This study developed a modeling methodology for statistical optimization-based geologic hazard susceptibility assessment,aiming to enhance the comprehensive performance and classification accuracy of the assessment mo...This study developed a modeling methodology for statistical optimization-based geologic hazard susceptibility assessment,aiming to enhance the comprehensive performance and classification accuracy of the assessment models.First,the cumulative probability method revealed that a low probability(15%)of geologic hazards between any two geologic hazard points occurred outside a buffer zone with a radius of 2297 m(i.e.,the distance threshold).The training dataset was established,consisting of negative samples(non-hazard points)randomly generated based on the distance threshold,positive samples(i.e.,historical hazards),and 13 conditioning factors.Then,models were built using five machine learning algorithms,namely random forest(RF),gradient boosting decision tree(GBDT),naive Bayes(NB),logistic regression(LR),and support vector machine(SVM).The comprehensive performance of the models was assessed using the area under the receiver operating characteristic curve(AUC)and overall accuracy(OA)as indicators,revealing that RF exhibited the best performance,with OA and AUC values of 2.7127 and 0.981,respectively.Furthermore,the machine learning models constructed by considering the distance threshold outperformed those built using the unoptimized dataset.The characteristic factors were ranked using the mutual information method,with their scores decreasing in the order of rainfall(0.1616),altitude(0.06),normalized difference vegetation index(NDVI;0.04),and distance from roads(0.03).Finally,the geologic hazard susceptibility classification was assessed using the natural breaks method combined with a clustering algorithm.The results indicate that the clustering algorithm exhibited higher classification accuracy than the natural breaks method.The findings of this study demonstrate that the proposed model optimization scheme can provide a scientific basis for the prevention and control of geologic hazards.展开更多
1.Introduction In recent years,intensifying climate extremes have triggered a sharp increase in global natural disasters,over 90%attributable to water-related hazards,particularly floods(Hirabayashi et al.,2013).Over ...1.Introduction In recent years,intensifying climate extremes have triggered a sharp increase in global natural disasters,over 90%attributable to water-related hazards,particularly floods(Hirabayashi et al.,2013).Over the past two decades,floods have inundated approximately 2.23 million km2 of land worldwide(Tellman et al.,2021),affecting over 250 million people and causing economic losses exceeding USD 651 billion(Devitt et al.,2023).Recent catastrophic floods in Pakistan,landslides in Indonesia,and dike breaches in China have intensified concerns over the effectiveness of current flood management strategies.展开更多
Slope units are divided according to the real topography and have clear geological characteristics,making them ideal units for evaluating the susceptibility to geological disasters.Based on the results of automaticall...Slope units are divided according to the real topography and have clear geological characteristics,making them ideal units for evaluating the susceptibility to geological disasters.Based on the results of automatically and manually corrected hydrological slope unit division,the Longhua District,Shenzhen City,Guangdong Province,was selected as the study area.A total of 15 influencing factors,namely Fluctuation,slope,slope aspect,curvature,topographic witness index(TWI),stream power index(SPI),topographic roughness index(TRI),annual average rainfall,distance to water system,engineering rock group,distance to fault,land use,normalized difference vegetation index(NDVI),nighttime light,and distance to road,were selected as evaluation indicators.The information volume model(IV)and random points were used to select non-geological disaster units,and then the random forest model(RF)was used to evaluate the susceptibility to geological disasters.The automatic slope unit and the hydrological slope unit were compared and analyzed in the random forest and information volume random forest models.The results show that the area under the curve(AUC)values of the automatic slope unit evaluation results are 0.931 for the IV-RF model and 0.716 for the RF model,which are 0.6%(IV-RF model)and 1.9%(RF model)higher than those for the hydrological slope unit.Based on a comparison of the evaluation methods based on the two types of slope units,the hydrological slope unit evaluation method based on manual correction is highly subjective,is complicated to operate,and has a low evaluation accuracy,whereas the evaluation method based on automatic slope unit division is efficient and accurate,is suitable for large-scale efficient geological disaster evaluation,and can better deal with the problem of geological disaster susceptibility evaluation.展开更多
The research findings on the ground motion and liquefaction potential analyses during the 2018 Great Indonesia Earthquake(M_(w)7.5)are significant and crucial.The earthquake triggered soil-structure damage due to liqu...The research findings on the ground motion and liquefaction potential analyses during the 2018 Great Indonesia Earthquake(M_(w)7.5)are significant and crucial.The earthquake triggered soil-structure damage due to liquefaction.This study,which thoroughly investigated four sites at Palu,was conducted by performing a comprehensive ground motion parameter analysis.The ground motion characteristics were presented and justified,particularly for the most impacted direction.Ground motion predictions were analysed to define the spectral accelerations,and matching spectral accelerations were conducted to produce ground motions for each site.Non-linear seismic ground response analysis based on the hyperbolic model of pressure pressure-dependent was performed to investigate cyclic soil behaviour.The results revealed that ground motion is crucial in significant soil damage,and the earthquake energy could trigger deep liquefaction.As the most significant ground motion,the vertical ground motion is essential in determining deep liquefaction.The discussion on the impact of liquefaction based on the results of the numerical analysis is presented.Significant ground motion with a longer duration could have a substantial impact on deep liquefaction in the study area.These findings depict how the 2018 Indonesia Earthquake(M_(w)7.5)triggered a mega-liquefaction in Palu City.The results could enhance the understanding of the importance of seismic hazard assessment.It is recommended that site investigation and soil improvement should be planned to counteract liquefaction damage before construction.This study also suggests conducting seismic hazard assessments for city development to minimise the potential disaster impact in the study area.展开更多
Shenzhen,a major city in southern China,has experienced rapid advancements in Unmanned Aerial Vehicle(UAV)technology,resulting in extensive logistics networks with thousands of daily flights.However,frequent disruptio...Shenzhen,a major city in southern China,has experienced rapid advancements in Unmanned Aerial Vehicle(UAV)technology,resulting in extensive logistics networks with thousands of daily flights.However,frequent disruptions due to its subtropical monsoon climate,including typhoons and gusty winds,present ongoing challenges.Despite the growing focus on operational costs and third-party risks,research on low-altitude urban wind fields remains scarce.This study addresses this gap by integrating wind field analysis into UAV path planning,introducing key innovations to the classical model.First,UAV wind resistance and turbulence constraints are analyzed,mapping high-wind-speed and turbulence-prone zones in the airspace.Second,wind dynamics are incorporated into path planning by considering airspeed and groundspeed variation,optimizing waypoint selection and flight speed adjustments to improve overall energy efficiency.Additionally,a wind-aware Theta*algorithm is proposed,leveraging wind vectors to expedite search process,while Computational Fluid Dynamics(CFD)techniques are employed to calculate wind fields.A case study of Shenzhen,examining wind patterns over the past decade,demonstrates a 6.23%improvement in groundspeed and a 7.69%reduction in energy consumption compared to wind-agnostic models.This framework advances UAV logistics by enhancing route safety and energy efficiency,contributing to more cost-effective operations.展开更多
Waste graphitization cathode carbon blocks are a type of hazardous solid waste generated during the aluminum electrolysis process,and their proper disposal is a key step in the resource utilization of discarded graphi...Waste graphitization cathode carbon blocks are a type of hazardous solid waste generated during the aluminum electrolysis process,and their proper disposal is a key step in the resource utilization of discarded graphite.This study utilizes the porous“defect advantage”of a cathode carbon block matrix to prepare silicon-doped and asphalt-coated detoxified and purified waste graphitization cathode carbon blocks for use as high-performance silicon/carbon composite anode materials.The results show that the uniformly silicondoped silicon/carbon composite material features a unique amorphous carbon-encapsulated“locked silicon”structure,which effectively addresses issues such as cathode volume expansion,excessive growth of the solid electrolyte interphase(SEI)film,and poor electrical contact between active materials.Consequently,electrochemical performance is enhanced.After assembly in a half-cell,the PSCC/10%Si@C(purified waste graphitization cathode carbon/10%Si@C)material exhibits optimal electrochemical stability,with an initial charging specific capacity of 514.5 mAh/g at 0.1 C(1 C=170 mA/g)and a capacity retention rate of 95.1%after 100 cycles.At a charge rate of 2.0 C,a specific capacity of 216.9 mAh/g is achieved.This technology provides a new pathway for the economical and high-value utilization of waste cathode carbon blocks and the development of low-cost,high-performance anode materials.展开更多
1.Introduction Artificial intelligence(AI)is rapidly reshaping geoscience,from Earth observation interpretation and hazard forecasting to subsurface characterisation and Earth system modelling(Kochupillai et al.,2022;...1.Introduction Artificial intelligence(AI)is rapidly reshaping geoscience,from Earth observation interpretation and hazard forecasting to subsurface characterisation and Earth system modelling(Kochupillai et al.,2022;Sun et al.,2024).These capabilities emerge at a time when geoscientific evidence is increasingly informing high-stakes decisions about climate adaptation,resource development,and disaster risk reduction(McGovern et al.,2022).展开更多
Na-ion batteries are considered a promising next-generation battery alternative to Li-ion batteries,due to the abundant Na resources and low cost.Most efforts focus on developing new materials to enhance energy densit...Na-ion batteries are considered a promising next-generation battery alternative to Li-ion batteries,due to the abundant Na resources and low cost.Most efforts focus on developing new materials to enhance energy density and electrochemical performance to enable it comparable to Li-ion batteries,without considering thermal hazard of Na-ion batteries and comparison with Li-ion batteries.To address this issue,our work comprehensively compares commercial prismatic lithium iron phosphate(LFP) battery,lithium nickel cobalt manganese oxide(NCM523) battery and Na-ion battery of the same size from thermal hazard perspective using Accelerating Rate Calorimeter.The thermal hazard of the three cells is then qualitatively assessed from thermal stability,early warning and thermal runaway severity perspectives by integrating eight characteristic parameters.The Na-ion cell displays comparable thermal stability with LFP while LFP exhibits the lowest thermal runaway hazard and severity.However,the Na-ion cell displays the lowest safety venting temperature and the longest time interval between safety venting and thermal runaway,allowing the generated gas to be released as early as possible and detected in a timely manner,providing sufficient time for early warning.Finally,a database of thermal runaway characteristic temperature for Li-ion and Na-ion cells is collected and processed to delineate four thermal hazard levels for quantitative assessment.Overall,LFP cells exhibit the lowest thermal hazard,followed by the Na-ion cells and NCM523 cells.This work clarifies the thermal hazard discrepancy between the Na-ion cell and prevalent Li-ion cells,providing crucial guidance for development and application of Na-ion cell.展开更多
0 INTRODUCTION.According to the China Earthquake Networks Center,an M6.8 earthquake struck Dingri County,Xizang Autonomous Region,China,on 7 January 2025 at 9:05 a.m.local time.The epicenter is located at 28.5°N,...0 INTRODUCTION.According to the China Earthquake Networks Center,an M6.8 earthquake struck Dingri County,Xizang Autonomous Region,China,on 7 January 2025 at 9:05 a.m.local time.The epicenter is located at 28.5°N,87.45°E,with a depth of~10 km.展开更多
Hurricanes are one of the most destructive natural disasters that can cause catastrophic losses to both communities and infrastructure.Assessment of hurricane risk furnishes a spatial depiction of the interplay among ...Hurricanes are one of the most destructive natural disasters that can cause catastrophic losses to both communities and infrastructure.Assessment of hurricane risk furnishes a spatial depiction of the interplay among hazard,vulnerability,exposure,and mitigation capacity,crucial for understanding and managing the risks hurricanes pose to communities.These assessments aid in gauging the efficacy of existing hurricane mitigation strategies and gauging their resilience across diverse climate change scenarios.A systematic review was conducted,encompassing 94 articles,to scrutinize the structure,data inputs,assumptions,methodologies,perils modelled,and key predictors of hurricane risk.This review identified key research gaps essential for enhancing future risk assessments.The complex interaction between hurricane perils may be disastrous and underestimated in the majority of risk assessments which focus on a single peril,commonly storm surge and flood,resulting in inadequacies in disaster resilience planning.Most risk assessments were based on hurricane frequency rather than hurricane damage,which is more insightful for policymakers.Furthermore,considering secondary indirect impacts stemming from hurricanes,including real estate market and business interruption,could enrich economic impact assessments.Hurricane mitigation measures were the most under-utilised category of predictors leveraged in only 5%of studies.The top six predictive factors for hurricane risk were land use,slope,precipitation,elevation,population density,and soil texture/drainage.Another notable research gap identified was the potential of machine learning techniques in risk assessments,offering advantages over traditional MCDM and numerical models due to their ability to capture complex nonlinear relationships and adaptability to different study regions.Existing machine learning based risk assessments leverage random forest models(42%of studies)followed by neural network models(19%of studies),with further research required to investigate diverse machine learning algorithms such as ensemble models.A further research gap is model validation,in particular assessing transferability to a new study region.Additionally,harnessing simulated data and refining projections related to demographic and built environment dynamics can bolster the sophistication of climate change scenario assessments.By addressing these research gaps,hurricane risk assessments can furnish invaluable insights for national policymakers,facilitating the development of robust hurricane mitigation strategies and the construction of hurricane-resilient communities.To the authors’knowledge,this represents the first literature review specifically dedicated to quantitative hurricane risk assessments,encompassing a comparison of Multi-criteria Decision Making(MCDM),numerical models,and machine learning models.Ultimately,advancements in hurricane risk assessments and modelling stand poised to mitigate potential losses to communities and infrastructure both in the immediate and long-term future.展开更多
The large-scale accumulation of industrial solid waste,including red mud and coal gangue,coupled with goafs left by under-ground mining activities,poses significant challenges to sustainable human development.In this ...The large-scale accumulation of industrial solid waste,including red mud and coal gangue,coupled with goafs left by under-ground mining activities,poses significant challenges to sustainable human development.In this study,red mud,coal gangue,and othersolid wastes were used to prepare underground backfilling materials.The utilization rate of the total solid waste reached 95%,with redmud accounting for approximately 40wt% of the total.The unconfined compressive strength,setting time,and slump tests were conduc-ted to evaluate the mechanical properties of the material.At the optimal ratio,the 7-and 28-d strengths reach 4.4 and 6.9 MPa,respect-ively.The initial and final setting times were 200 and 250 min,respectively,whereas the initial and 1-h slump exceed 250 and 210 mm,respectively.X-ray diffraction(XRD),Fourier-transform infrared spectroscopy(FTIR),and scanning electron microscopy(SEM)wereemployed to explore the microstructure,phase composition,and chemical bonding within the material.Needle-like,clustered,and granu-lar hydration products were observed,and the primary crystalline structures were identified as ettringite,gmelinite,C-A-S-H,andC-S-H.In addition,a thorough environmental risk assessment was conducted,complemented by detailed economic cost and carbonemission calculations.During the creation of backfill material,hazardous elements from solid waste are immobilized through adsorption,precipitation,and incorporation into the crystal lattice.The immobilization efficiencies for Ni,Al,Cr^(6+),and As were 97.03%,94.32%,86.43%,and 84.22%,respectively,at a pH of 8.49.Moreover,the use of solid waste as a raw material results in considerable cost savingsand marked reduction in carbon emissions.This study innovatively promotes the green cycle of alumina production in the bauxite miningindustry.展开更多
As an essential part of the urban infrastructure,underground utility tunnels have a long service life,complex structural performance evolution and dynamic changes both inside and outside the tunnel.These combined fact...As an essential part of the urban infrastructure,underground utility tunnels have a long service life,complex structural performance evolution and dynamic changes both inside and outside the tunnel.These combined factors result in a wide variety of disaster risks during the operation and maintenance phase,which make risk management and control particularly challenging.This work first reviews three common representative disaster factors during the operation and maintenance period:settlement,earthquakes,and explosions.It summarizes the causes of disasters,key technologies,and research methods.Then,it delves into the research on the intelligent operation and maintenance architecture for utility tunnels.Additionally,it explores the data challenges,monitoring technologies,and management platform architectures faced during the operation and maintenance process.This work provides new research perspectives for the long-term,healthy,and sustainable development of utility tunnels,which serve as the underground arteries of cities.展开更多
Landslides significantly threaten lives and infrastructure, especially in seismically active regions. This study conducts a probabilistic analysis of seismic landslide runout behavior, leveraging a large-deformation f...Landslides significantly threaten lives and infrastructure, especially in seismically active regions. This study conducts a probabilistic analysis of seismic landslide runout behavior, leveraging a large-deformation finite-element (LDFE) model that accounts for the three-dimensional (3D) spatial variability and cross-correlation in soil strength — a reflection of natural soils' inherent properties. LDFE model results are validated by comparing them against previous studies, followed by an examination of the effects of univariable, uncorrelated bivariable, and cross-correlated bivariable random fields on landslide runout behavior. The study's findings reveal that integrating variability in both friction angle and cohesion within uncorrelated bivariable random fields markedly influences runout distances when compared with univariable random fields. Moreover, the cross-correlation of soil cohesion and friction angle dramatically affects runout behavior, with positive correlations enlarging and negative correlations reducing runout distances. Transitioning from two-dimensional (2D) to 3D analyses, a more realistic representation of sliding surface, landslide velocity, runout distance and final deposit morphology is achieved. The study highlights that 2D random analyses substantially underestimate the mean value and overestimate the variability of runout distance, underscoring the importance of 3D modeling in accurately predicting landslide behavior. Overall, this work emphasizes the essential role of understanding 3D cross-correlation in soil strength for landslide hazard assessment and mitigation strategies.展开更多
Climate change and rising temperatures are accelerating the rate of deglaciation in the Hindu Kush Karakoram Himalaya(HKH)ranges,leading to the formation of new glacial lakes and the expansion of existing ones.These l...Climate change and rising temperatures are accelerating the rate of deglaciation in the Hindu Kush Karakoram Himalaya(HKH)ranges,leading to the formation of new glacial lakes and the expansion of existing ones.These lakes are often vulnerable to failure,posing a significant threat to downstream communities and infrastructure.Therefore,a comprehensive assessment of Glacier-Lake Outburst Flood(GLOF)hazards and risk assessment is crucial to evaluate flood runout characteristics and identify settlements and infrastructure that are exposed and vulnerable to floods,aiding in the development and implementation of risk reduction strategies.This study aims to simulate a GLOF event induced by the Shisper glacier lake in northern Pakistan,using the HEC-RAS,and to assess its impact on settlements,infrastructure,and agricultural land.For the hydrometeorological analysis of the GLOF event,topographic data from unmanned aerial vehicles(UAVs),stream profiles,discharge data,Manning's roughness coefficient(n),and land use/land cover(LULC)were analyzed using HEC-RAS and geographic information system(GIS).During the GLOF event on May 7,2022,a maximum water depth of 6.3 m and a maximum velocity of 9.5 m/s were recorded.Based on the runout characteristics of this event,vulnerability and risk assessments have been calculated.The physical,social,and environmental vulnerabilities of the at-risk elements were evaluated using the analytical hierarchy process(AHP)and integrated with the hazard data to develop a risk map.The study identified the areas,infrastructure and settlements susceptible to GLOF hazard to support the development and implementation of targeted and evidence-based mitigation and adaptation strategies.展开更多
Objective We aimed to investigate the patterns of fasting blood glucose(FBG)trajectories and analyze the relationship between various occupational hazard factors and FBG trajectories in male steelworkers.Methods The s...Objective We aimed to investigate the patterns of fasting blood glucose(FBG)trajectories and analyze the relationship between various occupational hazard factors and FBG trajectories in male steelworkers.Methods The study cohort included 3,728 workers who met the selection criteria for the Tanggang Occupational Cohort(TGOC)between 2017 and 2022.A group-based trajectory model was used to identify the FBG trajectories.Environmental risk scores(ERS)were constructed using regression coefficients from the occupational hazard model as weights.Univariate and multivariate logistic regression analyses were performed to explore the effects of occupational hazard factors using the ERS on FBG trajectories.Results FBG trajectories were categorized into three groups.An association was observed between high temperature,noise exposure,and FBG trajectory(P<0.05).Using the first quartile group of ERS1 as a reference,the fourth quartile group of ERS1 had an increased risk of medium and high FBG by 1.90and 2.21 times,respectively(odds ratio[OR]=1.90,95%confidence interval[CI]:1.17–3.10;OR=2.21,95%CI:1.09–4.45).Conclusion An association was observed between occupational hazards based on ERS and FBG trajectories.The risk of FBG trajectory levels increase with an increase in ERS.展开更多
With the rapid development of virtual reality(VR)and augmented reality(AR)technologies,their application potential in the field of education has become increasingly significant.For a long time,fire safety education in...With the rapid development of virtual reality(VR)and augmented reality(AR)technologies,their application potential in the field of education has become increasingly significant.For a long time,fire safety education in university laboratories has faced numerous challenges,and traditional teaching methods have been insufficiently effective,with high-risk scenarios difficult to realistically recreate.Especially in special scenarios involving hazardous chemicals,conventional training methods struggle to enable learners to achieve deep understanding and behavioral formation.This study systematically integrates immersive technology theory with safety education needs,providing a replicable technical solution for safety education in high-risk environments.Its modular design approach has reference value for expansion into other professional fields,offering practical evidence for innovation in safety education models in the digital age.展开更多
Retrogressive landslides in sensitive clays pose significant risks to nearby infrastructure,as natural toe erosion or localized disturbances can trigger progressive block failures.While prior studies have largely reli...Retrogressive landslides in sensitive clays pose significant risks to nearby infrastructure,as natural toe erosion or localized disturbances can trigger progressive block failures.While prior studies have largely relied on two-dimensional(2D)large-deformation analyses,such models overlook key three-dimensional(3D)failure mechanisms and variability effects.This study develops a 3D probabilistic framework by integrating the Coupled Eulerian–Lagrangian(CEL)method with random field theory to simulate retrogressive landslides in spatially variable clay.Using Monte Carlo simulations,we compare 2D and 3D random large-deformation models to evaluate failure modes,runout distances,sliding velocities,and influence zones.The 3D analyses captured more complex failure modes—such as lateral retrogression and asynchronous block mobilization across slope width.Additionally,the 3D analyses predict longer mean runout distances(13.76 vs.11.92 m),wider mean influence distance(11.35 vs.8.73 m),and higher mean sliding velocities(4.66 vs.3.94 m/s)than their 2D counterparts.Moreover,3D models exhibit lower coefficients of variation(e.g.,0.10 for runout distance)due to spatial averaging across slope width.Probabilistic hazard assessment shows that 2D models significantly underpredict near-field failure probabilities(e.g.,48.8%vs.89.9%at 12 m from the slope toe).These findings highlight the limitations of 2D analyses and the importance of multi-directional spatial variability for robust geohazard assessments.The proposed 3D framework enables more realistic prediction of landslide mobility and supports the design of safer,risk-informed infrastructure.展开更多
Frequent glacier-related watershed geohazard chains are causing severe damage to life and infrastructure,reported consistently from the Eastern Himalayan Syntaxis.This paper presents a systematic method for researchin...Frequent glacier-related watershed geohazard chains are causing severe damage to life and infrastructure,reported consistently from the Eastern Himalayan Syntaxis.This paper presents a systematic method for researching geohazard,from regional to individual scale.The methodology includes the establishment of geological chain inventories,discrimination of geohazard chain modes,analyses of dynamics and dam breaches,and risk assessments.The following results were obtained:(1)In the downstream of Yarlung Zangbo River,175 sites were identified as high-risk for river blockage disasters,indicating the development of watershed geohazards.Five geohazard chain modes were summarized by incorporating geomorphological characteristics,historical events,landslide zoning,and materials.The risk areas of typical hazard were identified and assessed using InSAR data.(2)Glacier-related watershed geohazard chains are significantly different from traditional landslides.A detailed inversion analysis was conducted on the massive rock-ice avalanche in the Sedongpu gully in 2021.This particular event lasted roughly 300 seconds,with a maximum flow velocity of 77.2 m/s and a maximum flow height of 93 meters.By scrutinizing the dynamic processes and mechanical characteristics,mobility stages and phase transitions can be divided into four stages.(3)Watershed geohazard chains tend to block rivers.The peak breach discharge of the Yigong Landslide reached 12.4×10^(4) m^(3)/s,which is 36 times the volume of the seasonal flood discharge in the Yigong River.Megafloods caused by landslide dam breaches have significantly shaped the geomorphology.This study offers insights into disaster patterns and the multistaged movement characteristics of glacier-related watershed geohazard chains,providing a comprehensive method for investigations and assessments in glacial regions.展开更多
Flexible and wearable electronics are attracting surging attention due to their potential applications in human health monitoring and precision therapies.Safety hazards including strong magnetic field and electric lea...Flexible and wearable electronics are attracting surging attention due to their potential applications in human health monitoring and precision therapies.Safety hazards including strong magnetic field and electric leakage are big risk factors for human health.It remains challenging to develop self‐powered and wearable safety hazard sensors that could not only be able to monitor human motions but also have functions for detecting potential hazards.In this work,we fabricated a self‐powered,shapeable,and wearable magnetic triboelectric nanogenerator(MTENG)based on ferrofluid,Ecoflex,and carbonized silk fabric that possessed effective hazard prevention and biomechanical motion sensing ability.A peak open‐circuit voltage of 0.7 V and short‐circuit current of 10μA m^(−2)can be achieved when magnetic field is changed between 3.5 and 37.1 mT.As a component of triboelectric layer of the MTENG,ferrofluid can substantially extend the range of its sensing capabilities to many hazardous cues such as dangerous magnetic field.Furtherly,the developed multifunctional and self‐powered sensor can be used to monitor human activities such as drinking water and bending finger.This effort opens up a new design opportunity for hazard avoidance wearable electronics and self‐powered sensors.展开更多
A glacier hazard chain can form a long-runout mass flow and generate a large flood,affecting downstream areas hundreds of kilometers away from the initiating hazard site.This study focuses on the Yarlung Zangbo Daxiag...A glacier hazard chain can form a long-runout mass flow and generate a large flood,affecting downstream areas hundreds of kilometers away from the initiating hazard site.This study focuses on the Yarlung Zangbo Daxiagu.The objective is to address two key unresolved issues:the evolution of detached glacier materials into debris flows or debris floods and the amplification of the impact range and threats.A comprehensive framework is developed that considers the impacts of near-field and far-field hazards.Numerical modeling,remote sensing,and field investigations were integrated to understand the interactions,transformations,and amplifications of hazards in the glacier hazard chain.The results indicate that extensive,nearly saturated sediments on the glacier valley floor,when entrained,amplify the magnitude of the mass flow.The topography plays a crucial role.When the valley outlet is perpendicular to the river course,topographic obstacles cause immediate halting,resulting in the formation of high barrier dams.Conversely,when the glacier valley aligns nearly parallel to the river course,the mass flow can travel a much longer distance upon entering the river,causing an enlarged affected area.The barrier dams can breach rapidly,causing breaching floods that amplify the downstream impact from several kilometers to hundreds of kilometers.Our analysis reveals that the overall impacts remain spatially limited.Specifically,downstream areas along the Yarlung Zangbo-Brahmaputra River are unlikely to face greater threats from the upstream floods than local monsoon floods.Our findings provide the foundation for the management of glacier hazard chains.展开更多
基金supported by a project entitled Loess Plateau Region-Watershed-Slope Geological Hazard Multi-Scale Collaborative Intelligent Early Warning System of the National Key R&D Program of China(2022YFC3003404)a project of the Shaanxi Youth Science and Technology Star(2021KJXX-87)public welfare geological survey projects of Shaanxi Institute of Geologic Survey(20180301,201918,202103,and 202413)。
文摘This study developed a modeling methodology for statistical optimization-based geologic hazard susceptibility assessment,aiming to enhance the comprehensive performance and classification accuracy of the assessment models.First,the cumulative probability method revealed that a low probability(15%)of geologic hazards between any two geologic hazard points occurred outside a buffer zone with a radius of 2297 m(i.e.,the distance threshold).The training dataset was established,consisting of negative samples(non-hazard points)randomly generated based on the distance threshold,positive samples(i.e.,historical hazards),and 13 conditioning factors.Then,models were built using five machine learning algorithms,namely random forest(RF),gradient boosting decision tree(GBDT),naive Bayes(NB),logistic regression(LR),and support vector machine(SVM).The comprehensive performance of the models was assessed using the area under the receiver operating characteristic curve(AUC)and overall accuracy(OA)as indicators,revealing that RF exhibited the best performance,with OA and AUC values of 2.7127 and 0.981,respectively.Furthermore,the machine learning models constructed by considering the distance threshold outperformed those built using the unoptimized dataset.The characteristic factors were ranked using the mutual information method,with their scores decreasing in the order of rainfall(0.1616),altitude(0.06),normalized difference vegetation index(NDVI;0.04),and distance from roads(0.03).Finally,the geologic hazard susceptibility classification was assessed using the natural breaks method combined with a clustering algorithm.The results indicate that the clustering algorithm exhibited higher classification accuracy than the natural breaks method.The findings of this study demonstrate that the proposed model optimization scheme can provide a scientific basis for the prevention and control of geologic hazards.
基金supported by National Key Research and Development Program of China(Grants No.2022YFF0802401 and 2023YFF0806900)China Postdoctoral Science Foundation(Grants No.2023M743456,GZB20230740,and 2024T170908).
文摘1.Introduction In recent years,intensifying climate extremes have triggered a sharp increase in global natural disasters,over 90%attributable to water-related hazards,particularly floods(Hirabayashi et al.,2013).Over the past two decades,floods have inundated approximately 2.23 million km2 of land worldwide(Tellman et al.,2021),affecting over 250 million people and causing economic losses exceeding USD 651 billion(Devitt et al.,2023).Recent catastrophic floods in Pakistan,landslides in Indonesia,and dike breaches in China have intensified concerns over the effectiveness of current flood management strategies.
文摘Slope units are divided according to the real topography and have clear geological characteristics,making them ideal units for evaluating the susceptibility to geological disasters.Based on the results of automatically and manually corrected hydrological slope unit division,the Longhua District,Shenzhen City,Guangdong Province,was selected as the study area.A total of 15 influencing factors,namely Fluctuation,slope,slope aspect,curvature,topographic witness index(TWI),stream power index(SPI),topographic roughness index(TRI),annual average rainfall,distance to water system,engineering rock group,distance to fault,land use,normalized difference vegetation index(NDVI),nighttime light,and distance to road,were selected as evaluation indicators.The information volume model(IV)and random points were used to select non-geological disaster units,and then the random forest model(RF)was used to evaluate the susceptibility to geological disasters.The automatic slope unit and the hydrological slope unit were compared and analyzed in the random forest and information volume random forest models.The results show that the area under the curve(AUC)values of the automatic slope unit evaluation results are 0.931 for the IV-RF model and 0.716 for the RF model,which are 0.6%(IV-RF model)and 1.9%(RF model)higher than those for the hydrological slope unit.Based on a comparison of the evaluation methods based on the two types of slope units,the hydrological slope unit evaluation method based on manual correction is highly subjective,is complicated to operate,and has a low evaluation accuracy,whereas the evaluation method based on automatic slope unit division is efficient and accurate,is suitable for large-scale efficient geological disaster evaluation,and can better deal with the problem of geological disaster susceptibility evaluation.
基金The World Class Professor(WCP)Program of the Directorate of Resources,Directorate General of Higher Education,Ministry of Education and Culture in 2023 supports this studythe JAPAN-ASEAN Science and Technology Innovation Platform(JASTIP-WP4)+3 种基金the University of Bengkulu's International Collaboration Research Fund(2183/UN30.15/LT/2019)for partial fundingthe C2F Fund for Postdoctoral Fellowship from Chulalongkorn Universitythe Thailand Science Research and Innovation Fund Chulalongkorn University(DISF68210001)the National Research Council of Thailand(N42A670572)。
文摘The research findings on the ground motion and liquefaction potential analyses during the 2018 Great Indonesia Earthquake(M_(w)7.5)are significant and crucial.The earthquake triggered soil-structure damage due to liquefaction.This study,which thoroughly investigated four sites at Palu,was conducted by performing a comprehensive ground motion parameter analysis.The ground motion characteristics were presented and justified,particularly for the most impacted direction.Ground motion predictions were analysed to define the spectral accelerations,and matching spectral accelerations were conducted to produce ground motions for each site.Non-linear seismic ground response analysis based on the hyperbolic model of pressure pressure-dependent was performed to investigate cyclic soil behaviour.The results revealed that ground motion is crucial in significant soil damage,and the earthquake energy could trigger deep liquefaction.As the most significant ground motion,the vertical ground motion is essential in determining deep liquefaction.The discussion on the impact of liquefaction based on the results of the numerical analysis is presented.Significant ground motion with a longer duration could have a substantial impact on deep liquefaction in the study area.These findings depict how the 2018 Indonesia Earthquake(M_(w)7.5)triggered a mega-liquefaction in Palu City.The results could enhance the understanding of the importance of seismic hazard assessment.It is recommended that site investigation and soil improvement should be planned to counteract liquefaction damage before construction.This study also suggests conducting seismic hazard assessments for city development to minimise the potential disaster impact in the study area.
基金supported by the National Natural Science Foundation of China(No.U2433214)。
文摘Shenzhen,a major city in southern China,has experienced rapid advancements in Unmanned Aerial Vehicle(UAV)technology,resulting in extensive logistics networks with thousands of daily flights.However,frequent disruptions due to its subtropical monsoon climate,including typhoons and gusty winds,present ongoing challenges.Despite the growing focus on operational costs and third-party risks,research on low-altitude urban wind fields remains scarce.This study addresses this gap by integrating wind field analysis into UAV path planning,introducing key innovations to the classical model.First,UAV wind resistance and turbulence constraints are analyzed,mapping high-wind-speed and turbulence-prone zones in the airspace.Second,wind dynamics are incorporated into path planning by considering airspeed and groundspeed variation,optimizing waypoint selection and flight speed adjustments to improve overall energy efficiency.Additionally,a wind-aware Theta*algorithm is proposed,leveraging wind vectors to expedite search process,while Computational Fluid Dynamics(CFD)techniques are employed to calculate wind fields.A case study of Shenzhen,examining wind patterns over the past decade,demonstrates a 6.23%improvement in groundspeed and a 7.69%reduction in energy consumption compared to wind-agnostic models.This framework advances UAV logistics by enhancing route safety and energy efficiency,contributing to more cost-effective operations.
基金supported by the National Natural Science Foundation of China(No.52274346).
文摘Waste graphitization cathode carbon blocks are a type of hazardous solid waste generated during the aluminum electrolysis process,and their proper disposal is a key step in the resource utilization of discarded graphite.This study utilizes the porous“defect advantage”of a cathode carbon block matrix to prepare silicon-doped and asphalt-coated detoxified and purified waste graphitization cathode carbon blocks for use as high-performance silicon/carbon composite anode materials.The results show that the uniformly silicondoped silicon/carbon composite material features a unique amorphous carbon-encapsulated“locked silicon”structure,which effectively addresses issues such as cathode volume expansion,excessive growth of the solid electrolyte interphase(SEI)film,and poor electrical contact between active materials.Consequently,electrochemical performance is enhanced.After assembly in a half-cell,the PSCC/10%Si@C(purified waste graphitization cathode carbon/10%Si@C)material exhibits optimal electrochemical stability,with an initial charging specific capacity of 514.5 mAh/g at 0.1 C(1 C=170 mA/g)and a capacity retention rate of 95.1%after 100 cycles.At a charge rate of 2.0 C,a specific capacity of 216.9 mAh/g is achieved.This technology provides a new pathway for the economical and high-value utilization of waste cathode carbon blocks and the development of low-cost,high-performance anode materials.
基金supported by the Natural Science Foundation of Jiangsu Province,China(Grant No.BK20240937)the Natural Science Foundation of Shandong Province(Grant No.ZR2021QE187)+2 种基金the Shandong Higher Education“Young Entrepreneurship Talents Introduction and Cultivation Program”Project(Grant No.ZXQT20221228001)the Natural Science Foundation of China(Grant No.42502273)the Science and Technology Innovation Program of Hunan Province(Grant No.2022RC4028).
文摘1.Introduction Artificial intelligence(AI)is rapidly reshaping geoscience,from Earth observation interpretation and hazard forecasting to subsurface characterisation and Earth system modelling(Kochupillai et al.,2022;Sun et al.,2024).These capabilities emerge at a time when geoscientific evidence is increasingly informing high-stakes decisions about climate adaptation,resource development,and disaster risk reduction(McGovern et al.,2022).
基金supported by the National Key R&D Program of China(No.2022YFE0207400)supported by the Xiaomi Young Talents Programsupported by the Youth Innovation Promotion Association CAS(No.Y201768)。
文摘Na-ion batteries are considered a promising next-generation battery alternative to Li-ion batteries,due to the abundant Na resources and low cost.Most efforts focus on developing new materials to enhance energy density and electrochemical performance to enable it comparable to Li-ion batteries,without considering thermal hazard of Na-ion batteries and comparison with Li-ion batteries.To address this issue,our work comprehensively compares commercial prismatic lithium iron phosphate(LFP) battery,lithium nickel cobalt manganese oxide(NCM523) battery and Na-ion battery of the same size from thermal hazard perspective using Accelerating Rate Calorimeter.The thermal hazard of the three cells is then qualitatively assessed from thermal stability,early warning and thermal runaway severity perspectives by integrating eight characteristic parameters.The Na-ion cell displays comparable thermal stability with LFP while LFP exhibits the lowest thermal runaway hazard and severity.However,the Na-ion cell displays the lowest safety venting temperature and the longest time interval between safety venting and thermal runaway,allowing the generated gas to be released as early as possible and detected in a timely manner,providing sufficient time for early warning.Finally,a database of thermal runaway characteristic temperature for Li-ion and Na-ion cells is collected and processed to delineate four thermal hazard levels for quantitative assessment.Overall,LFP cells exhibit the lowest thermal hazard,followed by the Na-ion cells and NCM523 cells.This work clarifies the thermal hazard discrepancy between the Na-ion cell and prevalent Li-ion cells,providing crucial guidance for development and application of Na-ion cell.
基金funded by the National Key R&D Program of China(No.2020YFC150071)partly supported by the Shaanxi Province Geoscience Big Data and Geohazard Prevention Innovation Team(2022)and the Research Funds for the Interdisciplinary Projects,CHU(No.300104240914)。
文摘0 INTRODUCTION.According to the China Earthquake Networks Center,an M6.8 earthquake struck Dingri County,Xizang Autonomous Region,China,on 7 January 2025 at 9:05 a.m.local time.The epicenter is located at 28.5°N,87.45°E,with a depth of~10 km.
基金supported by the Centre for Advanced Modelling and Geospatial Information Systems(CAMGIS),University of Technology Sydney(UTS),Australia and was supported by the Research Training Program(RTP)of the Australian Government.
文摘Hurricanes are one of the most destructive natural disasters that can cause catastrophic losses to both communities and infrastructure.Assessment of hurricane risk furnishes a spatial depiction of the interplay among hazard,vulnerability,exposure,and mitigation capacity,crucial for understanding and managing the risks hurricanes pose to communities.These assessments aid in gauging the efficacy of existing hurricane mitigation strategies and gauging their resilience across diverse climate change scenarios.A systematic review was conducted,encompassing 94 articles,to scrutinize the structure,data inputs,assumptions,methodologies,perils modelled,and key predictors of hurricane risk.This review identified key research gaps essential for enhancing future risk assessments.The complex interaction between hurricane perils may be disastrous and underestimated in the majority of risk assessments which focus on a single peril,commonly storm surge and flood,resulting in inadequacies in disaster resilience planning.Most risk assessments were based on hurricane frequency rather than hurricane damage,which is more insightful for policymakers.Furthermore,considering secondary indirect impacts stemming from hurricanes,including real estate market and business interruption,could enrich economic impact assessments.Hurricane mitigation measures were the most under-utilised category of predictors leveraged in only 5%of studies.The top six predictive factors for hurricane risk were land use,slope,precipitation,elevation,population density,and soil texture/drainage.Another notable research gap identified was the potential of machine learning techniques in risk assessments,offering advantages over traditional MCDM and numerical models due to their ability to capture complex nonlinear relationships and adaptability to different study regions.Existing machine learning based risk assessments leverage random forest models(42%of studies)followed by neural network models(19%of studies),with further research required to investigate diverse machine learning algorithms such as ensemble models.A further research gap is model validation,in particular assessing transferability to a new study region.Additionally,harnessing simulated data and refining projections related to demographic and built environment dynamics can bolster the sophistication of climate change scenario assessments.By addressing these research gaps,hurricane risk assessments can furnish invaluable insights for national policymakers,facilitating the development of robust hurricane mitigation strategies and the construction of hurricane-resilient communities.To the authors’knowledge,this represents the first literature review specifically dedicated to quantitative hurricane risk assessments,encompassing a comparison of Multi-criteria Decision Making(MCDM),numerical models,and machine learning models.Ultimately,advancements in hurricane risk assessments and modelling stand poised to mitigate potential losses to communities and infrastructure both in the immediate and long-term future.
基金financially supported by the National Nature Science Foundation of China(No.U23A20557)the Young Elite Scientists Sponsorship Program by China Association for Science and Technology(No.2022QNRC001)Fundamental Research Funds for the Central Universities,China(No.00007720)。
文摘The large-scale accumulation of industrial solid waste,including red mud and coal gangue,coupled with goafs left by under-ground mining activities,poses significant challenges to sustainable human development.In this study,red mud,coal gangue,and othersolid wastes were used to prepare underground backfilling materials.The utilization rate of the total solid waste reached 95%,with redmud accounting for approximately 40wt% of the total.The unconfined compressive strength,setting time,and slump tests were conduc-ted to evaluate the mechanical properties of the material.At the optimal ratio,the 7-and 28-d strengths reach 4.4 and 6.9 MPa,respect-ively.The initial and final setting times were 200 and 250 min,respectively,whereas the initial and 1-h slump exceed 250 and 210 mm,respectively.X-ray diffraction(XRD),Fourier-transform infrared spectroscopy(FTIR),and scanning electron microscopy(SEM)wereemployed to explore the microstructure,phase composition,and chemical bonding within the material.Needle-like,clustered,and granu-lar hydration products were observed,and the primary crystalline structures were identified as ettringite,gmelinite,C-A-S-H,andC-S-H.In addition,a thorough environmental risk assessment was conducted,complemented by detailed economic cost and carbonemission calculations.During the creation of backfill material,hazardous elements from solid waste are immobilized through adsorption,precipitation,and incorporation into the crystal lattice.The immobilization efficiencies for Ni,Al,Cr^(6+),and As were 97.03%,94.32%,86.43%,and 84.22%,respectively,at a pH of 8.49.Moreover,the use of solid waste as a raw material results in considerable cost savingsand marked reduction in carbon emissions.This study innovatively promotes the green cycle of alumina production in the bauxite miningindustry.
基金financially supported by the Scientific Research Projects of the Education Department of Zhejiang Province(Grant No.Y202454744)the Ningbo Public Welfare Science and Technology Project(Grant Nos.2023S007 and 2023S165)the Key Research and Development Program of Zhejiang(Grant No.2023C03183).
文摘As an essential part of the urban infrastructure,underground utility tunnels have a long service life,complex structural performance evolution and dynamic changes both inside and outside the tunnel.These combined factors result in a wide variety of disaster risks during the operation and maintenance phase,which make risk management and control particularly challenging.This work first reviews three common representative disaster factors during the operation and maintenance period:settlement,earthquakes,and explosions.It summarizes the causes of disasters,key technologies,and research methods.Then,it delves into the research on the intelligent operation and maintenance architecture for utility tunnels.Additionally,it explores the data challenges,monitoring technologies,and management platform architectures faced during the operation and maintenance process.This work provides new research perspectives for the long-term,healthy,and sustainable development of utility tunnels,which serve as the underground arteries of cities.
基金supported by the National Natural Science Foundation of China(Grant No.U22A20596)the Shenzhen Science and Technology Program(Grant No.GJHZ20220913142605010)the Jinan Lead Researcher Project(Grant No.202333051).
文摘Landslides significantly threaten lives and infrastructure, especially in seismically active regions. This study conducts a probabilistic analysis of seismic landslide runout behavior, leveraging a large-deformation finite-element (LDFE) model that accounts for the three-dimensional (3D) spatial variability and cross-correlation in soil strength — a reflection of natural soils' inherent properties. LDFE model results are validated by comparing them against previous studies, followed by an examination of the effects of univariable, uncorrelated bivariable, and cross-correlated bivariable random fields on landslide runout behavior. The study's findings reveal that integrating variability in both friction angle and cohesion within uncorrelated bivariable random fields markedly influences runout distances when compared with univariable random fields. Moreover, the cross-correlation of soil cohesion and friction angle dramatically affects runout behavior, with positive correlations enlarging and negative correlations reducing runout distances. Transitioning from two-dimensional (2D) to 3D analyses, a more realistic representation of sliding surface, landslide velocity, runout distance and final deposit morphology is achieved. The study highlights that 2D random analyses substantially underestimate the mean value and overestimate the variability of runout distance, underscoring the importance of 3D modeling in accurately predicting landslide behavior. Overall, this work emphasizes the essential role of understanding 3D cross-correlation in soil strength for landslide hazard assessment and mitigation strategies.
基金the Higher Education Commission of Pakistan for supporting the study through the CRG-CPEC-130 project。
文摘Climate change and rising temperatures are accelerating the rate of deglaciation in the Hindu Kush Karakoram Himalaya(HKH)ranges,leading to the formation of new glacial lakes and the expansion of existing ones.These lakes are often vulnerable to failure,posing a significant threat to downstream communities and infrastructure.Therefore,a comprehensive assessment of Glacier-Lake Outburst Flood(GLOF)hazards and risk assessment is crucial to evaluate flood runout characteristics and identify settlements and infrastructure that are exposed and vulnerable to floods,aiding in the development and implementation of risk reduction strategies.This study aims to simulate a GLOF event induced by the Shisper glacier lake in northern Pakistan,using the HEC-RAS,and to assess its impact on settlements,infrastructure,and agricultural land.For the hydrometeorological analysis of the GLOF event,topographic data from unmanned aerial vehicles(UAVs),stream profiles,discharge data,Manning's roughness coefficient(n),and land use/land cover(LULC)were analyzed using HEC-RAS and geographic information system(GIS).During the GLOF event on May 7,2022,a maximum water depth of 6.3 m and a maximum velocity of 9.5 m/s were recorded.Based on the runout characteristics of this event,vulnerability and risk assessments have been calculated.The physical,social,and environmental vulnerabilities of the at-risk elements were evaluated using the analytical hierarchy process(AHP)and integrated with the hazard data to develop a risk map.The study identified the areas,infrastructure and settlements susceptible to GLOF hazard to support the development and implementation of targeted and evidence-based mitigation and adaptation strategies.
基金supported by the Key Research and Development Program of the Ministry of Science and Technology of China(grant number:2016YF0900605)the Key Research and Development Program of Hebei Province(grant number:192777129D)+1 种基金the Joint Fund for Iron and Steel of the Natural Science Foundation of Hebei Province(grant number:H2016209058)the National Natural Science Foundation for Regional Joint Fund of China(grant number:U22A20364)。
文摘Objective We aimed to investigate the patterns of fasting blood glucose(FBG)trajectories and analyze the relationship between various occupational hazard factors and FBG trajectories in male steelworkers.Methods The study cohort included 3,728 workers who met the selection criteria for the Tanggang Occupational Cohort(TGOC)between 2017 and 2022.A group-based trajectory model was used to identify the FBG trajectories.Environmental risk scores(ERS)were constructed using regression coefficients from the occupational hazard model as weights.Univariate and multivariate logistic regression analyses were performed to explore the effects of occupational hazard factors using the ERS on FBG trajectories.Results FBG trajectories were categorized into three groups.An association was observed between high temperature,noise exposure,and FBG trajectory(P<0.05).Using the first quartile group of ERS1 as a reference,the fourth quartile group of ERS1 had an increased risk of medium and high FBG by 1.90and 2.21 times,respectively(odds ratio[OR]=1.90,95%confidence interval[CI]:1.17–3.10;OR=2.21,95%CI:1.09–4.45).Conclusion An association was observed between occupational hazards based on ERS and FBG trajectories.The risk of FBG trajectory levels increase with an increase in ERS.
文摘With the rapid development of virtual reality(VR)and augmented reality(AR)technologies,their application potential in the field of education has become increasingly significant.For a long time,fire safety education in university laboratories has faced numerous challenges,and traditional teaching methods have been insufficiently effective,with high-risk scenarios difficult to realistically recreate.Especially in special scenarios involving hazardous chemicals,conventional training methods struggle to enable learners to achieve deep understanding and behavioral formation.This study systematically integrates immersive technology theory with safety education needs,providing a replicable technical solution for safety education in high-risk environments.Its modular design approach has reference value for expansion into other professional fields,offering practical evidence for innovation in safety education models in the digital age.
基金supported by the National Key Research and Development Program of China(No.2024YFC2815400)the European Commission(Nos.HORIZON MSCA-2024-PF-01 and 101200637)+2 种基金the Opening Fund of the State Key Laboratory of Water Resources Engineering and Management at Wuhan University(No.2024SGG07)the Shandong Provincial Natural Science Foundation(No.ZR2025MS647)the Sand Hazards and Opportunities for Resilience,Energy,and Sustainability(SHORES)Center,funded by Tamkeen under the NYUAD Research Institute Award CG013.
文摘Retrogressive landslides in sensitive clays pose significant risks to nearby infrastructure,as natural toe erosion or localized disturbances can trigger progressive block failures.While prior studies have largely relied on two-dimensional(2D)large-deformation analyses,such models overlook key three-dimensional(3D)failure mechanisms and variability effects.This study develops a 3D probabilistic framework by integrating the Coupled Eulerian–Lagrangian(CEL)method with random field theory to simulate retrogressive landslides in spatially variable clay.Using Monte Carlo simulations,we compare 2D and 3D random large-deformation models to evaluate failure modes,runout distances,sliding velocities,and influence zones.The 3D analyses captured more complex failure modes—such as lateral retrogression and asynchronous block mobilization across slope width.Additionally,the 3D analyses predict longer mean runout distances(13.76 vs.11.92 m),wider mean influence distance(11.35 vs.8.73 m),and higher mean sliding velocities(4.66 vs.3.94 m/s)than their 2D counterparts.Moreover,3D models exhibit lower coefficients of variation(e.g.,0.10 for runout distance)due to spatial averaging across slope width.Probabilistic hazard assessment shows that 2D models significantly underpredict near-field failure probabilities(e.g.,48.8%vs.89.9%at 12 m from the slope toe).These findings highlight the limitations of 2D analyses and the importance of multi-directional spatial variability for robust geohazard assessments.The proposed 3D framework enables more realistic prediction of landslide mobility and supports the design of safer,risk-informed infrastructure.
基金supported by the National Natural Science Foundation of China(Nos.U2244227,U2244226,42177172)the National Key R&D Program of China(No.2022YFC3004301)China Geological Survey Project(No.DD20230538)。
文摘Frequent glacier-related watershed geohazard chains are causing severe damage to life and infrastructure,reported consistently from the Eastern Himalayan Syntaxis.This paper presents a systematic method for researching geohazard,from regional to individual scale.The methodology includes the establishment of geological chain inventories,discrimination of geohazard chain modes,analyses of dynamics and dam breaches,and risk assessments.The following results were obtained:(1)In the downstream of Yarlung Zangbo River,175 sites were identified as high-risk for river blockage disasters,indicating the development of watershed geohazards.Five geohazard chain modes were summarized by incorporating geomorphological characteristics,historical events,landslide zoning,and materials.The risk areas of typical hazard were identified and assessed using InSAR data.(2)Glacier-related watershed geohazard chains are significantly different from traditional landslides.A detailed inversion analysis was conducted on the massive rock-ice avalanche in the Sedongpu gully in 2021.This particular event lasted roughly 300 seconds,with a maximum flow velocity of 77.2 m/s and a maximum flow height of 93 meters.By scrutinizing the dynamic processes and mechanical characteristics,mobility stages and phase transitions can be divided into four stages.(3)Watershed geohazard chains tend to block rivers.The peak breach discharge of the Yigong Landslide reached 12.4×10^(4) m^(3)/s,which is 36 times the volume of the seasonal flood discharge in the Yigong River.Megafloods caused by landslide dam breaches have significantly shaped the geomorphology.This study offers insights into disaster patterns and the multistaged movement characteristics of glacier-related watershed geohazard chains,providing a comprehensive method for investigations and assessments in glacial regions.
基金financially supported by the National Natural Science Foundation of China(No.52125201)Beijing Natural Science Foundation(No.Z240025)and the Beijing Municipal Science and Technology(No.Z221100002722015).
文摘Flexible and wearable electronics are attracting surging attention due to their potential applications in human health monitoring and precision therapies.Safety hazards including strong magnetic field and electric leakage are big risk factors for human health.It remains challenging to develop self‐powered and wearable safety hazard sensors that could not only be able to monitor human motions but also have functions for detecting potential hazards.In this work,we fabricated a self‐powered,shapeable,and wearable magnetic triboelectric nanogenerator(MTENG)based on ferrofluid,Ecoflex,and carbonized silk fabric that possessed effective hazard prevention and biomechanical motion sensing ability.A peak open‐circuit voltage of 0.7 V and short‐circuit current of 10μA m^(−2)can be achieved when magnetic field is changed between 3.5 and 37.1 mT.As a component of triboelectric layer of the MTENG,ferrofluid can substantially extend the range of its sensing capabilities to many hazardous cues such as dangerous magnetic field.Furtherly,the developed multifunctional and self‐powered sensor can be used to monitor human activities such as drinking water and bending finger.This effort opens up a new design opportunity for hazard avoidance wearable electronics and self‐powered sensors.
基金support from the National Natural Science Foundation of China(U20A20112,42061160480,42377196,and 52479095)the NSFC/RGC Joint Research Scheme(42061160480 and N_HKUST620/20)+1 种基金the Research Grants Council of the Hong Kong SAR Government(16203720,T22-606/23-R,and JRFS25266S09)the Project of Hetao Shenzhen-Hong Kong Science and Technology Innovation Cooperation Zone(HZQB-KCZYB-2020083)。
文摘A glacier hazard chain can form a long-runout mass flow and generate a large flood,affecting downstream areas hundreds of kilometers away from the initiating hazard site.This study focuses on the Yarlung Zangbo Daxiagu.The objective is to address two key unresolved issues:the evolution of detached glacier materials into debris flows or debris floods and the amplification of the impact range and threats.A comprehensive framework is developed that considers the impacts of near-field and far-field hazards.Numerical modeling,remote sensing,and field investigations were integrated to understand the interactions,transformations,and amplifications of hazards in the glacier hazard chain.The results indicate that extensive,nearly saturated sediments on the glacier valley floor,when entrained,amplify the magnitude of the mass flow.The topography plays a crucial role.When the valley outlet is perpendicular to the river course,topographic obstacles cause immediate halting,resulting in the formation of high barrier dams.Conversely,when the glacier valley aligns nearly parallel to the river course,the mass flow can travel a much longer distance upon entering the river,causing an enlarged affected area.The barrier dams can breach rapidly,causing breaching floods that amplify the downstream impact from several kilometers to hundreds of kilometers.Our analysis reveals that the overall impacts remain spatially limited.Specifically,downstream areas along the Yarlung Zangbo-Brahmaputra River are unlikely to face greater threats from the upstream floods than local monsoon floods.Our findings provide the foundation for the management of glacier hazard chains.
