Effects of NHj concentiation, solution/soil ratio and temperature on NH_4^+adsorption were studied in a Eum-Orthic Anthrosol. The slopes of the soil NH_4^+ adsorptionisotherms and the fitted n, the coefficient for the...Effects of NHj concentiation, solution/soil ratio and temperature on NH_4^+adsorption were studied in a Eum-Orthic Anthrosol. The slopes of the soil NH_4^+ adsorptionisotherms and the fitted n, the coefficient for the adsorption intensity, and kappa, the coefficientrelated to adsorption capacity, of the Freundlich equation increased with increasing solution/soilratio (SSR) and with decreasing temperature (T). For the range of experimental conditions, the valueof delta q/delta c, the rate of change of the amount of NH_4^+ adsorbed in the soil solid phase (q)with respect to the equilibrium concentration of NH_4^+ in soil solution (c), was 0.840, indicatingthat q increased with increasing c. From 2 to 45 deg C, delta q/delta SSR, the rate of change of qwith respect to SSR, decreased from 2.598 to 1.996, showing that q increased with increasing SSR,while its increasing rate decreased with temperature. From SSR 1:1 to 20:1, delta q/delta T, therate of change of q with respect to T, decreased from -- 0.095 to -- 0.361, indicating that qdecreased with increasing temperature, and at the same time the negative effect of temperaturebecame larger as SSR increased. Thus under the experimental conditions the order of importance indetermining the amount of NH_4^+ adsorbed in the soil solid phase was delta q/delta SSR > deltaq/delta c > |delta q/delta T|, indicating that the greatest effect on the amount of NH_4^+ adsorbedwas with the solution/soil ratio; the equilibrium concentration of NH_4^+ had a lesser effect; andtemperature had the least effect.展开更多
One of the greatest challenges in critical zone studies is to document the moisture dynamics, water flux,and solute chemistry of the unsaturated, fractured and weathered bedrock that lies between the soil and groundwa...One of the greatest challenges in critical zone studies is to document the moisture dynamics, water flux,and solute chemistry of the unsaturated, fractured and weathered bedrock that lies between the soil and groundwater table. The central impediment to quantifying this component of the subsurface is the difficulty associated with direct observations. Here, we report solute chemistry as a function of depth collected over a full year across the shale-derived vadose zone of the Eel River Critical Zone Observatory using a set of novel sub-horizontal wellbores,referred to as the vadose zone monitoring system. The results of this first geochemical glimpse into the deep vadose zone indicate a dynamic temporal and depth-resolved structure. Major cation concentrations reflect seasonal changes in precipitation and water saturation, and normalized ratios span the full range of values reported for the world's largest rivers.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
Absorption cooling technology is an environmentally friendly method to generate continuous chilled water making use of multiple thermal sources,such as waste heat and renewable thermal energy.In this study,two absorpt...Absorption cooling technology is an environmentally friendly method to generate continuous chilled water making use of multiple thermal sources,such as waste heat and renewable thermal energy.In this study,two absorption chillers(nominal capacity of 400 kW)with series and parallel connections are evaluated.To research the ideal configuration of chillers after thermodynamic analysis,the structures of the chillers are optimized using the particle swarm optimization algorithm by considering the heat transfer area(HTA),exergy efficiency and total annual cost as single-objective functions.The impact of temperature differences between external and internal flows,heat exchanger efficiencies and the solution allocation ratio is estimated.The optimized HTA,coefficient of perform-ance,exergy efficiency and total annual cost are 149.0 m^(2),1.56,29.44%and$229119 for the series-connected chiller,and 146.7 m^(2),1.59,31.45%and$234562 for the parallel-connected type,respectively.Under the lowest HTA condition,compared with the reference simulation results,the energy and exergy performances are improved,while the annual total cost is higher.The annual total cost is highest when maximizing the exergy efficiency,which is attributed to the increase in the HTA.The operating cost accounts for 27.42%(series type)and 26.54%(parallel type)when the annual cost is the lowest.展开更多
Accuracy of the fluid property data plays an absolutely pivotal role in the reservoir computational processes.Reliable data can be obtained through various experimental methods,but these methods are very expensive and...Accuracy of the fluid property data plays an absolutely pivotal role in the reservoir computational processes.Reliable data can be obtained through various experimental methods,but these methods are very expensive and time consuming.Alternative methods are numerical models.These methods used measured experimental data to develop a representative model for predicting desired parameters.In this study,to predict saturation pressure,oil formation volume factor,and solution gas oil ratio,several Artificial Intelligent(AI)models were developed.582 reported data sets were used as data bank that covers a wide range of fluid properties.Accuracy and reliability of the model was examined by some statistical parameters such as correlation coefficient(R2),average absolute relative deviation(AARD),and root mean square error(RMSE).The results illustrated good accordance between predicted data and target values.The model was also compared with previous works and developed empirical correlations which indicated that it is more reliable than all compared models and correlations.At the end,relevancy factor was calculated for each input parameters to illustrate the impact of different parameters on the predicted values.Relevancy factor showed that in these models,solution gas oil ratio has greatest impact on both saturation pressure and oil formation volume factor.In the other hand,saturation pressure has greatest effect on solution gas oil ratio.展开更多
The necessity of oil formation volume factor(Bo)determination does not need to be greatly emphasized.Different types of reservoir oil have specific conditions which impart the hydrocarbon's major properties,among ...The necessity of oil formation volume factor(Bo)determination does not need to be greatly emphasized.Different types of reservoir oil have specific conditions which impart the hydrocarbon's major properties,among which is the oil formation volume factor.Therefore,it seems imperative to construct a model capable of estimating the value of oil formation volume factor.Previous studies have resulted in a number of correlations for oil formation volume factor estimation;however,a large portion of them do not provide an acceptable accuracy(at least in some range of data)and cause a huge error at these points.Some others are not flexible enough to be tuned for a specific type of reservoir oil and a comprehensive piece of work does not exist as well in order to compare the applicability of the new models for estimating the oil formation volume factor.In this research,a model based on simulated annealing(SA)has been built in terms of temperature,solution gas-oil ratio,and gravity of oil and gas to predict the oil formation volume factor.This model is compared with the models proposed in the most recent studies,which shows the greater performance of the new method.In addition,in this paper the models of the recent years were compared with each other and their applicability were discussed.Aiming to compare the models,420 data points were selected and the estimated values of each model for oil formation volume factor were compared with their experimental ones.展开更多
基金Project supported by the National Natural Science Foundation of China (No. 49901009).
文摘Effects of NHj concentiation, solution/soil ratio and temperature on NH_4^+adsorption were studied in a Eum-Orthic Anthrosol. The slopes of the soil NH_4^+ adsorptionisotherms and the fitted n, the coefficient for the adsorption intensity, and kappa, the coefficientrelated to adsorption capacity, of the Freundlich equation increased with increasing solution/soilratio (SSR) and with decreasing temperature (T). For the range of experimental conditions, the valueof delta q/delta c, the rate of change of the amount of NH_4^+ adsorbed in the soil solid phase (q)with respect to the equilibrium concentration of NH_4^+ in soil solution (c), was 0.840, indicatingthat q increased with increasing c. From 2 to 45 deg C, delta q/delta SSR, the rate of change of qwith respect to SSR, decreased from 2.598 to 1.996, showing that q increased with increasing SSR,while its increasing rate decreased with temperature. From SSR 1:1 to 20:1, delta q/delta T, therate of change of q with respect to T, decreased from -- 0.095 to -- 0.361, indicating that qdecreased with increasing temperature, and at the same time the negative effect of temperaturebecame larger as SSR increased. Thus under the experimental conditions the order of importance indetermining the amount of NH_4^+ adsorbed in the soil solid phase was delta q/delta SSR > deltaq/delta c > |delta q/delta T|, indicating that the greatest effect on the amount of NH_4^+ adsorbedwas with the solution/soil ratio; the equilibrium concentration of NH_4^+ had a lesser effect; andtemperature had the least effect.
基金supported by the US National Science Foundation,Project EAR-1331904 for the Eel River Critical Zone Observatory
文摘One of the greatest challenges in critical zone studies is to document the moisture dynamics, water flux,and solute chemistry of the unsaturated, fractured and weathered bedrock that lies between the soil and groundwater table. The central impediment to quantifying this component of the subsurface is the difficulty associated with direct observations. Here, we report solute chemistry as a function of depth collected over a full year across the shale-derived vadose zone of the Eel River Critical Zone Observatory using a set of novel sub-horizontal wellbores,referred to as the vadose zone monitoring system. The results of this first geochemical glimpse into the deep vadose zone indicate a dynamic temporal and depth-resolved structure. Major cation concentrations reflect seasonal changes in precipitation and water saturation, and normalized ratios span the full range of values reported for the world's largest rivers.
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.
基金supported by National Natural Science Foundation of China(grant no.51736006).
文摘Absorption cooling technology is an environmentally friendly method to generate continuous chilled water making use of multiple thermal sources,such as waste heat and renewable thermal energy.In this study,two absorption chillers(nominal capacity of 400 kW)with series and parallel connections are evaluated.To research the ideal configuration of chillers after thermodynamic analysis,the structures of the chillers are optimized using the particle swarm optimization algorithm by considering the heat transfer area(HTA),exergy efficiency and total annual cost as single-objective functions.The impact of temperature differences between external and internal flows,heat exchanger efficiencies and the solution allocation ratio is estimated.The optimized HTA,coefficient of perform-ance,exergy efficiency and total annual cost are 149.0 m^(2),1.56,29.44%and$229119 for the series-connected chiller,and 146.7 m^(2),1.59,31.45%and$234562 for the parallel-connected type,respectively.Under the lowest HTA condition,compared with the reference simulation results,the energy and exergy performances are improved,while the annual total cost is higher.The annual total cost is highest when maximizing the exergy efficiency,which is attributed to the increase in the HTA.The operating cost accounts for 27.42%(series type)and 26.54%(parallel type)when the annual cost is the lowest.
文摘Accuracy of the fluid property data plays an absolutely pivotal role in the reservoir computational processes.Reliable data can be obtained through various experimental methods,but these methods are very expensive and time consuming.Alternative methods are numerical models.These methods used measured experimental data to develop a representative model for predicting desired parameters.In this study,to predict saturation pressure,oil formation volume factor,and solution gas oil ratio,several Artificial Intelligent(AI)models were developed.582 reported data sets were used as data bank that covers a wide range of fluid properties.Accuracy and reliability of the model was examined by some statistical parameters such as correlation coefficient(R2),average absolute relative deviation(AARD),and root mean square error(RMSE).The results illustrated good accordance between predicted data and target values.The model was also compared with previous works and developed empirical correlations which indicated that it is more reliable than all compared models and correlations.At the end,relevancy factor was calculated for each input parameters to illustrate the impact of different parameters on the predicted values.Relevancy factor showed that in these models,solution gas oil ratio has greatest impact on both saturation pressure and oil formation volume factor.In the other hand,saturation pressure has greatest effect on solution gas oil ratio.
文摘The necessity of oil formation volume factor(Bo)determination does not need to be greatly emphasized.Different types of reservoir oil have specific conditions which impart the hydrocarbon's major properties,among which is the oil formation volume factor.Therefore,it seems imperative to construct a model capable of estimating the value of oil formation volume factor.Previous studies have resulted in a number of correlations for oil formation volume factor estimation;however,a large portion of them do not provide an acceptable accuracy(at least in some range of data)and cause a huge error at these points.Some others are not flexible enough to be tuned for a specific type of reservoir oil and a comprehensive piece of work does not exist as well in order to compare the applicability of the new models for estimating the oil formation volume factor.In this research,a model based on simulated annealing(SA)has been built in terms of temperature,solution gas-oil ratio,and gravity of oil and gas to predict the oil formation volume factor.This model is compared with the models proposed in the most recent studies,which shows the greater performance of the new method.In addition,in this paper the models of the recent years were compared with each other and their applicability were discussed.Aiming to compare the models,420 data points were selected and the estimated values of each model for oil formation volume factor were compared with their experimental ones.
