The results stemming from the calculation of heat transfer in torch furnaces by the laws, relating to radiation from solid surfaces and gas volumes are analyzed. The article presents the laws for radiation from gas vo...The results stemming from the calculation of heat transfer in torch furnaces by the laws, relating to radiation from solid surfaces and gas volumes are analyzed. The article presents the laws for radiation from gas volumes and the procedure for calculating heat transfer in torch furnaces, fire boxes, and combustion chambers, elaborated on their basis. The example of heat transfer calculation in a torch furnace is given, and it is significantly non-uniform in nature. Non-uniformity of heat flux distribution on heating surfaces is given. According to the results of calculations, a new furnace is designed to decrease the non-uniformity of ingot heating, fuel rate, and increase the furnace capacity. The calculation results of the distribution of heat fluxes on the heating surfaces are given in changing torch geometric dimensions. These results are confirmed by experimental studies.展开更多
In order to study the influence of gas-liquid two-phase flow on the performance and internal flow field of a centrifugal pump,the steady three-dimensional flow with different gas volume fractions was simulated by appl...In order to study the influence of gas-liquid two-phase flow on the performance and internal flow field of a centrifugal pump,the steady three-dimensional flow with different gas volume fractions was simulated by applying the Reynolds-average N-S equation and mixture gas-liquid two-phase flow model,and the compressibility of gas was taken into consideration in the simulation. Then the centrifugal pump characteristic and the gas distribution law in different gas volume fractions were analyzed. The computational results show that gas volume fraction has a certain influence on the performance of the centrifugal pump,and the efficiency and head of the pump are on the decline with the increase of it.Static pressure in the impeller increases in the radial direction,but the pressure gradient in the flow direction is different under the different gas volume fractions. The gas volume is distributed mainly in the ipsilateral direction of impeller back shroud in the flow channel of the volute. On the suction side of the blade inlet there is an obvious low-pressure area,which causes bubbles agglutination and higher gas volume fraction. With the gas entering passage flow,gas volume fraction in the suction decreases and the pressure surface rises gradually. Higher gas volume fraction causes air blocking phenomenon in the flow passage and the discharge capacity reduces. The increase of gas volume makes the turbulent motion within the impeller more and more intense,which leads to more and more energy loss.展开更多
This research was conducted to investigate the effects of three heating systems on cucumber yield,and cost and gas volume consumed in greenhouses located in Varamin region,Tehran province,Iran.Conventional heating sys...This research was conducted to investigate the effects of three heating systems on cucumber yield,and cost and gas volume consumed in greenhouses located in Varamin region,Tehran province,Iran.Conventional heating systems used in the greenhouses are:central heating system(including boiler+hot water pipes),gas heater system(including double-walled tank+blower)and traditional furnace system(including ignition chamber+torch+pipes carrying a mixture of hot air and flammable gases).The study was carried out for two consecutive cucumber cultivation periods from January to June.Average values of crop yield,volume and cost of gas consumed were determined separately for each heating system.Results of the study indicated that the central heating system with the highest crop yield(295 t/ha),and the lowest volume(100,000 m^(3)/ha)and cost(840 USD/ha)of gas consumed was the best and most suitable heating system for greenhouses producing cucumbers in Varamin region and other regions with the same and similar climate as well as regions with active greenhouses in the cold season.展开更多
This study uses the PΔV term in the ideal gas equation PΔV = nRΔT to show how the 1-degree temperature increase that expands the occupied volume of a gas by ΔV against constant pressure P also causes the system to...This study uses the PΔV term in the ideal gas equation PΔV = nRΔT to show how the 1-degree temperature increase that expands the occupied volume of a gas by ΔV against constant pressure P also causes the system to increase its entropy by ΔS. As the volume available to a gas sample increases, the locations for disordered molecular relocation also increase. The causal agent linking a volume increase ΔV and an entropy increase ΔS is absolute temperature T measured in kelvin units. Since a volume increase is empirically observable while an increase in randomized molecular disorder is not, a per-kelvin increase in gas volume provides a method for estimating entropy increase. Both volume and entropy are extensive variables dependent upon the number of molecules in the system. Both are deemed to be at their absolute minima at the absolute zero of temperature. This study provides an insight into how a per-kelvin temperature increase causes both a linear increase in gas volume and a linear increase in gas entropy. When people talk about randomized disorder without specifying absolute temperature and molecule-count for the system, they are discussing a concept other than thermodynamic entropy.展开更多
Tight gas reservoirs are often characterized by pronounced heterogeneity and poor continuity,resulting in wide variability in production enhancement and net present value(NPV)for different geological parameter combina...Tight gas reservoirs are often characterized by pronounced heterogeneity and poor continuity,resulting in wide variability in production enhancement and net present value(NPV)for different geological parameter combinations(see e.g.,the Ordos Basin).The conditions governing geological adaptability remain insufficiently defined.To address these challenges,this study integrates large-volume hydraulic fracturing,numerical production simulation,and economic evaluation to elucidate the mechanisms by which large-scale fracturing enhances fracture parameters in tight gas formations.The analysis reveals that,for identical proppant and fluid volumes,increasing the fracturing injection rate leads to longer and taller fractures.Over the same production period,this results in a more rapid decline in average reservoir pressure and a higher cumulative gas output.Through simulations conducted at varying injection rates across 11 production wells in the target block,the study demonstrates that large-volume fracturing can effectively connect otherwise isolated tight gas pockets,enlarge the drainage area,and substantially boost individual well production.A comparative assessment of simulation outcomes and economic performance shows that large-volume fracturing significantly improves gas recovery and NPV compared to conventional smaller-scale treatments.The study identifies the key geological indicators that influence differences in production enhancement and economic returns between small-and large-volume fracturing strategies.Based on these findings,a decision matrix is developed(utilizing a trapezoidal membership function)to evaluate the geological suitability of large-volume fracturing in tight gas reservoirs.This matrix is applied to the 11 target wells,with the evaluation results aligning well with those obtained from numerical simulations.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
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
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
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 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
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
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
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
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
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
文摘The results stemming from the calculation of heat transfer in torch furnaces by the laws, relating to radiation from solid surfaces and gas volumes are analyzed. The article presents the laws for radiation from gas volumes and the procedure for calculating heat transfer in torch furnaces, fire boxes, and combustion chambers, elaborated on their basis. The example of heat transfer calculation in a torch furnace is given, and it is significantly non-uniform in nature. Non-uniformity of heat flux distribution on heating surfaces is given. According to the results of calculations, a new furnace is designed to decrease the non-uniformity of ingot heating, fuel rate, and increase the furnace capacity. The calculation results of the distribution of heat fluxes on the heating surfaces are given in changing torch geometric dimensions. These results are confirmed by experimental studies.
基金The National Natural Science Foundation of China(51679196,51879216,51339005)
文摘In order to study the influence of gas-liquid two-phase flow on the performance and internal flow field of a centrifugal pump,the steady three-dimensional flow with different gas volume fractions was simulated by applying the Reynolds-average N-S equation and mixture gas-liquid two-phase flow model,and the compressibility of gas was taken into consideration in the simulation. Then the centrifugal pump characteristic and the gas distribution law in different gas volume fractions were analyzed. The computational results show that gas volume fraction has a certain influence on the performance of the centrifugal pump,and the efficiency and head of the pump are on the decline with the increase of it.Static pressure in the impeller increases in the radial direction,but the pressure gradient in the flow direction is different under the different gas volume fractions. The gas volume is distributed mainly in the ipsilateral direction of impeller back shroud in the flow channel of the volute. On the suction side of the blade inlet there is an obvious low-pressure area,which causes bubbles agglutination and higher gas volume fraction. With the gas entering passage flow,gas volume fraction in the suction decreases and the pressure surface rises gradually. Higher gas volume fraction causes air blocking phenomenon in the flow passage and the discharge capacity reduces. The increase of gas volume makes the turbulent motion within the impeller more and more intense,which leads to more and more energy loss.
基金the Agricultural Research,Education and Extension Organization(AREEO)。
文摘This research was conducted to investigate the effects of three heating systems on cucumber yield,and cost and gas volume consumed in greenhouses located in Varamin region,Tehran province,Iran.Conventional heating systems used in the greenhouses are:central heating system(including boiler+hot water pipes),gas heater system(including double-walled tank+blower)and traditional furnace system(including ignition chamber+torch+pipes carrying a mixture of hot air and flammable gases).The study was carried out for two consecutive cucumber cultivation periods from January to June.Average values of crop yield,volume and cost of gas consumed were determined separately for each heating system.Results of the study indicated that the central heating system with the highest crop yield(295 t/ha),and the lowest volume(100,000 m^(3)/ha)and cost(840 USD/ha)of gas consumed was the best and most suitable heating system for greenhouses producing cucumbers in Varamin region and other regions with the same and similar climate as well as regions with active greenhouses in the cold season.
文摘This study uses the PΔV term in the ideal gas equation PΔV = nRΔT to show how the 1-degree temperature increase that expands the occupied volume of a gas by ΔV against constant pressure P also causes the system to increase its entropy by ΔS. As the volume available to a gas sample increases, the locations for disordered molecular relocation also increase. The causal agent linking a volume increase ΔV and an entropy increase ΔS is absolute temperature T measured in kelvin units. Since a volume increase is empirically observable while an increase in randomized molecular disorder is not, a per-kelvin increase in gas volume provides a method for estimating entropy increase. Both volume and entropy are extensive variables dependent upon the number of molecules in the system. Both are deemed to be at their absolute minima at the absolute zero of temperature. This study provides an insight into how a per-kelvin temperature increase causes both a linear increase in gas volume and a linear increase in gas entropy. When people talk about randomized disorder without specifying absolute temperature and molecule-count for the system, they are discussing a concept other than thermodynamic entropy.
基金open fund of Hubei Key Laboratory of Oil and Gas Drilling and Production Engineering(Yangtze University)YQZC202404.
文摘Tight gas reservoirs are often characterized by pronounced heterogeneity and poor continuity,resulting in wide variability in production enhancement and net present value(NPV)for different geological parameter combinations(see e.g.,the Ordos Basin).The conditions governing geological adaptability remain insufficiently defined.To address these challenges,this study integrates large-volume hydraulic fracturing,numerical production simulation,and economic evaluation to elucidate the mechanisms by which large-scale fracturing enhances fracture parameters in tight gas formations.The analysis reveals that,for identical proppant and fluid volumes,increasing the fracturing injection rate leads to longer and taller fractures.Over the same production period,this results in a more rapid decline in average reservoir pressure and a higher cumulative gas output.Through simulations conducted at varying injection rates across 11 production wells in the target block,the study demonstrates that large-volume fracturing can effectively connect otherwise isolated tight gas pockets,enlarge the drainage area,and substantially boost individual well production.A comparative assessment of simulation outcomes and economic performance shows that large-volume fracturing significantly improves gas recovery and NPV compared to conventional smaller-scale treatments.The study identifies the key geological indicators that influence differences in production enhancement and economic returns between small-and large-volume fracturing strategies.Based on these findings,a decision matrix is developed(utilizing a trapezoidal membership function)to evaluate the geological suitability of large-volume fracturing in tight gas reservoirs.This matrix is applied to the 11 target wells,with the evaluation results aligning well with those obtained from numerical simulations.
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.
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 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.
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.
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.
