To analyze the correlation between the input energy parameters(V_(E))and typical intensity measures(IMs)of offshore ground motions,based on 273 earthquake events recorded by the K-NET in Japan,892 offshore ground moti...To analyze the correlation between the input energy parameters(V_(E))and typical intensity measures(IMs)of offshore ground motions,based on 273 earthquake events recorded by the K-NET in Japan,892 offshore ground motion records with moment magnitudes from 4.0 to 7.0 were used in this study.Residuals obtained through a ground motion model were calculated and analyzed for the correlation between V_(E) and amplitude,duration,frequency content and cumulative IMs.The results indicate that PGV and PGD have strong correlation with the V_(E)(T>0.2 s and T>0.4 s),the duration IMs have weakly negative correlation with the V_(E),Sd_(1) has a strong correlation with the V_(E) in the periods of T>0.4 s,T_(g) has a weak correlation with V_(E) and the cumulative IMs have strong correlation with the V_(E).The parametric predictive equations between typical IMs and V_(E) was proposed,and the differences between the prediction equations from the onshore ground motion records were compared.The differences in parametric predicted equations between offshore and onshore ground motions were confirmed in this study.Proposed correlation equations can be applied to offshore probabilistic seismic hazard analysis and the selection of ground motion records by generalized conditional intensity measures.展开更多
Production,processing and transportation of natural gases can be significantly affected by clathrate hydrates.Knowing the gas analysis is crucial to predict the right conditions for hydrate formation.Nevertheless,Katz...Production,processing and transportation of natural gases can be significantly affected by clathrate hydrates.Knowing the gas analysis is crucial to predict the right conditions for hydrate formation.Nevertheless,Katz gas gravity method can be used for initial estimation of hydrate formation temperature （HFT） under the circumstances of indeterminate gas composition.So far several correlations have been proposed for gas gravity method,in which the most accurate and reliable one has belonged to Bahadori and Vuthaluru.The main objective of this study is to present a simple and yet accurate correlation for fast prediction of sweet natural gases HFT based on the fit to Katz gravity chart.By reviewing the error analysis results,one can discover that the new proposed correlation has the best estimation capability among the widely accepted existing correlations within the investigated range.展开更多
In this article, the author obtains the large deviation principles for the empirical correlation coefficient of two Gaussian random variables X and Y. Especially, when considering two independent Gaussian random varia...In this article, the author obtains the large deviation principles for the empirical correlation coefficient of two Gaussian random variables X and Y. Especially, when considering two independent Gaussian random variables X, Y with the means EX, EY （both known）, wherein the author gives two kinds of different proofs and gets the same results.展开更多
Recently, introducing a transition predicting model into the Reynolds averaged Navier-Stokes （RANS） environment has been paid more and more attention. Langtry proposed a correlation-based transition model in 2006, w...Recently, introducing a transition predicting model into the Reynolds averaged Navier-Stokes （RANS） environment has been paid more and more attention. Langtry proposed a correlation-based transition model in 2006, which was built strictly on local variables. However, two core correlations in the model had not been published until 2009. In this paper, after considerable analyses and discussions of the mechanism of this transition model and a series of numerical validations in the skin friction coefficient of flat plate boundary layers, a new correlation based on free-stream turbulence intensity is developed, and the empirical correlation of the transition onset momentum thickness Reynold number aiming at the hypersonic transition is improved. Low-speed/transonic airfoils and a hypersonic double wedge fiat are tested to prove the reliability and practicability of this correlation.展开更多
The comprehensive evaluation method of enterprise core competitiveness is proposed by combining rough sets and gray correlation theories. Firstly,the initial index is screened through rough set attribute reduction alg...The comprehensive evaluation method of enterprise core competitiveness is proposed by combining rough sets and gray correlation theories. Firstly,the initial index is screened through rough set attribute reduction algorithm,and the evaluation weight of each index is obtained through the rough set theory. Then,based on the gray correlation theory, an evaluation model is built for empirical analysis. The 30 financial institutions on the Yangtze River Delta are examined from the theoretical and empirical perspective.The result demonstrates not only the feasibility of rough set attribute reduction algorithm in the core competitiveness index system of the financial institution,but also the accuracy of the combination of these two methods in the comprehensive evaluation of corporate core competitiveness.展开更多
The overall heat transfer coefficient(OHTC)of rock fractures is a fundamental parameter for characterizing the heat transfer behavior of rock fractures in hot dry rock(HDR)geothermal mining.Although a number of practi...The overall heat transfer coefficient(OHTC)of rock fractures is a fundamental parameter for characterizing the heat transfer behavior of rock fractures in hot dry rock(HDR)geothermal mining.Although a number of practical formulae for heat transfer coefficients have been developed in the literature,there is still no widely accepted analytical solution.This paper constructs highly accurate analytical solutions for the temperatures of the inner fracture wall and the fluid.Then they are employed to develop new definition-based formulae(formula A and its simplification formula B)of the OHTC,which are well validated by the experimental and numerical simulation results.An empirical correlation formula of heat transfer coefficient is proposed based on the definition-based formulae which can be directly used in the numerical simulations of heat transfer in rock fractures.A site-scale application example of numerical simulation also demonstrates the effectiveness of the empirical correlation formula.展开更多
Uniaxial compressive strength(UCS)is a significant mechanical measure in rock engineering,key for classifying rock masses,conducting stability assessments,and guiding design processes.Over the past five decades,numero...Uniaxial compressive strength(UCS)is a significant mechanical measure in rock engineering,key for classifying rock masses,conducting stability assessments,and guiding design processes.Over the past five decades,numerous techniques and devices have emerged for UCS measurement.This paper presents a comprehensive literature review of existing methodologies and advancements in UCS testing,examining the theoretical foundations,testing equipment,data processing techniques,and criteria for selecting appropriate UCS testing methods.Additionally,the study highlights a shift toward automated,precise,and computational approaches with multiple inputs(i.e.multiple regression,machine learning,ML)for UCS prediction.Approximately 221 articles published by various researchers between 2000 and 2024 related to ML were reviewed,focusing on the application of ML models,including artificial neural networks(ANNs),adaptive-network-based fuzzy inference system(ANFIS),random forest(RF),support vector machine(SVM),and extreme gradient boosting(XGBoost),in UCS prediction.The review also observed the growing use of hybrid models integrating ML with optimization techniques,significantly improving UCS estimation.Numerous empirical correlations,both direct and indirect,have been established in the past several years based on the physical properties of rocks.However,utilizing these proposed equations to reliably estimate UCS remains challenging due to the variability in lithology,rock origin,and other factors.This study systematically presents the established correlation expressions,considering their lithology,the number of samples used to establish the expressions,the coefficient of determination(R2),and the locations.This allows geologists and engineers to easily apply these established expressions in situations where direct estimation is not possible,enabling them to approximate UCS results.展开更多
Based on the demands of compact heat exchangers and micro cooling channels applied for aviation thermal protection, the flow resistance characteristics of aviation kerosene RP-3 were experimentally studied in a vertic...Based on the demands of compact heat exchangers and micro cooling channels applied for aviation thermal protection, the flow resistance characteristics of aviation kerosene RP-3 were experimentally studied in a vertically downward circular miniature tube with an inner diameter of 1.86 mm at supercritical pressures and constant heat fluxes. A long and short tube method was used to accurately calculate the frictional pressure drop, and experimental conditions are supercritical pressures of 4 MPa, mass flow rates of 2–4 g/s(i.e., mass fluxes of 736–1472 kg/(m^(2)·s)), heat fluxes of 100–500 kW/m^(2), and inlet temperatures of 373–673 K. Results show that the sharp variations of thermophysical properties, especially density, have significant influences on frictional resistances.Generally, the frictional pressure drop and the friction factor increase with increasing inlet temperatures, and this trend speeds up in the relatively high-temperature region. However, the friction factor has a sudden decline when the fuel outlet temperature exceeds the pseudo-critical temperature.The frictional pressure drop and the friction factor basically remain unchanged with increasing heat flux when the inlet temperature is relatively low, but increase quickly when the inlet temperature is relatively high. Besides, a larger mass flux yields a higher pressure drop but does not necessarily yield a higher friction factor. Finally, an empirical friction factor correlation is proposed and shows better predictive performance than those of previous models.展开更多
It has been known that the productivity of artesian wells is strongly dependent on the rheological properties of crude oils. This work targets two deep artesian wells(>5000 m) that are producing heavy crude oil. Th...It has been known that the productivity of artesian wells is strongly dependent on the rheological properties of crude oils. This work targets two deep artesian wells(>5000 m) that are producing heavy crude oil. The impacts of well conditions including temperature, pressure and shear rate, on the crude oil rheology were comprehensively investigated and correlated using several empirical rheological models. The experimental data indicate that this heavy oil is very sensitive to temperature as result of microstructure change caused by hydrogen bonding. The rheological behavior of the heavy oil is also significantly impacted by the imposed pressure, i.e., the viscosity flow activation energy(Eμ) gently increases with the increasing pressure. The viscosity–shear rate data are well fitted to the power law model at low temperature. However, due to the transition of fluid feature at high temperature(Newtonian fluid), the measured viscosity was found to slightly deviate from the fitting data. Combining the evaluated correlations, the viscosity profile of the heavy crude oil in these two deep artesian wells as a function of well depth was predicted using the oilfield producing data.展开更多
A new approach is demonstrated in which soft experimentation can be performed for MMP measurements, thus replacing the common practice of slim tube displacement laboratory experiments. Recovery potential from oil rese...A new approach is demonstrated in which soft experimentation can be performed for MMP measurements, thus replacing the common practice of slim tube displacement laboratory experiments. Recovery potential from oil reservoirs by miscible flue gas injection was studied by slim tube and field-scale numerical simulation using two flue gases and seven crude oils sampled at different depths in three candidate reservoirs. The soft experimentations were conducted using Eclipse300<sup>TM</sup>, a three-phase compositional simulator. This study investigates minimum miscibility pressure (MMP), a significant miscible gas injection project screening tool. Successful design of the project is contingent to the accurate determination of the MMP. This study evaluates effects of important factors such as injection pressure, oil component composition, and injection gas composition on the MMP and recovery efficiency for slim tube and field-scale displacements. Two applicable MMP correlations were used for comparison and validation purposes.展开更多
This work systematically simulates the external mass transfer from/to a spherical drop and solid particle suspended in a nonlinear uniaxial extensional creeping flow.The mass transfer problem is governed by three dime...This work systematically simulates the external mass transfer from/to a spherical drop and solid particle suspended in a nonlinear uniaxial extensional creeping flow.The mass transfer problem is governed by three dimensionless parameters:the viscosity ratio(λ),the Peclet number(Pe),and the nonlinear intensity of the flow(E).The existing mass transfer theory,valid for very large Peclet numbers only,is expanded,by numerical simulations,to include a much larger range of Peclet numbers(1≤Pe≤105).The simulation results show that the dimensionless mass transfer rate,expressed as the Sherwood number(5 h),agrees well with the theoretical results at the convection-dominated regime(Pe>103).Only when E>5/4,the simulated Sh for a solid sphere in the nonlinear uniaxial extensional flow is larger than theoretical results because the theory neglects the effect of the vortex formed outside the particle on the rate of mass transfer.Empirical correlations are proposed to predict the influence of the dimensionless governing parameters(λ,Pe,E)on the Sherwood number(Sh).The maximum deviations of all empirical correlations are less than 15%when compared to the numerical simulated results.展开更多
In the absence of a simple technique to predict convection heat transfer on BIPV （building integrated photovoltaic） surfaces, a mobile probe with two thermocouples was designed. Thermal boundary layers on vertical f...In the absence of a simple technique to predict convection heat transfer on BIPV （building integrated photovoltaic） surfaces, a mobile probe with two thermocouples was designed. Thermal boundary layers on vertical flat surfaces ofa PV （photovoltaic） and a metallic plate were traversed. The plate consisted of twelve heaters where heat flux and surface temperature were controlled and measured. Uniform heat flux condition was developed on the heaters to closely simulate non-uniform temperature distribution on vertical PV modules. The two thermocouples on the probe measured local air temperature and contact temperature with the wall surface. Experimental results were presented in the forms of local Nusselt numbers versus Rayleigh numbers ＂Nu = a＇（Ra）b＇＇, and surface temperature versus dimensionless height （Ts - T∞ = c.（z/h）d）. The constant values for ＂a＂, ＂b＂, ＂c＂ and ＂d＂ were determined from the best curve-fitting to the power-law relation. The convection heat transfer predictions from the empirical correlations were found to be in consistent with those predictions made by a number of correlations published in the open literature. A simple technique is then proposed to employ two experimental data from the probe to refine empirical correlations as the operational conditions change. A flexible technique to update correlations is of prime significance requirement in thermal design and operation of BIPV modules. The work is in progress to further extend the correlation to predict the combined radiation and convection on inclined PVs and channels.展开更多
The gas compressibility factor,also known as Z-factor,plays the determinative role for obtaining thermodynamic properties of gas reservoir.Typically,empirical correlations have been applied to determine this important...The gas compressibility factor,also known as Z-factor,plays the determinative role for obtaining thermodynamic properties of gas reservoir.Typically,empirical correlations have been applied to determine this important property.However,weak performance and some limitations of these correlations have persuaded the researchers to use intelligent models instead.In this work,prediction of Z-factor is aimed using different popular intelligent models in order to find the accurate one.The developed intelligent models are including Artificial Neural Network(ANN),Fuzzy Interface System(FIS)and Adaptive Neuro-Fuzzy System(ANFIS).Also optimization of equation of state(EOS)by Genetic Algorithm(GA)is done as well.The validity of developed intelligent models was tested using 1038 series of published data points in literature.It was observed that the accuracy of intelligent predicting models for Z-factor is significantly better than conventional empirical models.Also,results showed the improvement of optimized EOS predictions when coupled with GA optimization.Moreover,of the three intelligent models,ANN model outperforms other models considering all data and 263 field data points of an Iranian offshore gas condensate with R^(2) of 0.9999,while the R^(2) for best empirical correlation was about 0.8334.展开更多
This paper proposes a new signal noise level estimation approach by local regions. The estimated noise variance is applied as the threshold for an improved empirical mode decomposition（EMD） based signal denoising me...This paper proposes a new signal noise level estimation approach by local regions. The estimated noise variance is applied as the threshold for an improved empirical mode decomposition（EMD） based signal denoising method. The proposed estimation method can effectively extract the candidate regions for the noise level estimation by measuring the correlation coefficient between noisy signal and a Gaussian filtered signal. For the improved EMD based method, the situation of decomposed intrinsic mode function（IMFs） which contains noise and signal simultaneously are taken into account. Experimental results from two simulated signals and an X-ray pulsar signal demonstrate that the proposed method can achieve better performance than the conventional EMD and wavelet transform（WT） based denoising methods.展开更多
This paper presents a physical investigation and mathematical analysis on mechanical behavior of the regular jugged discontinuity.In particular,we focus on the creep property of structural plane with various slope ang...This paper presents a physical investigation and mathematical analysis on mechanical behavior of the regular jugged discontinuity.In particular,we focus on the creep property of structural plane with various slope angles under different normal stress through shear creep tests of structural plane under shear stresses.According to the test results,the shear creep property of structural plane was described and the creep velocity and long-term strength of the structural plane during shear creep were also investigated.An empirical formula is finally established to evaluate shear strength of discontinuity and a modified Burger model was proposed to represent the shear deformation property during creep.展开更多
Understanding the influencing mechanism of turbulent fluctuation on the ignition characteristics of millimeter coal particles is essential.In this work,to study the effect of turbulent fluctuation on ignition time,mil...Understanding the influencing mechanism of turbulent fluctuation on the ignition characteristics of millimeter coal particles is essential.In this work,to study the effect of turbulent fluctuation on ignition time,millimeter coal particles are subjected to a specific flow field,generated in a furnace with symmetric fans.A one-dimensional model with the new proposed correlation and the Ranz-Marshall(R-M)correlation for Nu(Nusselt number)is established to simulate the coal ignition process.In addition,the effects of fan speed,temperature,particle diameter,particle distance and coal type on the ignition time are investigated.It is found that an increase in fan speed from 0 to 3000 rpm leads to a particle Reynolds number Re_(p)increase from 0 to 22.5,and a turbulent particle Reynolds number Re_(t)*increase from 0 to 71.5.With a consideration of the fluctuation effect,the new correlation of Nu gives a better prediction of ignition time compared to the R-M correlation.Moreover,the ignition time is revealed to decrease with an increasing fan speed and an elevating temperature.While the ignition time shows merely an initial boost with enlarging particle distance,it exhibits a linearity with the term of particle diameter dp1.3-1.7 and Reynolds numbers(Nu*/Nu)-0.6(Nu*is turbulent Nusselt number).Based on this relationship,the difference of predicted ignition time is calculated at different Re_(p)and Re_(t)*.It is shown that at low Re_(p)or high Re_(t)*values,the new correlation should substitute for the R-M correlation.展开更多
The significance of gas compressibility factor in petroleum engineering encourages the researchers to employ the most accurate and precise methods for estimation of this factor.Commonly,empirical correlations due to t...The significance of gas compressibility factor in petroleum engineering encourages the researchers to employ the most accurate and precise methods for estimation of this factor.Commonly,empirical correlations due to their simplicity have been referred more than other approaches for prediction of Z-factor.There is no clear and reliable report to address an appropriate combination of correlation and mixing rule for each type of gas.In the present study,combination of several empirical correlations and mixing rules is examined and a decision tree is constructed to suggest best combination for each gas system.For this reason,2329 experimental data were used for analysis.According to the results,LelandeMueller mixing rule/Sanjari and Lay correlation is the best combination for sour and natural gas.Also,Van NesseAbbot mixing rule/HalleYarborough correlation,StewarteBurkhardteVoo mixing rule/Heidarian correlation and SattereCampbell mixing rule/Papay correlation are the most appropriate combination for gas condensate,binary and ternary mixtures respectively.For binary mixtures,a robust and novel empirical correlation was developed based on Kay mixing rule to estimate Z-factor.The results employed how good the new correlation is in agreement with the experimental data with significant R-squared 0.9843.展开更多
Throughflow design has the advantages of less time consumption and large optimization space,and thus is the corner stone of advanced design system of multi-stage axial-flow compressors.The majority of relevant studies...Throughflow design has the advantages of less time consumption and large optimization space,and thus is the corner stone of advanced design system of multi-stage axial-flow compressors.The majority of relevant studies were limited to the throughflow inverse designs,and quite few works have been till now devoted to the throughflow optimal designs.In this work,an automatic and rapid throughflow-based optimal design method is proposed for axial-flow compressors in which a throughflow inverse design solver is embedded in optimal genetic algorithm to improve the design efficiency of axial-flow compressor.Two types of design parameters in the throughflow inverse design of axial-flow compressors,i.e.,swirl and shroud curve,are simultaneously used to optimize both the blade shape and flow path.The proposed method is validated by the redesign optimization of the benchmark axial-flow compressor NASA Stage 35,and the CFD predictions show that the throughflow-based optimization leads to 1.18% efficiency benefit at design condition.The proposed method is then utilized to the two-dimensional throughflow optimal design of a large-scale 6.5-stage axial-flow industrial compressor.The optimal design results are confirmed by CFD predictions,indicating that the proposed method can effectively improve the design adiabatic efficiency of the compressors by 1.09% within a few minutes on desk-top computer.Two throughflow design implications are also obtained for advanced axial-flow industrial compressors.This work could enhance the capability of throughflow design method and has engineering application value to explore the throughflow optimization space of multi-stage axial-flow compressors.展开更多
Exact determination of pressure-volume-temperature(PVT)properties of the reservoir oils is necessary for reservoir calculations,reservoir performance prediction,and the design of optimal production conditions.The obje...Exact determination of pressure-volume-temperature(PVT)properties of the reservoir oils is necessary for reservoir calculations,reservoir performance prediction,and the design of optimal production conditions.The objective of this study is to develop intelligent and reliable models based on multilayer perceptron(MLP)and radial basis function(RBF)neural networks for estimating the solution gas–oil ratio as a function of bubble point pressure,reservoir temperature,oil gravity(API),and gas specific gravity.These models were developed and tested using a total of 710 experimental data sets representing the samples of crude oil from various geographical locations around the world.Performance of the developed MLP and RBF models were evaluated and investigated against a number of well-known empirical correlations using statistical and graphical error analyses.The results indicated that the proposed models outperform the considered empirical correlations,providing a strong agreement between predicted and experimental values,However,the developed RBF exhibited higher accuracy and efficiency compared to the proposed MLP model.展开更多
Bubble point pressure is one of the most important pressureevolumeetemperature properties of crude oil,and it plays an important role in reservoir and production engineering calculations.It can be precisely determined...Bubble point pressure is one of the most important pressureevolumeetemperature properties of crude oil,and it plays an important role in reservoir and production engineering calculations.It can be precisely determined experimentally.Although,experimental methods present valid and reliable results,they are expensive,time-consuming,and require much care when taking test samples.Some equations of state and empirical correlations can be used as alternative methods to estimate reservoir fluid properties(e.g.,bubble point pressure);however,these methods have a number of limitations.In the present study,a novel numerical model based on artificial neural network(ANN)is proposed for the prediction of bubble point pressure as a function of solution gaseoil ratio,reservoir temperature,oil gravity(API),and gas specific gravity in petroleum systems.The model was developed and evaluated using 760 experimental data sets gathered from oil fields around the world.An optimization process was performed on networks with different structures.Based on the obtained results,a network with one hidden layer and six neurons was observed to be associated with the highest efficiency for predicting bubble point pressure.The obtained ANN model was found to be reliable for the prediction of bubble point pressure of crude oils with solution gaseoil ratios in the range of 8.61e3298.66 SCF/STB,temperatures between 74 and 341.6F,oil gravity values of 6e56.8 API and gas gravity values between 0.521 and 3.444.The performance of the developed model was compared against those of several well-known predictive empirical correlations using statistical and graphical error analyses.The results showed that the proposed ANN model outperforms all of the studied empirical correlations significantly and provides predictions in acceptable agreement with experimental data.展开更多
基金National Natural Science Foundation of China under Grant No.52478568National Key R&D Program of China under Grant Nos.2021YFC3100701 and 2022YFC3003503the Nature Science Foundation of Hubei Province under Grant No.2023AFA030。
文摘To analyze the correlation between the input energy parameters(V_(E))and typical intensity measures(IMs)of offshore ground motions,based on 273 earthquake events recorded by the K-NET in Japan,892 offshore ground motion records with moment magnitudes from 4.0 to 7.0 were used in this study.Residuals obtained through a ground motion model were calculated and analyzed for the correlation between V_(E) and amplitude,duration,frequency content and cumulative IMs.The results indicate that PGV and PGD have strong correlation with the V_(E)(T>0.2 s and T>0.4 s),the duration IMs have weakly negative correlation with the V_(E),Sd_(1) has a strong correlation with the V_(E) in the periods of T>0.4 s,T_(g) has a weak correlation with V_(E) and the cumulative IMs have strong correlation with the V_(E).The parametric predictive equations between typical IMs and V_(E) was proposed,and the differences between the prediction equations from the onshore ground motion records were compared.The differences in parametric predicted equations between offshore and onshore ground motions were confirmed in this study.Proposed correlation equations can be applied to offshore probabilistic seismic hazard analysis and the selection of ground motion records by generalized conditional intensity measures.
文摘Production,processing and transportation of natural gases can be significantly affected by clathrate hydrates.Knowing the gas analysis is crucial to predict the right conditions for hydrate formation.Nevertheless,Katz gas gravity method can be used for initial estimation of hydrate formation temperature （HFT） under the circumstances of indeterminate gas composition.So far several correlations have been proposed for gas gravity method,in which the most accurate and reliable one has belonged to Bahadori and Vuthaluru.The main objective of this study is to present a simple and yet accurate correlation for fast prediction of sweet natural gases HFT based on the fit to Katz gravity chart.By reviewing the error analysis results,one can discover that the new proposed correlation has the best estimation capability among the widely accepted existing correlations within the investigated range.
文摘In this article, the author obtains the large deviation principles for the empirical correlation coefficient of two Gaussian random variables X and Y. Especially, when considering two independent Gaussian random variables X, Y with the means EX, EY （both known）, wherein the author gives two kinds of different proofs and gets the same results.
文摘Recently, introducing a transition predicting model into the Reynolds averaged Navier-Stokes （RANS） environment has been paid more and more attention. Langtry proposed a correlation-based transition model in 2006, which was built strictly on local variables. However, two core correlations in the model had not been published until 2009. In this paper, after considerable analyses and discussions of the mechanism of this transition model and a series of numerical validations in the skin friction coefficient of flat plate boundary layers, a new correlation based on free-stream turbulence intensity is developed, and the empirical correlation of the transition onset momentum thickness Reynold number aiming at the hypersonic transition is improved. Low-speed/transonic airfoils and a hypersonic double wedge fiat are tested to prove the reliability and practicability of this correlation.
文摘The comprehensive evaluation method of enterprise core competitiveness is proposed by combining rough sets and gray correlation theories. Firstly,the initial index is screened through rough set attribute reduction algorithm,and the evaluation weight of each index is obtained through the rough set theory. Then,based on the gray correlation theory, an evaluation model is built for empirical analysis. The 30 financial institutions on the Yangtze River Delta are examined from the theoretical and empirical perspective.The result demonstrates not only the feasibility of rough set attribute reduction algorithm in the core competitiveness index system of the financial institution,but also the accuracy of the combination of these two methods in the comprehensive evaluation of corporate core competitiveness.
基金support of this work by the National Natural Science Foundation of China (Grant Nos.41972316 and 41672252).
文摘The overall heat transfer coefficient(OHTC)of rock fractures is a fundamental parameter for characterizing the heat transfer behavior of rock fractures in hot dry rock(HDR)geothermal mining.Although a number of practical formulae for heat transfer coefficients have been developed in the literature,there is still no widely accepted analytical solution.This paper constructs highly accurate analytical solutions for the temperatures of the inner fracture wall and the fluid.Then they are employed to develop new definition-based formulae(formula A and its simplification formula B)of the OHTC,which are well validated by the experimental and numerical simulation results.An empirical correlation formula of heat transfer coefficient is proposed based on the definition-based formulae which can be directly used in the numerical simulations of heat transfer in rock fractures.A site-scale application example of numerical simulation also demonstrates the effectiveness of the empirical correlation formula.
文摘Uniaxial compressive strength(UCS)is a significant mechanical measure in rock engineering,key for classifying rock masses,conducting stability assessments,and guiding design processes.Over the past five decades,numerous techniques and devices have emerged for UCS measurement.This paper presents a comprehensive literature review of existing methodologies and advancements in UCS testing,examining the theoretical foundations,testing equipment,data processing techniques,and criteria for selecting appropriate UCS testing methods.Additionally,the study highlights a shift toward automated,precise,and computational approaches with multiple inputs(i.e.multiple regression,machine learning,ML)for UCS prediction.Approximately 221 articles published by various researchers between 2000 and 2024 related to ML were reviewed,focusing on the application of ML models,including artificial neural networks(ANNs),adaptive-network-based fuzzy inference system(ANFIS),random forest(RF),support vector machine(SVM),and extreme gradient boosting(XGBoost),in UCS prediction.The review also observed the growing use of hybrid models integrating ML with optimization techniques,significantly improving UCS estimation.Numerous empirical correlations,both direct and indirect,have been established in the past several years based on the physical properties of rocks.However,utilizing these proposed equations to reliably estimate UCS remains challenging due to the variability in lithology,rock origin,and other factors.This study systematically presents the established correlation expressions,considering their lithology,the number of samples used to establish the expressions,the coefficient of determination(R2),and the locations.This allows geologists and engineers to easily apply these established expressions in situations where direct estimation is not possible,enabling them to approximate UCS results.
基金co-supported by the National Science and Technology Major Project of China(Nos.2017-Ⅲ-00050029,J2019-Ⅲ-0021-0065,and J2019-Ⅲ-0015-0059)the National Natural Science Foundation of China(No.51906009)。
文摘Based on the demands of compact heat exchangers and micro cooling channels applied for aviation thermal protection, the flow resistance characteristics of aviation kerosene RP-3 were experimentally studied in a vertically downward circular miniature tube with an inner diameter of 1.86 mm at supercritical pressures and constant heat fluxes. A long and short tube method was used to accurately calculate the frictional pressure drop, and experimental conditions are supercritical pressures of 4 MPa, mass flow rates of 2–4 g/s(i.e., mass fluxes of 736–1472 kg/(m^(2)·s)), heat fluxes of 100–500 kW/m^(2), and inlet temperatures of 373–673 K. Results show that the sharp variations of thermophysical properties, especially density, have significant influences on frictional resistances.Generally, the frictional pressure drop and the friction factor increase with increasing inlet temperatures, and this trend speeds up in the relatively high-temperature region. However, the friction factor has a sudden decline when the fuel outlet temperature exceeds the pseudo-critical temperature.The frictional pressure drop and the friction factor basically remain unchanged with increasing heat flux when the inlet temperature is relatively low, but increase quickly when the inlet temperature is relatively high. Besides, a larger mass flux yields a higher pressure drop but does not necessarily yield a higher friction factor. Finally, an empirical friction factor correlation is proposed and shows better predictive performance than those of previous models.
基金Supported by the National Key Science&Technology Projects during 13th Five-Year Plan(2016ZX05053-003)Young Scholars Development fund of SWPU(201499010121)
文摘It has been known that the productivity of artesian wells is strongly dependent on the rheological properties of crude oils. This work targets two deep artesian wells(>5000 m) that are producing heavy crude oil. The impacts of well conditions including temperature, pressure and shear rate, on the crude oil rheology were comprehensively investigated and correlated using several empirical rheological models. The experimental data indicate that this heavy oil is very sensitive to temperature as result of microstructure change caused by hydrogen bonding. The rheological behavior of the heavy oil is also significantly impacted by the imposed pressure, i.e., the viscosity flow activation energy(Eμ) gently increases with the increasing pressure. The viscosity–shear rate data are well fitted to the power law model at low temperature. However, due to the transition of fluid feature at high temperature(Newtonian fluid), the measured viscosity was found to slightly deviate from the fitting data. Combining the evaluated correlations, the viscosity profile of the heavy crude oil in these two deep artesian wells as a function of well depth was predicted using the oilfield producing data.
文摘A new approach is demonstrated in which soft experimentation can be performed for MMP measurements, thus replacing the common practice of slim tube displacement laboratory experiments. Recovery potential from oil reservoirs by miscible flue gas injection was studied by slim tube and field-scale numerical simulation using two flue gases and seven crude oils sampled at different depths in three candidate reservoirs. The soft experimentations were conducted using Eclipse300<sup>TM</sup>, a three-phase compositional simulator. This study investigates minimum miscibility pressure (MMP), a significant miscible gas injection project screening tool. Successful design of the project is contingent to the accurate determination of the MMP. This study evaluates effects of important factors such as injection pressure, oil component composition, and injection gas composition on the MMP and recovery efficiency for slim tube and field-scale displacements. Two applicable MMP correlations were used for comparison and validation purposes.
基金support and helpful insight.This work was supported by the National Key Research and Development Program(2021YFC2902502)the National Natu-ral Science Foundation of China(21938009,91934301,22078320)+5 种基金the Major Scientific and Technological Innovation Projects in Shan-dong Province(2019JZZY010302)the Shandong Key Research and Development Program(International Cooperation Office)(2019GHZ018)the Shandong Province Postdoctoral Innovative Talents Support Plan(SDBX2020018)the External Cooperation Program of BIC,Chinese Academy of Sciences(122111KYSB20190032)Chemistry and Chemical Engineering Guangdong Laboratory(1922006)GHfund B(202107021062).
文摘This work systematically simulates the external mass transfer from/to a spherical drop and solid particle suspended in a nonlinear uniaxial extensional creeping flow.The mass transfer problem is governed by three dimensionless parameters:the viscosity ratio(λ),the Peclet number(Pe),and the nonlinear intensity of the flow(E).The existing mass transfer theory,valid for very large Peclet numbers only,is expanded,by numerical simulations,to include a much larger range of Peclet numbers(1≤Pe≤105).The simulation results show that the dimensionless mass transfer rate,expressed as the Sherwood number(5 h),agrees well with the theoretical results at the convection-dominated regime(Pe>103).Only when E>5/4,the simulated Sh for a solid sphere in the nonlinear uniaxial extensional flow is larger than theoretical results because the theory neglects the effect of the vortex formed outside the particle on the rate of mass transfer.Empirical correlations are proposed to predict the influence of the dimensionless governing parameters(λ,Pe,E)on the Sherwood number(Sh).The maximum deviations of all empirical correlations are less than 15%when compared to the numerical simulated results.
文摘In the absence of a simple technique to predict convection heat transfer on BIPV （building integrated photovoltaic） surfaces, a mobile probe with two thermocouples was designed. Thermal boundary layers on vertical flat surfaces ofa PV （photovoltaic） and a metallic plate were traversed. The plate consisted of twelve heaters where heat flux and surface temperature were controlled and measured. Uniform heat flux condition was developed on the heaters to closely simulate non-uniform temperature distribution on vertical PV modules. The two thermocouples on the probe measured local air temperature and contact temperature with the wall surface. Experimental results were presented in the forms of local Nusselt numbers versus Rayleigh numbers ＂Nu = a＇（Ra）b＇＇, and surface temperature versus dimensionless height （Ts - T∞ = c.（z/h）d）. The constant values for ＂a＂, ＂b＂, ＂c＂ and ＂d＂ were determined from the best curve-fitting to the power-law relation. The convection heat transfer predictions from the empirical correlations were found to be in consistent with those predictions made by a number of correlations published in the open literature. A simple technique is then proposed to employ two experimental data from the probe to refine empirical correlations as the operational conditions change. A flexible technique to update correlations is of prime significance requirement in thermal design and operation of BIPV modules. The work is in progress to further extend the correlation to predict the combined radiation and convection on inclined PVs and channels.
文摘The gas compressibility factor,also known as Z-factor,plays the determinative role for obtaining thermodynamic properties of gas reservoir.Typically,empirical correlations have been applied to determine this important property.However,weak performance and some limitations of these correlations have persuaded the researchers to use intelligent models instead.In this work,prediction of Z-factor is aimed using different popular intelligent models in order to find the accurate one.The developed intelligent models are including Artificial Neural Network(ANN),Fuzzy Interface System(FIS)and Adaptive Neuro-Fuzzy System(ANFIS).Also optimization of equation of state(EOS)by Genetic Algorithm(GA)is done as well.The validity of developed intelligent models was tested using 1038 series of published data points in literature.It was observed that the accuracy of intelligent predicting models for Z-factor is significantly better than conventional empirical models.Also,results showed the improvement of optimized EOS predictions when coupled with GA optimization.Moreover,of the three intelligent models,ANN model outperforms other models considering all data and 263 field data points of an Iranian offshore gas condensate with R^(2) of 0.9999,while the R^(2) for best empirical correlation was about 0.8334.
基金supported by the China Aerospace Science and Technology Corporation’s Aerospace Science and Technology Innovation Fund Project(casc2013086)CAST Innovation Fund Project(cast2012028)
文摘This paper proposes a new signal noise level estimation approach by local regions. The estimated noise variance is applied as the threshold for an improved empirical mode decomposition（EMD） based signal denoising method. The proposed estimation method can effectively extract the candidate regions for the noise level estimation by measuring the correlation coefficient between noisy signal and a Gaussian filtered signal. For the improved EMD based method, the situation of decomposed intrinsic mode function（IMFs） which contains noise and signal simultaneously are taken into account. Experimental results from two simulated signals and an X-ray pulsar signal demonstrate that the proposed method can achieve better performance than the conventional EMD and wavelet transform（WT） based denoising methods.
基金This work was supported by National Natural Science Foundation of China(51168005,51268003)Key Project of Guangxi Scientific Research and Technological Development Plan(10124006-10)+2 种基金Key Project of Guangxi Science and Technology Lab Center(LGZX201107)Natural Science Foundation of Guangxi(2012GXNSFAA053205)Foundation Project of Guangxi Key Laboratory of Disaster Prevention and Engineering Safety(2009TMZR004,2012ZDX08).
文摘This paper presents a physical investigation and mathematical analysis on mechanical behavior of the regular jugged discontinuity.In particular,we focus on the creep property of structural plane with various slope angles under different normal stress through shear creep tests of structural plane under shear stresses.According to the test results,the shear creep property of structural plane was described and the creep velocity and long-term strength of the structural plane during shear creep were also investigated.An empirical formula is finally established to evaluate shear strength of discontinuity and a modified Burger model was proposed to represent the shear deformation property during creep.
基金supports provided by the National Natural Science Foundation of China(grant Nos.52106189 and 52174220)are highly appreciatedThe support provided by the Shuangchuang Doctor Project of Jiangsu Province(grant No.202131196)is also appreciated+1 种基金This research was also financially supported by fund from Key Laboratory of Hubei Province for Coal Conversion and New Carbon Materials,Wuhan University of Science and Technology(grant No.WKDM202302)This research was also funded by“Double First Class”Construction Project to Enhance Independent Innovation Ability of China University of Mining&Technology(grant No.2022ZZCX03K06).
文摘Understanding the influencing mechanism of turbulent fluctuation on the ignition characteristics of millimeter coal particles is essential.In this work,to study the effect of turbulent fluctuation on ignition time,millimeter coal particles are subjected to a specific flow field,generated in a furnace with symmetric fans.A one-dimensional model with the new proposed correlation and the Ranz-Marshall(R-M)correlation for Nu(Nusselt number)is established to simulate the coal ignition process.In addition,the effects of fan speed,temperature,particle diameter,particle distance and coal type on the ignition time are investigated.It is found that an increase in fan speed from 0 to 3000 rpm leads to a particle Reynolds number Re_(p)increase from 0 to 22.5,and a turbulent particle Reynolds number Re_(t)*increase from 0 to 71.5.With a consideration of the fluctuation effect,the new correlation of Nu gives a better prediction of ignition time compared to the R-M correlation.Moreover,the ignition time is revealed to decrease with an increasing fan speed and an elevating temperature.While the ignition time shows merely an initial boost with enlarging particle distance,it exhibits a linearity with the term of particle diameter dp1.3-1.7 and Reynolds numbers(Nu*/Nu)-0.6(Nu*is turbulent Nusselt number).Based on this relationship,the difference of predicted ignition time is calculated at different Re_(p)and Re_(t)*.It is shown that at low Re_(p)or high Re_(t)*values,the new correlation should substitute for the R-M correlation.
文摘The significance of gas compressibility factor in petroleum engineering encourages the researchers to employ the most accurate and precise methods for estimation of this factor.Commonly,empirical correlations due to their simplicity have been referred more than other approaches for prediction of Z-factor.There is no clear and reliable report to address an appropriate combination of correlation and mixing rule for each type of gas.In the present study,combination of several empirical correlations and mixing rules is examined and a decision tree is constructed to suggest best combination for each gas system.For this reason,2329 experimental data were used for analysis.According to the results,LelandeMueller mixing rule/Sanjari and Lay correlation is the best combination for sour and natural gas.Also,Van NesseAbbot mixing rule/HalleYarborough correlation,StewarteBurkhardteVoo mixing rule/Heidarian correlation and SattereCampbell mixing rule/Papay correlation are the most appropriate combination for gas condensate,binary and ternary mixtures respectively.For binary mixtures,a robust and novel empirical correlation was developed based on Kay mixing rule to estimate Z-factor.The results employed how good the new correlation is in agreement with the experimental data with significant R-squared 0.9843.
基金financially supported by the National Science and Technology Major Project of China(Grant No.2017-Ⅱ-0006-0020)National Key Research and Development Project of China(Grant No.2016YFB0200901)+1 种基金National Natural Science Foundation of China(Grant No.51776154)Shaanxi Key Research and Development Project(Grant No.2018KWZ-01)。
文摘Throughflow design has the advantages of less time consumption and large optimization space,and thus is the corner stone of advanced design system of multi-stage axial-flow compressors.The majority of relevant studies were limited to the throughflow inverse designs,and quite few works have been till now devoted to the throughflow optimal designs.In this work,an automatic and rapid throughflow-based optimal design method is proposed for axial-flow compressors in which a throughflow inverse design solver is embedded in optimal genetic algorithm to improve the design efficiency of axial-flow compressor.Two types of design parameters in the throughflow inverse design of axial-flow compressors,i.e.,swirl and shroud curve,are simultaneously used to optimize both the blade shape and flow path.The proposed method is validated by the redesign optimization of the benchmark axial-flow compressor NASA Stage 35,and the CFD predictions show that the throughflow-based optimization leads to 1.18% efficiency benefit at design condition.The proposed method is then utilized to the two-dimensional throughflow optimal design of a large-scale 6.5-stage axial-flow industrial compressor.The optimal design results are confirmed by CFD predictions,indicating that the proposed method can effectively improve the design adiabatic efficiency of the compressors by 1.09% within a few minutes on desk-top computer.Two throughflow design implications are also obtained for advanced axial-flow industrial compressors.This work could enhance the capability of throughflow design method and has engineering application value to explore the throughflow optimization space of multi-stage axial-flow compressors.
文摘Exact determination of pressure-volume-temperature(PVT)properties of the reservoir oils is necessary for reservoir calculations,reservoir performance prediction,and the design of optimal production conditions.The objective of this study is to develop intelligent and reliable models based on multilayer perceptron(MLP)and radial basis function(RBF)neural networks for estimating the solution gas–oil ratio as a function of bubble point pressure,reservoir temperature,oil gravity(API),and gas specific gravity.These models were developed and tested using a total of 710 experimental data sets representing the samples of crude oil from various geographical locations around the world.Performance of the developed MLP and RBF models were evaluated and investigated against a number of well-known empirical correlations using statistical and graphical error analyses.The results indicated that the proposed models outperform the considered empirical correlations,providing a strong agreement between predicted and experimental values,However,the developed RBF exhibited higher accuracy and efficiency compared to the proposed MLP model.
文摘Bubble point pressure is one of the most important pressureevolumeetemperature properties of crude oil,and it plays an important role in reservoir and production engineering calculations.It can be precisely determined experimentally.Although,experimental methods present valid and reliable results,they are expensive,time-consuming,and require much care when taking test samples.Some equations of state and empirical correlations can be used as alternative methods to estimate reservoir fluid properties(e.g.,bubble point pressure);however,these methods have a number of limitations.In the present study,a novel numerical model based on artificial neural network(ANN)is proposed for the prediction of bubble point pressure as a function of solution gaseoil ratio,reservoir temperature,oil gravity(API),and gas specific gravity in petroleum systems.The model was developed and evaluated using 760 experimental data sets gathered from oil fields around the world.An optimization process was performed on networks with different structures.Based on the obtained results,a network with one hidden layer and six neurons was observed to be associated with the highest efficiency for predicting bubble point pressure.The obtained ANN model was found to be reliable for the prediction of bubble point pressure of crude oils with solution gaseoil ratios in the range of 8.61e3298.66 SCF/STB,temperatures between 74 and 341.6F,oil gravity values of 6e56.8 API and gas gravity values between 0.521 and 3.444.The performance of the developed model was compared against those of several well-known predictive empirical correlations using statistical and graphical error analyses.The results showed that the proposed ANN model outperforms all of the studied empirical correlations significantly and provides predictions in acceptable agreement with experimental data.
