The decision-making method of tunnel boring machine(TBM)operating parameters has a significant guiding significance for TBM safe and efficient construction,and it has been one of the TBM tunneling research hotspots.Fo...The decision-making method of tunnel boring machine(TBM)operating parameters has a significant guiding significance for TBM safe and efficient construction,and it has been one of the TBM tunneling research hotspots.For this purpose,this paper introduces an intelligent decision-making method of TBM operating parameters based on multiple constraints and objective optimization.First,linear cutting tests and numerical simulations are used to investigate the physical rules between different cutting parameters(penetration,cutter spacing,etc.)and rock compressive strength.Second,a dual-driven mapping of rock parameters and TBM operating parameters based on data mining and physical rules of rock breaking is established with high accuracy by combining rock-breaking rules and deep neural networks(DNNs).The decision-making method is established by dual-driven mapping,using the effective rock-breaking capacity and the rated value of mechanical parameters as constraints and the total excavation cost as the optimization objective.The best operational parameters can be obtained by searching for the revolutions per minute and penetration that correspond to the extremum of the constrained objective function.The practicability and effectiveness of the developed decision-making model is verified in the SecondWater Source Channel of Hangzhou,China,resulting in the average penetration rate increasing by 11.3%and the total cost decreasing by 10%.展开更多
In this study,the Stokes formula is used to analyze the separation effect of three-phase separators used in a Oilfield Central Processing Facility.The considered main influencing factors include(but are not limited to...In this study,the Stokes formula is used to analyze the separation effect of three-phase separators used in a Oilfield Central Processing Facility.The considered main influencing factors include(but are not limited to)the typical size of oil and water droplets,the residence time and temperature of fluid and the dosage of demulsifier.Using the“Specification for Oil and Gas Separators”as a basis,the control loops and operating parameters of each separator are optimized Considering the Halfaya Oilfield as a testbed,it is shown that the proposed approach can lead to good results in the production stage.展开更多
Computational simulations and high-temperature measurements of velocities near the surface of a mold were carried out by using the rod deflection method to study the effects of various operating parameters on the flow...Computational simulations and high-temperature measurements of velocities near the surface of a mold were carried out by using the rod deflection method to study the effects of various operating parameters on the flow field in slab continuous casting(CC)molds with narrow widths for the production of automobile exposed panels.Reasonable agreement between the calculated results and measured subsurface velocities of liquid steel was obtained under different operating parameters of the CC process.The simulation results reveal that the flow field in the horizontal plane located 50 mm from the meniscus can be used as the characteristic flow field to optimize the flow field of molten steel in the mold.Increases in casting speed can increase the subsurface velocity of molten steel and shift the position of the vortex core downward in the downward circulation zone.The flow field of liquid steel in a 1040 mm-wide slab CC mold can be improved by an Ar gas flow rate of 7 L·min^−1 and casting speed of 1.7 m·min^−1.Under the present experimental conditions,the double-roll flow pattern is generally stable at a submerged entry nozzle immersion depth of 170 mm.展开更多
An enclosed cyclone passageway(ECP)dust-collecting fan is discussed.The ECP fan separates dust by centrifugal force originating from a driven spiral airflow,and its design takes the constraints of Chinese underground ...An enclosed cyclone passageway(ECP)dust-collecting fan is discussed.The ECP fan separates dust by centrifugal force originating from a driven spiral airflow,and its design takes the constraints of Chinese underground coal mines into consideration.Using the force equilibrium law,a general equation for dust removal in the centrifugal dust removal section(CDRS)of the ECP fan is deduced.This general equation is simplified using the CDRS structure and the fan operating parameters and is analysed numerically.The attractive results show that increases in the airflow rate of the fan,the structural ratio of the ECPs and the radius of the extended axis can improve the dust removal performance of the CDRS.Furthermore,the effects of the structural ratio and the radius on dust removal dominate over that of the flow rate,and the effect of the structural ratio is more significant than that of the radius.展开更多
Solid oxide fuel cell combined with heat and power(SOFC-CHP)system is a distributed power generation system with low pollution and high efficiency.In this paper,a 10 kW SOFC-CHP system model using syngas was built in ...Solid oxide fuel cell combined with heat and power(SOFC-CHP)system is a distributed power generation system with low pollution and high efficiency.In this paper,a 10 kW SOFC-CHP system model using syngas was built in Aspen plus.Key operating parameters,such as steam to fuel ratio,stack temperature,reformer temperature,air flow rate,and air preheating temperature,were analyzed.Optimization was conducted based on the simulation results.Results suggest that higher steam to fuel ratio is beneficial to the electrical efficiency,but it might decrease the gross system efficiency.Higher stack and reformer temperatures contribute to the electrical efficiency,and the optimal operating temperatures of stack and reformer when considering the stack degradation are 750℃and 700℃,respectively.The air preheating temperature barely affects the electrical efficiency but affects the thermal efficiency and the gross system efficiency,the recommended value is around 600℃under the reference condition.展开更多
Gasification is a promising approach for converting solid fuel sources, including renewable ones like biomass, for use. The main problem in biomass gasification is the formation of condensable tars, including polycycl...Gasification is a promising approach for converting solid fuel sources, including renewable ones like biomass, for use. The main problem in biomass gasification is the formation of condensable tars, including polycyclic aromatic hydrocarbons (PAHs). This paper investigated the conversion of tar components during corn straw gasification. It analyzed collected tar components using a gas chromatograph-mass spectrograph (GC-MS). Experimental results indicate that, with increasing temperature from 700°C to 900°C, the concentrations of benzene, indene, phenanthrene, naphthalene, acenaphthylene, fluorene, and pyrene increased whereas those of toluene, phenol, 1-methylnaphthalene, and 2-methylnaphthalene decreased. As the equivalence ratio (ER) increased from 0.21 to 0.34, the concentrations of indene and phenanthrene increased from 0.148% and 0.087% to 0.232% and 0.223%, respectively. Further, the phenol content increased as ER increased from 0.21 to 0.26 and then decreased as the ER increased further to 0.34. Other parameters like the steam/biomass (S/B) ratio and catalyst also played a critical role in tar reduction. This paper demonstrates the conversion of some tar components and elucidates their chemical properties during gasification.展开更多
Various studies were reported for the evaluation of the adsorption performance of kaolin clay using single dye types.This paper aimed to evaluate the comparative adsorption capacity of prepared adsorbents from Ethiopi...Various studies were reported for the evaluation of the adsorption performance of kaolin clay using single dye types.This paper aimed to evaluate the comparative adsorption capacity of prepared adsorbents from Ethiopian kaolin for different dye types(Basic Yellow 28(BY 28),Congo Red(CR),and Reactive Red 120(RR 120)).Because different dye classes may have a significant impact on the removal efficiency by the prepared adsorbent.Moreover,we intended to investigate the interaction effect of adsorbent-sorbate in the adsorption phenomenon for the three different class dyes.The adsorbents from kaolin clay were prepared via mechanical treatment,beneficiation,and calcination(700℃).The effect of operating parameters(pH,adsorbent dose,contact time,dye concentration,and adsorption temperature)was evaluated.before and after adsorption of the adsorbents were characterized using FTIR spectroscopy.Furthermore,adsorption isotherm,kinetic models,and the thermodynamic processes in the adsorption phenomenon were computed.The percentage removal efficiency of dyes was recorded as 92.08%,88.63%,and 73.33%for BY 28,CR,and RR 120 dyes,respectively at the experimental condition:adsorbent dosage=1 g/100 mL,solution pH=9(BY 28),and pH=3(CR,and RR 120),contact time=60 min,initial dyes concentrations=20 mg/L,and temperature=30℃.The adsorption of adsorbates onto kaolin adsorbents was well fitted with pseudo-second-order kinetics and Langmuir isotherm models.The thermodynamic parameters indicate that the adsorption process is spontaneous and exothermic for all dyes.The comparative percentage removal of,with the same operational parameters and kaolin adsorbent,was recorded as BY 28>CR>RR120 resulting from their surface charge and molecular size/structure dyes properties.We confirm that the adsorption at each operational parameter and peak intensity of FTIR spectra,before and after adsorption,revealed that the different dye types have varied removal efficiency onto the prepared kaolin adsorbent.This is due to that being dominantly influenced by the electrostatic interaction and steric effects at the surface of the sorbent and sorbate characteristics.We deduced that the kaolin clay used as an adsorbent is highly dependent on the dye types and their featured characteristics.展开更多
An algorithm named InterOpt for optimizing operational parameters is proposed based on interpretable machine learning,and is demonstrated via optimization of shale gas development.InterOpt consists of three parts:a ne...An algorithm named InterOpt for optimizing operational parameters is proposed based on interpretable machine learning,and is demonstrated via optimization of shale gas development.InterOpt consists of three parts:a neural network is used to construct an emulator of the actual drilling and hydraulic fracturing process in the vector space(i.e.,virtual environment);:the Sharpley value method in inter-pretable machine learning is applied to analyzing the impact of geological and operational parameters in each well(i.e.,single well feature impact analysis):and ensemble randomized maximum likelihood(EnRML)is conducted to optimize the operational parameters to comprehensively improve the efficiency of shale gas development and reduce the average cost.In the experiment,InterOpt provides different drilling and fracturing plans for each well according to its specific geological conditions,and finally achieves an average cost reduction of 9.7%for a case study with 104 wells.展开更多
The impregnated diamond(ID)bit drilling is one of the main rotary drilling methods in hard rock drilling and it is widely used in mineral exploration,oil and gas exploration,mining,and construction industries.In this ...The impregnated diamond(ID)bit drilling is one of the main rotary drilling methods in hard rock drilling and it is widely used in mineral exploration,oil and gas exploration,mining,and construction industries.In this study,the quadratic polynomial model in ID bit drilling process was proposed as a function of controllable mechanical operating parameters,such as weight on bit(WOB)and revolutions per minute(RPM).Also,artificial neural networks(ANN)model for predicting the rate of penetration(ROP)was developed using datasets acquired during the drilling operation.The relationships among mechanical operating parameters(WOB and RPM)and ROP in ID bit drilling were analyzed using estimated quadratic polynomial model and trained ANN model.The results show that ROP has an exponential relationship with WOB,whereas ROP has linear relationship with RPM.Finally,the optimal regime of mechanical drilling parameters to achieve high ROP was confirmed using proposed model in combination with rock breaking principal.展开更多
The problem of effluent total nitrogen(TN)at most of the wastewater treatment plants(WWTPs)in China is important for meeting the related water quality standards,even under the condition of high energy consumption.To a...The problem of effluent total nitrogen(TN)at most of the wastewater treatment plants(WWTPs)in China is important for meeting the related water quality standards,even under the condition of high energy consumption.To achieve better prediction and control of effluent TN concentration,an efficient prediction model,based on controllable operation parameters,was constructed in a sequencing batch reactor process.Compared with previous models,this model has two main characteristics:①Superficial gas velocity and anoxic time are controllable operation parameters and are selected as the main input parameters instead of dissolved oxygen to improve the model controllability,and②the model prediction accuracy is improved on the basis of a feedforward neural network(FFNN)with algorithm optimization.The results demonstrated that the FFNN model was efficiently optimized by scaled conjugate gradient,and the performance was excellent compared with other models in terms of the correlation coefficient(R).The optimized FFNN model could provide an accurate prediction of effluent TN based on influent water parameters and key control parameters.This study revealed the possible application of the optimized FFNN model for the efficient removal of pollutants and lower energy consumption at most of the WWTPs.展开更多
During tunnel boring machine(TBM)excavation,lithology identification is an important issue to understand tunnelling performance and avoid time-consuming excavation.However,site investigation generally lacks ground sam...During tunnel boring machine(TBM)excavation,lithology identification is an important issue to understand tunnelling performance and avoid time-consuming excavation.However,site investigation generally lacks ground samples and the information is subjective,heterogeneous,and imbalanced due to mixed ground conditions.In this study,an unsupervised(K-means)and synthetic minority oversampling technique(SMOTE)-guided light-gradient boosting machine(LightGBM)classifier is proposed to identify the soft ground tunnel classification and determine the imbalanced issue of tunnelling data.During the tunnel excavation,an earth pressure balance(EPB)TBM recorded 18 different operational parameters along with the three main tunnel lithologies.The proposed model is applied using Python low-code PyCaret library.Next,four decision tree-based classifiers were obtained in a short time period with automatic hyperparameter tuning to determine the best model for clustering-guided SMOTE application.In addition,the Shapley additive explanation(SHAP)was implemented to avoid the model black box problem.The proposed model was evaluated using different metrics such as accuracy,F1 score,precision,recall,and receiver operating characteristics(ROC)curve to obtain a reasonable outcome for the minority class.It shows that the proposed model can provide significant tunnel lithology identification based on the operational parameters of EPB-TBM.The proposed method can be applied to heterogeneous tunnel formations with several TBM operational parameters to describe the tunnel lithologies for efficient tunnelling.展开更多
Membrane distillation(MD)is a promising membrane separation technique used to treat industrial wastewater.When coupled with cheap heat sources,MD has significant economic advantages.Therefore,MD can be combined with s...Membrane distillation(MD)is a promising membrane separation technique used to treat industrial wastewater.When coupled with cheap heat sources,MD has significant economic advantages.Therefore,MD can be combined with solar energy to realize the large-scale and low-cost treatment of highly mineralized mine water in the western coalproducing region of China.In this study,highly mineralized mine water from the Ningdong area of China was subjected to vacuum MD(VMD)using polyvinylidene fluoride hollow-fiber membranes.The optimal operation parameters of VMD were determined by response surface optimization.Subsequently,the feasibility of VMD for treating highly mineralized mine water was explored.The fouling behavior observed during VMD was further investigated by scanning electron microscopy with energy-dispersive X-ray spectroscopy(SEM-EDS).Under the optimal parameters(pressure=-0.08 MPa,temperature=70℃,and feed flow rate=1.5 L/min),the maximum membrane flux was 8.85 kg/(m^(2) h),and the desalination rate was 99.7%.Membrane fouling could be divided into three stages:membrane wetting,crystallization,and fouling layer formation.Physical cleaning restored the flux and salt rejection rate to 94%and 97%of the initial values,respectively;however,the cleaning interval and cleaning efficiency decreased as the VMD run time increased.SEM-EDS analysis revealed that the reduction in flux was caused by the precipitation of CaCO_(3).The findings also demonstrated that the membrane wetting could be attributed to the formation of NaCl on the cross section and outer surface of the membrane.Overall,the results confirm the feasibility of MD for treating mine water and provide meaningful guidance for the industrial application of MD.展开更多
This paper reviews the machinability and mechanical properties of natural fiber-reinforced composites. Coupling agents, operating parameters, as well as chemical treatment effects on natural fiber-reinforced composite...This paper reviews the machinability and mechanical properties of natural fiber-reinforced composites. Coupling agents, operating parameters, as well as chemical treatment effects on natural fiber-reinforced composites’ machinability are also reviewed. Moreover, the impacts of fibers’ physical properties on the machinability of the composite are mentioned. Fiber volume fraction (V<sub>f</sub>), fiber orientation as well as chemical treatment effects on mechanical properties are also defined. Conclusively, the effect of fibers’ physical properties as well as mechanical properties is described. It was discovered that chemical treatment of natural fibers improved their compatibility with the matrix by removing their surface tissues, increasing the roughness average (Ra), and reducing moisture absorption. Also, the Orientation of the fiber plays an important role in controlling the mechanical properties of the composite. Moreover, some physical properties of the fibers, including quality of fiber distributed in the matrix;fiber size, length, and diameter;moisture absorption;porosity and the way fibers break during compounding with the matrix, were found to affect the mechanical properties of the composites formed.展开更多
Disc cutter consumption is a critical problem that influences work performance during shield tunneling processes and directly affects the cutter change decision.This study proposes a new model to estimate the disc cut...Disc cutter consumption is a critical problem that influences work performance during shield tunneling processes and directly affects the cutter change decision.This study proposes a new model to estimate the disc cutter life(Hf)by integrating a group method of data handling(GMDH)-type neural network(NN)with a genetic algorithm(GA).The efficiency and effectiveness of the GMDH network structure are optimized by the GA,which enables each neuron to search for its optimum connections set from the previous layer.With the proposed model,monitoring data including the shield performance database,disc cutter consumption,geological conditions,and operational parameters can be analyzed.To verify the performance of the proposed model,a case study in China is presented and a database is adopted to illustrate the excellence of the hybrid model.The results indicate that the hybrid model predicts disc cutter life with high accuracy.The sensitivity analysis reveals that the penetration rate(PR)has a significant influence on disc cutter life.The results of this study can be beneficial in both the planning and construction stages of shield tunneling.展开更多
Accurate prediction of shield tunneling-induced settlement is a complex problem that requires consideration of many influential parameters.Recent studies reveal that machine learning(ML)algorithms can predict the sett...Accurate prediction of shield tunneling-induced settlement is a complex problem that requires consideration of many influential parameters.Recent studies reveal that machine learning(ML)algorithms can predict the settlement caused by tunneling.However,well-performing ML models are usually less interpretable.Irrelevant input features decrease the performance and interpretability of an ML model.Nonetheless,feature selection,a critical step in the ML pipeline,is usually ignored in most studies that focused on predicting tunneling-induced settlement.This study applies four techniques,i.e.Pearson correlation method,sequential forward selection(SFS),sequential backward selection(SBS)and Boruta algorithm,to investigate the effect of feature selection on the model’s performance when predicting the tunneling-induced maximum surface settlement(S_(max)).The data set used in this study was compiled from two metro tunnel projects excavated in Hangzhou,China using earth pressure balance(EPB)shields and consists of 14 input features and a single output(i.e.S_(max)).The ML model that is trained on features selected from the Boruta algorithm demonstrates the best performance in both the training and testing phases.The relevant features chosen from the Boruta algorithm further indicate that tunneling-induced settlement is affected by parameters related to tunnel geometry,geological conditions and shield operation.The recently proposed Shapley additive explanations(SHAP)method explores how the input features contribute to the output of a complex ML model.It is observed that the larger settlements are induced during shield tunneling in silty clay.Moreover,the SHAP analysis reveals that the low magnitudes of face pressure at the top of the shield increase the model’s output。展开更多
A geothermal demonstration exploitation area will be established in the Enhanced Geothermal System of the Qiabuqia field, Gonghe Basin, Qinghai–Xizang Plateau in China. Selection of operational parameters for geother...A geothermal demonstration exploitation area will be established in the Enhanced Geothermal System of the Qiabuqia field, Gonghe Basin, Qinghai–Xizang Plateau in China. Selection of operational parameters for geothermal field extraction is thus of great significance to realize the best production performance. A novel integrated method of finite element and multi-objective optimization has been employed to obtain the optimal scheme for thermal extraction from the Gonghe Basin. A thermal-hydraulic-mechanical coupling model(THM) is established to analyze the thermal performance. From this it has been found that there exists a contraction among different heat extraction indexes. Parametric study indicates that injection mass rate(Q_(in)) is the most sensitive parameter to the heat extraction, followed by well spacing(WS) and injection temperature(T_(in)). The least sensitive parameter is production pressure(p_(out)). The optimal combination of operational parameters acquired is such that(T_(in), p_(out), Q_(in), WS) equals(72.72°C, 30.56 MPa, 18.32 kg/s, 327.82 m). Results indicate that the maximum electrical power is 1.41 MW for the optimal case over 20 years. The thermal break has been relieved and the pressure difference reduced by 8 MPa compared with the base case. The optimal case would extract 50% more energy than that of a previous case and the outcome will provide a remarkable reference for the construction of Gonghe project.展开更多
Ethylene cracking process is the core production process in ethylene industry,and is paid more attention to reduce high energy consumption.Because of the interdependent relationships between multi-flow allocation and ...Ethylene cracking process is the core production process in ethylene industry,and is paid more attention to reduce high energy consumption.Because of the interdependent relationships between multi-flow allocation and multi-parameter setting in cracking process,it is difficult to find the overall energy efficiency scheduling for the purpose of saving energy.The traditional scheduling solutions with optimal economic benefit are not applicable for energy efficiency scheduling issue due to the neglecting of recycle and lost energy,as well as critical operation parameters as coil outlet pressure(COP)and dilution ratio.In addition,the scheduling solutions mostly regard each cracking furnace as an elementary unit,regardless of the coordinated operation of internal dual radiation chambers(DRC).Therefore,to improve energy utilization and production operation,a novel energy efficiency scheduling solution for ethylene cracking process is proposed in this paper.Specifically,steam heat recycle and exhaust heat loss are considered in cracking process based on 6 types of extreme learning machine(ELM)based cracking models incorporating DRC operation and three operation parameters as coil outlet temperature(COT),COP,and dilution ratio according to semi-mechanism analysis.Then to provide long-term decision-making basis for energy efficiency scheduling,overall energy efficiency indexes,including overall output per unit net energy input(OONE),output-input ratio per unit net energy input(ORNE),exhaust gas heat loss ratio(EGHL),are designed based on input-output analysis in terms of material and energy flows.Finally,a multiobjective evolutionary algorithm based on decomposition(MOEA/D)is employed to solve the formulated multi-objective mixed-integer nonlinear programming(MOMINLP)model.The validities of the proposed scheduling solution are illustrated through a case study.The scheduling results demonstrate that an optimal balance between multi-flow allocation,multi-parameter setting,and DRC coordinated operation is reached,which achieves 3.37%and 2.63%decreases in net energy input for same product output and conversion ratio,as well as the 1.56%decrease in energy loss ratio.展开更多
Observations of surface displacements are expected to aid in geomechanical analyses of injectioninduced seismicity.However,the controlling factors of the displacement magnitude remain poorly understood except the elas...Observations of surface displacements are expected to aid in geomechanical analyses of injectioninduced seismicity.However,the controlling factors of the displacement magnitude remain poorly understood except the elastic modulus of the fluid-bearing reservoir.Here,an experiment scheme of numerical simulation based on fully-coupled poroelasticity is designed to investigate the displacements induced by deep underground fluid injection.According to the sealing ability of deep reservoirs,the numerical experiments are classified into two scenarios:injection into open and sealed reservoirs.Potential effects from both geological and operational parameters are considered during the experiments,which include the hydromechanical properties,the reservoir geometry,injection rates and volumes.Experimental results reveal that in addition to the reservoir depth and Young’s modulus,the porosity also has significant influences on the surface displacements.Geodetic modeling of injection-induced displacements should include the parameter of reservoir porosity.When the reservoir is characterized by a good sealing ability,fluid injection is prone to induce larger horizontal displacements than vertical uplifts.Most of injection activities including hydraulic fracturing can probably induce detectable surface displacements.Geodetic surveying,especially using Global Navigation Satellite System(GNSS)with both horizontal and vertical observations,should become an essential monitoring task for anthropogenic fluid injection/production activities,which is conducive to assess and mitigate some geohazards including earthquakes.展开更多
The determination of operational parameters in the underground coal gasification(UCG)process should be considered in two aspects:first,the total coal in each UCG panel must be gasified and second,the calorific value o...The determination of operational parameters in the underground coal gasification(UCG)process should be considered in two aspects:first,the total coal in each UCG panel must be gasified and second,the calorific value of the produced gas should be acceptable.The main aim of this study is to present a model that meets these aspects and increasing the calorific value of syngas during this process.In order to achieve those aims,eight different increasing scenarios were devised for total gasification of coal per panel.These scenarios included:increasing oxygen injection rate(scenario 1),the amount of steam injection(scenario 2),operation time(scenario 3),cavity pressure(scenario 4),increase operation time and cavity pressure simultaneously(scenario 5),increase steam injection speed and oxygen injection rate simultaneously(scenario 6),increase in cavity pressure,operating time,steam injection rate and oxygen injection rate simultaneously(scenario 7)and also simultaneous increase in the operating time and steam injection rate(scenario 8).The results showed that for producing syngas with a higher calorific value,the following parameters had the most positive effects respectively:operation time,cavity pressure,steam injection rate and oxygen injection rate.Finally,the model validation was performed for the Centralia LBK-1 UCG pilot and the results showed that this model is very close to reality.展开更多
By using the parameter differential method of operators,we recast the combination function of coordinate and momentum operators into its normal and anti-normal orderings,which is more ecumenical,simpler,and neater tha...By using the parameter differential method of operators,we recast the combination function of coordinate and momentum operators into its normal and anti-normal orderings,which is more ecumenical,simpler,and neater than the existing ways.These products are very useful in obtaining some new differential relations and useful mathematical integral formulas.Further,we derive the normally ordered form of the operator(fQ+gP)^-n with n being an arbitrary positive integer by using the parameter tracing method of operators together with the intermediate coordinate-momentum representation.In addition,general mutual transformation rules of the normal and anti-normal orderings,which have good universality,are derived and hence the anti-normal ordering of(fQ+gP)^-n is also obtained.Finally,the application of some new identities is given.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.52021005)Outstanding Youth Foundation of Shandong Province of China(Grant No.ZR2021JQ22)Taishan Scholars Program of Shandong Province of China(Grant No.tsqn201909003)。
文摘The decision-making method of tunnel boring machine(TBM)operating parameters has a significant guiding significance for TBM safe and efficient construction,and it has been one of the TBM tunneling research hotspots.For this purpose,this paper introduces an intelligent decision-making method of TBM operating parameters based on multiple constraints and objective optimization.First,linear cutting tests and numerical simulations are used to investigate the physical rules between different cutting parameters(penetration,cutter spacing,etc.)and rock compressive strength.Second,a dual-driven mapping of rock parameters and TBM operating parameters based on data mining and physical rules of rock breaking is established with high accuracy by combining rock-breaking rules and deep neural networks(DNNs).The decision-making method is established by dual-driven mapping,using the effective rock-breaking capacity and the rated value of mechanical parameters as constraints and the total excavation cost as the optimization objective.The best operational parameters can be obtained by searching for the revolutions per minute and penetration that correspond to the extremum of the constrained objective function.The practicability and effectiveness of the developed decision-making model is verified in the SecondWater Source Channel of Hangzhou,China,resulting in the average penetration rate increasing by 11.3%and the total cost decreasing by 10%.
基金This study was supported by the Natural Science Foundation of Shandong Province(Grant No.ZR2021QE030).
文摘In this study,the Stokes formula is used to analyze the separation effect of three-phase separators used in a Oilfield Central Processing Facility.The considered main influencing factors include(but are not limited to)the typical size of oil and water droplets,the residence time and temperature of fluid and the dosage of demulsifier.Using the“Specification for Oil and Gas Separators”as a basis,the control loops and operating parameters of each separator are optimized Considering the Halfaya Oilfield as a testbed,it is shown that the proposed approach can lead to good results in the production stage.
基金This work was financially supported by the Hunan Valin Lianyuan Iron&Steel Co.,Ltd.,China(No.18H00582).The authors are grateful to Hunan Valin Lianyuan Iron&Steel Co.,Ltd.,China for their assistance with the industrial measurement of velocities near the mold surface.
文摘Computational simulations and high-temperature measurements of velocities near the surface of a mold were carried out by using the rod deflection method to study the effects of various operating parameters on the flow field in slab continuous casting(CC)molds with narrow widths for the production of automobile exposed panels.Reasonable agreement between the calculated results and measured subsurface velocities of liquid steel was obtained under different operating parameters of the CC process.The simulation results reveal that the flow field in the horizontal plane located 50 mm from the meniscus can be used as the characteristic flow field to optimize the flow field of molten steel in the mold.Increases in casting speed can increase the subsurface velocity of molten steel and shift the position of the vortex core downward in the downward circulation zone.The flow field of liquid steel in a 1040 mm-wide slab CC mold can be improved by an Ar gas flow rate of 7 L·min^−1 and casting speed of 1.7 m·min^−1.Under the present experimental conditions,the double-roll flow pattern is generally stable at a submerged entry nozzle immersion depth of 170 mm.
基金supported by the Natural Science Foundation of China and Shenhua Group Corporation Limited(U1361118)the Hunan Provincial Natural Science Foundation of China(13JJ8016,2015JJ2061)+1 种基金the State Key Laboratory for Geomechanics and Deep Underground Engineering(SKLGDUEK1018)the Project of Scientific Research Fund of Hunan Provincial Education Department(Nos.12C1099,14C0425).
文摘An enclosed cyclone passageway(ECP)dust-collecting fan is discussed.The ECP fan separates dust by centrifugal force originating from a driven spiral airflow,and its design takes the constraints of Chinese underground coal mines into consideration.Using the force equilibrium law,a general equation for dust removal in the centrifugal dust removal section(CDRS)of the ECP fan is deduced.This general equation is simplified using the CDRS structure and the fan operating parameters and is analysed numerically.The attractive results show that increases in the airflow rate of the fan,the structural ratio of the ECPs and the radius of the extended axis can improve the dust removal performance of the CDRS.Furthermore,the effects of the structural ratio and the radius on dust removal dominate over that of the flow rate,and the effect of the structural ratio is more significant than that of the radius.
基金the National Key R&D Program of China(2017YFB0601903).
文摘Solid oxide fuel cell combined with heat and power(SOFC-CHP)system is a distributed power generation system with low pollution and high efficiency.In this paper,a 10 kW SOFC-CHP system model using syngas was built in Aspen plus.Key operating parameters,such as steam to fuel ratio,stack temperature,reformer temperature,air flow rate,and air preheating temperature,were analyzed.Optimization was conducted based on the simulation results.Results suggest that higher steam to fuel ratio is beneficial to the electrical efficiency,but it might decrease the gross system efficiency.Higher stack and reformer temperatures contribute to the electrical efficiency,and the optimal operating temperatures of stack and reformer when considering the stack degradation are 750℃and 700℃,respectively.The air preheating temperature barely affects the electrical efficiency but affects the thermal efficiency and the gross system efficiency,the recommended value is around 600℃under the reference condition.
基金This work was financially supported by the National Natural Science Funds for Young Scholars of China(Grant No.51806033)National Key Technologies Research and Development Program(Grant No.2018YFB0905104)Jilin Provincial Science and Technology Development Program(Grant No.20190201096JC).
文摘Gasification is a promising approach for converting solid fuel sources, including renewable ones like biomass, for use. The main problem in biomass gasification is the formation of condensable tars, including polycyclic aromatic hydrocarbons (PAHs). This paper investigated the conversion of tar components during corn straw gasification. It analyzed collected tar components using a gas chromatograph-mass spectrograph (GC-MS). Experimental results indicate that, with increasing temperature from 700°C to 900°C, the concentrations of benzene, indene, phenanthrene, naphthalene, acenaphthylene, fluorene, and pyrene increased whereas those of toluene, phenol, 1-methylnaphthalene, and 2-methylnaphthalene decreased. As the equivalence ratio (ER) increased from 0.21 to 0.34, the concentrations of indene and phenanthrene increased from 0.148% and 0.087% to 0.232% and 0.223%, respectively. Further, the phenol content increased as ER increased from 0.21 to 0.26 and then decreased as the ER increased further to 0.34. Other parameters like the steam/biomass (S/B) ratio and catalyst also played a critical role in tar reduction. This paper demonstrates the conversion of some tar components and elucidates their chemical properties during gasification.
文摘Various studies were reported for the evaluation of the adsorption performance of kaolin clay using single dye types.This paper aimed to evaluate the comparative adsorption capacity of prepared adsorbents from Ethiopian kaolin for different dye types(Basic Yellow 28(BY 28),Congo Red(CR),and Reactive Red 120(RR 120)).Because different dye classes may have a significant impact on the removal efficiency by the prepared adsorbent.Moreover,we intended to investigate the interaction effect of adsorbent-sorbate in the adsorption phenomenon for the three different class dyes.The adsorbents from kaolin clay were prepared via mechanical treatment,beneficiation,and calcination(700℃).The effect of operating parameters(pH,adsorbent dose,contact time,dye concentration,and adsorption temperature)was evaluated.before and after adsorption of the adsorbents were characterized using FTIR spectroscopy.Furthermore,adsorption isotherm,kinetic models,and the thermodynamic processes in the adsorption phenomenon were computed.The percentage removal efficiency of dyes was recorded as 92.08%,88.63%,and 73.33%for BY 28,CR,and RR 120 dyes,respectively at the experimental condition:adsorbent dosage=1 g/100 mL,solution pH=9(BY 28),and pH=3(CR,and RR 120),contact time=60 min,initial dyes concentrations=20 mg/L,and temperature=30℃.The adsorption of adsorbates onto kaolin adsorbents was well fitted with pseudo-second-order kinetics and Langmuir isotherm models.The thermodynamic parameters indicate that the adsorption process is spontaneous and exothermic for all dyes.The comparative percentage removal of,with the same operational parameters and kaolin adsorbent,was recorded as BY 28>CR>RR120 resulting from their surface charge and molecular size/structure dyes properties.We confirm that the adsorption at each operational parameter and peak intensity of FTIR spectra,before and after adsorption,revealed that the different dye types have varied removal efficiency onto the prepared kaolin adsorbent.This is due to that being dominantly influenced by the electrostatic interaction and steric effects at the surface of the sorbent and sorbate characteristics.We deduced that the kaolin clay used as an adsorbent is highly dependent on the dye types and their featured characteristics.
文摘An algorithm named InterOpt for optimizing operational parameters is proposed based on interpretable machine learning,and is demonstrated via optimization of shale gas development.InterOpt consists of three parts:a neural network is used to construct an emulator of the actual drilling and hydraulic fracturing process in the vector space(i.e.,virtual environment);:the Sharpley value method in inter-pretable machine learning is applied to analyzing the impact of geological and operational parameters in each well(i.e.,single well feature impact analysis):and ensemble randomized maximum likelihood(EnRML)is conducted to optimize the operational parameters to comprehensively improve the efficiency of shale gas development and reduce the average cost.In the experiment,InterOpt provides different drilling and fracturing plans for each well according to its specific geological conditions,and finally achieves an average cost reduction of 9.7%for a case study with 104 wells.
文摘The impregnated diamond(ID)bit drilling is one of the main rotary drilling methods in hard rock drilling and it is widely used in mineral exploration,oil and gas exploration,mining,and construction industries.In this study,the quadratic polynomial model in ID bit drilling process was proposed as a function of controllable mechanical operating parameters,such as weight on bit(WOB)and revolutions per minute(RPM).Also,artificial neural networks(ANN)model for predicting the rate of penetration(ROP)was developed using datasets acquired during the drilling operation.The relationships among mechanical operating parameters(WOB and RPM)and ROP in ID bit drilling were analyzed using estimated quadratic polynomial model and trained ANN model.The results show that ROP has an exponential relationship with WOB,whereas ROP has linear relationship with RPM.Finally,the optimal regime of mechanical drilling parameters to achieve high ROP was confirmed using proposed model in combination with rock breaking principal.
基金This work was funded by the Major Science and Technology Program for Water Pollution Control and Treatment(2017ZX07201003)the National Natural Science Foundation of China(51961125101)the Science and Technology Project of Zhejiang Province(2018C03003).
文摘The problem of effluent total nitrogen(TN)at most of the wastewater treatment plants(WWTPs)in China is important for meeting the related water quality standards,even under the condition of high energy consumption.To achieve better prediction and control of effluent TN concentration,an efficient prediction model,based on controllable operation parameters,was constructed in a sequencing batch reactor process.Compared with previous models,this model has two main characteristics:①Superficial gas velocity and anoxic time are controllable operation parameters and are selected as the main input parameters instead of dissolved oxygen to improve the model controllability,and②the model prediction accuracy is improved on the basis of a feedforward neural network(FFNN)with algorithm optimization.The results demonstrated that the FFNN model was efficiently optimized by scaled conjugate gradient,and the performance was excellent compared with other models in terms of the correlation coefficient(R).The optimized FFNN model could provide an accurate prediction of effluent TN based on influent water parameters and key control parameters.This study revealed the possible application of the optimized FFNN model for the efficient removal of pollutants and lower energy consumption at most of the WWTPs.
基金supported by Japan Society for the Promotion of Science KAKENHI(Grant No.JP22H01580).
文摘During tunnel boring machine(TBM)excavation,lithology identification is an important issue to understand tunnelling performance and avoid time-consuming excavation.However,site investigation generally lacks ground samples and the information is subjective,heterogeneous,and imbalanced due to mixed ground conditions.In this study,an unsupervised(K-means)and synthetic minority oversampling technique(SMOTE)-guided light-gradient boosting machine(LightGBM)classifier is proposed to identify the soft ground tunnel classification and determine the imbalanced issue of tunnelling data.During the tunnel excavation,an earth pressure balance(EPB)TBM recorded 18 different operational parameters along with the three main tunnel lithologies.The proposed model is applied using Python low-code PyCaret library.Next,four decision tree-based classifiers were obtained in a short time period with automatic hyperparameter tuning to determine the best model for clustering-guided SMOTE application.In addition,the Shapley additive explanation(SHAP)was implemented to avoid the model black box problem.The proposed model was evaluated using different metrics such as accuracy,F1 score,precision,recall,and receiver operating characteristics(ROC)curve to obtain a reasonable outcome for the minority class.It shows that the proposed model can provide significant tunnel lithology identification based on the operational parameters of EPB-TBM.The proposed method can be applied to heterogeneous tunnel formations with several TBM operational parameters to describe the tunnel lithologies for efficient tunnelling.
基金This research was supported by the Open Fund Project of the State Key Laboratory of Water Resources Protection and Utilization in Coal Mining(GJNY-18-73.13).
文摘Membrane distillation(MD)is a promising membrane separation technique used to treat industrial wastewater.When coupled with cheap heat sources,MD has significant economic advantages.Therefore,MD can be combined with solar energy to realize the large-scale and low-cost treatment of highly mineralized mine water in the western coalproducing region of China.In this study,highly mineralized mine water from the Ningdong area of China was subjected to vacuum MD(VMD)using polyvinylidene fluoride hollow-fiber membranes.The optimal operation parameters of VMD were determined by response surface optimization.Subsequently,the feasibility of VMD for treating highly mineralized mine water was explored.The fouling behavior observed during VMD was further investigated by scanning electron microscopy with energy-dispersive X-ray spectroscopy(SEM-EDS).Under the optimal parameters(pressure=-0.08 MPa,temperature=70℃,and feed flow rate=1.5 L/min),the maximum membrane flux was 8.85 kg/(m^(2) h),and the desalination rate was 99.7%.Membrane fouling could be divided into three stages:membrane wetting,crystallization,and fouling layer formation.Physical cleaning restored the flux and salt rejection rate to 94%and 97%of the initial values,respectively;however,the cleaning interval and cleaning efficiency decreased as the VMD run time increased.SEM-EDS analysis revealed that the reduction in flux was caused by the precipitation of CaCO_(3).The findings also demonstrated that the membrane wetting could be attributed to the formation of NaCl on the cross section and outer surface of the membrane.Overall,the results confirm the feasibility of MD for treating mine water and provide meaningful guidance for the industrial application of MD.
文摘This paper reviews the machinability and mechanical properties of natural fiber-reinforced composites. Coupling agents, operating parameters, as well as chemical treatment effects on natural fiber-reinforced composites’ machinability are also reviewed. Moreover, the impacts of fibers’ physical properties on the machinability of the composite are mentioned. Fiber volume fraction (V<sub>f</sub>), fiber orientation as well as chemical treatment effects on mechanical properties are also defined. Conclusively, the effect of fibers’ physical properties as well as mechanical properties is described. It was discovered that chemical treatment of natural fibers improved their compatibility with the matrix by removing their surface tissues, increasing the roughness average (Ra), and reducing moisture absorption. Also, the Orientation of the fiber plays an important role in controlling the mechanical properties of the composite. Moreover, some physical properties of the fibers, including quality of fiber distributed in the matrix;fiber size, length, and diameter;moisture absorption;porosity and the way fibers break during compounding with the matrix, were found to affect the mechanical properties of the composites formed.
基金The research work was funded by“The Pearl River Talent Recruitment Program”in 2019(2019CX01G338)Guangdong Province and the Research Funding of Shantou University for New Faculty Member(NTF19024-2019),China.
文摘Disc cutter consumption is a critical problem that influences work performance during shield tunneling processes and directly affects the cutter change decision.This study proposes a new model to estimate the disc cutter life(Hf)by integrating a group method of data handling(GMDH)-type neural network(NN)with a genetic algorithm(GA).The efficiency and effectiveness of the GMDH network structure are optimized by the GA,which enables each neuron to search for its optimum connections set from the previous layer.With the proposed model,monitoring data including the shield performance database,disc cutter consumption,geological conditions,and operational parameters can be analyzed.To verify the performance of the proposed model,a case study in China is presented and a database is adopted to illustrate the excellence of the hybrid model.The results indicate that the hybrid model predicts disc cutter life with high accuracy.The sensitivity analysis reveals that the penetration rate(PR)has a significant influence on disc cutter life.The results of this study can be beneficial in both the planning and construction stages of shield tunneling.
基金support provided by The Science and Technology Development Fund,Macao SAR,China(File Nos.0057/2020/AGJ and SKL-IOTSC-2021-2023)Science and Technology Program of Guangdong Province,China(Grant No.2021A0505080009).
文摘Accurate prediction of shield tunneling-induced settlement is a complex problem that requires consideration of many influential parameters.Recent studies reveal that machine learning(ML)algorithms can predict the settlement caused by tunneling.However,well-performing ML models are usually less interpretable.Irrelevant input features decrease the performance and interpretability of an ML model.Nonetheless,feature selection,a critical step in the ML pipeline,is usually ignored in most studies that focused on predicting tunneling-induced settlement.This study applies four techniques,i.e.Pearson correlation method,sequential forward selection(SFS),sequential backward selection(SBS)and Boruta algorithm,to investigate the effect of feature selection on the model’s performance when predicting the tunneling-induced maximum surface settlement(S_(max)).The data set used in this study was compiled from two metro tunnel projects excavated in Hangzhou,China using earth pressure balance(EPB)shields and consists of 14 input features and a single output(i.e.S_(max)).The ML model that is trained on features selected from the Boruta algorithm demonstrates the best performance in both the training and testing phases.The relevant features chosen from the Boruta algorithm further indicate that tunneling-induced settlement is affected by parameters related to tunnel geometry,geological conditions and shield operation.The recently proposed Shapley additive explanations(SHAP)method explores how the input features contribute to the output of a complex ML model.It is observed that the larger settlements are induced during shield tunneling in silty clay.Moreover,the SHAP analysis reveals that the low magnitudes of face pressure at the top of the shield increase the model’s output。
基金the National Key R&D Program of China(Grant No.2018YFB1501804)the National Natural Science Funds for Excellent Young Scholars of China(Grant No.51822406)+2 种基金the Sichuan Science and Technology Program(2021YJ0389)the Program of Introducing Talents of Discipline to Chinese Universities(111 Plan)(Grant No.B17045)the Beijing Outstanding Young Scientist Program(Grant No.BJJWZYJH01201911414038)。
文摘A geothermal demonstration exploitation area will be established in the Enhanced Geothermal System of the Qiabuqia field, Gonghe Basin, Qinghai–Xizang Plateau in China. Selection of operational parameters for geothermal field extraction is thus of great significance to realize the best production performance. A novel integrated method of finite element and multi-objective optimization has been employed to obtain the optimal scheme for thermal extraction from the Gonghe Basin. A thermal-hydraulic-mechanical coupling model(THM) is established to analyze the thermal performance. From this it has been found that there exists a contraction among different heat extraction indexes. Parametric study indicates that injection mass rate(Q_(in)) is the most sensitive parameter to the heat extraction, followed by well spacing(WS) and injection temperature(T_(in)). The least sensitive parameter is production pressure(p_(out)). The optimal combination of operational parameters acquired is such that(T_(in), p_(out), Q_(in), WS) equals(72.72°C, 30.56 MPa, 18.32 kg/s, 327.82 m). Results indicate that the maximum electrical power is 1.41 MW for the optimal case over 20 years. The thermal break has been relieved and the pressure difference reduced by 8 MPa compared with the base case. The optimal case would extract 50% more energy than that of a previous case and the outcome will provide a remarkable reference for the construction of Gonghe project.
基金supported by the High-tech Research and Development Program of China(2014AA041802)。
文摘Ethylene cracking process is the core production process in ethylene industry,and is paid more attention to reduce high energy consumption.Because of the interdependent relationships between multi-flow allocation and multi-parameter setting in cracking process,it is difficult to find the overall energy efficiency scheduling for the purpose of saving energy.The traditional scheduling solutions with optimal economic benefit are not applicable for energy efficiency scheduling issue due to the neglecting of recycle and lost energy,as well as critical operation parameters as coil outlet pressure(COP)and dilution ratio.In addition,the scheduling solutions mostly regard each cracking furnace as an elementary unit,regardless of the coordinated operation of internal dual radiation chambers(DRC).Therefore,to improve energy utilization and production operation,a novel energy efficiency scheduling solution for ethylene cracking process is proposed in this paper.Specifically,steam heat recycle and exhaust heat loss are considered in cracking process based on 6 types of extreme learning machine(ELM)based cracking models incorporating DRC operation and three operation parameters as coil outlet temperature(COT),COP,and dilution ratio according to semi-mechanism analysis.Then to provide long-term decision-making basis for energy efficiency scheduling,overall energy efficiency indexes,including overall output per unit net energy input(OONE),output-input ratio per unit net energy input(ORNE),exhaust gas heat loss ratio(EGHL),are designed based on input-output analysis in terms of material and energy flows.Finally,a multiobjective evolutionary algorithm based on decomposition(MOEA/D)is employed to solve the formulated multi-objective mixed-integer nonlinear programming(MOMINLP)model.The validities of the proposed scheduling solution are illustrated through a case study.The scheduling results demonstrate that an optimal balance between multi-flow allocation,multi-parameter setting,and DRC coordinated operation is reached,which achieves 3.37%and 2.63%decreases in net energy input for same product output and conversion ratio,as well as the 1.56%decrease in energy loss ratio.
基金who provided financial support for this studysupported by the CUHK Research Fellowship Scheme(4200555)NSFC/RGC joint Research Scheme(NCUHK418/15)。
文摘Observations of surface displacements are expected to aid in geomechanical analyses of injectioninduced seismicity.However,the controlling factors of the displacement magnitude remain poorly understood except the elastic modulus of the fluid-bearing reservoir.Here,an experiment scheme of numerical simulation based on fully-coupled poroelasticity is designed to investigate the displacements induced by deep underground fluid injection.According to the sealing ability of deep reservoirs,the numerical experiments are classified into two scenarios:injection into open and sealed reservoirs.Potential effects from both geological and operational parameters are considered during the experiments,which include the hydromechanical properties,the reservoir geometry,injection rates and volumes.Experimental results reveal that in addition to the reservoir depth and Young’s modulus,the porosity also has significant influences on the surface displacements.Geodetic modeling of injection-induced displacements should include the parameter of reservoir porosity.When the reservoir is characterized by a good sealing ability,fluid injection is prone to induce larger horizontal displacements than vertical uplifts.Most of injection activities including hydraulic fracturing can probably induce detectable surface displacements.Geodetic surveying,especially using Global Navigation Satellite System(GNSS)with both horizontal and vertical observations,should become an essential monitoring task for anthropogenic fluid injection/production activities,which is conducive to assess and mitigate some geohazards including earthquakes.
文摘The determination of operational parameters in the underground coal gasification(UCG)process should be considered in two aspects:first,the total coal in each UCG panel must be gasified and second,the calorific value of the produced gas should be acceptable.The main aim of this study is to present a model that meets these aspects and increasing the calorific value of syngas during this process.In order to achieve those aims,eight different increasing scenarios were devised for total gasification of coal per panel.These scenarios included:increasing oxygen injection rate(scenario 1),the amount of steam injection(scenario 2),operation time(scenario 3),cavity pressure(scenario 4),increase operation time and cavity pressure simultaneously(scenario 5),increase steam injection speed and oxygen injection rate simultaneously(scenario 6),increase in cavity pressure,operating time,steam injection rate and oxygen injection rate simultaneously(scenario 7)and also simultaneous increase in the operating time and steam injection rate(scenario 8).The results showed that for producing syngas with a higher calorific value,the following parameters had the most positive effects respectively:operation time,cavity pressure,steam injection rate and oxygen injection rate.Finally,the model validation was performed for the Centralia LBK-1 UCG pilot and the results showed that this model is very close to reality.
基金Project supported by the National Natural Science Foundation of China(Grant No.11347026)the Natural Science Foundation of Shandong Province,China(Grant Nos.ZR2016AM03 and ZR2017MA011)the Natural Science Foundation of Heze University,China(Grant Nos.XY17KJ09 and XY18PY13).
文摘By using the parameter differential method of operators,we recast the combination function of coordinate and momentum operators into its normal and anti-normal orderings,which is more ecumenical,simpler,and neater than the existing ways.These products are very useful in obtaining some new differential relations and useful mathematical integral formulas.Further,we derive the normally ordered form of the operator(fQ+gP)^-n with n being an arbitrary positive integer by using the parameter tracing method of operators together with the intermediate coordinate-momentum representation.In addition,general mutual transformation rules of the normal and anti-normal orderings,which have good universality,are derived and hence the anti-normal ordering of(fQ+gP)^-n is also obtained.Finally,the application of some new identities is given.
