion battery ascribing to its high energy density.Nevertheless,the poor rate performance and limited cycling life remain unresolved through conventional approaches that...Silicon stands as a key anode material in lithium-ion battery ascribing to its high energy density.Nevertheless,the poor rate performance and limited cycling life remain unresolved through conventional approaches that involve carbon composites or nanostructures,primarily due to the un-controllable effects arising from the substantial formation of a solid electrolyte interphase(SEI)during the cycling.Here,an ultra-thin and homogeneous Ti doping alumina oxide catalytic interface is meticulously applied on the porous Si through a synergistic etching and hydrolysis process.This defect-rich oxide interface promotes a selective adsorption of fluoroethylene carbonate,leading to a catalytic reaction that can be aptly described as“molecular concentration-in situ conversion”.The resultant inorganic-rich SEI layer is electrochemical stable and favors ion-transport,particularly at high-rate cycling and high temperature.The robustly shielded porous Si,with a large surface area,achieves a high initial Coulombic efficiency of 84.7%and delivers exceptional high-rate performance at 25 A g^(−1)(692 mAh g^(−1))and a high Coulombic efficiency of 99.7%over 1000 cycles.The robust SEI constructed through a precious catalytic layer promises significant advantages for the fast development of silicon-based anode in fast-charging batteries.展开更多
The poor reversibility and stability of Zn anodes greatly restrict the practical application of aqueous Zn-ion batteries(AZIBs),resulting from the uncontrollable dendrite growth and H_(2)O-induced side reactions durin...The poor reversibility and stability of Zn anodes greatly restrict the practical application of aqueous Zn-ion batteries(AZIBs),resulting from the uncontrollable dendrite growth and H_(2)O-induced side reactions during cycling.Electrolyte additive modification is considered one of the most effective and simplest methods for solving the aforementioned problems.Herein,the pyridine derivatives(PD)including 2,4-dihydroxypyridine(2,4-DHP),2,3-dihydroxypyridine(2,3-DHP),and 2-hydroxypyrdine(2-DHP),were em-ployed as novel electrolyte additives in ZnSO_(4)electrolyte.Both density functional theory calculation and experimental findings demonstrated that the incorporation of PD additives into the electrolyte effectively modulates the solvation structure of hydrated Zn ions,thereby suppressing side reactions in AZIBs.Ad-ditionally,the adsorption of PD molecules on the zinc anode surface contributed to uniform Zn deposi-tion and dendrite growth inhibition.Consequently,a 2,4-DHP-modified Zn/Zn symmetrical cell achieved an extremely long cyclic stability up to 5650 h at 1 mA cm^(-2).Furthermore,the Zn/NH_(4)V_(4)O_(10)full cell with 2,4-DHP-containing electrolyte exhibited an outstanding initial capacity of 204 mAh g^(-1),with a no-table capacity retention of 79%after 1000 cycles at 5 A g^(-1).Hence,this study expands the selection of electrolyte additives for AZIBs,and the working mechanism of PD additives provides new insights for electrolyte modification enabling highly reversible zinc anode.展开更多
Brain-computer interfaces(BCIs)represent an emerging technology that facilitates direct communication between the brain and external devices.In recent years,numerous review articles have explored various aspects of BC...Brain-computer interfaces(BCIs)represent an emerging technology that facilitates direct communication between the brain and external devices.In recent years,numerous review articles have explored various aspects of BCIs,including their fundamental principles,technical advancements,and applications in specific domains.However,these reviews often focus on signal processing,hardware development,or limited applications such as motor rehabilitation or communication.This paper aims to offer a comprehensive review of recent electroencephalogram(EEG)-based BCI applications in the medical field across 8 critical areas,encompassing rehabilitation,daily communication,epilepsy,cerebral resuscitation,sleep,neurodegenerative diseases,anesthesiology,and emotion recognition.Moreover,the current challenges and future trends of BCIs were also discussed,including personal privacy and ethical concerns,network security vulnerabilities,safety issues,and biocompatibility.展开更多
Forced imbibition,the invasion of a wetting fluid into porous rocks,plays an important role in the effective exploitation of hydrocarbon resources and the geological sequestration of carbon dioxide.However,the interfa...Forced imbibition,the invasion of a wetting fluid into porous rocks,plays an important role in the effective exploitation of hydrocarbon resources and the geological sequestration of carbon dioxide.However,the interface dynamics influenced by complex topology commonly leads to non-wetting fluid trapping.Particularly,the underlying mechanisms under viscously unfavorable conditions remain unclear.This study employs a direct numerical simulation method to simulate forced imbibition through the reconstructed digital rocks of sandstone.The interface dynamics and fluid–fluid interactions are investigated through transient simulations,while the pore topology metrics are introduced to analyze the impact on steady-state residual fluid distribution obtained by a pseudo-transient scheme.The results show that the cooperative pore-filling process promoted by corner flow is dominant at low capillary numbers.This leads to unstable inlet pressure,mass flow,and interface curvature,which correspond to complicated interface dynamics and higher residual fluid saturation.During forced imbibition,the interface curvature gradually increases,with the pore-filling mechanisms involving the cooperation of main terminal meniscus movement and arc menisci filling.Complex topology with small diameter pores may result in the destabilization of interface curvature.The residual fluid saturation is negatively correlated with porosity and pore throat size,and positively correlated with tortuosity and aspect ratio.A large mean coordination number characterizing global connectivity promotes imbibition.However,high connectivity characterized by the standardized Euler number corresponding to small pores is associated with a high probability of non-wetting fluid trapping.展开更多
In order to solve the problem of poor formability caused by different materials and properties in the process of tailor-welded sheets forming,a forming method was proposed to change the stress state of tailor-welded s...In order to solve the problem of poor formability caused by different materials and properties in the process of tailor-welded sheets forming,a forming method was proposed to change the stress state of tailor-welded sheets by covering the tailor-welded sheets with better plastic properties overlapping sheets.At the same time,the interface friction effect between the overlapping and tailor-welded sheets was utilized to control the stress magnitude and further improve the formability and quality of the tailor-welded sheets.In this work,the bulging process of the tailor-welded overlapping sheets was taken as the research object.Aluminum alloy tailor-welded overlapping sheets bulging specimens were studied by a combination of finite element analysis and experimental verification.The results show that the appropriate use of interface friction between tailor-welded and overlapping sheets can improve the formability of tailor-welded sheets and control the flow of weld seam to improve the forming quality.When increasing the interface friction coefficient on the side of tailor-welded sheets with higher strength and decreasing that on the side of tailor-welded sheets with lower strength,the deformation of the tailor-welded sheets are more uniform,the offset of the weld seam is minimal,the limit bulging height is maximal,and the forming quality is optimal.展开更多
Previous studies have shown that deep learning is very effective in detecting known attacks.However,when facing unknown attacks,models such as Deep Neural Networks(DNN)combined with Long Short-Term Memory(LSTM),Convol...Previous studies have shown that deep learning is very effective in detecting known attacks.However,when facing unknown attacks,models such as Deep Neural Networks(DNN)combined with Long Short-Term Memory(LSTM),Convolutional Neural Networks(CNN)combined with LSTM,and so on are built by simple stacking,which has the problems of feature loss,low efficiency,and low accuracy.Therefore,this paper proposes an autonomous detectionmodel for Distributed Denial of Service attacks,Multi-Scale Convolutional Neural Network-Bidirectional Gated Recurrent Units-Single Headed Attention(MSCNN-BiGRU-SHA),which is based on a Multistrategy Integrated Zebra Optimization Algorithm(MI-ZOA).The model undergoes training and testing with the CICDDoS2019 dataset,and its performance is evaluated on a new GINKS2023 dataset.The hyperparameters for Conv_filter and GRU_unit are optimized using the Multi-strategy Integrated Zebra Optimization Algorithm(MIZOA).The experimental results show that the test accuracy of the MSCNN-BiGRU-SHA model based on the MIZOA proposed in this paper is as high as 0.9971 in the CICDDoS 2019 dataset.The evaluation accuracy of the new dataset GINKS2023 created in this paper is 0.9386.Compared to the MSCNN-BiGRU-SHA model based on the Zebra Optimization Algorithm(ZOA),the detection accuracy on the GINKS2023 dataset has improved by 5.81%,precisionhas increasedby 1.35%,the recallhas improvedby 9%,and theF1scorehas increasedby 5.55%.Compared to the MSCNN-BiGRU-SHA models developed using Grid Search,Random Search,and Bayesian Optimization,the MSCNN-BiGRU-SHA model optimized with the MI-ZOA exhibits better performance in terms of accuracy,precision,recall,and F1 score.展开更多
Open caissons are widely used in foundation engineering because of their load-bearing efficiency and adaptability in diverse soil conditions.However,accurately predicting their undrained bearing capacity in layered so...Open caissons are widely used in foundation engineering because of their load-bearing efficiency and adaptability in diverse soil conditions.However,accurately predicting their undrained bearing capacity in layered soils remains a complex challenge.This study presents a novel application of five ensemble machine(ML)algorithms-random forest(RF),gradient boosting machine(GBM),extreme gradient boosting(XGBoost),adaptive boosting(AdaBoost),and categorical boosting(CatBoost)-to predict the undrained bearing capacity factor(Nc)of circular open caissons embedded in two-layered clay on the basis of results from finite element limit analysis(FELA).The input dataset consists of 1188 numerical simulations using the Tresca failure criterion,varying in geometrical and soil parameters.The FELA was performed via OptumG2 software with adaptive meshing techniques and verified against existing benchmark studies.The ML models were trained on 70% of the dataset and tested on the remaining 30%.Their performance was evaluated using six statistical metrics:coefficient of determination(R²),mean absolute error(MAE),root mean squared error(RMSE),index of scatter(IOS),RMSE-to-standard deviation ratio(RSR),and variance explained factor(VAF).The results indicate that all the models achieved high accuracy,with R²values exceeding 97.6%and RMSE values below 0.02.Among them,AdaBoost and CatBoost consistently outperformed the other methods across both the training and testing datasets,demonstrating superior generalizability and robustness.The proposed ML framework offers an efficient,accurate,and data-driven alternative to traditional methods for estimating caisson capacity in stratified soils.This approach can aid in reducing computational costs while improving reliability in the early stages of foundation design.展开更多
As a mathematical analysis method,fractal analysis can be used to quantitatively describe irregular shapes with self-similar or self-affine properties.Fractal analysis has been used to characterize the shapes of metal...As a mathematical analysis method,fractal analysis can be used to quantitatively describe irregular shapes with self-similar or self-affine properties.Fractal analysis has been used to characterize the shapes of metal materials at various scales and dimensions.Conventional methods make it difficult to quantitatively describe the relationship between the regular characteristics and properties of metal material surfaces and interfaces.However,fractal analysis can be used to quantitatively describe the shape characteristics of metal materials and to establish the quantitative relationships between the shape characteristics and various properties of metal materials.From the perspective of two-dimensional planes and three-dimensional curved surfaces,this paper reviews the current research status of the fractal analysis of metal precipitate interfaces,metal grain boundary interfaces,metal-deposited film surfaces,metal fracture surfaces,metal machined surfaces,and metal wear surfaces.The relationship between the fractal dimensions and properties of metal material surfaces and interfaces is summarized.Starting from three perspectives of fractal analysis,namely,research scope,image acquisition methods,and calculation methods,this paper identifies the direction of research on fractal analysis of metal material surfaces and interfaces that need to be developed.It is believed that revealing the deep influence mechanism between the fractal dimensions and properties of metal material surfaces and interfaces will be the key research direction of the fractal analysis of metal materials in the future.展开更多
Research efforts on electromagnetic interference(EMI)shielding materials have begun to converge on green and sustainable biomass materials.These materials offer numerous advantages such as being lightweight,porous,and...Research efforts on electromagnetic interference(EMI)shielding materials have begun to converge on green and sustainable biomass materials.These materials offer numerous advantages such as being lightweight,porous,and hierarchical.Due to their porous nature,interfacial compatibility,and electrical conductivity,biomass materials hold significant potential as EMI shielding materials.Despite concerted efforts on the EMI shielding of biomass materials have been reported,this research area is still relatively new compared to traditional EMI shielding materials.In particular,a more comprehensive study and summary of the factors influencing biomass EMI shielding materials including the pore structure adjustment,preparation process,and micro-control would be valuable.The preparation methods and characteristics of wood,bamboo,cellulose and lignin in EMI shielding field are critically discussed in this paper,and similar biomass EMI materials are summarized and analyzed.The composite methods and fillers of various biomass materials were reviewed.this paper also highlights the mechanism of EMI shielding as well as existing prospects and challenges for development trends in this field.展开更多
To improve the efficiency and accuracy of path planning for fan inspection tasks in thermal power plants,this paper proposes an intelligent inspection robot path planning scheme based on an improved A^(*)algorithm.The...To improve the efficiency and accuracy of path planning for fan inspection tasks in thermal power plants,this paper proposes an intelligent inspection robot path planning scheme based on an improved A^(*)algorithm.The inspection robot utilizes multiple sensors to monitor key parameters of the fans,such as vibration,noise,and bearing temperature,and upload the data to the monitoring center.The robot’s inspection path employs the improved A^(*)algorithm,incorporating obstacle penalty terms,path reconstruction,and smoothing optimization techniques,thereby achieving optimal path planning for the inspection robot in complex environments.Simulation results demonstrate that the improved A^(*)algorithm significantly outperforms the traditional A^(*)algorithm in terms of total path distance,smoothness,and detour rate,effectively improving the execution efficiency of inspection tasks.展开更多
In order to improve the efficiency of cloud-based web services,an improved plant growth simulation algorithm scheduling model.This model first used mathematical methods to describe the relationships between cloud-base...In order to improve the efficiency of cloud-based web services,an improved plant growth simulation algorithm scheduling model.This model first used mathematical methods to describe the relationships between cloud-based web services and the constraints of system resources.Then,a light-induced plant growth simulation algorithm was established.The performance of the algorithm was compared through several plant types,and the best plant model was selected as the setting for the system.Experimental results show that when the number of test cloud-based web services reaches 2048,the model being 2.14 times faster than PSO,2.8 times faster than the ant colony algorithm,2.9 times faster than the bee colony algorithm,and a remarkable 8.38 times faster than the genetic algorithm.展开更多
A new method based on the iterative adaptive algorithm(IAA)and blocking matrix preprocessing(BMP)is proposed to study the suppression of multi-mainlobe interference.The algorithm is applied to precisely estimate the s...A new method based on the iterative adaptive algorithm(IAA)and blocking matrix preprocessing(BMP)is proposed to study the suppression of multi-mainlobe interference.The algorithm is applied to precisely estimate the spatial spectrum and the directions of arrival(DOA)of interferences to overcome the drawbacks associated with conventional adaptive beamforming(ABF)methods.The mainlobe interferences are identified by calculating the correlation coefficients between direction steering vectors(SVs)and rejected by the BMP pretreatment.Then,IAA is subsequently employed to reconstruct a sidelobe interference-plus-noise covariance matrix for the preferable ABF and residual interference suppression.Simulation results demonstrate the excellence of the proposed method over normal methods based on BMP and eigen-projection matrix perprocessing(EMP)under both uncorrelated and coherent circumstances.展开更多
The Rock-soil interface is a common geological interface.Due to mechanical differences between soil and rock,the stress waves generated by underground blasting undergo intense polarization when crossing the rock-soil ...The Rock-soil interface is a common geological interface.Due to mechanical differences between soil and rock,the stress waves generated by underground blasting undergo intense polarization when crossing the rock-soil interface,making propagation laws difficult to predict.Currently,the characteristics of the impact of the rock-soil interface on blasting stress waves remain unclear.Therefore,the vibration field caused by cylindrical charge blasting in elastic rock and partial-saturation poro-viscoelastic soil was solved.A forward algorithm for the underground blasting vibration field in rock-soil sites was proposed,considering medium damping and geometric diffusion effects of stress waves.Further investigation into the influence of rock and soil parameters and blasting source parameters revealed the following conclusions:stress waves in soil exhibit dispersion,causing peak particle velocity(PPV)to display a discrete distribution.Soil parameters affect PPV attenuation only within the soil,while blasting source parameters affect PPV attenuation throughout the entire site.Multi-wave coupling effects induced by the rocksoil interface result in zones of enhanced and attenuated PPV within the site.The size of the enhancement zone is inversely correlated with the distance from the blasting source and positively correlated with the blasting source attenuation rate and burial depth,providing guidance for selecting explosives and blasting positions.Additionally,PPV attenuation rate increases with distance from the rock-soil interface,but an amplification effect occurs near the interface,most noticeable at 0.1 m.Thus,a sufficient safety distance from the rock-soil interface is necessary during underground blasting.展开更多
基金financially supported by the National Natural Science Foundation of China(No.52377026 and No.52301192)Taishan Scholars and Young Experts Program of Shandong Province(No.tsqn202103057)+4 种基金Postdoctoral Fellowship Program of CPSF under Grant Number(No.GZB20240327)Shandong Postdoctoral Science Foundation(No.SDCXZG-202400275)Qingdao Postdoctoral Application Research Project(No.QDBSH20240102023)China Postdoctoral Science Foundation(No.2024M751563)the Qingchuang Talents Induction Program of Shandong Higher Education Institution(Research and Innovation Team of Structural-Functional Polymer Composites).
文摘Currently,the demand for electromagnetic wave(EMW)absorbing materials with specific functions and capable of withstanding harsh environments is becoming increasingly urgent.Multi-component interface engineering is considered an effective means to achieve high-efficiency EMW absorption.However,interface modulation engineering has not been fully discussed and has great potential in the field of EMW absorption.In this study,multi-component tin compound fiber composites based on carbon fiber(CF)substrate were prepared by electrospinning,hydrothermal synthesis,and high-temperature thermal reduction.By utilizing the different properties of different substances,rich heterogeneous interfaces are constructed.This effectively promotes charge transfer and enhances interfacial polarization and conduction loss.The prepared SnS/SnS_(2)/SnO_(2)/CF composites with abundant heterogeneous interfaces have and exhibit excellent EMW absorption properties at a loading of 50 wt%in epoxy resin.The minimum reflection loss(RL)is−46.74 dB and the maximum effective absorption bandwidth is 5.28 GHz.Moreover,SnS/SnS_(2)/SnO_(2)/CF epoxy composite coatings exhibited long-term corrosion resistance on Q235 steel surfaces.Therefore,this study provides an effective strategy for the design of high-efficiency EMW absorbing materials in complex and harsh environments.
基金supported by the National Natural Science Foundation of China(NSFC)under Grant(No.51677058).
文摘Precisely estimating the state of health(SOH)of lithium-ion batteries is essential for battery management systems(BMS),as it plays a key role in ensuring the safe and reliable operation of battery systems.However,current SOH estimation methods often overlook the valuable temperature information that can effectively characterize battery aging during capacity degradation.Additionally,the Elman neural network,which is commonly employed for SOH estimation,exhibits several drawbacks,including slow training speed,a tendency to become trapped in local minima,and the initialization of weights and thresholds using pseudo-random numbers,leading to unstable model performance.To address these issues,this study addresses the challenge of precise and effective SOH detection by proposing a method for estimating the SOH of lithium-ion batteries based on differential thermal voltammetry(DTV)and an SSA-Elman neural network.Firstly,two health features(HFs)considering temperature factors and battery voltage are extracted fromthe differential thermal voltammetry curves and incremental capacity curves.Next,the Sparrow Search Algorithm(SSA)is employed to optimize the initial weights and thresholds of the Elman neural network,forming the SSA-Elman neural network model.To validate the performance,various neural networks,including the proposed SSA-Elman network,are tested using the Oxford battery aging dataset.The experimental results demonstrate that the method developed in this study achieves superior accuracy and robustness,with a mean absolute error(MAE)of less than 0.9%and a rootmean square error(RMSE)below 1.4%.
基金National Natural Science Foundation of China(11971211,12171388).
文摘Complex network models are frequently employed for simulating and studyingdiverse real-world complex systems.Among these models,scale-free networks typically exhibit greater fragility to malicious attacks.Consequently,enhancing the robustness of scale-free networks has become a pressing issue.To address this problem,this paper proposes a Multi-Granularity Integration Algorithm(MGIA),which aims to improve the robustness of scale-free networks while keeping the initial degree of each node unchanged,ensuring network connectivity and avoiding the generation of multiple edges.The algorithm generates a multi-granularity structure from the initial network to be optimized,then uses different optimization strategies to optimize the networks at various granular layers in this structure,and finally realizes the information exchange between different granular layers,thereby further enhancing the optimization effect.We propose new network refresh,crossover,and mutation operators to ensure that the optimized network satisfies the given constraints.Meanwhile,we propose new network similarity and network dissimilarity evaluation metrics to improve the effectiveness of the optimization operators in the algorithm.In the experiments,the MGIA enhances the robustness of the scale-free network by 67.6%.This improvement is approximately 17.2%higher than the optimization effects achieved by eight currently existing complex network robustness optimization algorithms.
基金supported by Yunnan Provincial Basic Research Project(202401AT070344,202301AT070443)National Natural Science Foundation of China(62263014,52207105)+1 种基金Yunnan Lancang-Mekong International Electric Power Technology Joint Laboratory(202203AP140001)Major Science and Technology Projects in Yunnan Province(202402AG050006).
文摘Accurate short-term wind power forecast technique plays a crucial role in maintaining the safety and economic efficiency of smart grids.Although numerous studies have employed various methods to forecast wind power,there remains a research gap in leveraging swarm intelligence algorithms to optimize the hyperparameters of the Transformer model for wind power prediction.To improve the accuracy of short-term wind power forecast,this paper proposes a hybrid short-term wind power forecast approach named STL-IAOA-iTransformer,which is based on seasonal and trend decomposition using LOESS(STL)and iTransformer model optimized by improved arithmetic optimization algorithm(IAOA).First,to fully extract the power data features,STL is used to decompose the original data into components with less redundant information.The extracted components as well as the weather data are then input into iTransformer for short-term wind power forecast.The final predicted short-term wind power curve is obtained by combining the predicted components.To improve the model accuracy,IAOA is employed to optimize the hyperparameters of iTransformer.The proposed approach is validated using real-generation data from different seasons and different power stations inNorthwest China,and ablation experiments have been conducted.Furthermore,to validate the superiority of the proposed approach under different wind characteristics,real power generation data fromsouthwestChina are utilized for experiments.Thecomparative results with the other six state-of-the-art prediction models in experiments show that the proposed model well fits the true value of generation series and achieves high prediction accuracy.
基金Funded by the Research Funds of China University of Mining and Technology(No.102523215)。
文摘The pre-wetting of aggregate surface is a means to improve the interface performance of SBS modified asphalt and aggregate.The effect of pre-wetting technology on the interaction between SBS modified asphalt and aggregate was analyzed by molecular dynamics simulation.The diffusion coefficient and concentration distribution of SBS modified asphalt on aggregate surface are included.The simulation results show that the diffusion coefficient of the aggregate surface of SBS modified asphalt is increased by 47.6%and 70.5%respectively after 110#asphalt and 130#asphalt are pre-wetted.The concentration distribution of SBS modified asphalt on the aggregate surface after pre-wetting is more uniform.According to the results of interface energy calculation,the interface energy of SBS modified bitumen and aggregate can be increased by about 5%after pre-wetting.According to the results of molecular dynamics simulation,the pre-wetting technology can effectively improve the interface workability of SBS modified bitumen and aggregate,so as to improve the interface performance.
基金supported by the National Natural Science Foundation of China(No.62373027).
文摘In disaster relief operations,multiple UAVs can be used to search for trapped people.In recent years,many researchers have proposed machine le arning-based algorithms,sampling-based algorithms,and heuristic algorithms to solve the problem of multi-UAV path planning.The Dung Beetle Optimization(DBO)algorithm has been widely applied due to its diverse search patterns in the above algorithms.However,the update strategies for the rolling and thieving dung beetles of the DBO algorithm are overly simplistic,potentially leading to an inability to fully explore the search space and a tendency to converge to local optima,thereby not guaranteeing the discovery of the optimal path.To address these issues,we propose an improved DBO algorithm guided by the Landmark Operator(LODBO).Specifically,we first use tent mapping to update the population strategy,which enables the algorithm to generate initial solutions with enhanced diversity within the search space.Second,we expand the search range of the rolling ball dung beetle by using the landmark factor.Finally,by using the adaptive factor that changes with the number of iterations.,we improve the global search ability of the stealing dung beetle,making it more likely to escape from local optima.To verify the effectiveness of the proposed method,extensive simulation experiments are conducted,and the result shows that the LODBO algorithm can obtain the optimal path using the shortest time compared with the Genetic Algorithm(GA),the Gray Wolf Optimizer(GWO),the Whale Optimization Algorithm(WOA)and the original DBO algorithm in the disaster search and rescue task set.
基金Supported by the Natural Science Foundation of Chongqing(General Program,NO.CSTB2022NSCQ-MSX0884)Discipline Teaching Special Project of Yangtze Normal University(csxkjx14)。
文摘In this paper,we prove that Euclid's algorithm,Bezout's equation and Divi-sion algorithm are equivalent to each other.Our result shows that Euclid has preliminarily established the theory of divisibility and the greatest common divisor.We further provided several suggestions for teaching.
基金the National Key R&D Plan of the Ministry of Science and Technology of China(2022YFE0122400)National Natural Science Foundation of China(52002238,22102207)+1 种基金Science and Technology Commission of Shanghai Municipality(22ZR1423800,21ZR1465200,23ZR1423600)Shanghai Municipal Education Commission and the NSRF via the Program Management Unit for Human Resources&Institutional Development,Research and Innovation(B49G680115).
文摘Silicon stands as a key anode material in lithium-ion battery ascribing to its high energy density.Nevertheless,the poor rate performance and limited cycling life remain unresolved through conventional approaches that involve carbon composites or nanostructures,primarily due to the un-controllable effects arising from the substantial formation of a solid electrolyte interphase(SEI)during the cycling.Here,an ultra-thin and homogeneous Ti doping alumina oxide catalytic interface is meticulously applied on the porous Si through a synergistic etching and hydrolysis process.This defect-rich oxide interface promotes a selective adsorption of fluoroethylene carbonate,leading to a catalytic reaction that can be aptly described as“molecular concentration-in situ conversion”.The resultant inorganic-rich SEI layer is electrochemical stable and favors ion-transport,particularly at high-rate cycling and high temperature.The robustly shielded porous Si,with a large surface area,achieves a high initial Coulombic efficiency of 84.7%and delivers exceptional high-rate performance at 25 A g^(−1)(692 mAh g^(−1))and a high Coulombic efficiency of 99.7%over 1000 cycles.The robust SEI constructed through a precious catalytic layer promises significant advantages for the fast development of silicon-based anode in fast-charging batteries.
基金supported by the Key Science and Technol-ogy Program of Henan Province(No.232102241020)the Ph.D.Research Startup Foundation of Henan University of Science and Technology(No.400613480015)+1 种基金the Postdoctoral Research Startup Foundation of Henan University of Science and Technology(No.400613554001)the Natural Science Foundation of Henan Province(242300420021).
文摘The poor reversibility and stability of Zn anodes greatly restrict the practical application of aqueous Zn-ion batteries(AZIBs),resulting from the uncontrollable dendrite growth and H_(2)O-induced side reactions during cycling.Electrolyte additive modification is considered one of the most effective and simplest methods for solving the aforementioned problems.Herein,the pyridine derivatives(PD)including 2,4-dihydroxypyridine(2,4-DHP),2,3-dihydroxypyridine(2,3-DHP),and 2-hydroxypyrdine(2-DHP),were em-ployed as novel electrolyte additives in ZnSO_(4)electrolyte.Both density functional theory calculation and experimental findings demonstrated that the incorporation of PD additives into the electrolyte effectively modulates the solvation structure of hydrated Zn ions,thereby suppressing side reactions in AZIBs.Ad-ditionally,the adsorption of PD molecules on the zinc anode surface contributed to uniform Zn deposi-tion and dendrite growth inhibition.Consequently,a 2,4-DHP-modified Zn/Zn symmetrical cell achieved an extremely long cyclic stability up to 5650 h at 1 mA cm^(-2).Furthermore,the Zn/NH_(4)V_(4)O_(10)full cell with 2,4-DHP-containing electrolyte exhibited an outstanding initial capacity of 204 mAh g^(-1),with a no-table capacity retention of 79%after 1000 cycles at 5 A g^(-1).Hence,this study expands the selection of electrolyte additives for AZIBs,and the working mechanism of PD additives provides new insights for electrolyte modification enabling highly reversible zinc anode.
基金supported by the National Key R&D Program of China(2021YFF1200602)the National Science Fund for Excellent Overseas Scholars(0401260011)+3 种基金the National Defense Science and Technology Innovation Fund of Chinese Academy of Sciences(c02022088)the Tianjin Science and Technology Program(20JCZDJC00810)the National Natural Science Foundation of China(82202798)the Shanghai Sailing Program(22YF1404200).
文摘Brain-computer interfaces(BCIs)represent an emerging technology that facilitates direct communication between the brain and external devices.In recent years,numerous review articles have explored various aspects of BCIs,including their fundamental principles,technical advancements,and applications in specific domains.However,these reviews often focus on signal processing,hardware development,or limited applications such as motor rehabilitation or communication.This paper aims to offer a comprehensive review of recent electroencephalogram(EEG)-based BCI applications in the medical field across 8 critical areas,encompassing rehabilitation,daily communication,epilepsy,cerebral resuscitation,sleep,neurodegenerative diseases,anesthesiology,and emotion recognition.Moreover,the current challenges and future trends of BCIs were also discussed,including personal privacy and ethical concerns,network security vulnerabilities,safety issues,and biocompatibility.
基金supported by the National Natural Science Foundation of China(Grant Nos.42172159 and 42302143)the Postdoctora Fellowship Program of the China Postdoctoral Science Foundation(CPSF)(Grant No.GZB20230864).
文摘Forced imbibition,the invasion of a wetting fluid into porous rocks,plays an important role in the effective exploitation of hydrocarbon resources and the geological sequestration of carbon dioxide.However,the interface dynamics influenced by complex topology commonly leads to non-wetting fluid trapping.Particularly,the underlying mechanisms under viscously unfavorable conditions remain unclear.This study employs a direct numerical simulation method to simulate forced imbibition through the reconstructed digital rocks of sandstone.The interface dynamics and fluid–fluid interactions are investigated through transient simulations,while the pore topology metrics are introduced to analyze the impact on steady-state residual fluid distribution obtained by a pseudo-transient scheme.The results show that the cooperative pore-filling process promoted by corner flow is dominant at low capillary numbers.This leads to unstable inlet pressure,mass flow,and interface curvature,which correspond to complicated interface dynamics and higher residual fluid saturation.During forced imbibition,the interface curvature gradually increases,with the pore-filling mechanisms involving the cooperation of main terminal meniscus movement and arc menisci filling.Complex topology with small diameter pores may result in the destabilization of interface curvature.The residual fluid saturation is negatively correlated with porosity and pore throat size,and positively correlated with tortuosity and aspect ratio.A large mean coordination number characterizing global connectivity promotes imbibition.However,high connectivity characterized by the standardized Euler number corresponding to small pores is associated with a high probability of non-wetting fluid trapping.
基金Funded by the National Natural Science Foundation of China(Nos.52075347,51575364)and the Natural Science Foundation of Liaoning Provincial(No.2022-MS-295)。
文摘In order to solve the problem of poor formability caused by different materials and properties in the process of tailor-welded sheets forming,a forming method was proposed to change the stress state of tailor-welded sheets by covering the tailor-welded sheets with better plastic properties overlapping sheets.At the same time,the interface friction effect between the overlapping and tailor-welded sheets was utilized to control the stress magnitude and further improve the formability and quality of the tailor-welded sheets.In this work,the bulging process of the tailor-welded overlapping sheets was taken as the research object.Aluminum alloy tailor-welded overlapping sheets bulging specimens were studied by a combination of finite element analysis and experimental verification.The results show that the appropriate use of interface friction between tailor-welded and overlapping sheets can improve the formability of tailor-welded sheets and control the flow of weld seam to improve the forming quality.When increasing the interface friction coefficient on the side of tailor-welded sheets with higher strength and decreasing that on the side of tailor-welded sheets with lower strength,the deformation of the tailor-welded sheets are more uniform,the offset of the weld seam is minimal,the limit bulging height is maximal,and the forming quality is optimal.
基金supported by Science and Technology Innovation Programfor Postgraduate Students in IDP Subsidized by Fundamental Research Funds for the Central Universities(Project No.ZY20240335)support of the Research Project of the Key Technology of Malicious Code Detection Based on Data Mining in APT Attack(Project No.2022IT173)the Research Project of the Big Data Sensitive Information Supervision Technology Based on Convolutional Neural Network(Project No.2022011033).
文摘Previous studies have shown that deep learning is very effective in detecting known attacks.However,when facing unknown attacks,models such as Deep Neural Networks(DNN)combined with Long Short-Term Memory(LSTM),Convolutional Neural Networks(CNN)combined with LSTM,and so on are built by simple stacking,which has the problems of feature loss,low efficiency,and low accuracy.Therefore,this paper proposes an autonomous detectionmodel for Distributed Denial of Service attacks,Multi-Scale Convolutional Neural Network-Bidirectional Gated Recurrent Units-Single Headed Attention(MSCNN-BiGRU-SHA),which is based on a Multistrategy Integrated Zebra Optimization Algorithm(MI-ZOA).The model undergoes training and testing with the CICDDoS2019 dataset,and its performance is evaluated on a new GINKS2023 dataset.The hyperparameters for Conv_filter and GRU_unit are optimized using the Multi-strategy Integrated Zebra Optimization Algorithm(MIZOA).The experimental results show that the test accuracy of the MSCNN-BiGRU-SHA model based on the MIZOA proposed in this paper is as high as 0.9971 in the CICDDoS 2019 dataset.The evaluation accuracy of the new dataset GINKS2023 created in this paper is 0.9386.Compared to the MSCNN-BiGRU-SHA model based on the Zebra Optimization Algorithm(ZOA),the detection accuracy on the GINKS2023 dataset has improved by 5.81%,precisionhas increasedby 1.35%,the recallhas improvedby 9%,and theF1scorehas increasedby 5.55%.Compared to the MSCNN-BiGRU-SHA models developed using Grid Search,Random Search,and Bayesian Optimization,the MSCNN-BiGRU-SHA model optimized with the MI-ZOA exhibits better performance in terms of accuracy,precision,recall,and F1 score.
文摘Open caissons are widely used in foundation engineering because of their load-bearing efficiency and adaptability in diverse soil conditions.However,accurately predicting their undrained bearing capacity in layered soils remains a complex challenge.This study presents a novel application of five ensemble machine(ML)algorithms-random forest(RF),gradient boosting machine(GBM),extreme gradient boosting(XGBoost),adaptive boosting(AdaBoost),and categorical boosting(CatBoost)-to predict the undrained bearing capacity factor(Nc)of circular open caissons embedded in two-layered clay on the basis of results from finite element limit analysis(FELA).The input dataset consists of 1188 numerical simulations using the Tresca failure criterion,varying in geometrical and soil parameters.The FELA was performed via OptumG2 software with adaptive meshing techniques and verified against existing benchmark studies.The ML models were trained on 70% of the dataset and tested on the remaining 30%.Their performance was evaluated using six statistical metrics:coefficient of determination(R²),mean absolute error(MAE),root mean squared error(RMSE),index of scatter(IOS),RMSE-to-standard deviation ratio(RSR),and variance explained factor(VAF).The results indicate that all the models achieved high accuracy,with R²values exceeding 97.6%and RMSE values below 0.02.Among them,AdaBoost and CatBoost consistently outperformed the other methods across both the training and testing datasets,demonstrating superior generalizability and robustness.The proposed ML framework offers an efficient,accurate,and data-driven alternative to traditional methods for estimating caisson capacity in stratified soils.This approach can aid in reducing computational costs while improving reliability in the early stages of foundation design.
基金financially supported by the National Key R&D Program of China(No.2022YFE0121300)the National Natural Science Foundation of China(No.52374376)the Introduction Plan for High-end Foreign Experts(No.G2023105001L)。
文摘As a mathematical analysis method,fractal analysis can be used to quantitatively describe irregular shapes with self-similar or self-affine properties.Fractal analysis has been used to characterize the shapes of metal materials at various scales and dimensions.Conventional methods make it difficult to quantitatively describe the relationship between the regular characteristics and properties of metal material surfaces and interfaces.However,fractal analysis can be used to quantitatively describe the shape characteristics of metal materials and to establish the quantitative relationships between the shape characteristics and various properties of metal materials.From the perspective of two-dimensional planes and three-dimensional curved surfaces,this paper reviews the current research status of the fractal analysis of metal precipitate interfaces,metal grain boundary interfaces,metal-deposited film surfaces,metal fracture surfaces,metal machined surfaces,and metal wear surfaces.The relationship between the fractal dimensions and properties of metal material surfaces and interfaces is summarized.Starting from three perspectives of fractal analysis,namely,research scope,image acquisition methods,and calculation methods,this paper identifies the direction of research on fractal analysis of metal material surfaces and interfaces that need to be developed.It is believed that revealing the deep influence mechanism between the fractal dimensions and properties of metal material surfaces and interfaces will be the key research direction of the fractal analysis of metal materials in the future.
基金National Natural Science Foundation of China(32201491)Young Elite Scientists Sponsorship Program by CAST(2023QNRC001)The authors extend their appreciation to the Deanship of Scientific Research at Northern Border University,Arar,KSA for funding this research work through the project number“NBU-FPEJ-2024-1101-02”.
文摘Research efforts on electromagnetic interference(EMI)shielding materials have begun to converge on green and sustainable biomass materials.These materials offer numerous advantages such as being lightweight,porous,and hierarchical.Due to their porous nature,interfacial compatibility,and electrical conductivity,biomass materials hold significant potential as EMI shielding materials.Despite concerted efforts on the EMI shielding of biomass materials have been reported,this research area is still relatively new compared to traditional EMI shielding materials.In particular,a more comprehensive study and summary of the factors influencing biomass EMI shielding materials including the pore structure adjustment,preparation process,and micro-control would be valuable.The preparation methods and characteristics of wood,bamboo,cellulose and lignin in EMI shielding field are critically discussed in this paper,and similar biomass EMI materials are summarized and analyzed.The composite methods and fillers of various biomass materials were reviewed.this paper also highlights the mechanism of EMI shielding as well as existing prospects and challenges for development trends in this field.
文摘To improve the efficiency and accuracy of path planning for fan inspection tasks in thermal power plants,this paper proposes an intelligent inspection robot path planning scheme based on an improved A^(*)algorithm.The inspection robot utilizes multiple sensors to monitor key parameters of the fans,such as vibration,noise,and bearing temperature,and upload the data to the monitoring center.The robot’s inspection path employs the improved A^(*)algorithm,incorporating obstacle penalty terms,path reconstruction,and smoothing optimization techniques,thereby achieving optimal path planning for the inspection robot in complex environments.Simulation results demonstrate that the improved A^(*)algorithm significantly outperforms the traditional A^(*)algorithm in terms of total path distance,smoothness,and detour rate,effectively improving the execution efficiency of inspection tasks.
基金Shanxi Province Higher Education Science and Technology Innovation Fund Project(2022-676)Shanxi Soft Science Program Research Fund Project(2016041008-6)。
文摘In order to improve the efficiency of cloud-based web services,an improved plant growth simulation algorithm scheduling model.This model first used mathematical methods to describe the relationships between cloud-based web services and the constraints of system resources.Then,a light-induced plant growth simulation algorithm was established.The performance of the algorithm was compared through several plant types,and the best plant model was selected as the setting for the system.Experimental results show that when the number of test cloud-based web services reaches 2048,the model being 2.14 times faster than PSO,2.8 times faster than the ant colony algorithm,2.9 times faster than the bee colony algorithm,and a remarkable 8.38 times faster than the genetic algorithm.
基金The National Natural Science Foundation of China(No.U19B2031).
文摘A new method based on the iterative adaptive algorithm(IAA)and blocking matrix preprocessing(BMP)is proposed to study the suppression of multi-mainlobe interference.The algorithm is applied to precisely estimate the spatial spectrum and the directions of arrival(DOA)of interferences to overcome the drawbacks associated with conventional adaptive beamforming(ABF)methods.The mainlobe interferences are identified by calculating the correlation coefficients between direction steering vectors(SVs)and rejected by the BMP pretreatment.Then,IAA is subsequently employed to reconstruct a sidelobe interference-plus-noise covariance matrix for the preferable ABF and residual interference suppression.Simulation results demonstrate the excellence of the proposed method over normal methods based on BMP and eigen-projection matrix perprocessing(EMP)under both uncorrelated and coherent circumstances.
基金supported by the National Natural Science Foundation of China(Grant Nos.41972286 and 42102329).
文摘The Rock-soil interface is a common geological interface.Due to mechanical differences between soil and rock,the stress waves generated by underground blasting undergo intense polarization when crossing the rock-soil interface,making propagation laws difficult to predict.Currently,the characteristics of the impact of the rock-soil interface on blasting stress waves remain unclear.Therefore,the vibration field caused by cylindrical charge blasting in elastic rock and partial-saturation poro-viscoelastic soil was solved.A forward algorithm for the underground blasting vibration field in rock-soil sites was proposed,considering medium damping and geometric diffusion effects of stress waves.Further investigation into the influence of rock and soil parameters and blasting source parameters revealed the following conclusions:stress waves in soil exhibit dispersion,causing peak particle velocity(PPV)to display a discrete distribution.Soil parameters affect PPV attenuation only within the soil,while blasting source parameters affect PPV attenuation throughout the entire site.Multi-wave coupling effects induced by the rocksoil interface result in zones of enhanced and attenuated PPV within the site.The size of the enhancement zone is inversely correlated with the distance from the blasting source and positively correlated with the blasting source attenuation rate and burial depth,providing guidance for selecting explosives and blasting positions.Additionally,PPV attenuation rate increases with distance from the rock-soil interface,but an amplification effect occurs near the interface,most noticeable at 0.1 m.Thus,a sufficient safety distance from the rock-soil interface is necessary during underground blasting.
