Ice-breaking methods have become increasingly significant with the ongoing development of the polar regions.Among many ice-breaking methods,ice-breaking that utilizes a moving load is unique compared with the common c...Ice-breaking methods have become increasingly significant with the ongoing development of the polar regions.Among many ice-breaking methods,ice-breaking that utilizes a moving load is unique compared with the common collision or impact methods.A moving load can generate flexural-gravity waves(FGWs),under the influence of which the ice sheet undergoes deformation and may even experience structural damage.Moving loads can be divided into above-ice loads and underwater loads.For the above-ice loads,we discuss the characteristics of the FGWs generated by a moving load acting on a complete ice sheet,an ice sheet with a crack,and an ice sheet with a lead of open water.For underwater loads,we discuss the influence on the ice-breaking characteristics of FGWs of the mode of motion,the geometrical features,and the trajectory of motion of the load.In addition to discussing the status of current research and the technical challenges of ice-breaking by moving loads,this paper also looks ahead to future research prospects and presents some preliminary ideas for consideration.展开更多
Non-seismically designed(NSD)beam-column joints are susceptible to joint shear failure under seismic loads.Although significant research is available on the seismic behavior of such joints of planar frames,the informa...Non-seismically designed(NSD)beam-column joints are susceptible to joint shear failure under seismic loads.Although significant research is available on the seismic behavior of such joints of planar frames,the information on the seismic behavior of joints of space frames(3D joints)is insufficient.The 3D joints are subjected to bi-directional excitation,which results in an interaction between the shear strength obtained for the joint in the two orthogonal directions separately.The bi-directional seismic behavior of corner reinforced concrete(RC)joints is the focus of this study.First,a detailed finite element(FE)model using the FE software Abaqus,is developed and validated using the test results from the literature.The validated modeling procedure is used to conduct a parametric study to investigate the influence of different parameters such as concrete strength,dimensions of main and transverse beams framing into the joint,presence or absence of a slab,axial load ratio and loading direction on the seismic behavior of joints.By subjecting the models to different combinations of loads on the beams along perpendicular directions,the interaction of the joint shear strength in two orthogonal directions is studied.The comparison of the interaction curves of the joints obtained from the numerical study with a quadratic(circular)interaction curve indicates that in a majority of cases,the quadratic interaction model can represent the strength interaction diagrams of RC beam to column connections with governing joint shear failure reasonably well.展开更多
A conceptual model of intermittent joints is introduced to the cyclic shear test in the laboratory to explore the effects of loading parameters on its shear behavior under cyclic shear loading.The results show that th...A conceptual model of intermittent joints is introduced to the cyclic shear test in the laboratory to explore the effects of loading parameters on its shear behavior under cyclic shear loading.The results show that the loading parameters(initial normal stress,normal stiffness,and shear velocity)determine propagation paths of the wing and secondary cracks in rock bridges during the initial shear cycle,creating different morphologies of macroscopic step-path rupture surfaces and asperities on them.The differences in stress state and rupture surface induce different cyclic shear responses.It shows that high initial normal stress accelerates asperity degradation,raises shear resistance,and promotes compression of intermittent joints.In addition,high normal stiffness provides higher normal stress and shear resistance during the initial cycles and inhibits the dilation and compression of intermittent joints.High shear velocity results in a higher shear resistance,greater dilation,and greater compression.Finally,shear strength is most sensitive to initial normal stress,followed by shear velocity and normal stiffness.Moreover,average dilation angle is most sensitive to initial normal stress,followed by normal stiffness and shear velocity.During the shear cycles,frictional coefficient is affected by asperity degradation,backfilling of rock debris,and frictional area,exhibiting a non-monotonic behavior.展开更多
More than 200 years after Parkinson's disease was first described by the English surgeon whose name would eventually be given to the condition,available treatments remain purely symptomatic,leaving a critical unme...More than 200 years after Parkinson's disease was first described by the English surgeon whose name would eventually be given to the condition,available treatments remain purely symptomatic,leaving a critical unmet clinical need for a diseasemodifying therapy.展开更多
In rock drilling and blasting,the misfire of electronic detonators will not only affect the rock fragmentation result but also bring serious potential safety hazards to engineering construction.An accurate and compreh...In rock drilling and blasting,the misfire of electronic detonators will not only affect the rock fragmentation result but also bring serious potential safety hazards to engineering construction.An accurate and comprehensive understanding of the failure mechanisms of electronic detonators subjected to impact loading is of great significance to the reliability design and field safety use of electronic detonators.The spatial distribution characteristics and failure modes of misfired electronic detonators under different application scenarios are statistically analysed.The results show that under high impact loads,electronic detonators will experience failure phenomena such as rupture of the fuse head,fracture of the bridge wire,falling off of the solder joint,chip module damage and insufficient initiation energy after deformation.The lack of impact resistance is the primary cause of misfire of electronic detonators.Combined with the underwater impact resistance test and the impact load test in the adjacent blasthole on site,the formulas of the impact failure probability of the electronic detonator under different stress‒strength distribution curves are deduced.The test and evaluation method of the impact resistance of electronic detonators based on stress‒strength interference theory is proposed.Furthermore,the impact failure model of electronic detonators considering the strength degradation effect under repeated random loads is established.On this basis,the failure mechanism of electronic detonators under different application environments,such as open-pit blasting and underground blasting,is revealed,which provides scientific theory and methods for the reliability analysis,design and type selection of electronic detonators in rock drilling and blasting.展开更多
Nonlinear variations in the coordinate time series of global navigation satellite system(GNSS) reference stations are strongly correlated with surface displacements caused by environmental loading effects,including at...Nonlinear variations in the coordinate time series of global navigation satellite system(GNSS) reference stations are strongly correlated with surface displacements caused by environmental loading effects,including atmospheric, hydrological, and nontidal ocean loading. Continuous improvements in the accuracy of surface mass loading products, performance of Earth models, and precise data-processing technologies have significantly advanced research on the effects of environmental loading on nonlinear variations in GNSS coordinate time series. However, owing to theoretical limitations, the lack of high spatiotemporal resolution surface mass observations, and the coupling of GNSS technology-related systematic errors, environmental loading and nonlinear GNSS reference station displacements remain inconsistent. The applicability and capability of these loading products across different regions also require further evaluation. This paper outlines methods for modeling environmental loading, surface mass loading products, and service organizations. In addition, it summarizes recent advances in applying environmental loading to address nonlinear variations in global and regional GNSS coordinate time series. Moreover, the scientific questions of existing studies are summarized, and insights into future research directions are provided. The complex nonlinear motion of reference stations is a major factor limiting the accuracy of the current terrestrial reference frame. Further refining the environmental load modeling method, establishing a surface mass distribution model with high spatiotemporal resolution and reliability, exploring other environmental load factors such as ice sheet and artificial mass-change effects, and developing an optimal data-processing model and strategy for reprocessing global reference station data consistently could contribute to the development of a millimeter-level nonlinear motion model for GNSS reference stations with actual physical significance and provide theoretical support for establishing a terrestrial reference frame with 1 mm accuracy by 2050.展开更多
The current single-atom catalysts(SACs)for medicine still suffer from the limited active site density.Here,we develop a synthetic method capable of increasing both the metal loading and mass-specific activity of SACs ...The current single-atom catalysts(SACs)for medicine still suffer from the limited active site density.Here,we develop a synthetic method capable of increasing both the metal loading and mass-specific activity of SACs by exchanging zinc with iron.The constructed iron SACs(h^(3)-FNC)with a high metal loading of 6.27 wt%and an optimized adjacent Fe distance of~4 A exhibit excellent oxidase-like catalytic performance without significant activity decay after being stored for six months and promising antibacterial effects.Attractively,a“density effect”has been found at a high-enough metal doping amount,at which individual active sites become close enough to interact with each other and alter the electronic structure,resulting in significantly boosted intrinsic activity of single-atomic iron sites in h^(3)-FNCs by 2.3 times compared to low-and medium-loading SACs.Consequently,the overall catalytic activity of h^(3)-FNC is highly improved,with mass activity and metal mass-specific activity that are,respectively,66 and 315 times higher than those of commercial Pt/C.In addition,h^(3)-FNCs demonstrate efficiently enhanced capability in catalyzing oxygen reduction into superoxide anion(O_(2)·^(−))and glutathione(GSH)depletion.Both in vitro and in vivo assays demonstrate the superior antibacterial efficacy of h^(3)-FNCs in promoting wound healing.This work presents an intriguing activity-enhancement effect in catalysts and exhibits impressive therapeutic efficacy in combating bacterial infections.展开更多
Ice load on underwater vehicles breaking through ice covers from underneath is a significant concern for researchers in polar exploration,and the research on this problem is still in its early stages.Both mechanical e...Ice load on underwater vehicles breaking through ice covers from underneath is a significant concern for researchers in polar exploration,and the research on this problem is still in its early stages.Both mechanical experimental measurement and numerical simulation pose research challenges.This study focuses on the ice load of a cylinder structure breaking upward through the ice sheet form underneath in the Small Ice Model Basin of China Ship Scientific Research Center(CSSRC SIMB).A high-speed camera system was employed to observe the ice sheet failure during the tests,in which,with the loading position as center,local radial cracks and circumferential cracks were generated.A load sensor was used to measure the overall ice load during this process.Meanwhile,a numerical model was developed using LS-DYNA for validation and comparison.With this model,numerical simulation was conducted under various ice thicknesses and upgoing speeds to analyze the instantaneous curves of ice load.The calculation results were statistically analyzed under different working conditions to determine the influence of the factors on the ice load of the cylinder.The study explores the measurement method about ice load of objects vertically breaking through model ice sheet and is expected to provide some fundamental insights into the safety design of underwater structures operating in ice waters.展开更多
Load forecasting is of great significance to the development of new power systems.With the advancement of smart grids,the integration and distribution of distributed renewable energy sources and power electronics devi...Load forecasting is of great significance to the development of new power systems.With the advancement of smart grids,the integration and distribution of distributed renewable energy sources and power electronics devices have made power load data increasingly complex and volatile.This places higher demands on the prediction and analysis of power loads.In order to improve the prediction accuracy of short-term power load,a CNN-BiLSTMTPA short-term power prediction model based on the Improved Whale Optimization Algorithm(IWOA)with mixed strategies was proposed.Firstly,the model combined the Convolutional Neural Network(CNN)with the Bidirectional Long Short-Term Memory Network(BiLSTM)to fully extract the spatio-temporal characteristics of the load data itself.Then,the Temporal Pattern Attention(TPA)mechanism was introduced into the CNN-BiLSTM model to automatically assign corresponding weights to the hidden states of the BiLSTM.This allowed the model to differentiate the importance of load sequences at different time intervals.At the same time,in order to solve the problem of the difficulties of selecting the parameters of the temporal model,and the poor global search ability of the whale algorithm,which is easy to fall into the local optimization,the whale algorithm(IWOA)was optimized by using the hybrid strategy of Tent chaos mapping and Levy flight strategy,so as to better search the parameters of the model.In this experiment,the real load data of a region in Zhejiang was taken as an example to analyze,and the prediction accuracy(R2)of the proposed method reached 98.83%.Compared with the prediction models such as BP,WOA-CNN-BiLSTM,SSA-CNN-BiLSTM,CNN-BiGRU-Attention,etc.,the experimental results showed that the model proposed in this study has a higher prediction accuracy.展开更多
This paper proposes a novel cargo loading algorithm applicable to automated conveyor-type loading systems.The algorithm offers improvements in computational efficiency and robustness by utilizing the concept of discre...This paper proposes a novel cargo loading algorithm applicable to automated conveyor-type loading systems.The algorithm offers improvements in computational efficiency and robustness by utilizing the concept of discrete derivatives and introducing logistics-related constraints.Optional consideration of the rotation of the cargoes was made to further enhance the optimality of the solutions,if possible to be physically implemented.Evaluation metrics were developed for accurate evaluation and enhancement of the algorithm’s ability to efficiently utilize the loading space and provide a high level of dynamic stability.Experimental results demonstrate the extensive robustness of the proposed algorithm to the diversity of cargoes present in Business-to-Consumer environments.This study contributes practical advancements in both cargo loading optimization and automation of the logistics industry,with potential applications in last-mile delivery services,warehousing,and supply chain management.展开更多
The service load on high temperature rotating components of aero-engines generally exhibits flight mission characteristics. The general shape of the load spectrum is that Type Ⅲ/Ⅳ cyclic loading and creep loading ar...The service load on high temperature rotating components of aero-engines generally exhibits flight mission characteristics. The general shape of the load spectrum is that Type Ⅲ/Ⅳ cyclic loading and creep loading are superimposed on Type Ⅰ cyclic loading. Meanwhile, the sequence of the Type Ⅲ/Ⅳ cyclic and creep loading varies with mission. This work performed load spectrum test with this characteristic on the Ni-based alloy FGH96. Then a life prediction method was developed based on the Chaboche fatigue damage accumulation model and a modified time fraction model. Creep followed by Fatigue (C-F) test was carried out to reveal the creep-fatigue interaction and calibrate parameters. The results show that most test results fall within the 2-fold deviation band. The sequence of creep-fatigue loading within the load spectrum exhibited a limited effect on life. Finally, simplified methods were developed to improve analysis efficiency, and cases where simplified methods could replace the proposed method were discussed.展开更多
This work aims to reveal the mechanical responses and energy evolution characteristics of skarn rock under constant amplitude-varied frequency loading paths.Testing results show that the fatigue lifetime,stress−strain...This work aims to reveal the mechanical responses and energy evolution characteristics of skarn rock under constant amplitude-varied frequency loading paths.Testing results show that the fatigue lifetime,stress−strain responses,deformation,energy dissipation and fracture morphology are all impacted by the loading rate.A pronounced influence of the loading rate on rock deformation is found,with slower loading rate eliciting enhanced strain development,alongside augmented energy absorption and dissipation.In addition,it is revealed that the loading rate and cyclic loading amplitude jointly influence the phase shift distribution,with accelerated rates leading to a narrower phase shift duration.It is suggested that lower loading rate leads to more significant energy dissipation.Finally,the tensile or shear failure modes were intrinsically linked to loading strategy,with cyclic loading predominantly instigating shear damage,as manifest in the increased presence of pulverized grain particles.This work would give new insights into the fortification of mining structures and the optimization of mining methodologies.展开更多
In this study,a uniaxial cyclic compression test is conducted on coal-rock composite structures under two cyclic loads using MTSE45.104 testing apparatus to investigate the macro-mesoscopic deformation,damage behavior...In this study,a uniaxial cyclic compression test is conducted on coal-rock composite structures under two cyclic loads using MTSE45.104 testing apparatus to investigate the macro-mesoscopic deformation,damage behavior,and energy evolution characteristics of these structures under different cyclic stress disturbances.Three loading and unloading rates(LURs)are tested to examine the damage behaviors and energy-driven characteristics of the composites.The findings reveal that the energy-driven behavior,mechanical properties,and macro-micro degradation characteristics of the composites are significantly influenced by the loading rate.Under the gradual cyclic loading and unloading(CLU)path with a constant lower limit(path I)and the CLU path with variable upper and lower boundaries(path II),an increase in LURs from 0.05 to 0.15 mm/min reduces the average loading time by 32.39%and 48.60%,respectively.Consequently,the total number of cracks in the samples increases by 1.66-fold for path I and 1.41-fold for path II.As LURs further increase,the energy storage limit of samples expands,leading to a higher proportion of transmatrix and shear cracks.Under both cyclic loading conditions,a broader cyclic stress range promotes energy dissipation and the formation of internal fractures.Notably,at higher loading rates,cracks tend to propagate along primary weak surfaces,leading to an increased incidence of intermatrix fractures.This behavior indicates a microscopic feature of the failure mechanisms in composite structures.These results provide a theoretical basis for elucidating the damage and failure characteristics of coal-rock composite structures under cyclic stress disturbances.展开更多
Load time series analysis is critical for resource management and optimization decisions,especially automated analysis techniques.Existing research has insufficiently interpreted the overall characteristics of samples...Load time series analysis is critical for resource management and optimization decisions,especially automated analysis techniques.Existing research has insufficiently interpreted the overall characteristics of samples,leading to significant differences in load level detection conclusions for samples with different characteristics(trend,seasonality,cyclicality).Achieving automated,feature-adaptive,and quantifiable analysis methods remains a challenge.This paper proposes a Threshold Recognition-based Load Level Detection Algorithm(TRLLD),which effectively identifies different load level regions in samples of arbitrary size and distribution type based on sample characteristics.By utilizing distribution density uniformity,the algorithm classifies data points and ultimately obtains normalized load values.In the feature recognition step,the algorithm employs the Density Uniformity Index Based on Differences(DUID),High Load Level Concentration(HLLC),and Low Load Level Concentration(LLLC)to assess sample characteristics,which are independent of specific load values,providing a standardized perspective on features,ensuring high efficiency and strong interpretability.Compared to traditional methods,the proposed approach demonstrates better adaptive and real-time analysis capabilities.Experimental results indicate that it can effectively identify high load and low load regions in 16 groups of time series samples with different load characteristics,yielding highly interpretable results.The correlation between the DUID and sample density distribution uniformity reaches 98.08%.When introducing 10% MAD intensity noise,the maximum relative error is 4.72%,showcasing high robustness.Notably,it exhibits significant advantages in general and low sample scenarios.展开更多
In rock engineering,the cyclic shear characteristics of rough joints under dynamic disturbances are still insufficiently studied.This study conducted cyclic shear experiments on rough joints under dynamic normal loads...In rock engineering,the cyclic shear characteristics of rough joints under dynamic disturbances are still insufficiently studied.This study conducted cyclic shear experiments on rough joints under dynamic normal loads to assess the impact of shear frequency(f_(h))and shear displacement amplitude(u_(d))on the frictional properties of the joint.The results reveal that within a single shearing cycle,the normal displacement negatively correlates with the dynamic normal force.As the shear cycle number increases,the joint surface undergoes progressive wear,resulting in an exponential decrease in the peak normal displacement.In the cyclic shearing procedure,the forward peak values of shear force and friction coefficient display larger fluctuations at either lower or higher shear frequencies.However,under moderate shear frequency conditions,the changes in the shear strength of the joint surface are smaller,and the degree of degradation post-shearing is relatively limited.As the shear displacement amplitude increases,the range of normal deformation within the joint widens.Furthermore,after shearing,the corresponding joint roughness coefficient trend shows a gradual decrease with an increasing shear displacement amplitude,while varying with the shearing frequency in a pattern that initially rises and then falls,with a turning point at 0.05 Hz.The findings of this research contribute to a profound comprehension of the cyclic frictional properties of rock joints under dynamic disturbances.展开更多
Accurate Electric Load Forecasting(ELF)is crucial for optimizing production capacity,improving operational efficiency,and managing energy resources effectively.Moreover,precise ELF contributes to a smaller environment...Accurate Electric Load Forecasting(ELF)is crucial for optimizing production capacity,improving operational efficiency,and managing energy resources effectively.Moreover,precise ELF contributes to a smaller environmental footprint by reducing the risks of disruption,downtime,and waste.However,with increasingly complex energy consumption patterns driven by renewable energy integration and changing consumer behaviors,no single approach has emerged as universally effective.In response,this research presents a hybrid modeling framework that combines the strengths of Random Forest(RF)and Autoregressive Integrated Moving Average(ARIMA)models,enhanced with advanced feature selection—Minimum Redundancy Maximum Relevancy and Maximum Synergy(MRMRMS)method—to produce a sparse model.Additionally,the residual patterns are analyzed to enhance forecast accuracy.High-resolution weather data from Weather Underground and historical energy consumption data from PJM for Duke Energy Ohio and Kentucky(DEO&K)are used in this application.This methodology,termed SP-RF-ARIMA,is evaluated against existing approaches;it demonstrates more than 40%reduction in mean absolute error and root mean square error compared to the second-best method.展开更多
Maintaining high-quality service supply and sustainability in modern cloud computing is essential to ensuring optimal system performance and energy efficiency.A novel approach is introduced in this study to decrease a...Maintaining high-quality service supply and sustainability in modern cloud computing is essential to ensuring optimal system performance and energy efficiency.A novel approach is introduced in this study to decrease a system's overall delay and energy consumption by using a deep reinforcement learning(DRL)model to predict and allocate incoming workloads flexibly.The proposed methodology integrates workload prediction utilising long short-term memory(LSTM)networks with efficient load-balancing techniques led by deep Q-learning and Actor-critic algorithms.By continuously analysing current and historical data,the model can efficiently allocate resources,prioritizing speed and energy preservation.The experimental results demonstrate that our load balancing system,which utilises DRL,significantly reduces average response times and energy usage compared to traditional methods.This approach provides a scalable and adaptable strategy for enhancing cloud infrastructure performance.It consistently provides reliable and durable performance across a range of dynamic workloads.展开更多
Surface deformation calculations due to environmental loading typically rely on the Preliminary Reference Earth Model(PREM),which assumes a homogeneous and isotropic Earth structure,leading to noticeable errors.To enh...Surface deformation calculations due to environmental loading typically rely on the Preliminary Reference Earth Model(PREM),which assumes a homogeneous and isotropic Earth structure,leading to noticeable errors.To enhance accuracy,the high-precision crustal model CRUST 1.0 is used to refine calculations of regional surface deformation caused by hydrological and non-tidal atmospheric loading.The improved model is applied to 27 Global Navigation Satellite System(GNSS)reference stations in the first phase of the Crustal Movement Observation Network of China(CMONOC),considering their geographical locations.Green's functions are employed to compute surface deformation at each site.Results indicate relative discrepancies of 11.78%and 14.14%for non-tidal atmospheric and hydrological loading compared to PREM,with vertical deformation differences reaching an average of 18.95%.Additionally,the distinct spatial distribution characteristics of the relative differences in each direction indicate that the improved RPREM model is more responsive to the mass variations derived from Gravity Recovery and Climate Experiment(GRACE).The results suggest that the improved PRREM model demonstrates higher sensitivity to loading variations than the PREM model.Utilizing the enhanced method of calculating surface deformation through the utilization of Green's function at the site could effectively reduce the calculation error caused by regional structure,leading to enhanced uniformity and isotropy of PREM.展开更多
Accurate daily suspended sediment load(SSL)prediction is essential for sustainable water resource management,sediment control,and environmental planning.However,SSL prediction is highly complex due to its nonlinear an...Accurate daily suspended sediment load(SSL)prediction is essential for sustainable water resource management,sediment control,and environmental planning.However,SSL prediction is highly complex due to its nonlinear and dynamic nature,making traditional empirical models inadequate.This study proposes a novel hybrid approach,integrating the Adaptive Neuro-Fuzzy Inference System(ANFIS)with the Gradient-Based Optimizer(GBO),to enhance SSL forecasting accuracy.The research compares the performance of ANFIS-GBO with three alternative models:standard ANFIS,ANFIS with Particle Swarm Optimization(ANFIS-PSO),and ANFIS with Grey Wolf Optimization(ANFIS-GWO).Historical SSL and streamflow data from the Bailong River Basin,China,are used to train and validate the models.The input selection process is optimized using the Multivariate Adaptive Regression Splines(MARS)method.Model performance is evaluated using statistical metrics such as Root Mean Square Error(RMSE),Mean Absolute Error(MAE),Mean Absolute Percentage Error(MAPE),Nash Sutcliffe Efficiency(NSE),and Determination Coefficient(R^(2)).Additionally,visual assessments,including scatter plots,Taylor diagrams,and violin plots,provide further insights into model reliability.The results indicate that including historical SSL data improves predictive accuracy,with ANFIS-GBO outperforming the other models.ANFIS-GBO achieves the lowest RMSE and MAE and the highest NSE and R^(2),demonstrating its superior learning ability and adaptability.The findings highlight the effectiveness of nature-inspired optimization algorithms in enhancing sediment load forecasting and contribute to the advancement of AI-based hydrological modeling.Future research should explore the integration of additional environmental and climatic variables to enhance predictive capabilities further.展开更多
基金Supported by the National Natural Science Foundation of China(Nos.52192693,52192690,52371270,U20A20327)the National Key Research and Development Program of China(Nos.2021YFC2803400).
文摘Ice-breaking methods have become increasingly significant with the ongoing development of the polar regions.Among many ice-breaking methods,ice-breaking that utilizes a moving load is unique compared with the common collision or impact methods.A moving load can generate flexural-gravity waves(FGWs),under the influence of which the ice sheet undergoes deformation and may even experience structural damage.Moving loads can be divided into above-ice loads and underwater loads.For the above-ice loads,we discuss the characteristics of the FGWs generated by a moving load acting on a complete ice sheet,an ice sheet with a crack,and an ice sheet with a lead of open water.For underwater loads,we discuss the influence on the ice-breaking characteristics of FGWs of the mode of motion,the geometrical features,and the trajectory of motion of the load.In addition to discussing the status of current research and the technical challenges of ice-breaking by moving loads,this paper also looks ahead to future research prospects and presents some preliminary ideas for consideration.
文摘Non-seismically designed(NSD)beam-column joints are susceptible to joint shear failure under seismic loads.Although significant research is available on the seismic behavior of such joints of planar frames,the information on the seismic behavior of joints of space frames(3D joints)is insufficient.The 3D joints are subjected to bi-directional excitation,which results in an interaction between the shear strength obtained for the joint in the two orthogonal directions separately.The bi-directional seismic behavior of corner reinforced concrete(RC)joints is the focus of this study.First,a detailed finite element(FE)model using the FE software Abaqus,is developed and validated using the test results from the literature.The validated modeling procedure is used to conduct a parametric study to investigate the influence of different parameters such as concrete strength,dimensions of main and transverse beams framing into the joint,presence or absence of a slab,axial load ratio and loading direction on the seismic behavior of joints.By subjecting the models to different combinations of loads on the beams along perpendicular directions,the interaction of the joint shear strength in two orthogonal directions is studied.The comparison of the interaction curves of the joints obtained from the numerical study with a quadratic(circular)interaction curve indicates that in a majority of cases,the quadratic interaction model can represent the strength interaction diagrams of RC beam to column connections with governing joint shear failure reasonably well.
基金financially supported by the National Natural Science Foundation of China(Grant No.42172292)Taishan Scholars Project Special Funding,and Shandong Energy Group(Grant No.SNKJ 2022A01-R26).
文摘A conceptual model of intermittent joints is introduced to the cyclic shear test in the laboratory to explore the effects of loading parameters on its shear behavior under cyclic shear loading.The results show that the loading parameters(initial normal stress,normal stiffness,and shear velocity)determine propagation paths of the wing and secondary cracks in rock bridges during the initial shear cycle,creating different morphologies of macroscopic step-path rupture surfaces and asperities on them.The differences in stress state and rupture surface induce different cyclic shear responses.It shows that high initial normal stress accelerates asperity degradation,raises shear resistance,and promotes compression of intermittent joints.In addition,high normal stiffness provides higher normal stress and shear resistance during the initial cycles and inhibits the dilation and compression of intermittent joints.High shear velocity results in a higher shear resistance,greater dilation,and greater compression.Finally,shear strength is most sensitive to initial normal stress,followed by shear velocity and normal stiffness.Moreover,average dilation angle is most sensitive to initial normal stress,followed by normal stiffness and shear velocity.During the shear cycles,frictional coefficient is affected by asperity degradation,backfilling of rock debris,and frictional area,exhibiting a non-monotonic behavior.
基金funded by The Michael J.Fox Foundation for Parkinson’s Research(grant numbers:17244 and 023410)Science Foundation Ireland(grant number:19/FFP/6554)(to ED)。
文摘More than 200 years after Parkinson's disease was first described by the English surgeon whose name would eventually be given to the condition,available treatments remain purely symptomatic,leaving a critical unmet clinical need for a diseasemodifying therapy.
基金supported by the Chongqing Youth Talent Support Program(Cstc2022ycjh-bgzxm0079)the Chinese National Natural Science Foundation(52379128,51979152)+2 种基金Science Fund for Distinguished Young Scholars of Hubei Proivnce(2023AFA048)Educational Commission of Hubei Province of China(T2020005)the Young Top-notch Talent Cultivation Program of Hubei Province.
文摘In rock drilling and blasting,the misfire of electronic detonators will not only affect the rock fragmentation result but also bring serious potential safety hazards to engineering construction.An accurate and comprehensive understanding of the failure mechanisms of electronic detonators subjected to impact loading is of great significance to the reliability design and field safety use of electronic detonators.The spatial distribution characteristics and failure modes of misfired electronic detonators under different application scenarios are statistically analysed.The results show that under high impact loads,electronic detonators will experience failure phenomena such as rupture of the fuse head,fracture of the bridge wire,falling off of the solder joint,chip module damage and insufficient initiation energy after deformation.The lack of impact resistance is the primary cause of misfire of electronic detonators.Combined with the underwater impact resistance test and the impact load test in the adjacent blasthole on site,the formulas of the impact failure probability of the electronic detonator under different stress‒strength distribution curves are deduced.The test and evaluation method of the impact resistance of electronic detonators based on stress‒strength interference theory is proposed.Furthermore,the impact failure model of electronic detonators considering the strength degradation effect under repeated random loads is established.On this basis,the failure mechanism of electronic detonators under different application environments,such as open-pit blasting and underground blasting,is revealed,which provides scientific theory and methods for the reliability analysis,design and type selection of electronic detonators in rock drilling and blasting.
基金supported by the Basic Science Center Project of the National Natural Science Foundation of China(42388102)the National Natural Science Foundation of China(42174030)+2 种基金the Special Fund of Hubei Luojia Laboratory(220100020)the Major Science and Technology Program for Hubei Province(2022AAA002)the Fundamental Research Funds for the Central Universities of China(2042022dx0001 and 2042023kfyq01)。
文摘Nonlinear variations in the coordinate time series of global navigation satellite system(GNSS) reference stations are strongly correlated with surface displacements caused by environmental loading effects,including atmospheric, hydrological, and nontidal ocean loading. Continuous improvements in the accuracy of surface mass loading products, performance of Earth models, and precise data-processing technologies have significantly advanced research on the effects of environmental loading on nonlinear variations in GNSS coordinate time series. However, owing to theoretical limitations, the lack of high spatiotemporal resolution surface mass observations, and the coupling of GNSS technology-related systematic errors, environmental loading and nonlinear GNSS reference station displacements remain inconsistent. The applicability and capability of these loading products across different regions also require further evaluation. This paper outlines methods for modeling environmental loading, surface mass loading products, and service organizations. In addition, it summarizes recent advances in applying environmental loading to address nonlinear variations in global and regional GNSS coordinate time series. Moreover, the scientific questions of existing studies are summarized, and insights into future research directions are provided. The complex nonlinear motion of reference stations is a major factor limiting the accuracy of the current terrestrial reference frame. Further refining the environmental load modeling method, establishing a surface mass distribution model with high spatiotemporal resolution and reliability, exploring other environmental load factors such as ice sheet and artificial mass-change effects, and developing an optimal data-processing model and strategy for reprocessing global reference station data consistently could contribute to the development of a millimeter-level nonlinear motion model for GNSS reference stations with actual physical significance and provide theoretical support for establishing a terrestrial reference frame with 1 mm accuracy by 2050.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFB3804500)the National Natural Science Foundation of China(Grant No.52202352,22335006)+4 种基金the Shanghai Municipal Health Commission(Grant No.20224Y0010)the CAMS Innovation Fund for Medical Sciences(Grant No.2021-I2M-5-012)the Basic Research Program of Shanghai Municipal Government(Grant No.21JC1406000)the Fundamental Research Funds for the Central Universities(Grant No.22120230237,2023-3-YB-11,22120220618)the Basic Research Program of Shanghai Municipal Government(23DX1900200).
文摘The current single-atom catalysts(SACs)for medicine still suffer from the limited active site density.Here,we develop a synthetic method capable of increasing both the metal loading and mass-specific activity of SACs by exchanging zinc with iron.The constructed iron SACs(h^(3)-FNC)with a high metal loading of 6.27 wt%and an optimized adjacent Fe distance of~4 A exhibit excellent oxidase-like catalytic performance without significant activity decay after being stored for six months and promising antibacterial effects.Attractively,a“density effect”has been found at a high-enough metal doping amount,at which individual active sites become close enough to interact with each other and alter the electronic structure,resulting in significantly boosted intrinsic activity of single-atomic iron sites in h^(3)-FNCs by 2.3 times compared to low-and medium-loading SACs.Consequently,the overall catalytic activity of h^(3)-FNC is highly improved,with mass activity and metal mass-specific activity that are,respectively,66 and 315 times higher than those of commercial Pt/C.In addition,h^(3)-FNCs demonstrate efficiently enhanced capability in catalyzing oxygen reduction into superoxide anion(O_(2)·^(−))and glutathione(GSH)depletion.Both in vitro and in vivo assays demonstrate the superior antibacterial efficacy of h^(3)-FNCs in promoting wound healing.This work presents an intriguing activity-enhancement effect in catalysts and exhibits impressive therapeutic efficacy in combating bacterial infections.
文摘Ice load on underwater vehicles breaking through ice covers from underneath is a significant concern for researchers in polar exploration,and the research on this problem is still in its early stages.Both mechanical experimental measurement and numerical simulation pose research challenges.This study focuses on the ice load of a cylinder structure breaking upward through the ice sheet form underneath in the Small Ice Model Basin of China Ship Scientific Research Center(CSSRC SIMB).A high-speed camera system was employed to observe the ice sheet failure during the tests,in which,with the loading position as center,local radial cracks and circumferential cracks were generated.A load sensor was used to measure the overall ice load during this process.Meanwhile,a numerical model was developed using LS-DYNA for validation and comparison.With this model,numerical simulation was conducted under various ice thicknesses and upgoing speeds to analyze the instantaneous curves of ice load.The calculation results were statistically analyzed under different working conditions to determine the influence of the factors on the ice load of the cylinder.The study explores the measurement method about ice load of objects vertically breaking through model ice sheet and is expected to provide some fundamental insights into the safety design of underwater structures operating in ice waters.
文摘Load forecasting is of great significance to the development of new power systems.With the advancement of smart grids,the integration and distribution of distributed renewable energy sources and power electronics devices have made power load data increasingly complex and volatile.This places higher demands on the prediction and analysis of power loads.In order to improve the prediction accuracy of short-term power load,a CNN-BiLSTMTPA short-term power prediction model based on the Improved Whale Optimization Algorithm(IWOA)with mixed strategies was proposed.Firstly,the model combined the Convolutional Neural Network(CNN)with the Bidirectional Long Short-Term Memory Network(BiLSTM)to fully extract the spatio-temporal characteristics of the load data itself.Then,the Temporal Pattern Attention(TPA)mechanism was introduced into the CNN-BiLSTM model to automatically assign corresponding weights to the hidden states of the BiLSTM.This allowed the model to differentiate the importance of load sequences at different time intervals.At the same time,in order to solve the problem of the difficulties of selecting the parameters of the temporal model,and the poor global search ability of the whale algorithm,which is easy to fall into the local optimization,the whale algorithm(IWOA)was optimized by using the hybrid strategy of Tent chaos mapping and Levy flight strategy,so as to better search the parameters of the model.In this experiment,the real load data of a region in Zhejiang was taken as an example to analyze,and the prediction accuracy(R2)of the proposed method reached 98.83%.Compared with the prediction models such as BP,WOA-CNN-BiLSTM,SSA-CNN-BiLSTM,CNN-BiGRU-Attention,etc.,the experimental results showed that the model proposed in this study has a higher prediction accuracy.
基金supported by the BK21 FOUR funded by the Ministry of Education of Korea and National Research Foundation of Korea,a Korea Agency for Infrastructure Technology Advancement(KAIA)grant funded by the Ministry of Land,Infrastructure,and Transport(Grant 1615013176)IITP(Institute of Information&Coummunications Technology Planning&Evaluation)-ICAN(ICT Challenge and Advanced Network of HRD)grant funded by the Korea government(Ministry of Science and ICT)(RS-2024-00438411).
文摘This paper proposes a novel cargo loading algorithm applicable to automated conveyor-type loading systems.The algorithm offers improvements in computational efficiency and robustness by utilizing the concept of discrete derivatives and introducing logistics-related constraints.Optional consideration of the rotation of the cargoes was made to further enhance the optimality of the solutions,if possible to be physically implemented.Evaluation metrics were developed for accurate evaluation and enhancement of the algorithm’s ability to efficiently utilize the loading space and provide a high level of dynamic stability.Experimental results demonstrate the extensive robustness of the proposed algorithm to the diversity of cargoes present in Business-to-Consumer environments.This study contributes practical advancements in both cargo loading optimization and automation of the logistics industry,with potential applications in last-mile delivery services,warehousing,and supply chain management.
基金supported by the National Science and Technology Major Project of China(No.J2019-IV-0017-0085)the National Natural Science Foundation of China(Nos.12172021,52205177)the Natural Science Foundation of Hunan Province,China(No.2021JJ40741).
文摘The service load on high temperature rotating components of aero-engines generally exhibits flight mission characteristics. The general shape of the load spectrum is that Type Ⅲ/Ⅳ cyclic loading and creep loading are superimposed on Type Ⅰ cyclic loading. Meanwhile, the sequence of the Type Ⅲ/Ⅳ cyclic and creep loading varies with mission. This work performed load spectrum test with this characteristic on the Ni-based alloy FGH96. Then a life prediction method was developed based on the Chaboche fatigue damage accumulation model and a modified time fraction model. Creep followed by Fatigue (C-F) test was carried out to reveal the creep-fatigue interaction and calibrate parameters. The results show that most test results fall within the 2-fold deviation band. The sequence of creep-fatigue loading within the load spectrum exhibited a limited effect on life. Finally, simplified methods were developed to improve analysis efficiency, and cases where simplified methods could replace the proposed method were discussed.
基金Project(52174069) supported by the National Natural Science Foundation of ChinaProject(8202033) supported by the Beijing Natural Science Foundation,ChinaProject(KCF2203) supported by the Henan Key Laboratory for Green and Efficient Mining&Comprehensive Utilization of Mineral Resources (Henan Polytechnic University),China。
文摘This work aims to reveal the mechanical responses and energy evolution characteristics of skarn rock under constant amplitude-varied frequency loading paths.Testing results show that the fatigue lifetime,stress−strain responses,deformation,energy dissipation and fracture morphology are all impacted by the loading rate.A pronounced influence of the loading rate on rock deformation is found,with slower loading rate eliciting enhanced strain development,alongside augmented energy absorption and dissipation.In addition,it is revealed that the loading rate and cyclic loading amplitude jointly influence the phase shift distribution,with accelerated rates leading to a narrower phase shift duration.It is suggested that lower loading rate leads to more significant energy dissipation.Finally,the tensile or shear failure modes were intrinsically linked to loading strategy,with cyclic loading predominantly instigating shear damage,as manifest in the increased presence of pulverized grain particles.This work would give new insights into the fortification of mining structures and the optimization of mining methodologies.
基金Project(2023YFC3009003) supported by the National Key R&D Program of ChinaProjects(52130409, 52121003, 52374249, 52204220) supported by the National Natural Science Foundation of ChinaProject(2024JCCXAQ01) supported by the Fundamental Research Funds for the Central Universities,China。
文摘In this study,a uniaxial cyclic compression test is conducted on coal-rock composite structures under two cyclic loads using MTSE45.104 testing apparatus to investigate the macro-mesoscopic deformation,damage behavior,and energy evolution characteristics of these structures under different cyclic stress disturbances.Three loading and unloading rates(LURs)are tested to examine the damage behaviors and energy-driven characteristics of the composites.The findings reveal that the energy-driven behavior,mechanical properties,and macro-micro degradation characteristics of the composites are significantly influenced by the loading rate.Under the gradual cyclic loading and unloading(CLU)path with a constant lower limit(path I)and the CLU path with variable upper and lower boundaries(path II),an increase in LURs from 0.05 to 0.15 mm/min reduces the average loading time by 32.39%and 48.60%,respectively.Consequently,the total number of cracks in the samples increases by 1.66-fold for path I and 1.41-fold for path II.As LURs further increase,the energy storage limit of samples expands,leading to a higher proportion of transmatrix and shear cracks.Under both cyclic loading conditions,a broader cyclic stress range promotes energy dissipation and the formation of internal fractures.Notably,at higher loading rates,cracks tend to propagate along primary weak surfaces,leading to an increased incidence of intermatrix fractures.This behavior indicates a microscopic feature of the failure mechanisms in composite structures.These results provide a theoretical basis for elucidating the damage and failure characteristics of coal-rock composite structures under cyclic stress disturbances.
文摘Load time series analysis is critical for resource management and optimization decisions,especially automated analysis techniques.Existing research has insufficiently interpreted the overall characteristics of samples,leading to significant differences in load level detection conclusions for samples with different characteristics(trend,seasonality,cyclicality).Achieving automated,feature-adaptive,and quantifiable analysis methods remains a challenge.This paper proposes a Threshold Recognition-based Load Level Detection Algorithm(TRLLD),which effectively identifies different load level regions in samples of arbitrary size and distribution type based on sample characteristics.By utilizing distribution density uniformity,the algorithm classifies data points and ultimately obtains normalized load values.In the feature recognition step,the algorithm employs the Density Uniformity Index Based on Differences(DUID),High Load Level Concentration(HLLC),and Low Load Level Concentration(LLLC)to assess sample characteristics,which are independent of specific load values,providing a standardized perspective on features,ensuring high efficiency and strong interpretability.Compared to traditional methods,the proposed approach demonstrates better adaptive and real-time analysis capabilities.Experimental results indicate that it can effectively identify high load and low load regions in 16 groups of time series samples with different load characteristics,yielding highly interpretable results.The correlation between the DUID and sample density distribution uniformity reaches 98.08%.When introducing 10% MAD intensity noise,the maximum relative error is 4.72%,showcasing high robustness.Notably,it exhibits significant advantages in general and low sample scenarios.
基金funding support from the National Natural Science Foundation of China(Grant Nos.52174092 and 51904290)the Natural Science Foundation of Jiangsu Province,China(Grant No.BK20220157).
文摘In rock engineering,the cyclic shear characteristics of rough joints under dynamic disturbances are still insufficiently studied.This study conducted cyclic shear experiments on rough joints under dynamic normal loads to assess the impact of shear frequency(f_(h))and shear displacement amplitude(u_(d))on the frictional properties of the joint.The results reveal that within a single shearing cycle,the normal displacement negatively correlates with the dynamic normal force.As the shear cycle number increases,the joint surface undergoes progressive wear,resulting in an exponential decrease in the peak normal displacement.In the cyclic shearing procedure,the forward peak values of shear force and friction coefficient display larger fluctuations at either lower or higher shear frequencies.However,under moderate shear frequency conditions,the changes in the shear strength of the joint surface are smaller,and the degree of degradation post-shearing is relatively limited.As the shear displacement amplitude increases,the range of normal deformation within the joint widens.Furthermore,after shearing,the corresponding joint roughness coefficient trend shows a gradual decrease with an increasing shear displacement amplitude,while varying with the shearing frequency in a pattern that initially rises and then falls,with a turning point at 0.05 Hz.The findings of this research contribute to a profound comprehension of the cyclic frictional properties of rock joints under dynamic disturbances.
基金supported by the Startup Grant(PG18929)awarded to F.Shokoohi.
文摘Accurate Electric Load Forecasting(ELF)is crucial for optimizing production capacity,improving operational efficiency,and managing energy resources effectively.Moreover,precise ELF contributes to a smaller environmental footprint by reducing the risks of disruption,downtime,and waste.However,with increasingly complex energy consumption patterns driven by renewable energy integration and changing consumer behaviors,no single approach has emerged as universally effective.In response,this research presents a hybrid modeling framework that combines the strengths of Random Forest(RF)and Autoregressive Integrated Moving Average(ARIMA)models,enhanced with advanced feature selection—Minimum Redundancy Maximum Relevancy and Maximum Synergy(MRMRMS)method—to produce a sparse model.Additionally,the residual patterns are analyzed to enhance forecast accuracy.High-resolution weather data from Weather Underground and historical energy consumption data from PJM for Duke Energy Ohio and Kentucky(DEO&K)are used in this application.This methodology,termed SP-RF-ARIMA,is evaluated against existing approaches;it demonstrates more than 40%reduction in mean absolute error and root mean square error compared to the second-best method.
文摘Maintaining high-quality service supply and sustainability in modern cloud computing is essential to ensuring optimal system performance and energy efficiency.A novel approach is introduced in this study to decrease a system's overall delay and energy consumption by using a deep reinforcement learning(DRL)model to predict and allocate incoming workloads flexibly.The proposed methodology integrates workload prediction utilising long short-term memory(LSTM)networks with efficient load-balancing techniques led by deep Q-learning and Actor-critic algorithms.By continuously analysing current and historical data,the model can efficiently allocate resources,prioritizing speed and energy preservation.The experimental results demonstrate that our load balancing system,which utilises DRL,significantly reduces average response times and energy usage compared to traditional methods.This approach provides a scalable and adaptable strategy for enhancing cloud infrastructure performance.It consistently provides reliable and durable performance across a range of dynamic workloads.
基金supported by the National Natural Science Foundation of China(Grant 42204006)the Education Commission of Hubei Province of China(Grant D20232802)+1 种基金the Open Fund of Wuhan,Gravitationand Solid EarthTides,National Observationand Research Station(Grant WHYWZ202407)the Open Fund of Hubei Luojia Laboratory(Grant 230100020,230100019).
文摘Surface deformation calculations due to environmental loading typically rely on the Preliminary Reference Earth Model(PREM),which assumes a homogeneous and isotropic Earth structure,leading to noticeable errors.To enhance accuracy,the high-precision crustal model CRUST 1.0 is used to refine calculations of regional surface deformation caused by hydrological and non-tidal atmospheric loading.The improved model is applied to 27 Global Navigation Satellite System(GNSS)reference stations in the first phase of the Crustal Movement Observation Network of China(CMONOC),considering their geographical locations.Green's functions are employed to compute surface deformation at each site.Results indicate relative discrepancies of 11.78%and 14.14%for non-tidal atmospheric and hydrological loading compared to PREM,with vertical deformation differences reaching an average of 18.95%.Additionally,the distinct spatial distribution characteristics of the relative differences in each direction indicate that the improved RPREM model is more responsive to the mass variations derived from Gravity Recovery and Climate Experiment(GRACE).The results suggest that the improved PRREM model demonstrates higher sensitivity to loading variations than the PREM model.Utilizing the enhanced method of calculating surface deformation through the utilization of Green's function at the site could effectively reduce the calculation error caused by regional structure,leading to enhanced uniformity and isotropy of PREM.
基金supported by the National Natural Science Foundation of China(52350410465)the General Projects of Guangdong Natural Science Research Projects(2023A1515011520).
文摘Accurate daily suspended sediment load(SSL)prediction is essential for sustainable water resource management,sediment control,and environmental planning.However,SSL prediction is highly complex due to its nonlinear and dynamic nature,making traditional empirical models inadequate.This study proposes a novel hybrid approach,integrating the Adaptive Neuro-Fuzzy Inference System(ANFIS)with the Gradient-Based Optimizer(GBO),to enhance SSL forecasting accuracy.The research compares the performance of ANFIS-GBO with three alternative models:standard ANFIS,ANFIS with Particle Swarm Optimization(ANFIS-PSO),and ANFIS with Grey Wolf Optimization(ANFIS-GWO).Historical SSL and streamflow data from the Bailong River Basin,China,are used to train and validate the models.The input selection process is optimized using the Multivariate Adaptive Regression Splines(MARS)method.Model performance is evaluated using statistical metrics such as Root Mean Square Error(RMSE),Mean Absolute Error(MAE),Mean Absolute Percentage Error(MAPE),Nash Sutcliffe Efficiency(NSE),and Determination Coefficient(R^(2)).Additionally,visual assessments,including scatter plots,Taylor diagrams,and violin plots,provide further insights into model reliability.The results indicate that including historical SSL data improves predictive accuracy,with ANFIS-GBO outperforming the other models.ANFIS-GBO achieves the lowest RMSE and MAE and the highest NSE and R^(2),demonstrating its superior learning ability and adaptability.The findings highlight the effectiveness of nature-inspired optimization algorithms in enhancing sediment load forecasting and contribute to the advancement of AI-based hydrological modeling.Future research should explore the integration of additional environmental and climatic variables to enhance predictive capabilities further.
