Plackett-Burman和Central Composite Design试验设计法优化石榴皮中熊果酸的SFE-CO_2萃取工艺

目的:探讨应用SFE-CO2萃取石榴皮中熊果酸的最佳工艺。方法:以熊果酸得率为考察指标,通过Plackett-Burman(PB)试验设计筛选影响熊果酸得率的显著性因素,最陡爬坡试验逼近熊果酸得率最大区域,Central Composite Design(CCD)试验设计对显著性因素进行响应面优化得到影响熊果酸得率的二阶数学模型,进而得出最佳工艺条件。结果:SFE-CO2萃取石榴皮中熊果酸的最佳工艺条件为:萃取温度46.29℃,萃取时间91.6 min,萃取压力34.49 MPa,在此条件下,验证试验测得熊果酸得率为12.508 mg/g,与模型预测值12.645 mg/g接近。结论:将PB试验和CCD试验设计联合应用于优化石榴皮中熊果酸SFE-CO2萃取工艺,筛选结果具有统计学意义,工艺操作具有可行性。

Analysis of Heat Transfer Performance of Oscillating Heat Pipes Based on a Central Composite Design

Oscillating heat pipes (OHPs) are very promising cooling devices. Their heat transfer performance is af- fected by many factors, and the form of the relationship between the performance and the factors is complex and non-linear. In this paper, the effects of charging ratio, inclination angle, and heat input and their interaction effects on heat transfer performance of a looped copper-water OHP are analyzed. First, suppose that the relationship between the response and the variables approximates a second-order model. And use the central composite design to arrange the ex- periment. Then, the method of least squares is used to estimate the parameters in the second-order model. Finally, multi- variate variance analysis is used to analyze the model. The results show that the assumption is right, that is to say, the re- lationship is well modeled by a second-order function. Among the three main effect variables, the effect of inclination angle is the most significant, but their interaction effects are not significant. In the range of the considered factors, both the optimum charging ratio and the optimum inclination angle increase as the heating water flow rate increases.

Towards data-efficient mechanical design of bicontinuous composites usinggenerative AI

The distribution of material phases is crucial to determine the composite’s mechanical property.While the full structure-mechanics relationship of highly ordered material distributions can be studied with finite number of cases,this relationship is difficult to be revealed for complex irregular distributions,preventing design of such material structures to meet certain mechanical requirements.The noticeable developments of artificial intelligence(AI)algorithms in material design enables to detect the hidden structure-mechanics correlations which is essential for designing composite of complex structures.It is intriguing how these tools can assist composite design.Here,we focus on the rapid generation of bicontinuous composite structures together with the stress distribution in loading.We find that generative AI,enabled through fine-tuned Low Rank Adaptation models,can be trained with a few inputs to generate both synthetic composite structures and the corresponding von Mises stress distribution.The results show that this technique is convenient in generating massive composites designs with useful mechanical information that dictate stiffness,fracture and robustness of the material with one model,and such has to be done by several different experimental or simulation tests.This research offers valuable insights for the improvement of composite design with the goal of expanding the design space and automatic screening of composite designs for improved mechanical functions.

Application of response surface methodology and central composite rotatable design for modeling the influence of some operating variables of the lab scale thickener performance

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.

Modeling and Optimization of Catalytic Dehydration of Ethanol to Ethylene Using Central Composite Design

The central composite design in the modeling and optimization of catalytic dehydration of ethanol to ethylene was performed to improve the ethylene yield.A total of 20 experiments at random were conducted to investigate the effect of reaction temperature,Si/Al ratios of H-ZSM-5 catalyst and liquid hourly space velocity(LHSV) on the ethylene yield.The results show that the relationship between ethylene yield and the three significant independent variables can be approximated by a nonlinear polynomial model,with R-squared of 99.9%and adjusted R-squared of 99.8%.The maximal response for ethylene yield is 93.4%under the optimal condition of 328 ℃,Si/Al ratio 85,and LHSV 3.8 h-1.

Optimization of Extraction Process of Clerodendrum philippinum Schauer var. simplex Mlodenke Total Flavonoids(CPTF) by Central Composite Design-Response Surface Methodology

[Objectives] The research aimed to optimize extraction process of Clerodendrum philippinum Schauer var. simplex Mlodenke total flavonoids( CPTF),and provide reference for its development and utilization. [Methods] Based on single-factor test,ethanol concentration,extraction temperature and extraction time were taken as independent variables,and total flavonoids yield was taken as dependent variable. The test was conducted according to central composite design principle. Multivariate linear regression and binomial equation fitting of the result were conducted,and extraction process of CPTF was optimized by using response surface methodology. [Results]The optimal extraction process of CPTF was as below: ethanol concentration 54. 76%,extraction temperature 83. 92℃,extraction time 102. 64 min,solid-liquid ratio 1:20,extraction for twice. [Conclusions] The extraction process of CPTF by central composite design-response surface methodology was simple and feasible,with reliable prediction result,which was suitable for industrial production.

Composite armor philosophy(CAP):Holistic design methodology of multi-layered composite protection systems for armored vehicles

A philosophy for the design of novel,lightweight,multi-layered armor,referred to as Composite Armor Philosophy(CAP),which can adapt to the passive protection of light-,medium-,and heavy-armored vehicles,is presented in this study.CAP can serve as a guiding principle to assist designers in comprehending the distinct roles fulfilled by each component.The CAP proposal comprises four functional layers,organized in a suggested hierarchy of materials.Particularly notable is the inclusion of a ceramic-composite principle,representing an advanced and innovative solution in the field of armor design.This paper showcases real-world defense industry applications,offering case studies that demonstrate the effectiveness of this advanced approach.CAP represents a significant milestone in the history of passive protection,marking an evolutionary leap in the field.This philosophical approach provides designers with a powerful toolset with which to enhance the protection capabilities of military vehicles,making them more resilient and better equipped to meet the challenges of modern warfare.

A Multiscale Reliability-Based Design Optimization Method for Carbon-Fiber-Reinforced Composite Drive Shafts

Carbon fiber composites,characterized by their high specific strength and low weight,are becoming increasingly crucial in automotive lightweighting.However,current research primarily emphasizes layer count and orientation,often neglecting the potential of microstructural design,constraints in the layup process,and performance reliability.This study,therefore,introduces a multiscale reliability-based design optimization method for carbon fiber-reinforced plastic(CFRP)drive shafts.Initially,parametric modeling of the microscale cell was performed,and its elastic performance parameters were predicted using two homogenization methods,examining the impact of fluctuations in microscale cell parameters on composite material performance.A finite element model of the CFRP drive shaft was then constructed,achieving parameter transfer between microscale and macroscale through Python programming.This enabled an investigation into the influence of both micro and macro design parameters on the CFRP drive shaft’s performance.The Multi-Objective Particle Swarm Optimization(MOPSO)algorithm was enhanced for particle generation and updating strategies,facilitating the resolution of multi-objective reliability optimization problems,including composite material layup process constraints.Case studies demonstrated that this approach leads to over 30%weight reduction in CFRP drive shafts compared to metallic counterparts while satisfying reliability requirements and offering insights for the lightweight design of other vehicle components.

Calibration of Discrete Element Heat Transfer Parameters by Central Composite Design

The efficiency and precision of parameter calibration in discrete element method （DEM） are not satisfactory, and parameter calibration for granular heat transfer is rarely involved. Accordingly, parameter calibration for granular heat transfer with the DEM is studied. The heat transfer in granular assemblies is simulated with DEM, and the effective thermal conductivity （ETC） of these granular assemblies is measured with the transient method in simulations. The measurement testbed is designed to test the ETC of the granular assemblies under normal pressure and a vacuum based on the steady method. Central composite design （CCD） is used to simulate the impact of the DEM parameters on the ETC of granular assemblies, and the heat transfer parameters are calibrated and compared with experimental data. The results show that, within the scope of the considered parameters, the ETC of the granular assemblies increases with an increasing particle thermal conductivity and decreases with an increasing particle shear modulus and particle diameter. The particle thermal conductivity has the greatest impact on the ETC of granular assemblies followed by the particle shear modulus and then the particle diameter. The calibration results show good agreement with the experimental results. The error is less than 4%, which is within a reasonable range for the scope of the CCD parameters. The proposed research provides high efficiency and high accuracy parameter calibration for granular heat transfer in DEM.

Optimization of Extraction Process of Total Flavonoids from Akebia trifoliata (Thunb.) Koidz. by Central Composite Design-Response Surface Methodology

[Objectives]To optimize extraction process of total flavonoids from Akebia trifoliata( Thunb.) Koidz.,so as to provide references for development and use of Akebia trifoliata( Thunb.) Koidz. [Methods]The extraction rate of total flavonoids of Akebia trifoliata( Thunb.)Koidz. was taken as observation indicator. On the basis of single factor experiment,central composite design( CCD) was used to evaluate the effects of the extraction temperature,extraction time,and ethanol concentration on the extraction process. Multiple linear regression and binomial fitting were used,and response surface methodology( RSM) was used to select the optimum extraction process. [Results] The optimum extraction process conditions for total flavonoids of Akebia trifoliata( Thunb.) Koidz. was extraction temperature: 83. 92 ℃; extraction time:96. 47 min; ethanol concentration: 63. 92%; extraction times: two times; solid to liquid ratio: 1 ∶ 20; extraction rate of total flavonoids:4. 55%. [Conclusions] The central composite design-response surface methodology( CCD-RSM) is simple,convenient,and feasible for extraction of total flavonoids from Akebia trifoliata( Thunb.) Koidz.,and the prediction results are reliable.

Extraction Process Optimization of Total Flavonoids from Mallotus apelta Stems by Central Composite Design/Response Surface Method

[Objectives] To optimize the extraction process of total flavonoids in stems of Mallotus apelta. [Methods]On the basis of singlefactor test,with volume fraction of ethanol,extraction time and ratio of solvent as independent variables,the content of total flavonoids as dependent variables,the completely secondary response surface regression fitting was conducted on the independent and dependent variables,and the Response Surface Method was used to optimize the optimum extraction process of total flavonoids in Mallotus apelta stems and predict the optimum process. [Results] The optimum extraction process of total flavonoids in Mallotus apelta was determined as follows: ethanol concentration of 71. 5%; extraction time of 154. 6 min; solid-liquid ratio of 1∶19. 2; total flavonoids content of 7. 060 mg/g; fitted binomial squared correlation coefficient R^2= 0. 8751.[Conclusions]Composite Design/Response Surface Method could be used in the extraction process optimization of total flavonoids in Mallotus apelta stems,the mathematical model established had high prediction accuracy,the method was simple and operability was good.

Modeling of biodiesel production: Performance comparison of Box–Behnken, face central composite and full factorial design

The performances of the response surface methodology(RSM)in connection with the Box–Behnken,face central composite or full factorial design(BBD,FCCD or FFD,respectively)were compared for the use in modeling of the NaOH-catalyzed sunflower oil ethanolysis.The influence of temperature,catalyst loading,and ethanol-to-oil molar ratio(EOMR)on fatty acid ethyl esters(FAEE)content was evaluated.All three multivariate strategies were efficient in the statistical modeling and optimization of the influential process variables but BBD and FCCD realization involved less number of experiments,generating smaller costs,requiring less work and consuming shorter time than the corresponding FFD.All three designs resulted in the same optimal catalyst loading(1.25%of oil)and EOMR(12:1).The reduced two-factorinteraction(2 FI)models based on the BBD and FCCD defined a range of optimal reaction temperature(25℃–75℃)and 25℃,respectively while the same model based on the 33 FFD appointed 75℃.The predicted FAEE content of about 97%–98.0%was close to the experimentally obtained FAEE content of about 97.0%–97.6%under the optimal reaction conditions.Therefore,the simpler BBD or FCCD might successfully be applied for statistical modeling of biodiesel production processes instead of the more extensive,more laborious and more expensive FFD.

Optimization of extraction technology of safflower polysaccharide based on central composite design-response surface methodology

Objective:To explore the best extraction technology of safflower polysaccharide by central composite design response surface methodology and evaluate its quality.Methods:Taking the extraction rate of Carthamus tinctorius polysaccharide as the index,taking the ratio of solid to liquid,extraction time,extraction temperature and extraction times as the investigation factors,based on the single factor experiment,the central composite design-response surface methodology was used to optimize the optimum extraction process of Carthamus tinctorius polysaccharide and verify it.Results:The response surface model was established with the extraction rate of Carthamus tinctorius polysaccharide as dependent variable Y,the ratio of solid to liquid,extraction time and extraction temperature as independent variables X,P<0.0001.The optimum extraction process was as follows:the ratio of solid to liquid was 1:16.69,the extraction temperature was 91.39℃,and the extraction working time was 89.78min.Under these conditions,the extraction rate of safflower polysaccharide can reach 7.45%,The experimental results show that RSD is 1.05%,and the model can well predict the experimental results.Conclusion:Central Composite Design-Response Surface Methodology has the advantages of high extraction rate,simple,effective and reasonable process operation,high stability and high precision,which can be fully applied to the resource management and utilization of safflower polysaccharide.

Central Composite Design Method for the Preparation, Stability and Properties of Water-in-Diesel Nano Emulsions

Water in diesel nano-emulsion (WiDNE) due to their nano size, kinetically stable gives its beneficial in commercial and environmental aspects. However, the capability of this fuel strongly depends on the method of preparation, stability and their physic-chemical properties. Central composite design (CCD) method was used to optimize variable interactions in order to obtain maximum stability. Methodology RSM method with six independent variables was selected in order to understand the impacts on droplet size. The response surface and 3D plots of the quadratic polynomial model were created for studying the combination effect on response. Dynamic light scattering DLS technique was used for measuring of droplet sizes. The analysis result by ANOVA was with 95% confidence displaying F value model was 52.82. The results displayed model was fulfilled with the assumptions of ANOVA. This study has relied on Design Expert software to locate the optimum droplet size situations. The measured diameter is 26 nm, with 0.0297 errors between actual conditions and measured value. The optimum blend properties of prepared WiDNE fuel were compared with conventional diesel. Improvements in physical properties were observed in presence of water in WiDNE.

Central Composite Design响应面法优化厚裂凤仙花总黄酮提取工艺研究

为厚裂凤仙花中总黄酮资源的开发利用,本文采用单因素与星点-效应面法相结合的方式,考察提取溶剂浓度、料液比、提取时间、提取次数对厚裂凤仙花中总黄酮提取率的影响。优选出厚裂凤仙花总黄酮最佳提取方法为:甲醇体积分数80%,料液比为1︰64,提取时间为50 min;提次数为3次;验证实验结果表明,总黄酮平均提取率为5.51 mg/g,与实验模型RSD值为0.79%。建立的模型与实际方案有较高拟合度,可作为苗药厚裂凤仙花总黄酮提取工艺参数。

Central-Composite Design响应面实验设计用于金盏菊提取工艺的研究

目的:确定金盏菊最佳提取工艺条件。方法:以金盏菊中总黄酮含量及浸膏得率为考察指标,应用中心组合(Central composite design,CCD)响应面实验设计,考察药材与提取溶剂的比例(料液比)、乙醇浓度、提取时间对金盏花提取效率的影响。结果:根据二项式拟合方程,确定金盏花最佳提取工艺条件为药材与溶剂的比例为1∶12,乙醇浓度为68%,提取时间为1.8 h,提取两次。结论:中心组合响应面实验设计能够对金盏菊的提取工艺进行优化筛选。

Structural Design Strategies of Polymer Matrix Composites for Electromagnetic Interference Shielding:A Review

With the widespread application of electronic communication technology,the resulting electromagnetic radiation pollution has been significantly increased.Metal matrix electromagnetic interference(EMI)shielding materials have disadvantages such as high density,easy corrosion,difficult processing and high price,etc.Polymer matrix EMI shielding composites possess light weight,corrosion resistance and easy processing.However,the current polymer matrix composites present relatively low electrical conductivity and poor EMI shielding performance.This review firstly discusses the key concept,loss mechanism and test method of EMI shielding.Then the current development status of EMI shielding materials is summarized,and the research progress of polymer matrix EMI shielding composites with different structures is illustrated,especially for their preparation methods and evaluation.Finally,the corresponding key scientific and technical problems are proposed,and their development trend is also prospected.

RELIABILITY-BASED DESIGN OF COMPOSITES UNDER THE MIXED UNCERTAINTIES AND THE OPTIMIZATION ALGORITHM

This paper proposed a reliability design model for composite materials under the mixture of random and interval variables. Together with the inverse reliability analysis technique, the sequential single-loop optimization method is applied to the reliability-based design of composites. In the sequential single-loop optimization, the optimization and the reliability analysis are decoupled to improve the computational efficiency. As shown in examples, the minimum weight problems under the constraint of structural reliability are solved for laminated composites. The Particle Swarm Optimization （PSO） algorithm is utilized to search for the optimal solutions. The design results indicate that, under the mixture of random and interval variables, the method that combines the sequential single-loop optimization and the PSO algorithm can deal effectively with the reliability-based design of composites.

ROBUST OPTIMUM DESIGN OF LAMINATED COMPOSITE PLATES

A last-ply failure (LPF) analysis method for laminated composite plates is incorpo- rated into the ?nite element code-ANSYS, and a robust optimum design method is presented. The composite structure is analyzed by considering both in-plane and out-of-plane loads. For a lamina, two major failure modes are considered: matrix failure and ?ber breakage that are characterized by the proper strength criteria in the literature. When a lamina has failed, the laminate sti?ness is modi?ed to re?ect the damage, and stresses in the structure are re-analyzed. This procedure is repeatedly performed until the whole structure fails and thus the ultimate strength is determined. A structural optimization problem is solved with the ?ber orientation and the lamina thickness as the design variables and the LPF load as the objective. Finally, the robust optimum design method for laminates is presented and discussed.

Hashin Failure Theory Based Damage Assessment Methodology of Composite Tidal Turbine Blades and Implications for the Blade Design

A damage assessment methodology based on the Hashin failure theory for glass fiber reinforced polymer(GFRP)composite blade is proposed. The typical failure mechanisms including the fiber tension/compression and matrix tension/compression are considered to describe the damage behaviors. To give the flapwise and edgewise loading along the blade span, the Blade Element Momentum Theory(BEMT) is adopted. In conjunction with the hydrodynamic analysis, the structural analysis of the composite blade is cooperatively performed with the Hashin damage model. The damage characteristics of the composite blade, under normal and extreme operational conditions,are comparatively analyzed. Numerical results demonstrate that the matrix tension damage is the most significant failure mode which occurs in the mid-span of the blade. The blade internal configurations including the box-beam, Ibeam, left-C beam and right-C beam are compared and analyzed. The GFRP and carbon fiber reinforced polymer(CFRP) are considered and combined. Numerical results show that the I-beam is the best structural type. The structural performance of composite tidal turbine blades could be improved by combining the GFRP and CFRP structure considering the damage and cost-effectiveness synthetically.