Porosity is an important attribute for evaluating the petrophysical properties of reservoirs, and has guiding significance for the exploration and development of oil and gas. The seismic inversion is a key method for ...Porosity is an important attribute for evaluating the petrophysical properties of reservoirs, and has guiding significance for the exploration and development of oil and gas. The seismic inversion is a key method for comprehensively obtaining the porosity. Deep learning methods provide an intelligent approach to suppress the ambiguity of the conventional inversion method. However, under the trace-bytrace inversion strategy, there is a lack of constraints from geological structural information, resulting in poor lateral continuity of prediction results. In addition, the heterogeneity and the sedimentary variability of subsurface media also lead to uncertainty in intelligent prediction. To achieve fine prediction of porosity, we consider the lateral continuity and variability and propose an improved structural modeling deep learning porosity prediction method. First, we combine well data, waveform attributes, and structural information as constraints to model geophysical parameters, constructing a high-quality training dataset with sedimentary facies-controlled significance. Subsequently, we introduce a gated axial attention mechanism to enhance the features of dataset and design a bidirectional closed-loop network system constrained by inversion and forward processes. The constraint coefficient is adaptively adjusted by the petrophysical information contained between the porosity and impedance in the study area. We demonstrate the effectiveness of the adaptive coefficient through numerical experiments.Finally, we compare the performance differences between the proposed method and conventional deep learning methods using data from two study areas. The proposed method achieves better consistency with the logging porosity, demonstrating the superiority of the proposed method.展开更多
Controversy is ongoing regarding the relationship between ore formation and the structural evolution of the Hadamengou gold deposit.To address this issue,we conducted a comprehensive investigation of mineralization-re...Controversy is ongoing regarding the relationship between ore formation and the structural evolution of the Hadamengou gold deposit.To address this issue,we conducted a comprehensive investigation of mineralization-related structures,geochronology and Fe isotopes.From the perspective of spatial evolution,hydrothermal fluids originating from the Shadegai and Xishadegai plutons have extracted accumulated ore-forming elements from the Wulashan Group(Ar2WL)and then evolved,initiating at Exploration Line 11 and migrating eastwards and westwards along the EW-trending thrust fault system to form orebodies.From the temporal evolution standpoint,the Wulashan Group(Ar_(2)WL)experienced diagenesis(2591.00 Ma to 2204.00 Ma)and metamorphism(2074.00 Ma to 1625.00 Ma)from late Neoarchean to early Paleoproterozoic,when ore-forming materials were initially accumulated;in the early Paleozoic(440.71 Ma to 425.00 Ma),the collision led to the formation of early-stage EW-trending imbricated thrust faults,which established a fundamental structural framework for the orefield and further accumulated ore-forming materials;from the late Paleozoic to the Mesozoic,multiple subsequent episodes of regional tectonic-magmatic-hydrothermal events have superimposed,modified and reactivated the thrust fault system.Notably,the Triassic period,particularly between 245.00 Ma and 217.90 Ma,is considered to be a primary ore-forming stage.In summary,the intricate relationship between ore-formation and structural evolution has been fundamentally elucidated.展开更多
Dentistry is a profession with a high prevalence of work-related musculoskeletal disorders(WMSDs),with symptoms often appearing very early in one’s career[1].WMSDs are conditions affecting the muscles,bones,and nervo...Dentistry is a profession with a high prevalence of work-related musculoskeletal disorders(WMSDs),with symptoms often appearing very early in one’s career[1].WMSDs are conditions affecting the muscles,bones,and nervous system due to occupational factors.In 2002,the International Labor Organization included musculoskeletal diseases in the International List of Occupational Diseases.China’s recently updated Classification and Catalog of Occupational Diseases has introduced two new categories of occupational illnesses,including occupational musculoskeletal disorders.WMSDs significantly impact the health and work of dentists,reducing their quality of life and causing economic losses.These disorders are multifactorial in nature,influenced by personal,psychosocial,biomechanical,and environmental factors.Dentists frequently maintain static or awkward postures during procedures,which leads to musculoskeletal strain and discomfort;additionally,long working hours contribute to psychological stress,further increasing the risk of WMSDs[2].展开更多
Taking the second member of the Xujiahe Formation of the Upper Triassic in the Xinchang structural belt as an example,based on data such as logging,production,seismic interpretation and test,a systematic analysis was ...Taking the second member of the Xujiahe Formation of the Upper Triassic in the Xinchang structural belt as an example,based on data such as logging,production,seismic interpretation and test,a systematic analysis was conducted on the structural characteristics and evolution,reservoir diagenesis and densification processes,and types and stages of faults/fractures,and revealing the multi-stage and multi-factor dynamic coupled enrichment mechanisms of tight gas reservoirs.(1)In the early Yanshan period,the paleo-structural traps were formed with low-medium maturity hydrocarbons accumulating in structural highs driven by buoyancy since reservoirs were not fully densified in this stage,demonstrating paleo-structure control on traps and early hydrocarbon accumulation.(2)In the middle-late Yanshan period,the source rocks became mature to generate and expel a large quantity of hydrocarbons.Grain size and type of sandstone controlled the time of reservoir densification,which restricted the scale of hydrocarbon charging,allowing for only a small-scale migration through sand bodies near the fault/fracture or less-densified matrix reservoirs.(3)During the Himalayan period,the source rocks reached overmaturity,and the residual oil cracking gas was efficiently transported along the late-stage faults/fractures.Wells with high production capacity were mainly located in Type I and II fault/fracture zones comprising the late-stage north-south trending fourth-order faults and the late-stage fractures.The productivity of the wells was controlled by the transformation of the late-stage faults/fractures.(4)The Xinchang structural belt underwent three stages of tectonic evolution,two stages of reservoir formation,and three stages of fault/fractures development.Hydrocarbons mainly accumulated in the paleo-structure highs.After reservoir densification and late fault/fracture adjustment,a complex gas-water distribution pattern was formed.Thus,it is summarized as the model of“near-source and low-abundance hydrocarbon charging in the early stage,and differential enrichment of natural gas under the joint control of fault-fold-fracture complex,high-quality reservoirs and structural highs in the late stage”.Faults/fractures with well-coupled fault-fold-fracture-pore are favorable exploration targets with high exploration effectiveness.展开更多
The utilization of iron coke provides a green pathway for low-carbon ironmaking.To uncover the influence mechanism of iron ore on the behavior and kinetics of iron coke gasification,the effect of iron ore on the micro...The utilization of iron coke provides a green pathway for low-carbon ironmaking.To uncover the influence mechanism of iron ore on the behavior and kinetics of iron coke gasification,the effect of iron ore on the microstructure of iron coke was investigated.Furthermore,a comparative study of the gasification reactions between iron coke and coke was conducted through non-isothermal thermogravimetric method.The findings indicate that compared to coke,iron coke exhibits an augmentation in micropores and specific surface area,and the micropores further extend and interconnect.This provides more adsorption sites for CO_(2) molecules during the gasification process,resulting in a reduction in the initial gasification temperature of iron coke.Accelerating the heating rate in non-isothermal gasification can enhance the reactivity of iron coke.The metallic iron reduced from iron ore is embedded in the carbon matrix,reducing the orderliness of the carbon structure,which is primarily responsible for the heightened reactivity of the carbon atoms.The kinetic study indicates that the random pore model can effectively represent the gasification process of iron coke due to its rich pore structure.Moreover,as the proportion of iron ore increases,the activation energy for the carbon gasification gradually decreases,from 246.2 kJ/mol for coke to 192.5 kJ/mol for iron coke 15wt%.展开更多
Existing lithospheric velocity models exhibit similar structures typically associated with the first-order tectonic features,with dissimilarities due to different data and methods used in model generation.The quantifi...Existing lithospheric velocity models exhibit similar structures typically associated with the first-order tectonic features,with dissimilarities due to different data and methods used in model generation.The quantification of model structural similarity can help in interpreting the geophysical properties of Earth's interior and establishing unified models crucial in natural hazard assessment and resource exploration.Here we employ the complex wavelet structural similarity index measure(CW-SSIM)active in computer image processing to analyze the structural similarity of four lithospheric velocity models of Chinese mainland published in the past decade.We take advantage of this method in its multiscale definition and insensitivity to slight geometrical distortion like translation and scaling,which is particularly crucial in the structural similarity analysis of velocity models accounting for uncertainty and resolution.Our results show that the CW-SSIM values vary in different model pairs,horizontal locations,and depths.While variations in the inter-model CW-SSIM are partly owing to different databases in the model generation,the difference of tomography methods may significantly impact the similar structural features of models,such as the low similarities between the full-wave based FWEA18 and other three models in northeastern China.We finally suggest potential solutions for the next generation of tomographic modeling in different areas according to corresponding structural similarities of existing models.展开更多
Structural Health Monitoring(SHM)systems have become a crucial tool for the operational management of long tunnels.For immersed tunnels exposed to both traffic loads and the effects of the marine environment,efficient...Structural Health Monitoring(SHM)systems have become a crucial tool for the operational management of long tunnels.For immersed tunnels exposed to both traffic loads and the effects of the marine environment,efficiently identifying abnormal conditions from the extensive unannotated SHM data presents a significant challenge.This study proposed amodel-based approach for anomaly detection and conducted validation and comparative analysis of two distinct temporal predictive models using SHM data from a real immersed tunnel.Firstly,a dynamic predictive model-based anomaly detectionmethod is proposed,which utilizes a rolling time window for modeling to achieve dynamic prediction.Leveraging the assumption of temporal data similarity,an interval prediction value deviation was employed to determine the abnormality of the data.Subsequently,dynamic predictive models were constructed based on the Autoregressive Integrated Moving Average(ARIMA)and Long Short-Term Memory(LSTM)models.The hyperparameters of these models were optimized and selected using monitoring data from the immersed tunnel,yielding viable static and dynamic predictive models.Finally,the models were applied within the same segment of SHM data,to validate the effectiveness of the anomaly detection approach based on dynamic predictive modeling.A detailed comparative analysis discusses the discrepancies in temporal anomaly detection between the ARIMA-and LSTM-based models.The results demonstrated that the dynamic predictive modelbased anomaly detection approach was effective for dealing with unannotated SHM data.In a comparison between ARIMA and LSTM,it was found that ARIMA demonstrated higher modeling efficiency,rendering it suitable for short-term predictions.In contrast,the LSTM model exhibited greater capacity to capture long-term performance trends and enhanced early warning capabilities,thereby resulting in superior overall performance.展开更多
Structural planes play an important role in controlling the stability of rock engineering,and the influence of structural planes should be considered in the design and construction process of rock engineering.In this ...Structural planes play an important role in controlling the stability of rock engineering,and the influence of structural planes should be considered in the design and construction process of rock engineering.In this paper,mechanical properties,constitutive theory,and numerical application of structural plane are studied by a combination method of laboratory tests,theoretical derivation,and program development.The test results reveal the change laws of various mechanical parameters under different roughness and normal stress.At the pre-peak stage,a non-stationary model of shear stiffness is established,and threedimensional empirical prediction models for initial shear stiffness and residual stage roughness are proposed.The nonlinear constitutive models are established based on elasto-plastic mechanics,and the algorithms of the models are developed based on the return mapping algorithm.According to a large number of statistical analysis results,empirical prediction models are proposed for model parameters expressed by structural plane characteristic parameters.Finally,the discrete element method(DEM)is chosen to embed the constitutive models for practical application.The running programs of the constitutive models have been compiled into the discrete element model library.The comparison results between the proposed model and the Mohr-Coulomb slip model show that the proposed model can better describe nonlinear changes at different stages,and the predicted shear strength,peak strain and shear stiffness are closer to the test results.The research results of the paper are conducive to the accurate evaluation of structural plane in rock engineering.展开更多
Coal has a highly complex chemical structure,similar to polymers,coal is a macromolecular structure composed of a large number of“similar compounds”,which is called the basic structural unit.Understanding coal struc...Coal has a highly complex chemical structure,similar to polymers,coal is a macromolecular structure composed of a large number of“similar compounds”,which is called the basic structural unit.Understanding coal structure is the basis of its transformation and utilization.Shendong(SD)coal was analyzed by FTIR,XRD,XPS,and NMR.The results show that SD coal normalized structure formula is C_(100)H_(68.5)O_(35.7)N_(1.2)S_(0.2)and the average number of aromatic rings is 1.98.-CH_(2)-content accounts for about 82%in aliphatic CeH region,and the ratio of ether bond CeO,aromatic ether C-O and C=O is about 2:1:11 in oxygen-containing functional group region.The d_(002),L_(C),L_(a)and N_(C)of S_(D)coal microcrystalline structure parameters are 0.1832 nm,1.4688 nm,2.0852 nm and 9.017,respectively.Aromatic carbon and aliphatic carbon ratios of SD coal are 55.67%and 29.97%,aromatic cluster size and average methylene chain length are 0.224 and 1.817.Based on these structural parameters,molecular model of SD coal was constructed with^(13)C SSNMR experimental spectra as a reference.The model was constructed with an atom composition of C_(214)H_(214)O_(49)N_(2)S.展开更多
This study introduces an innovative“Big Model”strategy to enhance Bridge Structural Health Monitoring(SHM)using a Convolutional Neural Network(CNN),time-frequency analysis,and fine element analysis.Leveraging ensemb...This study introduces an innovative“Big Model”strategy to enhance Bridge Structural Health Monitoring(SHM)using a Convolutional Neural Network(CNN),time-frequency analysis,and fine element analysis.Leveraging ensemble methods,collaborative learning,and distributed computing,the approach effectively manages the complexity and scale of large-scale bridge data.The CNN employs transfer learning,fine-tuning,and continuous monitoring to optimize models for adaptive and accurate structural health assessments,focusing on extracting meaningful features through time-frequency analysis.By integrating Finite Element Analysis,time-frequency analysis,and CNNs,the strategy provides a comprehensive understanding of bridge health.Utilizing diverse sensor data,sophisticated feature extraction,and advanced CNN architecture,the model is optimized through rigorous preprocessing and hyperparameter tuning.This approach significantly enhances the ability to make accurate predictions,monitor structural health,and support proactive maintenance practices,thereby ensuring the safety and longevity of critical infrastructure.展开更多
To ensure the operational safety of railways in the landslide-prone areas of mountainous regions,a large-scale model test and numerical simulation were conducted to study the bending moment distribution,internal force...To ensure the operational safety of railways in the landslide-prone areas of mountainous regions,a large-scale model test and numerical simulation were conducted to study the bending moment distribution,internal force distribution,deformation development,and crack propagation characteristics of a framed anti-sliding structure(FAS)under landslide thrust up to the point of failure.Results show that the maximum bending moment and its increase rate in the fore pile are greater than those in the rear pile,with the maximum bending moment of the fore pile approximately 1.1 times that of the rear pile.When the FAS fails,the displacement at the top of the fore pile is significantly greater,about 1.27 times that of the rear pile in the experiment.Major cracks develop at locations corresponding to the peak bending moments.Small transverse cracks initially appear on the upper surface at the intersection between the primary beam and rear pile and then spread to the side of the structure.At the failure stage,major cracks are observed at the pil-beam intersections and near the anchor points.Strengthening flexural stiffness at intersections where major cracks occur can improve the overall thrust-deformation coordination of the FAS,thereby maximizing its performance.展开更多
The acetylpolyamine oxidase(APAO),spermine oxidase(SMO),and spermidine/spermine N1-acetyltransferase(SSAT)are pivotal enzymes in polyamine metabolism,exerting direct influence on polyamine homeostasis regulation.Dysfu...The acetylpolyamine oxidase(APAO),spermine oxidase(SMO),and spermidine/spermine N1-acetyltransferase(SSAT)are pivotal enzymes in polyamine metabolism,exerting direct influence on polyamine homeostasis regulation.Dysfunctions in these enzymes are intricately linked to inflammatory diseases and cancers.Establishing their three-dimensional structures is essential for exploring enzymatic catalytic mechanisms and designing inhibitors at the atomic level.This article primarily assesses the precision of AlphaFold2 and molecular dynamics simulations in determining the three-dimensional structures of these enzymes,utilizing protein conformation rationality assessment,residue correlation matrix,and other techniques.This provides robust models for subsequent polyamine catabolic metabolism calculations and offers valuable insights for modeling proteins that have yet to acquire crystal structures.展开更多
BACKGROUND Depression,non-suicidal self-injury(NSSI),and suicide attempts(SA)often co-occur during adolescence and are associated with long-term adverse health outcomes.Unfortunately,neural mechanisms underlying self-...BACKGROUND Depression,non-suicidal self-injury(NSSI),and suicide attempts(SA)often co-occur during adolescence and are associated with long-term adverse health outcomes.Unfortunately,neural mechanisms underlying self-injury and SA are poorly understood in depressed adolescents but likely relate to the structural abnormalities in brain regions.AIM To investigate structural network communication within large-scale brain networks in adolescents with depression.METHODS We constructed five distinct network communication models to evaluate structural network efficiency at the whole-brain level in adolescents with depression.Diffusion magnetic resonance imaging data were acquired from 32 healthy controls and 85 depressed adolescents,including 17 depressed adolescents without SA or NSSI(major depressive disorder group),27 depressed adolescents with NSSI but no SA(NSSI group),and 41 depressed adolescents with SA and NSSI(NSSI+SA group).RESULTS Significant differences in structural network communication were observed across the four groups,involving spatially widespread brain regions,particularly encompassing cortico-cortical connections(e.g.,dorsal posterior cingulate gyrus and the right ventral posterior cingulate gyrus;connections based on precentral gyrus)and cortico-subcortical circuits(e.g.,the nucleus accumbens-frontal circuit).In addition,we examined whether compromised communication efficiency was linked to clinical symptoms in the depressed adolescents.We observed significant correlations between network communication efficiencies and clinical scale scores derived from depressed adolescents with NSSI and SA.CONCLUSION This study provides evidence of structural network communication differences in depressed adolescents with NSSI and SA,highlighting impaired neuroanatomical communication efficiency as a potential contributor to their symptoms.These findings offer new insights into the pathophysiological mechanisms underlying the comorbidity of NSSI and SA in adolescent depression.展开更多
Beach groynes are structures for erosion protection along sandy coasts near inlets and can reduce the coastal erosion substantially,but open groynes cannot stop erosion completely because sand can be removed from the ...Beach groynes are structures for erosion protection along sandy coasts near inlets and can reduce the coastal erosion substantially,but open groynes cannot stop erosion completely because sand can be removed from the groyne compartments by cross-shore processes.Beach groynes should be designed with sufficient bypassing of sand to minimise erosion.Regular beach maintenance is required to keep a sufficient beach width for recreational purposes.The effectiveness of groyne compartments can be significantly improved by using T-head groynes or by using a submerged sill or breakwater in between the groynes.An economic evaluation shows that the beach maintenance costs over 50 years may be substantially higher than the construction costs of a submerged breakwater.An important parameter to be studied is the longshore transport,which requires detailed information of the wave climate,preferably based on measured data(offshore buoys)in combination with deep water wave modelling.Various models have been used to determine the net longshore sand transport and coastline changes.The design of groynes to reduce coastal erosion is illustrated by three field cases(Atlantic coast near Soulac,France;Lagos coast,Nigeria and Black Sea coast,Romania).These example cases show that beach groynes are effective structures,but sufficient bypassing of longshore sand transport is essential to minimise erosion.Regular beach fills in the groyne compartments may be required at high-energy(exposed)coasts.A submerged or emerged breakwater can be built between the groynes to protect the beach in the groyne compartments against erosion by cross-shore processes.展开更多
In the structural reliability analysis,the first-order reliability method(FORM)often yields significant errors when addressing nonlinear problems.Although the second-order reliability method(SORM)can provide higher ac...In the structural reliability analysis,the first-order reliability method(FORM)often yields significant errors when addressing nonlinear problems.Although the second-order reliability method(SORM)can provide higher accuracy,the additional computation of the Hessian matrix leads to lower computational efficiency.Additionally,when the dimensionality of the random variables is high,the approximation formula of SORM can result in larger errors.To address these issues,a structural reliability analysis method based on Kriging and spherical cap area integral is proposed.Firstly,this method integrates FORM with the quasi-Newton algorithm Broyden-Fletcher-Goldfarb-Shanno(BFGS),trains the Kriging model by using sample points from the algorithm’s iteration process,and combines the Kriging model with gradient information to approximate the Hessian matrix.Then,the failure surface is approximated as a rotating paraboloid,utilizing the spherical cap to replace the complex surface.For the n-dimensional case,the hyperspherical cap area expression is combined with the integral method to calculate the failure probability.Finally,the method is validated through three examples,demonstrating improved computational accuracy and efficiency compared to traditional methods.展开更多
Accurate prediction of coal reservoir permeability is crucial for engineering applications,including coal mining,coalbed methane(CBM)extraction,and carbon storage in deep unmineable coal seams.Owing to the inherent he...Accurate prediction of coal reservoir permeability is crucial for engineering applications,including coal mining,coalbed methane(CBM)extraction,and carbon storage in deep unmineable coal seams.Owing to the inherent heterogeneity and complex internal structure of coal,a well-established method for predicting permeability based on microscopic fracture structures remains elusive.This paper presents a novel integrated approach that leverages the intrinsic relationship between microscopic fracture structure and permeability to construct a predictive model for coal permeability.The proposed framework encompasses data generation through the integration of three-dimensional(3D)digital core analysis and numerical simulations,followed by data-driven modeling via machine learning(ML)techniques.Key data-driven strategies,including feature selection and hyperparameter tuning,are employed to improve model performance.We propose and evaluate twelve data-driven models,including multilayer perceptron(MLP),random forest(RF),and hybrid methods.The results demonstrate that the ML model based on the RF algorithm achieves the highest accuracy and best generalization capability in predicting permeability.This method enables rapid estimation of coal permeability by inputting two-dimensional(2D)computed tomography images or parameters of the microscopic fracture structure,thereby providing an accurate and efficient means of permeability prediction.展开更多
Machine learning(ML)has emerged as a powerful tool for predicting polymer properties,including glass transition temperature(Tg),which is a critical factor influencing polymer applications.In this study,a dataset of po...Machine learning(ML)has emerged as a powerful tool for predicting polymer properties,including glass transition temperature(Tg),which is a critical factor influencing polymer applications.In this study,a dataset of polymer structures and their Tg values were created and represented as adjacency matrices based on molecular graph theory.Four key structural descriptors,flexibility,side chain occupancy length,polarity,and hydrogen bonding capacity,were extracted and used as inputs for ML models:Extra Trees(ET),Random Forest(RF),Gaussian Process Regression(GPR),and Gradient Boosting(GB).Among these,ET and GPR achieved the highest predictive performance,with R2 values of 0.97,and mean absolute errors(MAE)of approximately 7–7.5 K.The use of these extracted features significantly improved the prediction accuracy compared to previous studies.Feature importance analysis revealed that flexibility had the strongest influence on Tg,followed by side-chain occupancy length,hydrogen bonding,and polarity.This work demonstrates the potential of data-driven approaches in polymer science,providing a fast and reliable method for Tg prediction that does not require experimental inputs.展开更多
Existing sandstone rock structure evaluation methods rely on visual inspection,with low efficiency,semi-quantitative analysis of roundness,and inability to perform classified statistics in particle size analysis.This ...Existing sandstone rock structure evaluation methods rely on visual inspection,with low efficiency,semi-quantitative analysis of roundness,and inability to perform classified statistics in particle size analysis.This study presents an intelligent evaluation method for sandstone rock structure based on the Segment Anything Model(SAM).By developing a lightweight SAM fine-tuning method with rank-decomposition matrix adapters,a multispectral rock particle segmentation model named CoreSAM is constructed,which achieves rock particle edge extraction and type identification.Building upon this,we propose a comprehensive quantitative evaluation system for rock structure,assessing parameters including particle size,sorting,roundness,particle contact and cementation types.The experimental results demonstrate that CoreSAM outperforms existing methods in rock particle segmentation accuracy while showing excellent generalization across different image types such as CT scans and core photographs.The proposed method enables full-sample,classified particle size analysis and quantitative characterization of parameters like roundness,advancing reservoir evaluation towards more precise,quantitative,intuitive,and comprehensive development.展开更多
Structure-type rockbursts frequently occur in deep tunnels,with structural planes and stress conditions being critical factors in their formation.In this study,we utilized specially developed analogous materials that ...Structure-type rockbursts frequently occur in deep tunnels,with structural planes and stress conditions being critical factors in their formation.In this study,we utilized specially developed analogous materials that exhibit the high brittleness and strength characteristics of deep hard rock to construct physical models representing different types of structural planes,including composite,exposed,non-exposed,and throughgoing structural planes.Physical simulation experiments were conducted on structuretype rockbursts in deep horseshoe-shaped tunnels,focusing on strain differentiation characteristics,critical triggering conditions,critical crack opening displacement,the incubation process,the reduction effects of structural planes on failure intensity,and formation mechanisms.These experiments were complemented by acoustic and optical monitoring,as well as discrete element numerical simulations,to provide a comprehensive analysis.The results revealed that the most significant strain heterogeneity in the surrounding rock occurs at the tip of the structural plane along the tunnel's minimum principal stress direction,driven by the combined effects of tensile and shear forces.We quantitatively determined the critical stress and strain conditions for structure-type rockbursts and evaluated the intensity of rockbursts induced by different structural planes using critical crack opening displacement(COD)values,the uniformity coefficient,and the curvature coefficient.Analysis of acoustic emission events,including frequency,amplitude,and b-value,indicated that the macro-fracture process is governed by both the principal stress differential and the characteristics of the structural plane.Furthermore,using the bearing capacity reduction coefficient,we found that exposed structural planes have the most significant weakening effect on rock mass strength,followed by non-exposed and throughgoing structural planes.The analysis of average frequency(AF)and rise angle(RA)parameters revealed a close correlation between the failure modes of structure-type rockbursts,the rock mass structure,and the stress levels.These findings provide critical theoretical support for the prediction and prevention of structure-type rockburst disasters.展开更多
To mill fine and well-defined micro-dimpled structures,a machining manner of spiral trajectory tool reciprocating motion,where the tool repeats the process of‘feed milling–retract–cutting feed–feed milling again’...To mill fine and well-defined micro-dimpled structures,a machining manner of spiral trajectory tool reciprocating motion,where the tool repeats the process of‘feed milling–retract–cutting feed–feed milling again’along the spiral trajectory,was proposed.From the kinematics analysis,it is found that the machining quality of micro-dimpled structures is highly dependent on the machining trajectory using spiral trajectory tool reciprocating motion.To reveal this causation,simulation modelling and experimental studies were carried out.A simulation model was developed to quantitatively and qualitatively investigate the influence of the trajectory discretization strategies(constant-angle and constant-arc length)and parameters(discrete angle,discrete arc length,and pitch)on surface texture and residual height of micro-dimpled structures.Subsequently,micro-dimpled structures were milled under different trajectory discretization strategies and parameters with spiral trajectory tool reciprocating motion.A comprehensive comparison between the milled results and simulation analysis was made based on geometry accuracy,surface morphology and surface roughness of milled dimples.Meanwhile,the errors and factors affecting the above three aspects were analyzed.The results demonstrate both the feasibility of the established simulation model and the machining capability of this machining way in milling high-quality micro-dimpled structures.Spiral trajectory tool reciprocating motion provides a new machining way for milling micro-dimpled structures and micro-dimpled functional surfaces.And an appropriate machining trajectory can be generated based on the optimized trajectory parameters,thus contributing to the improvement of machining quality and efficiency.展开更多
基金the support of Research Program of Fine Exploration and Surrounding Rock Classification Technology for Deep Buried Long Tunnels Driven by Horizontal Directional Drilling and Magnetotelluric Methods Based on Deep Learning under Grant E202408010the Sichuan Science and Technology Program under Grant 2024NSFSC1984 and Grant 2024NSFSC1990。
文摘Porosity is an important attribute for evaluating the petrophysical properties of reservoirs, and has guiding significance for the exploration and development of oil and gas. The seismic inversion is a key method for comprehensively obtaining the porosity. Deep learning methods provide an intelligent approach to suppress the ambiguity of the conventional inversion method. However, under the trace-bytrace inversion strategy, there is a lack of constraints from geological structural information, resulting in poor lateral continuity of prediction results. In addition, the heterogeneity and the sedimentary variability of subsurface media also lead to uncertainty in intelligent prediction. To achieve fine prediction of porosity, we consider the lateral continuity and variability and propose an improved structural modeling deep learning porosity prediction method. First, we combine well data, waveform attributes, and structural information as constraints to model geophysical parameters, constructing a high-quality training dataset with sedimentary facies-controlled significance. Subsequently, we introduce a gated axial attention mechanism to enhance the features of dataset and design a bidirectional closed-loop network system constrained by inversion and forward processes. The constraint coefficient is adaptively adjusted by the petrophysical information contained between the porosity and impedance in the study area. We demonstrate the effectiveness of the adaptive coefficient through numerical experiments.Finally, we compare the performance differences between the proposed method and conventional deep learning methods using data from two study areas. The proposed method achieves better consistency with the logging porosity, demonstrating the superiority of the proposed method.
基金the financial support by the Major Research Plan of National Natural Science Foundation of China(92062219)the Young Elite Scientists Sponsorship Program by BAST(No.BYESS2023411)+2 种基金the Open Research Project from the State Key Laboratory of Geological Processes and Mineral Resources,China University of Geosciences(GPMR202407)the Geological Survey Project of the China Geological Survey„General survey of Hadamengou Rock Gold Deposit in Inner Mongolia'(DD20191017)the Geological Survey Project(H90063).
文摘Controversy is ongoing regarding the relationship between ore formation and the structural evolution of the Hadamengou gold deposit.To address this issue,we conducted a comprehensive investigation of mineralization-related structures,geochronology and Fe isotopes.From the perspective of spatial evolution,hydrothermal fluids originating from the Shadegai and Xishadegai plutons have extracted accumulated ore-forming elements from the Wulashan Group(Ar2WL)and then evolved,initiating at Exploration Line 11 and migrating eastwards and westwards along the EW-trending thrust fault system to form orebodies.From the temporal evolution standpoint,the Wulashan Group(Ar_(2)WL)experienced diagenesis(2591.00 Ma to 2204.00 Ma)and metamorphism(2074.00 Ma to 1625.00 Ma)from late Neoarchean to early Paleoproterozoic,when ore-forming materials were initially accumulated;in the early Paleozoic(440.71 Ma to 425.00 Ma),the collision led to the formation of early-stage EW-trending imbricated thrust faults,which established a fundamental structural framework for the orefield and further accumulated ore-forming materials;from the late Paleozoic to the Mesozoic,multiple subsequent episodes of regional tectonic-magmatic-hydrothermal events have superimposed,modified and reactivated the thrust fault system.Notably,the Triassic period,particularly between 245.00 Ma and 217.90 Ma,is considered to be a primary ore-forming stage.In summary,the intricate relationship between ore-formation and structural evolution has been fundamentally elucidated.
基金supported by the 2021 Shandong Province Higher Education Institutions“Youth Innovation Talent Introduction and Cultivation Plan”(Public Health Safety Risk Assessment and Response Innovation Team)National Traditional Chinese Medicine Comprehensive Reform Demonstration Zone Science and Technology Co construction Project(No.GZYKJSSD-2024-106)Research Project of Shandong Educational Supervision Society(No.SDJYDDXH2023-2159).
文摘Dentistry is a profession with a high prevalence of work-related musculoskeletal disorders(WMSDs),with symptoms often appearing very early in one’s career[1].WMSDs are conditions affecting the muscles,bones,and nervous system due to occupational factors.In 2002,the International Labor Organization included musculoskeletal diseases in the International List of Occupational Diseases.China’s recently updated Classification and Catalog of Occupational Diseases has introduced two new categories of occupational illnesses,including occupational musculoskeletal disorders.WMSDs significantly impact the health and work of dentists,reducing their quality of life and causing economic losses.These disorders are multifactorial in nature,influenced by personal,psychosocial,biomechanical,and environmental factors.Dentists frequently maintain static or awkward postures during procedures,which leads to musculoskeletal strain and discomfort;additionally,long working hours contribute to psychological stress,further increasing the risk of WMSDs[2].
基金Supported by the National Natural Science Foundation of China(42302141).
文摘Taking the second member of the Xujiahe Formation of the Upper Triassic in the Xinchang structural belt as an example,based on data such as logging,production,seismic interpretation and test,a systematic analysis was conducted on the structural characteristics and evolution,reservoir diagenesis and densification processes,and types and stages of faults/fractures,and revealing the multi-stage and multi-factor dynamic coupled enrichment mechanisms of tight gas reservoirs.(1)In the early Yanshan period,the paleo-structural traps were formed with low-medium maturity hydrocarbons accumulating in structural highs driven by buoyancy since reservoirs were not fully densified in this stage,demonstrating paleo-structure control on traps and early hydrocarbon accumulation.(2)In the middle-late Yanshan period,the source rocks became mature to generate and expel a large quantity of hydrocarbons.Grain size and type of sandstone controlled the time of reservoir densification,which restricted the scale of hydrocarbon charging,allowing for only a small-scale migration through sand bodies near the fault/fracture or less-densified matrix reservoirs.(3)During the Himalayan period,the source rocks reached overmaturity,and the residual oil cracking gas was efficiently transported along the late-stage faults/fractures.Wells with high production capacity were mainly located in Type I and II fault/fracture zones comprising the late-stage north-south trending fourth-order faults and the late-stage fractures.The productivity of the wells was controlled by the transformation of the late-stage faults/fractures.(4)The Xinchang structural belt underwent three stages of tectonic evolution,two stages of reservoir formation,and three stages of fault/fractures development.Hydrocarbons mainly accumulated in the paleo-structure highs.After reservoir densification and late fault/fracture adjustment,a complex gas-water distribution pattern was formed.Thus,it is summarized as the model of“near-source and low-abundance hydrocarbon charging in the early stage,and differential enrichment of natural gas under the joint control of fault-fold-fracture complex,high-quality reservoirs and structural highs in the late stage”.Faults/fractures with well-coupled fault-fold-fracture-pore are favorable exploration targets with high exploration effectiveness.
基金financially supported by the National Science Foundation of China(Nos.51974212 and 52274316)the China Baowu Low Carbon Metallurgy Innovation Foundation(No.BWLCF202116)+1 种基金the Science and Technology Major Project of Wuhan(No.2023020302020572)the Foundation of Key Laboratory for Ferrous Metallurgy and Resources Utilization of Ministry of Education(No.FMRUlab23-04)。
文摘The utilization of iron coke provides a green pathway for low-carbon ironmaking.To uncover the influence mechanism of iron ore on the behavior and kinetics of iron coke gasification,the effect of iron ore on the microstructure of iron coke was investigated.Furthermore,a comparative study of the gasification reactions between iron coke and coke was conducted through non-isothermal thermogravimetric method.The findings indicate that compared to coke,iron coke exhibits an augmentation in micropores and specific surface area,and the micropores further extend and interconnect.This provides more adsorption sites for CO_(2) molecules during the gasification process,resulting in a reduction in the initial gasification temperature of iron coke.Accelerating the heating rate in non-isothermal gasification can enhance the reactivity of iron coke.The metallic iron reduced from iron ore is embedded in the carbon matrix,reducing the orderliness of the carbon structure,which is primarily responsible for the heightened reactivity of the carbon atoms.The kinetic study indicates that the random pore model can effectively represent the gasification process of iron coke due to its rich pore structure.Moreover,as the proportion of iron ore increases,the activation energy for the carbon gasification gradually decreases,from 246.2 kJ/mol for coke to 192.5 kJ/mol for iron coke 15wt%.
基金supported by the National Natural Science Foundation of China(Nos.42174063,92155307,41976046)Guangdong Provincial Key Laboratory of Geophysical High-resolution Imaging Technology under(No.2022B1212010002)Project for introduced Talents Team of Southern Marine Science and Engineering Guangdong(Guangzhou)(No.GML2019ZD0203)。
文摘Existing lithospheric velocity models exhibit similar structures typically associated with the first-order tectonic features,with dissimilarities due to different data and methods used in model generation.The quantification of model structural similarity can help in interpreting the geophysical properties of Earth's interior and establishing unified models crucial in natural hazard assessment and resource exploration.Here we employ the complex wavelet structural similarity index measure(CW-SSIM)active in computer image processing to analyze the structural similarity of four lithospheric velocity models of Chinese mainland published in the past decade.We take advantage of this method in its multiscale definition and insensitivity to slight geometrical distortion like translation and scaling,which is particularly crucial in the structural similarity analysis of velocity models accounting for uncertainty and resolution.Our results show that the CW-SSIM values vary in different model pairs,horizontal locations,and depths.While variations in the inter-model CW-SSIM are partly owing to different databases in the model generation,the difference of tomography methods may significantly impact the similar structural features of models,such as the low similarities between the full-wave based FWEA18 and other three models in northeastern China.We finally suggest potential solutions for the next generation of tomographic modeling in different areas according to corresponding structural similarities of existing models.
基金supported by the Research and Development Center of Transport Industry of New Generation of Artificial Intelligence Technology(Grant No.202202H)the National Key R&D Program of China(Grant No.2019YFB1600702)the National Natural Science Foundation of China(Grant Nos.51978600&51808336).
文摘Structural Health Monitoring(SHM)systems have become a crucial tool for the operational management of long tunnels.For immersed tunnels exposed to both traffic loads and the effects of the marine environment,efficiently identifying abnormal conditions from the extensive unannotated SHM data presents a significant challenge.This study proposed amodel-based approach for anomaly detection and conducted validation and comparative analysis of two distinct temporal predictive models using SHM data from a real immersed tunnel.Firstly,a dynamic predictive model-based anomaly detectionmethod is proposed,which utilizes a rolling time window for modeling to achieve dynamic prediction.Leveraging the assumption of temporal data similarity,an interval prediction value deviation was employed to determine the abnormality of the data.Subsequently,dynamic predictive models were constructed based on the Autoregressive Integrated Moving Average(ARIMA)and Long Short-Term Memory(LSTM)models.The hyperparameters of these models were optimized and selected using monitoring data from the immersed tunnel,yielding viable static and dynamic predictive models.Finally,the models were applied within the same segment of SHM data,to validate the effectiveness of the anomaly detection approach based on dynamic predictive modeling.A detailed comparative analysis discusses the discrepancies in temporal anomaly detection between the ARIMA-and LSTM-based models.The results demonstrated that the dynamic predictive modelbased anomaly detection approach was effective for dealing with unannotated SHM data.In a comparison between ARIMA and LSTM,it was found that ARIMA demonstrated higher modeling efficiency,rendering it suitable for short-term predictions.In contrast,the LSTM model exhibited greater capacity to capture long-term performance trends and enhanced early warning capabilities,thereby resulting in superior overall performance.
基金This work presented in this paper was funded by the National Natural Science Foundation of China(Grant Nos.51478031 and 51278046)Shenzhen Science and Technology Innovation Fund(Grant No.FA24405041).The authors are grateful to the editor and reviewers for discerning comments on this paper.
文摘Structural planes play an important role in controlling the stability of rock engineering,and the influence of structural planes should be considered in the design and construction process of rock engineering.In this paper,mechanical properties,constitutive theory,and numerical application of structural plane are studied by a combination method of laboratory tests,theoretical derivation,and program development.The test results reveal the change laws of various mechanical parameters under different roughness and normal stress.At the pre-peak stage,a non-stationary model of shear stiffness is established,and threedimensional empirical prediction models for initial shear stiffness and residual stage roughness are proposed.The nonlinear constitutive models are established based on elasto-plastic mechanics,and the algorithms of the models are developed based on the return mapping algorithm.According to a large number of statistical analysis results,empirical prediction models are proposed for model parameters expressed by structural plane characteristic parameters.Finally,the discrete element method(DEM)is chosen to embed the constitutive models for practical application.The running programs of the constitutive models have been compiled into the discrete element model library.The comparison results between the proposed model and the Mohr-Coulomb slip model show that the proposed model can better describe nonlinear changes at different stages,and the predicted shear strength,peak strain and shear stiffness are closer to the test results.The research results of the paper are conducive to the accurate evaluation of structural plane in rock engineering.
基金financed by the Department of education of Gansu Province:Young Doctor Fund Project(2022QB-029)the Fundamental Research Funds for the Central Universities(31920240125-06,31920240059)+1 种基金the Scientific Research Project of Introducing Talents of Northwest Minzu University(xbmuyjrc202215,xbmuyjrc202216)the National Natural Science Foundation of China(22178289).
文摘Coal has a highly complex chemical structure,similar to polymers,coal is a macromolecular structure composed of a large number of“similar compounds”,which is called the basic structural unit.Understanding coal structure is the basis of its transformation and utilization.Shendong(SD)coal was analyzed by FTIR,XRD,XPS,and NMR.The results show that SD coal normalized structure formula is C_(100)H_(68.5)O_(35.7)N_(1.2)S_(0.2)and the average number of aromatic rings is 1.98.-CH_(2)-content accounts for about 82%in aliphatic CeH region,and the ratio of ether bond CeO,aromatic ether C-O and C=O is about 2:1:11 in oxygen-containing functional group region.The d_(002),L_(C),L_(a)and N_(C)of S_(D)coal microcrystalline structure parameters are 0.1832 nm,1.4688 nm,2.0852 nm and 9.017,respectively.Aromatic carbon and aliphatic carbon ratios of SD coal are 55.67%and 29.97%,aromatic cluster size and average methylene chain length are 0.224 and 1.817.Based on these structural parameters,molecular model of SD coal was constructed with^(13)C SSNMR experimental spectra as a reference.The model was constructed with an atom composition of C_(214)H_(214)O_(49)N_(2)S.
文摘This study introduces an innovative“Big Model”strategy to enhance Bridge Structural Health Monitoring(SHM)using a Convolutional Neural Network(CNN),time-frequency analysis,and fine element analysis.Leveraging ensemble methods,collaborative learning,and distributed computing,the approach effectively manages the complexity and scale of large-scale bridge data.The CNN employs transfer learning,fine-tuning,and continuous monitoring to optimize models for adaptive and accurate structural health assessments,focusing on extracting meaningful features through time-frequency analysis.By integrating Finite Element Analysis,time-frequency analysis,and CNNs,the strategy provides a comprehensive understanding of bridge health.Utilizing diverse sensor data,sophisticated feature extraction,and advanced CNN architecture,the model is optimized through rigorous preprocessing and hyperparameter tuning.This approach significantly enhances the ability to make accurate predictions,monitor structural health,and support proactive maintenance practices,thereby ensuring the safety and longevity of critical infrastructure.
基金The National Natural Science Foundation of China(No.52078427).
文摘To ensure the operational safety of railways in the landslide-prone areas of mountainous regions,a large-scale model test and numerical simulation were conducted to study the bending moment distribution,internal force distribution,deformation development,and crack propagation characteristics of a framed anti-sliding structure(FAS)under landslide thrust up to the point of failure.Results show that the maximum bending moment and its increase rate in the fore pile are greater than those in the rear pile,with the maximum bending moment of the fore pile approximately 1.1 times that of the rear pile.When the FAS fails,the displacement at the top of the fore pile is significantly greater,about 1.27 times that of the rear pile in the experiment.Major cracks develop at locations corresponding to the peak bending moments.Small transverse cracks initially appear on the upper surface at the intersection between the primary beam and rear pile and then spread to the side of the structure.At the failure stage,major cracks are observed at the pil-beam intersections and near the anchor points.Strengthening flexural stiffness at intersections where major cracks occur can improve the overall thrust-deformation coordination of the FAS,thereby maximizing its performance.
基金National Natural Science Foundation of China(22073023)Natural Science Foundation of Henan Province(242300421134)+1 种基金the Young Backbone Teacher in Colleges and Universities of Henan Province(2021GGJS020)Foundation of State Key Laboratory of Antiviral Drugs。
文摘The acetylpolyamine oxidase(APAO),spermine oxidase(SMO),and spermidine/spermine N1-acetyltransferase(SSAT)are pivotal enzymes in polyamine metabolism,exerting direct influence on polyamine homeostasis regulation.Dysfunctions in these enzymes are intricately linked to inflammatory diseases and cancers.Establishing their three-dimensional structures is essential for exploring enzymatic catalytic mechanisms and designing inhibitors at the atomic level.This article primarily assesses the precision of AlphaFold2 and molecular dynamics simulations in determining the three-dimensional structures of these enzymes,utilizing protein conformation rationality assessment,residue correlation matrix,and other techniques.This provides robust models for subsequent polyamine catabolic metabolism calculations and offers valuable insights for modeling proteins that have yet to acquire crystal structures.
基金Supported by the National Natural Science Foundation of China,No.81871081 and No.62201265the Fundamental Research Funds for the Central Universities,No.NJ2024029-14the Talent Support Programs of Wuxi Health Commission,No.BJ2023085,No.FZXK2021012,and No.M202358.
文摘BACKGROUND Depression,non-suicidal self-injury(NSSI),and suicide attempts(SA)often co-occur during adolescence and are associated with long-term adverse health outcomes.Unfortunately,neural mechanisms underlying self-injury and SA are poorly understood in depressed adolescents but likely relate to the structural abnormalities in brain regions.AIM To investigate structural network communication within large-scale brain networks in adolescents with depression.METHODS We constructed five distinct network communication models to evaluate structural network efficiency at the whole-brain level in adolescents with depression.Diffusion magnetic resonance imaging data were acquired from 32 healthy controls and 85 depressed adolescents,including 17 depressed adolescents without SA or NSSI(major depressive disorder group),27 depressed adolescents with NSSI but no SA(NSSI group),and 41 depressed adolescents with SA and NSSI(NSSI+SA group).RESULTS Significant differences in structural network communication were observed across the four groups,involving spatially widespread brain regions,particularly encompassing cortico-cortical connections(e.g.,dorsal posterior cingulate gyrus and the right ventral posterior cingulate gyrus;connections based on precentral gyrus)and cortico-subcortical circuits(e.g.,the nucleus accumbens-frontal circuit).In addition,we examined whether compromised communication efficiency was linked to clinical symptoms in the depressed adolescents.We observed significant correlations between network communication efficiencies and clinical scale scores derived from depressed adolescents with NSSI and SA.CONCLUSION This study provides evidence of structural network communication differences in depressed adolescents with NSSI and SA,highlighting impaired neuroanatomical communication efficiency as a potential contributor to their symptoms.These findings offer new insights into the pathophysiological mechanisms underlying the comorbidity of NSSI and SA in adolescent depression.
文摘Beach groynes are structures for erosion protection along sandy coasts near inlets and can reduce the coastal erosion substantially,but open groynes cannot stop erosion completely because sand can be removed from the groyne compartments by cross-shore processes.Beach groynes should be designed with sufficient bypassing of sand to minimise erosion.Regular beach maintenance is required to keep a sufficient beach width for recreational purposes.The effectiveness of groyne compartments can be significantly improved by using T-head groynes or by using a submerged sill or breakwater in between the groynes.An economic evaluation shows that the beach maintenance costs over 50 years may be substantially higher than the construction costs of a submerged breakwater.An important parameter to be studied is the longshore transport,which requires detailed information of the wave climate,preferably based on measured data(offshore buoys)in combination with deep water wave modelling.Various models have been used to determine the net longshore sand transport and coastline changes.The design of groynes to reduce coastal erosion is illustrated by three field cases(Atlantic coast near Soulac,France;Lagos coast,Nigeria and Black Sea coast,Romania).These example cases show that beach groynes are effective structures,but sufficient bypassing of longshore sand transport is essential to minimise erosion.Regular beach fills in the groyne compartments may be required at high-energy(exposed)coasts.A submerged or emerged breakwater can be built between the groynes to protect the beach in the groyne compartments against erosion by cross-shore processes.
基金National Natural Science Foundation of China(No.52375236)Fundamental Research Funds for the Central Universities,China(No.23D110316)。
文摘In the structural reliability analysis,the first-order reliability method(FORM)often yields significant errors when addressing nonlinear problems.Although the second-order reliability method(SORM)can provide higher accuracy,the additional computation of the Hessian matrix leads to lower computational efficiency.Additionally,when the dimensionality of the random variables is high,the approximation formula of SORM can result in larger errors.To address these issues,a structural reliability analysis method based on Kriging and spherical cap area integral is proposed.Firstly,this method integrates FORM with the quasi-Newton algorithm Broyden-Fletcher-Goldfarb-Shanno(BFGS),trains the Kriging model by using sample points from the algorithm’s iteration process,and combines the Kriging model with gradient information to approximate the Hessian matrix.Then,the failure surface is approximated as a rotating paraboloid,utilizing the spherical cap to replace the complex surface.For the n-dimensional case,the hyperspherical cap area expression is combined with the integral method to calculate the failure probability.Finally,the method is validated through three examples,demonstrating improved computational accuracy and efficiency compared to traditional methods.
基金supported by the Zhejiang Provincial Natural Science Foundation of China(Grant No.LY23E040001)Fundamental Research Funding Project of Zhejiang Province,China(Project Category A,Grant No.2022YW06)National Key R&D Program of China(Grant No.2023YFF0614902).
文摘Accurate prediction of coal reservoir permeability is crucial for engineering applications,including coal mining,coalbed methane(CBM)extraction,and carbon storage in deep unmineable coal seams.Owing to the inherent heterogeneity and complex internal structure of coal,a well-established method for predicting permeability based on microscopic fracture structures remains elusive.This paper presents a novel integrated approach that leverages the intrinsic relationship between microscopic fracture structure and permeability to construct a predictive model for coal permeability.The proposed framework encompasses data generation through the integration of three-dimensional(3D)digital core analysis and numerical simulations,followed by data-driven modeling via machine learning(ML)techniques.Key data-driven strategies,including feature selection and hyperparameter tuning,are employed to improve model performance.We propose and evaluate twelve data-driven models,including multilayer perceptron(MLP),random forest(RF),and hybrid methods.The results demonstrate that the ML model based on the RF algorithm achieves the highest accuracy and best generalization capability in predicting permeability.This method enables rapid estimation of coal permeability by inputting two-dimensional(2D)computed tomography images or parameters of the microscopic fracture structure,thereby providing an accurate and efficient means of permeability prediction.
文摘Machine learning(ML)has emerged as a powerful tool for predicting polymer properties,including glass transition temperature(Tg),which is a critical factor influencing polymer applications.In this study,a dataset of polymer structures and their Tg values were created and represented as adjacency matrices based on molecular graph theory.Four key structural descriptors,flexibility,side chain occupancy length,polarity,and hydrogen bonding capacity,were extracted and used as inputs for ML models:Extra Trees(ET),Random Forest(RF),Gaussian Process Regression(GPR),and Gradient Boosting(GB).Among these,ET and GPR achieved the highest predictive performance,with R2 values of 0.97,and mean absolute errors(MAE)of approximately 7–7.5 K.The use of these extracted features significantly improved the prediction accuracy compared to previous studies.Feature importance analysis revealed that flexibility had the strongest influence on Tg,followed by side-chain occupancy length,hydrogen bonding,and polarity.This work demonstrates the potential of data-driven approaches in polymer science,providing a fast and reliable method for Tg prediction that does not require experimental inputs.
基金Supported by the National Natural Science Foundation of China(42372175,72088101)PetroChina Science and Technology Project of(2023DJ84)Basic Research Cooperation Project between China National Petroleum Corporation and Peking University.
文摘Existing sandstone rock structure evaluation methods rely on visual inspection,with low efficiency,semi-quantitative analysis of roundness,and inability to perform classified statistics in particle size analysis.This study presents an intelligent evaluation method for sandstone rock structure based on the Segment Anything Model(SAM).By developing a lightweight SAM fine-tuning method with rank-decomposition matrix adapters,a multispectral rock particle segmentation model named CoreSAM is constructed,which achieves rock particle edge extraction and type identification.Building upon this,we propose a comprehensive quantitative evaluation system for rock structure,assessing parameters including particle size,sorting,roundness,particle contact and cementation types.The experimental results demonstrate that CoreSAM outperforms existing methods in rock particle segmentation accuracy while showing excellent generalization across different image types such as CT scans and core photographs.The proposed method enables full-sample,classified particle size analysis and quantitative characterization of parameters like roundness,advancing reservoir evaluation towards more precise,quantitative,intuitive,and comprehensive development.
基金supported by the National Natural Science Foundation of China(Grant Nos.42307241 and 42107211)the State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project(Grant No.SKLGP2022Z008).
文摘Structure-type rockbursts frequently occur in deep tunnels,with structural planes and stress conditions being critical factors in their formation.In this study,we utilized specially developed analogous materials that exhibit the high brittleness and strength characteristics of deep hard rock to construct physical models representing different types of structural planes,including composite,exposed,non-exposed,and throughgoing structural planes.Physical simulation experiments were conducted on structuretype rockbursts in deep horseshoe-shaped tunnels,focusing on strain differentiation characteristics,critical triggering conditions,critical crack opening displacement,the incubation process,the reduction effects of structural planes on failure intensity,and formation mechanisms.These experiments were complemented by acoustic and optical monitoring,as well as discrete element numerical simulations,to provide a comprehensive analysis.The results revealed that the most significant strain heterogeneity in the surrounding rock occurs at the tip of the structural plane along the tunnel's minimum principal stress direction,driven by the combined effects of tensile and shear forces.We quantitatively determined the critical stress and strain conditions for structure-type rockbursts and evaluated the intensity of rockbursts induced by different structural planes using critical crack opening displacement(COD)values,the uniformity coefficient,and the curvature coefficient.Analysis of acoustic emission events,including frequency,amplitude,and b-value,indicated that the macro-fracture process is governed by both the principal stress differential and the characteristics of the structural plane.Furthermore,using the bearing capacity reduction coefficient,we found that exposed structural planes have the most significant weakening effect on rock mass strength,followed by non-exposed and throughgoing structural planes.The analysis of average frequency(AF)and rise angle(RA)parameters revealed a close correlation between the failure modes of structure-type rockbursts,the rock mass structure,and the stress levels.These findings provide critical theoretical support for the prediction and prevention of structure-type rockburst disasters.
基金co-supported the National Natural Science Foundation of China(No.52235010)the Heilongjiang Postdoctoral Fund(No.LBH-Z22136)the New Era Longjiang Excellent Master and Doctoral Dissertation Fund(No.LJYXL2022-057).
文摘To mill fine and well-defined micro-dimpled structures,a machining manner of spiral trajectory tool reciprocating motion,where the tool repeats the process of‘feed milling–retract–cutting feed–feed milling again’along the spiral trajectory,was proposed.From the kinematics analysis,it is found that the machining quality of micro-dimpled structures is highly dependent on the machining trajectory using spiral trajectory tool reciprocating motion.To reveal this causation,simulation modelling and experimental studies were carried out.A simulation model was developed to quantitatively and qualitatively investigate the influence of the trajectory discretization strategies(constant-angle and constant-arc length)and parameters(discrete angle,discrete arc length,and pitch)on surface texture and residual height of micro-dimpled structures.Subsequently,micro-dimpled structures were milled under different trajectory discretization strategies and parameters with spiral trajectory tool reciprocating motion.A comprehensive comparison between the milled results and simulation analysis was made based on geometry accuracy,surface morphology and surface roughness of milled dimples.Meanwhile,the errors and factors affecting the above three aspects were analyzed.The results demonstrate both the feasibility of the established simulation model and the machining capability of this machining way in milling high-quality micro-dimpled structures.Spiral trajectory tool reciprocating motion provides a new machining way for milling micro-dimpled structures and micro-dimpled functional surfaces.And an appropriate machining trajectory can be generated based on the optimized trajectory parameters,thus contributing to the improvement of machining quality and efficiency.
