A response surface method was utilized for the finite element model updating of a cable-stayed bridge in this paper to establish a baseline finite element model(FEM)that accurately reflects the characteristics of the ...A response surface method was utilized for the finite element model updating of a cable-stayed bridge in this paper to establish a baseline finite element model(FEM)that accurately reflects the characteristics of the actual bridge structure.Firstly,an initial FEM was established by the large-scale finite element software ANSYS,and the modal analysis was carried out on the dynamic response measured by the actual bridge structural health monitoring system.The initial error was obtained by comparing the dynamic characteristics of the measured data with those of the initial finite element model.Then,the second-order complete polynomial was selected to construct the response surface model;the corrected parameters were chosen using the sensitivity method.The response surface model(RSM)was fitted under the test cases designed using the central composite design method.After constructing the objective function,the RSMwas optimized and iterated by the sequential quadratic programmingmethod to obtain the corrected FEM.Finally,the dynamic characteristics of the modified FEM were compared with those of the actual bridge to get the final error.The results show that the modified FEM simulates the dynamic characteristics of the actual cable-stayed bridges more accurately.展开更多
A modified cellular automata （CA） model of dynamic recrystallization （DRX） and a flow stress-based nucleation parameter identification method have been developed. In the method, the modified CA model, which takes ...A modified cellular automata （CA） model of dynamic recrystallization （DRX） and a flow stress-based nucleation parameter identification method have been developed. In the method, the modified CA model, which takes the role of deformation degree on nucleation behavior into consideration, is coupled with an adaptive response surface model （ARSM） to search for the optimum nucleation parameter. The DRX behavior of an oxygen free high conductivity （OFHC） copper with different initial grain sizes has been taken as an example to validate the model. Good agreement is found between the simulated and the experimental results, which demonstrates that the new method can effectively improve the simulation accuracy.展开更多
The application of leaching process to extracting Mn from a low-grade manganese ore was investigated using a software based design of experiments. Four main parameters, i.e. sulfuric acid concentration, oxalic acid co...The application of leaching process to extracting Mn from a low-grade manganese ore was investigated using a software based design of experiments. Four main parameters, i.e. sulfuric acid concentration, oxalic acid concentration, time and temperature were considered in a central composite response surface design. The recoveries of Mn and Fe were selected as response of design. The optimum conditions under which the Mn and Fe recoveries were the highest and the time and temperature were the lowest were determined using statistical analysis and analysis of variance （ANOVA）. The results showed that Mn and Fe recoveries were 93.44% and 15.72% under the optimum condition, respectively. Also, sulfuric acid concentration was the most effective parameter affecting the process. The amounts of sulfuric and oxalic acid were obtained to be 7% and 42.50 g/L in optimum condition and the best time and temperature were 65 min and 63 ℃.展开更多
This investigation was undertaken to predict the mass gain （MG） of cobalt electroless deposition （ED） on ceramic SiC particles.Response surface methodology （RSM） based on a full factorial design with three ED pa...This investigation was undertaken to predict the mass gain （MG） of cobalt electroless deposition （ED） on ceramic SiC particles.Response surface methodology （RSM） based on a full factorial design with three ED parameters and 30 runs was used to conduct the experiments and to establish a mathematical model by means of Design-Expert software.Three ED parameters considered were pH,bath temperature and ceramic particle morphology.Analysis of variance was applied to validate the predicted model.The results of confirmation analysis by scanning electron microscopy （SEM） show that the developed models are reasonably accurate.The pH is the most effective parameter for the MG.Also,the highest mass gain is obtained for the lowest pH,highest bath temperatures and heat-treated SiC particles.In addition,the developed model shows that the optimal parameters to get a maximum value of mass gain are pH,bath temperature and ceramic particle state of 8,70 ℃ and heat treatment,respectively.展开更多
Performance of a hybrid reactor comprising of trickling filter （TF） and aeration tank （AT） unit was studied for biological treatment of wastewater containing mixture of phenol and m-cresol, using mixed microbial c...Performance of a hybrid reactor comprising of trickling filter （TF） and aeration tank （AT） unit was studied for biological treatment of wastewater containing mixture of phenol and m-cresol, using mixed microbial culture. The reactor was operated with hydraulic loading rates （HLR） and phenolics loading rates （PLR） between 0.222-1.078 m3/（m2-day） and 0.900-3.456 kg/（m3.day）, respectively. The efficiency of substrate removal varied between 71%-100% for the range of HLR and PLR studied. The fixed film unit showed better substrate removal efficiency than the aeration tank and was more resistant to substrate inhibition. The kinetic parameters related to both units of the reactor were evaluated and their variation with HLR and PLR were monitored. It revealed the presence of substrate inhibition at high PLR both in TF and AT unit. The biofilm model established the substrate concentration profile within the film by solving differential equation of substrate mass transfer using boundary problem solver tool ＇bvp4c＇ of MATLAB 7. 1 software. Response surface methodology was used to design and optimize the biodegradation process using Design Expert 8 software, where phenol and m-cresol concentrations, residence time were chosen as input variables and percentage of removal was the response. The design of experiment showed that a quadratic model could be fitted best for the present experimental study. Significant interaction of the residence time with the substrate concentrations was observed. The optimized condition for operating the reactor as predicted by the model was 230 mg/L of phenol, 190 mg/L of m-cresol with residence time of 24.82 hr to achieve 99.92% substrate removal.展开更多
This study discussed the application of response surface methodology(RSM)and central composite rotatable design(CCRD)for modeling and optimization of the influence of some operating variables on the performance of a l...This study discussed the application of response surface methodology(RSM)and central composite rotatable design(CCRD)for modeling and optimization of the influence of some operating variables on the performance of a lab scale thickener for dewatering of tailing in the flotation circuit.Four thickener operating variables,namely feed flowrate,solid percent,flocculant dosage and feedwell height were changed during the tests based on CCRD.The ranges of values of the thickener variables used in the design were a feed flowrate of 9–21 L/min,solid percent of 8%–20%,flocculant dosage of 1.25–4.25 g/t and feedwell height of 16–26 cm.A total of 30 thickening tests were conducted using lab scale thickener on flotation tailing obtained from the Sarcheshmeh copper mine,Iran.The underflow solid percent and bed height were expressed as functions of four operating parameters of thickener.Predicted values were found to be in good agreement with experimental values(R2values of 0.992 and 0.997 for underflow solid percent and bed height,respectively).This study has shown that the RSM and CCRD could effciently be applied for the modeling of thickener for dewatering of flotation tailing.展开更多
To develop a sound ozone（O_3） pollution control strategy,it is important to well understand and characterize the source contribution due to the complex chemical and physical formation processes of O_3.Using the ＂Sh...To develop a sound ozone（O_3） pollution control strategy,it is important to well understand and characterize the source contribution due to the complex chemical and physical formation processes of O_3.Using the ＂Shunde＂ city as a pilot summer case study,we apply an innovative response surface modeling（RSM） methodology based on the Community Multi-Scale Air Quality（CMAQ） modeling simulations to identify the O_3 regime and provide dynamic analysis of the precursor contributions to effectively assess the O_3 impacts of volatile organic compound（VOC） control strategy.Our results show that Shunde is a typical VOC-limited urban O_3 polluted city.The ＂Jiangmen＂ city,as the main upper wind area during July 2014,its VOCs and nitrogen oxides（NO_x） emissions make up the largest contribution（9.06%）.On the contrary,the contribution from local（Shunde） emission is lowest（6.35%） among the seven neighbor regions.The local VOCs industrial source emission has the largest contribution comparing to other precursor emission sectors in Shunde.The results of dynamic source contribution analysis further show that the local NO_x control could slightly increase the ground O_3 under low（10.00%） and medium（40.00%）reduction ratios,while it could start to turn positive to decrease ground O_3 under the high NO_x abatement ratio（75.00%）.The real-time assessment of O_3 impacts from VOCs control strategies in Pearl River Delta（PRD） shows that the joint regional VOCs emission control policy will effectively reduce the ground O_3 concentration in Shunde.展开更多
The copper extraction in shaking bioreactors was modeled and optimized using response surface methodology（RSM）. Influential parameters in the mesophilic bioleaching process of a low-grade copper ore including p H va...The copper extraction in shaking bioreactors was modeled and optimized using response surface methodology（RSM）. Influential parameters in the mesophilic bioleaching process of a low-grade copper ore including p H value, pulp density, and initial concentration of ferrous ions were comprehensively studied. The effect of leaching time on the response（copper extraction） at the 1st, 4th, 9th, 14 th and 22 nd days of treatment was modeled and examined. The central composite design methodology（CCD） was used as the design matrix to predict the optimal level of these parameters. Then, the model equation at the 22 nd day was optimized using the quadratic programming（QP） to maximize the total copper extraction within the studied experimental range. Under the optimal condition（initial p H value of 2.0, pulp density of 1.59%, and initial concentration of ferrous ions of 0 g/L）, the total copper extraction predicted by the model is 85.98% which is significantly close to that obtained from the experiment（84.57%）. The results show that RSM could be useful to predict the maximum copper extraction from a low-grade ore and investigate the effects of variables on the final response. Besides, a couple of statistically significant interactions are derived between p H value and pulp density as well as p H value and initial ferrous ion concentration which are precisely interpreted. However, there is no statistically significant interaction between the initial ferrous ion concentration and the pulp density. Additionally, the response at optimal levels of p H value and pulp density is found to be independent on the level of initial ferrous concentration.展开更多
The present paper discusses the modeling of tool geometry effects on the friction stir aluminum welds using response surface methodology. The friction stir welding tools were designed with different shoulder and tool ...The present paper discusses the modeling of tool geometry effects on the friction stir aluminum welds using response surface methodology. The friction stir welding tools were designed with different shoulder and tool probe geometries based on a design matrix. The matrix for the tool designing was made for three types of tools, based on three types of probes, with three levels each for defining the shoulder surface type and probe profile geometries. Then, the effects of tool shoulder and probe geometries on friction stirred aluminum welds were experimentally investigated with respect to weld strength, weld cross section area, grain size of weld and grain size of thermo-mechanically affected zone. These effects were modeled using multiple and response surface regression analysis. The response surface regression modeling were found to be appropriate for defining the friction stir weldment characteristics.展开更多
This paper investigates the scaled prediction variances in the errors-in-variables model and compares the performance with those in classic model of response surface designs for three factors.The ordinary least square...This paper investigates the scaled prediction variances in the errors-in-variables model and compares the performance with those in classic model of response surface designs for three factors.The ordinary least squares estimators of regression coefficients are derived from a second-order response surface model with errors in variables.Three performance criteria are proposed.The first is the difference between the empirical mean of maximum value of scaled prediction variance with errors and the maximum value of scaled prediction variance without errors.The second is the mean squared deviation from the mean of simulated maximum scaled prediction variance with errors.The last performance measure is the mean squared scaled prediction variance change with and without errors.In the simulations,1 000 random samples were performed following three factors with 20 experimental runs for central composite designs and 15 for Box-Behnken design.The independent variables are coded variables in these designs.Comparative results show that for the low level errors in variables,central composite face-centered design is optimal;otherwise,Box-Behnken design has a relatively better performance.展开更多
The Response Surface Methodology (RSM) has been applied to explore the thermal structure of the experimentally studied catalytic combustion of stabilized confined turbulent gaseous diffusion flames. The Pt/γAl2O3 and...The Response Surface Methodology (RSM) has been applied to explore the thermal structure of the experimentally studied catalytic combustion of stabilized confined turbulent gaseous diffusion flames. The Pt/γAl2O3 and Pd/γAl2O3 disc burners were situated in the combustion domain and the experiments were performed under both fuel-rich and fuel-lean conditions at a modified equivalence (fuel/air) ratio (ø) of 0.75 and 0.25 respectively. The thermal structure of these catalytic flames developed over the Pt and Pd disc burners were inspected via measuring the mean temperature profiles in the radial direction at different discrete axial locations along the flames. The RSM considers the effect of the two operating parameters explicitly (r), the radial distance from the center line of the flame, and (x), axial distance along the flame over the disc, on the measured temperature of the flames and finds the predicted maximum temperature and the corresponding process variables. Also the RSM has been employed to elucidate such effects in the three and two dimensions and displays the location of the predicted maximum temperature.展开更多
The modern aircraft Thermal Management System(TMS)faces significant challenges due to increasing thermal loads and limited heat dissipation pathways.To optimize TMS during the conceptual design stage,the development o...The modern aircraft Thermal Management System(TMS)faces significant challenges due to increasing thermal loads and limited heat dissipation pathways.To optimize TMS during the conceptual design stage,the development of a modeling and simulation tool is crucial.In this study,a TMS simulation model library was created using MATLAB/SIMULINK.To simplify the complexity of the Vapor Cycle System(VCS)model,a Response Surface Model(RSM)was constructed using the Monte Carlo method and validated through simulation experiments.Taking the F-22 fighter TMS as an example,a thermal dynamic simulation model was constructed to analyze the variation of thermal response parameters in key subsystems and elucidate their coupling relationships.Furthermore,the impact of total fuel flow and ram air flow on the TMS was investigated.The findings demonstrate the existence of an optimal total fuel flow that achieves a balance between maximizing fuel heat sink utilization and minimizing bleed air demand.The adaptive distribution of fuel and ram air flow was found to enhance aircraft thermal management performance.This study contributes to improving modeling efficiency and enhancing the understanding of the thermal dynamic characteristics of TMS,thereby facilitating further optimization in aircraft TMS design.展开更多
This article, in order to improve the assembly of the high-pressure spool, presents an assembly variation identification method achieved by response surface method （RSM）-based model updating using IV-optimal designs...This article, in order to improve the assembly of the high-pressure spool, presents an assembly variation identification method achieved by response surface method （RSM）-based model updating using IV-optimal designs. The method involves screening out non-relevant assembly parameters using IV-optimal designs and the preload of the joints is chosen as the input features and modal frequency is the only response feature. Emphasis is placed on the construction of response surface models including the interactions between the bolted joints by which the non-linear relationship between the assembly variation caused by the changes ofpreload and the output frequency variation is established. By achieving an optimal process of selected variables in the model, assembly variation can be identified. With a case study of the laboratory bolted disks as an example, the proposed method is verified and it gives enough accuracy in variation identification. It has been observed that the first-order response surface models considering the interactions between the bolted joints based on the IV-optimal criterion are adequate for assembly purposes.展开更多
This work deals with phosphate ions removal in aqueous solution by adsorption carried out using two clays, both in activated form. One, non-swelling clay, rich in kaolinite, is associated with illite and quartz. The o...This work deals with phosphate ions removal in aqueous solution by adsorption carried out using two clays, both in activated form. One, non-swelling clay, rich in kaolinite, is associated with illite and quartz. The other, swelling, richer in montmorillonite, is associated with kaolinite, illite and quartz. Seven factors including these two clays were taken into account in a series of experimental designs in order to model and optimize the acidic activation process favoring a better phosphate removal. In addition to the choice of clay nature, the study was also interested in the identification of the mineral acid, between hydrochloric acid and sulfuric acid, which would promote this acidic activation. Response Surface Methodology (RSM) was used for this purpose by sequentially applying Plackett and Burman Design and Full Factorial Design (FD) for screening. Then, a central composite design (CCD) was used for modeling the activation process. A mathematical surface model has been successfully established. Thus, the best acidic activation conditions were obtained by activating the montmorillonite clay with a 2N sulfuric acid solution, in an acid/clay mass ratio of 7.5 at 100°C for 16H. The phosphate removal maximum rate obtained was estimated at 89.32% ± 0.86%.展开更多
Multiple response surface methodology (MRSM) most often involves the analysis of small sample size datasets which have associated inherent statistical modeling problems. Firstly, classical model selection criteria in ...Multiple response surface methodology (MRSM) most often involves the analysis of small sample size datasets which have associated inherent statistical modeling problems. Firstly, classical model selection criteria in use are very inefficient with small sample size datasets. Secondly, classical model selection criteria have an acknowledged selection uncertainty problem. Finally, there is a credibility problem associated with modeling small sample sizes of the order of most MRSM datasets. This work focuses on determination of a solution to these identified problems. The small sample model selection uncertainty problem is analysed using sixteen model selection criteria and a typical two-input MRSM dataset. Selection of candidate models, for the responses in consideration, is done based on response surface conformity to expectation to deliberately avoid selection of models using the problematic classical model selection criteria. A set of permutations of combinations of response models with conforming response surfaces is determined. Each combination is optimised and results are obtained using overlaying of data matrices. The permutation of results is then averaged to obtain credible results. Thus, a transparent multiple model approach is used to obtain the solution which gives some credibility to the small sample size results of the typical MRSM dataset. The conclusion is that, for a two-input process MRSM problem, conformity of response surfaces can be effectively used to select candidate models and thus the use of the problematic model selection criteria is avoidable.展开更多
Because of the recent growth in ground-level ozone and increased emission of volatile organic compounds(VOCs),VOC emission control has become a major concern in China.In response,emission caps to control VOC have been...Because of the recent growth in ground-level ozone and increased emission of volatile organic compounds(VOCs),VOC emission control has become a major concern in China.In response,emission caps to control VOC have been stipulated in recent policies,but few of them were constrained by the co-control target of PM_(2.5)and ozone,and discussed the factor that influence the emission cap formulation.Herein,we proposed a framework for quantification of VOC emission caps constrained by targets for PM_(2.5)and ozone via a new response surface modeling(RSM)technique,achieving 50%computational cost savings of the quantification.In the Pearl River Delta(PRD)region,the VOC emission caps constrained by air quality targets varied greatly with the NOxemission reduction level.If control measures in the surrounding areas of the PRD region were not considered,there could be two feasible strategies for VOC emission caps to meet air quality targets(160μg/m^(3)for the maximum 8-hr-average 90th-percentile(MDA8-90%)ozone and 25μg/m^(3)for the annual average of PM_(2.5)):a moderate VOC emission cap with<20%NOxemission reductions or a notable VOC emission cap with>60%NOxemission reductions.If the ozone concentration target were reduced to 155μg/m^(3),deep NOxemission reductions is the only feasible ozone control measure in PRD.Optimization of seasonal VOC emission caps based on the Monte Carlo simulation could allow us to gain higher ozone benefits or greater VOC emission reductions.If VOC emissions were further reduced in autumn,MDA8-90%ozone could be lowered by 0.3-1.5μg/m^(3),equaling the ozone benefits of 10%VOC emission reduction measures.The method for VOC emission cap quantification and optimization proposed in this study could provide scientific guidance for coordinated control of regional PM_(2.5)and O_(3)pollution in China.展开更多
Kinetin is an important growth hormone used for in vitro propagation, but its dynamic and temporal effects on Dioscoreaalata have not been thoroughly evaluated. In this study, surface response models were developed to...Kinetin is an important growth hormone used for in vitro propagation, but its dynamic and temporal effects on Dioscoreaalata have not been thoroughly evaluated. In this study, surface response models were developed to better elucidate the effects ofkinetin on D. alata propagated in vitro. Nodal segments were obtained from Akaaba, an important D. alata cultivar in Ghana, andpropagated in vitro under five kinetin rates （0, 2.5, 5, 7.5 and 10 μM）. The models were developed using segmented multipleregression with time and kinetin as the predictors. The effects on plant height, the number of leaves, shoots and roots were assessedwith three-dimensional figures for better observation of temporal trends. The model fit was very good with normalized root meansquared error （NRMSE） = 0.1, R-squared = 0.83 and adjusted R-squared = 0.82, averaged across the different growth parameters.Different kinetin levels elicited the maximum shoot, leaf and root formation, as well as the growth rates over time. Moderate kinetinlevels （2-4 μM） provided better growth at early culturing period. Higher kinetin levels （5-10 μM） suppressed the growth of theplantlets at early stages, but the plantlets recovered from the stress and resumed normal growth thereafter. After 4-5 weeks, thegrowth rates of the moderate kinetin levels （2-4 μM） declined much faster and were lower compared to the higher kinetin levels,except plant height and the number of roots which were still higher at the moderate kinetin level even after eight weeks of culturing.Thus, kinetin requirements vary depending on the growth parameters of interest.展开更多
Response surface methodology（RSM） is introduced into corrosion research as a tool to assess the effects of environmental factors and their interactions on corrosion behavior and establish a model for corrosion predi...Response surface methodology（RSM） is introduced into corrosion research as a tool to assess the effects of environmental factors and their interactions on corrosion behavior and establish a model for corrosion prediction in complex coupled environment（CCE）. In this study, a typical CCE, that is, the corrosion environment of pipelines in gas field is taken as an example. The effects of environmental factors such as chloride concentration, pH value and pressure as well as their interactions on critical pitting temperature（CPT） were evaluated, and a quadratic polynomial model was developed for corrosion prediction by RSM. The results showed that the model was excellent in corrosion prediction with R2= 0.9949. CPT was mostly affected by single environmental factor rather than interaction, and among the whole factors, chloride concentration was the most influential factor of CPT.展开更多
In order to shorten the design period, the paper describes a new optimization strategy for computationally expensive design optimization of turbomachinery, combined with design of experiment (DOE), response surface mo...In order to shorten the design period, the paper describes a new optimization strategy for computationally expensive design optimization of turbomachinery, combined with design of experiment (DOE), response surface models (RSM), genetic algorithm (GA) and a 3-D Navier-Stokes solver(Numeca Fine). Data points for response evaluations were selected by improved distributed hypercube sampling (IHS) and the 3-D Navier-Stokes analysis was carried out at these sample points. The quadratic response surface model was used to approximate the relationships between the design variables and flow parameters. To maximize the adiabatic efficiency, the genetic algorithm was applied to the response surface model to perform global optimization to achieve the optimum design of NASA Stage 35. An optimum leading edge line was found, which produced a new 3-D rotor blade combined with sweep and lean, and a new stator one with skew. It is concluded that the proposed strategy can provide a reliable method for design optimization of turbomachinery blades at reasonable computing cost.展开更多
Due to the size effects of rockfill materials, the settlement difference between numerical simulation and in situ monitoring of rockfill dams is a topic of general concern.The constitutive model parameters obtained fr...Due to the size effects of rockfill materials, the settlement difference between numerical simulation and in situ monitoring of rockfill dams is a topic of general concern.The constitutive model parameters obtained from laboratory triaxial tests often underestimate the deformation of high rockfill dams.Therefore, constitutive model parameters obtained by back analysis were used to calculate and predict the long-term deformation of rockfill dams.Instead of using artificial neural networks (ANNs), the response surface method (RSM) was employed to replace the finite element simulation used in the optimization iteration.Only 27 training samples were required for RSM, improving computational efficiency compared with ANN, which required 300 training samples.RSM can be used to describe the relationship between the constitutive model parameters and dam settlements.The inversion results of the Shuibuya concrete face rockfill dam (CFRD) show that the calculated settlements agree with the measured data, indicating the accuracy and efficiency of RSM.展开更多
基金supported by the National Natural Science Foundation of China(NNSFC)(Grant no.12272148).
文摘A response surface method was utilized for the finite element model updating of a cable-stayed bridge in this paper to establish a baseline finite element model(FEM)that accurately reflects the characteristics of the actual bridge structure.Firstly,an initial FEM was established by the large-scale finite element software ANSYS,and the modal analysis was carried out on the dynamic response measured by the actual bridge structural health monitoring system.The initial error was obtained by comparing the dynamic characteristics of the measured data with those of the initial finite element model.Then,the second-order complete polynomial was selected to construct the response surface model;the corrected parameters were chosen using the sensitivity method.The response surface model(RSM)was fitted under the test cases designed using the central composite design method.After constructing the objective function,the RSMwas optimized and iterated by the sequential quadratic programmingmethod to obtain the corrected FEM.Finally,the dynamic characteristics of the modified FEM were compared with those of the actual bridge to get the final error.The results show that the modified FEM simulates the dynamic characteristics of the actual cable-stayed bridges more accurately.
基金supported by the National Basic Research Program of China (No. 2006CB705401)the National Natural Science Foundation of China (No.51075270)the Natural Science Foundation of the Jiangsu Higher Education Institutions of China (No.10KJD460003)
文摘A modified cellular automata （CA） model of dynamic recrystallization （DRX） and a flow stress-based nucleation parameter identification method have been developed. In the method, the modified CA model, which takes the role of deformation degree on nucleation behavior into consideration, is coupled with an adaptive response surface model （ARSM） to search for the optimum nucleation parameter. The DRX behavior of an oxygen free high conductivity （OFHC） copper with different initial grain sizes has been taken as an example to validate the model. Good agreement is found between the simulated and the experimental results, which demonstrates that the new method can effectively improve the simulation accuracy.
文摘The application of leaching process to extracting Mn from a low-grade manganese ore was investigated using a software based design of experiments. Four main parameters, i.e. sulfuric acid concentration, oxalic acid concentration, time and temperature were considered in a central composite response surface design. The recoveries of Mn and Fe were selected as response of design. The optimum conditions under which the Mn and Fe recoveries were the highest and the time and temperature were the lowest were determined using statistical analysis and analysis of variance （ANOVA）. The results showed that Mn and Fe recoveries were 93.44% and 15.72% under the optimum condition, respectively. Also, sulfuric acid concentration was the most effective parameter affecting the process. The amounts of sulfuric and oxalic acid were obtained to be 7% and 42.50 g/L in optimum condition and the best time and temperature were 65 min and 63 ℃.
文摘This investigation was undertaken to predict the mass gain （MG） of cobalt electroless deposition （ED） on ceramic SiC particles.Response surface methodology （RSM） based on a full factorial design with three ED parameters and 30 runs was used to conduct the experiments and to establish a mathematical model by means of Design-Expert software.Three ED parameters considered were pH,bath temperature and ceramic particle morphology.Analysis of variance was applied to validate the predicted model.The results of confirmation analysis by scanning electron microscopy （SEM） show that the developed models are reasonably accurate.The pH is the most effective parameter for the MG.Also,the highest mass gain is obtained for the lowest pH,highest bath temperatures and heat-treated SiC particles.In addition,the developed model shows that the optimal parameters to get a maximum value of mass gain are pH,bath temperature and ceramic particle state of 8,70 ℃ and heat treatment,respectively.
文摘Performance of a hybrid reactor comprising of trickling filter （TF） and aeration tank （AT） unit was studied for biological treatment of wastewater containing mixture of phenol and m-cresol, using mixed microbial culture. The reactor was operated with hydraulic loading rates （HLR） and phenolics loading rates （PLR） between 0.222-1.078 m3/（m2-day） and 0.900-3.456 kg/（m3.day）, respectively. The efficiency of substrate removal varied between 71%-100% for the range of HLR and PLR studied. The fixed film unit showed better substrate removal efficiency than the aeration tank and was more resistant to substrate inhibition. The kinetic parameters related to both units of the reactor were evaluated and their variation with HLR and PLR were monitored. It revealed the presence of substrate inhibition at high PLR both in TF and AT unit. The biofilm model established the substrate concentration profile within the film by solving differential equation of substrate mass transfer using boundary problem solver tool ＇bvp4c＇ of MATLAB 7. 1 software. Response surface methodology was used to design and optimize the biodegradation process using Design Expert 8 software, where phenol and m-cresol concentrations, residence time were chosen as input variables and percentage of removal was the response. The design of experiment showed that a quadratic model could be fitted best for the present experimental study. Significant interaction of the residence time with the substrate concentrations was observed. The optimized condition for operating the reactor as predicted by the model was 230 mg/L of phenol, 190 mg/L of m-cresol with residence time of 24.82 hr to achieve 99.92% substrate removal.
基金supported by the National Iranian Copper Industry Co.
文摘This study discussed the application of response surface methodology(RSM)and central composite rotatable design(CCRD)for modeling and optimization of the influence of some operating variables on the performance of a lab scale thickener for dewatering of tailing in the flotation circuit.Four thickener operating variables,namely feed flowrate,solid percent,flocculant dosage and feedwell height were changed during the tests based on CCRD.The ranges of values of the thickener variables used in the design were a feed flowrate of 9–21 L/min,solid percent of 8%–20%,flocculant dosage of 1.25–4.25 g/t and feedwell height of 16–26 cm.A total of 30 thickening tests were conducted using lab scale thickener on flotation tailing obtained from the Sarcheshmeh copper mine,Iran.The underflow solid percent and bed height were expressed as functions of four operating parameters of thickener.Predicted values were found to be in good agreement with experimental values(R2values of 0.992 and 0.997 for underflow solid percent and bed height,respectively).This study has shown that the RSM and CCRD could effciently be applied for the modeling of thickener for dewatering of flotation tailing.
基金Financial support for this work is provided by the Shunde Environment ProtectionTransportation and Urban Administration Bureau(no.0851-1361FS02CL51)+5 种基金the Guangdong Provincial Science and Technology Plan Projects(no.2014A050503019)Guangzhou Environmental Protection Bureau(no.x2hjB2150020)supported by the funding of State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complexthe project of Atmospheric Haze Collaboration Control Technology Design(no.XDB05030400)from Chinese Academy of Sciencesthe Special Program for Applied Research on Super Computation of the NSFC-Guangdong Joint Fund(U1501501)(the second phase)the Guangdong Provincial Engineering and Technology Research Center for Environmental Risk Prevention and Emergency Disposal(no.b2152120)
文摘To develop a sound ozone（O_3） pollution control strategy,it is important to well understand and characterize the source contribution due to the complex chemical and physical formation processes of O_3.Using the ＂Shunde＂ city as a pilot summer case study,we apply an innovative response surface modeling（RSM） methodology based on the Community Multi-Scale Air Quality（CMAQ） modeling simulations to identify the O_3 regime and provide dynamic analysis of the precursor contributions to effectively assess the O_3 impacts of volatile organic compound（VOC） control strategy.Our results show that Shunde is a typical VOC-limited urban O_3 polluted city.The ＂Jiangmen＂ city,as the main upper wind area during July 2014,its VOCs and nitrogen oxides（NO_x） emissions make up the largest contribution（9.06%）.On the contrary,the contribution from local（Shunde） emission is lowest（6.35%） among the seven neighbor regions.The local VOCs industrial source emission has the largest contribution comparing to other precursor emission sectors in Shunde.The results of dynamic source contribution analysis further show that the local NO_x control could slightly increase the ground O_3 under low（10.00%） and medium（40.00%）reduction ratios,while it could start to turn positive to decrease ground O_3 under the high NO_x abatement ratio（75.00%）.The real-time assessment of O_3 impacts from VOCs control strategies in Pearl River Delta（PRD） shows that the joint regional VOCs emission control policy will effectively reduce the ground O_3 concentration in Shunde.
文摘The copper extraction in shaking bioreactors was modeled and optimized using response surface methodology（RSM）. Influential parameters in the mesophilic bioleaching process of a low-grade copper ore including p H value, pulp density, and initial concentration of ferrous ions were comprehensively studied. The effect of leaching time on the response（copper extraction） at the 1st, 4th, 9th, 14 th and 22 nd days of treatment was modeled and examined. The central composite design methodology（CCD） was used as the design matrix to predict the optimal level of these parameters. Then, the model equation at the 22 nd day was optimized using the quadratic programming（QP） to maximize the total copper extraction within the studied experimental range. Under the optimal condition（initial p H value of 2.0, pulp density of 1.59%, and initial concentration of ferrous ions of 0 g/L）, the total copper extraction predicted by the model is 85.98% which is significantly close to that obtained from the experiment（84.57%）. The results show that RSM could be useful to predict the maximum copper extraction from a low-grade ore and investigate the effects of variables on the final response. Besides, a couple of statistically significant interactions are derived between p H value and pulp density as well as p H value and initial ferrous ion concentration which are precisely interpreted. However, there is no statistically significant interaction between the initial ferrous ion concentration and the pulp density. Additionally, the response at optimal levels of p H value and pulp density is found to be independent on the level of initial ferrous concentration.
基金supported by the Department of Scientific and Industrial Research(DSIR),India
文摘The present paper discusses the modeling of tool geometry effects on the friction stir aluminum welds using response surface methodology. The friction stir welding tools were designed with different shoulder and tool probe geometries based on a design matrix. The matrix for the tool designing was made for three types of tools, based on three types of probes, with three levels each for defining the shoulder surface type and probe profile geometries. Then, the effects of tool shoulder and probe geometries on friction stirred aluminum welds were experimentally investigated with respect to weld strength, weld cross section area, grain size of weld and grain size of thermo-mechanically affected zone. These effects were modeled using multiple and response surface regression analysis. The response surface regression modeling were found to be appropriate for defining the friction stir weldment characteristics.
基金Supported by National Natural Science Foundation of China (No.70871087 and No.70931004)
文摘This paper investigates the scaled prediction variances in the errors-in-variables model and compares the performance with those in classic model of response surface designs for three factors.The ordinary least squares estimators of regression coefficients are derived from a second-order response surface model with errors in variables.Three performance criteria are proposed.The first is the difference between the empirical mean of maximum value of scaled prediction variance with errors and the maximum value of scaled prediction variance without errors.The second is the mean squared deviation from the mean of simulated maximum scaled prediction variance with errors.The last performance measure is the mean squared scaled prediction variance change with and without errors.In the simulations,1 000 random samples were performed following three factors with 20 experimental runs for central composite designs and 15 for Box-Behnken design.The independent variables are coded variables in these designs.Comparative results show that for the low level errors in variables,central composite face-centered design is optimal;otherwise,Box-Behnken design has a relatively better performance.
文摘The Response Surface Methodology (RSM) has been applied to explore the thermal structure of the experimentally studied catalytic combustion of stabilized confined turbulent gaseous diffusion flames. The Pt/γAl2O3 and Pd/γAl2O3 disc burners were situated in the combustion domain and the experiments were performed under both fuel-rich and fuel-lean conditions at a modified equivalence (fuel/air) ratio (ø) of 0.75 and 0.25 respectively. The thermal structure of these catalytic flames developed over the Pt and Pd disc burners were inspected via measuring the mean temperature profiles in the radial direction at different discrete axial locations along the flames. The RSM considers the effect of the two operating parameters explicitly (r), the radial distance from the center line of the flame, and (x), axial distance along the flame over the disc, on the measured temperature of the flames and finds the predicted maximum temperature and the corresponding process variables. Also the RSM has been employed to elucidate such effects in the three and two dimensions and displays the location of the predicted maximum temperature.
文摘The modern aircraft Thermal Management System(TMS)faces significant challenges due to increasing thermal loads and limited heat dissipation pathways.To optimize TMS during the conceptual design stage,the development of a modeling and simulation tool is crucial.In this study,a TMS simulation model library was created using MATLAB/SIMULINK.To simplify the complexity of the Vapor Cycle System(VCS)model,a Response Surface Model(RSM)was constructed using the Monte Carlo method and validated through simulation experiments.Taking the F-22 fighter TMS as an example,a thermal dynamic simulation model was constructed to analyze the variation of thermal response parameters in key subsystems and elucidate their coupling relationships.Furthermore,the impact of total fuel flow and ram air flow on the TMS was investigated.The findings demonstrate the existence of an optimal total fuel flow that achieves a balance between maximizing fuel heat sink utilization and minimizing bleed air demand.The adaptive distribution of fuel and ram air flow was found to enhance aircraft thermal management performance.This study contributes to improving modeling efficiency and enhancing the understanding of the thermal dynamic characteristics of TMS,thereby facilitating further optimization in aircraft TMS design.
文摘This article, in order to improve the assembly of the high-pressure spool, presents an assembly variation identification method achieved by response surface method （RSM）-based model updating using IV-optimal designs. The method involves screening out non-relevant assembly parameters using IV-optimal designs and the preload of the joints is chosen as the input features and modal frequency is the only response feature. Emphasis is placed on the construction of response surface models including the interactions between the bolted joints by which the non-linear relationship between the assembly variation caused by the changes ofpreload and the output frequency variation is established. By achieving an optimal process of selected variables in the model, assembly variation can be identified. With a case study of the laboratory bolted disks as an example, the proposed method is verified and it gives enough accuracy in variation identification. It has been observed that the first-order response surface models considering the interactions between the bolted joints based on the IV-optimal criterion are adequate for assembly purposes.
文摘This work deals with phosphate ions removal in aqueous solution by adsorption carried out using two clays, both in activated form. One, non-swelling clay, rich in kaolinite, is associated with illite and quartz. The other, swelling, richer in montmorillonite, is associated with kaolinite, illite and quartz. Seven factors including these two clays were taken into account in a series of experimental designs in order to model and optimize the acidic activation process favoring a better phosphate removal. In addition to the choice of clay nature, the study was also interested in the identification of the mineral acid, between hydrochloric acid and sulfuric acid, which would promote this acidic activation. Response Surface Methodology (RSM) was used for this purpose by sequentially applying Plackett and Burman Design and Full Factorial Design (FD) for screening. Then, a central composite design (CCD) was used for modeling the activation process. A mathematical surface model has been successfully established. Thus, the best acidic activation conditions were obtained by activating the montmorillonite clay with a 2N sulfuric acid solution, in an acid/clay mass ratio of 7.5 at 100°C for 16H. The phosphate removal maximum rate obtained was estimated at 89.32% ± 0.86%.
文摘Multiple response surface methodology (MRSM) most often involves the analysis of small sample size datasets which have associated inherent statistical modeling problems. Firstly, classical model selection criteria in use are very inefficient with small sample size datasets. Secondly, classical model selection criteria have an acknowledged selection uncertainty problem. Finally, there is a credibility problem associated with modeling small sample sizes of the order of most MRSM datasets. This work focuses on determination of a solution to these identified problems. The small sample model selection uncertainty problem is analysed using sixteen model selection criteria and a typical two-input MRSM dataset. Selection of candidate models, for the responses in consideration, is done based on response surface conformity to expectation to deliberately avoid selection of models using the problematic classical model selection criteria. A set of permutations of combinations of response models with conforming response surfaces is determined. Each combination is optimised and results are obtained using overlaying of data matrices. The permutation of results is then averaged to obtain credible results. Thus, a transparent multiple model approach is used to obtain the solution which gives some credibility to the small sample size results of the typical MRSM dataset. The conclusion is that, for a two-input process MRSM problem, conformity of response surfaces can be effectively used to select candidate models and thus the use of the problematic model selection criteria is avoidable.
基金supported by the National Key Research and Development Program of China(No.2018YFC0213905)the National Natural Science Foundation of China(No.41805068)。
文摘Because of the recent growth in ground-level ozone and increased emission of volatile organic compounds(VOCs),VOC emission control has become a major concern in China.In response,emission caps to control VOC have been stipulated in recent policies,but few of them were constrained by the co-control target of PM_(2.5)and ozone,and discussed the factor that influence the emission cap formulation.Herein,we proposed a framework for quantification of VOC emission caps constrained by targets for PM_(2.5)and ozone via a new response surface modeling(RSM)technique,achieving 50%computational cost savings of the quantification.In the Pearl River Delta(PRD)region,the VOC emission caps constrained by air quality targets varied greatly with the NOxemission reduction level.If control measures in the surrounding areas of the PRD region were not considered,there could be two feasible strategies for VOC emission caps to meet air quality targets(160μg/m^(3)for the maximum 8-hr-average 90th-percentile(MDA8-90%)ozone and 25μg/m^(3)for the annual average of PM_(2.5)):a moderate VOC emission cap with<20%NOxemission reductions or a notable VOC emission cap with>60%NOxemission reductions.If the ozone concentration target were reduced to 155μg/m^(3),deep NOxemission reductions is the only feasible ozone control measure in PRD.Optimization of seasonal VOC emission caps based on the Monte Carlo simulation could allow us to gain higher ozone benefits or greater VOC emission reductions.If VOC emissions were further reduced in autumn,MDA8-90%ozone could be lowered by 0.3-1.5μg/m^(3),equaling the ozone benefits of 10%VOC emission reduction measures.The method for VOC emission cap quantification and optimization proposed in this study could provide scientific guidance for coordinated control of regional PM_(2.5)and O_(3)pollution in China.
文摘Kinetin is an important growth hormone used for in vitro propagation, but its dynamic and temporal effects on Dioscoreaalata have not been thoroughly evaluated. In this study, surface response models were developed to better elucidate the effects ofkinetin on D. alata propagated in vitro. Nodal segments were obtained from Akaaba, an important D. alata cultivar in Ghana, andpropagated in vitro under five kinetin rates （0, 2.5, 5, 7.5 and 10 μM）. The models were developed using segmented multipleregression with time and kinetin as the predictors. The effects on plant height, the number of leaves, shoots and roots were assessedwith three-dimensional figures for better observation of temporal trends. The model fit was very good with normalized root meansquared error （NRMSE） = 0.1, R-squared = 0.83 and adjusted R-squared = 0.82, averaged across the different growth parameters.Different kinetin levels elicited the maximum shoot, leaf and root formation, as well as the growth rates over time. Moderate kinetinlevels （2-4 μM） provided better growth at early culturing period. Higher kinetin levels （5-10 μM） suppressed the growth of theplantlets at early stages, but the plantlets recovered from the stress and resumed normal growth thereafter. After 4-5 weeks, thegrowth rates of the moderate kinetin levels （2-4 μM） declined much faster and were lower compared to the higher kinetin levels,except plant height and the number of roots which were still higher at the moderate kinetin level even after eight weeks of culturing.Thus, kinetin requirements vary depending on the growth parameters of interest.
基金financially supported by the Hundred Talents Program of Chinese Academy of Sciencesthe National Natural Science Foundation of China (No. U1460202)the Key Laboratory of Superlight Material and Surface Technology (Harbin Engineering University), Ministry of Education
文摘Response surface methodology（RSM） is introduced into corrosion research as a tool to assess the effects of environmental factors and their interactions on corrosion behavior and establish a model for corrosion prediction in complex coupled environment（CCE）. In this study, a typical CCE, that is, the corrosion environment of pipelines in gas field is taken as an example. The effects of environmental factors such as chloride concentration, pH value and pressure as well as their interactions on critical pitting temperature（CPT） were evaluated, and a quadratic polynomial model was developed for corrosion prediction by RSM. The results showed that the model was excellent in corrosion prediction with R2= 0.9949. CPT was mostly affected by single environmental factor rather than interaction, and among the whole factors, chloride concentration was the most influential factor of CPT.
文摘In order to shorten the design period, the paper describes a new optimization strategy for computationally expensive design optimization of turbomachinery, combined with design of experiment (DOE), response surface models (RSM), genetic algorithm (GA) and a 3-D Navier-Stokes solver(Numeca Fine). Data points for response evaluations were selected by improved distributed hypercube sampling (IHS) and the 3-D Navier-Stokes analysis was carried out at these sample points. The quadratic response surface model was used to approximate the relationships between the design variables and flow parameters. To maximize the adiabatic efficiency, the genetic algorithm was applied to the response surface model to perform global optimization to achieve the optimum design of NASA Stage 35. An optimum leading edge line was found, which produced a new 3-D rotor blade combined with sweep and lean, and a new stator one with skew. It is concluded that the proposed strategy can provide a reliable method for design optimization of turbomachinery blades at reasonable computing cost.
基金supported by the National Natural Science Foundation of China(Grant No.51579193)the Science and Technology Planning Project of Guizhou Province(Grant No.[2016]1154)
文摘Due to the size effects of rockfill materials, the settlement difference between numerical simulation and in situ monitoring of rockfill dams is a topic of general concern.The constitutive model parameters obtained from laboratory triaxial tests often underestimate the deformation of high rockfill dams.Therefore, constitutive model parameters obtained by back analysis were used to calculate and predict the long-term deformation of rockfill dams.Instead of using artificial neural networks (ANNs), the response surface method (RSM) was employed to replace the finite element simulation used in the optimization iteration.Only 27 training samples were required for RSM, improving computational efficiency compared with ANN, which required 300 training samples.RSM can be used to describe the relationship between the constitutive model parameters and dam settlements.The inversion results of the Shuibuya concrete face rockfill dam (CFRD) show that the calculated settlements agree with the measured data, indicating the accuracy and efficiency of RSM.
