Gas content serves as a critical indicator for assessing the resource potential of deep coal mines and forecasting coal mine gas outburst risks.However,existing sampling technologies face challenges in maintaining the...Gas content serves as a critical indicator for assessing the resource potential of deep coal mines and forecasting coal mine gas outburst risks.However,existing sampling technologies face challenges in maintaining the integrity of gas content within samples and are often constrained by estimation errors inherent in empirical formulas,which results in inaccurate gas content measurements.This study introduces a lightweight,in-situ pressure-and gas-preserved corer designed to collect coal samples under the pressure conditions at the sampling point,effectively preventing gas loss during transfer and significantly improving measurement accuracy.Additionally,a gas migration model for deep coal mines was developed to elucidate gas migration characteristics under pressure-preserved coring conditions.The model offers valuable insights for optimizing coring parameters,demonstrating that both minimizing the coring hole diameter and reducing the pressure difference between the coring-point pressure and the original pore pressure can effectively improve the precision of gas content measurements.Coring tests conducted at an experimental base validated the performance of the corer and its effectiveness in sample collection.Furthermore,successful horizontal coring tests conducted in an underground coal mine roadway demonstrated that the measured gas content using pressure-preserved coring was 34%higher than that obtained through open sampling methods.展开更多
Background Social media listening is a new approach for gathering insights from social media platforms about users experiences.This approach has not been applied to analyse discussions about Alzheimer's disease(AD...Background Social media listening is a new approach for gathering insights from social media platforms about users experiences.This approach has not been applied to analyse discussions about Alzheimer's disease(AD)in China.Aims We aimed to leverage multisource Chinese data to gain deeper insights into the current state of the daily management of Chinese patients with AD and the burdens faced by their caregivers.Methods We searched ninemainstreampublic onlineplatforms in China fromSeptember2010 to March 2024.Natural language processing tools were used to identify patients and caregivers,and categorise patients by disease stage forfurther analysis.We analysed the current state of patient daily management,including diagnosis and treatment,choice oftreatment scenarios,patient safetyand caregiverconcerns.Results Atotal of 1211patientswithAD(66% female,82% aged 60-90)and 756caregiversfor patients with AD were identified from 107556 online sources.Most patients were derived from online consultation platforms(43%),followed by bulletin board system platforms(24%).Among the patients categorised into specific disease stages(n=382),42% were in the moderate stage.The most frequent diagnostic tools included medical history(97%)and symptoms(84%).Treatment options for patients with AD primarily included cholinesterase inhibitors,N-methyl-D-aspartate receptor antagonists and antipsychotics.Both quantitative and qualitative analysis of patients whoexperiencedwandering(n=92)indicated a higher incidence of wandering during the moderate stage of the disease.Most caregivers were family members,with their primary concerns focusing on disease management and treatment(90%),followed by daily life care(37%)and psychosocial support(25%).Conclusions Online platform data provide a broad spectrum of real-world insights into individuals affected byAD in China.This study enhances our understanding of the experiences of patients with AD and their caregivers,providing guidance for developing personalised interventions,providing advicefor caregivers and improving care for patients with AD.展开更多
Laser-induced breakdown spectroscopy(LIBS)has become a widely used atomic spectroscopic technique for rapid coal analysis.However,the vast amount of spectral information in LIBS contains signal uncertainty,which can a...Laser-induced breakdown spectroscopy(LIBS)has become a widely used atomic spectroscopic technique for rapid coal analysis.However,the vast amount of spectral information in LIBS contains signal uncertainty,which can affect its quantification performance.In this work,we propose a hybrid variable selection method to improve the performance of LIBS quantification.Important variables are first identified using Pearson's correlation coefficient,mutual information,least absolute shrinkage and selection operator(LASSO)and random forest,and then filtered and combined with empirical variables related to fingerprint elements of coal ash content.Subsequently,these variables are fed into a partial least squares regression(PLSR).Additionally,in some models,certain variables unrelated to ash content are removed manually to study the impact of variable deselection on model performance.The proposed hybrid strategy was tested on three LIBS datasets for quantitative analysis of coal ash content and compared with the corresponding data-driven baseline method.It is significantly better than the variable selection only method based on empirical knowledge and in most cases outperforms the baseline method.The results showed that on all three datasets the hybrid strategy for variable selection combining empirical knowledge and data-driven algorithms achieved the lowest root mean square error of prediction(RMSEP)values of 1.605,3.478 and 1.647,respectively,which were significantly lower than those obtained from multiple linear regression using only 12 empirical variables,which are 1.959,3.718 and 2.181,respectively.The LASSO-PLSR model with empirical support and 20 selected variables exhibited a significantly improved performance after variable deselection,with RMSEP values dropping from 1.635,3.962 and 1.647 to 1.483,3.086 and 1.567,respectively.Such results demonstrate that using empirical knowledge as a support for datadriven variable selection can be a viable approach to improve the accuracy and reliability of LIBS quantification.展开更多
Understanding the quantitative responses of anisotropic dynamic properties in organic-rich shale with different kerogen content(KC)is of great significance in hydrocarbon exploration and development.Conducting control...Understanding the quantitative responses of anisotropic dynamic properties in organic-rich shale with different kerogen content(KC)is of great significance in hydrocarbon exploration and development.Conducting controlled experiments with a single variable is challenging for natural shales due to their high variations in components,diagenesis conditions,or pore fluid.We employed the hot-pressing technique to construct 11 well-controlled artificial shale with varying KC.These artificial shale samples were successive machined into prismatic shape for ultrasonic measurements along different directions.Observations revealed bedding perpendicular P-wave velocities are more sensitive to the increasing KC than bedding paralleling velocities due to the preferential alignments of kerogen.All elastic stiffnesses except C_(13)are generally decreasing with the increasing KC,the variation of C_(1) and C_(33)on kerogen content are more sensitive than those of C_(44)and C_(66).Apparent dynamic mechanical parameters(v and E)were found to have linear correlation with the true ones from complete anisotropic equations independent of KC,which hold value towards the interpretation of well logs consistently across formations,Anisotropic mechanical parameters(ΔE and brittlenessΔB)tend to decrease with the reducing KC,withΔB showing great sensitivity to KC variations.In the range of low KC(<10%),the V_(P)/V_(S) ratio demonstrated a linearly negative correlation with KC,and the V_(P)/V_(S) ratio magnitude of less than 1.75may serve as a significant characterization for highly organic-rich(>10%)shale,compilation of data from natural organic rich-shales globally verified the similar systematic relationships that can be empirically used to predict the fraction of KC in shales.展开更多
Limited research has been conducted on the influences of fiber content on close-in blasting characteristics for ultrahigh-performance fiber-reinforced concrete(UHPFRC)beams.This paper aims to address this knowledge ga...Limited research has been conducted on the influences of fiber content on close-in blasting characteristics for ultrahigh-performance fiber-reinforced concrete(UHPFRC)beams.This paper aims to address this knowledge gap through experimental and mesoscale numerical methods.Experiments were conducted on ten UHPFRC beams built with varying steel fiber volumetric fractions subjected to close-in explosive conditions.Additionally,this study considered other parameters,such as the longitudinal reinforcement type and ratio.In the case of UHPFRC beams featuring normal-strength longitudinal reinforcement of diametersΦ12,Φ16,andΦ20,a reduction in maximum displacement by magnitudes of19.6%,19.5%,and 17.4%was observed,respectively,as the volumetric fractions of fiber increased from1.0%to 2.5%.In addition,increasing the longitudinal reinforcement ratio and using high-strength steel longitudinal reinforcement both significantly reduced the deformation characteristics and increase the blasting resistances of UHPFRC beams.However,the effects on the local crushing and spalling damage were not significant.A mesoscale finite element model,which considers the impacts of fiber parameters on UHPFRC beam behaviors,was also established and well correlated with the test findings.Nevertheless,parametric analyses were further conducted to examine the impacts of the steel fiber content and length and the hybrid effects of various types of microfibers and steel fibers on the blasting performance of UHPFRC beams.展开更多
The Lower Cambrian shale gas in the western Hubei area,South China has a great resource prospect,but the gas-in-place(GIP)content in different sedimentary facies varies widely,and the relevant mechanism has been not w...The Lower Cambrian shale gas in the western Hubei area,South China has a great resource prospect,but the gas-in-place(GIP)content in different sedimentary facies varies widely,and the relevant mechanism has been not well understood.In the present study,two sets of the Lower Cambrian shale samples from the Wells YD4 and YD5 in the western Hubei area,representing the deep-water shelf facies and shallowwater platform facies,respectively,were investigated on the differences of pore types,pore structure and methane adsorption capacity between them,and the main controlling factor and mechanism of their methane adsorption capacities and GIP contents were discussed.The results show that the organic matter(OM)pores in the YD4 shale samples are dominant,while the inorganic mineral(IM)pores in the YD5 shale samples are primary,with underdeveloped OM pores.The pore specific surface area(SSA)and pore volume(PV)of the YD4 shale samples are mainly from micropores and mesopores,respectively,while those of the YD5 shale samples are mainly from micropores and macropores,respectively.The methane adsorption capacity of the YD4 shale samples is significantly higher than that of the YD5 shale samples,with a maximum absolute adsorption capacity of 3.13 cm^(3)/g and 1.31 cm^(3)/g in average,respectively.Compared with the shallow-water platform shale,the deep-water shelf shale has a higher TOC content,a better kerogen type and more developed OM pores,which is the main mechanism for its higher adsorption capacity.The GIP content models based on two samples with a similar TOC content selected respectively from the Wells YD4 and YD5 further indicate that the GIP content of the deep-water shelf shale is mainly 34 m^(3)/t within a depth range of 1000—4000 m,with shale gas exploration and development potential,while the shallow-water platform shale has normally a GIP content of<1 m^(3)/t,with little shale gas potential.Considering the geological and geochemical conditions of shale gas formation and preservation,the deep-water shelf facies is the most favorable target for the Lower Cambrian shale gas exploration and development in the western Hubei area,South China.展开更多
During the operation of sandy railways, the challenge posed by wind-blown sand is a persistent issue. An in-depth study on the influence of wind-blown sand content on the macroscopic and microscopic mechanical propert...During the operation of sandy railways, the challenge posed by wind-blown sand is a persistent issue. An in-depth study on the influence of wind-blown sand content on the macroscopic and microscopic mechanical properties of the ballast bed is of great significance for understanding the potential problems of sandy railways and proposing reasonable and adequate maintenance and repair strategies. Building upon existing research, this study proposes a new assessment indicator for sand content. Utilizing the discrete element method(DEM) and fully considering the complex interactions between ballast and sand particles, three-dimensional(3D) multi-scale analysis models of sandy ballast beds with different wind-blown sand contents are established and validated through field experiments. The effects of varying wind-blown sand content on the microscopic contact distribution and macroscopic mechanical behavior(such as resistance and support stiffness) of ballast beds are carefully analyzed. The results show that with the increase in sand content, the average contact force and coordination number between ballast particles gradually decrease, and the disparity in contact forces between different layers of the ballast bed diminishes. The longitudinal and lateral resistance of the ballast bed initially decreases and then increases, with a critical point at 10% sand content. At 15% sand content, the lateral resistance is mainly shared by the ballast shoulder. The longitudinal resistance sharing ratio is always the largest on the sleeper side, followed by that at the sleeper bottom, and the smallest on the ballast shoulder. When the sand content exceeds 10%, the contribution of sand particles to stiffness significantly increases, leading to an accelerated growth rate of the overall support stiffness of the ballast bed, which is highly detrimental to the long-term service performance of the ballast bed. In conclusion, it is recommended that maintenance and repair operations should be promptly conducted when the sand content of the ballast bed reaches or exceeds 10%.展开更多
基金supported by the National Natural Science Foundation of China(Nos.51827901,42477191,and 52304033)the Fundamental Research Funds for the Central Universities(No.YJ202449)+1 种基金the Open Research Fund of State Key Laboratory of Geomechanics and Geotechnical Engineering,Institute of Rock and Soil Mechanics,Chinese Academy of Sciences(No.SKLGME022009)the China Postdoctoral Science Foundation(No.2023M742446).
文摘Gas content serves as a critical indicator for assessing the resource potential of deep coal mines and forecasting coal mine gas outburst risks.However,existing sampling technologies face challenges in maintaining the integrity of gas content within samples and are often constrained by estimation errors inherent in empirical formulas,which results in inaccurate gas content measurements.This study introduces a lightweight,in-situ pressure-and gas-preserved corer designed to collect coal samples under the pressure conditions at the sampling point,effectively preventing gas loss during transfer and significantly improving measurement accuracy.Additionally,a gas migration model for deep coal mines was developed to elucidate gas migration characteristics under pressure-preserved coring conditions.The model offers valuable insights for optimizing coring parameters,demonstrating that both minimizing the coring hole diameter and reducing the pressure difference between the coring-point pressure and the original pore pressure can effectively improve the precision of gas content measurements.Coring tests conducted at an experimental base validated the performance of the corer and its effectiveness in sample collection.Furthermore,successful horizontal coring tests conducted in an underground coal mine roadway demonstrated that the measured gas content using pressure-preserved coring was 34%higher than that obtained through open sampling methods.
基金funded by the Ministry of Science and Technology of the People's Republic of China(2021ZD0201804,GW).
文摘Background Social media listening is a new approach for gathering insights from social media platforms about users experiences.This approach has not been applied to analyse discussions about Alzheimer's disease(AD)in China.Aims We aimed to leverage multisource Chinese data to gain deeper insights into the current state of the daily management of Chinese patients with AD and the burdens faced by their caregivers.Methods We searched ninemainstreampublic onlineplatforms in China fromSeptember2010 to March 2024.Natural language processing tools were used to identify patients and caregivers,and categorise patients by disease stage forfurther analysis.We analysed the current state of patient daily management,including diagnosis and treatment,choice oftreatment scenarios,patient safetyand caregiverconcerns.Results Atotal of 1211patientswithAD(66% female,82% aged 60-90)and 756caregiversfor patients with AD were identified from 107556 online sources.Most patients were derived from online consultation platforms(43%),followed by bulletin board system platforms(24%).Among the patients categorised into specific disease stages(n=382),42% were in the moderate stage.The most frequent diagnostic tools included medical history(97%)and symptoms(84%).Treatment options for patients with AD primarily included cholinesterase inhibitors,N-methyl-D-aspartate receptor antagonists and antipsychotics.Both quantitative and qualitative analysis of patients whoexperiencedwandering(n=92)indicated a higher incidence of wandering during the moderate stage of the disease.Most caregivers were family members,with their primary concerns focusing on disease management and treatment(90%),followed by daily life care(37%)and psychosocial support(25%).Conclusions Online platform data provide a broad spectrum of real-world insights into individuals affected byAD in China.This study enhances our understanding of the experiences of patients with AD and their caregivers,providing guidance for developing personalised interventions,providing advicefor caregivers and improving care for patients with AD.
基金financial supports from National Natural Science Foundation of China(No.62205172)Huaneng Group Science and Technology Research Project(No.HNKJ22-H105)Tsinghua University Initiative Scientific Research Program and the International Joint Mission on Climate Change and Carbon Neutrality。
文摘Laser-induced breakdown spectroscopy(LIBS)has become a widely used atomic spectroscopic technique for rapid coal analysis.However,the vast amount of spectral information in LIBS contains signal uncertainty,which can affect its quantification performance.In this work,we propose a hybrid variable selection method to improve the performance of LIBS quantification.Important variables are first identified using Pearson's correlation coefficient,mutual information,least absolute shrinkage and selection operator(LASSO)and random forest,and then filtered and combined with empirical variables related to fingerprint elements of coal ash content.Subsequently,these variables are fed into a partial least squares regression(PLSR).Additionally,in some models,certain variables unrelated to ash content are removed manually to study the impact of variable deselection on model performance.The proposed hybrid strategy was tested on three LIBS datasets for quantitative analysis of coal ash content and compared with the corresponding data-driven baseline method.It is significantly better than the variable selection only method based on empirical knowledge and in most cases outperforms the baseline method.The results showed that on all three datasets the hybrid strategy for variable selection combining empirical knowledge and data-driven algorithms achieved the lowest root mean square error of prediction(RMSEP)values of 1.605,3.478 and 1.647,respectively,which were significantly lower than those obtained from multiple linear regression using only 12 empirical variables,which are 1.959,3.718 and 2.181,respectively.The LASSO-PLSR model with empirical support and 20 selected variables exhibited a significantly improved performance after variable deselection,with RMSEP values dropping from 1.635,3.962 and 1.647 to 1.483,3.086 and 1.567,respectively.Such results demonstrate that using empirical knowledge as a support for datadriven variable selection can be a viable approach to improve the accuracy and reliability of LIBS quantification.
基金supported by the National Natural Science Foundation of China(42004112,42274175,42030812,41974160)Natural Science Foundation of Sichuan Province(2023NSFSC0764)。
文摘Understanding the quantitative responses of anisotropic dynamic properties in organic-rich shale with different kerogen content(KC)is of great significance in hydrocarbon exploration and development.Conducting controlled experiments with a single variable is challenging for natural shales due to their high variations in components,diagenesis conditions,or pore fluid.We employed the hot-pressing technique to construct 11 well-controlled artificial shale with varying KC.These artificial shale samples were successive machined into prismatic shape for ultrasonic measurements along different directions.Observations revealed bedding perpendicular P-wave velocities are more sensitive to the increasing KC than bedding paralleling velocities due to the preferential alignments of kerogen.All elastic stiffnesses except C_(13)are generally decreasing with the increasing KC,the variation of C_(1) and C_(33)on kerogen content are more sensitive than those of C_(44)and C_(66).Apparent dynamic mechanical parameters(v and E)were found to have linear correlation with the true ones from complete anisotropic equations independent of KC,which hold value towards the interpretation of well logs consistently across formations,Anisotropic mechanical parameters(ΔE and brittlenessΔB)tend to decrease with the reducing KC,withΔB showing great sensitivity to KC variations.In the range of low KC(<10%),the V_(P)/V_(S) ratio demonstrated a linearly negative correlation with KC,and the V_(P)/V_(S) ratio magnitude of less than 1.75may serve as a significant characterization for highly organic-rich(>10%)shale,compilation of data from natural organic rich-shales globally verified the similar systematic relationships that can be empirically used to predict the fraction of KC in shales.
基金supported by the National Natural Science Foundation of China(Grant No.12102050)the Open Fund of State Key Laboratory of Explosion Science and Technology(Grant No.SKLEST-ZZ-21-18)。
文摘Limited research has been conducted on the influences of fiber content on close-in blasting characteristics for ultrahigh-performance fiber-reinforced concrete(UHPFRC)beams.This paper aims to address this knowledge gap through experimental and mesoscale numerical methods.Experiments were conducted on ten UHPFRC beams built with varying steel fiber volumetric fractions subjected to close-in explosive conditions.Additionally,this study considered other parameters,such as the longitudinal reinforcement type and ratio.In the case of UHPFRC beams featuring normal-strength longitudinal reinforcement of diametersΦ12,Φ16,andΦ20,a reduction in maximum displacement by magnitudes of19.6%,19.5%,and 17.4%was observed,respectively,as the volumetric fractions of fiber increased from1.0%to 2.5%.In addition,increasing the longitudinal reinforcement ratio and using high-strength steel longitudinal reinforcement both significantly reduced the deformation characteristics and increase the blasting resistances of UHPFRC beams.However,the effects on the local crushing and spalling damage were not significant.A mesoscale finite element model,which considers the impacts of fiber parameters on UHPFRC beam behaviors,was also established and well correlated with the test findings.Nevertheless,parametric analyses were further conducted to examine the impacts of the steel fiber content and length and the hybrid effects of various types of microfibers and steel fibers on the blasting performance of UHPFRC beams.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.42030804 and 42330811)the“Deep-time Digital Earth”Science and Technology Leading Talents Team Funds for the Central Universities for the Frontiers Science Center for Deep-time Digital Earth,China University of Geosciences(Beijing)(Fundamental Research Funds for the Central UniversitiesGrant No.2652023001)。
文摘The Lower Cambrian shale gas in the western Hubei area,South China has a great resource prospect,but the gas-in-place(GIP)content in different sedimentary facies varies widely,and the relevant mechanism has been not well understood.In the present study,two sets of the Lower Cambrian shale samples from the Wells YD4 and YD5 in the western Hubei area,representing the deep-water shelf facies and shallowwater platform facies,respectively,were investigated on the differences of pore types,pore structure and methane adsorption capacity between them,and the main controlling factor and mechanism of their methane adsorption capacities and GIP contents were discussed.The results show that the organic matter(OM)pores in the YD4 shale samples are dominant,while the inorganic mineral(IM)pores in the YD5 shale samples are primary,with underdeveloped OM pores.The pore specific surface area(SSA)and pore volume(PV)of the YD4 shale samples are mainly from micropores and mesopores,respectively,while those of the YD5 shale samples are mainly from micropores and macropores,respectively.The methane adsorption capacity of the YD4 shale samples is significantly higher than that of the YD5 shale samples,with a maximum absolute adsorption capacity of 3.13 cm^(3)/g and 1.31 cm^(3)/g in average,respectively.Compared with the shallow-water platform shale,the deep-water shelf shale has a higher TOC content,a better kerogen type and more developed OM pores,which is the main mechanism for its higher adsorption capacity.The GIP content models based on two samples with a similar TOC content selected respectively from the Wells YD4 and YD5 further indicate that the GIP content of the deep-water shelf shale is mainly 34 m^(3)/t within a depth range of 1000—4000 m,with shale gas exploration and development potential,while the shallow-water platform shale has normally a GIP content of<1 m^(3)/t,with little shale gas potential.Considering the geological and geochemical conditions of shale gas formation and preservation,the deep-water shelf facies is the most favorable target for the Lower Cambrian shale gas exploration and development in the western Hubei area,South China.
基金supported by the National Natural Science Foundation of China (Grant No. 52372425)the Fundamental Research Funds for the Central Universities (Science and Technology Leading Talent Team Poject) Grant No. 2022JBXT010。
文摘During the operation of sandy railways, the challenge posed by wind-blown sand is a persistent issue. An in-depth study on the influence of wind-blown sand content on the macroscopic and microscopic mechanical properties of the ballast bed is of great significance for understanding the potential problems of sandy railways and proposing reasonable and adequate maintenance and repair strategies. Building upon existing research, this study proposes a new assessment indicator for sand content. Utilizing the discrete element method(DEM) and fully considering the complex interactions between ballast and sand particles, three-dimensional(3D) multi-scale analysis models of sandy ballast beds with different wind-blown sand contents are established and validated through field experiments. The effects of varying wind-blown sand content on the microscopic contact distribution and macroscopic mechanical behavior(such as resistance and support stiffness) of ballast beds are carefully analyzed. The results show that with the increase in sand content, the average contact force and coordination number between ballast particles gradually decrease, and the disparity in contact forces between different layers of the ballast bed diminishes. The longitudinal and lateral resistance of the ballast bed initially decreases and then increases, with a critical point at 10% sand content. At 15% sand content, the lateral resistance is mainly shared by the ballast shoulder. The longitudinal resistance sharing ratio is always the largest on the sleeper side, followed by that at the sleeper bottom, and the smallest on the ballast shoulder. When the sand content exceeds 10%, the contribution of sand particles to stiffness significantly increases, leading to an accelerated growth rate of the overall support stiffness of the ballast bed, which is highly detrimental to the long-term service performance of the ballast bed. In conclusion, it is recommended that maintenance and repair operations should be promptly conducted when the sand content of the ballast bed reaches or exceeds 10%.
文摘利用全球导航卫星系统(Global Navigation Satellite System,GNSS)双频差分信号进行电离层电子含量反演是一种常用的电离层探测手段,但GNSS信号在强电磁干扰环境下,被淹没于电磁噪声中而无法被提取,影响电离层总电子含量(total electron content,TEC)反演系统的可靠性。采用传统调零抗干扰阵列天线方案能解决干扰源剥离的问题,但调零信号的天线相位中心不稳定导致高精度的相位平滑伪距和精密单点定位(precise point positioning,PPP)算法无法收敛。针对强干扰环境下的电离层监测需求,本文提出一种抗干扰TEC数据反演手段,通过对阵列天线通道幅相一致性进行校正,保证相位中心的稳定性,从而推算出准确的电离层TEC信息,提高了系统的可靠性和抗干扰能力。
