Multiple principal element alloys(MPEAs),also known as high-entropy alloys,have attracted significant attention because of their exceptional mechanical and thermal properties.A critical factor influencing these proper...Multiple principal element alloys(MPEAs),also known as high-entropy alloys,have attracted significant attention because of their exceptional mechanical and thermal properties.A critical factor influencing these properties is suggested to be the presence of chemical short-range order(SRO),characterized by specific atomic arrangements occurring more frequently than in a random distribution.Despite extensive efforts to elucidate SRO,particularly in face-centered cubic(fcc)3d transition metal-based MPEAs,several key aspects remain under debate:the conditions under which SRO forms,the reliability of characterization methods for detecting SRO,and its quantitative impact on mechanical performance.This review summarizes the challenges and unresolved issues in this emerging field,drawing comparisons with well-established research on SRO in binary alloys over the past few decades.Through this cross-system comparison,we aim to provide new insights into SRO from a comprehensive perspective.展开更多
Fracture(fault)reactivation can lead to dynamic geological hazards including earthquakes,rock collapses,landslides,and rock bursts.True triaxial compression tests were conducted to analyze the fracture reactivation pr...Fracture(fault)reactivation can lead to dynamic geological hazards including earthquakes,rock collapses,landslides,and rock bursts.True triaxial compression tests were conducted to analyze the fracture reactivation process under two different orientations of σ_(2),i.e.σ_(2) parallel to the fracture plane(Scheme 2)and σ_(2) cutting through the fracture plane(Scheme 3),under varying σ_(3) from 10 MPa to 40 MPa.The peak or fracture reactivation strength,deformation,failure mode,and post-peak mechanical behavior of intact(Scheme 1)and pre-fractured(Schemes 2 and 3)specimens were also compared.Results show that for intact specimens,the stress remains nearly constant in the residual sliding stage with no stick-slip,and the newly formed fracture surface only propagates along the σ_(2) direction when σ_(3) ranges from 10 MPa to 30 MPa,while it extends along both σ_(2) and σ_(3) directions when σ_(3) increases to 40 MPa;for the pre-fractured specimens,the fractures are usually reactivated under all the σ_(3) levels in Scheme 2,but fracture reactivation only occurs when σ_(3) is greater than 25 MPa in Scheme 3,below which new faulting traversing the original macro fracture occurs.In all the test schemes,both ε_(2) and ε_(3) experience an accumulative process of elongation,after which an abrupt change occurs at the point of the final failure;the degree of this change is dependent on the orientation of the new faulting or the slip direction of the original fracture,and it is generally more than 10 times larger in the slip direction of the original fracture than in the non-slip direction.Besides,the differential stress(peak stress)required for reactivation and the post-peak stress drop increase with increasing σ_(3).Post-peak stress drop and residual strength in Scheme 3 are generally greater than those in Scheme 2 at the same σ_(3) value.Our study clearly shows that intermediate principal stress orientation not only affects the fracture reactivation strength but also influences the slip deformation and failure modes.These new findings facilitate the mitigation of dynamic geological hazards associated with fracture and fault slip.展开更多
The principal stresses will increase or decrease during mining,leading to variations in surrounding rock strength and subsequently an influence on the risk of rockbursts.To address this issue,this study conducted theo...The principal stresses will increase or decrease during mining,leading to variations in surrounding rock strength and subsequently an influence on the risk of rockbursts.To address this issue,this study conducted theoretical analysis,numerical simulation,and field monitoring.A rockburst risk analysis method that integrates dynamic changes in the stress and strength of surrounding rock was proposed and verified in the field.The dynamic changes in maximum(σ_(1))and minimum(σ_(3))principal stresses are represented by the σ_(1) and σ_(3) differentials,respectively.The difference in principal stress differential(DPSD),defined as the difference between σ_(1) and σ_(3),was introduced as a novel indicator for rockburst risk analysis.The findings of this study demonstrate a positive correlation between increases in DPSD and heightened risks of rockbursts,as evidenced by an increase in both the frequency of rockbursts and the occurrence of large-energy microseismic events.Conversely,a decrease in DPSD is associated with a reduction in risk.Specifically,in the W1123 panel of a coal mine susceptible to rockbursts,areas exhibiting higher DPSD values experienced more frequent and severe rockbursts.The DPSD-based analysis aligned well with the observed rockburst occurrences.Subsequent optimization of rockburst prevention measures in areas with elevated DPSD led to a reduction in DPSD.Following these adjustments,the W1123 panel predominantly experienced low-energy microseismic events,with a significant decrease in large-energy microseismic events and no further rockbursts.The DPSD analysis is a valuable tool for evaluating rockburst risk and aiding in prevention,which is of great significance for disaster prevention.展开更多
A series of true triaxial unloading tests are conducted on sandstone specimens with a single structural plane to investigate their mechanical behaviors and failure characteristics under different in situ stress states...A series of true triaxial unloading tests are conducted on sandstone specimens with a single structural plane to investigate their mechanical behaviors and failure characteristics under different in situ stress states.The experimental results indicate that the dip angle of structural plane(θ)and the intermediate principal stress(σ2)have an important influence on the peak strength,cracking mode,and rockburst severity.The peak strength exhibits a first increase and then decrease as a function ofσ2 for a constantθ.However,whenσ2 is constant,the maximum peak strength is obtained atθof 90°,and the minimum peak strength is obtained atθof 30°or 45°.For the case of an inclined structural plane,the crack type at the tips of structural plane transforms from a mix of wing and anti-wing cracks to wing cracks with an increase inσ2,while the crack type around the tips of structural plane is always anti-wing cracks for the vertical structural plane,accompanied by a series of tensile cracks besides.The specimens with structural plane do not undergo slabbing failure regardless ofθ,and always exhibit composite tensile-shear failure whatever theσ2 value is.With an increase inσ2 andθ,the intensity of the rockburst is consistent with the tendency of the peak strength.By analyzing the relationship between the cohesion(c),internal friction angle(φ),andθin sandstone specimens,we incorporateθinto the true triaxial unloading strength criterion,and propose a modified linear Mogi-Coulomb criterion.Moreover,the crack propagation mechanism at the tips of structural plane,and closure degree of the structural plane under true triaxial unloading conditions are also discussed and summarized.This study provides theoretical guidance for stability assessment of surrounding rocks containing geological structures in deep complex stress environments.展开更多
Joint roughness coefficient(JRC)is the most commonly used parameter for quantifying surface roughness of rock discontinuities in practice.The system composed of multiple roughness statistical parameters to measure JRC...Joint roughness coefficient(JRC)is the most commonly used parameter for quantifying surface roughness of rock discontinuities in practice.The system composed of multiple roughness statistical parameters to measure JRC is a nonlinear system with a lot of overlapping information.In this paper,a dataset of eight roughness statistical parameters covering 112 digital joints is established.Then,the principal component analysis method is introduced to extract the significant information,which solves the information overlap problem of roughness characterization.Based on the two principal components of extracted features,the white shark optimizer algorithm was introduced to optimize the extreme gradient boosting model,and a new machine learning(ML)prediction model was established.The prediction accuracy of the new model and the other 17 models was measured using statistical metrics.The results show that the prediction result of the new model is more consistent with the real JRC value,with higher recognition accuracy and generalization ability.展开更多
Restoration of phase aberrations is crucial for addressing atmospheric turbulence in light propagation.Traditional restoration algorithms based on Zernike polynomials(ZPs)often encounter challenges related to high com...Restoration of phase aberrations is crucial for addressing atmospheric turbulence in light propagation.Traditional restoration algorithms based on Zernike polynomials(ZPs)often encounter challenges related to high computational complexity and insufficient capture of high-frequency phase aberration components,so we proposed a Principal-Component-Analysis-based method for representing phase aberrations.This paper discusses the factors influencing the accuracy of restoration,mainly including the sample space size and the sampling interval of D/r_(0),on the basis of characterizing phase aberrations by Principal Components(PCs).The experimental results show that a larger D/r_(0)sampling interval can ensure the generalization ability and robustness of the principal components in the case of a limited amount of original data,which can help to achieve high-precision deployment of the model in practical applications quickly.In the environment with relatively strong turbulence in the test set of D/r_(0)=24,the use of 34 terms of PCs can improve the corrected Strehl ratio(SR)from 0.007 to 0.1585,while the Strehl ratio of the light spot after restoration using 34 terms of ZPs is only 0.0215,demonstrating almost no correction effect.The results indicate that PCs can serve as a better alternative in representing and restoring the characteristics of atmospheric turbulence induced phase aberrations.These findings pave the way to use PCs of phase aberrations with fewer terms than traditional ZPs to achieve data dimensionality reduction,and offer a reference to accelerate and stabilize the model and deep learning based adaptive optics correction.展开更多
The Global Navigation Satellite System(GNSS)is vital for monitoring terrestrial water storage(TWS).However,effectively extracting hydrological load deformation from GNSS observations poses a significant challenge.This...The Global Navigation Satellite System(GNSS)is vital for monitoring terrestrial water storage(TWS).However,effectively extracting hydrological load deformation from GNSS observations poses a significant challenge.This study proposes a novel strategy;the seasonal hydrological load signals are removed from the raw data,and the remaining signals use principal component analysis(PCA).Simulation results from Yunnan Province demonstrate that the spatial distribution of the root mean square error(RMSE)is improved by approximately 15% compared with traditional PCA extraction from raw data.From January 2013 to December 2022,TWS was inverted from 24 GNSS stations in Yunnan Province.The spatial distribution and time series of TWS inverted from GNSS align well with those TWS inferred from the Gravity Recovery and Climate Experiment(GRACE),GRACE Follow-On(GFO),and the Global Land Data Assimilation System(GLDAS)land surface model.However,the amplitude of the GNSS-inverted TWS is slightly higher.Since GNSS ground stations are more sensitive to hydrological load signals,they show correlations with precipitation data that are 8.6%and 6.0%higher than those of GRACE and GLDAS,respectively.In the power spectral density analysis of GRACE/GFO,GLDAS,and GNSS,the signal strength of GNSS is much higher than that of GRACE/GFO and GLDAS in the June and February cycles.These findings suggest that the new data extraction strategy can capture higher frequency hydrological signals in TWS,and GNSS observations can help address limitations in GRACE/GFO observations.This study demonstrates the potential of GNSS TWS in capturing higher-frequency hydrological signals and climate extremes application.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
The basement aquifers in Burkina Faso are increasingly exposed to groundwater pollution,largely due to socio-economic activities and climatic fluctuations,particularly the reduction in rainfall.This pollution makes th...The basement aquifers in Burkina Faso are increasingly exposed to groundwater pollution,largely due to socio-economic activities and climatic fluctuations,particularly the reduction in rainfall.This pollution makes the management and understanding of these aquifers particularly complex.To elucidate the processes controlling this contamination,a methodological approach combining principal component analysis(PCA)and multivariate statistical techniques was adopted.The study analyzed sixteen physicochemical parameters from 58 water samples.The primary objective of this research is to assess groundwater quality and deepen the understanding of the key factors influencing the spatial variation of their chemical composition.The results obtained will contribute to better planning of preservation and sustainable management measures for water resources in Burkina Faso.The results show that three principal components explain 72%of the variance,identifying anthropogenic inputs,with two components affected by mineralization and one by pollution.The study reveals that the groundwater is aggressive and highly corrosive,with calcite saturation.Water-rock interactions appear to be the main mechanisms controlling the hydrochemistry of groundwater,with increasing concentrations of cations and anions as the water travels through percolation pathways.PCA also revealed that the residence time of the water and leaching due to human activities significantly influence water quality,primarily through mineralization processes.These results suggest that rock weathering,coupled with reduced rainfall,constitutes a major vulnerability for aquifer recharge.展开更多
Traditional beamforming techniques may not accurately locate sources in scenarios with both stationary and rotating sound sources.The existence of rotating sound sources can cause blurring in the stationary beamformin...Traditional beamforming techniques may not accurately locate sources in scenarios with both stationary and rotating sound sources.The existence of rotating sound sources can cause blurring in the stationary beamforming map.Current algorithms for separating different moving sound sources have limited effectiveness,leading to significant residual noise,especially when the rotating source is strong enough to mask stationary sources completely.To overcome these challenges,a novel solution utilizing a virtual rotating array in the modal domain combined with robust principal component analysis is proposed to separate sound sources with different rotational speeds.This approach,named Robust Principal Component Analysis in the Modal domain(RPCA-M),investigates the performance of convex nuclear norm and non-convex Schatten-p norm to distinguish stationary and rotating sources.By comparing the errors in Cross-Spectral Matrix(CSM)recovery and acoustic imaging across different algorithms,the effectiveness of RPCA-M in separating stationary and moving sound sources is demonstrated.Importantly,this method effectively separates sound sources,even when there are significant variations in their amplitudes at different rotation speeds.展开更多
Understanding the stress distribution derived from monitoring the principal stress(PS)in slopes is of great importance.In this study,a miniature sensor for quantifying the two-dimensional(2D)PS in landslide model test...Understanding the stress distribution derived from monitoring the principal stress(PS)in slopes is of great importance.In this study,a miniature sensor for quantifying the two-dimensional(2D)PS in landslide model tests is proposed.The fundamental principle and design of the sensor are demonstrated.The sensor comprises three earth pressure gages and one gyroscope,with the utilization of three-dimensional(3D)printing technology.The difficulties of installation location during model preparation and sensor rotation during testing can be effectively overcome using this sensor.Two different arrangements of the sensors are tested in verification tests.Additionally,the application of the sensor in an excavated-induced slope model is tested.The results demonstrate that the sensor exhibits commendable performance and achieves a desirable level of accuracy,with a principal stress angle error of±5°in the verification tests.The stress transformation of the slope model,generated by excavation,is demonstrated in the application test by monitoring the two miniature principal stress(MPS)sensors.The sensor has a significant potential for measuring primary stress in landslide model tests and other geotechnical model experiments.展开更多
This study employs Principal Component Analysis(PCA)and 13 years of SD-WACCM-X model data(2007-2019)to investigate the characteristics and mechanisms of Inter-hemispheric Coupling(IHC)triggered by sudden stratospheric...This study employs Principal Component Analysis(PCA)and 13 years of SD-WACCM-X model data(2007-2019)to investigate the characteristics and mechanisms of Inter-hemispheric Coupling(IHC)triggered by sudden stratospheric warming(SSW)events.IHC in both hemispheres leads to a cold anomaly in the equatorial stratosphere,a warm anomaly in the equatorial mesosphere,and increased temperatures in the mesosphere and lower thermosphere(MLT)region of the summer hemisphere.However,the IHC features during boreal winter period are significantly weaker than during the austral winter period,primarily due to weaker stationary planetary wave activity in the Southern Hemisphere(SH).During the austral winter period,IHC results in a warm anomaly in the polar mesosphere of the SH,which does not occur in the NH during boreal winter period.This study also examines the possible influence of quasi-two-day waves(QTDWs)on IHC.We found that the largest temperature anomaly in the summer polar MLT region is associated with a large wind instability area,and a well-developed critical layer structure of QTDW in January.In contrast,during July,despite favorable conditions for QTDW propagation in the Northern Hemisphere,weaker IHC response is observed,suggesting that IHC features and the relationship with QTDWs during July would be more complex than during January.展开更多
Groundwater is a crucial water source for urban areas in Africa, particularly where surface water is insufficient to meet demand. This study analyses the water quality of five shallow wells (WW1-WW5) in Half-London Wa...Groundwater is a crucial water source for urban areas in Africa, particularly where surface water is insufficient to meet demand. This study analyses the water quality of five shallow wells (WW1-WW5) in Half-London Ward, Tunduma Town, Tanzania, using Principal Component Analysis (PCA) to identify the primary factors influencing groundwater contamination. Monthly samples were collected over 12 months and analysed for physical, chemical, and biological parameters. The PCA revealed between four and six principal components (PCs) for each well, explaining between 84.61% and 92.55% of the total variance in water quality data. In WW1, five PCs captured 87.53% of the variability, with PC1 (33.05%) dominated by pH, EC, TDS, and microbial contamination, suggesting significant influences from surface runoff and pit latrines. In WW2, six PCs explained 92.55% of the variance, with PC1 (36.17%) highlighting the effects of salinity, TDS, and agricultural runoff. WW3 had four PCs explaining 84.61% of the variance, with PC1 (39.63%) showing high contributions from pH, hardness, and salinity, indicating geological influences and contamination from human activities. Similarly, in WW4, six PCs explained 90.83% of the variance, where PC1 (43.53%) revealed contamination from pit latrines and fertilizers. WW5 also had six PCs, accounting for 92.51% of the variance, with PC1 (42.73%) indicating significant contamination from agricultural runoff and pit latrines. The study concludes that groundwater quality in Half-London Ward is primarily affected by a combination of surface runoff, pit latrine contamination, agricultural inputs, and geological factors. The presence of microbial contaminants and elevated nitrate and phosphate levels underscores the need for improved sanitation and sustainable agricultural practices. Recommendations include strengthening sanitation infrastructure, promoting responsible farming techniques, and implementing regular groundwater monitoring to safeguard water resources and public health in the region.展开更多
Room and pillar mining is an underground mining method that utilizes natural pillar support to control rock mass behavior,ensuring mine stability and a safe mine environment.This study specifically documents the influ...Room and pillar mining is an underground mining method that utilizes natural pillar support to control rock mass behavior,ensuring mine stability and a safe mine environment.This study specifically documents the influence of the intermediate principal stress component on the pillar behavior.So far only classical failure criteria ignoring the influence of the intermediate principal stress component were used for underground pillar design.By using an extended Hoek-Brown failure criterion in comparison with the classical Hoek-Brown failure criterion,the influence of the intermediate principal stress component is documented by indicating those areas where the failure criterion is violated.This study demonstrates,that depending on the rock type,the intermediate principal stress component can have a significant effect.Ignoring this influence can lead to uneconomic pillar design and incorrect determination of the factor of safety.展开更多
We study the influence of disorder on the Moore–Read state by principal component analysis(PCA),which is one of the ground state candidates for the 5/2 fractional Hall state.By using PCA,the topological features of t...We study the influence of disorder on the Moore–Read state by principal component analysis(PCA),which is one of the ground state candidates for the 5/2 fractional Hall state.By using PCA,the topological features of the ground state wave functions with different disorder strengths can be distilled.As the disorder strength increases,the Moore–Read state will be destroyed.We explore the phase transition by analyzing the overlaps between the random sample wave functions and the topologically distilled state.The cross-point between the amplitudes of the principal component and its counterpart is the phase transition point.Additionally,the origin of the second component comes from the excited states,which is different from the Laughlin state.展开更多
In order to carry out tensor analysis in a neighborhood of a reference surface,the principal-direction orthogonal basis accompanying with Lame s coefficients or general curvilinear coordinate systems are widely used.A...In order to carry out tensor analysis in a neighborhood of a reference surface,the principal-direction orthogonal basis accompanying with Lame s coefficients or general curvilinear coordinate systems are widely used.A novel kind of field theory termed as the nonholonomic theory of the Principal-Direction Orthonormal Basis(PDOB)is presented systematically in the present paper,in which the formal Christoffel symbols are related directly to the principal and geodesic curvatures with respect to the principal directions of the surface.Furthermore,a systematic and simple way to determine the curvatures of the surface are presented with some examples.It provides a way to recognize qualitatively the bending property of a surface.展开更多
To achieve the loading of the stress path of hard rock,the spherical discrete element model(DEM)and the new flexible membrane technology were utilized to realize the transient loading of three principal stresses with ...To achieve the loading of the stress path of hard rock,the spherical discrete element model(DEM)and the new flexible membrane technology were utilized to realize the transient loading of three principal stresses with arbitrary magnitudes and orientations.Furthermore,based on the deep tunnel of China Jinping Underground Laboratory II(CJPL-II),the deformation and fracture evolution characteristics of deep hard rock induced by excavation stress path were analyzed,and the mechanisms of transient loading-unloading and stress rotation-induced fractures were revealed from a mesoscopic perspective.The results indicated that the stressestrain curve exhibits different trends and degrees of sudden changes when subjected to transient changes in principal stress,accompanied by sudden changes in strain rate.Stress rotation induces spatially directional deformation,resulting in fractures of different degrees and orientations,and increasing the degree of deformation anisotropy.The correlation between the degree of induced fracture and the unloading magnitude of minimum principal stress,as well as its initial level is significant and positive.The process of mechanical response during transient unloading exhibits clear nonlinearity and directivity.After transient unloading,both the minimum principal stress and minimum principal strain rate decrease sharply and then tend to stabilize.This occurs from the edge to the interior and from the direction of the minimum principal stress to the direction of the maximum principal stress on theε1-ε3 plane.Transient unloading will induce a tensile stress wave.The ability to induce fractures due to changes in principal stress magnitude,orientation and rotation paths gradually increases.The analysis indicates a positive correlation between the abrupt change amplitude of strain rate and the maximum unloading magnitude,which is determined by the magnitude and rotation of principal stress.A high tensile strain rate is more likely to induce fractures under low minimum principal stress.展开更多
Ore production is usually affected by multiple influencing inputs at open-pit mines.Nevertheless,the complex nonlinear relationships between these inputs and ore production remain unclear.This becomes even more challe...Ore production is usually affected by multiple influencing inputs at open-pit mines.Nevertheless,the complex nonlinear relationships between these inputs and ore production remain unclear.This becomes even more challenging when training data(e.g.truck haulage information and weather conditions)are massive.In machine learning(ML)algorithms,deep neural network(DNN)is a superior method for processing nonlinear and massive data by adjusting the amount of neurons and hidden layers.This study adopted DNN to forecast ore production using truck haulage information and weather conditions at open-pit mines as training data.Before the prediction models were built,principal component analysis(PCA)was employed to reduce the data dimensionality and eliminate the multicollinearity among highly correlated input variables.To verify the superiority of DNN,three ANNs containing only one hidden layer and six traditional ML models were established as benchmark models.The DNN model with multiple hidden layers performed better than the ANN models with a single hidden layer.The DNN model outperformed the extensively applied benchmark models in predicting ore production.This can provide engineers and researchers with an accurate method to forecast ore production,which helps make sound budgetary decisions and mine planning at open-pit mines.展开更多
The failure modes of rock after roadway excavation are diverse and complex.A comprehensive investigation of the internal stress field and the rotation behavior of the stress axis in roadways is essential for elucidati...The failure modes of rock after roadway excavation are diverse and complex.A comprehensive investigation of the internal stress field and the rotation behavior of the stress axis in roadways is essential for elucidating the mechanism of roadway failure.This study aimed to examine the spatial relationship between roadways and stress fields.The law of stress axis rotation under three-dimensional(3D)stress has been extensively studied.A stress model of roadways in the spatial stress field was established,and the far-field stress state at different spatial positions of the roadways was analyzed.A mechanical model of roadways under a 3D stress state was established using far-field stress solutions as boundary conditions.The distribution of principal stressesσ1,σ2 andσ3 around the roadways and the variation of the stress principal axis were solved.It was found that the stability boundary of the stress principal axis exhibits hysteresis when compared with that of the principal stress magnitudes.A numerical analysis model for spatial roadways was established to validate the distribution of principal stress and the mechanism of principal axis rotation.Research has demonstrated that the stress axis undergoes varying degrees of spatial rotation in different orientations and radial depths.Based on the distribution of principal stress and the rotation law of the stress principal axis,the entire evolution mechanism of the two stress adjustments to form the final failure form after roadway excavation has been revealed.The on-site detection results also corroborate the findings presented in this paper.The results provide a basis for the analysis of the failure mechanism under a 3D stress state.展开更多
The safety and integrity requirements of aerospace composite structures necessitate real-time health monitoring throughout their service life.To this end,distributed optical fiber sensors utilizing back Rayleigh scatt...The safety and integrity requirements of aerospace composite structures necessitate real-time health monitoring throughout their service life.To this end,distributed optical fiber sensors utilizing back Rayleigh scattering have been extensively deployed in structural health monitoring due to their advantages,such as lightweight and ease of embedding.However,identifying the precise location of damage from the optical fiber signals remains a critical challenge.In this paper,a novel approach which namely Modified Sliding Window Principal Component Analysis(MSWPCA)was proposed to facilitate automatic damage identification and localization via distributed optical fiber sensors.The proposed method is able to extract signal characteristics interfered by measurement noise to improve the accuracy of damage detection.Specifically,we applied the MSWPCA method to monitor and analyze the debonding propagation process in honeycomb sandwich panel structures.Our findings demonstrate that the training model exhibits high precision in detecting the location and size of honeycomb debonding,thereby facilitating reliable and efficient online assessment of the structural health state.展开更多
基金supported by the Shanghai Key Laboratory of Material Frontiers Research in Extreme Environments,China(Grant No.22dz2260800)the Shanghai Science and Technology Committee,China(Grant No.22JC1410300).
文摘Multiple principal element alloys(MPEAs),also known as high-entropy alloys,have attracted significant attention because of their exceptional mechanical and thermal properties.A critical factor influencing these properties is suggested to be the presence of chemical short-range order(SRO),characterized by specific atomic arrangements occurring more frequently than in a random distribution.Despite extensive efforts to elucidate SRO,particularly in face-centered cubic(fcc)3d transition metal-based MPEAs,several key aspects remain under debate:the conditions under which SRO forms,the reliability of characterization methods for detecting SRO,and its quantitative impact on mechanical performance.This review summarizes the challenges and unresolved issues in this emerging field,drawing comparisons with well-established research on SRO in binary alloys over the past few decades.Through this cross-system comparison,we aim to provide new insights into SRO from a comprehensive perspective.
基金funding support from the National Nature Science Foundation of China(Grant No.42272334)the National Key Research and Development Program of China(Grant No.2022YFE0137200)the Taishan Scholars Program(Grant No.2019RKB01083).
文摘Fracture(fault)reactivation can lead to dynamic geological hazards including earthquakes,rock collapses,landslides,and rock bursts.True triaxial compression tests were conducted to analyze the fracture reactivation process under two different orientations of σ_(2),i.e.σ_(2) parallel to the fracture plane(Scheme 2)and σ_(2) cutting through the fracture plane(Scheme 3),under varying σ_(3) from 10 MPa to 40 MPa.The peak or fracture reactivation strength,deformation,failure mode,and post-peak mechanical behavior of intact(Scheme 1)and pre-fractured(Schemes 2 and 3)specimens were also compared.Results show that for intact specimens,the stress remains nearly constant in the residual sliding stage with no stick-slip,and the newly formed fracture surface only propagates along the σ_(2) direction when σ_(3) ranges from 10 MPa to 30 MPa,while it extends along both σ_(2) and σ_(3) directions when σ_(3) increases to 40 MPa;for the pre-fractured specimens,the fractures are usually reactivated under all the σ_(3) levels in Scheme 2,but fracture reactivation only occurs when σ_(3) is greater than 25 MPa in Scheme 3,below which new faulting traversing the original macro fracture occurs.In all the test schemes,both ε_(2) and ε_(3) experience an accumulative process of elongation,after which an abrupt change occurs at the point of the final failure;the degree of this change is dependent on the orientation of the new faulting or the slip direction of the original fracture,and it is generally more than 10 times larger in the slip direction of the original fracture than in the non-slip direction.Besides,the differential stress(peak stress)required for reactivation and the post-peak stress drop increase with increasing σ_(3).Post-peak stress drop and residual strength in Scheme 3 are generally greater than those in Scheme 2 at the same σ_(3) value.Our study clearly shows that intermediate principal stress orientation not only affects the fracture reactivation strength but also influences the slip deformation and failure modes.These new findings facilitate the mitigation of dynamic geological hazards associated with fracture and fault slip.
基金support from the National Natural Science Foundation of China(Grant Nos.52374180 and 52327804).
文摘The principal stresses will increase or decrease during mining,leading to variations in surrounding rock strength and subsequently an influence on the risk of rockbursts.To address this issue,this study conducted theoretical analysis,numerical simulation,and field monitoring.A rockburst risk analysis method that integrates dynamic changes in the stress and strength of surrounding rock was proposed and verified in the field.The dynamic changes in maximum(σ_(1))and minimum(σ_(3))principal stresses are represented by the σ_(1) and σ_(3) differentials,respectively.The difference in principal stress differential(DPSD),defined as the difference between σ_(1) and σ_(3),was introduced as a novel indicator for rockburst risk analysis.The findings of this study demonstrate a positive correlation between increases in DPSD and heightened risks of rockbursts,as evidenced by an increase in both the frequency of rockbursts and the occurrence of large-energy microseismic events.Conversely,a decrease in DPSD is associated with a reduction in risk.Specifically,in the W1123 panel of a coal mine susceptible to rockbursts,areas exhibiting higher DPSD values experienced more frequent and severe rockbursts.The DPSD-based analysis aligned well with the observed rockburst occurrences.Subsequent optimization of rockburst prevention measures in areas with elevated DPSD led to a reduction in DPSD.Following these adjustments,the W1123 panel predominantly experienced low-energy microseismic events,with a significant decrease in large-energy microseismic events and no further rockbursts.The DPSD analysis is a valuable tool for evaluating rockburst risk and aiding in prevention,which is of great significance for disaster prevention.
基金supports from the National Natural Science Foundation of China (Grant Nos.52004143 and 52374095)the open fund for the Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines (Grant No.SKLMRDPC21KF06).
文摘A series of true triaxial unloading tests are conducted on sandstone specimens with a single structural plane to investigate their mechanical behaviors and failure characteristics under different in situ stress states.The experimental results indicate that the dip angle of structural plane(θ)and the intermediate principal stress(σ2)have an important influence on the peak strength,cracking mode,and rockburst severity.The peak strength exhibits a first increase and then decrease as a function ofσ2 for a constantθ.However,whenσ2 is constant,the maximum peak strength is obtained atθof 90°,and the minimum peak strength is obtained atθof 30°or 45°.For the case of an inclined structural plane,the crack type at the tips of structural plane transforms from a mix of wing and anti-wing cracks to wing cracks with an increase inσ2,while the crack type around the tips of structural plane is always anti-wing cracks for the vertical structural plane,accompanied by a series of tensile cracks besides.The specimens with structural plane do not undergo slabbing failure regardless ofθ,and always exhibit composite tensile-shear failure whatever theσ2 value is.With an increase inσ2 andθ,the intensity of the rockburst is consistent with the tendency of the peak strength.By analyzing the relationship between the cohesion(c),internal friction angle(φ),andθin sandstone specimens,we incorporateθinto the true triaxial unloading strength criterion,and propose a modified linear Mogi-Coulomb criterion.Moreover,the crack propagation mechanism at the tips of structural plane,and closure degree of the structural plane under true triaxial unloading conditions are also discussed and summarized.This study provides theoretical guidance for stability assessment of surrounding rocks containing geological structures in deep complex stress environments.
基金funding from the National Natural Science Foundation of China (Grant No.42277175)the pilot project of cooperation between the Ministry of Natural Resources and Hunan Province“Research and demonstration of key technologies for comprehensive remote sensing identification of geological hazards in typical regions of Hunan Province” (Grant No.2023ZRBSHZ056)the National Key Research and Development Program of China-2023 Key Special Project (Grant No.2023YFC2907400).
文摘Joint roughness coefficient(JRC)is the most commonly used parameter for quantifying surface roughness of rock discontinuities in practice.The system composed of multiple roughness statistical parameters to measure JRC is a nonlinear system with a lot of overlapping information.In this paper,a dataset of eight roughness statistical parameters covering 112 digital joints is established.Then,the principal component analysis method is introduced to extract the significant information,which solves the information overlap problem of roughness characterization.Based on the two principal components of extracted features,the white shark optimizer algorithm was introduced to optimize the extreme gradient boosting model,and a new machine learning(ML)prediction model was established.The prediction accuracy of the new model and the other 17 models was measured using statistical metrics.The results show that the prediction result of the new model is more consistent with the real JRC value,with higher recognition accuracy and generalization ability.
文摘Restoration of phase aberrations is crucial for addressing atmospheric turbulence in light propagation.Traditional restoration algorithms based on Zernike polynomials(ZPs)often encounter challenges related to high computational complexity and insufficient capture of high-frequency phase aberration components,so we proposed a Principal-Component-Analysis-based method for representing phase aberrations.This paper discusses the factors influencing the accuracy of restoration,mainly including the sample space size and the sampling interval of D/r_(0),on the basis of characterizing phase aberrations by Principal Components(PCs).The experimental results show that a larger D/r_(0)sampling interval can ensure the generalization ability and robustness of the principal components in the case of a limited amount of original data,which can help to achieve high-precision deployment of the model in practical applications quickly.In the environment with relatively strong turbulence in the test set of D/r_(0)=24,the use of 34 terms of PCs can improve the corrected Strehl ratio(SR)from 0.007 to 0.1585,while the Strehl ratio of the light spot after restoration using 34 terms of ZPs is only 0.0215,demonstrating almost no correction effect.The results indicate that PCs can serve as a better alternative in representing and restoring the characteristics of atmospheric turbulence induced phase aberrations.These findings pave the way to use PCs of phase aberrations with fewer terms than traditional ZPs to achieve data dimensionality reduction,and offer a reference to accelerate and stabilize the model and deep learning based adaptive optics correction.
基金supported by the Natural Science Foundation of China(Grant Nos.42374032,42174103,42004073)Provincial Natural Science Foundation(2024JJ8348)the Key Laboratory of Natural Resources Monitoring and Supervision in Southern Hilly Region,Ministry of Natural Resources(NRMSSHR2023Y01)。
文摘The Global Navigation Satellite System(GNSS)is vital for monitoring terrestrial water storage(TWS).However,effectively extracting hydrological load deformation from GNSS observations poses a significant challenge.This study proposes a novel strategy;the seasonal hydrological load signals are removed from the raw data,and the remaining signals use principal component analysis(PCA).Simulation results from Yunnan Province demonstrate that the spatial distribution of the root mean square error(RMSE)is improved by approximately 15% compared with traditional PCA extraction from raw data.From January 2013 to December 2022,TWS was inverted from 24 GNSS stations in Yunnan Province.The spatial distribution and time series of TWS inverted from GNSS align well with those TWS inferred from the Gravity Recovery and Climate Experiment(GRACE),GRACE Follow-On(GFO),and the Global Land Data Assimilation System(GLDAS)land surface model.However,the amplitude of the GNSS-inverted TWS is slightly higher.Since GNSS ground stations are more sensitive to hydrological load signals,they show correlations with precipitation data that are 8.6%and 6.0%higher than those of GRACE and GLDAS,respectively.In the power spectral density analysis of GRACE/GFO,GLDAS,and GNSS,the signal strength of GNSS is much higher than that of GRACE/GFO and GLDAS in the June and February cycles.These findings suggest that the new data extraction strategy can capture higher frequency hydrological signals in TWS,and GNSS observations can help address limitations in GRACE/GFO observations.This study demonstrates the potential of GNSS TWS in capturing higher-frequency hydrological signals and climate extremes application.
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.
文摘The basement aquifers in Burkina Faso are increasingly exposed to groundwater pollution,largely due to socio-economic activities and climatic fluctuations,particularly the reduction in rainfall.This pollution makes the management and understanding of these aquifers particularly complex.To elucidate the processes controlling this contamination,a methodological approach combining principal component analysis(PCA)and multivariate statistical techniques was adopted.The study analyzed sixteen physicochemical parameters from 58 water samples.The primary objective of this research is to assess groundwater quality and deepen the understanding of the key factors influencing the spatial variation of their chemical composition.The results obtained will contribute to better planning of preservation and sustainable management measures for water resources in Burkina Faso.The results show that three principal components explain 72%of the variance,identifying anthropogenic inputs,with two components affected by mineralization and one by pollution.The study reveals that the groundwater is aggressive and highly corrosive,with calcite saturation.Water-rock interactions appear to be the main mechanisms controlling the hydrochemistry of groundwater,with increasing concentrations of cations and anions as the water travels through percolation pathways.PCA also revealed that the residence time of the water and leaching due to human activities significantly influence water quality,primarily through mineralization processes.These results suggest that rock weathering,coupled with reduced rainfall,constitutes a major vulnerability for aquifer recharge.
基金supported by the National Key Research and Development Plan of China(No.2023YFB3406500)the National Natural Science Foundation of China(No.52475132)+2 种基金the Aeronautical Science Foundation of China(No.20200015053001)the Shaanxi Key Research Program Project,China(No.2024GX-ZDCYL-01–16)the Xi’an Key Industrial Chain Technology Research Project,China(No.2023JH-RGZNGG-0033)。
文摘Traditional beamforming techniques may not accurately locate sources in scenarios with both stationary and rotating sound sources.The existence of rotating sound sources can cause blurring in the stationary beamforming map.Current algorithms for separating different moving sound sources have limited effectiveness,leading to significant residual noise,especially when the rotating source is strong enough to mask stationary sources completely.To overcome these challenges,a novel solution utilizing a virtual rotating array in the modal domain combined with robust principal component analysis is proposed to separate sound sources with different rotational speeds.This approach,named Robust Principal Component Analysis in the Modal domain(RPCA-M),investigates the performance of convex nuclear norm and non-convex Schatten-p norm to distinguish stationary and rotating sources.By comparing the errors in Cross-Spectral Matrix(CSM)recovery and acoustic imaging across different algorithms,the effectiveness of RPCA-M in separating stationary and moving sound sources is demonstrated.Importantly,this method effectively separates sound sources,even when there are significant variations in their amplitudes at different rotation speeds.
基金supported by the National Nature Science Foundation of China(Grant No.42207216)the Major Program of the National Natural Science Foundation of China(Grant No.42090055)the National Nature Science Foundation of China(Grant No.42377182).
文摘Understanding the stress distribution derived from monitoring the principal stress(PS)in slopes is of great importance.In this study,a miniature sensor for quantifying the two-dimensional(2D)PS in landslide model tests is proposed.The fundamental principle and design of the sensor are demonstrated.The sensor comprises three earth pressure gages and one gyroscope,with the utilization of three-dimensional(3D)printing technology.The difficulties of installation location during model preparation and sensor rotation during testing can be effectively overcome using this sensor.Two different arrangements of the sensors are tested in verification tests.Additionally,the application of the sensor in an excavated-induced slope model is tested.The results demonstrate that the sensor exhibits commendable performance and achieves a desirable level of accuracy,with a principal stress angle error of±5°in the verification tests.The stress transformation of the slope model,generated by excavation,is demonstrated in the application test by monitoring the two miniature principal stress(MPS)sensors.The sensor has a significant potential for measuring primary stress in landslide model tests and other geotechnical model experiments.
基金supported by the National Natural Science Foundation of China(Grant Numbers 42374195 and 42188101)the fellowship of China National Postdoctoral Program for Innovative Talents(Grant Number BX20230273)+1 种基金the Hubei Provincial Natural Science Foundation of China(Grant Number 2024AFB-097)the Postdoctor Project of Hubei Province(Grant Number 2024HBBHCXA054).
文摘This study employs Principal Component Analysis(PCA)and 13 years of SD-WACCM-X model data(2007-2019)to investigate the characteristics and mechanisms of Inter-hemispheric Coupling(IHC)triggered by sudden stratospheric warming(SSW)events.IHC in both hemispheres leads to a cold anomaly in the equatorial stratosphere,a warm anomaly in the equatorial mesosphere,and increased temperatures in the mesosphere and lower thermosphere(MLT)region of the summer hemisphere.However,the IHC features during boreal winter period are significantly weaker than during the austral winter period,primarily due to weaker stationary planetary wave activity in the Southern Hemisphere(SH).During the austral winter period,IHC results in a warm anomaly in the polar mesosphere of the SH,which does not occur in the NH during boreal winter period.This study also examines the possible influence of quasi-two-day waves(QTDWs)on IHC.We found that the largest temperature anomaly in the summer polar MLT region is associated with a large wind instability area,and a well-developed critical layer structure of QTDW in January.In contrast,during July,despite favorable conditions for QTDW propagation in the Northern Hemisphere,weaker IHC response is observed,suggesting that IHC features and the relationship with QTDWs during July would be more complex than during January.
文摘Groundwater is a crucial water source for urban areas in Africa, particularly where surface water is insufficient to meet demand. This study analyses the water quality of five shallow wells (WW1-WW5) in Half-London Ward, Tunduma Town, Tanzania, using Principal Component Analysis (PCA) to identify the primary factors influencing groundwater contamination. Monthly samples were collected over 12 months and analysed for physical, chemical, and biological parameters. The PCA revealed between four and six principal components (PCs) for each well, explaining between 84.61% and 92.55% of the total variance in water quality data. In WW1, five PCs captured 87.53% of the variability, with PC1 (33.05%) dominated by pH, EC, TDS, and microbial contamination, suggesting significant influences from surface runoff and pit latrines. In WW2, six PCs explained 92.55% of the variance, with PC1 (36.17%) highlighting the effects of salinity, TDS, and agricultural runoff. WW3 had four PCs explaining 84.61% of the variance, with PC1 (39.63%) showing high contributions from pH, hardness, and salinity, indicating geological influences and contamination from human activities. Similarly, in WW4, six PCs explained 90.83% of the variance, where PC1 (43.53%) revealed contamination from pit latrines and fertilizers. WW5 also had six PCs, accounting for 92.51% of the variance, with PC1 (42.73%) indicating significant contamination from agricultural runoff and pit latrines. The study concludes that groundwater quality in Half-London Ward is primarily affected by a combination of surface runoff, pit latrine contamination, agricultural inputs, and geological factors. The presence of microbial contaminants and elevated nitrate and phosphate levels underscores the need for improved sanitation and sustainable agricultural practices. Recommendations include strengthening sanitation infrastructure, promoting responsible farming techniques, and implementing regular groundwater monitoring to safeguard water resources and public health in the region.
文摘Room and pillar mining is an underground mining method that utilizes natural pillar support to control rock mass behavior,ensuring mine stability and a safe mine environment.This study specifically documents the influence of the intermediate principal stress component on the pillar behavior.So far only classical failure criteria ignoring the influence of the intermediate principal stress component were used for underground pillar design.By using an extended Hoek-Brown failure criterion in comparison with the classical Hoek-Brown failure criterion,the influence of the intermediate principal stress component is documented by indicating those areas where the failure criterion is violated.This study demonstrates,that depending on the rock type,the intermediate principal stress component can have a significant effect.Ignoring this influence can lead to uneconomic pillar design and incorrect determination of the factor of safety.
基金supported by the National Natural Science Foundation of China(Grant Nos.12104075 and 12347101).
文摘We study the influence of disorder on the Moore–Read state by principal component analysis(PCA),which is one of the ground state candidates for the 5/2 fractional Hall state.By using PCA,the topological features of the ground state wave functions with different disorder strengths can be distilled.As the disorder strength increases,the Moore–Read state will be destroyed.We explore the phase transition by analyzing the overlaps between the random sample wave functions and the topologically distilled state.The cross-point between the amplitudes of the principal component and its counterpart is the phase transition point.Additionally,the origin of the second component comes from the excited states,which is different from the Laughlin state.
基金Project supported by the National Natural Science Foundation of China(11972120,11472082,12032016)。
文摘In order to carry out tensor analysis in a neighborhood of a reference surface,the principal-direction orthogonal basis accompanying with Lame s coefficients or general curvilinear coordinate systems are widely used.A novel kind of field theory termed as the nonholonomic theory of the Principal-Direction Orthonormal Basis(PDOB)is presented systematically in the present paper,in which the formal Christoffel symbols are related directly to the principal and geodesic curvatures with respect to the principal directions of the surface.Furthermore,a systematic and simple way to determine the curvatures of the surface are presented with some examples.It provides a way to recognize qualitatively the bending property of a surface.
基金the financial support from the National Natural Science Foundation of China(Grant No.51839003)Liaoning Revitalization Talents Program(Grant No.XLYCYSZX 1902)Hubei Key Laboratory for Efficient Utilization and Agglomeration of Metallurgic Mineral Resources(Grant No.2023zy002).
文摘To achieve the loading of the stress path of hard rock,the spherical discrete element model(DEM)and the new flexible membrane technology were utilized to realize the transient loading of three principal stresses with arbitrary magnitudes and orientations.Furthermore,based on the deep tunnel of China Jinping Underground Laboratory II(CJPL-II),the deformation and fracture evolution characteristics of deep hard rock induced by excavation stress path were analyzed,and the mechanisms of transient loading-unloading and stress rotation-induced fractures were revealed from a mesoscopic perspective.The results indicated that the stressestrain curve exhibits different trends and degrees of sudden changes when subjected to transient changes in principal stress,accompanied by sudden changes in strain rate.Stress rotation induces spatially directional deformation,resulting in fractures of different degrees and orientations,and increasing the degree of deformation anisotropy.The correlation between the degree of induced fracture and the unloading magnitude of minimum principal stress,as well as its initial level is significant and positive.The process of mechanical response during transient unloading exhibits clear nonlinearity and directivity.After transient unloading,both the minimum principal stress and minimum principal strain rate decrease sharply and then tend to stabilize.This occurs from the edge to the interior and from the direction of the minimum principal stress to the direction of the maximum principal stress on theε1-ε3 plane.Transient unloading will induce a tensile stress wave.The ability to induce fractures due to changes in principal stress magnitude,orientation and rotation paths gradually increases.The analysis indicates a positive correlation between the abrupt change amplitude of strain rate and the maximum unloading magnitude,which is determined by the magnitude and rotation of principal stress.A high tensile strain rate is more likely to induce fractures under low minimum principal stress.
基金This work was supported by the Pilot Seed Grant(Grant No.RES0049944)the Collaborative Research Project(Grant No.RES0043251)from the University of Alberta.
文摘Ore production is usually affected by multiple influencing inputs at open-pit mines.Nevertheless,the complex nonlinear relationships between these inputs and ore production remain unclear.This becomes even more challenging when training data(e.g.truck haulage information and weather conditions)are massive.In machine learning(ML)algorithms,deep neural network(DNN)is a superior method for processing nonlinear and massive data by adjusting the amount of neurons and hidden layers.This study adopted DNN to forecast ore production using truck haulage information and weather conditions at open-pit mines as training data.Before the prediction models were built,principal component analysis(PCA)was employed to reduce the data dimensionality and eliminate the multicollinearity among highly correlated input variables.To verify the superiority of DNN,three ANNs containing only one hidden layer and six traditional ML models were established as benchmark models.The DNN model with multiple hidden layers performed better than the ANN models with a single hidden layer.The DNN model outperformed the extensively applied benchmark models in predicting ore production.This can provide engineers and researchers with an accurate method to forecast ore production,which helps make sound budgetary decisions and mine planning at open-pit mines.
基金supported by the National Natural Science Foundation of China (Grant No.52225404)Beijing Outstanding Young Scientist Program (Grant No.BJJWZYJH01201911413037)Central University Excellent Youth Team Funding Project (Grant No.2023YQTD01).
文摘The failure modes of rock after roadway excavation are diverse and complex.A comprehensive investigation of the internal stress field and the rotation behavior of the stress axis in roadways is essential for elucidating the mechanism of roadway failure.This study aimed to examine the spatial relationship between roadways and stress fields.The law of stress axis rotation under three-dimensional(3D)stress has been extensively studied.A stress model of roadways in the spatial stress field was established,and the far-field stress state at different spatial positions of the roadways was analyzed.A mechanical model of roadways under a 3D stress state was established using far-field stress solutions as boundary conditions.The distribution of principal stressesσ1,σ2 andσ3 around the roadways and the variation of the stress principal axis were solved.It was found that the stability boundary of the stress principal axis exhibits hysteresis when compared with that of the principal stress magnitudes.A numerical analysis model for spatial roadways was established to validate the distribution of principal stress and the mechanism of principal axis rotation.Research has demonstrated that the stress axis undergoes varying degrees of spatial rotation in different orientations and radial depths.Based on the distribution of principal stress and the rotation law of the stress principal axis,the entire evolution mechanism of the two stress adjustments to form the final failure form after roadway excavation has been revealed.The on-site detection results also corroborate the findings presented in this paper.The results provide a basis for the analysis of the failure mechanism under a 3D stress state.
基金supported by the National Key Research and Development Program of China(No.2018YFA0702800)the National Natural Science Foundation of China(No.12072056)supported by National Defense Fundamental Scientific Research Project(XXXX2018204BXXX).
文摘The safety and integrity requirements of aerospace composite structures necessitate real-time health monitoring throughout their service life.To this end,distributed optical fiber sensors utilizing back Rayleigh scattering have been extensively deployed in structural health monitoring due to their advantages,such as lightweight and ease of embedding.However,identifying the precise location of damage from the optical fiber signals remains a critical challenge.In this paper,a novel approach which namely Modified Sliding Window Principal Component Analysis(MSWPCA)was proposed to facilitate automatic damage identification and localization via distributed optical fiber sensors.The proposed method is able to extract signal characteristics interfered by measurement noise to improve the accuracy of damage detection.Specifically,we applied the MSWPCA method to monitor and analyze the debonding propagation process in honeycomb sandwich panel structures.Our findings demonstrate that the training model exhibits high precision in detecting the location and size of honeycomb debonding,thereby facilitating reliable and efficient online assessment of the structural health state.
