In this study, to meet the development and application requirements for high-strength and hightoughness energetic structural materials, a representative volume element of a TA15 matrix embedded with a TaZrNb sphere wa...In this study, to meet the development and application requirements for high-strength and hightoughness energetic structural materials, a representative volume element of a TA15 matrix embedded with a TaZrNb sphere was designed and fabricated via diffusion bonding. The mechanisms of the microstructural evolution of the TaZrNb/TA15 interface were investigated via SEM, EBSD, EDS, and XRD.Interface mechanical property tests and in-situ tensile tests were conducted on the sphere-containing structure, and an equivalent tensile-strength model was established for the structure. The results revealed that the TA15 titanium alloy and joint had high density and no pores or cracks. The thickness of the planar joint was approximately 50-60 μm. The average tensile and shear strengths were 767 MPa and 608 MPa, respectively. The thickness of the spherical joint was approximately 60 μm. The Zr and Nb elements in the joint diffused uniformly and formed strong bonds with Ti without forming intermetallic compounds. The interface exhibited submicron grain refinement and a concave-convex interlocking structure. The tensile fracture surface primarily exhibited intergranular fracture combined with some transgranular fracture, which constituted a quasi-brittle fracture mode. The shear fracture surface exhibited brittle fracture with regular arrangements of furrows. Internal fracture occurred along the spherical interface, as revealed by advanced in-situ X-ray microcomputed tomography. The experimental results agreed well with the theoretical predictions, indicating that the high-strength interface contributes to the overall strength and toughness of the sphere-containing structure.展开更多
The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recogni...The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recognized to be limited at data boundaries and high frequencies,which can significantly reduce the signal-to-noise ratio(SNR).To solve this problem,a novel method synergistically integrating Principal Component Analysis(PCA)with SG filtering is proposed in this paper.This approach avoids the is-sue of excessive smoothing associated with larger window sizes.The proposed PCA-SG filtering algorithm was applied to a CO gas sensing system based on Cavity Ring-Down Spectroscopy(CRDS).The perform-ance of the PCA-SG filtering algorithm is demonstrated through comparison with Moving Average Filtering(MAF),Wavelet Transformation(WT),Kalman Filtering(KF),and the SG filter.The results demonstrate that the proposed algorithm exhibits superior noise reduction capabilities compared to the other algorithms evaluated.The SNR of the ring-down signal was improved from 11.8612 dB to 29.0913 dB,and the stand-ard deviation of the extracted ring-down time constant was reduced from 0.037μs to 0.018μs.These results confirm that the proposed PCA-SG filtering algorithm effectively improves the smoothness of the ring-down curve data,demonstrating its feasibility.展开更多
Natural Gas Industry B创刊于2014年,是天然气工业杂志社与KeAi公司合作出版的国际OA期刊,在爱思唯尔旗下的Science Direct平台上双月出版。论文聚焦天然气、氢气、氦气、地热等地质能源,涵盖地质勘探、气藏开发、工程技术、储运利用...Natural Gas Industry B创刊于2014年,是天然气工业杂志社与KeAi公司合作出版的国际OA期刊,在爱思唯尔旗下的Science Direct平台上双月出版。论文聚焦天然气、氢气、氦气、地热等地质能源,涵盖地质勘探、气藏开发、工程技术、储运利用、净化化工、产业趋势等专业方向。期刊服务全球天然气产业,并积极推动能源行业碳减排和低碳转型的发展。展开更多
Natural Gas Industry B创刊于2014年,是天然气工业杂志社与KeAi公司合作出版的国际OA期刊,在爱思唯尔旗下的ScienceDirect平台上双月出版。论文聚焦天然气、氢气、氦气、地热等地质能源,涵盖地质勘探、气藏开发、工程技术、储运利用、...Natural Gas Industry B创刊于2014年,是天然气工业杂志社与KeAi公司合作出版的国际OA期刊,在爱思唯尔旗下的ScienceDirect平台上双月出版。论文聚焦天然气、氢气、氦气、地热等地质能源,涵盖地质勘探、气藏开发、工程技术、储运利用、净化化工、产业趋势等专业方向。期刊服务全球天然气产业,并积极推动能源行业碳减排和低碳转型的发展。展开更多
Gas wells often encounter blockages in gas recovery channels owing to fluid accumulation during the later stages of extraction,which adversely affects subsequent recovery efforts.These undesirable conditions(e.g.,high...Gas wells often encounter blockages in gas recovery channels owing to fluid accumulation during the later stages of extraction,which adversely affects subsequent recovery efforts.These undesirable conditions(e.g.,high condensate content,high temperature,and high salinity)often affect foaming agent performance.In this study,surfactants were screened using an airflow method that closely resembles field treatment method.Notably,alcohol ether sulfates(AE_(n)S)with various polyoxyethylene(EO)units demonstrated exceptional performance in terms of liquid unloading efficiency and foam stability.At 80℃,the unloading efficiency of AE_(n)S with two EO units(AE_(2)S)in a high NaCl mass concentration(up to 200 g/L)and high condensate volume fraction(up to 20%)reached 84%.The dynamic surface tension and interfacial tension measured at the same temperature were used to analyze the influence of the diffusion rate and interfacial characteristics on the AE_(n)S foam,while the viscosity and liquid film thickness measurements reflected the mechanical strength and liquid-carrying capacity.In addition,transmission electron microscopy(TEM)revealed that AE_(2)S formed“dendritic”micellar aggregates at a high NaCl mass concentration,which significantly enhanced the viscosity and stability of the foam.The interactions among AE_(n)S,NaCl,and H2O were analyzed using molecular dynamics,and it was confirmed from a molecular mechanics perspective that a stable structure can form among the three,contributing to the foam stability.These findings demonstrate the significant potential of the AE_(2)S foam for gas well deliquification.展开更多
This paper examines how natural gas disperses vertically when high-pressure pipelines with large openings fail in unconfined environments,providing insight into hazardous gas cloud development and behavior.A comprehen...This paper examines how natural gas disperses vertically when high-pressure pipelines with large openings fail in unconfined environments,providing insight into hazardous gas cloud development and behavior.A comprehensive study was conducted using a full-scale field experiment(1,219 mm diameter,12 MPa pressure,100 mm aperture)combined with a validated computational fluid dynamics(CFD)numerical simulation model to systematically analyze the coupling effects of pipeline pressure and ambient wind speed.The results indicate that:(1)Pipeline pressure determines the vertical jet scale,where jet height is positively correlated with pressure;at 12 MPa,the maximum jet height reaches 69.4 m(approximately 2.65 times that at 4 MPa),and the lower explosive limit(LEL)cloud area follows a quadratic polynomial trend.(2)Ambient wind speed significantly alters the diffusion trajectory;at a wind speed of 10 m/s,the LEL gas cloud area expands by 1.69 times compared to calm conditions,while the jet height is suppressed to 29.9%of the calm wind value.(3)Our developed dynamic prediction model for the hazardous gas-cloud region achieves a determination coefficient of 0.975 and maintaining prediction errors maintained within approximately 12%.The proposed empirical correlations and dynamic prediction model provide essential quantitative data support for safety-distance design and emergency-response decision-making for high-pressure natural gas pipelines.展开更多
Selectivity remains a significant challenge for gas sensors. In contrast to conventional gas sensors that depend solely on conductivity to detect gases, we exploited a single NiO-doped SnO_(2) sensor to simultaneously...Selectivity remains a significant challenge for gas sensors. In contrast to conventional gas sensors that depend solely on conductivity to detect gases, we exploited a single NiO-doped SnO_(2) sensor to simultaneously monitor transient changes in both sensor conductivity and temperature. The distinct response profiles of H_(2) and NH_(3) gases were attributed to differences in their redox rates and enthalpy changes during chemical reactions, which provided an opportunity for gas identification using machine learning(ML) algorithms. The test results indicate that preprocessing the extracted calorimetric and chemi-resistive parameters using the principal component analysis(PCA), followed by the application of ML classifiers for identification,enables a 100% accuracy for both target analytes. This work presents a facile gas identification method that enhances chiplevel sensor applications while minimizing the need for complex sensor arrays.展开更多
Thermal power plants are the main contributors to greenhouse gas emissions.The prediction of the emission supports the decision makers and environmental sustainability.The objective of this study is to enhance the acc...Thermal power plants are the main contributors to greenhouse gas emissions.The prediction of the emission supports the decision makers and environmental sustainability.The objective of this study is to enhance the accuracy of emission prediction models,supporting more effective real-time monitoring and enabling informed operational decisions that align with environmental compliance efforts.This paper presents a data-driven approach for the accurate prediction of gas emissions,specifically nitrogen oxides(NOx)and carbon monoxide(CO),in natural gas power plants using an optimized hybrid machine learning framework.The proposed model integrates a Feedforward Neural Network(FFNN)trained using Particle Swarm Optimization to capture the nonlinear emission dynamics under varying gas turbine operating conditions.To further enhance predictive performance,the K-Nearest Neighbor(K-NN)algorithm serves as a post-processing method to enhance IPSO-FFNN predictions through adjustment and refinement,improving overall prediction accuracy,while Neighbor Component Analysis is used to identify and rank the most influential operational variables.The study makes a significant contribution through the combination of NCA feature selection with PSO global optimization,FFNN nonlinear modelling,and K-NN error correction into one unified system,which delivers precise emission predictions.The model was developed and tested using a real-world dataset collected from gas-fired turbine operations,with validated results demonstrating robust accuracy,achieving Root Mean Square Error values of 0.355 for CO and 0.368 for NOx.When benchmarked against conventional models such as standard FFNN,Support Vector Regression,and Long Short-Term Memory networks,the hybrid model achieved substantial improvements,up to 97.8%in Mean Squared Error,95%in Mean Absolute Error(MAE),and 85.19%in RMSE for CO;and 97.16%in MSE,93.4%in MAE,and 83.15%in RMSE for NOx.These results underscore the model’s potential for improving emission prediction,thereby supporting enhanced operational efficiency and adherence to environmental standards.展开更多
Single-crystal GaN epilayers were irradiated with heavy inert gas ions(2.3-MeV Ne^(8+),5.3-MeV Kr^(19+))to fluences ranging from 1.0×1.0^(11) to 1.0×1.0^(15)ions∕cm^(2).The strain-related damage accumulatio...Single-crystal GaN epilayers were irradiated with heavy inert gas ions(2.3-MeV Ne^(8+),5.3-MeV Kr^(19+))to fluences ranging from 1.0×1.0^(11) to 1.0×1.0^(15)ions∕cm^(2).The strain-related damage accumulation versus ion fluences was studied using highresolution X-ray diffraction(HRXRD)and ultraviolet–visible(UV–Vis)spectroscopy.The results showed that the damage accumulation was mainly dominated by nuclear energy loss.When the ion fluence was less than∼0.055 displacement per atom(dpa),the lattice expansions and lattice strains markedly increased linearly with increasing ion fluences,accompanied by a slow enhancement in the dislocation densities,distortion parameters,and Urbach energy for both ion irradiations.Above this fluence(∼0.055 dpa),the lattice strains presented a slight increase,whereas a remarkable increase was observed in the dislocation densities,distortion parameters,and Urbach energy with the ion fluences after both ion irradiations.∼0.055 dpa is the threshold ion fluence for defect evolution and lattice damage related to strain.The mechanisms underlying the damage accumulation are discussed in detail.展开更多
The critical components of gas turbines suffer from prolonged exposure to factors such as thermal oxidation,mechanical wear,and airflow disturbances during prolonged operation.These conditions can lead to a series of ...The critical components of gas turbines suffer from prolonged exposure to factors such as thermal oxidation,mechanical wear,and airflow disturbances during prolonged operation.These conditions can lead to a series of issues,including mechanical faults,air path malfunctions,and combustion irregularities.Traditional modelbased approaches face inherent limitations due to their inability to handle nonlinear problems,natural factors,measurement uncertainties,fault coupling,and implementation challenges.The development of artificial intelligence algorithms has provided an effective solution to these issues,sparking extensive research into data-driven fault diagnosis methodologies.The review mechanism involved searching IEEE Xplore,ScienceDirect,and Web of Science for peerreviewed articles published between 2019 and 2025,focusing on multi-fault diagnosis techniques.A total of 220 papers were identified,with 123 meeting the inclusion criteria.This paper provides a comprehensive review of diagnostic methodologies,detailing their operational principles and distinctive features.It analyzes current research hotspots and challenges while forecasting future trends.The study systematically evaluates the strengths and limitations of various fault diagnosis techniques,revealing their practical applicability and constraints through comparative analysis.Furthermore,this paper looks forward to the future development direction of this field and provides a valuable reference for the optimization and development of gas turbine fault diagnosis technology in the future.展开更多
The Dongsha area,a key target for gas hydrate exploration,is influenced by multiple factors,including sedimentary processes and the paleoenvironment,which play critical roles in gas hydrate formation.To elucidate the ...The Dongsha area,a key target for gas hydrate exploration,is influenced by multiple factors,including sedimentary processes and the paleoenvironment,which play critical roles in gas hydrate formation.To elucidate the coupling among sedimentary processes,paleoenvironment,and gas hydrate accumulation,this study investigates the Site DS-W16 using particle size analysis,biological component content,and geochemistry data.Oxygen isotope data from foraminifera and biostratigraphic evidence indicate that sedimentation at the bottom of core interval from Site DS-W16 began during MIS 11(Marine isotope stage).The sedimentation dynamics of the studied layers are complex,involving gravity flows,traction currents,and suspended deposition.Organic matter shows a significant correlation with transgressive-regressive cycle.The site DS-W16 contains two distinct gas hydrate reservoirs:a shallow reservoir(10-24 mbsf)and a deep reservoir(below 182 mbsf).The paleomarine environment influences gas hydrate accumulation by altering sedimentary processes and sediment characteristics,especially the distribution of biological components.Both shallow and deep gas hydrate reservoirs formed under dynamic conditions dominated by traction currents and are characterized by a higher abundance of foraminifera.Sedimentary layers rich in foraminifera and modified by traction currents represent key intervals for preferential gas hydrate accumulation.展开更多
Automated classification of gas flow states in blast furnaces using top-camera imagery typically demands a large volume of labeled data,whose manual annotation is both labor-intensive and cost-prohibitive.To mitigate ...Automated classification of gas flow states in blast furnaces using top-camera imagery typically demands a large volume of labeled data,whose manual annotation is both labor-intensive and cost-prohibitive.To mitigate this challenge,we present an enhanced semi-supervised learning approach based on the Mean Teacher framework,incorporating a novel feature loss module to maximize classification performance with limited labeled samples.The model studies show that the proposed model surpasses both the baseline Mean Teacher model and fully supervised method in accuracy.Specifically,for datasets with 20%,30%,and 40%label ratios,using a single training iteration,the model yields accuracies of 78.61%,82.21%,and 85.2%,respectively,while multiple-cycle training iterations achieves 82.09%,81.97%,and 81.59%,respectively.Furthermore,scenario-specific training schemes are introduced to support diverse deployment need.These findings highlight the potential of the proposed technique in minimizing labeling requirements and advancing intelligent blast furnace diagnostics.展开更多
As the global leader in rice production,China's paddy fields contribute substantially to greenhouse gas emissions through methane(CH_(4))and nitrous oxide(N_(2)O)releases.Aromatic rice cultivation practices have b...As the global leader in rice production,China's paddy fields contribute substantially to greenhouse gas emissions through methane(CH_(4))and nitrous oxide(N_(2)O)releases.Aromatic rice cultivation practices have been optimized to enhance the aroma,so the relationship between its cultivation and greenhouse gas emissions from paddy fields is unclear.To investigate how aroma-enhancing cultivation practices drive microbial community dynamics in aromatic rice paddies and their implications for greenhouse gas emissions,a two-year experiment in five ecological locations(Xingning,Nanxiong,Conghua,Luoding,and Zengcheng)compared two farming practices:partial organic substitution for inorganic fertilizers combined with water-saving irrigation(IOF+W)and traditional cultivation(CK).The CH_(4)and N_(2)O emissions,soil microbial composition and function,global warming potential(GWP),nitrogen use efficiency,yield,and the content of 2-acetyl-1-pyrroline(2-AP)were measured and analyzed.The main purpose was to investigate the impact of IOF+W on CH_(4)and N_(2)O emissions and their relationship with soil microorganisms.The results showed that IOF+W significantly reduced CH_(4)emission fluxes and totals(36.95%)and GWP(31.29%),while significantly increasing N_(2)O emission fluxes and totals(14.82%).The soil microbial community structure was reshaped by the IOF+W treatment,which suppressed methanogens but enhanced the abundances of nitrifying and denitrifying bacteria.Key enzymatic activities involved in CH_(4)production,such as methyl-coenzyme M reductase,formylmethanofuran dehydrogenase,and methyltransferase,decreased.In contrast,the activity of the key CH_(4)-oxidizing enzyme methanol dehydrogenase increased.This shift led to an overall attenuation of the CH_(4)production metabolism while enhancing the CH_(4)oxidation metabolism.In addition,the activities of pivotal enzymes involved in denitrification and nitrification were improved,thus enhancing nitrogen nitrification and denitrification metabolism.Moreover,the IOF+W treatment significantly increased nitrogen use efficiency(47.83%),yield(14.77%),and 2-AP content(13.78%).Therefore,the IOF+W treatment demonstrated good efficacy as a sustainable strategy for achieving productive,green,resource-efficient,and premium-quality aromatic rice cultivation in South China.展开更多
As the primary functional component of a fusion reactor,the fusion blanket pebble bed,composed of numerous particles,is crucial for tritium breeding,neutron multiplication,and radiation shielding.Particles within trit...As the primary functional component of a fusion reactor,the fusion blanket pebble bed,composed of numerous particles,is crucial for tritium breeding,neutron multiplication,and radiation shielding.Particles within tritium-breeding pebble beds are subjected to prolonged neutron irradiation,high thermal loads,and strong magnetic fields in fusion environments.Such conditions render them susceptible to pulverization and fragmentation.The resulting fragments and powders migrate and are deposited into the gas channel,driven by the purge gas.The reduction in the effective flow area of the gas increases the flow resistance,resulting in tritium retention,degraded heat transfer,and other adverse effects.These conditions impair the thermodynamic properties of the pebble beds and hinder the self-maintenance of tritium.Limited information exists on powder migration and clogging mechanisms in fusion blanket pebble beds,particularly under diverse physical conditions.The aim of this study was to use a computational fluid dynamics model coupled with the discrete element method(CFD-DEM)to numerically explore powder migration and clogging in pebble beds.The model considers factors such as breeder orientation,purge velocity,powder size distribution,and friction coefficient.We propose two migration and clogging mechanisms.One involves powder with a large particle size,and the other does not.The results indicate that the powder migration velocity progresses through three stages:rapid decay,linear decay,and stability.Pebble-bed clogging manifests in two forms:extensive superficial clogging and uniform internal clogging.Two fitted curves were used to depict the migration and clogging tendencies.The powder size distribution significantly influenced the powder migration.The breeder orientation,powder size,and friction coefficient affected the distribution of the clogging powders.However,the impact of the purge velocity on powder migration and clogging in pebble beds was limited,and this effect varied significantly with different particle size ratios.Based on the analysis,a formula is proposed to characterize the behavior of the powder in the pebble beds.The results of this study can aid in analyzing and predicting powder dynamics in pebble beds.展开更多
The shale gas development in China faces challenges such as complex reservoir conditions and high development costs.Based on the pore pressure and geostress coupling theory,this paper studies the geostress evolution l...The shale gas development in China faces challenges such as complex reservoir conditions and high development costs.Based on the pore pressure and geostress coupling theory,this paper studies the geostress evolution laws and fracture network characteristics of shale gas infill wells.A mechanism model of CN platform logging data and geomechanical parameters is established to simulate the influence of parent well’s production on the geostress in the infill well area.It is suggested that with the increase of production time,normal fault stress state and horizontal stress deflection will occur.The smaller the parent well spacing and the longer the production time,the earlier the normal fault stress state appears and the larger the range.Based on the model,the fracture network morphology and construction parameters of infill wells are optimized.parentparentparentparent The results indicate that:1:A well spacing of 500 m achieves a Pareto optimum between“full reserve coverage”and“stress barrier”;2:A parent well recovery degree of 30%corresponds to the critical point of stress reversal,where the lateral deflection rate of the infill fracture is less than 8%and the SRV loss is minimized;3:6-cluster intensive completion with twice the liquid intensity increases the fracture complexity index by 1.7 times,enhances well group EUR by 15.4%,and reduces single-well cost by 22%.This research fills the theoretical gap in the collaborative optimization of“multi-parameter,multi-objective and multi-constraint”and provide parameter optimization basis for shale gas infill well development in China and help to improve the development efficiency and economic benefits.展开更多
Developing a chiral material as versatile and universal chiral stationary phase(CSP) for chiral separation in diverse chromatographic techniques simultaneously is of great significance.In this study,we demonstrated fo...Developing a chiral material as versatile and universal chiral stationary phase(CSP) for chiral separation in diverse chromatographic techniques simultaneously is of great significance.In this study,we demonstrated for the first time that a chiral metal-organic cage(MOC),[Zn_(6)M_(4)],as a universal chiral recognition material for both multi-mode high-performance liquid chromatography(HPLC) and capillary gas chromatography(GC) enantioseparation.Two novel HPLC CSPs with different bonding arms(CSP-A with a cationic imidazolium bonding arm and CSP-B with an alkyl chain bonding arm) were prepared by clicking of functionalized chiral MOC [Zn_(6)M_(4)] onto thiolated silica via thiol-ene click chemistry.Meanwhile,a capillary GC column statically coated with the chiral MOC [Zn_(6)M_(4)] was also fabricated.The results showed that the chiral MOC exhibits excellent enantioselectivity not only in normal phase HPLC(NP-HPLC) and reversed phase(RP-HPLC) but also in GC,and various racemates were well separated,including alcohols,diols,esters,ketones,ethers,amines,and epoxides.Importantly,CSP-A and CSP-B are complementary to commercially available Chiralcel OD-H and Chiralpak AD-H columns in enantioseparation,which can separate some racemates that could not be or could not well be separated by the two widely used commercial columns,suggesting the great potential of the two prepared CSPs in enantioseparation.This work reveals that the chiral MOC is potential versatile chiral recognition materials for both HPLC and GC,and also paves the way to expand the potential applications of MOCs.展开更多
Coke oven gas(COG)and natural gas(NG),both high-calorific by-products derived from the steel industry,have gained prominence as alternative fuels in the sintering process,thereby supporting dual objectives of emission...Coke oven gas(COG)and natural gas(NG),both high-calorific by-products derived from the steel industry,have gained prominence as alternative fuels in the sintering process,thereby supporting dual objectives of emission reduction and carbon neutrality.While existing research on hydrogen-rich gas injection has predominantly concentrated on conventional thin-bed sintering,investigations into its application within thick-bed sintering remain comparatively scarce.Thick-bed sintering,recognized for enhancing energy efficiency and increasing sinter output,encounters challenges such as uneven heat distribution and diminished permeability,which can negatively impact process efficiency and product quality.To address these issues,sinter pot experiments were conducted to assess the effects of NG and COG injection on thick-bed sintering performance.Findings reveal that NG injection in thick beds mirrors the behavior observed in conventional thin-bed sintering,effectively optimizing the process and achieving a carbon reduction potential exceeding 10%.In contrast,COG injection in thick-bed conditions demonstrates notable differences,substantially lowering the solid fuel consumption rate but detrimentally affecting sinter strength and overall production.However,by optimizing the timing of COG injection,it is feasible to improve sinter yield while concurrently reducing solid fuel usage.These outcomes provide valuable insights for the advancement of gas injection technologies in thick-bed sintering,thereby contributing to energy conservation and emission mitigation efforts within the sintering industry.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.12372351).
文摘In this study, to meet the development and application requirements for high-strength and hightoughness energetic structural materials, a representative volume element of a TA15 matrix embedded with a TaZrNb sphere was designed and fabricated via diffusion bonding. The mechanisms of the microstructural evolution of the TaZrNb/TA15 interface were investigated via SEM, EBSD, EDS, and XRD.Interface mechanical property tests and in-situ tensile tests were conducted on the sphere-containing structure, and an equivalent tensile-strength model was established for the structure. The results revealed that the TA15 titanium alloy and joint had high density and no pores or cracks. The thickness of the planar joint was approximately 50-60 μm. The average tensile and shear strengths were 767 MPa and 608 MPa, respectively. The thickness of the spherical joint was approximately 60 μm. The Zr and Nb elements in the joint diffused uniformly and formed strong bonds with Ti without forming intermetallic compounds. The interface exhibited submicron grain refinement and a concave-convex interlocking structure. The tensile fracture surface primarily exhibited intergranular fracture combined with some transgranular fracture, which constituted a quasi-brittle fracture mode. The shear fracture surface exhibited brittle fracture with regular arrangements of furrows. Internal fracture occurred along the spherical interface, as revealed by advanced in-situ X-ray microcomputed tomography. The experimental results agreed well with the theoretical predictions, indicating that the high-strength interface contributes to the overall strength and toughness of the sphere-containing structure.
文摘The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recognized to be limited at data boundaries and high frequencies,which can significantly reduce the signal-to-noise ratio(SNR).To solve this problem,a novel method synergistically integrating Principal Component Analysis(PCA)with SG filtering is proposed in this paper.This approach avoids the is-sue of excessive smoothing associated with larger window sizes.The proposed PCA-SG filtering algorithm was applied to a CO gas sensing system based on Cavity Ring-Down Spectroscopy(CRDS).The perform-ance of the PCA-SG filtering algorithm is demonstrated through comparison with Moving Average Filtering(MAF),Wavelet Transformation(WT),Kalman Filtering(KF),and the SG filter.The results demonstrate that the proposed algorithm exhibits superior noise reduction capabilities compared to the other algorithms evaluated.The SNR of the ring-down signal was improved from 11.8612 dB to 29.0913 dB,and the stand-ard deviation of the extracted ring-down time constant was reduced from 0.037μs to 0.018μs.These results confirm that the proposed PCA-SG filtering algorithm effectively improves the smoothness of the ring-down curve data,demonstrating its feasibility.
文摘Natural Gas Industry B创刊于2014年,是天然气工业杂志社与KeAi公司合作出版的国际OA期刊,在爱思唯尔旗下的Science Direct平台上双月出版。论文聚焦天然气、氢气、氦气、地热等地质能源,涵盖地质勘探、气藏开发、工程技术、储运利用、净化化工、产业趋势等专业方向。期刊服务全球天然气产业,并积极推动能源行业碳减排和低碳转型的发展。
文摘Natural Gas Industry B创刊于2014年,是天然气工业杂志社与KeAi公司合作出版的国际OA期刊,在爱思唯尔旗下的ScienceDirect平台上双月出版。论文聚焦天然气、氢气、氦气、地热等地质能源,涵盖地质勘探、气藏开发、工程技术、储运利用、净化化工、产业趋势等专业方向。期刊服务全球天然气产业,并积极推动能源行业碳减排和低碳转型的发展。
文摘Gas wells often encounter blockages in gas recovery channels owing to fluid accumulation during the later stages of extraction,which adversely affects subsequent recovery efforts.These undesirable conditions(e.g.,high condensate content,high temperature,and high salinity)often affect foaming agent performance.In this study,surfactants were screened using an airflow method that closely resembles field treatment method.Notably,alcohol ether sulfates(AE_(n)S)with various polyoxyethylene(EO)units demonstrated exceptional performance in terms of liquid unloading efficiency and foam stability.At 80℃,the unloading efficiency of AE_(n)S with two EO units(AE_(2)S)in a high NaCl mass concentration(up to 200 g/L)and high condensate volume fraction(up to 20%)reached 84%.The dynamic surface tension and interfacial tension measured at the same temperature were used to analyze the influence of the diffusion rate and interfacial characteristics on the AE_(n)S foam,while the viscosity and liquid film thickness measurements reflected the mechanical strength and liquid-carrying capacity.In addition,transmission electron microscopy(TEM)revealed that AE_(2)S formed“dendritic”micellar aggregates at a high NaCl mass concentration,which significantly enhanced the viscosity and stability of the foam.The interactions among AE_(n)S,NaCl,and H2O were analyzed using molecular dynamics,and it was confirmed from a molecular mechanics perspective that a stable structure can form among the three,contributing to the foam stability.These findings demonstrate the significant potential of the AE_(2)S foam for gas well deliquification.
基金supported by the National Natural Science Foundation of China(Grant No.52574278)the Xinjiang Uygur Autonomous Region Key R&D Program Project(Grant No.2024B01003).
文摘This paper examines how natural gas disperses vertically when high-pressure pipelines with large openings fail in unconfined environments,providing insight into hazardous gas cloud development and behavior.A comprehensive study was conducted using a full-scale field experiment(1,219 mm diameter,12 MPa pressure,100 mm aperture)combined with a validated computational fluid dynamics(CFD)numerical simulation model to systematically analyze the coupling effects of pipeline pressure and ambient wind speed.The results indicate that:(1)Pipeline pressure determines the vertical jet scale,where jet height is positively correlated with pressure;at 12 MPa,the maximum jet height reaches 69.4 m(approximately 2.65 times that at 4 MPa),and the lower explosive limit(LEL)cloud area follows a quadratic polynomial trend.(2)Ambient wind speed significantly alters the diffusion trajectory;at a wind speed of 10 m/s,the LEL gas cloud area expands by 1.69 times compared to calm conditions,while the jet height is suppressed to 29.9%of the calm wind value.(3)Our developed dynamic prediction model for the hazardous gas-cloud region achieves a determination coefficient of 0.975 and maintaining prediction errors maintained within approximately 12%.The proposed empirical correlations and dynamic prediction model provide essential quantitative data support for safety-distance design and emergency-response decision-making for high-pressure natural gas pipelines.
基金supported in part by the National Natural Science Foundation of China (62431018)in part by the Guangzhou Municipal Science and Technology Bureau (SL2023A04J00435)in part by the One Hundred Youth Project of Guangdong University of Technology (263113873)。
文摘Selectivity remains a significant challenge for gas sensors. In contrast to conventional gas sensors that depend solely on conductivity to detect gases, we exploited a single NiO-doped SnO_(2) sensor to simultaneously monitor transient changes in both sensor conductivity and temperature. The distinct response profiles of H_(2) and NH_(3) gases were attributed to differences in their redox rates and enthalpy changes during chemical reactions, which provided an opportunity for gas identification using machine learning(ML) algorithms. The test results indicate that preprocessing the extracted calorimetric and chemi-resistive parameters using the principal component analysis(PCA), followed by the application of ML classifiers for identification,enables a 100% accuracy for both target analytes. This work presents a facile gas identification method that enhances chiplevel sensor applications while minimizing the need for complex sensor arrays.
文摘Thermal power plants are the main contributors to greenhouse gas emissions.The prediction of the emission supports the decision makers and environmental sustainability.The objective of this study is to enhance the accuracy of emission prediction models,supporting more effective real-time monitoring and enabling informed operational decisions that align with environmental compliance efforts.This paper presents a data-driven approach for the accurate prediction of gas emissions,specifically nitrogen oxides(NOx)and carbon monoxide(CO),in natural gas power plants using an optimized hybrid machine learning framework.The proposed model integrates a Feedforward Neural Network(FFNN)trained using Particle Swarm Optimization to capture the nonlinear emission dynamics under varying gas turbine operating conditions.To further enhance predictive performance,the K-Nearest Neighbor(K-NN)algorithm serves as a post-processing method to enhance IPSO-FFNN predictions through adjustment and refinement,improving overall prediction accuracy,while Neighbor Component Analysis is used to identify and rank the most influential operational variables.The study makes a significant contribution through the combination of NCA feature selection with PSO global optimization,FFNN nonlinear modelling,and K-NN error correction into one unified system,which delivers precise emission predictions.The model was developed and tested using a real-world dataset collected from gas-fired turbine operations,with validated results demonstrating robust accuracy,achieving Root Mean Square Error values of 0.355 for CO and 0.368 for NOx.When benchmarked against conventional models such as standard FFNN,Support Vector Regression,and Long Short-Term Memory networks,the hybrid model achieved substantial improvements,up to 97.8%in Mean Squared Error,95%in Mean Absolute Error(MAE),and 85.19%in RMSE for CO;and 97.16%in MSE,93.4%in MAE,and 83.15%in RMSE for NOx.These results underscore the model’s potential for improving emission prediction,thereby supporting enhanced operational efficiency and adherence to environmental standards.
基金supported by the Program for National Natural Science Foundation of China(No.11675231)the Sichuan Science and Technology Program(Nos.2022YFG0263 and 2024NSFSC1097)the Scientific Research Starting Foundation for talents(Nos.21zx7109 and 22zx7175,24ycx1005).
文摘Single-crystal GaN epilayers were irradiated with heavy inert gas ions(2.3-MeV Ne^(8+),5.3-MeV Kr^(19+))to fluences ranging from 1.0×1.0^(11) to 1.0×1.0^(15)ions∕cm^(2).The strain-related damage accumulation versus ion fluences was studied using highresolution X-ray diffraction(HRXRD)and ultraviolet–visible(UV–Vis)spectroscopy.The results showed that the damage accumulation was mainly dominated by nuclear energy loss.When the ion fluence was less than∼0.055 displacement per atom(dpa),the lattice expansions and lattice strains markedly increased linearly with increasing ion fluences,accompanied by a slow enhancement in the dislocation densities,distortion parameters,and Urbach energy for both ion irradiations.Above this fluence(∼0.055 dpa),the lattice strains presented a slight increase,whereas a remarkable increase was observed in the dislocation densities,distortion parameters,and Urbach energy with the ion fluences after both ion irradiations.∼0.055 dpa is the threshold ion fluence for defect evolution and lattice damage related to strain.The mechanisms underlying the damage accumulation are discussed in detail.
基金funded by the Science and Technology Vice President Project in Changping District,Beijing(Project Name:Research on multi-scale optimization and intelligent control technology of integrated energy systemProject number:202302007013).
文摘The critical components of gas turbines suffer from prolonged exposure to factors such as thermal oxidation,mechanical wear,and airflow disturbances during prolonged operation.These conditions can lead to a series of issues,including mechanical faults,air path malfunctions,and combustion irregularities.Traditional modelbased approaches face inherent limitations due to their inability to handle nonlinear problems,natural factors,measurement uncertainties,fault coupling,and implementation challenges.The development of artificial intelligence algorithms has provided an effective solution to these issues,sparking extensive research into data-driven fault diagnosis methodologies.The review mechanism involved searching IEEE Xplore,ScienceDirect,and Web of Science for peerreviewed articles published between 2019 and 2025,focusing on multi-fault diagnosis techniques.A total of 220 papers were identified,with 123 meeting the inclusion criteria.This paper provides a comprehensive review of diagnostic methodologies,detailing their operational principles and distinctive features.It analyzes current research hotspots and challenges while forecasting future trends.The study systematically evaluates the strengths and limitations of various fault diagnosis techniques,revealing their practical applicability and constraints through comparative analysis.Furthermore,this paper looks forward to the future development direction of this field and provides a valuable reference for the optimization and development of gas turbine fault diagnosis technology in the future.
基金supported by National Natural Science Foundation of China(No.42376217)Fundamental Research Funds for the Central Universities of China(No.3-7-10-2025-03)National Key Research and Development Program of China(No.2024YFC2814702).
文摘The Dongsha area,a key target for gas hydrate exploration,is influenced by multiple factors,including sedimentary processes and the paleoenvironment,which play critical roles in gas hydrate formation.To elucidate the coupling among sedimentary processes,paleoenvironment,and gas hydrate accumulation,this study investigates the Site DS-W16 using particle size analysis,biological component content,and geochemistry data.Oxygen isotope data from foraminifera and biostratigraphic evidence indicate that sedimentation at the bottom of core interval from Site DS-W16 began during MIS 11(Marine isotope stage).The sedimentation dynamics of the studied layers are complex,involving gravity flows,traction currents,and suspended deposition.Organic matter shows a significant correlation with transgressive-regressive cycle.The site DS-W16 contains two distinct gas hydrate reservoirs:a shallow reservoir(10-24 mbsf)and a deep reservoir(below 182 mbsf).The paleomarine environment influences gas hydrate accumulation by altering sedimentary processes and sediment characteristics,especially the distribution of biological components.Both shallow and deep gas hydrate reservoirs formed under dynamic conditions dominated by traction currents and are characterized by a higher abundance of foraminifera.Sedimentary layers rich in foraminifera and modified by traction currents represent key intervals for preferential gas hydrate accumulation.
基金financial support provided by the Natural Science Foundation of Hebei Province,China(No.E2024105036)the Tangshan Talent Funding Project,China(Nos.B202302007 and A2021110015)+1 种基金the National Natural Science Foundation of China(No.52264042)the Australian Research Council(No.IH230100010)。
文摘Automated classification of gas flow states in blast furnaces using top-camera imagery typically demands a large volume of labeled data,whose manual annotation is both labor-intensive and cost-prohibitive.To mitigate this challenge,we present an enhanced semi-supervised learning approach based on the Mean Teacher framework,incorporating a novel feature loss module to maximize classification performance with limited labeled samples.The model studies show that the proposed model surpasses both the baseline Mean Teacher model and fully supervised method in accuracy.Specifically,for datasets with 20%,30%,and 40%label ratios,using a single training iteration,the model yields accuracies of 78.61%,82.21%,and 85.2%,respectively,while multiple-cycle training iterations achieves 82.09%,81.97%,and 81.59%,respectively.Furthermore,scenario-specific training schemes are introduced to support diverse deployment need.These findings highlight the potential of the proposed technique in minimizing labeling requirements and advancing intelligent blast furnace diagnostics.
基金provided by the Guangdong Province Low-Carbon Fragrant Rice Cultivation Demonstration Project,China(F23032)。
文摘As the global leader in rice production,China's paddy fields contribute substantially to greenhouse gas emissions through methane(CH_(4))and nitrous oxide(N_(2)O)releases.Aromatic rice cultivation practices have been optimized to enhance the aroma,so the relationship between its cultivation and greenhouse gas emissions from paddy fields is unclear.To investigate how aroma-enhancing cultivation practices drive microbial community dynamics in aromatic rice paddies and their implications for greenhouse gas emissions,a two-year experiment in five ecological locations(Xingning,Nanxiong,Conghua,Luoding,and Zengcheng)compared two farming practices:partial organic substitution for inorganic fertilizers combined with water-saving irrigation(IOF+W)and traditional cultivation(CK).The CH_(4)and N_(2)O emissions,soil microbial composition and function,global warming potential(GWP),nitrogen use efficiency,yield,and the content of 2-acetyl-1-pyrroline(2-AP)were measured and analyzed.The main purpose was to investigate the impact of IOF+W on CH_(4)and N_(2)O emissions and their relationship with soil microorganisms.The results showed that IOF+W significantly reduced CH_(4)emission fluxes and totals(36.95%)and GWP(31.29%),while significantly increasing N_(2)O emission fluxes and totals(14.82%).The soil microbial community structure was reshaped by the IOF+W treatment,which suppressed methanogens but enhanced the abundances of nitrifying and denitrifying bacteria.Key enzymatic activities involved in CH_(4)production,such as methyl-coenzyme M reductase,formylmethanofuran dehydrogenase,and methyltransferase,decreased.In contrast,the activity of the key CH_(4)-oxidizing enzyme methanol dehydrogenase increased.This shift led to an overall attenuation of the CH_(4)production metabolism while enhancing the CH_(4)oxidation metabolism.In addition,the activities of pivotal enzymes involved in denitrification and nitrification were improved,thus enhancing nitrogen nitrification and denitrification metabolism.Moreover,the IOF+W treatment significantly increased nitrogen use efficiency(47.83%),yield(14.77%),and 2-AP content(13.78%).Therefore,the IOF+W treatment demonstrated good efficacy as a sustainable strategy for achieving productive,green,resource-efficient,and premium-quality aromatic rice cultivation in South China.
文摘As the primary functional component of a fusion reactor,the fusion blanket pebble bed,composed of numerous particles,is crucial for tritium breeding,neutron multiplication,and radiation shielding.Particles within tritium-breeding pebble beds are subjected to prolonged neutron irradiation,high thermal loads,and strong magnetic fields in fusion environments.Such conditions render them susceptible to pulverization and fragmentation.The resulting fragments and powders migrate and are deposited into the gas channel,driven by the purge gas.The reduction in the effective flow area of the gas increases the flow resistance,resulting in tritium retention,degraded heat transfer,and other adverse effects.These conditions impair the thermodynamic properties of the pebble beds and hinder the self-maintenance of tritium.Limited information exists on powder migration and clogging mechanisms in fusion blanket pebble beds,particularly under diverse physical conditions.The aim of this study was to use a computational fluid dynamics model coupled with the discrete element method(CFD-DEM)to numerically explore powder migration and clogging in pebble beds.The model considers factors such as breeder orientation,purge velocity,powder size distribution,and friction coefficient.We propose two migration and clogging mechanisms.One involves powder with a large particle size,and the other does not.The results indicate that the powder migration velocity progresses through three stages:rapid decay,linear decay,and stability.Pebble-bed clogging manifests in two forms:extensive superficial clogging and uniform internal clogging.Two fitted curves were used to depict the migration and clogging tendencies.The powder size distribution significantly influenced the powder migration.The breeder orientation,powder size,and friction coefficient affected the distribution of the clogging powders.However,the impact of the purge velocity on powder migration and clogging in pebble beds was limited,and this effect varied significantly with different particle size ratios.Based on the analysis,a formula is proposed to characterize the behavior of the powder in the pebble beds.The results of this study can aid in analyzing and predicting powder dynamics in pebble beds.
文摘The shale gas development in China faces challenges such as complex reservoir conditions and high development costs.Based on the pore pressure and geostress coupling theory,this paper studies the geostress evolution laws and fracture network characteristics of shale gas infill wells.A mechanism model of CN platform logging data and geomechanical parameters is established to simulate the influence of parent well’s production on the geostress in the infill well area.It is suggested that with the increase of production time,normal fault stress state and horizontal stress deflection will occur.The smaller the parent well spacing and the longer the production time,the earlier the normal fault stress state appears and the larger the range.Based on the model,the fracture network morphology and construction parameters of infill wells are optimized.parentparentparentparent The results indicate that:1:A well spacing of 500 m achieves a Pareto optimum between“full reserve coverage”and“stress barrier”;2:A parent well recovery degree of 30%corresponds to the critical point of stress reversal,where the lateral deflection rate of the infill fracture is less than 8%and the SRV loss is minimized;3:6-cluster intensive completion with twice the liquid intensity increases the fracture complexity index by 1.7 times,enhances well group EUR by 15.4%,and reduces single-well cost by 22%.This research fills the theoretical gap in the collaborative optimization of“multi-parameter,multi-objective and multi-constraint”and provide parameter optimization basis for shale gas infill well development in China and help to improve the development efficiency and economic benefits.
基金supported by the National Natural Science Foundation of China (Nos.22064020,22364022,and 22174125)the Applied Basic Research Foundation of Yunnan Province (Nos.202101AT070101 and 202201AT070029)。
文摘Developing a chiral material as versatile and universal chiral stationary phase(CSP) for chiral separation in diverse chromatographic techniques simultaneously is of great significance.In this study,we demonstrated for the first time that a chiral metal-organic cage(MOC),[Zn_(6)M_(4)],as a universal chiral recognition material for both multi-mode high-performance liquid chromatography(HPLC) and capillary gas chromatography(GC) enantioseparation.Two novel HPLC CSPs with different bonding arms(CSP-A with a cationic imidazolium bonding arm and CSP-B with an alkyl chain bonding arm) were prepared by clicking of functionalized chiral MOC [Zn_(6)M_(4)] onto thiolated silica via thiol-ene click chemistry.Meanwhile,a capillary GC column statically coated with the chiral MOC [Zn_(6)M_(4)] was also fabricated.The results showed that the chiral MOC exhibits excellent enantioselectivity not only in normal phase HPLC(NP-HPLC) and reversed phase(RP-HPLC) but also in GC,and various racemates were well separated,including alcohols,diols,esters,ketones,ethers,amines,and epoxides.Importantly,CSP-A and CSP-B are complementary to commercially available Chiralcel OD-H and Chiralpak AD-H columns in enantioseparation,which can separate some racemates that could not be or could not well be separated by the two widely used commercial columns,suggesting the great potential of the two prepared CSPs in enantioseparation.This work reveals that the chiral MOC is potential versatile chiral recognition materials for both HPLC and GC,and also paves the way to expand the potential applications of MOCs.
基金supported by the National Natural Science Foundation of China(Grant No.52474347)Postdoctoral Science Foundation of China(Grant No.2024T171095)the Fundamental Research Funds for the Central Universities(Grant No.2024CDJXY003).
文摘Coke oven gas(COG)and natural gas(NG),both high-calorific by-products derived from the steel industry,have gained prominence as alternative fuels in the sintering process,thereby supporting dual objectives of emission reduction and carbon neutrality.While existing research on hydrogen-rich gas injection has predominantly concentrated on conventional thin-bed sintering,investigations into its application within thick-bed sintering remain comparatively scarce.Thick-bed sintering,recognized for enhancing energy efficiency and increasing sinter output,encounters challenges such as uneven heat distribution and diminished permeability,which can negatively impact process efficiency and product quality.To address these issues,sinter pot experiments were conducted to assess the effects of NG and COG injection on thick-bed sintering performance.Findings reveal that NG injection in thick beds mirrors the behavior observed in conventional thin-bed sintering,effectively optimizing the process and achieving a carbon reduction potential exceeding 10%.In contrast,COG injection in thick-bed conditions demonstrates notable differences,substantially lowering the solid fuel consumption rate but detrimentally affecting sinter strength and overall production.However,by optimizing the timing of COG injection,it is feasible to improve sinter yield while concurrently reducing solid fuel usage.These outcomes provide valuable insights for the advancement of gas injection technologies in thick-bed sintering,thereby contributing to energy conservation and emission mitigation efforts within the sintering industry.
