Magnesium(Mg)and its alloys,known for their low density and high specific strength,are increasingly explored as lightweight structural materials across a broad range of industrial applications.However,their widespread...Magnesium(Mg)and its alloys,known for their low density and high specific strength,are increasingly explored as lightweight structural materials across a broad range of industrial applications.However,their widespread application remains constrained by intrinsic mechanical limitations,fundamentally rooted in the nature of crystallographic defects.Atomic-scale modeling techniques are transforming our ability to unravel the structures,energetics,and dynamics of these defects and to explore their complex interactions,thereby guiding defect engineering in Mg alloys.However,the growing body of available data can make it difficult for researchers to identify critical knowledge gaps and promising areas for further exploration.To address this challenge,we highlight key research domains with significant potential for impactful advancements,aiming to illuminate these areas while inspiring innovative approaches and encouraging deeper exploration of pivotal topics that may shape the future of Mg alloy development.This review presents a comprehensive overview of the state-of-the-art in atomic-scale modeling of defects in Mg and its alloys.We introduce key simulation methodologies,including density functional theory and atomistic simulations,and highlight their applications to defect distribution,defect dynamics,and defect-defect interactions.By bridging fundamental insights in defects with alloy design strategies,this review aims to support and inspire the broader Mg research community and to underscore the growing impact of atomic-scale modeling in the accelerated development of high-performance Mg alloys.展开更多
Bone fractures represent a significant global healthcare burden.Although fractures typically heal on their own,some fail to regenerate properly,leading to nonunion,a condition that causes prolonged disability,morbidit...Bone fractures represent a significant global healthcare burden.Although fractures typically heal on their own,some fail to regenerate properly,leading to nonunion,a condition that causes prolonged disability,morbidity,and mortality.The challenge of treating nonunion fractures is further complicated in patients with underlying bone disorders where systemic and local factors impair bone healing.Traditional treatment approaches,including autografts,allografts,xenografts,and synthetic biomaterials,face limitations such as donor site pain,immune rejection,and insufficient mechanical strength,underscoring the need for alternative strategies.Biologic therapies have emerged as promising tools to enhance bone regeneration by leveraging the body’s natural healing processes.This review explores the critical role of conventional and emerging biologics in fracture healing.We categorize biologic therapies into protein-based treatments,gene and transcript therapies,small molecules,peptides,and cell-based therapies,highlighting their mechanisms of action,advantages,and clinical relevance.Finally,we examine the potential applications of biologics in treating fractures associated with bone disorders such as osteoporosis,osteogenesis imperfecta,rickets,osteomalacia,Paget’s disease,and bone tumors.By integrating biologic therapies with existing biomaterial-based strategies,these innovative approaches have the potential to transform clinical management and improve outcomes for patients with difficult-to-heal fractures.展开更多
Mine surveying is an indispensable and crucial basic technical work in the process of mineral resource development.It plays an important role throughout the entire life cycle of a mine,from exploration,design,construc...Mine surveying is an indispensable and crucial basic technical work in the process of mineral resource development.It plays an important role throughout the entire life cycle of a mine,from exploration,design,construction,and production to closure,and is known as the“eyes of the mine”.With the rapid development of satellite technology,computer science,artificial intelligence,robotics,and spatiotemporal big data,mine surveying science and technology supported by spatial information technology is increasingly playing the role of the“brain of the mine”.This paper systematically summarizes the characteristics of mining surveying science and technology in contemporary and future mining development.First,based on the requirements of safe,efficient,and green development in modern mining,an analysis is conducted on the innovative practices of intelligent mining methods;secondly,it explains the transformation of regional economic and mining economic integration towards lengthening the industrial chain and scientific and technological innovation.Regarding intelligent mining,this paper discusses three technical dimensions:(1)By establishing a spatiotemporal data model of the mine,real-time perception and remote intelligent control of the production system are realized;(2)Based on the transparent mine three-dimensional geological modelling technology,the accuracy of geological condition prediction and the scientific nature of mining decisions are significantly improved;(3)By integrating multi-source remote sensing data and deep learning algorithms,a high-precision coal and rock identification system is constructed.The study further revealed the innovative application value of mine surveying in the post-mining era,including:diversified utilization of underground space in mining areas(tourism development,geothermal energy storage,pumped storage,etc.),multi-platform remote sensing coordinated ecological restoration monitoring,and optimized land space planning in mining areas.Practice has proved that mine surveying technology is an important technical engine for promoting green transformation and high-quality development in resource-based regions,and has irreplaceable strategic significance for achieving coordinated development of energy,economy,and environment.展开更多
Traumatic injuries to the central nervous system(CNS) result in disruption of the intricate network of axons which connect functionally related neurons that are widely distributed throughout the brain and spinal cord....Traumatic injuries to the central nervous system(CNS) result in disruption of the intricate network of axons which connect functionally related neurons that are widely distributed throughout the brain and spinal cord.Under normal conditions,maintenance of this complex system is structurally and functionally supported by astrocytes (ACs)and other glial cells,the processes of which form a framework surrounding neuronal cell bodies,dendrites,axons,and synapses.展开更多
Developing sensorless techniques for estimating battery expansion is essential for effective mechanical state monitoring,improving the accuracy of digital twin simulation and abnormality detection.Therefore,this paper...Developing sensorless techniques for estimating battery expansion is essential for effective mechanical state monitoring,improving the accuracy of digital twin simulation and abnormality detection.Therefore,this paper presents a data-driven approach to expansion estimation using electromechanical coupled models with machine learning.The proposed method integrates reduced-order impedance models with data-driven mechanical models,coupling the electrochemical and mechanical states through the state of charge(SOC)and mechanical pressure within a state estimation framework.The coupling relationship was established through experimental insights into pressure-related impedance parameters and the nonlinear mechanical behavior with SOC and pressure.The data-driven model was interpreted by introducing a novel swelling coefficient defined by component stiffnesses to capture the nonlinear mechanical behavior across various mechanical constraints.Sensitivity analysis of the impedance model shows that updating model parameters with pressure can reduce the mean absolute error of simulated voltage by 20 mV and SOC estimation error by 2%.The results demonstrate the model's estimation capabilities,achieving a root mean square error of less than 1 kPa when the maximum expansion force is from 30 kPa to 120 kPa,outperforming calibrated stiffness models and other machine learning techniques.The model's robustness and generalizability are further supported by its effective handling of SOC estimation and pressure measurement errors.This work highlights the importance of the proposed framework in enhancing state estimation and fault diagnosis for lithium-ion batteries.展开更多
Phosphorus(P)poses a global challenge to the environment and human health due to its natural association with heavy metals.Sustainable use of P is crucial to ensure food security for future generations.An analysis of ...Phosphorus(P)poses a global challenge to the environment and human health due to its natural association with heavy metals.Sustainable use of P is crucial to ensure food security for future generations.An analysis of the 150 phosphate fertilizers stored at the Institute for Crop and Soil Science in Germany has been conducted,supplemented by previously published data.The elements Cd,Bi,U,Cr,Zn,Tl,As,B,Sb,Ni,and Se are found in higher concentrations in sedimentary derived phosphates compared to igneous derived phosphates.Mineral fertilizers contain more than ten times the amount of U,Cd,B,and As compared to farmyard manure.Principal component analyses(PCA)indicate that U,Cd,Be,and Cr are primarily present in sedimentary derived phosphates and their concentrations are 2 to 10 times higher than those in igneous derived phosphates.Regarding heavy metal contamination,over 1000 potential combinations were identified;36% of these were significant but weak(>0.1).It is estimated that approximately 707 t of uranium enter farmland annually through the application of mineral phosphate fertilizers in European countries.This contribution addresses environmental issues related to the utilization of rock phosphate as well as alternative production methods for cleaner and safer phosphate fertilizers while presenting a roadmap with measures for mitigation.展开更多
BACKGROUND Proton pump inhibitors(PPIs)are widely used,including among cancer patients,to manage gastroesophageal reflux and other gastric acid-related disorders.Recent evidence suggests associations between long-term...BACKGROUND Proton pump inhibitors(PPIs)are widely used,including among cancer patients,to manage gastroesophageal reflux and other gastric acid-related disorders.Recent evidence suggests associations between long-term PPI use and higher risks for various adverse health outcomes,including greater mortality.AIM To investigate the association between PPI use and all-cause mortality among cancer patients by a comprehensive analysis after adjustment for various confounders and a robust methodological approach to minimize bias.METHODS This retrospective cohort study used data from the TriNetX research network,with electronic health records from multiple healthcare organizations.The study employed a new-user,active comparator design,which compared newly treated PPI users with non-users and newly treated histamine2 receptor antagonists(H2RA)users among adult cancer patients.Newly prescribed PPIs(esomeprazole,lansoprazole,omeprazole,pantoprazole,or rabeprazole)users were compared to non-users or newly prescribed H2RAs(cimetidine,famotidine,nizatidine,or ranitidine)users.The primary outcome was all-cause mortality.Each patient in the main group was matched to a patient in the control group using 1:1 propensity score matching to reduce confounding effects.Multivariable Cox regression models were used to estimate hazard ratios(HRs)and 95% confidence interval(CI).RESULTS During the follow-up period(median 5.4±1.8 years for PPI users and 6.5±1.0 years for non-users),PPI users demonstrated a higher all-cause mortality rate than non-users after 1 year,2 years,and at the end of follow up(HRs:2.34-2.72).Compared with H2RA users,PPI users demonstrated a higher rate of all-cause mortality HR:1.51(95%CI:1.41-1.69).Similar results were observed across sensitivity analyses by excluding deaths from the first 9 months and 1-year post-exposure,confirming the robustness of these findings.In a sensitivity analysis,we analyzed all-cause mortality outcomes between former PPI users and individuals who have never used PPIs,providing insights into the long-term effects of past PPI use.In addition,at 1-year follow-up,the analysis revealed a significant difference in mortality rates between former PPI users and non-users(HR:1.84;95%CI:1.82-1.96).CONCLUSION PPI use among cancer patients was associated with a higher risk of all-cause mortality compared to non-users or H2RA users.These findings emphasize the need for cautious use of PPIs in cancer patients and suggest that alternative treatments should be considered when clinically feasible.However,further studies are needed to corroborate our findings,given the significant adverse outcomes in cancer patients.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
Coupled thermo-hydro-mechanical(THM)processes in fractured rock are playing a crucial role in geoscience and geoengineering applications.Diverse and conceptually distinct approaches have emerged over the past decades ...Coupled thermo-hydro-mechanical(THM)processes in fractured rock are playing a crucial role in geoscience and geoengineering applications.Diverse and conceptually distinct approaches have emerged over the past decades in both continuum and discontinuum perspectives leading to significant progress in their comprehending and modeling.This review paper offers an integrated perspective on existing modeling methodologies providing guidance for model selection based on the initial and boundary conditions.By comparing various models,one can better assess the uncertainties in predictions,particularly those related to the conceptual models.The review explores how these methodologies have significantlyenhanced the fundamental understanding of how fractures respond to fluid injection and production,and improved predictive capabilities pertaining to coupled processes within fractured systems.It emphasizes the importance of utilizing advanced computational technologies and thoroughly considering fundamental theories and principles established through past experimental evidence and practical experience.The selection and calibration of model parameters should be based on typical ranges and applied to the specificconditions of applications.The challenges arising from inherent heterogeneity and uncertainties,nonlinear THM coupled processes,scale dependence,and computational limitations in representing fieldscale fractures are discussed.Realizing potential advances on computational capacity calls for methodical conceptualization,mathematical modeling,selection of numerical solution strategies,implementation,and calibration to foster simulation outcomes that intricately reflectthe nuanced complexities of geological phenomena.Future research efforts should focus on innovative approaches to tackle the hurdles and advance the state-of-the-art in this critical fieldof study.展开更多
In this study,the wave motion in elastodynamics for unbounded media is modeled using an unsplit-field perfectly matched layer(PML)formulation that is solved by employing an isogeometric analysis(IGA).In the adopted co...In this study,the wave motion in elastodynamics for unbounded media is modeled using an unsplit-field perfectly matched layer(PML)formulation that is solved by employing an isogeometric analysis(IGA).In the adopted combination,the non-uniform rational B-spline(NURBS)functions are employed as basis functions.Moreover,the unbounded and artificial domains,defined in the PML method,are contained in a single patch domain.Based on the proposed scheme,the approximation of the geometry problem is set in a new scheme in which the PML’s absorbing and attenuation properties and the description of traveling waves can be represented.This includes a higher continuity and smoother approximation of the computed domain.As high-order NURBS basis functions are non-interpolatory,a penalty method is present to apply a time-dependent displacement load.The performance of the NURBS-based PML is analyzed through numerical examples for 1D and 2D domains,considering homogeneous and heterogeneous media.Further,we verify the long-time numerical stability of the present method.The developed method can be used to simulate hypothetical stratified domains commonly encountered in soil-structure interaction analyses.展开更多
基金support by the Deutsche Forschungsgemeinschaft(DFG)-Projektnummer 505716422the French National Research Agency(ANR)grants ANR22-CE92-0058-01(SILA)and ANR-21-CE08-0001(ATOUUM)+2 种基金support by the DFG through the projects A05 of the SFB1394 StructuralChemical Atomic Complexity-From Defect Phase Diagrams to Material Properties,project ID 409476157support funded by the DFG-Projektnummer 562592407 and 555365333.
文摘Magnesium(Mg)and its alloys,known for their low density and high specific strength,are increasingly explored as lightweight structural materials across a broad range of industrial applications.However,their widespread application remains constrained by intrinsic mechanical limitations,fundamentally rooted in the nature of crystallographic defects.Atomic-scale modeling techniques are transforming our ability to unravel the structures,energetics,and dynamics of these defects and to explore their complex interactions,thereby guiding defect engineering in Mg alloys.However,the growing body of available data can make it difficult for researchers to identify critical knowledge gaps and promising areas for further exploration.To address this challenge,we highlight key research domains with significant potential for impactful advancements,aiming to illuminate these areas while inspiring innovative approaches and encouraging deeper exploration of pivotal topics that may shape the future of Mg alloy development.This review presents a comprehensive overview of the state-of-the-art in atomic-scale modeling of defects in Mg and its alloys.We introduce key simulation methodologies,including density functional theory and atomistic simulations,and highlight their applications to defect distribution,defect dynamics,and defect-defect interactions.By bridging fundamental insights in defects with alloy design strategies,this review aims to support and inspire the broader Mg research community and to underscore the growing impact of atomic-scale modeling in the accelerated development of high-performance Mg alloys.
基金performed as part of the cmRNAbone project funded by the European Union’s Horizon 2020 research and innovation program under the Grant Agreement No 874790。
文摘Bone fractures represent a significant global healthcare burden.Although fractures typically heal on their own,some fail to regenerate properly,leading to nonunion,a condition that causes prolonged disability,morbidity,and mortality.The challenge of treating nonunion fractures is further complicated in patients with underlying bone disorders where systemic and local factors impair bone healing.Traditional treatment approaches,including autografts,allografts,xenografts,and synthetic biomaterials,face limitations such as donor site pain,immune rejection,and insufficient mechanical strength,underscoring the need for alternative strategies.Biologic therapies have emerged as promising tools to enhance bone regeneration by leveraging the body’s natural healing processes.This review explores the critical role of conventional and emerging biologics in fracture healing.We categorize biologic therapies into protein-based treatments,gene and transcript therapies,small molecules,peptides,and cell-based therapies,highlighting their mechanisms of action,advantages,and clinical relevance.Finally,we examine the potential applications of biologics in treating fractures associated with bone disorders such as osteoporosis,osteogenesis imperfecta,rickets,osteomalacia,Paget’s disease,and bone tumors.By integrating biologic therapies with existing biomaterial-based strategies,these innovative approaches have the potential to transform clinical management and improve outcomes for patients with difficult-to-heal fractures.
基金supported by the National Natural Science Foundation of China(Nos.52394193 and U22A20569)the National Key R&D Program Projects(Nos.2023YFC3804200 and 2023YFC3804205).
文摘Mine surveying is an indispensable and crucial basic technical work in the process of mineral resource development.It plays an important role throughout the entire life cycle of a mine,from exploration,design,construction,and production to closure,and is known as the“eyes of the mine”.With the rapid development of satellite technology,computer science,artificial intelligence,robotics,and spatiotemporal big data,mine surveying science and technology supported by spatial information technology is increasingly playing the role of the“brain of the mine”.This paper systematically summarizes the characteristics of mining surveying science and technology in contemporary and future mining development.First,based on the requirements of safe,efficient,and green development in modern mining,an analysis is conducted on the innovative practices of intelligent mining methods;secondly,it explains the transformation of regional economic and mining economic integration towards lengthening the industrial chain and scientific and technological innovation.Regarding intelligent mining,this paper discusses three technical dimensions:(1)By establishing a spatiotemporal data model of the mine,real-time perception and remote intelligent control of the production system are realized;(2)Based on the transparent mine three-dimensional geological modelling technology,the accuracy of geological condition prediction and the scientific nature of mining decisions are significantly improved;(3)By integrating multi-source remote sensing data and deep learning algorithms,a high-precision coal and rock identification system is constructed.The study further revealed the innovative application value of mine surveying in the post-mining era,including:diversified utilization of underground space in mining areas(tourism development,geothermal energy storage,pumped storage,etc.),multi-platform remote sensing coordinated ecological restoration monitoring,and optimized land space planning in mining areas.Practice has proved that mine surveying technology is an important technical engine for promoting green transformation and high-quality development in resource-based regions,and has irreplaceable strategic significance for achieving coordinated development of energy,economy,and environment.
文摘Traumatic injuries to the central nervous system(CNS) result in disruption of the intricate network of axons which connect functionally related neurons that are widely distributed throughout the brain and spinal cord.Under normal conditions,maintenance of this complex system is structurally and functionally supported by astrocytes (ACs)and other glial cells,the processes of which form a framework surrounding neuronal cell bodies,dendrites,axons,and synapses.
基金Fund supported this work for Excellent Youth Scholars of China(Grant No.52222708)the National Natural Science Foundation of China(Grant No.51977007)+1 种基金Part of this work is supported by the research project“SPEED”(03XP0585)at RWTH Aachen Universityfunded by the German Federal Ministry of Education and Research(BMBF)。
文摘Developing sensorless techniques for estimating battery expansion is essential for effective mechanical state monitoring,improving the accuracy of digital twin simulation and abnormality detection.Therefore,this paper presents a data-driven approach to expansion estimation using electromechanical coupled models with machine learning.The proposed method integrates reduced-order impedance models with data-driven mechanical models,coupling the electrochemical and mechanical states through the state of charge(SOC)and mechanical pressure within a state estimation framework.The coupling relationship was established through experimental insights into pressure-related impedance parameters and the nonlinear mechanical behavior with SOC and pressure.The data-driven model was interpreted by introducing a novel swelling coefficient defined by component stiffnesses to capture the nonlinear mechanical behavior across various mechanical constraints.Sensitivity analysis of the impedance model shows that updating model parameters with pressure can reduce the mean absolute error of simulated voltage by 20 mV and SOC estimation error by 2%.The results demonstrate the model's estimation capabilities,achieving a root mean square error of less than 1 kPa when the maximum expansion force is from 30 kPa to 120 kPa,outperforming calibrated stiffness models and other machine learning techniques.The model's robustness and generalizability are further supported by its effective handling of SOC estimation and pressure measurement errors.This work highlights the importance of the proposed framework in enhancing state estimation and fault diagnosis for lithium-ion batteries.
基金funded by the Project of Yunnan Province’s Xingdian Talents Support Program(yfgrc202437)the Project of the International Cooperation Science Program of National Natural Science Foundation of China(42361144885).
文摘Phosphorus(P)poses a global challenge to the environment and human health due to its natural association with heavy metals.Sustainable use of P is crucial to ensure food security for future generations.An analysis of the 150 phosphate fertilizers stored at the Institute for Crop and Soil Science in Germany has been conducted,supplemented by previously published data.The elements Cd,Bi,U,Cr,Zn,Tl,As,B,Sb,Ni,and Se are found in higher concentrations in sedimentary derived phosphates compared to igneous derived phosphates.Mineral fertilizers contain more than ten times the amount of U,Cd,B,and As compared to farmyard manure.Principal component analyses(PCA)indicate that U,Cd,Be,and Cr are primarily present in sedimentary derived phosphates and their concentrations are 2 to 10 times higher than those in igneous derived phosphates.Regarding heavy metal contamination,over 1000 potential combinations were identified;36% of these were significant but weak(>0.1).It is estimated that approximately 707 t of uranium enter farmland annually through the application of mineral phosphate fertilizers in European countries.This contribution addresses environmental issues related to the utilization of rock phosphate as well as alternative production methods for cleaner and safer phosphate fertilizers while presenting a roadmap with measures for mitigation.
文摘BACKGROUND Proton pump inhibitors(PPIs)are widely used,including among cancer patients,to manage gastroesophageal reflux and other gastric acid-related disorders.Recent evidence suggests associations between long-term PPI use and higher risks for various adverse health outcomes,including greater mortality.AIM To investigate the association between PPI use and all-cause mortality among cancer patients by a comprehensive analysis after adjustment for various confounders and a robust methodological approach to minimize bias.METHODS This retrospective cohort study used data from the TriNetX research network,with electronic health records from multiple healthcare organizations.The study employed a new-user,active comparator design,which compared newly treated PPI users with non-users and newly treated histamine2 receptor antagonists(H2RA)users among adult cancer patients.Newly prescribed PPIs(esomeprazole,lansoprazole,omeprazole,pantoprazole,or rabeprazole)users were compared to non-users or newly prescribed H2RAs(cimetidine,famotidine,nizatidine,or ranitidine)users.The primary outcome was all-cause mortality.Each patient in the main group was matched to a patient in the control group using 1:1 propensity score matching to reduce confounding effects.Multivariable Cox regression models were used to estimate hazard ratios(HRs)and 95% confidence interval(CI).RESULTS During the follow-up period(median 5.4±1.8 years for PPI users and 6.5±1.0 years for non-users),PPI users demonstrated a higher all-cause mortality rate than non-users after 1 year,2 years,and at the end of follow up(HRs:2.34-2.72).Compared with H2RA users,PPI users demonstrated a higher rate of all-cause mortality HR:1.51(95%CI:1.41-1.69).Similar results were observed across sensitivity analyses by excluding deaths from the first 9 months and 1-year post-exposure,confirming the robustness of these findings.In a sensitivity analysis,we analyzed all-cause mortality outcomes between former PPI users and individuals who have never used PPIs,providing insights into the long-term effects of past PPI use.In addition,at 1-year follow-up,the analysis revealed a significant difference in mortality rates between former PPI users and non-users(HR:1.84;95%CI:1.82-1.96).CONCLUSION PPI use among cancer patients was associated with a higher risk of all-cause mortality compared to non-users or H2RA users.These findings emphasize the need for cautious use of PPIs in cancer patients and suggest that alternative treatments should be considered when clinically feasible.However,further studies are needed to corroborate our findings,given the significant adverse outcomes in cancer patients.
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funding from the European Research Council(ERC)under the European Union’s Horizon 2020 Research and Innovation Program through the Starting Grant GEoREST(grant agreement No.801809)support by MICIU/AEI/10.13039/501100011033 and by"European Union Next Generation EU/PRTR"through the‘Ramón y Cajal’fellowship(reference RYC2021-032780-I)+9 种基金funding by MICIU/AEI/10.13039/501100011033 and by“ERDF,EU”through the‘HydroPoreII’project(reference PID2022-137652NBC44)support by the Institute for Korea Spent Nuclear Fuel(iKSNF)National Research Foundation of Korea(NRF)grant funded by the Korea government(Ministry of Science and ICT,MSIT)(2021M2E1A1085196)support by the Swedish Radiation Safety(SSM),Swedish Transport Administration(Trafikverket),Swedish Rock Engineering Foundation(BeFo),and Nordic Energy Research(Grant 187658)supported by the US Department of Energy(DOE),the Officeof Nuclear Energy,Spent Fuel and Waste Science and Technology Campaign,and by the US Department of Energy(DOE),the Office of Basic Energy Sciences,Chemical Sciences,Geosciences,and Biosciences Division both under Contract Number DE-AC02-05CH11231 with Lawrence Berkeley National Laboratorysupport from the US National Science Foundation(grant CMMI-2239630)funding from the European Research Council(ERC)under the European Union’s Horizon 2020 research and innovation programme(grant agreement No.101002507)the UK Natural Environment Research Council(NERC)for funding SeisGreen Project(Grant No.NE/W009293/1)which supported this workthe Royal Society UK for supporting this research through fellowship UF160443IMEDEA is an accredited"Maria de Maeztu Excellence Unit"(Grant CEX2021-001198,funded by MICIU/AEI/10.13039/501100011033).
文摘Coupled thermo-hydro-mechanical(THM)processes in fractured rock are playing a crucial role in geoscience and geoengineering applications.Diverse and conceptually distinct approaches have emerged over the past decades in both continuum and discontinuum perspectives leading to significant progress in their comprehending and modeling.This review paper offers an integrated perspective on existing modeling methodologies providing guidance for model selection based on the initial and boundary conditions.By comparing various models,one can better assess the uncertainties in predictions,particularly those related to the conceptual models.The review explores how these methodologies have significantlyenhanced the fundamental understanding of how fractures respond to fluid injection and production,and improved predictive capabilities pertaining to coupled processes within fractured systems.It emphasizes the importance of utilizing advanced computational technologies and thoroughly considering fundamental theories and principles established through past experimental evidence and practical experience.The selection and calibration of model parameters should be based on typical ranges and applied to the specificconditions of applications.The challenges arising from inherent heterogeneity and uncertainties,nonlinear THM coupled processes,scale dependence,and computational limitations in representing fieldscale fractures are discussed.Realizing potential advances on computational capacity calls for methodical conceptualization,mathematical modeling,selection of numerical solution strategies,implementation,and calibration to foster simulation outcomes that intricately reflectthe nuanced complexities of geological phenomena.Future research efforts should focus on innovative approaches to tackle the hurdles and advance the state-of-the-art in this critical fieldof study.
文摘In this study,the wave motion in elastodynamics for unbounded media is modeled using an unsplit-field perfectly matched layer(PML)formulation that is solved by employing an isogeometric analysis(IGA).In the adopted combination,the non-uniform rational B-spline(NURBS)functions are employed as basis functions.Moreover,the unbounded and artificial domains,defined in the PML method,are contained in a single patch domain.Based on the proposed scheme,the approximation of the geometry problem is set in a new scheme in which the PML’s absorbing and attenuation properties and the description of traveling waves can be represented.This includes a higher continuity and smoother approximation of the computed domain.As high-order NURBS basis functions are non-interpolatory,a penalty method is present to apply a time-dependent displacement load.The performance of the NURBS-based PML is analyzed through numerical examples for 1D and 2D domains,considering homogeneous and heterogeneous media.Further,we verify the long-time numerical stability of the present method.The developed method can be used to simulate hypothetical stratified domains commonly encountered in soil-structure interaction analyses.
