A detailed analysis of operational process and principle of ammonia-recovery system in the modified equipment of flax fiber,which will be applied to parameters optimizing of the ammoniarecovery system as a foundationa...A detailed analysis of operational process and principle of ammonia-recovery system in the modified equipment of flax fiber,which will be applied to parameters optimizing of the ammoniarecovery system as a foundational principle,is presented. According to the principle,an ammonia compressor,whose working conditions are based on key operational parameters of the whole ammoniarecovery system, is the mainly energy-consumption part of ammonia-recovery system in the modified equipment of flax fiber. A generally mathematical model based on work efficiency of an ammonia compressor is founded,which is available to rate effective work and energy consumption of the ammonia compressor. The optimum operation-efficiency of the ammonia compressor is chosen as the goal to analyze and calculate the key operational parameters of the ammonia-recovery system. In the above analyzing and calculating,a mathematical model on ammonia flowing from the reactor to the register 1 is developed,in order to provide further understanding of the principle of an ammonia-recovery system. At the meantime,the ammonia flow regime in the pipeline and the process of ammonia inflation and deflation from the reactor to the register 1 are taken separately into account in the model. An iterative method is for obtaining parametric solutions of the mathematical model on ammonia flowing from the reactor to the register 1 and the key operational parameters of the ammoniarecovery system. A parametric analysis is put forward to complete showing the ammonia velocity or the state of the reactor and the register 1. The key optimized parameters will be achieved in term of the minimum efficiency after comparing the work efficiencies of an ammonia compressor at different working conditions.展开更多
Aim To obtain an optimizing range of the main configuration parameters of double swirls combustion system (DSCS) Methods To analyze the influence of DS combustion cham-ber configuration parameters on fuel spray and mi...Aim To obtain an optimizing range of the main configuration parameters of double swirls combustion system (DSCS) Methods To analyze the influence of DS combustion cham-ber configuration parameters on fuel spray and mixing by means of the fuel jet developmentperiphery charts obtained by the high speed photography with a modeling test device deve-loped by authors,and to examine it by the tests on a single cylinder diesel engine.Resultsand Conclusion The mixing process can be divided into four phases.The optimizing range of the ration of the inner chamber diameter to the cylinder bore,d2/D,is 0.4-0.7; and the outerchamber diameter,d1 the height of the circular ridge to the piston top face,h1,the radius of outer/inner chamber circle,R1,R2 ,the max depth of outer/inner chamber bowl,H1,H2,etc. are also important展开更多
From the Physical Optics theory (PO) and Leontovich Impedance Boundary Condition (IBC), We research RCS reduction (RCSR) of multilayer dielectric and magnetic medium on different shape conductors such as plate, cuboid...From the Physical Optics theory (PO) and Leontovich Impedance Boundary Condition (IBC), We research RCS reduction (RCSR) of multilayer dielectric and magnetic medium on different shape conductors such as plate, cuboid and cone by use of Matlab programs. Some available RCS data and graph results are given. These show the connection between Radar Absorbent Material (RAM) parameters and the number of layers. In the mean time, the relation between RAM optimized parameters and RCS value is also shown. It has better practical significance.展开更多
The method for optimizing the hydraulic fracturing parameters of the cube development infill well pad was proposed,aiming at the well pattern characteristic of“multi-layer and multi-period”of the infill wells in Sic...The method for optimizing the hydraulic fracturing parameters of the cube development infill well pad was proposed,aiming at the well pattern characteristic of“multi-layer and multi-period”of the infill wells in Sichuan Basin.The fracture propagation and inter-well interference model were established based on the evolution of 4D in-situ stress,and the evolution characteristics of stress and the mechanism of interference between wells were analyzed.The research shows that the increase in horizontal stress difference and the existence of natural fractures/faults are the main reasons for inter-well interference.Inter-well interference is likely to occur near the fracture zones and between the infill wells and parent wells that have been in production for a long time.When communication channels are formed between the infill wells and parent wells,it can increase the productivity of parent wells in the short term.However,it will have a delayed negative impact on the long-term sustained production of both infill wells and parent wells.The change trend of in-situ stress caused by parent well production is basically consistent with the decline trend of pore pressure.The lateral disturbance range of in-situ stress is initially the same as the fracture length and reaches 1.5 to 1.6 times that length after 2.5 years.The key to avoiding inter-well interference is to optimize the fracturing parameters.By adopting the M-shaped well pattern,the optimal well spacing for the infill wells is 300 m,the cluster spacing is 10 m,and the liquid volume per stage is 1800 m^(3).展开更多
This work proposes an optimization method for gas storage operation parameters under multi-factor coupled constraints to improve the peak-shaving capacity of gas storage reservoirs while ensuring operational safety.Pr...This work proposes an optimization method for gas storage operation parameters under multi-factor coupled constraints to improve the peak-shaving capacity of gas storage reservoirs while ensuring operational safety.Previous research primarily focused on integrating reservoir,wellbore,and surface facility constraints,often resulting in broad constraint ranges and slow model convergence.To solve this problem,the present study introduces additional constraints on maximum withdrawal rates by combining binomial deliverability equations with material balance equations for closed gas reservoirs,while considering extreme peak-shaving demands.This approach effectively narrows the constraint range.Subsequently,a collaborative optimization model with maximum gas production as the objective function is established,and the model employs a joint solution strategy combining genetic algorithms and numerical simulation techniques.Finally,this methodology was applied to optimize operational parameters for Gas Storage T.The results demonstrate:(1)The convergence of the model was achieved after 6 iterations,which significantly improved the convergence speed of the model;(2)The maximum working gas volume reached 11.605×10^(8) m^(3),which increased by 13.78%compared with the traditional optimization method;(3)This method greatly improves the operation safety and the ultimate peak load balancing capability.The research provides important technical support for the intelligent decision of injection and production parameters of gas storage and improving peak load balancing ability.展开更多
Specialized vanadium(V)-iron(Fe)-based alloy additives utilized in the production of V-containing steels were investigated.Vanadium slag from the Panzhihua region of China was utilized as a raw material to optimize pr...Specialized vanadium(V)-iron(Fe)-based alloy additives utilized in the production of V-containing steels were investigated.Vanadium slag from the Panzhihua region of China was utilized as a raw material to optimize process parameters for the preparation of V-Fe-based alloy via silicon thermal reduction.Experiments were conducted to investigate the effects of reduction temperature,holding time,and slag composition on alloy-slag separation,alloy microstructure,and the oxide content of residual slag,with an emphasis on the recovery of valuable metal elements.The results indicated that the optimal process conditions for silicon thermal reduction were achieved at reduction temperature of 1823 K,holding time of 240 min,and slag composition of 45 wt.%SiO_(2),40 wt.%CaO,and 15 wt.%Al_(2)O_(3).The resulting V-Fe-based alloy predominantly consisted of Fe-based phases such as Fe,titanium(Ti),silicon(Si)and manganese(Mn),with Si,V,as well as chromium(Cr)concentrated in the intercrystalline phase of the Fe-based alloy.The recoveries of Fe,Mn,Cr,V,and Ti under the optimal conditions were 96.30%,91.96%,86.53%,80.29%,and 74.82%,respectively.The key components of the V-Fe-based alloy obtained were 41.96 wt.%Si,27.55 wt.%Fe,12.13 wt.%Mn,5.53 wt.%V,4.86 wt.%Cr,and 3.74 wt.%Ti,thereby enabling the comprehensive recovery of the valuable metal from vanadium slag.展开更多
Silicone material extrusion(MEX)is widely used for processing liquids and pastes.Owing to the uneven linewidth and elastic extrusion deformation caused by material accumulation,products may exhibit geometric errors an...Silicone material extrusion(MEX)is widely used for processing liquids and pastes.Owing to the uneven linewidth and elastic extrusion deformation caused by material accumulation,products may exhibit geometric errors and performance defects,leading to a decline in product quality and affecting its service life.This study proposes a process parameter optimization method that considers the mechanical properties of printed specimens and production costs.To improve the quality of silicone printing samples and reduce production costs,three machine learning models,kernel extreme learning machine(KELM),support vector regression(SVR),and random forest(RF),were developed to predict these three factors.Training data were obtained through a complete factorial experiment.A new dataset is obtained using the Euclidean distance method,which assigns the elimination factor.It is trained with Bayesian optimization algorithms for parameter optimization,the new dataset is input into the improved double Gaussian extreme learning machine,and finally obtains the improved KELM model.The results showed improved prediction accuracy over SVR and RF.Furthermore,a multi-objective optimization framework was proposed by combining genetic algorithm technology with the improved KELM model.The effectiveness and reasonableness of the model algorithm were verified by comparing the optimized results with the experimental results.展开更多
Rocking the drillstring at the surface during slide drilling is a common method for reducing drag when drilling horizontal wells.However,the current methods for determining the parameters for rocking are insufficient,...Rocking the drillstring at the surface during slide drilling is a common method for reducing drag when drilling horizontal wells.However,the current methods for determining the parameters for rocking are insufficient,limiting the widespread use of this technology.In this study,the influence of rocking parameters on the friction-reduction effect was investigated using an axialetorsional dynamic model of the drillstring and an experimental apparatus for rocking-assisted slide drilling in a simulated horizontal well.The research shows that increasing the rocking speed is beneficial improving the friction-reduction effect,but there is a diminishing marginal effect.A method was proposed to optimize the rocking speed using the equivalent axial drag coefficienterocking speed curve.Under the influence of rocking,the downhole weight on bit(WOB)exhibits a sinusoidal-like variation,with the predominant frequency being twice the rocking frequency.The fluctuation amplitude of the WOB in the horizontal section has a linear relationship with the rocking-affected depth.Based on this,a method was proposed to estimate the rockingaffected depth using the fluctuation amplitude of the standpipe pressure difference.Application of this method in the drilling field has improved the rate of penetration and toolface stability,demonstrating the reliability and effectiveness of the methods proposed in this paper.展开更多
Purpose-The indoor vibration compaction test(IVCT)was a key step in controlling the compaction quality for high-speed railway graded aggregate(HRGA),which currently had a research gap on the assessment indicators and ...Purpose-The indoor vibration compaction test(IVCT)was a key step in controlling the compaction quality for high-speed railway graded aggregate(HRGA),which currently had a research gap on the assessment indicators and compaction parameters.Design/methodology/approach-To address these issues,a novel multi-indicator IVCT method was proposed,including physical indicator dry density(ρd)and mechanical indicators dynamic stiffness(Krb)and bearing capacity coefficient(K20).Then,a series of IVCTs on HRGA under different compaction parameters were conducted with an improved vibration compactor,which could monitor the physical-mechanical indicators in real-time.Finally,the optimal vibration compaction parameters,including the moisture content(ω),the diameter-to-maximum particle size ratio(Rd),the thickness-to-maximum particle size ratio(Rh),the vibration frequency(f),the vibration mass(Mc)and the eccentric distance(re),were determined based on the evolution characteristics for the physical-mechanical indicators during compaction.Findings-All results indicated that theρd gradually increased and then stabilized,and the Krb initially increased and then decreased.Moreover,the inflection time of the Krb was present as the optimal compaction time(Tlp)during compaction.Additionally,optimal compaction was achieved whenωwas the water-holding content after mud pumping,Rd was 3.4,Rh was 3.5,f was the resonance frequency,and the ratio between the excitation force and the Mc was 1.8.Originality/value-The findings of this paper were significant for the quality control of HRGA compaction.展开更多
The high temperature deformation behaviors of α＋β type titanium alloy TC11 （Ti-6.5Al-3.5Mo-1.5Zr-0.3Si） with coarse lamellar starting microstructure were investigated based on the hot compression tests in the tem...The high temperature deformation behaviors of α＋β type titanium alloy TC11 （Ti-6.5Al-3.5Mo-1.5Zr-0.3Si） with coarse lamellar starting microstructure were investigated based on the hot compression tests in the temperature range of 950-1100 ℃ and the strain rate range of 0.001-10 s-1. The processing maps at different strains were then constructed based on the dynamic materials model, and the hot compression process parameters and deformation mechanism were optimized and analyzed, respectively. The results show that the processing maps exhibit two domains with a high efficiency of power dissipation and a flow instability domain with a less efficiency of power dissipation. The types of domains were characterized by convergence and divergence of the efficiency of power dissipation, respectively. The convergent domain in a＋fl phase field is at the temperature of 950-990 ℃ and the strain rate of 0.001-0.01 s^-1, which correspond to a better hot compression process window of α＋β phase field. The peak of efficiency of power dissipation in α＋β phase field is at 950 ℃ and 0.001 s 1, which correspond to the best hot compression process parameters of α＋β phase field. The convergent domain in β phase field is at the temperature of 1020-1080 ℃ and the strain rate of 0.001-0.1 s^-l, which correspond to a better hot compression process window of β phase field. The peak of efficiency of power dissipation in ℃ phase field occurs at 1050 ℃ over the strain rates from 0.001 s^-1 to 0.01 s^-1, which correspond to the best hot compression process parameters of ,8 phase field. The divergence domain occurs at the strain rates above 0.5 s^-1 and in all the tested temperature range, which correspond to flow instability that is manifested as flow localization and indicated by the flow softening phenomenon in stress-- strain curves. The deformation mechanisms of the optimized hot compression process windows in a＋β and β phase fields are identified to be spheroidizing and dynamic recrystallizing controlled by self-diffusion mechanism, respectively. The microstructure observation of the deformed specimens in different domains matches very well with the optimized results.展开更多
With the help of FESEM, high resolution electron backscatter diffraction can investigate the grains/subgrains as small as a few tens of nanometers with a good angular resolution （~0.5°）. Fast development of EBS...With the help of FESEM, high resolution electron backscatter diffraction can investigate the grains/subgrains as small as a few tens of nanometers with a good angular resolution （~0.5°）. Fast development of EBSD speed （up to 1100 patterns per second） contributes that the number of published articles related to EBSD has been increasing sharply year by year. This paper reviews the sample preparation, parameters optimization and analysis of EBSD technique, emphasizing on the investigation of ultrafine grained and nanostructured materials processed by severe plastic deformation （SPD）. Detailed and practical parameters of the electropolishing, silica polishing and ion milling have been summarized. It is shown that ion milling is a real universal and promising polishing method for EBSD preparation of almost all materials. There exists a maximum value of indexed points as a function of step size. The optimum step size depends on the magnification and the board resolution/electronic step size. Grains/subgrains and texture, and grain boundary structure are readily obtained by EBSD. Strain and stored energy may be analyzed by EBSD.展开更多
The paper analyzes the factors influencing machine tool selection. By using fuzzy mathematics theory, we establish a theorietical model for optimal machine tool selection considering geometric features, clamping size,...The paper analyzes the factors influencing machine tool selection. By using fuzzy mathematics theory, we establish a theorietical model for optimal machine tool selection considering geometric features, clamping size, machining range, machining precision and surface roughness. By means of fuzzy comprehensive evaluation method, the membership degree of machine tool selection and the largest comprehensive evaluation index are determined. Then the reasonably automatic selection of machine tool is realized in the generative computer aided process planning （CAPP） system. Finally, the finite element model based on ABAQUS is established and the cutting process of machine tool is simulated. According to the theoretical and empirical cutting parameters and the curve of surface residual stress, the optimal cutting parameters can be determined.展开更多
Electroless copper plating on diamond particles precoated with 1%Cr was carried out to evaluate the effects of various experimental parameters on coating quality and deposition rate to obtain the optimized reaction pa...Electroless copper plating on diamond particles precoated with 1%Cr was carried out to evaluate the effects of various experimental parameters on coating quality and deposition rate to obtain the optimized reaction parameters. The formulated samples under optimized parameters were characterized by X-ray diffraction, scanning electron microscopy, energy dispersive spectroscopy, X-ray photoelectron spectra and optical microscopy. The best parameters, where uniform and maximum coating thickness was achieved, are etching with 20%NaOH for 30 min, sensitization and activation with SnCl2 and PdCl2 for 5 and 20 min, respectively. The composition of the copper solution bath was 16 g/L CuSO4＆#183;5H2O, 35 mL/L formaldehyde （HCHO）, 23 g/L KNaC4H4O6 at 60 ℃, pH=13 and stirring at （350±15） r/min under ultrasonication.展开更多
A grating eddy current displacement sensor(GECDS) can be used in a watertight electronic transducer to realize long range displacement or position measurement with high accuracy in difficult industry conditions.The pa...A grating eddy current displacement sensor(GECDS) can be used in a watertight electronic transducer to realize long range displacement or position measurement with high accuracy in difficult industry conditions.The parameters optimization of the sensor is essential for economic and efficient production.This paper proposes a method to combine an artificial neural network(ANN) and a genetic algorithm(GA) for the sensor parameters optimization.A neural network model is developed to map the complex relationship between design parameters and the nonlinearity error of the GECDS,and then a GA is used in the optimization process to determine the design parameter values,resulting in a desired minimal nonlinearity error of about 0.11%.The calculated nonlinearity error is 0.25%.These results show that the proposed method performs well for the parameters optimization of the GECDS.展开更多
The research on the parameters optimization for gasbag polishing machine tools, mainly aims at a better kinematics performance and a design scheme. Serial structural arm is mostly employed in gasbag polishing machine ...The research on the parameters optimization for gasbag polishing machine tools, mainly aims at a better kinematics performance and a design scheme. Serial structural arm is mostly employed in gasbag polishing machine tools at present, but it is disadvantaged by its complexity, big inertia, and so on. In the multi-objective parameters optimization, it is very difficult to select good parameters to achieve excellent performance of the mechanism. In this paper, a statistics parameters optimization method based on index atlases is presented for a novel 5-DOF gasbag polishing machine tool. In the position analyses, the structure and workspace for a novel 5-DOF gasbag polishing machine tool is developed, where the gasbag polishing machine tool is advantaged by its simple structure, lower inertia and bigger workspace. In the kinematics analyses, several kinematics performance evaluation indices of the machine tool are proposed and discussed, and the global kinematics performance evaluation atlases are given. In the parameters optimization process, considering the assembly technique, a design scheme of the 5-DOF gasbag polishing machine tool is given to own better kinematics performance based on the proposed statistics parameters optimization method, and the global linear isotropic performance index is 0.5, the global rotational isotropic performance index is 0.5, the global linear velocity transmission performance index is 1.012 3 m/s in the case of unit input matrix, the global rotational velocity transmission performance index is 0.102 7 rad/s in the case of unit input matrix, and the workspace volume is 1. The proposed research provides the basis for applications of the novel 5-DOF gasbag polishing machine tool, which can be applied to the modern industrial fields requiring machines with lower inertia, better kinematics transmission performance and better technological efficiency.展开更多
As the manufacturing industry is facing increasingly serious environmental problems, because of which carbon tax policies are being implemented, choosing the optimum cutting parameters during the machining process is ...As the manufacturing industry is facing increasingly serious environmental problems, because of which carbon tax policies are being implemented, choosing the optimum cutting parameters during the machining process is crucial for automobile panel dies in order to achieve synergistic minimization of the environment impact, product quality, and processing efficiency. This paper presents a processing task-based evaluation method to optimize the cutting parameters, considering the trade-off among carbon emissions, surface roughness, and processing time. Three objective models and their relationships with the cutting parameters were obtained through input–output, response surface, and theoretical analyses, respectively. Examples of cylindrical turning were applied to achieve a central composite design(CCD), and relative validation experiments were applied to evaluate the proposed method. The experiments were conducted on the CAK50135 di lathe cutting of AISI 1045 steel, and NSGA-Ⅱ was used to obtain the Pareto fronts of the three objectives. Based on the TOPSIS method, the Pareto solution set was ranked to find the optimal solution to evaluate and select the optimal cutting parameters. An S/N ratio analysis and contour plots were applied to analyze the influence of each decision variable on the optimization objective. Finally, the changing rules of a single factor for each objective were analyzed. The results demonstrate that the proposed method is effective in finding the trade-off among the three objectives and obtaining reasonable application ranges of the cutting parameters from Pareto fronts.展开更多
The grating eddy current displacement sensor (GECDS) for distance or position measurement used in watertight electronic calipers was described. The sensor relies on repetitive variation of inductance against displacem...The grating eddy current displacement sensor (GECDS) for distance or position measurement used in watertight electronic calipers was described. The sensor relies on repetitive variation of inductance against displacement caused by the change of coupling areas between moving coils and static reflectors. The investigations focused on setting up and utilizing a computer model of the 3D eddy current fields and geometry to analyze causes of the production of measurement blind areas, and to investigate effects of the sensor parameters, such as axial gap between coils and reflectors, reflector length and reflector width on characteristics of the sensor. Simulation results indicated that the sensor has the smallest nonlinearity error of 0.15%, which agrees well with the experimental results.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
In order that the mechanism designed meets the requirements of kinematics with optimal dynamics behaviors, a quadratic optimization method is proposed based on the different characteristics of kinematic and dynamic op...In order that the mechanism designed meets the requirements of kinematics with optimal dynamics behaviors, a quadratic optimization method is proposed based on the different characteristics of kinematic and dynamic optimization. This method includes two steps of optimization, that is, kinematic and dynamic optimization. Meanwhile, it uses the results of the kinematic optimization as the constraint equations of dynamic optimization. This method is used in the parameters optimization of transplanting mechanism with elliptic planetary gears of high-speed rice seedling transplanter with remarkable significance. The parameters spectrum, which meets to the kinematic requirements, is obtained through visualized human-computer interactions in the kinematics optimization, and the optimal parameters are obtained based on improved genetic algorithm in dynamic optimization. In the dynamic optimization, the objective function is chosen as the optimal＇ dynamic behavior and the constraint equations are from the results of the kinematic optimization, This method is suitable for multi-objective optimization when both the kinematic and dynamic performances act as objective functions.展开更多
Aerodynamic parameters are important factors that affect projectile flight movement. To obtain accurate aerodynamic parameters, a hybrid genetic algorithm is proposed to identify and optimize the aerodynamic parameter...Aerodynamic parameters are important factors that affect projectile flight movement. To obtain accurate aerodynamic parameters, a hybrid genetic algorithm is proposed to identify and optimize the aerodynamic parameters of projectile. By combining the traditional simulated annealing method that is easy to fall into local optimum solution but hard to get global parameters with the genetic algorithm that has good global optimization ability but slow local optimization ability, the hybrid genetic algo- rithm makes full use of the advantages of the two algorithms for the optimization of projectile aerodynamic parameters. The simulation results show that the hybrid genetic algorithm is better than a single algorithm.展开更多
基金National Science and Technology Support Program,China(No.2012BAF13B03)Program of Shanghai Subject Chief Scientist,China(No.12XD1420300)
文摘A detailed analysis of operational process and principle of ammonia-recovery system in the modified equipment of flax fiber,which will be applied to parameters optimizing of the ammoniarecovery system as a foundational principle,is presented. According to the principle,an ammonia compressor,whose working conditions are based on key operational parameters of the whole ammoniarecovery system, is the mainly energy-consumption part of ammonia-recovery system in the modified equipment of flax fiber. A generally mathematical model based on work efficiency of an ammonia compressor is founded,which is available to rate effective work and energy consumption of the ammonia compressor. The optimum operation-efficiency of the ammonia compressor is chosen as the goal to analyze and calculate the key operational parameters of the ammonia-recovery system. In the above analyzing and calculating,a mathematical model on ammonia flowing from the reactor to the register 1 is developed,in order to provide further understanding of the principle of an ammonia-recovery system. At the meantime,the ammonia flow regime in the pipeline and the process of ammonia inflation and deflation from the reactor to the register 1 are taken separately into account in the model. An iterative method is for obtaining parametric solutions of the mathematical model on ammonia flowing from the reactor to the register 1 and the key operational parameters of the ammoniarecovery system. A parametric analysis is put forward to complete showing the ammonia velocity or the state of the reactor and the register 1. The key optimized parameters will be achieved in term of the minimum efficiency after comparing the work efficiencies of an ammonia compressor at different working conditions.
文摘Aim To obtain an optimizing range of the main configuration parameters of double swirls combustion system (DSCS) Methods To analyze the influence of DS combustion cham-ber configuration parameters on fuel spray and mixing by means of the fuel jet developmentperiphery charts obtained by the high speed photography with a modeling test device deve-loped by authors,and to examine it by the tests on a single cylinder diesel engine.Resultsand Conclusion The mixing process can be divided into four phases.The optimizing range of the ration of the inner chamber diameter to the cylinder bore,d2/D,is 0.4-0.7; and the outerchamber diameter,d1 the height of the circular ridge to the piston top face,h1,the radius of outer/inner chamber circle,R1,R2 ,the max depth of outer/inner chamber bowl,H1,H2,etc. are also important
文摘From the Physical Optics theory (PO) and Leontovich Impedance Boundary Condition (IBC), We research RCS reduction (RCSR) of multilayer dielectric and magnetic medium on different shape conductors such as plate, cuboid and cone by use of Matlab programs. Some available RCS data and graph results are given. These show the connection between Radar Absorbent Material (RAM) parameters and the number of layers. In the mean time, the relation between RAM optimized parameters and RCS value is also shown. It has better practical significance.
基金Supported by the General Program of the NATIONAL NATURAL SCIENCE FOUNDATION OF CHINA(52374004)National Key Research and Development Program(2023YFF06141022023YFE0110900)。
文摘The method for optimizing the hydraulic fracturing parameters of the cube development infill well pad was proposed,aiming at the well pattern characteristic of“multi-layer and multi-period”of the infill wells in Sichuan Basin.The fracture propagation and inter-well interference model were established based on the evolution of 4D in-situ stress,and the evolution characteristics of stress and the mechanism of interference between wells were analyzed.The research shows that the increase in horizontal stress difference and the existence of natural fractures/faults are the main reasons for inter-well interference.Inter-well interference is likely to occur near the fracture zones and between the infill wells and parent wells that have been in production for a long time.When communication channels are formed between the infill wells and parent wells,it can increase the productivity of parent wells in the short term.However,it will have a delayed negative impact on the long-term sustained production of both infill wells and parent wells.The change trend of in-situ stress caused by parent well production is basically consistent with the decline trend of pore pressure.The lateral disturbance range of in-situ stress is initially the same as the fracture length and reaches 1.5 to 1.6 times that length after 2.5 years.The key to avoiding inter-well interference is to optimize the fracturing parameters.By adopting the M-shaped well pattern,the optimal well spacing for the infill wells is 300 m,the cluster spacing is 10 m,and the liquid volume per stage is 1800 m^(3).
基金supported by the Science and Technology Research Program of Chongqing Municipal Education Commission(KJQN202401501,KJZD-M202401501).
文摘This work proposes an optimization method for gas storage operation parameters under multi-factor coupled constraints to improve the peak-shaving capacity of gas storage reservoirs while ensuring operational safety.Previous research primarily focused on integrating reservoir,wellbore,and surface facility constraints,often resulting in broad constraint ranges and slow model convergence.To solve this problem,the present study introduces additional constraints on maximum withdrawal rates by combining binomial deliverability equations with material balance equations for closed gas reservoirs,while considering extreme peak-shaving demands.This approach effectively narrows the constraint range.Subsequently,a collaborative optimization model with maximum gas production as the objective function is established,and the model employs a joint solution strategy combining genetic algorithms and numerical simulation techniques.Finally,this methodology was applied to optimize operational parameters for Gas Storage T.The results demonstrate:(1)The convergence of the model was achieved after 6 iterations,which significantly improved the convergence speed of the model;(2)The maximum working gas volume reached 11.605×10^(8) m^(3),which increased by 13.78%compared with the traditional optimization method;(3)This method greatly improves the operation safety and the ultimate peak load balancing capability.The research provides important technical support for the intelligent decision of injection and production parameters of gas storage and improving peak load balancing ability.
基金the financial support provided by the National Key R&D Program of China(Grant No.2023YFC3903900)the Science and Technology Innovation Talent Program of Hubei Province(Grant No.2022EJD002)+1 种基金the Sichuan Science and Technology Program(Grant No.2025ZNSFSC0378)the Key Laboratory of Green Chemistry of Sichuan Institutes of Higher Education(Grant No.LZJ2303).
文摘Specialized vanadium(V)-iron(Fe)-based alloy additives utilized in the production of V-containing steels were investigated.Vanadium slag from the Panzhihua region of China was utilized as a raw material to optimize process parameters for the preparation of V-Fe-based alloy via silicon thermal reduction.Experiments were conducted to investigate the effects of reduction temperature,holding time,and slag composition on alloy-slag separation,alloy microstructure,and the oxide content of residual slag,with an emphasis on the recovery of valuable metal elements.The results indicated that the optimal process conditions for silicon thermal reduction were achieved at reduction temperature of 1823 K,holding time of 240 min,and slag composition of 45 wt.%SiO_(2),40 wt.%CaO,and 15 wt.%Al_(2)O_(3).The resulting V-Fe-based alloy predominantly consisted of Fe-based phases such as Fe,titanium(Ti),silicon(Si)and manganese(Mn),with Si,V,as well as chromium(Cr)concentrated in the intercrystalline phase of the Fe-based alloy.The recoveries of Fe,Mn,Cr,V,and Ti under the optimal conditions were 96.30%,91.96%,86.53%,80.29%,and 74.82%,respectively.The key components of the V-Fe-based alloy obtained were 41.96 wt.%Si,27.55 wt.%Fe,12.13 wt.%Mn,5.53 wt.%V,4.86 wt.%Cr,and 3.74 wt.%Ti,thereby enabling the comprehensive recovery of the valuable metal from vanadium slag.
基金supported by the National Key R&D Program of China(No.2022YFA1005204l)。
文摘Silicone material extrusion(MEX)is widely used for processing liquids and pastes.Owing to the uneven linewidth and elastic extrusion deformation caused by material accumulation,products may exhibit geometric errors and performance defects,leading to a decline in product quality and affecting its service life.This study proposes a process parameter optimization method that considers the mechanical properties of printed specimens and production costs.To improve the quality of silicone printing samples and reduce production costs,three machine learning models,kernel extreme learning machine(KELM),support vector regression(SVR),and random forest(RF),were developed to predict these three factors.Training data were obtained through a complete factorial experiment.A new dataset is obtained using the Euclidean distance method,which assigns the elimination factor.It is trained with Bayesian optimization algorithms for parameter optimization,the new dataset is input into the improved double Gaussian extreme learning machine,and finally obtains the improved KELM model.The results showed improved prediction accuracy over SVR and RF.Furthermore,a multi-objective optimization framework was proposed by combining genetic algorithm technology with the improved KELM model.The effectiveness and reasonableness of the model algorithm were verified by comparing the optimized results with the experimental results.
基金sponsored by the National Natural Science Foundation of China,China(No.52304002).
文摘Rocking the drillstring at the surface during slide drilling is a common method for reducing drag when drilling horizontal wells.However,the current methods for determining the parameters for rocking are insufficient,limiting the widespread use of this technology.In this study,the influence of rocking parameters on the friction-reduction effect was investigated using an axialetorsional dynamic model of the drillstring and an experimental apparatus for rocking-assisted slide drilling in a simulated horizontal well.The research shows that increasing the rocking speed is beneficial improving the friction-reduction effect,but there is a diminishing marginal effect.A method was proposed to optimize the rocking speed using the equivalent axial drag coefficienterocking speed curve.Under the influence of rocking,the downhole weight on bit(WOB)exhibits a sinusoidal-like variation,with the predominant frequency being twice the rocking frequency.The fluctuation amplitude of the WOB in the horizontal section has a linear relationship with the rocking-affected depth.Based on this,a method was proposed to estimate the rockingaffected depth using the fluctuation amplitude of the standpipe pressure difference.Application of this method in the drilling field has improved the rate of penetration and toolface stability,demonstrating the reliability and effectiveness of the methods proposed in this paper.
基金funded by the National Key R&D Program“Transportation Infrastructure”project(No.2022YFB2603400)the Technology Research and Development Plan Program of China State Railway Group Co.,Ltd.(No.Q2024T001)the National project pre research project of Suzhou City University(No.2023SGY019).
文摘Purpose-The indoor vibration compaction test(IVCT)was a key step in controlling the compaction quality for high-speed railway graded aggregate(HRGA),which currently had a research gap on the assessment indicators and compaction parameters.Design/methodology/approach-To address these issues,a novel multi-indicator IVCT method was proposed,including physical indicator dry density(ρd)and mechanical indicators dynamic stiffness(Krb)and bearing capacity coefficient(K20).Then,a series of IVCTs on HRGA under different compaction parameters were conducted with an improved vibration compactor,which could monitor the physical-mechanical indicators in real-time.Finally,the optimal vibration compaction parameters,including the moisture content(ω),the diameter-to-maximum particle size ratio(Rd),the thickness-to-maximum particle size ratio(Rh),the vibration frequency(f),the vibration mass(Mc)and the eccentric distance(re),were determined based on the evolution characteristics for the physical-mechanical indicators during compaction.Findings-All results indicated that theρd gradually increased and then stabilized,and the Krb initially increased and then decreased.Moreover,the inflection time of the Krb was present as the optimal compaction time(Tlp)during compaction.Additionally,optimal compaction was achieved whenωwas the water-holding content after mud pumping,Rd was 3.4,Rh was 3.5,f was the resonance frequency,and the ratio between the excitation force and the Mc was 1.8.Originality/value-The findings of this paper were significant for the quality control of HRGA compaction.
基金Project (51005112) supported by the National Natural Science Foundation of ChinaProject (2010ZF56019) supported by the Aviation Science Foundation of China+1 种基金Project (GJJ11156) supported by the Education Commission of Jiangxi Province, ChinaProject(GF200901008) supported by the Open Fund of National Defense Key Disciplines Laboratory of Light Alloy Processing Science and Technology, China
文摘The high temperature deformation behaviors of α＋β type titanium alloy TC11 （Ti-6.5Al-3.5Mo-1.5Zr-0.3Si） with coarse lamellar starting microstructure were investigated based on the hot compression tests in the temperature range of 950-1100 ℃ and the strain rate range of 0.001-10 s-1. The processing maps at different strains were then constructed based on the dynamic materials model, and the hot compression process parameters and deformation mechanism were optimized and analyzed, respectively. The results show that the processing maps exhibit two domains with a high efficiency of power dissipation and a flow instability domain with a less efficiency of power dissipation. The types of domains were characterized by convergence and divergence of the efficiency of power dissipation, respectively. The convergent domain in a＋fl phase field is at the temperature of 950-990 ℃ and the strain rate of 0.001-0.01 s^-1, which correspond to a better hot compression process window of α＋β phase field. The peak of efficiency of power dissipation in α＋β phase field is at 950 ℃ and 0.001 s 1, which correspond to the best hot compression process parameters of α＋β phase field. The convergent domain in β phase field is at the temperature of 1020-1080 ℃ and the strain rate of 0.001-0.1 s^-l, which correspond to a better hot compression process window of β phase field. The peak of efficiency of power dissipation in ℃ phase field occurs at 1050 ℃ over the strain rates from 0.001 s^-1 to 0.01 s^-1, which correspond to the best hot compression process parameters of ,8 phase field. The divergence domain occurs at the strain rates above 0.5 s^-1 and in all the tested temperature range, which correspond to flow instability that is manifested as flow localization and indicated by the flow softening phenomenon in stress-- strain curves. The deformation mechanisms of the optimized hot compression process windows in a＋β and β phase fields are identified to be spheroidizing and dynamic recrystallizing controlled by self-diffusion mechanism, respectively. The microstructure observation of the deformed specimens in different domains matches very well with the optimized results.
基金Project (192450/I30) supported by the Norwegian Research Council under the Strategic University Program
文摘With the help of FESEM, high resolution electron backscatter diffraction can investigate the grains/subgrains as small as a few tens of nanometers with a good angular resolution （~0.5°）. Fast development of EBSD speed （up to 1100 patterns per second） contributes that the number of published articles related to EBSD has been increasing sharply year by year. This paper reviews the sample preparation, parameters optimization and analysis of EBSD technique, emphasizing on the investigation of ultrafine grained and nanostructured materials processed by severe plastic deformation （SPD）. Detailed and practical parameters of the electropolishing, silica polishing and ion milling have been summarized. It is shown that ion milling is a real universal and promising polishing method for EBSD preparation of almost all materials. There exists a maximum value of indexed points as a function of step size. The optimum step size depends on the magnification and the board resolution/electronic step size. Grains/subgrains and texture, and grain boundary structure are readily obtained by EBSD. Strain and stored energy may be analyzed by EBSD.
基金Shanxi Province Science and Technology Research Project(No.20140321008-03)
文摘The paper analyzes the factors influencing machine tool selection. By using fuzzy mathematics theory, we establish a theorietical model for optimal machine tool selection considering geometric features, clamping size, machining range, machining precision and surface roughness. By means of fuzzy comprehensive evaluation method, the membership degree of machine tool selection and the largest comprehensive evaluation index are determined. Then the reasonably automatic selection of machine tool is realized in the generative computer aided process planning （CAPP） system. Finally, the finite element model based on ABAQUS is established and the cutting process of machine tool is simulated. According to the theoretical and empirical cutting parameters and the curve of surface residual stress, the optimal cutting parameters can be determined.
基金Project(9140A12060110BQ03)supported by the National Key Laboratory of Science and Technology on Materials under Shock and Impact,China
文摘Electroless copper plating on diamond particles precoated with 1%Cr was carried out to evaluate the effects of various experimental parameters on coating quality and deposition rate to obtain the optimized reaction parameters. The formulated samples under optimized parameters were characterized by X-ray diffraction, scanning electron microscopy, energy dispersive spectroscopy, X-ray photoelectron spectra and optical microscopy. The best parameters, where uniform and maximum coating thickness was achieved, are etching with 20%NaOH for 30 min, sensitization and activation with SnCl2 and PdCl2 for 5 and 20 min, respectively. The composition of the copper solution bath was 16 g/L CuSO4＆#183;5H2O, 35 mL/L formaldehyde （HCHO）, 23 g/L KNaC4H4O6 at 60 ℃, pH=13 and stirring at （350±15） r/min under ultrasonication.
文摘A grating eddy current displacement sensor(GECDS) can be used in a watertight electronic transducer to realize long range displacement or position measurement with high accuracy in difficult industry conditions.The parameters optimization of the sensor is essential for economic and efficient production.This paper proposes a method to combine an artificial neural network(ANN) and a genetic algorithm(GA) for the sensor parameters optimization.A neural network model is developed to map the complex relationship between design parameters and the nonlinearity error of the GECDS,and then a GA is used in the optimization process to determine the design parameter values,resulting in a desired minimal nonlinearity error of about 0.11%.The calculated nonlinearity error is 0.25%.These results show that the proposed method performs well for the parameters optimization of the GECDS.
基金supported by National Natural Science Foundation of China (Grant No. 51005207)Open Foundation of the Mechanical Engineering in Zhejiang University of Technology, China (Grant No.2009EP004)Foundation of Zhejiang Provincial Education Department of China (Grant No. Y200908129)
文摘The research on the parameters optimization for gasbag polishing machine tools, mainly aims at a better kinematics performance and a design scheme. Serial structural arm is mostly employed in gasbag polishing machine tools at present, but it is disadvantaged by its complexity, big inertia, and so on. In the multi-objective parameters optimization, it is very difficult to select good parameters to achieve excellent performance of the mechanism. In this paper, a statistics parameters optimization method based on index atlases is presented for a novel 5-DOF gasbag polishing machine tool. In the position analyses, the structure and workspace for a novel 5-DOF gasbag polishing machine tool is developed, where the gasbag polishing machine tool is advantaged by its simple structure, lower inertia and bigger workspace. In the kinematics analyses, several kinematics performance evaluation indices of the machine tool are proposed and discussed, and the global kinematics performance evaluation atlases are given. In the parameters optimization process, considering the assembly technique, a design scheme of the 5-DOF gasbag polishing machine tool is given to own better kinematics performance based on the proposed statistics parameters optimization method, and the global linear isotropic performance index is 0.5, the global rotational isotropic performance index is 0.5, the global linear velocity transmission performance index is 1.012 3 m/s in the case of unit input matrix, the global rotational velocity transmission performance index is 0.102 7 rad/s in the case of unit input matrix, and the workspace volume is 1. The proposed research provides the basis for applications of the novel 5-DOF gasbag polishing machine tool, which can be applied to the modern industrial fields requiring machines with lower inertia, better kinematics transmission performance and better technological efficiency.
基金Supported by National Hi-tech Research and Development Program of China(863 Program,Grant No.2014AA041503)National Natural Science Foundation of China(Key Program,Grant No.51235003)
文摘As the manufacturing industry is facing increasingly serious environmental problems, because of which carbon tax policies are being implemented, choosing the optimum cutting parameters during the machining process is crucial for automobile panel dies in order to achieve synergistic minimization of the environment impact, product quality, and processing efficiency. This paper presents a processing task-based evaluation method to optimize the cutting parameters, considering the trade-off among carbon emissions, surface roughness, and processing time. Three objective models and their relationships with the cutting parameters were obtained through input–output, response surface, and theoretical analyses, respectively. Examples of cylindrical turning were applied to achieve a central composite design(CCD), and relative validation experiments were applied to evaluate the proposed method. The experiments were conducted on the CAK50135 di lathe cutting of AISI 1045 steel, and NSGA-Ⅱ was used to obtain the Pareto fronts of the three objectives. Based on the TOPSIS method, the Pareto solution set was ranked to find the optimal solution to evaluate and select the optimal cutting parameters. An S/N ratio analysis and contour plots were applied to analyze the influence of each decision variable on the optimization objective. Finally, the changing rules of a single factor for each objective were analyzed. The results demonstrate that the proposed method is effective in finding the trade-off among the three objectives and obtaining reasonable application ranges of the cutting parameters from Pareto fronts.
文摘The grating eddy current displacement sensor (GECDS) for distance or position measurement used in watertight electronic calipers was described. The sensor relies on repetitive variation of inductance against displacement caused by the change of coupling areas between moving coils and static reflectors. The investigations focused on setting up and utilizing a computer model of the 3D eddy current fields and geometry to analyze causes of the production of measurement blind areas, and to investigate effects of the sensor parameters, such as axial gap between coils and reflectors, reflector length and reflector width on characteristics of the sensor. Simulation results indicated that the sensor has the smallest nonlinearity error of 0.15%, which agrees well with the experimental results.
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.
基金This project is supported by National Natural Science Foundation of China (No.50275137)Basic Research Major Project of China Science and Technology Ministry(No.2004CCA05700)Provincial Natural Science Foundation of Zhejiang, China (No. Z105706).
文摘In order that the mechanism designed meets the requirements of kinematics with optimal dynamics behaviors, a quadratic optimization method is proposed based on the different characteristics of kinematic and dynamic optimization. This method includes two steps of optimization, that is, kinematic and dynamic optimization. Meanwhile, it uses the results of the kinematic optimization as the constraint equations of dynamic optimization. This method is used in the parameters optimization of transplanting mechanism with elliptic planetary gears of high-speed rice seedling transplanter with remarkable significance. The parameters spectrum, which meets to the kinematic requirements, is obtained through visualized human-computer interactions in the kinematics optimization, and the optimal parameters are obtained based on improved genetic algorithm in dynamic optimization. In the dynamic optimization, the objective function is chosen as the optimal＇ dynamic behavior and the constraint equations are from the results of the kinematic optimization, This method is suitable for multi-objective optimization when both the kinematic and dynamic performances act as objective functions.
文摘Aerodynamic parameters are important factors that affect projectile flight movement. To obtain accurate aerodynamic parameters, a hybrid genetic algorithm is proposed to identify and optimize the aerodynamic parameters of projectile. By combining the traditional simulated annealing method that is easy to fall into local optimum solution but hard to get global parameters with the genetic algorithm that has good global optimization ability but slow local optimization ability, the hybrid genetic algo- rithm makes full use of the advantages of the two algorithms for the optimization of projectile aerodynamic parameters. The simulation results show that the hybrid genetic algorithm is better than a single algorithm.
