Glacier landslide cascading hazards pose threats to communities and infrastructure,affected by complex processes including the amplification of mass flow volume through erosion and entrainment,transformation of hazard...Glacier landslide cascading hazards pose threats to communities and infrastructure,affected by complex processes including the amplification of mass flow volume through erosion and entrainment,transformation of hazard types,ice-water phase change,and enhanced mobility of the mass flow.Scientifically simulating these physical phenomena proves challenging.This study introduces GMFA(glacier mass flow analysis),an integrated numerical model that advances the field by:(1)proposing depth-averaged fluctuation energy and internal energy equations,(2)incorporating the ice-water phase change and the entrainment-deposition process,and(3)capturing their effects on mass flow runout characteristics.The model employs the finite volume method to solve the multi-physics coupled governing equations,enabling efficient large-scale simulations.The model is verified through three numerical tests covering flow dynamics,temperature evolution,and thermo-hydro-mechanical runout processes.The model is applied to analyze a hazard chain that occurred on 10 September 2020 on the Tibetan Plateau.The multi-scenario simulation results indicate an entrained mass volume of(4.95±0.11)×10^(5)m^(3),and a ratio of entrained mass volume to source material volume of 0.44.The solid concentration decreases from 0.6-0.7 to 0.1-0.15 with increasing runout distance,indicating a transition from avalanche to debris flood.The internal energy rises by(3-4)×10^(3)kJ/m^(3),driving rapid ice melting from 0.1 to 0.2 to near-zero concentration.The model effectively quantifies volume amplification,ice-water phase changes,and multi-hazard transformations.This model pushes the geoscience frontier,extending computational capability from single-to multi-hazard simulations and providing a powerful tool for analyzing glacier cascading hazards.展开更多
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
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
The identification of rock mass hazard sources is fundamental for preventing rockfall and landslide disasters in mountainous regions,with rock mass structural characteristics playing a vital role in hazard assessment....The identification of rock mass hazard sources is fundamental for preventing rockfall and landslide disasters in mountainous regions,with rock mass structural characteristics playing a vital role in hazard assessment.In this study,terrestrial laser scanning(TLS)and unmanned aerial vehicle(UAV)technologies were integrated to enhance the evaluation methodology for rock mass hazard sources,focusing on the Sichuan Yanjiang Expressway project in China.The findings demonstrate that TLS-UAV technology enhanced both spatial coverage and data density in slope modeling.Through integrated algorithmic analysis,rock discontinuities within heterogeneous datasets were systematically identified,enabling quantitative extraction and statistical analysis of key geometric parameters,including orientation,trace length,spacing,and roughness.Furthermore,quantitative models were developed for cohesion,friction angle and the morphology parameter M of in situ discontinuities,respectively,facilitating efficient mechanical parameter acquisition.A novel rock mass hazard index(RHI)was developed incorporating discontinuity geometric rating(DGR),discontinuity mechanical rating(DMR),and slope mass rating(SMR).Field validation confirmed the methodology's effectiveness in evaluating risk levels and spatial heterogeneity of rock mass hazard sources,revealing the contribution of different discontinuity sets to the rock mass hazard and identifying the primary discontinuity sets controlling instability mechanisms.This study is of great significance for evaluating discontinuity-controlled rock mass hazard sources and preventing rockfall disasters.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
This study investigated the impacts of random negative training datasets(NTDs)on the uncertainty of machine learning models for geologic hazard susceptibility assessment of the Loess Plateau,northern Shaanxi Province,...This study investigated the impacts of random negative training datasets(NTDs)on the uncertainty of machine learning models for geologic hazard susceptibility assessment of the Loess Plateau,northern Shaanxi Province,China.Based on randomly generated 40 NTDs,the study developed models for the geologic hazard susceptibility assessment using the random forest algorithm and evaluated their performances using the area under the receiver operating characteristic curve(AUC).Specifically,the means and standard deviations of the AUC values from all models were then utilized to assess the overall spatial correlation between the conditioning factors and the susceptibility assessment,as well as the uncertainty introduced by the NTDs.A risk and return methodology was thus employed to quantify and mitigate the uncertainty,with log odds ratios used to characterize the susceptibility assessment levels.The risk and return values were calculated based on the standard deviations and means of the log odds ratios of various locations.After the mean log odds ratios were converted into probability values,the final susceptibility map was plotted,which accounts for the uncertainty induced by random NTDs.The results indicate that the AUC values of the models ranged from 0.810 to 0.963,with an average of 0.852 and a standard deviation of 0.035,indicating encouraging prediction effects and certain uncertainty.The risk and return analysis reveals that low-risk and high-return areas suggest lower standard deviations and higher means across multiple model-derived assessments.Overall,this study introduces a new framework for quantifying the uncertainty of multiple training and evaluation models,aimed at improving their robustness and reliability.Additionally,by identifying low-risk and high-return areas,resource allocation for geologic hazard prevention and control can be optimized,thus ensuring that limited resources are directed toward the most effective prevention and control measures.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
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
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
The southern region of Saudi Arabia exhibits a distinct seismic profile shaped by the Red Sea Rift and local fault systems, necessitating rigorous seismic hazard evaluations and tailored structural design strategies. ...The southern region of Saudi Arabia exhibits a distinct seismic profile shaped by the Red Sea Rift and local fault systems, necessitating rigorous seismic hazard evaluations and tailored structural design strategies. This study applies a robust Probabilistic Seismic Hazard Analysis (PSHA) framework to compute Maximum Considered Earthquake (MCE) and Risk-Targeted Maximum Considered Earthquake (MCER) values for major cities, including Jazan, Abha, and Najran. Utilizing local seismotectonic models, ground motion prediction equations (GMPEs), and soil classifications, the study generates precise ground motion parameters critical for infrastructure planning and safety. Results indicate significant seismic hazard variability, with Jazan showing high seismic risks with an MCER SA (0.2 s) of 0.45 g, compared to Najran’s lower risks at 0.23 g. Structural design guidelines, informed by MCE and MCER calculations, prioritize the integration of site-specific seismic data, enhanced ductility requirements, and advanced analytical methods to ensure resilient and sustainable infrastructure. The study underscores the necessity of localized seismic assessments and modern engineering practices to effectively mitigate seismic risks in this geologically complex region.展开更多
In order to evaluate the reliability of long-lifetime products with degradation data, a new proportional hazard degradation model is proposed. By the similarity between time-degradation data and stress-accelerated lif...In order to evaluate the reliability of long-lifetime products with degradation data, a new proportional hazard degradation model is proposed. By the similarity between time-degradation data and stress-accelerated lifetime, and the failure rate function of degradation data which is assumed to be proportional to the time covariate, the reliability assessment based on a proportional hazard degradation model is realized. The least squares method is used to estimate the model＇s parameters. Based on the failure rate of the degradation data and the proportion function of the known time, the failure rate and the reliability function under the given time and the predetermined failure threshold can be extrapolated. A long life GaAs laser is selected as a case study and its reliability is evaluated. The results show that the proposed method can accurately describe the degradation process and it is effective for the reliability assessment of long lifetime products.展开更多
Snow avalanches present a significant threat to infrastructure,affecting buildings,roads,railways,and power lines,and frequently leading to massive economic losses in livelihoods and production.With the increase in re...Snow avalanches present a significant threat to infrastructure,affecting buildings,roads,railways,and power lines,and frequently leading to massive economic losses in livelihoods and production.With the increase in regional temperatures and the occurrence of extreme snowfall events,the frequency and intensity of avalanches have escalated,resulting in more severe incidents and higher casualty rates.As natural archives of environmental changes,tree rings offer valuable proxies for avalanche hazard assessments in regions where direct observation data is scarce,particularly in high-altitude regions.The dendrogeomorphology has been gradually being applied in avalanche hazard evaluation,however,it remains limited in China.To address this gap,this study systematically investigates the principles and methodologies for reconstructing avalanche histories and evaluates their applications in avalanche hazard assessments through a literature review and field observations.It provides a comprehensive overview of recent advancements in key areas,including the impact of avalanches on forest ecosystems,the reconstruction of avalanches,and the analysis of avalanche events(i.e.,the spatiotemporal distribution,the historical recurrence intervals,magnitudes,and triggering conditions of avalanches).Considering the current limitations in avalanche hazard assessments and the urgent need for such research in China,we outline key priorities and future directions,including refining reconstruction methodologies,developing a comprehensive tree-ring-based avalanche database for high-altitude regions,and establishing an advanced hazard assessment framework based on dendrochronological evidence.展开更多
This comprehensive review synthesizes findings from the studies conducted for more than two decades to assess en-vironmental and human health impacts near Spain's first hazardous waste incinerator(HWI)located in C...This comprehensive review synthesizes findings from the studies conducted for more than two decades to assess en-vironmental and human health impacts near Spain's first hazardous waste incinerator(HWI)located in Constantí(Tarra-gona,Catalonia).Through integrated analysis of polychlorinated dibenzo-p-dioxins/furans(PCDD/Fs)and metals across soil,vegetation,human tissues,and dietary matrices,the studies have shown:(1)PCDD/F concentrations decreased 75-96%in biological samples and dietary intake over 20 years,aligning with global emission reductions rather than HWI-4 operations;(2)metal trajectories showed arsenic intermittently exceeding carcinogenic thresholds in soils(1.1×10^(-4) risk index)and chromium accumulating in autopsy tissues(+16% in kidney),although without HWI-specific spatial gradi-ents;(3)systemic biomarkers revealed policy-driven declines—blood lead dropped 70% post-EU regulations,while mer-cury became undetectable in tissues post-2010.Health risk assessments confirmed that PCDD/F intake(0.122 pg WHO-TEQ/kg/day)remained still below WHO thresholds,with no attributable cancer risks for metals except legacy arsenic.The studies included in the program of surveillance show that PCDD/Fs and metals emissions by the HWI have meant a rather low contribution to population exposure to metals and PCDD/Fs compared to dietary and historical sources.How-ever,residual risks warrant attention.It mainly concerns chromium speciation and arsenic in soils,as well as the effects on vulnerable subpopulations and the synergistic effects among toxicants.Epidemiological studies are also required.展开更多
The classification of dams or off-stream reservoirs concerning potential hazards in the event of failure often involves the use of two-dimensional hydraulic models for computing floodwave effects.These models necessit...The classification of dams or off-stream reservoirs concerning potential hazards in the event of failure often involves the use of two-dimensional hydraulic models for computing floodwave effects.These models necessitate defining breach geometry and formation time,for which various parametric models have been proposed.These models yield different values for average breach width,time of failure,and consequently,peak flows,as demonstrated by several researchers.This study analyzed the effect of selecting a breach parametric model on the hydraulic variables,potential damages,and hazard classification of structures.Three common parametric models were compared using a set of synthetic cases and a real off-stream reservoir.Results indicated significant effects of model choice.Material erodibility exerted a significant impact,surpassing that of failure mode.Other factors,such as the Manning coefficient,significantly affected the results.Utilizing an inadequate model or lacking information on dike material can lead to overly conservative or underestimated outcomes,thereby affecting hazard classification.展开更多
This paper presents a standardised workflow for conducting hazard assessments of mass wasting processes in remote mountain areas with limited data.The methodology integrates geomorphological mapping and remote sensing...This paper presents a standardised workflow for conducting hazard assessments of mass wasting processes in remote mountain areas with limited data.The methodology integrates geomorphological mapping and remote sensing techniques and is adaptable to different national standards,thus ensuring its applicability in a variety of contexts.The principal objective is to guarantee the safety of mountainous regions,particularly in the vicinity of essential infrastructure,where the scope for implementing structural measures is restricted.The framework commences with comprehensive geomorphological mapping,which facilitates the identification of past hazardous processes and potential future hazards.New technologies,such as uncrewed aerial vehicles(UAVs),are employed to create high-resolution DEMs,which are particularly beneficial in regions with limited data availability.These models facilitate the assessment of potential hazards and inform decisions regarding protective measures.The utilisation of UAVs enhances the accuracy and efficiency of data collection,particularly in remote mountainous regions where alternative remotely sensed information may be unavailable.The integration of modern approaches into traditional hazard assessment methods allows for a comprehensive analysis of the spatial distribution of factors driving mass wasting processes.This workflow provides valuable insights that assist in the prioritisation of interventions and the optimisation of risk reduction in high mountainous areas.展开更多
Source term estimation(STE)of hazardous gas leakages in chemical industrial parks(CIPs)is important for addressing environmental pollution and improving safety and reliability in engineering practice.To achieve real-t...Source term estimation(STE)of hazardous gas leakages in chemical industrial parks(CIPs)is important for addressing environmental pollution and improving safety and reliability in engineering practice.To achieve real-time STE,least squares-based STE methods have recently been developed.However,these methods require the number and locations of potential hazardous gas leakage sources are known as a priori,which is difficult in many practical scenarios.To address this limitation,we propose a new datadriven STE approach,which enables the STE to be implemented in real time and applicable to complicated turbulent dispersion scenarios.The linear independent analysis in data science is applied to historically collected concentration data of a hazardous gas of concern from a network of sensors to extract the sensor data which represent independent hazardous gas leakage scenarios(IHGLSs).An appropriate Gaussian model approximation to a high-fidelity computational fluid dynamics(CFD)model that must be used to represent the hazardous gas leakage scenarios of concern is built,and the off-line STE of IHGLSs using the approximating Gaussian model is then performed to build the datadriven STE model.The performance of the proposed approach is evaluated by using data that are generated by simulating ethane leakage scenarios in a CIP using a CFD model.Results indicate that the leakage localization accuracy is 100%and the mean relative estimation error for the leakage strength is6.76%.Moreover,the proposed approach is validated with real data in Prairie Grass field dispersion experiments,demonstrating the practical applicability of the proposed approach.展开更多
The fragile and intricate geological environment of the Qinghai-Tibet Plateau gives rise to numerous precarious rocks along the riverbanks,posing significant risks for the upcoming construction of hydropower stations....The fragile and intricate geological environment of the Qinghai-Tibet Plateau gives rise to numerous precarious rocks along the riverbanks,posing significant risks for the upcoming construction of hydropower stations.In order to identify potential rockfalls that could endanger the Zixia hydropower project,a comprehensive analysis employing various methods was conducted to investigate the kinematic characteristics and dynamic fragmentation of such precarious rocks.Initially,UAV oblique photography and field survey were used to create a digital elevation model with a resolution of 0.25 m and map the spatial distribution of precarious rocks.Subsequently,the development characteristics of joints within rock masses were analyzed through an adit investigation.Following these preliminary steps,a transportation simulation utilizing RocPro3D,considering stochastic initiation orientation,was employed to predict the trajectories of 18 precarious rocks.As a result,two hazardous rocks that pose a direct threat to the cofferdam were identified.Finally,considering the influence of internal structure planes,a discrete element method was applied for accurately simulating the kinematic characteristics and dynamic fragmentation of these hazardous rocks.The findings underscore several key observations:(1)Slopeparallel structure planes within these hazardous rocks play a pivotal role in both the progressive failure during initiation and dynamic fragmentation during transportation;(2)Hazardous rocksⅢ-1 andⅣ-1 would pose a direct threat to the cofferdam.Notably,block b4 from hazardous rockⅢ-1,could potentially impact the cofferdam with an energy of 4598.65 kJ and an impact force of 3007.5 kN;and(3)Continuous collisions encountered during transportation facilitate the disintegration of rock masses along structure planes and generate substantial high-velocity fragments.Finally,to cope with the impact risk of collapsing blocks,a reinforced retaining wall as the mitigation measure is recommended.展开更多
基金supports from the National Natural Science Foundation of China(Grant No.U20A20112)the Research Grants Council of the Hong Kong SAR Government,China(Grant Nos.T22-606/23-R and 16206923).
文摘Glacier landslide cascading hazards pose threats to communities and infrastructure,affected by complex processes including the amplification of mass flow volume through erosion and entrainment,transformation of hazard types,ice-water phase change,and enhanced mobility of the mass flow.Scientifically simulating these physical phenomena proves challenging.This study introduces GMFA(glacier mass flow analysis),an integrated numerical model that advances the field by:(1)proposing depth-averaged fluctuation energy and internal energy equations,(2)incorporating the ice-water phase change and the entrainment-deposition process,and(3)capturing their effects on mass flow runout characteristics.The model employs the finite volume method to solve the multi-physics coupled governing equations,enabling efficient large-scale simulations.The model is verified through three numerical tests covering flow dynamics,temperature evolution,and thermo-hydro-mechanical runout processes.The model is applied to analyze a hazard chain that occurred on 10 September 2020 on the Tibetan Plateau.The multi-scenario simulation results indicate an entrained mass volume of(4.95±0.11)×10^(5)m^(3),and a ratio of entrained mass volume to source material volume of 0.44.The solid concentration decreases from 0.6-0.7 to 0.1-0.15 with increasing runout distance,indicating a transition from avalanche to debris flood.The internal energy rises by(3-4)×10^(3)kJ/m^(3),driving rapid ice melting from 0.1 to 0.2 to near-zero concentration.The model effectively quantifies volume amplification,ice-water phase changes,and multi-hazard transformations.This model pushes the geoscience frontier,extending computational capability from single-to multi-hazard simulations and providing a powerful tool for analyzing glacier cascading hazards.
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support from the National Natural Science Foundation of China(Grant Nos.42177142 and 52378477)the Key Research and Development Program of Shaanxi(Grant No.2023-YBSF-486).
文摘The identification of rock mass hazard sources is fundamental for preventing rockfall and landslide disasters in mountainous regions,with rock mass structural characteristics playing a vital role in hazard assessment.In this study,terrestrial laser scanning(TLS)and unmanned aerial vehicle(UAV)technologies were integrated to enhance the evaluation methodology for rock mass hazard sources,focusing on the Sichuan Yanjiang Expressway project in China.The findings demonstrate that TLS-UAV technology enhanced both spatial coverage and data density in slope modeling.Through integrated algorithmic analysis,rock discontinuities within heterogeneous datasets were systematically identified,enabling quantitative extraction and statistical analysis of key geometric parameters,including orientation,trace length,spacing,and roughness.Furthermore,quantitative models were developed for cohesion,friction angle and the morphology parameter M of in situ discontinuities,respectively,facilitating efficient mechanical parameter acquisition.A novel rock mass hazard index(RHI)was developed incorporating discontinuity geometric rating(DGR),discontinuity mechanical rating(DMR),and slope mass rating(SMR).Field validation confirmed the methodology's effectiveness in evaluating risk levels and spatial heterogeneity of rock mass hazard sources,revealing the contribution of different discontinuity sets to the rock mass hazard and identifying the primary discontinuity sets controlling instability mechanisms.This study is of great significance for evaluating discontinuity-controlled rock mass hazard sources and preventing rockfall disasters.
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 investigated the impacts of random negative training datasets(NTDs)on the uncertainty of machine learning models for geologic hazard susceptibility assessment of the Loess Plateau,northern Shaanxi Province,China.Based on randomly generated 40 NTDs,the study developed models for the geologic hazard susceptibility assessment using the random forest algorithm and evaluated their performances using the area under the receiver operating characteristic curve(AUC).Specifically,the means and standard deviations of the AUC values from all models were then utilized to assess the overall spatial correlation between the conditioning factors and the susceptibility assessment,as well as the uncertainty introduced by the NTDs.A risk and return methodology was thus employed to quantify and mitigate the uncertainty,with log odds ratios used to characterize the susceptibility assessment levels.The risk and return values were calculated based on the standard deviations and means of the log odds ratios of various locations.After the mean log odds ratios were converted into probability values,the final susceptibility map was plotted,which accounts for the uncertainty induced by random NTDs.The results indicate that the AUC values of the models ranged from 0.810 to 0.963,with an average of 0.852 and a standard deviation of 0.035,indicating encouraging prediction effects and certain uncertainty.The risk and return analysis reveals that low-risk and high-return areas suggest lower standard deviations and higher means across multiple model-derived assessments.Overall,this study introduces a new framework for quantifying the uncertainty of multiple training and evaluation models,aimed at improving their robustness and reliability.Additionally,by identifying low-risk and high-return areas,resource allocation for geologic hazard prevention and control can be optimized,thus ensuring that limited resources are directed toward the most effective prevention and control measures.
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.
文摘The southern region of Saudi Arabia exhibits a distinct seismic profile shaped by the Red Sea Rift and local fault systems, necessitating rigorous seismic hazard evaluations and tailored structural design strategies. This study applies a robust Probabilistic Seismic Hazard Analysis (PSHA) framework to compute Maximum Considered Earthquake (MCE) and Risk-Targeted Maximum Considered Earthquake (MCER) values for major cities, including Jazan, Abha, and Najran. Utilizing local seismotectonic models, ground motion prediction equations (GMPEs), and soil classifications, the study generates precise ground motion parameters critical for infrastructure planning and safety. Results indicate significant seismic hazard variability, with Jazan showing high seismic risks with an MCER SA (0.2 s) of 0.45 g, compared to Najran’s lower risks at 0.23 g. Structural design guidelines, informed by MCE and MCER calculations, prioritize the integration of site-specific seismic data, enhanced ductility requirements, and advanced analytical methods to ensure resilient and sustainable infrastructure. The study underscores the necessity of localized seismic assessments and modern engineering practices to effectively mitigate seismic risks in this geologically complex region.
基金The National Natural Science Foundation of China (No.50405021)
文摘In order to evaluate the reliability of long-lifetime products with degradation data, a new proportional hazard degradation model is proposed. By the similarity between time-degradation data and stress-accelerated lifetime, and the failure rate function of degradation data which is assumed to be proportional to the time covariate, the reliability assessment based on a proportional hazard degradation model is realized. The least squares method is used to estimate the model＇s parameters. Based on the failure rate of the degradation data and the proportion function of the known time, the failure rate and the reliability function under the given time and the predetermined failure threshold can be extrapolated. A long life GaAs laser is selected as a case study and its reliability is evaluated. The results show that the proposed method can accurately describe the degradation process and it is effective for the reliability assessment of long lifetime products.
基金supported by National Natural Science Foundation of China(NO.42371085)the Tibet Science and Technology Program(XZ202201ZY0011G)the Second Tibetan Plateau Scientific Expedition and Research Program(2019QZKK0906).
文摘Snow avalanches present a significant threat to infrastructure,affecting buildings,roads,railways,and power lines,and frequently leading to massive economic losses in livelihoods and production.With the increase in regional temperatures and the occurrence of extreme snowfall events,the frequency and intensity of avalanches have escalated,resulting in more severe incidents and higher casualty rates.As natural archives of environmental changes,tree rings offer valuable proxies for avalanche hazard assessments in regions where direct observation data is scarce,particularly in high-altitude regions.The dendrogeomorphology has been gradually being applied in avalanche hazard evaluation,however,it remains limited in China.To address this gap,this study systematically investigates the principles and methodologies for reconstructing avalanche histories and evaluates their applications in avalanche hazard assessments through a literature review and field observations.It provides a comprehensive overview of recent advancements in key areas,including the impact of avalanches on forest ecosystems,the reconstruction of avalanches,and the analysis of avalanche events(i.e.,the spatiotemporal distribution,the historical recurrence intervals,magnitudes,and triggering conditions of avalanches).Considering the current limitations in avalanche hazard assessments and the urgent need for such research in China,we outline key priorities and future directions,including refining reconstruction methodologies,developing a comprehensive tree-ring-based avalanche database for high-altitude regions,and establishing an advanced hazard assessment framework based on dendrochronological evidence.
文摘This comprehensive review synthesizes findings from the studies conducted for more than two decades to assess en-vironmental and human health impacts near Spain's first hazardous waste incinerator(HWI)located in Constantí(Tarra-gona,Catalonia).Through integrated analysis of polychlorinated dibenzo-p-dioxins/furans(PCDD/Fs)and metals across soil,vegetation,human tissues,and dietary matrices,the studies have shown:(1)PCDD/F concentrations decreased 75-96%in biological samples and dietary intake over 20 years,aligning with global emission reductions rather than HWI-4 operations;(2)metal trajectories showed arsenic intermittently exceeding carcinogenic thresholds in soils(1.1×10^(-4) risk index)and chromium accumulating in autopsy tissues(+16% in kidney),although without HWI-specific spatial gradi-ents;(3)systemic biomarkers revealed policy-driven declines—blood lead dropped 70% post-EU regulations,while mer-cury became undetectable in tissues post-2010.Health risk assessments confirmed that PCDD/F intake(0.122 pg WHO-TEQ/kg/day)remained still below WHO thresholds,with no attributable cancer risks for metals except legacy arsenic.The studies included in the program of surveillance show that PCDD/Fs and metals emissions by the HWI have meant a rather low contribution to population exposure to metals and PCDD/Fs compared to dietary and historical sources.How-ever,residual risks warrant attention.It mainly concerns chromium speciation and arsenic in soils,as well as the effects on vulnerable subpopulations and the synergistic effects among toxicants.Epidemiological studies are also required.
基金supported by the Spanish Ministry of Science,Innovation and Universities through the projects ACROPOLIS(Grant No.RTC2019-007343-5)and DOLMEN(Grant No.PID2021-122661OB-I00)the Spanish Ministry of Economy and Competitiveness through the project“Severo Ochoa Programme for Centres of Excellence in R&D”(Grant No.CEX2018-000797-S).
文摘The classification of dams or off-stream reservoirs concerning potential hazards in the event of failure often involves the use of two-dimensional hydraulic models for computing floodwave effects.These models necessitate defining breach geometry and formation time,for which various parametric models have been proposed.These models yield different values for average breach width,time of failure,and consequently,peak flows,as demonstrated by several researchers.This study analyzed the effect of selecting a breach parametric model on the hydraulic variables,potential damages,and hazard classification of structures.Three common parametric models were compared using a set of synthetic cases and a real off-stream reservoir.Results indicated significant effects of model choice.Material erodibility exerted a significant impact,surpassing that of failure mode.Other factors,such as the Manning coefficient,significantly affected the results.Utilizing an inadequate model or lacking information on dike material can lead to overly conservative or underestimated outcomes,thereby affecting hazard classification.
基金Open access funding provided by University of Natural Resources and Life Sciences Vienna(BOKU).
文摘This paper presents a standardised workflow for conducting hazard assessments of mass wasting processes in remote mountain areas with limited data.The methodology integrates geomorphological mapping and remote sensing techniques and is adaptable to different national standards,thus ensuring its applicability in a variety of contexts.The principal objective is to guarantee the safety of mountainous regions,particularly in the vicinity of essential infrastructure,where the scope for implementing structural measures is restricted.The framework commences with comprehensive geomorphological mapping,which facilitates the identification of past hazardous processes and potential future hazards.New technologies,such as uncrewed aerial vehicles(UAVs),are employed to create high-resolution DEMs,which are particularly beneficial in regions with limited data availability.These models facilitate the assessment of potential hazards and inform decisions regarding protective measures.The utilisation of UAVs enhances the accuracy and efficiency of data collection,particularly in remote mountainous regions where alternative remotely sensed information may be unavailable.The integration of modern approaches into traditional hazard assessment methods allows for a comprehensive analysis of the spatial distribution of factors driving mass wasting processes.This workflow provides valuable insights that assist in the prioritisation of interventions and the optimisation of risk reduction in high mountainous areas.
基金supported by the National Natural Science Foundation of China(Basic Science Center Program 61988101,62303186,62203173)。
文摘Source term estimation(STE)of hazardous gas leakages in chemical industrial parks(CIPs)is important for addressing environmental pollution and improving safety and reliability in engineering practice.To achieve real-time STE,least squares-based STE methods have recently been developed.However,these methods require the number and locations of potential hazardous gas leakage sources are known as a priori,which is difficult in many practical scenarios.To address this limitation,we propose a new datadriven STE approach,which enables the STE to be implemented in real time and applicable to complicated turbulent dispersion scenarios.The linear independent analysis in data science is applied to historically collected concentration data of a hazardous gas of concern from a network of sensors to extract the sensor data which represent independent hazardous gas leakage scenarios(IHGLSs).An appropriate Gaussian model approximation to a high-fidelity computational fluid dynamics(CFD)model that must be used to represent the hazardous gas leakage scenarios of concern is built,and the off-line STE of IHGLSs using the approximating Gaussian model is then performed to build the datadriven STE model.The performance of the proposed approach is evaluated by using data that are generated by simulating ethane leakage scenarios in a CIP using a CFD model.Results indicate that the leakage localization accuracy is 100%and the mean relative estimation error for the leakage strength is6.76%.Moreover,the proposed approach is validated with real data in Prairie Grass field dispersion experiments,demonstrating the practical applicability of the proposed approach.
基金gratefully acknowledge support from the National Key Research and Development Program of China(Grant No.2022YFC3005704)the National Natural Science Foundation of China(Grant No.42277143)the Sichuan Province natural Science Foundation project(Grant No.2024NSFSC0100).
文摘The fragile and intricate geological environment of the Qinghai-Tibet Plateau gives rise to numerous precarious rocks along the riverbanks,posing significant risks for the upcoming construction of hydropower stations.In order to identify potential rockfalls that could endanger the Zixia hydropower project,a comprehensive analysis employing various methods was conducted to investigate the kinematic characteristics and dynamic fragmentation of such precarious rocks.Initially,UAV oblique photography and field survey were used to create a digital elevation model with a resolution of 0.25 m and map the spatial distribution of precarious rocks.Subsequently,the development characteristics of joints within rock masses were analyzed through an adit investigation.Following these preliminary steps,a transportation simulation utilizing RocPro3D,considering stochastic initiation orientation,was employed to predict the trajectories of 18 precarious rocks.As a result,two hazardous rocks that pose a direct threat to the cofferdam were identified.Finally,considering the influence of internal structure planes,a discrete element method was applied for accurately simulating the kinematic characteristics and dynamic fragmentation of these hazardous rocks.The findings underscore several key observations:(1)Slopeparallel structure planes within these hazardous rocks play a pivotal role in both the progressive failure during initiation and dynamic fragmentation during transportation;(2)Hazardous rocksⅢ-1 andⅣ-1 would pose a direct threat to the cofferdam.Notably,block b4 from hazardous rockⅢ-1,could potentially impact the cofferdam with an energy of 4598.65 kJ and an impact force of 3007.5 kN;and(3)Continuous collisions encountered during transportation facilitate the disintegration of rock masses along structure planes and generate substantial high-velocity fragments.Finally,to cope with the impact risk of collapsing blocks,a reinforced retaining wall as the mitigation measure is recommended.
