The work takes a new liquid-cooling plate in a power battery with pin fins inside the channel as the object.A mathematical model is established via the central composite design of the response surface to study the rel...The work takes a new liquid-cooling plate in a power battery with pin fins inside the channel as the object.A mathematical model is established via the central composite design of the response surface to study the relationships among the length,width,height,and spacing of pin fins;the maximum temperature and temperature difference of the battery module;and the pressure drop of the liquid-cooling plate.Model accuracy is verified via variance analysis.The new liquid-cooling plate enables the power battery to work within an optimal temperature range.Appropriately increasing the length,width,and height and reducing the spacing of pin fins could reduce the temperature of the power battery module and improve the temperature uniformity.However,the pressure drop of the liquid-cooling plate increases.The structural parameters of the pin fins are optimized to minimize the maximum temperature and the temperature difference of the battery module as well as the pressure drop of the liquid-cooling plate.The errors between the values predicted and actual by the simulation test are 0.58%,4%,and 0.48%,respectively,which further verifies the model accuracy.The results reveal the influence of the structural parameters of the pin fins inside the liquid-cooling plate on its heat dissipation performance and pressure drop characteristics.A theoretical basis is provided for the design of liquid-cooling plates in power batteries and the optimization of structural parameters.展开更多
In order to improve the quality of 3D printed raspberry preserves after post-processing,microwave ovens combining infrared and microwave methods were utilized.The effects of infrared heating temperature,infrared heati...In order to improve the quality of 3D printed raspberry preserves after post-processing,microwave ovens combining infrared and microwave methods were utilized.The effects of infrared heating temperature,infrared heating time,microwave power,microwave heating time on the center temperature,moisture content,the chroma(C*),the total color difference(ΔE*),shape fidelity,hardness,and the total anthocyanin content of 3D printed raspberry preserves were analyzed by response surface method(RSM).The results showed that under combining with the two methods,infrared heating improved the fidelity and quality degradation of printed products,while microwave heating enhanced the efficiency of infrared heating.Infrared-microwave combination cooking could maintain relatively stable color appearance and shape of 3D printed raspberry preserves.The AHP–CRITIC hybrid weighting method combined with the response surface test to determine the comprehensive weights of the evaluation indicators optimized the process parameters,and the optimal process parameters were obtained:infrared heating temperature of 190℃,infrared heating time of 10 min and 30 s,microwave power of 300 W,and microwave heating time of 2 min and 6 s.The 3D printed raspberry cooking methods obtained under the optimal conditions seldom had color variation,porous structure,uniform texture,and high shape fidelity,which retained the characteristics of personalized manufacturing by 3D printing.This study could provide a reference for the postprocessing and quality control of 3D cooking methods.展开更多
A proper weapon system is very important for a na- tional defense system. Generally, it means selecting the optimal weapon system among many alternatives, which is a multiple- attribute decision making （MADM） proble...A proper weapon system is very important for a na- tional defense system. Generally, it means selecting the optimal weapon system among many alternatives, which is a multiple- attribute decision making （MADM） problem. This paper proposes a new mathematical model based on the response surface method （RSM） and the grey relational analysis （GRA）. RSM is used to obtain the experimental points and analyze the factors that have a significant impact on the selection results. GRA is used to an- alyze the trend relationship between alternatives and reference series. And then an RSM model is obtained, which can be used to calculate all alternatives and obtain ranking results. A real world application is introduced to illustrate the utilization of the model for the weapon selection problem. The results show that this model can be used to help decision-makers to make a quick comparison of alternatives and select a proper weapon system from multiple alternatives, which is an effective and adaptable method for solving the weapon system selection problem.展开更多
In order to present a new method for analyzing the reliability of a two-link flexible robot manipulator,Lagrange dynamics differential equations of the two-link flexible robot manipulator were established by using the...In order to present a new method for analyzing the reliability of a two-link flexible robot manipulator,Lagrange dynamics differential equations of the two-link flexible robot manipulator were established by using the integrated modal method and the multi-body system dynamics method.By using the Monte Carlo method,the random sample values of the dynamic parameters were obtained and Lagrange dynamics differential equations were solved for each random sample value which revealed their displacement,speed and acceleration.On this basis,dynamic stresses and deformations were obtained.By taking the maximum values of the stresses and the deformations as output responses and the random sample values of dynamic parameters as input quantities,extremum response surface functions were established.A number of random samples were then obtained by using the Monte Carlo method and then the reliability was analyzed by using the extremum response surface method.The results show that the extremum response surface method is an efficient and fast reliability analysis method with high-accuracy for the two-link flexible robot manipulator.展开更多
The response surface method(RSM) is one of the main approaches for analyzing reliability problems with implicit performance functions.An improved adaptive RSM based on uniform design(UD) and double weighted regression...The response surface method(RSM) is one of the main approaches for analyzing reliability problems with implicit performance functions.An improved adaptive RSM based on uniform design(UD) and double weighted regression(DWR) was presented.In the proposed method,the basic principle of the iteratively adaptive response surface method is applied.Uniform design is used to sample the fitting points.And a double weighted regression system considering the distances from the fitting points to the limit state surface and to the estimated design points is set to determine the coefficients of the response surface model.Compared with the conventional approaches,the fitting points selected by UD are more representative,and a better approximation in the key region is also observed with DWR.Numerical examples show that the proposed method has good convergent capability and computational accuracy.展开更多
Platycodon grandiflorum A.DC.(PAl)C)root was taken as experiment material to extract polysaccharide.On the base of single factor tests(extraction time,extraction temperature,liquid-solid ratio,solvent pH value and NaC...Platycodon grandiflorum A.DC.(PAl)C)root was taken as experiment material to extract polysaccharide.On the base of single factor tests(extraction time,extraction temperature,liquid-solid ratio,solvent pH value and NaCl concentration),the study concluded the main factors affecting the extraction of PADC polysaccharide,which are liquid-solid ratio,extraction time and extraction temperature.Then through central-composite test design,the extraction conditions were concluded as liquid-solid ratio 34.43,extraction time 89.83 min and extraction temperature 52.47℃.By means of validation experiments,the adequacy of this model was confirmed.展开更多
A new method for optimizing a butterfly-shaped linear ultrasonic motor was proposed to maximize its mechanical output. The finite element analysis technology and response surface methodology were combined together to ...A new method for optimizing a butterfly-shaped linear ultrasonic motor was proposed to maximize its mechanical output. The finite element analysis technology and response surface methodology were combined together to realize the optimal design of the butterfly-shaped linear ultrasonic motor. First, the operation principle of the motor was introduced. Second, the finite element parameterized model of the stator of the motor was built using ANSYS parametric design language and some structure parameters of the stator were selected as design variables. Third, the sample points were selected in design variable space using latin hypercube Design. Through modal analysis and harmonic response analysis of the stator based on these sample points, the target responses were obtained. These sample points and response values were combined together to build a response surface model. Finally, the simplex method was used to find the optimal solution. The experimental results showed that many aspects of the design requirements of the butterfly-shaped linear ultrasonic motor have been fulfilled. The prototype motor fabricated based on the optimal design result exhibited considerably high dynamic performance, such as no-load speed of 873 ram/s, maximal thrust of 27.5 N, maximal efficiency of 43%, and thrust-weight ratio of 45.8.展开更多
An approach of limit state equation for surrounding rock was put forward based on deformation criterion. A method of symmetrical sampling of basic random variables adopted by classical response surface method was mend...An approach of limit state equation for surrounding rock was put forward based on deformation criterion. A method of symmetrical sampling of basic random variables adopted by classical response surface method was mended, and peak value and deflection degree of basic random variables distribution curve were took into account in the mended sampling method. A calculation way of probability moment, based on mended Rosenbluth method, suitable for non-explicit performance function was put forward. The first, second, third and fourth order moments of functional function value were calculated by mended Rosenbluth method through the first, second, third and fourth order moments of basic random variable. A probability density the function（PDF） of functional function was deduced through its first, second, third and fourth moments, the PDF in the new method took the place of the method of quadratic polynomial to approximate real functional function and reliability probability was calculated through integral by the PDF for random variable of functional function value in the new method. The result shows that the improved response surface method can adapt to various statistic distribution types of basic random variables, its calculation process is legible and need not itemtive circulation. In addition, a stability probability of surrounding rock for a tunnel was calculated by the improved method, whose workload is only 30% of classical method and its accuracy is comparative.展开更多
The response surface methodology(RSM)was used to optimize the operating parameters during the bioleaching of Jinchuan high-magnesium nickel sulfide ore.The particle size,acid addition,pulp density and inoculation amou...The response surface methodology(RSM)was used to optimize the operating parameters during the bioleaching of Jinchuan high-magnesium nickel sulfide ore.The particle size,acid addition,pulp density and inoculation amount were chosen as the investigated parameters.To maximize the leaching efficiency of nickel,copper,cobalt and minimize the dissolution of magnesium and iron ions,the model suggested a combination of optimal parameters of particles less than 0.074 mm being 72.11%,sulfuric acid addition being 300 kg/t,pulp density being 5%and inoculation amount being 12.88%.Under the conditions,the average results of three parallel experiments were 89.43%of nickel leaching efficiency,36.78%of copper leaching efficiency,84.07%of cobalt leaching efficiency,49.19%of magnesium leaching efficiency and 0.20 g/L of iron concentration.The model indicated that the most significant factor in response of the leaching efficiency of valuable metal is the particle size,and the most significant factor in response to the leaching efficiency of harmful ions(Mg2+)is the amount of sulfuric acid addition.And according to the suggested models,no significance of the interaction effect between particle size and acid addition was shown.Under the optimized parameters suggested by models,the valuable metals could be separated from harmful ions during the bioleaching process.展开更多
The traditional voltage stability analysis method is mostly based on the deterministic mode1.and ignores the uncertainties of bus loads,power supplies,changes in network configuration and so on.However,the great expan...The traditional voltage stability analysis method is mostly based on the deterministic mode1.and ignores the uncertainties of bus loads,power supplies,changes in network configuration and so on.However,the great expansion of renewable power generations such as wind and solar energy in a power system has increased their uncertainty,and仃aditional techniques are limited in capturing their variable behavior.This leads to greater needs of new techniques and methodologies to properly quan tify the voltage stability of power systems.展开更多
In the non-linear microwave drying process, the incremental improved back-propagation （BP） neural network and response surface methodology （RSM） were used to build a predictive model of the combined effects of ind...In the non-linear microwave drying process, the incremental improved back-propagation （BP） neural network and response surface methodology （RSM） were used to build a predictive model of the combined effects of independent variables （the microwave power, the acting time and the rotational frequency） for microwave drying of selenium-rich slag. The optimum operating conditions obtained from the quadratic form of the RSM are： the microwave power of 14.97 kW, the acting time of 89.58 min, the rotational frequency of 10.94 Hz, and the temperature of 136.407 ℃. The relative dehydration rate of 97.1895% is obtained. Under the optimum operating conditions, the incremental improved BP neural network prediction model can predict the drying process results and different effects on the results of the independent variables. The verification experiments demonstrate the prediction accuracy of the network, and the mean squared error is 0.16. The optimized results indicate that RSM can optimize the experimental conditions within much more broad range by considering the combination of factors and the neural network model can predict the results effectively and provide the theoretical guidance for the follow-up production process.展开更多
Deformation prediction and the analysis of underground goaf are important to the safe and efficient recovery of residual ore when shifting from open-pit mining to underground mining.To address the comprehensive proble...Deformation prediction and the analysis of underground goaf are important to the safe and efficient recovery of residual ore when shifting from open-pit mining to underground mining.To address the comprehensive problem of stability in the double mined-out area of the Tong-Lv-Shan(TLS)mine,which employed the dry stacked gangue technology,this paper applies the function fitting theory and a regression analysis method to screen the sensitive interval of four influencing factors based on single-factor experiments and the numerical simulation software FLAC3D.The influencing factors of the TLS mine consist of the column thickness(d),gob area span(D),boundary pillar thickness(h)and height of tailing gangue(H).The fitting degree between the four factors and the displacement of the gob roof(W)is reasonable because the correlation coefficient(R2)is greater than0.9701.After establishing29groups that satisfy the principles of Box-Behnken design(BBD),the dry gangue tailings process was re-simulated for the selected sensitive interval.Using a combination of an analysis of variance(ANOVA),regression equations and a significance analysis,the prediction results of the response surface methodology(RSM)show that the significant degree for the stability of the mined-out area for the factors satisfies the relationship of h>D>d>H.The importance of the four factors cannot be disregarded in a comparison of the prediction results of the engineering test stope in the TLS mine.By comparing the data of monitoring points and function prediction,the proposed method has shown promising results,and the prediction accuracy of RSM model is acceptable.The relative errors of the two test stopes are1.67%and3.85%,respectively,which yield satisfactory reliability and reference values for the mines.展开更多
To reduce the fuel consumption and emissions and also enhance the molten aluminum quality, a mathematical model with user-developed melting model and burning capacity model, were established according to the features ...To reduce the fuel consumption and emissions and also enhance the molten aluminum quality, a mathematical model with user-developed melting model and burning capacity model, were established according to the features of melting process of regenerative aluminum melting furnaces. Based on validating results by heat balance test for an aluminum melting furnace, CFD （computational fluid dynamics） technique, in association with statistical experimental design were used to optimize the melting process of the aluminum melting furnace. Four important factors influencing the melting time, such as horizontal angle between burners, height-to-radius ratio, natural gas mass flow and air preheated temperature, were identified by PLACKETT-BURMAN design. A steepest descent method was undertaken to determine the optimal regions of these factors. Response surface methodology with BOX-BEHNKEN design was adopted to further investigate the mutual interactions between these variables on RSD （relative standard deviation） of aluminum temperature, RSD of furnace temperature and melting time. Multiple-response optimization by desirability function approach was used to determine the optimum melting process parameters. The results indicate that the interaction between the height-to-radius ratio and horizontal angle between burners affects the response variables significantly. The predicted results show that the minimum RSD of aluminum temperature （12.13%）, RSD of furnace temperature （18.50%） and melting time （3.9 h） could be obtained under the optimum conditions of horizontal angle between burners as 64°, height-to-radius ratio as 0.3, natural gas mass flow as 599 m3/h, and air preheated temperature as 639 ℃. These predicted values were further verified by validation experiments. The excellent correlation between the predicted and experimental values confirms the validity and practicability of this statistical optimum strategy.展开更多
The fatigue life of aeroengine turbine disc presents great dispersion due to the randomness of the basic variables,such as applied load,working temperature,geometrical dimensions and material properties.In order to am...The fatigue life of aeroengine turbine disc presents great dispersion due to the randomness of the basic variables,such as applied load,working temperature,geometrical dimensions and material properties.In order to ameliorate reliability analysis efficiency without loss of reliability,the distributed collaborative response surface method(DCRSM) was proposed,and its basic theories were established in this work.Considering the failure dependency among the failure modes,the distributed response surface was constructed to establish the relationship between the failure mode and the relevant random variables.Then,the failure modes were considered as the random variables of system response to obtain the distributed collaborative response surface model based on structure failure criterion.Finally,the given turbine disc structure was employed to illustrate the feasibility and validity of the presented method.Through the comparison of DCRSM,Monte Carlo method(MCM) and the traditional response surface method(RSM),the results show that the computational precision for DCRSM is more consistent with MCM than RSM,while DCRSM needs far less computing time than MCM and RSM under the same simulation conditions.Thus,DCRSM is demonstrated to be a feasible and valid approach for improving the computational efficiency of reliability analysis for aeroengine turbine disc fatigue life with multiple random variables,and has great potential value for the complicated mechanical structure with multi-component and multi-failure mode.展开更多
The technology that waste activated carbon after extracting gold is regenerated with steam under microwave heating was studied. The influence of the activation temperature, activation duration and steam flow rate on i...The technology that waste activated carbon after extracting gold is regenerated with steam under microwave heating was studied. The influence of the activation temperature, activation duration and steam flow rate on iodine adsorption value and regeneration yield of activated carbon was investigated. The response surface methodology （RSM） technique was utilized to optimize the process conditions. The optimum conditions for the preparation of activated carbon are identified to be activation temperature of 831 ℃, activation duration of 40 min and steam flow rate of 2.67 mL/min. The optimum conditions result in an activated carbon with an iodine number of 1048 mg/g and a yield of 40%, and the BET surface area evaluated using nitrogen adsorption isotherm is 1493 m2/g, with total pore volume of 1.242 cm3/g. And the pore structure of activated carbon regenerated is mainly composed of micropores and a small amount of mesopores.展开更多
Minimizing the impact of the mixed uncertainties(i.e.,the aleatory uncertainty and the epistemic uncertainty) for a complex product of compliant mechanism(CPCM) quality improvement signifies a fascinating research top...Minimizing the impact of the mixed uncertainties(i.e.,the aleatory uncertainty and the epistemic uncertainty) for a complex product of compliant mechanism(CPCM) quality improvement signifies a fascinating research topic to enhance the robustness.However, most of the existing works in the CPCM robust design optimization neglect the mixed uncertainties, which might result in an unstable design or even an infeasible design. To solve this issue, a response surface methodology-based hybrid robust design optimization(RSM-based HRDO) approach is proposed to improve the robustness of the quality characteristic for the CPCM via considering the mixed uncertainties in the robust design optimization. A bridge-type amplification mechanism is used to manifest the effectiveness of the proposed approach. The comparison results prove that the proposed approach can not only keep its superiority in the robustness, but also provide a robust scheme for optimizing the design parameters.展开更多
To make the dynamic assembly reliability analysis more effective for complex machinery of multi-object multi-discipline(MOMD),distributed collaborative extremum response surface method(DCERSM)was proposed based on ext...To make the dynamic assembly reliability analysis more effective for complex machinery of multi-object multi-discipline(MOMD),distributed collaborative extremum response surface method(DCERSM)was proposed based on extremum response surface method(ERSM).Firstly,the basic theories of the ERSM and DCERSM were investigated,and the strengths of DCERSM were proved theoretically.Secondly,the mathematical model of the DCERSM was established based upon extremum response surface function(ERSF).Finally,this model was applied to the reliability analysis of blade-tip radial running clearance(BTRRC)of an aeroengine high pressure turbine(HPT)to verify its advantages.The results show that the DCERSM can not only reshape the possibility of the reliability analysis for the complex turbo machinery,but also greatly improve the computational speed,save the computational time and improve the computational efficiency while keeping the accuracy.Thus,the DCERSM is verified to be feasible and effective in the dynamic assembly reliability(DAR)analysis of complex machinery.Moreover,this method offers an useful insight for designing and optimizing the dynamic reliability of complex machinery.展开更多
Some effective parameters on the copper extraction from Kiire chalcopyrite concentrate were optimized by using response surface methodology （RSM）. Experiments designed by RSM were carried out in the presence of ammo...Some effective parameters on the copper extraction from Kiire chalcopyrite concentrate were optimized by using response surface methodology （RSM）. Experiments designed by RSM were carried out in the presence of ammonium persulfate （APS） and different types of impeller in an autoclave system. Ammonium persulfate concentration and leaching temperature were defined numerically and three types of impellers were defined categorically as independent variables using experimental design software. The optimum condition for copper extraction from the chalcopyrite concentrate is found to be ammonium persulfate concentration of 277.77 kg/m3, leaching temperature of 389.98 K and wheel type of impeller. The proposed model equation using RSM has shown good agreement with the experimental data, with correlation coefficients R2 and RaZaj for the model as 0.89 and 0.84, respectively.展开更多
Rhamnolipid production by Pseudomonas aeruginosa ATCC 9027 with waste frying oil as sole carbon source was studied using response surface method. Cultures were incubated in shaking flask with temperature, NO3- and Mg2...Rhamnolipid production by Pseudomonas aeruginosa ATCC 9027 with waste frying oil as sole carbon source was studied using response surface method. Cultures were incubated in shaking flask with temperature, NO3- and Mg2+ concentrations as the variables. Meanwhile, fed-batch fermentation experiments were conducted. The results show that the three variables are closely related to rhamnolipid production. The optimal cultivation conditions are of 6.4 g/L NaNO3 , 3.1 g/L MgSO4 at 32 ℃, with the maximum rhamnolipid production of 6.6 g/L. The results of fed-batch fermentation experiments show that feeding the oil in two batches can enhance rhamnolipid production. The best time interval is 72 h with the maximum rhamnolipid production of 8.5 g/L. The data are potentially useful for mass production of rhamnolipid on oil waste with this bacterium.展开更多
To reasonably design the blade-tip radial running clearance(BTRRC) of high pressure turbine and improve the performance and reliability of gas turbine, the multi-object multi-discipline reliability sensitivity analysi...To reasonably design the blade-tip radial running clearance(BTRRC) of high pressure turbine and improve the performance and reliability of gas turbine, the multi-object multi-discipline reliability sensitivity analysis of BTRRC was accomplished from a probabilistic prospective by considering nonlinear material attributes and dynamic loads. Firstly, multiply response surface model(MRSM) was proposed and the mathematical model of this method was established based on quadratic function. Secondly, the BTRRC was decomposed into three sub-components(turbine disk, blade and casing), and then the single response surface functions(SRSFs) of three structures were built in line with the basic idea of MRSM. Thirdly, the response surface function(MRSM) of BTRRC was reshaped by coordinating SRSFs. From the analysis, it is acquired to probabilistic distribution characteristics of input-output variables, failure probabilities of blade-tip clearance under different static blade-tip clearances δ and major factors impacting BTRRC. Considering the reliability and efficiency of gas turbine, δ=1.87 mm is an optimally acceptable option for rational BTRRC. Through the comparison of three analysis methods(Monte Carlo method, traditional response surface method and MRSM), the results show that MRSM has higher accuracy and higher efficiency in reliability sensitivity analysis of BTRRC. These strengths are likely to become more prominent with the increasing times of simulations. The present study offers an effective and promising approach for reliability sensitivity analysis and optimal design of complex dynamic assembly relationship.展开更多
基金supported by the Education and Teaching Research Project of Universities in Fujian Province(FBJY20230167).
文摘The work takes a new liquid-cooling plate in a power battery with pin fins inside the channel as the object.A mathematical model is established via the central composite design of the response surface to study the relationships among the length,width,height,and spacing of pin fins;the maximum temperature and temperature difference of the battery module;and the pressure drop of the liquid-cooling plate.Model accuracy is verified via variance analysis.The new liquid-cooling plate enables the power battery to work within an optimal temperature range.Appropriately increasing the length,width,and height and reducing the spacing of pin fins could reduce the temperature of the power battery module and improve the temperature uniformity.However,the pressure drop of the liquid-cooling plate increases.The structural parameters of the pin fins are optimized to minimize the maximum temperature and the temperature difference of the battery module as well as the pressure drop of the liquid-cooling plate.The errors between the values predicted and actual by the simulation test are 0.58%,4%,and 0.48%,respectively,which further verifies the model accuracy.The results reveal the influence of the structural parameters of the pin fins inside the liquid-cooling plate on its heat dissipation performance and pressure drop characteristics.A theoretical basis is provided for the design of liquid-cooling plates in power batteries and the optimization of structural parameters.
基金Supported by the National Natural Science Foundation of China(32072352)。
文摘In order to improve the quality of 3D printed raspberry preserves after post-processing,microwave ovens combining infrared and microwave methods were utilized.The effects of infrared heating temperature,infrared heating time,microwave power,microwave heating time on the center temperature,moisture content,the chroma(C*),the total color difference(ΔE*),shape fidelity,hardness,and the total anthocyanin content of 3D printed raspberry preserves were analyzed by response surface method(RSM).The results showed that under combining with the two methods,infrared heating improved the fidelity and quality degradation of printed products,while microwave heating enhanced the efficiency of infrared heating.Infrared-microwave combination cooking could maintain relatively stable color appearance and shape of 3D printed raspberry preserves.The AHP–CRITIC hybrid weighting method combined with the response surface test to determine the comprehensive weights of the evaluation indicators optimized the process parameters,and the optimal process parameters were obtained:infrared heating temperature of 190℃,infrared heating time of 10 min and 30 s,microwave power of 300 W,and microwave heating time of 2 min and 6 s.The 3D printed raspberry cooking methods obtained under the optimal conditions seldom had color variation,porous structure,uniform texture,and high shape fidelity,which retained the characteristics of personalized manufacturing by 3D printing.This study could provide a reference for the postprocessing and quality control of 3D cooking methods.
基金supported by the National Natural Science Foundation of China(51375389)
文摘A proper weapon system is very important for a na- tional defense system. Generally, it means selecting the optimal weapon system among many alternatives, which is a multiple- attribute decision making （MADM） problem. This paper proposes a new mathematical model based on the response surface method （RSM） and the grey relational analysis （GRA）. RSM is used to obtain the experimental points and analyze the factors that have a significant impact on the selection results. GRA is used to an- alyze the trend relationship between alternatives and reference series. And then an RSM model is obtained, which can be used to calculate all alternatives and obtain ranking results. A real world application is introduced to illustrate the utilization of the model for the weapon selection problem. The results show that this model can be used to help decision-makers to make a quick comparison of alternatives and select a proper weapon system from multiple alternatives, which is an effective and adaptable method for solving the weapon system selection problem.
基金Project(2006AA04Z405)supported by the National High Technology Research and Development Program of ChinaProject(3102019)supported by Beijing Municipal Natural Science Foundation,China
文摘In order to present a new method for analyzing the reliability of a two-link flexible robot manipulator,Lagrange dynamics differential equations of the two-link flexible robot manipulator were established by using the integrated modal method and the multi-body system dynamics method.By using the Monte Carlo method,the random sample values of the dynamic parameters were obtained and Lagrange dynamics differential equations were solved for each random sample value which revealed their displacement,speed and acceleration.On this basis,dynamic stresses and deformations were obtained.By taking the maximum values of the stresses and the deformations as output responses and the random sample values of dynamic parameters as input quantities,extremum response surface functions were established.A number of random samples were then obtained by using the Monte Carlo method and then the reliability was analyzed by using the extremum response surface method.The results show that the extremum response surface method is an efficient and fast reliability analysis method with high-accuracy for the two-link flexible robot manipulator.
基金Project(50774095) supported by the National Natural Science Foundation of ChinaProject(200449) supported by National Outstanding Doctoral Dissertations Special Funds of China
文摘The response surface method(RSM) is one of the main approaches for analyzing reliability problems with implicit performance functions.An improved adaptive RSM based on uniform design(UD) and double weighted regression(DWR) was presented.In the proposed method,the basic principle of the iteratively adaptive response surface method is applied.Uniform design is used to sample the fitting points.And a double weighted regression system considering the distances from the fitting points to the limit state surface and to the estimated design points is set to determine the coefficients of the response surface model.Compared with the conventional approaches,the fitting points selected by UD are more representative,and a better approximation in the key region is also observed with DWR.Numerical examples show that the proposed method has good convergent capability and computational accuracy.
文摘Platycodon grandiflorum A.DC.(PAl)C)root was taken as experiment material to extract polysaccharide.On the base of single factor tests(extraction time,extraction temperature,liquid-solid ratio,solvent pH value and NaCl concentration),the study concluded the main factors affecting the extraction of PADC polysaccharide,which are liquid-solid ratio,extraction time and extraction temperature.Then through central-composite test design,the extraction conditions were concluded as liquid-solid ratio 34.43,extraction time 89.83 min and extraction temperature 52.47℃.By means of validation experiments,the adequacy of this model was confirmed.
基金Projects(51275235, 50975135) supported by the National Natural Science Foundation of ChinaProject(U0934004) supported by the Natural Science Foundation of Guangdong Province, ChinaProject(2011CB707602) supported by the National Basic Research Program of China
文摘A new method for optimizing a butterfly-shaped linear ultrasonic motor was proposed to maximize its mechanical output. The finite element analysis technology and response surface methodology were combined together to realize the optimal design of the butterfly-shaped linear ultrasonic motor. First, the operation principle of the motor was introduced. Second, the finite element parameterized model of the stator of the motor was built using ANSYS parametric design language and some structure parameters of the stator were selected as design variables. Third, the sample points were selected in design variable space using latin hypercube Design. Through modal analysis and harmonic response analysis of the stator based on these sample points, the target responses were obtained. These sample points and response values were combined together to build a response surface model. Finally, the simplex method was used to find the optimal solution. The experimental results showed that many aspects of the design requirements of the butterfly-shaped linear ultrasonic motor have been fulfilled. The prototype motor fabricated based on the optimal design result exhibited considerably high dynamic performance, such as no-load speed of 873 ram/s, maximal thrust of 27.5 N, maximal efficiency of 43%, and thrust-weight ratio of 45.8.
基金Project(50378036) supported by the National Natural Science Foundation of China Project (200503) supported by the Foundation ofCommunications Department of Hunan Province, China
文摘An approach of limit state equation for surrounding rock was put forward based on deformation criterion. A method of symmetrical sampling of basic random variables adopted by classical response surface method was mended, and peak value and deflection degree of basic random variables distribution curve were took into account in the mended sampling method. A calculation way of probability moment, based on mended Rosenbluth method, suitable for non-explicit performance function was put forward. The first, second, third and fourth order moments of functional function value were calculated by mended Rosenbluth method through the first, second, third and fourth order moments of basic random variable. A probability density the function（PDF） of functional function was deduced through its first, second, third and fourth moments, the PDF in the new method took the place of the method of quadratic polynomial to approximate real functional function and reliability probability was calculated through integral by the PDF for random variable of functional function value in the new method. The result shows that the improved response surface method can adapt to various statistic distribution types of basic random variables, its calculation process is legible and need not itemtive circulation. In addition, a stability probability of surrounding rock for a tunnel was calculated by the improved method, whose workload is only 30% of classical method and its accuracy is comparative.
基金Projects(51704028,51574036)supported by the National Natural Science Foundation of China。
文摘The response surface methodology(RSM)was used to optimize the operating parameters during the bioleaching of Jinchuan high-magnesium nickel sulfide ore.The particle size,acid addition,pulp density and inoculation amount were chosen as the investigated parameters.To maximize the leaching efficiency of nickel,copper,cobalt and minimize the dissolution of magnesium and iron ions,the model suggested a combination of optimal parameters of particles less than 0.074 mm being 72.11%,sulfuric acid addition being 300 kg/t,pulp density being 5%and inoculation amount being 12.88%.Under the conditions,the average results of three parallel experiments were 89.43%of nickel leaching efficiency,36.78%of copper leaching efficiency,84.07%of cobalt leaching efficiency,49.19%of magnesium leaching efficiency and 0.20 g/L of iron concentration.The model indicated that the most significant factor in response of the leaching efficiency of valuable metal is the particle size,and the most significant factor in response to the leaching efficiency of harmful ions(Mg2+)is the amount of sulfuric acid addition.And according to the suggested models,no significance of the interaction effect between particle size and acid addition was shown.Under the optimized parameters suggested by models,the valuable metals could be separated from harmful ions during the bioleaching process.
文摘The traditional voltage stability analysis method is mostly based on the deterministic mode1.and ignores the uncertainties of bus loads,power supplies,changes in network configuration and so on.However,the great expansion of renewable power generations such as wind and solar energy in a power system has increased their uncertainty,and仃aditional techniques are limited in capturing their variable behavior.This leads to greater needs of new techniques and methodologies to properly quan tify the voltage stability of power systems.
基金Project(50734007) supported by the National Natural Science Foundation of China
文摘In the non-linear microwave drying process, the incremental improved back-propagation （BP） neural network and response surface methodology （RSM） were used to build a predictive model of the combined effects of independent variables （the microwave power, the acting time and the rotational frequency） for microwave drying of selenium-rich slag. The optimum operating conditions obtained from the quadratic form of the RSM are： the microwave power of 14.97 kW, the acting time of 89.58 min, the rotational frequency of 10.94 Hz, and the temperature of 136.407 ℃. The relative dehydration rate of 97.1895% is obtained. Under the optimum operating conditions, the incremental improved BP neural network prediction model can predict the drying process results and different effects on the results of the independent variables. The verification experiments demonstrate the prediction accuracy of the network, and the mean squared error is 0.16. The optimized results indicate that RSM can optimize the experimental conditions within much more broad range by considering the combination of factors and the neural network model can predict the results effectively and provide the theoretical guidance for the follow-up production process.
基金Project(2017YFC0602902) supported by the National Science and Technology Pillar Program during the 13th Five-Year Plan Period,ChinaProject(2015CX005) supported by the Innovation Driven Plan of Central South University,ChinaProject(2016zzts445) supported by the Fundamental Research Funds for the Central Universities,China
文摘Deformation prediction and the analysis of underground goaf are important to the safe and efficient recovery of residual ore when shifting from open-pit mining to underground mining.To address the comprehensive problem of stability in the double mined-out area of the Tong-Lv-Shan(TLS)mine,which employed the dry stacked gangue technology,this paper applies the function fitting theory and a regression analysis method to screen the sensitive interval of four influencing factors based on single-factor experiments and the numerical simulation software FLAC3D.The influencing factors of the TLS mine consist of the column thickness(d),gob area span(D),boundary pillar thickness(h)and height of tailing gangue(H).The fitting degree between the four factors and the displacement of the gob roof(W)is reasonable because the correlation coefficient(R2)is greater than0.9701.After establishing29groups that satisfy the principles of Box-Behnken design(BBD),the dry gangue tailings process was re-simulated for the selected sensitive interval.Using a combination of an analysis of variance(ANOVA),regression equations and a significance analysis,the prediction results of the response surface methodology(RSM)show that the significant degree for the stability of the mined-out area for the factors satisfies the relationship of h>D>d>H.The importance of the four factors cannot be disregarded in a comparison of the prediction results of the engineering test stope in the TLS mine.By comparing the data of monitoring points and function prediction,the proposed method has shown promising results,and the prediction accuracy of RSM model is acceptable.The relative errors of the two test stopes are1.67%and3.85%,respectively,which yield satisfactory reliability and reference values for the mines.
基金Project(2009BSXT022) supported by the Dissertation Innovation Foundation of Central South University, ChinaProject(07JJ4016) supported by Natural Science Foundation of Hunan Province, ChinaProject(U0937604) supported by National Natural Science Foundation of China
文摘To reduce the fuel consumption and emissions and also enhance the molten aluminum quality, a mathematical model with user-developed melting model and burning capacity model, were established according to the features of melting process of regenerative aluminum melting furnaces. Based on validating results by heat balance test for an aluminum melting furnace, CFD （computational fluid dynamics） technique, in association with statistical experimental design were used to optimize the melting process of the aluminum melting furnace. Four important factors influencing the melting time, such as horizontal angle between burners, height-to-radius ratio, natural gas mass flow and air preheated temperature, were identified by PLACKETT-BURMAN design. A steepest descent method was undertaken to determine the optimal regions of these factors. Response surface methodology with BOX-BEHNKEN design was adopted to further investigate the mutual interactions between these variables on RSD （relative standard deviation） of aluminum temperature, RSD of furnace temperature and melting time. Multiple-response optimization by desirability function approach was used to determine the optimum melting process parameters. The results indicate that the interaction between the height-to-radius ratio and horizontal angle between burners affects the response variables significantly. The predicted results show that the minimum RSD of aluminum temperature （12.13%）, RSD of furnace temperature （18.50%） and melting time （3.9 h） could be obtained under the optimum conditions of horizontal angle between burners as 64°, height-to-radius ratio as 0.3, natural gas mass flow as 599 m3/h, and air preheated temperature as 639 ℃. These predicted values were further verified by validation experiments. The excellent correlation between the predicted and experimental values confirms the validity and practicability of this statistical optimum strategy.
基金Project(51335003)supported by the National Natural Science Foundation of ChinaProject(20111102110011)supported by the Specialized Research Fund for the Doctoral Program of Higher Education of China
文摘The fatigue life of aeroengine turbine disc presents great dispersion due to the randomness of the basic variables,such as applied load,working temperature,geometrical dimensions and material properties.In order to ameliorate reliability analysis efficiency without loss of reliability,the distributed collaborative response surface method(DCRSM) was proposed,and its basic theories were established in this work.Considering the failure dependency among the failure modes,the distributed response surface was constructed to establish the relationship between the failure mode and the relevant random variables.Then,the failure modes were considered as the random variables of system response to obtain the distributed collaborative response surface model based on structure failure criterion.Finally,the given turbine disc structure was employed to illustrate the feasibility and validity of the presented method.Through the comparison of DCRSM,Monte Carlo method(MCM) and the traditional response surface method(RSM),the results show that the computational precision for DCRSM is more consistent with MCM than RSM,while DCRSM needs far less computing time than MCM and RSM under the same simulation conditions.Thus,DCRSM is demonstrated to be a feasible and valid approach for improving the computational efficiency of reliability analysis for aeroengine turbine disc fatigue life with multiple random variables,and has great potential value for the complicated mechanical structure with multi-component and multi-failure mode.
基金Project(2013AA064003)supported by the National High Technology Research and Development Program of ChinaProject(2012HB008)supported by Young and Middle-aged Academic Technology Leader Backup Talent Cultivation Program in Yunnan Province,China
文摘The technology that waste activated carbon after extracting gold is regenerated with steam under microwave heating was studied. The influence of the activation temperature, activation duration and steam flow rate on iodine adsorption value and regeneration yield of activated carbon was investigated. The response surface methodology （RSM） technique was utilized to optimize the process conditions. The optimum conditions for the preparation of activated carbon are identified to be activation temperature of 831 ℃, activation duration of 40 min and steam flow rate of 2.67 mL/min. The optimum conditions result in an activated carbon with an iodine number of 1048 mg/g and a yield of 40%, and the BET surface area evaluated using nitrogen adsorption isotherm is 1493 m2/g, with total pore volume of 1.242 cm3/g. And the pore structure of activated carbon regenerated is mainly composed of micropores and a small amount of mesopores.
基金supported by the National Natural Science Foundation of China(71702072 71811540414+2 种基金 71573115)the Natural Science Foundation for Jiangsu Institutions(BK20170810)the Ministry of Education of Humanities and Social Science Planning Fund(18YJA630008)
文摘Minimizing the impact of the mixed uncertainties(i.e.,the aleatory uncertainty and the epistemic uncertainty) for a complex product of compliant mechanism(CPCM) quality improvement signifies a fascinating research topic to enhance the robustness.However, most of the existing works in the CPCM robust design optimization neglect the mixed uncertainties, which might result in an unstable design or even an infeasible design. To solve this issue, a response surface methodology-based hybrid robust design optimization(RSM-based HRDO) approach is proposed to improve the robustness of the quality characteristic for the CPCM via considering the mixed uncertainties in the robust design optimization. A bridge-type amplification mechanism is used to manifest the effectiveness of the proposed approach. The comparison results prove that the proposed approach can not only keep its superiority in the robustness, but also provide a robust scheme for optimizing the design parameters.
基金Project(51175017)supported by the National Natural Science Foundation of ChinaProject(YWF-12-RBYJ-008)supported by the Innovation Foundation of Beihang University for PhD Graduates,ChinaProject(20111102110011)supported by the Research Fund for the Doctoral Program of Higher Education of China
文摘To make the dynamic assembly reliability analysis more effective for complex machinery of multi-object multi-discipline(MOMD),distributed collaborative extremum response surface method(DCERSM)was proposed based on extremum response surface method(ERSM).Firstly,the basic theories of the ERSM and DCERSM were investigated,and the strengths of DCERSM were proved theoretically.Secondly,the mathematical model of the DCERSM was established based upon extremum response surface function(ERSF).Finally,this model was applied to the reliability analysis of blade-tip radial running clearance(BTRRC)of an aeroengine high pressure turbine(HPT)to verify its advantages.The results show that the DCERSM can not only reshape the possibility of the reliability analysis for the complex turbo machinery,but also greatly improve the computational speed,save the computational time and improve the computational efficiency while keeping the accuracy.Thus,the DCERSM is verified to be feasible and effective in the dynamic assembly reliability(DAR)analysis of complex machinery.Moreover,this method offers an useful insight for designing and optimizing the dynamic reliability of complex machinery.
基金supported by the TUBITAK(Scientific and Technological Research Council of Turkey) under the Project No:106M177
文摘Some effective parameters on the copper extraction from Kiire chalcopyrite concentrate were optimized by using response surface methodology （RSM）. Experiments designed by RSM were carried out in the presence of ammonium persulfate （APS） and different types of impeller in an autoclave system. Ammonium persulfate concentration and leaching temperature were defined numerically and three types of impellers were defined categorically as independent variables using experimental design software. The optimum condition for copper extraction from the chalcopyrite concentrate is found to be ammonium persulfate concentration of 277.77 kg/m3, leaching temperature of 389.98 K and wheel type of impeller. The proposed model equation using RSM has shown good agreement with the experimental data, with correlation coefficients R2 and RaZaj for the model as 0.89 and 0.84, respectively.
基金Project(108100) supported by the Key Program for Science and Technology Research of Ministry of Education of ChinaProjects(50978087, 50908081) supported by the National Natural Science Foundation of China+1 种基金Project(531107011019) supported by the Hunan University Graduate Education Innovation Program, ChinaProject(CX2010B157) supported by the Hunan Provincial Innovation Foundation for Postgraduate students, China
文摘Rhamnolipid production by Pseudomonas aeruginosa ATCC 9027 with waste frying oil as sole carbon source was studied using response surface method. Cultures were incubated in shaking flask with temperature, NO3- and Mg2+ concentrations as the variables. Meanwhile, fed-batch fermentation experiments were conducted. The results show that the three variables are closely related to rhamnolipid production. The optimal cultivation conditions are of 6.4 g/L NaNO3 , 3.1 g/L MgSO4 at 32 ℃, with the maximum rhamnolipid production of 6.6 g/L. The results of fed-batch fermentation experiments show that feeding the oil in two batches can enhance rhamnolipid production. The best time interval is 72 h with the maximum rhamnolipid production of 8.5 g/L. The data are potentially useful for mass production of rhamnolipid on oil waste with this bacterium.
基金Projects(51175017,51245027)supported by the National Natural Science Foundation of China
文摘To reasonably design the blade-tip radial running clearance(BTRRC) of high pressure turbine and improve the performance and reliability of gas turbine, the multi-object multi-discipline reliability sensitivity analysis of BTRRC was accomplished from a probabilistic prospective by considering nonlinear material attributes and dynamic loads. Firstly, multiply response surface model(MRSM) was proposed and the mathematical model of this method was established based on quadratic function. Secondly, the BTRRC was decomposed into three sub-components(turbine disk, blade and casing), and then the single response surface functions(SRSFs) of three structures were built in line with the basic idea of MRSM. Thirdly, the response surface function(MRSM) of BTRRC was reshaped by coordinating SRSFs. From the analysis, it is acquired to probabilistic distribution characteristics of input-output variables, failure probabilities of blade-tip clearance under different static blade-tip clearances δ and major factors impacting BTRRC. Considering the reliability and efficiency of gas turbine, δ=1.87 mm is an optimally acceptable option for rational BTRRC. Through the comparison of three analysis methods(Monte Carlo method, traditional response surface method and MRSM), the results show that MRSM has higher accuracy and higher efficiency in reliability sensitivity analysis of BTRRC. These strengths are likely to become more prominent with the increasing times of simulations. The present study offers an effective and promising approach for reliability sensitivity analysis and optimal design of complex dynamic assembly relationship.
