The phenomenon of nutrient maximums at 70～200 m occurred only in the regionof the Canada Basin among the world oceans. The prevailing hypothesis was that the direct injectionof the low-temperature high-nutrient brine...The phenomenon of nutrient maximums at 70～200 m occurred only in the regionof the Canada Basin among the world oceans. The prevailing hypothesis was that the direct injectionof the low-temperature high-nutrient brines from the Chukchi Sea shelf (【 50 m) in winter providedthe nutrient maximums. However, we found that there are five problems in the direct injectionprocess. Formerly Jin et al. considered that the formation of nutrient maximums can be a process oflocally long-term regeneration. Here we propose a regeneration-mixture process. Data of temperature,salinity, oxygen and nutrients were collected at three stations in the southern Canada Basin duringthe summer 1999 cruise. We identified the cores of the surface, near-surface, potential temperaturemaximum waters and Arctic Bottom Water by the diagrams and vertical profiles of salinity, potentialtemperature, oxygen and nutrients. The historical ^(129)I data indicated that the surface andnear-surface waters were Pacific-origin, but the waters below the potential temperature maximum coredepth was Atlantic-origin. Along with the correlation of nutrient maximums and very low oxygencontents in the near-surface water, we hypothesize that, the putative organic matter was decomposedto inorganic nutrients; and the Pacific water was mixed with the Atlantic water in the transitionzone. The idea of the regeneration-mixture process agrees with the historical observations of noapparent seasonal changes, the smooth nutrient profiles, the lowest saturation of CaCO_3 above 400m, low rate of CFC-11 ventilation and ~3H-~3He ages of 8～18 a around the nutrient maximum depths.展开更多
Domain adaptation aims to reduce the distribution gap between the training data(source domain)and the target data.This enables effective predictions even for domains not seen during training.However,most conventional ...Domain adaptation aims to reduce the distribution gap between the training data(source domain)and the target data.This enables effective predictions even for domains not seen during training.However,most conventional domain adaptation methods assume a single source domain,making them less suitable for modern deep learning settings that rely on diverse and large-scale datasets.To address this limitation,recent research has focused on Multi-Source Domain Adaptation(MSDA),which aims to learn effectively from multiple source domains.In this paper,we propose Efficient Domain Transition for Multi-source(EDTM),a novel and efficient framework designed to tackle two major challenges in existing MSDA approaches:(1)integrating knowledge across different source domains and(2)aligning label distributions between source and target domains.EDTM leverages an ensemble-based classifier expert mechanism to enhance the contribution of source domains that are more similar to the target domain.To further stabilize the learning process and improve performance,we incorporate imitation learning into the training of the target model.In addition,Maximum Classifier Discrepancy(MCD)is employed to align class-wise label distributions between the source and target domains.Experiments were conducted using Digits-Five,one of the most representative benchmark datasets for MSDA.The results show that EDTM consistently outperforms existing methods in terms of average classification accuracy.Notably,EDTM achieved significantly higher performance on target domains such as Modified National Institute of Standards and Technolog with blended background images(MNIST-M)and Street View House Numbers(SVHN)datasets,demonstrating enhanced generalization compared to baseline approaches.Furthermore,an ablation study analyzing the contribution of each loss component validated the effectiveness of the framework,highlighting the importance of each module in achieving optimal performance.展开更多
We incorporate a non-Markovian feedback mechanism into the simulated bifurcation method for dynamical solvers addressing combinatorial optimization problems.By reinjecting a portion of dissipated kinetic energy into e...We incorporate a non-Markovian feedback mechanism into the simulated bifurcation method for dynamical solvers addressing combinatorial optimization problems.By reinjecting a portion of dissipated kinetic energy into each spin in a history-dependent and trajectory-informed manner,the method effectively suppresses early freezing induced by inelastic boundaries and enhances the system's ability to explore complex energy landscapes.Numerical results on the maximum cut(MAX-CUT)instances of fully connected Sherrington–Kirkpatrick(SK)spin glass models,including the 2000-spin K_(2000)benchmark,demonstrate that the non-Markovian algorithm significantly improves both solution quality and convergence speed.Tests on randomly generated SK instances with 100 to 1000 spins further indicate favorable scalability and substantial gains in computational efficiency.Moreover,the proposed scheme is well suited for massively parallel hardware implementations,such as field-programmable gate arrays,providing a practical and scalable approach for solving large-scale combinatorial optimization problems.展开更多
This study investigates the impacts of mixing time,execution procedure,cement dosage(α),and total water-to-cement ratio(W_(Total)/C)on the mixing energy(E)of deep soil mixing(DSM)columns and how E influences the stre...This study investigates the impacts of mixing time,execution procedure,cement dosage(α),and total water-to-cement ratio(W_(Total)/C)on the mixing energy(E)of deep soil mixing(DSM)columns and how E influences the strength of treated sand.Columns with a diameter of 7.5 cm were constructed using three mixing times(130,190,and 250 s),two execution procedures(normal and zigzag),threeαvalues(300,400,and 500 kg/m^(3)),and three W_(Total)/C ratios(2.5,3.0,and 3.5).For comparison,equivalent laboratory samples were also examined.Results revealed that increasing the mixing time andα,adopting the zigzag execution procedure,and reducing the W_(Total)/C ratio increase E.Outcomes indicated that an increase in E from 0.49-0.70 kJ to 0.70-0.90 kJ,0.90-1.10 kJ,and 1.10-1.40 kJ improves the unconfined compressive strength(UCS)of columns on average by 66%,124%,and 179%,respectively,and the secant modulus by 61%,110%,and 152%.Average strain at maximum stress also rises from 0.68%to 0.75%,0.81%,and 0.84%,respectively.The study identified a threshold in the direct relationship between E and the strength ratio(λ),beyond whichλdid not increase significantly with further increases in E.Additionally,at low and high E levels,DSM samples mainly failed by crushing and cracking modes,respectively.In DSM columns withα=500 kg/m^(3)and W_(Total)/C=2.5,increasing average E from 0.77 kJ to 0.95 kJ,1.08 kJ,and 1.28 kJ resulted in a reduction of coefficients of variation of UCS from 30.4%to 27.8%,24.5%,and 21.1%,respectively.展开更多
We present a computer-modeling framework for photovoltaic(PV)source emulation that preserves the exact single-diode physics while enabling iteration-free,real-time evaluation.We derive two closed-form explicit solvers...We present a computer-modeling framework for photovoltaic(PV)source emulation that preserves the exact single-diode physics while enabling iteration-free,real-time evaluation.We derive two closed-form explicit solvers based on the Lambert W function:a voltage-driven V-Lambert solver for high-fidelity I–V computation and a resistance-driven R-Lambert solver designed for seamless integration in a closed-loop PV emulator.Unlike Taylor-linearized explicit models,our proposed formulation retains the exponential nonlinearity of the PV equations.It employs a numerically stable analytical evaluation that eliminates the need for lookup tables and root-finding,all while maintaining limited computational costs and a small memory footprint.The R-Lambert model is integrated into a buck-converter emulator equipped with a discrete PI regulator,which generates current references directly from sensed operating points,thus supporting hardware-constrained implementation.Comprehensive numerical experiments conducted on six commercial modules from various technologies(mono,poly,and multicrystalline)demonstrate significant accuracy improvements under the IEC EN 50530 near-MPP criterion:the V-Lambert solver reduces the±10%Vmpp band error by up to 61 times compared to an explicit-model baseline.Dynamic simulations under varying irradiance,temperature,and load conditions achieve millisecond-scale settling with accurate trajectory tracking.Additionally,processor-in-the-loop experimental validation on an embedded microcontroller supports the simulation results.By unifying exact analytical modeling with embedded realization,this work advances computer modeling for PV emulation,MPPT benchmarking,and controller verification in integrated renewable energy systems.展开更多
Climate change is altering river regimes in mountainous regions,affecting water availability and the functioning of aquatic ecosystems.In the Andes Mountains,characterizing the natural flow regime is essential for est...Climate change is altering river regimes in mountainous regions,affecting water availability and the functioning of aquatic ecosystems.In the Andes Mountains,characterizing the natural flow regime is essential for establishing operational conditions that balance multiple water uses(irrigation,supply,hydropower)with the conservation of high-elevation ecosystems in the context of increasing hydroclimatic variability.This study analyzes extreme hydrological conditions in nivoglacial rivers of the upper Mendoza River Basin(Argentina),using indicators of magnitude,frequency,duration,and timing of high(HP)and low(LP)pulses.Daily flow records from the Cuevas,Vacas,Tupungato,and Mendoza Rivers were used to define eight ecologically relevant extreme hydrological parameters over the period 1956–2023.The results reveal a reduction in the magnitude of extreme flows since 2010(−30%to–55%)and significant delays in their timing,with maximum and minimum flow shifting by 15–20 days later in recent decades.The duration of LP events increased by 120%–240%in the Cuevas,Tupungato,and Mendoza Rivers,while in the Tupungato River,HP events tended to occur less frequently but with longer durations.These changes are associated with a 0.1℃decade^(−1)rise in mean temperature and a∼25%decrease in precipitation since 2009.Such trends have major implications for water resource management and the resilience of high-Andean ecosystems under climate warming.展开更多
Triggered seismicity is a key hazard where fluids are injected or withdrawn from the subsurface and may impact permeability. Understanding the mechanisms that control fluid injection-triggered seismicity allows its mi...Triggered seismicity is a key hazard where fluids are injected or withdrawn from the subsurface and may impact permeability. Understanding the mechanisms that control fluid injection-triggered seismicity allows its mitigation. Key controls on seismicity are defined in terms of fault and fracture strength, second-order frictional response and stability, and competing fluid-driven mechanisms for arrest. We desire to constrain maximum event magnitudes in triggered earthquakes by relating pre-existing critical stresses to fluid injection volume to explain why some recorded events are significantly larger than anticipated seismic moment thresholds. This formalism is consistent with several uncharacteristically large fluid injection-triggered earthquakes. Such methods of reactivating fractures and faults by hydraulic stimulation in shear or tensile fracturing are routinely used to create permeability in the subsurface. Microearthquakes (MEQs) generated by such stimulations can be used to diagnose permeability evolution. Although high-fidelity data sets are scarce, the EGS-Collab and Utah FORGE hydraulic stimulation field demonstration projects provide high-fidelity data sets that concurrently track permeability evolution and triggered seismicity. Machine learning deciphers the principal features of MEQs and the resulting permeability evolution that best track permeability changes – with transfer learning methods allowing robust predictions across multiple eological settings. Changes in permeability at reactivated fractures in both shear and extensional modes suggest that permeability change (Δk) scales with the seismic moment (M) of individual MEQs as Δk∝M. This scaling relation is exact at early times but degrades with successive MEQs, but provides a method for characterizing crustal permeability evolution using MEQs, alone. Importantly, we quantify for the first time the role of prestress in defining the elevated magnitude and seismic moment of fluid injection-triggered events, and demonstrate that such MEQs can also be used as diagnostic in quantifying permeability evolution in the crust.展开更多
To investigate the effects of the maximum principal stress direction(θ)and cross-section shape on the failure characteristics of sandstone,true-triaxial compression experiments were conducted using cubic samples with...To investigate the effects of the maximum principal stress direction(θ)and cross-section shape on the failure characteristics of sandstone,true-triaxial compression experiments were conducted using cubic samples with rectangular,circular,and D-shaped holes.Asθincreases from 0°to 60°in the rectangular hole,the left failure location shifts from the left corner to the left sidewall,the left corner,and then the floor,while the right failure location shifts from the right corner to the right sidewall,right roof corner,and then the roof.Furthermore,the initial failure vertical stress first decreases and then increases.In comparison,the failure severity in the rectangular hole decreases for variousθvalues as 30°>45°>60°>0°.With increasingθ,the fractal dimension(D)of rock slices first increases and then decreases.For the rectangular and D-shaped holes,whenθ=0°,30°,and 90°,D for the rectangular hole is less than that of the D-shaped hole.Whenθ=45°and 60°,D for the rectangular hole is greater than that of the D-shaped hole.Theoretical analysis indicates that the stress concentration at the rectangular and D-shaped corners is greater than the other areas.The failure location rotates with the rotation ofθ,and the failure occurs on the side with a high concentration of compressive stress,while the side with the tensile and compressive stresses remains relatively stable.Therefore,the fundamental reason for the rotation of failure location is the rotation of stress concentration,and the external influencing factor is the rotation ofθ.展开更多
In this paper,an advanced satellite navigation filter design,referred to as the Variational Bayesian Maximum Correntropy Extended Kalman Filter(VBMCEKF),is introduced to enhance robustness and adaptability in scenario...In this paper,an advanced satellite navigation filter design,referred to as the Variational Bayesian Maximum Correntropy Extended Kalman Filter(VBMCEKF),is introduced to enhance robustness and adaptability in scenarios with non-Gaussian noise and heavy-tailed outliers.The proposed design modifies the extended Kalman filter(EKF)for the global navigation satellite system(GNSS),integrating the maximum correntropy criterion(MCC)and the variational Bayesian(VB)method.This adaptive algorithm effectively reduces non-line-of-sight(NLOS)reception contamination and improves estimation accuracy,particularly in time-varying GNSS measurements.Experimental results show that the proposed method significantly outperforms conventional approaches in estimation accuracy under heavy-tailed outliers and non-Gaussian noise.By combining MCC with VB approximation for real-time noise covariance estimation using fixed-point iteration,the VBMCEKF achieves superior filtering performance in challenging GNSS conditions.The method’s adaptability and precision make it ideal for improving satellite navigation performance in stochastic environments.展开更多
Understanding the mechanical properties of the lithologies is crucial to accurately determine the horizontal stress magnitude.To investigate the correlation between the rock mass properties and maximum horizontal stre...Understanding the mechanical properties of the lithologies is crucial to accurately determine the horizontal stress magnitude.To investigate the correlation between the rock mass properties and maximum horizontal stress,the three-dimensional(3D)stress tensors at 89 measuring points determined using an improved overcoring technique in nine mines in China were adopted,a newly defined characteristic parameter C_(ERP)was proposed as an indicator for evaluating the structural properties of rock masses,and a fuzzy relation matrix was established using the information distribution method.The results indicate that both the vertical stress and horizontal stress exhibit a good linear growth relationship with depth.There is no remarkable correlation between the elastic modulus,Poisson's ratio and depth,and the distribution of data points is scattered and messy.Moreover,there is no obvious relationship between the rock quality designation(RQD)and depth.The maximum horizontal stress σ_(H) is a function of rock properties,showing a certain linear relationship with the C_(ERP)at the same depth.In addition,the overall change trend of σ_(H) determined by the established fuzzy identification method is to increase with the increase of C_(ERP).The fuzzy identification method also demonstrates a relatively detailed local relationship betweenσ_H and C_(ERP),and the predicted curve rises in a fluctuating way,which is in accord well with the measured stress data.展开更多
Statistical characteristics and the classification of the topside ionospheric mid-latitude trough are systemically analyzed,using observations from the Defense Meteorological Satellite Program F18(DMSP-F18)satellite.T...Statistical characteristics and the classification of the topside ionospheric mid-latitude trough are systemically analyzed,using observations from the Defense Meteorological Satellite Program F18(DMSP-F18)satellite.The data was obtained at an altitude of around 860 km in near polar orbit,throughout 2013.Our study identified the auroral boundary based on the in-situ electron density and electron spectrum,allowing us to precisely determine the location of the mid-latitude trough.This differs from most previous works,which only use Total Electron Content(TEC)or in-situ electron density.In our study,the troughs exhibited a higher occurrence rate in local winter than in summer,and extended to lower latitudes with increasing geomagnetic activity.It was found that the ionospheric mid-latitude trough,which is associated with temperature changes or enhanced ion drift,exhibited distinct characteristics.Specifically,the ionospheric mid-latitude troughs related to electron temperature(Te)peak were located more equatorward of auroral oval boundary in winter than in summer.The ionospheric mid-latitude troughs related to Te-maximum were less frequently observed at 60−70°S magnetic latitude and 90−240°E longitude.Furthermore,the troughs related to ion temperature(Ti)maximums were observed at relatively higher latitudes,occurring more frequently in winter.In addition,the troughs related to ion velocity(Vi)maximums could be observed in all seasons.The troughs with the maximum-Ti and maximum-Vi were located closer to the equatorward boundary of the auroral oval at the nightside,and in both hemispheres.This implies that enhanced ion drift velocity contributes to increased collisional frictional heating and enhanced ion temperatures,resulting in a density depletion within the trough region.展开更多
Let(M,g)be a compact Riemann surface with unit area,h a smooth function on M.The Kazdan-Warner problem is that under what kind of conditions on h the equationΔu=8π-8πhe^(u) has a solution.In this survey article,we ...Let(M,g)be a compact Riemann surface with unit area,h a smooth function on M.The Kazdan-Warner problem is that under what kind of conditions on h the equationΔu=8π-8πhe^(u) has a solution.In this survey article,we shall review the development of this problem along the variational method.展开更多
Gamma-ray imaging systems are powerful tools in radiographic diagnosis.However,the recorded images suffer from degradations such as noise,blurring,and downsampling,consequently failing to meet high-precision diagnosti...Gamma-ray imaging systems are powerful tools in radiographic diagnosis.However,the recorded images suffer from degradations such as noise,blurring,and downsampling,consequently failing to meet high-precision diagnostic requirements.In this paper,we propose a novel single-image super-resolution algorithm to enhance the spatial resolution of gamma-ray imaging systems.A mathematical model of the gamma-ray imaging system is established based on maximum a posteriori estimation.Within the plug-and-play framework,the half-quadratic splitting method is employed to decouple the data fidelit term and the regularization term.An image denoiser using convolutional neural networks is adopted as an implicit image prior,referred to as a deep denoiser prior,eliminating the need to explicitly design a regularization term.Furthermore,the impact of the image boundary condition on reconstruction results is considered,and a method for estimating image boundaries is introduced.The results show that the proposed algorithm can effectively addresses boundary artifacts.By increasing the pixel number of the reconstructed images,the proposed algorithm is capable of recovering more details.Notably,in both simulation and real experiments,the proposed algorithm is demonstrated to achieve subpixel resolution,surpassing the Nyquist sampling limit determined by the camera pixel size.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
The extended Kalman filter(EKF)is extensively applied in integrated navigation systems that combine the global navigation satellite system(GNSS)and strap-down inertial navigation system(SINS).However,the performance o...The extended Kalman filter(EKF)is extensively applied in integrated navigation systems that combine the global navigation satellite system(GNSS)and strap-down inertial navigation system(SINS).However,the performance of the EKF can be severely impacted by non-Gaussian noise and measurement noise uncertainties,making it difficult to achieve optimal GNSS/INS integration.Dealing with non-Gaussian noise remains a significant challenge in filter development today.Therefore,the maximum correntropy criterion(MCC)is utilized in EKFs to manage heavytailed measurement noise.However,its capability to handle non-Gaussian process noise and unknown disturbances remains largely unexplored.In this paper,we extend correntropy from using a single kernel to a multi-kernel approach.This leads to the development of a multi-kernel maximum correntropy extended Kalman filter(MKMC-EKF),which is designed to effectively manage multivariate non-Gaussian noise and disturbances.Further,theoretical analysis,including advanced stability proofs,can enhance understanding,while hybrid approaches integrating MKMC-EKF with particle filters may improve performance in nonlinear systems.The MKMC-EKF enhances estimation accuracy using a multi-kernel bandwidth approach.As bandwidth increases,the filter’s sensitivity to non-Gaussian features decreases,and its behavior progressively approximates that of the iterated EKF.The proposed approach for enhancing positioning in navigation is validated through performance evaluations,which demonstrate its practical applications in real-world systems like GPS navigation and measuring radar targets.展开更多
The rapid expansion of tobacco farming poses a significant threat to biodiversity in Yunnan Province,China,a region known for its rich biodiversity.This study aims to understand the trade-offs between tobacco farming ...The rapid expansion of tobacco farming poses a significant threat to biodiversity in Yunnan Province,China,a region known for its rich biodiversity.This study aims to understand the trade-offs between tobacco farming and higher plant species diversity,and to identify priority counties for conservation.We employed an integrated approach combining species distribution modeling,GIS overlay analysis,and empirical spatial regression to em pirically assess the impact of tobacco farming intensity on biodiversity risk.Our findings reveal a compelling negative spatial correlation between tobacco farming expansion and higher plant species diversity.Specifically,southern counties in Wenshan and Honghe prefectures are major priority areas of conservation that exhibit signif icant spatial correlations between biodiversity risks and high tobacco farming intensity.Quantitatively,at county level,a 1%increase in tobacco farming area corresponds to a 0.094%decrease in endemic higher plant species richness across the entire province.These results underscore the need for targeted and region-specific regulations to mitigate biodiversity loss and promote sustainable development in Yunnan Province.The integrated approach used in this study provides a comprehensive assessment of the tobacco-biodiversity trade-offs,offering actionable insights for policymaking.展开更多
Globally bentoite clay has been proposed as an engineered barrier material for safe underground disposal of high-level nuclear waste.Clay has many favorable properties such as high liquid limit,and plastic limit along...Globally bentoite clay has been proposed as an engineered barrier material for safe underground disposal of high-level nuclear waste.Clay has many favorable properties such as high liquid limit,and plastic limit along with other properties which make it the most suitable for this application.In the present study,an attempt has been made to study the behavior of Barmer bentonite under the influence of high temperatures up to 120℃.Properties of barmer bentonite namely,liquid limit,plastic limit,and maximum dry density have been determined after thermal treatment at 25℃,60℃,80℃,100℃ and 120℃.The extensive experimental results indicate that liquid limit and plastic limit show a decreasing trend while maximum dry density increases with an increase in temperature.Liquid limit and plastic limit decrease up to 12%and 11%respectively when the temperature reaches up to 120℃.Maximum dry density increases by 10%due to thermal treatment and optimum water content decreases by up to 4%.Statistical analysis has been carried out to obtain the correlation between temperature and physical properties of Barmer bentonite such as liquid limit,plastic limit,maximum dry density,and optimum water content.The XRD analysis of Barmer bentonite at room temperature and 120℃ shows very small variation in mineralogical composition.Whereas,interlayer distance has been measured and found to be decreasing with an increase in temperature.Further,a comparative analysis shows that the measured properties of studied Barmer bentonite lie in the range of previously measured values of other types of bentonite across the globe.展开更多
Amid increasingly frequent military conflicts and explosion events,accurately predicting the dynamic response of reinforced concrete(RC) slabs,key load-bearing components in building structures,is essential for unders...Amid increasingly frequent military conflicts and explosion events,accurately predicting the dynamic response of reinforced concrete(RC) slabs,key load-bearing components in building structures,is essential for understanding blast-induced damage and enhancing structural protection.However,current approaches predominantly rely on experimental tests,finite element(FE) simulations,and conventional machine learning(ML) techniques,which are o ften costly,inefficie nt,narrowly applicable,and insufficiently accurate.To overcome these challenges,this study aims to optimize ML models,refine architectural designs,and improve model interpretability.A comprehensive dataset comprising 489 samples was constructed by integrating experimental and simulation data from existing literature,incorporating 15 input features and one target variable.Based on this dataset,a novel method,termed MOPSO-TXGBoost,was proposed.Building on XGBoost as a baseline,the method employs multiobjective particle swarm optimization(MOPSO) for hyperparameter tuning,introduces a tri-stream stacking architecture to enhance feature representation,and trains three distinct models to improve generalization performance.A weighted fusion strategy is employed to further enhance the accuracy of predictio n.Additio nally,a model comprehensive evaluation(MCE) index is introduced,which integrates error metrics and fitting performance to facilitate systematic model assessment.Experimental results indicate that,compared with the baseline XGBoost model,the proposed approach reduces prediction error by 61.4% and increases the coefficient of determination(R^(2)) by 0.217.Moreover,it outperforms several mainstream machine learning(ML) algorithms.The findings of this study advance ML-based blast damage prediction and provide theoretical support for safety assessment and protection optimization of RC slab structures.展开更多
During upward horizontal stratified backfill mining,stable backfill is essential for cap and sill pillar recovery.Currently,the primary method for calculating the required strength of backfill is the generalized three...During upward horizontal stratified backfill mining,stable backfill is essential for cap and sill pillar recovery.Currently,the primary method for calculating the required strength of backfill is the generalized three-dimensional(3 D)vertical stress model,which ignores the effect of mine depth,failing to obtain the vertical stress at different positions along stope length.Therefore,this paper develops and validates an improved 3 D model solution through numerical simulation in Rhino-FLAC^(3D),and examines the stress state and stability of backfill under different conditions.The results show that the improved model can accurately calculate the vertical stress at different mine depths and positions along stope length.The error rates between the results of the improved model and numerical simulation are below 4%,indicating high reliability and applicability.The maximum vertical stress(σ_(zz,max))in backfill is positively correlated with the degree of rock-backfill closure,which is enhanced by mine depth and elastic modulus of backfill,while weakened by stope width and inclination,backfill friction angle,and elastic modulus of rock mass.Theσ_(zz,max)reaches its peak when the stope length is 150 m,whileσ_(zz,max)is insensitive to changes in rock-backfill interface parameters.In all cases,the backfill stability can be improved by reducingσ_(zz,max).The results provide theoretical guidance for the backfill strength design and the safe and efficient recovery of ore pillars in deep mining.展开更多
基金supported by the Ministry of Finance of China,organized by the Chinese Arctic and Antarctic Administration(CAA)supported by the National Natu-ral Science Foundation of China under contract Nos 40476003 and 40403013the National“973”Pro-gram of China under contract No.G1999043704.
文摘The phenomenon of nutrient maximums at 70～200 m occurred only in the regionof the Canada Basin among the world oceans. The prevailing hypothesis was that the direct injectionof the low-temperature high-nutrient brines from the Chukchi Sea shelf (【 50 m) in winter providedthe nutrient maximums. However, we found that there are five problems in the direct injectionprocess. Formerly Jin et al. considered that the formation of nutrient maximums can be a process oflocally long-term regeneration. Here we propose a regeneration-mixture process. Data of temperature,salinity, oxygen and nutrients were collected at three stations in the southern Canada Basin duringthe summer 1999 cruise. We identified the cores of the surface, near-surface, potential temperaturemaximum waters and Arctic Bottom Water by the diagrams and vertical profiles of salinity, potentialtemperature, oxygen and nutrients. The historical ^(129)I data indicated that the surface andnear-surface waters were Pacific-origin, but the waters below the potential temperature maximum coredepth was Atlantic-origin. Along with the correlation of nutrient maximums and very low oxygencontents in the near-surface water, we hypothesize that, the putative organic matter was decomposedto inorganic nutrients; and the Pacific water was mixed with the Atlantic water in the transitionzone. The idea of the regeneration-mixture process agrees with the historical observations of noapparent seasonal changes, the smooth nutrient profiles, the lowest saturation of CaCO_3 above 400m, low rate of CFC-11 ventilation and ~3H-~3He ages of 8～18 a around the nutrient maximum depths.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(No.RS-2024-00406320)the Institute of Information&Communica-tions Technology Planning&Evaluation(IITP)-Innovative Human Resource Development for Local Intellectualization Program Grant funded by the Korea government(MSIT)(IITP-2026-RS-2023-00259678).
文摘Domain adaptation aims to reduce the distribution gap between the training data(source domain)and the target data.This enables effective predictions even for domains not seen during training.However,most conventional domain adaptation methods assume a single source domain,making them less suitable for modern deep learning settings that rely on diverse and large-scale datasets.To address this limitation,recent research has focused on Multi-Source Domain Adaptation(MSDA),which aims to learn effectively from multiple source domains.In this paper,we propose Efficient Domain Transition for Multi-source(EDTM),a novel and efficient framework designed to tackle two major challenges in existing MSDA approaches:(1)integrating knowledge across different source domains and(2)aligning label distributions between source and target domains.EDTM leverages an ensemble-based classifier expert mechanism to enhance the contribution of source domains that are more similar to the target domain.To further stabilize the learning process and improve performance,we incorporate imitation learning into the training of the target model.In addition,Maximum Classifier Discrepancy(MCD)is employed to align class-wise label distributions between the source and target domains.Experiments were conducted using Digits-Five,one of the most representative benchmark datasets for MSDA.The results show that EDTM consistently outperforms existing methods in terms of average classification accuracy.Notably,EDTM achieved significantly higher performance on target domains such as Modified National Institute of Standards and Technolog with blended background images(MNIST-M)and Street View House Numbers(SVHN)datasets,demonstrating enhanced generalization compared to baseline approaches.Furthermore,an ablation study analyzing the contribution of each loss component validated the effectiveness of the framework,highlighting the importance of each module in achieving optimal performance.
基金supported by the National Key Research and Development Program of China(Grant No.2024YFA1408500)the National Natural Science Foundation of China(Grant Nos.12174028 and 12574115)the Open Fund of the State Key Laboratory of Spintronics Devices and Technologies(Grant No.SPL-2408)。
文摘We incorporate a non-Markovian feedback mechanism into the simulated bifurcation method for dynamical solvers addressing combinatorial optimization problems.By reinjecting a portion of dissipated kinetic energy into each spin in a history-dependent and trajectory-informed manner,the method effectively suppresses early freezing induced by inelastic boundaries and enhances the system's ability to explore complex energy landscapes.Numerical results on the maximum cut(MAX-CUT)instances of fully connected Sherrington–Kirkpatrick(SK)spin glass models,including the 2000-spin K_(2000)benchmark,demonstrate that the non-Markovian algorithm significantly improves both solution quality and convergence speed.Tests on randomly generated SK instances with 100 to 1000 spins further indicate favorable scalability and substantial gains in computational efficiency.Moreover,the proposed scheme is well suited for massively parallel hardware implementations,such as field-programmable gate arrays,providing a practical and scalable approach for solving large-scale combinatorial optimization problems.
文摘This study investigates the impacts of mixing time,execution procedure,cement dosage(α),and total water-to-cement ratio(W_(Total)/C)on the mixing energy(E)of deep soil mixing(DSM)columns and how E influences the strength of treated sand.Columns with a diameter of 7.5 cm were constructed using three mixing times(130,190,and 250 s),two execution procedures(normal and zigzag),threeαvalues(300,400,and 500 kg/m^(3)),and three W_(Total)/C ratios(2.5,3.0,and 3.5).For comparison,equivalent laboratory samples were also examined.Results revealed that increasing the mixing time andα,adopting the zigzag execution procedure,and reducing the W_(Total)/C ratio increase E.Outcomes indicated that an increase in E from 0.49-0.70 kJ to 0.70-0.90 kJ,0.90-1.10 kJ,and 1.10-1.40 kJ improves the unconfined compressive strength(UCS)of columns on average by 66%,124%,and 179%,respectively,and the secant modulus by 61%,110%,and 152%.Average strain at maximum stress also rises from 0.68%to 0.75%,0.81%,and 0.84%,respectively.The study identified a threshold in the direct relationship between E and the strength ratio(λ),beyond whichλdid not increase significantly with further increases in E.Additionally,at low and high E levels,DSM samples mainly failed by crushing and cracking modes,respectively.In DSM columns withα=500 kg/m^(3)and W_(Total)/C=2.5,increasing average E from 0.77 kJ to 0.95 kJ,1.08 kJ,and 1.28 kJ resulted in a reduction of coefficients of variation of UCS from 30.4%to 27.8%,24.5%,and 21.1%,respectively.
基金funded by Scientific Research Deanship at University of Ha’il-Saudi Arabia through project number(RG-24014).
文摘We present a computer-modeling framework for photovoltaic(PV)source emulation that preserves the exact single-diode physics while enabling iteration-free,real-time evaluation.We derive two closed-form explicit solvers based on the Lambert W function:a voltage-driven V-Lambert solver for high-fidelity I–V computation and a resistance-driven R-Lambert solver designed for seamless integration in a closed-loop PV emulator.Unlike Taylor-linearized explicit models,our proposed formulation retains the exponential nonlinearity of the PV equations.It employs a numerically stable analytical evaluation that eliminates the need for lookup tables and root-finding,all while maintaining limited computational costs and a small memory footprint.The R-Lambert model is integrated into a buck-converter emulator equipped with a discrete PI regulator,which generates current references directly from sensed operating points,thus supporting hardware-constrained implementation.Comprehensive numerical experiments conducted on six commercial modules from various technologies(mono,poly,and multicrystalline)demonstrate significant accuracy improvements under the IEC EN 50530 near-MPP criterion:the V-Lambert solver reduces the±10%Vmpp band error by up to 61 times compared to an explicit-model baseline.Dynamic simulations under varying irradiance,temperature,and load conditions achieve millisecond-scale settling with accurate trajectory tracking.Additionally,processor-in-the-loop experimental validation on an embedded microcontroller supports the simulation results.By unifying exact analytical modeling with embedded realization,this work advances computer modeling for PV emulation,MPPT benchmarking,and controller verification in integrated renewable energy systems.
基金National Scientific and Technical Research Council of Argentina(CONICET),Grant/Award Number:PIBAA2022-202328720210100485CO。
文摘Climate change is altering river regimes in mountainous regions,affecting water availability and the functioning of aquatic ecosystems.In the Andes Mountains,characterizing the natural flow regime is essential for establishing operational conditions that balance multiple water uses(irrigation,supply,hydropower)with the conservation of high-elevation ecosystems in the context of increasing hydroclimatic variability.This study analyzes extreme hydrological conditions in nivoglacial rivers of the upper Mendoza River Basin(Argentina),using indicators of magnitude,frequency,duration,and timing of high(HP)and low(LP)pulses.Daily flow records from the Cuevas,Vacas,Tupungato,and Mendoza Rivers were used to define eight ecologically relevant extreme hydrological parameters over the period 1956–2023.The results reveal a reduction in the magnitude of extreme flows since 2010(−30%to–55%)and significant delays in their timing,with maximum and minimum flow shifting by 15–20 days later in recent decades.The duration of LP events increased by 120%–240%in the Cuevas,Tupungato,and Mendoza Rivers,while in the Tupungato River,HP events tended to occur less frequently but with longer durations.These changes are associated with a 0.1℃decade^(−1)rise in mean temperature and a∼25%decrease in precipitation since 2009.Such trends have major implications for water resource management and the resilience of high-Andean ecosystems under climate warming.
基金Derek Elsworth acknowledges the support from a Gledden Visiting Fellowship from the Institute of Advanced Studies at the University of Western Australia,Australia,and the G.Albert Shoemaker Endowment at Pennsylvania State University,USA.
文摘Triggered seismicity is a key hazard where fluids are injected or withdrawn from the subsurface and may impact permeability. Understanding the mechanisms that control fluid injection-triggered seismicity allows its mitigation. Key controls on seismicity are defined in terms of fault and fracture strength, second-order frictional response and stability, and competing fluid-driven mechanisms for arrest. We desire to constrain maximum event magnitudes in triggered earthquakes by relating pre-existing critical stresses to fluid injection volume to explain why some recorded events are significantly larger than anticipated seismic moment thresholds. This formalism is consistent with several uncharacteristically large fluid injection-triggered earthquakes. Such methods of reactivating fractures and faults by hydraulic stimulation in shear or tensile fracturing are routinely used to create permeability in the subsurface. Microearthquakes (MEQs) generated by such stimulations can be used to diagnose permeability evolution. Although high-fidelity data sets are scarce, the EGS-Collab and Utah FORGE hydraulic stimulation field demonstration projects provide high-fidelity data sets that concurrently track permeability evolution and triggered seismicity. Machine learning deciphers the principal features of MEQs and the resulting permeability evolution that best track permeability changes – with transfer learning methods allowing robust predictions across multiple eological settings. Changes in permeability at reactivated fractures in both shear and extensional modes suggest that permeability change (Δk) scales with the seismic moment (M) of individual MEQs as Δk∝M. This scaling relation is exact at early times but degrades with successive MEQs, but provides a method for characterizing crustal permeability evolution using MEQs, alone. Importantly, we quantify for the first time the role of prestress in defining the elevated magnitude and seismic moment of fluid injection-triggered events, and demonstrate that such MEQs can also be used as diagnostic in quantifying permeability evolution in the crust.
基金supported by the National Natural Science Foundation of China (Grant Nos.52304227 and 52104133)Scientific and Technological Research Platform for Disaster Prevention and Control of Deep Coal Mining (Anhui University of Science and Technology) (Grant No.DPDCM2208).
文摘To investigate the effects of the maximum principal stress direction(θ)and cross-section shape on the failure characteristics of sandstone,true-triaxial compression experiments were conducted using cubic samples with rectangular,circular,and D-shaped holes.Asθincreases from 0°to 60°in the rectangular hole,the left failure location shifts from the left corner to the left sidewall,the left corner,and then the floor,while the right failure location shifts from the right corner to the right sidewall,right roof corner,and then the roof.Furthermore,the initial failure vertical stress first decreases and then increases.In comparison,the failure severity in the rectangular hole decreases for variousθvalues as 30°>45°>60°>0°.With increasingθ,the fractal dimension(D)of rock slices first increases and then decreases.For the rectangular and D-shaped holes,whenθ=0°,30°,and 90°,D for the rectangular hole is less than that of the D-shaped hole.Whenθ=45°and 60°,D for the rectangular hole is greater than that of the D-shaped hole.Theoretical analysis indicates that the stress concentration at the rectangular and D-shaped corners is greater than the other areas.The failure location rotates with the rotation ofθ,and the failure occurs on the side with a high concentration of compressive stress,while the side with the tensile and compressive stresses remains relatively stable.Therefore,the fundamental reason for the rotation of failure location is the rotation of stress concentration,and the external influencing factor is the rotation ofθ.
基金supported by the National Science and Technology Council,Taiwan under grants NSTC 111-2221-E-019-047 and NSTC 112-2221-E-019-030.
文摘In this paper,an advanced satellite navigation filter design,referred to as the Variational Bayesian Maximum Correntropy Extended Kalman Filter(VBMCEKF),is introduced to enhance robustness and adaptability in scenarios with non-Gaussian noise and heavy-tailed outliers.The proposed design modifies the extended Kalman filter(EKF)for the global navigation satellite system(GNSS),integrating the maximum correntropy criterion(MCC)and the variational Bayesian(VB)method.This adaptive algorithm effectively reduces non-line-of-sight(NLOS)reception contamination and improves estimation accuracy,particularly in time-varying GNSS measurements.Experimental results show that the proposed method significantly outperforms conventional approaches in estimation accuracy under heavy-tailed outliers and non-Gaussian noise.By combining MCC with VB approximation for real-time noise covariance estimation using fixed-point iteration,the VBMCEKF achieves superior filtering performance in challenging GNSS conditions.The method’s adaptability and precision make it ideal for improving satellite navigation performance in stochastic environments.
基金financially supported by the National Natural Science Foundation of China(No.52204084)the Open Research Fund of the State Key Laboratory of Coal Resources and safe Mining,CUMT,China(No.SKLCRSM 23KF004)+3 种基金the Interdisciplinary Research Project for Young Teachers of USTB(Fundamental Research Funds for the Central Universities),China(No.FRF-IDRY-GD22-002)the Fundamental Research Funds for the Central Universities and the Youth Teacher International Exchange and Growth Program,China(No.QNXM20220009)the National Key R&D Program of China(Nos.2022YFC2905600 and 2022 YFC3004601)the Science,Technology&Innovation Project of Xiongan New Area,China(No.2023XAGG0061)。
文摘Understanding the mechanical properties of the lithologies is crucial to accurately determine the horizontal stress magnitude.To investigate the correlation between the rock mass properties and maximum horizontal stress,the three-dimensional(3D)stress tensors at 89 measuring points determined using an improved overcoring technique in nine mines in China were adopted,a newly defined characteristic parameter C_(ERP)was proposed as an indicator for evaluating the structural properties of rock masses,and a fuzzy relation matrix was established using the information distribution method.The results indicate that both the vertical stress and horizontal stress exhibit a good linear growth relationship with depth.There is no remarkable correlation between the elastic modulus,Poisson's ratio and depth,and the distribution of data points is scattered and messy.Moreover,there is no obvious relationship between the rock quality designation(RQD)and depth.The maximum horizontal stress σ_(H) is a function of rock properties,showing a certain linear relationship with the C_(ERP)at the same depth.In addition,the overall change trend of σ_(H) determined by the established fuzzy identification method is to increase with the increase of C_(ERP).The fuzzy identification method also demonstrates a relatively detailed local relationship betweenσ_H and C_(ERP),and the predicted curve rises in a fluctuating way,which is in accord well with the measured stress data.
基金supported by the National Key R&D Program of China(2022YFF0504400)the National Natural Science Foundation of China(42188101,42274195,42174193)+2 种基金the International Partnership Program Of Chinese Academy of Sciences(Grant No.183311KYSB20200003)the USTC Research Funds of the Double First-Class Initiative(YD2080002013)the Joint Open Fund of Mengcheng National Geophysical Observatory(MENGO-202408).
文摘Statistical characteristics and the classification of the topside ionospheric mid-latitude trough are systemically analyzed,using observations from the Defense Meteorological Satellite Program F18(DMSP-F18)satellite.The data was obtained at an altitude of around 860 km in near polar orbit,throughout 2013.Our study identified the auroral boundary based on the in-situ electron density and electron spectrum,allowing us to precisely determine the location of the mid-latitude trough.This differs from most previous works,which only use Total Electron Content(TEC)or in-situ electron density.In our study,the troughs exhibited a higher occurrence rate in local winter than in summer,and extended to lower latitudes with increasing geomagnetic activity.It was found that the ionospheric mid-latitude trough,which is associated with temperature changes or enhanced ion drift,exhibited distinct characteristics.Specifically,the ionospheric mid-latitude troughs related to electron temperature(Te)peak were located more equatorward of auroral oval boundary in winter than in summer.The ionospheric mid-latitude troughs related to Te-maximum were less frequently observed at 60−70°S magnetic latitude and 90−240°E longitude.Furthermore,the troughs related to ion temperature(Ti)maximums were observed at relatively higher latitudes,occurring more frequently in winter.In addition,the troughs related to ion velocity(Vi)maximums could be observed in all seasons.The troughs with the maximum-Ti and maximum-Vi were located closer to the equatorward boundary of the auroral oval at the nightside,and in both hemispheres.This implies that enhanced ion drift velocity contributes to increased collisional frictional heating and enhanced ion temperatures,resulting in a density depletion within the trough region.
文摘Let(M,g)be a compact Riemann surface with unit area,h a smooth function on M.The Kazdan-Warner problem is that under what kind of conditions on h the equationΔu=8π-8πhe^(u) has a solution.In this survey article,we shall review the development of this problem along the variational method.
基金supported by the National Natural Science Foundation of China(Grant No.12175183)。
文摘Gamma-ray imaging systems are powerful tools in radiographic diagnosis.However,the recorded images suffer from degradations such as noise,blurring,and downsampling,consequently failing to meet high-precision diagnostic requirements.In this paper,we propose a novel single-image super-resolution algorithm to enhance the spatial resolution of gamma-ray imaging systems.A mathematical model of the gamma-ray imaging system is established based on maximum a posteriori estimation.Within the plug-and-play framework,the half-quadratic splitting method is employed to decouple the data fidelit term and the regularization term.An image denoiser using convolutional neural networks is adopted as an implicit image prior,referred to as a deep denoiser prior,eliminating the need to explicitly design a regularization term.Furthermore,the impact of the image boundary condition on reconstruction results is considered,and a method for estimating image boundaries is introduced.The results show that the proposed algorithm can effectively addresses boundary artifacts.By increasing the pixel number of the reconstructed images,the proposed algorithm is capable of recovering more details.Notably,in both simulation and real experiments,the proposed algorithm is demonstrated to achieve subpixel resolution,surpassing the Nyquist sampling limit determined by the camera pixel size.
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 support from National Science and Technology Council,Taiwan under grant numbers NSTC 113-2811-E-019-001 and NSTC 113-2221-E-019-059.
文摘The extended Kalman filter(EKF)is extensively applied in integrated navigation systems that combine the global navigation satellite system(GNSS)and strap-down inertial navigation system(SINS).However,the performance of the EKF can be severely impacted by non-Gaussian noise and measurement noise uncertainties,making it difficult to achieve optimal GNSS/INS integration.Dealing with non-Gaussian noise remains a significant challenge in filter development today.Therefore,the maximum correntropy criterion(MCC)is utilized in EKFs to manage heavytailed measurement noise.However,its capability to handle non-Gaussian process noise and unknown disturbances remains largely unexplored.In this paper,we extend correntropy from using a single kernel to a multi-kernel approach.This leads to the development of a multi-kernel maximum correntropy extended Kalman filter(MKMC-EKF),which is designed to effectively manage multivariate non-Gaussian noise and disturbances.Further,theoretical analysis,including advanced stability proofs,can enhance understanding,while hybrid approaches integrating MKMC-EKF with particle filters may improve performance in nonlinear systems.The MKMC-EKF enhances estimation accuracy using a multi-kernel bandwidth approach.As bandwidth increases,the filter’s sensitivity to non-Gaussian features decreases,and its behavior progressively approximates that of the iterated EKF.The proposed approach for enhancing positioning in navigation is validated through performance evaluations,which demonstrate its practical applications in real-world systems like GPS navigation and measuring radar targets.
文摘The rapid expansion of tobacco farming poses a significant threat to biodiversity in Yunnan Province,China,a region known for its rich biodiversity.This study aims to understand the trade-offs between tobacco farming and higher plant species diversity,and to identify priority counties for conservation.We employed an integrated approach combining species distribution modeling,GIS overlay analysis,and empirical spatial regression to em pirically assess the impact of tobacco farming intensity on biodiversity risk.Our findings reveal a compelling negative spatial correlation between tobacco farming expansion and higher plant species diversity.Specifically,southern counties in Wenshan and Honghe prefectures are major priority areas of conservation that exhibit signif icant spatial correlations between biodiversity risks and high tobacco farming intensity.Quantitatively,at county level,a 1%increase in tobacco farming area corresponds to a 0.094%decrease in endemic higher plant species richness across the entire province.These results underscore the need for targeted and region-specific regulations to mitigate biodiversity loss and promote sustainable development in Yunnan Province.The integrated approach used in this study provides a comprehensive assessment of the tobacco-biodiversity trade-offs,offering actionable insights for policymaking.
文摘Globally bentoite clay has been proposed as an engineered barrier material for safe underground disposal of high-level nuclear waste.Clay has many favorable properties such as high liquid limit,and plastic limit along with other properties which make it the most suitable for this application.In the present study,an attempt has been made to study the behavior of Barmer bentonite under the influence of high temperatures up to 120℃.Properties of barmer bentonite namely,liquid limit,plastic limit,and maximum dry density have been determined after thermal treatment at 25℃,60℃,80℃,100℃ and 120℃.The extensive experimental results indicate that liquid limit and plastic limit show a decreasing trend while maximum dry density increases with an increase in temperature.Liquid limit and plastic limit decrease up to 12%and 11%respectively when the temperature reaches up to 120℃.Maximum dry density increases by 10%due to thermal treatment and optimum water content decreases by up to 4%.Statistical analysis has been carried out to obtain the correlation between temperature and physical properties of Barmer bentonite such as liquid limit,plastic limit,maximum dry density,and optimum water content.The XRD analysis of Barmer bentonite at room temperature and 120℃ shows very small variation in mineralogical composition.Whereas,interlayer distance has been measured and found to be decreasing with an increase in temperature.Further,a comparative analysis shows that the measured properties of studied Barmer bentonite lie in the range of previously measured values of other types of bentonite across the globe.
文摘Amid increasingly frequent military conflicts and explosion events,accurately predicting the dynamic response of reinforced concrete(RC) slabs,key load-bearing components in building structures,is essential for understanding blast-induced damage and enhancing structural protection.However,current approaches predominantly rely on experimental tests,finite element(FE) simulations,and conventional machine learning(ML) techniques,which are o ften costly,inefficie nt,narrowly applicable,and insufficiently accurate.To overcome these challenges,this study aims to optimize ML models,refine architectural designs,and improve model interpretability.A comprehensive dataset comprising 489 samples was constructed by integrating experimental and simulation data from existing literature,incorporating 15 input features and one target variable.Based on this dataset,a novel method,termed MOPSO-TXGBoost,was proposed.Building on XGBoost as a baseline,the method employs multiobjective particle swarm optimization(MOPSO) for hyperparameter tuning,introduces a tri-stream stacking architecture to enhance feature representation,and trains three distinct models to improve generalization performance.A weighted fusion strategy is employed to further enhance the accuracy of predictio n.Additio nally,a model comprehensive evaluation(MCE) index is introduced,which integrates error metrics and fitting performance to facilitate systematic model assessment.Experimental results indicate that,compared with the baseline XGBoost model,the proposed approach reduces prediction error by 61.4% and increases the coefficient of determination(R^(2)) by 0.217.Moreover,it outperforms several mainstream machine learning(ML) algorithms.The findings of this study advance ML-based blast damage prediction and provide theoretical support for safety assessment and protection optimization of RC slab structures.
基金Project(2024ZD1003704)supported by the Deep Earth Probe and Mineral Resources Exploration-National Science and Technology Major Project,ChinaProjects(51834001,52130404)supported by the National Natural Science Foundation of China。
文摘During upward horizontal stratified backfill mining,stable backfill is essential for cap and sill pillar recovery.Currently,the primary method for calculating the required strength of backfill is the generalized three-dimensional(3 D)vertical stress model,which ignores the effect of mine depth,failing to obtain the vertical stress at different positions along stope length.Therefore,this paper develops and validates an improved 3 D model solution through numerical simulation in Rhino-FLAC^(3D),and examines the stress state and stability of backfill under different conditions.The results show that the improved model can accurately calculate the vertical stress at different mine depths and positions along stope length.The error rates between the results of the improved model and numerical simulation are below 4%,indicating high reliability and applicability.The maximum vertical stress(σ_(zz,max))in backfill is positively correlated with the degree of rock-backfill closure,which is enhanced by mine depth and elastic modulus of backfill,while weakened by stope width and inclination,backfill friction angle,and elastic modulus of rock mass.Theσ_(zz,max)reaches its peak when the stope length is 150 m,whileσ_(zz,max)is insensitive to changes in rock-backfill interface parameters.In all cases,the backfill stability can be improved by reducingσ_(zz,max).The results provide theoretical guidance for the backfill strength design and the safe and efficient recovery of ore pillars in deep mining.
