Due to the complex chemical composition of nickel ores, the requests for the decrease of production costs, and the increase of nickel extraction in the existing depletion of high-grade sulfide ores around the world, c...Due to the complex chemical composition of nickel ores, the requests for the decrease of production costs, and the increase of nickel extraction in the existing depletion of high-grade sulfide ores around the world, computer modeling of nickel ore leaching process be- came a need and a challenge. In this paper, the design of experiments （DOE） theory was used to determine the optimal experimental design plan matrix based on the D optimality criterion. In the high-pressure sulfuric acid leaching （HPSAL） process for nickel laterite in ＂Rudjinci＂ ore in Serbia, the temperature, the sulfuric acid to ore ratio, the stirring speed, and the leaching time as the predictor variables, and the degree of nickel extraction as the response have been considered. To model the process, the multiple linear regression （MLR） and response surface method （RSM）, together with the two-level and four-factor full factorial central composite design （CCD） plan, were used. The proposed re- gression models have not been proven adequate. Therefore, the artificial neural network （ANN） approach with the same experimental plan was used in order to reduce operational costs, give a better modeling accuracy, and provide a more successful process optimization. The model is based on the multi-layer neural networks with the back-propagation （BP） learning algorithm and the bipolar sigmoid activation function.展开更多
One promising joining method for NiTi-SMA （shape memory alloy）-components is laser welding. This joining technology bears huge potential regarding process automation and mechanical properties as well as durability, ...One promising joining method for NiTi-SMA （shape memory alloy）-components is laser welding. This joining technology bears huge potential regarding process automation and mechanical properties as well as durability, especially within the field of small- and medium-sized actuators. However, there is still need for research due to unsolved issues influencing the microstructure and thus effecting mechanical properties as well as SMA-characteristics of these joints. Therefore, the purpose of this paper is the evaluation of quality parameters of NiTi-NiTi-wire-joints. For this purpose, design of experiments with a fractional factorial design is used for the investigation, because of its high potential to decrease experimental effort. This paper provides a basis for future research in the field of SMA-actuators and joining.展开更多
The design of new Satellite Launch Vehicle （SLV） is of interest, especially when a combination of Solid and Liquid Propulsion is included. Proposed is a conceptual design and optimization technique for multistage Lo...The design of new Satellite Launch Vehicle （SLV） is of interest, especially when a combination of Solid and Liquid Propulsion is included. Proposed is a conceptual design and optimization technique for multistage Low Earth Orbit （LEO） bound SLV comprising of solid and liquid stages with the use of Genetic Algorithm （GA） as global optimizer. Convergence of GA is improved by introducing initial population based on the Design of Experiments （DOE） Technique. Latin Hypercube Sampling （LHS）-DOE is used for its good space filling properties. LHS is a stratified random procedure that provides an efficient way of sampling variables from their multivariate distributions. In SLV design minimum Gross Lift offWeight （GLOW） concept is traditionally being sought. Since the development costs tend to vary as a function of GLOW, this minimum GLOW is considered as a minimum development cost concept. The design approach is meaningful to initial design sizing purpose for its computational efficiency gives a quick insight into the vehicle performance prior to detailed design.展开更多
In this study, a design of experiments (DoE) approach was used to develop a PLA open-cell foam morphology using the compression molding technique. The effect of three molding parameters (foaming time, mold opening tem...In this study, a design of experiments (DoE) approach was used to develop a PLA open-cell foam morphology using the compression molding technique. The effect of three molding parameters (foaming time, mold opening temperature, and weight concentration of the ADA blowing agent) on the cellular structure was investigated. A regression equation relating the average cell size to the above three processing parameters was developed from the DoE and the analysis of variance (ANOVA) was used to find the best dimensional fitting parameters based on the experimental data. With the help of the DoE technique, we were able to develop various foam morphologies having different average cell size distribution levels, which is important in the development of open-cell PLA scaffolds for bone regeneration for which the control of cell morphology is crucial for osteoblasts proliferation. For example, at a constant ADA weight concentration of 5.95 wt%, we were able to develop a narrow average cell size distribution ranging between 275 and 300 μm by varying the mold opening temperature between 106°C and 112°C, while maintaining the foaming time constant at 8 min, or by varying the mold foaming time between 6 and 11 min and maintaining the mold opening temperature at 109°C.展开更多
As a highly tempting technology to close the carbon cycle,electrochemical CO_(2)reduction calls for the development of highly efficient and durable electrocatalysts.In the current study,Design of Experiments utilizing...As a highly tempting technology to close the carbon cycle,electrochemical CO_(2)reduction calls for the development of highly efficient and durable electrocatalysts.In the current study,Design of Experiments utilizing the response surface method is exploited to predict the optimal process variables for preparing high-performance Cu catalysts,unraveling that the selectivity towards methane or ethylene can be simply modulated by varying the evaporation parameters,among which the Cu film thickness is the most pivotal factor to determine the product selectivity.The predicted optimal catalyst with a low Cu thickness affords a high methane Faradaic efficiency of 70.6%at the partial current density of 211.8 m A cm^(-2),whereas that of a high Cu thickness achieves a high ethylene selectivity of 66.8%at267.2 m A cm^(-2)in the flow cell.Further structure-performance correlation and in-situ electrospectroscopic measurements attribute the high methane selectivity to isolated Cu clusters with low packing density and monotonous lattice structure,and the high ethylene efficiency to coalesced Cu nanoparticles with rich grain boundaries and lattice defects.The high Cu packing density and crystallographic diversity is of essence to promoting C–C coupling by stabilizing*CO and suppressing*H coverage on the catalyst surface.This work highlights the implementation of scientific and mathematic methods to uncover optimal catalysts and mechanistic understandings toward selective electrochemical CO_(2)reduction.展开更多
Objective:Quality by design integration is exceedingly imperative for industries dealing with pharmaceuticals,but it diminishes product variability and delivers an extraordinary degree of assurance that the product wo...Objective:Quality by design integration is exceedingly imperative for industries dealing with pharmaceuticals,but it diminishes product variability and delivers an extraordinary degree of assurance that the product would achieve the purpose for which it was formulated.The objective of the manuscript is to strengthen the understanding of the design of experimentation approach from the primary level.Hence,this review paper aims to get one experience with a course emphasizing product quality during its development process.Methods:The present work describes how experimental statistical designs can optimize the process.It is a strategy to improve the manufacturing of products and discuss the main factors involved in the production.The review describes different designs,advantages,disadvantages and design of experiments requirements concerning regulatory submissions.Results:Quality by design encourages the pharmaceutical industry to deal with risk management and proper understanding of products and manufacturing processes,assuring a good quality product.Having knowledge of quality by design and design of experiments in the formulation and process development will be beneficial for the optimization of drug delivery systems in upcoming times.Conclusion:Implementing quality by design at different phases in pharmaceutical manufacturing,the final product with a great degree of reproducible quality may be assured,depending upon experimental data.This contains valuable information in guiding new researchers about the importance and ways of using the design of experiments.展开更多
Spraying parameters during particle agglomeration processes can affect the agglomeration kinetics and particle growth.This study was conducted to better understand the influence of the spraying parameters in a fluidiz...Spraying parameters during particle agglomeration processes can affect the agglomeration kinetics and particle growth.This study was conducted to better understand the influence of the spraying parameters in a fluidized bed wet agglomeration process,and the influence on the stability characteristics of carbon tablets.A formulation based on fine carbon and peroxide powder,as well as carboxymethyl cellulose as a binder,was used to produce agglomerates in a first production step.Thereafter in a second production step carbon tablets with a high porosity were molded for the customer goods industry.The optimization of the compressive strength of these carbon tablets was the goal of the trials.Carbon agglomerates were produced with a laboratory scale granulator called“ProCell”and were compressed with a five-cavity mechanical press.The screening of the agglomeration process parameters and their influence on the agglomerates quality,as well as the performance characteristics of the carbon tablets,were investigated using a multilevel factorial design.The experimental runs were done by varying atomized air pressure and feed rate of the fluid.This was determined by the design model.The findings of the statistical trials showed that low atomized air pressure and a low feed rate lead to a higher tablet compressive strength.展开更多
The study is focused on the use of nanofluids in a micro-open tall cavity,which is a type of micro heat exchanger(MHE).The cavity is heated from the bottom sidewall in a sinusoidal pattern,and the effects of four inpu...The study is focused on the use of nanofluids in a micro-open tall cavity,which is a type of micro heat exchanger(MHE).The cavity is heated from the bottom sidewall in a sinusoidal pattern,and the effects of four input parameters(Ra,Ha,Kn,and Vf)on heat transfer and irreversibility are investigated using numerical simulations based on Lattice Boltzmann Method(LBM).The findings of the study suggest that the local heat transfer on the bottom sidewall is strongly influenced by Ra and Ha,while the surface distribution of entropy generation is mainly dependent on Kn.The study also shows that the optimization of the magnitude and wavelength of the sinusoidal temperature can improve both local heat transfer and surface distribution of entropy generation.The results of the study provide valuable insights into the design of micro heat exchangers and suggest that the optimization of micro-porous geometries using DOE could lead to increased energy efficiency.The study contributes to our understanding of the complex interactions between input parameters in micro heat exchangers and highlights the importance of considering multiple parameters in the design process.展开更多
The present work is aimed at determining the optimal geometry layout of a wave energy converter platform for plate energy harvesting performance.A linear potential fluid theory method was applied to analyzing the inte...The present work is aimed at determining the optimal geometry layout of a wave energy converter platform for plate energy harvesting performance.A linear potential fluid theory method was applied to analyzing the interaction between the platform and plate.Three factors of layout geometry were tested and the performance of the plate was analyzed.The methodology of design of experiments was used to confirm factor significance and build response surface model.The 1st order model and the 2nd order model were built to describe the relation between factors and plate performance.The significance of two factors and their interactions were revealed,and an optimal parameter set was found.The wave form in front of the plate confirmed the interactions.It is clear that a wide entrance and enclosing channel for waves can maximize the plate performance.展开更多
A renaissance in cell-free protein synthesis(CFPS)is underway,enabled by the acceleration and adoption of synthetic biology methods.CFPS has emerged as a powerful platform technology for synthetic gene network design,...A renaissance in cell-free protein synthesis(CFPS)is underway,enabled by the acceleration and adoption of synthetic biology methods.CFPS has emerged as a powerful platform technology for synthetic gene network design,biosensing and on-demand biomanufacturing.Whilst primarily of bacterial origin,cell-free extracts derived from a variety of host organisms have been explored,aiming to capitalise on cellular diversity and the advantageous properties associated with those organisms.However,cell-free extracts produced from eukaryotes are often overlooked due to their relatively low yields,despite the potential for improved protein folding and posttranslational modifications.Here we describe further development of a Pichia pastoris cell-free platform,a widely used expression host in both academia and the biopharmaceutical industry.Using a minimised Design of Experiments(DOE)approach,we were able to increase the productivity of the system by improving the composition of the complex reaction mixture.This was achieved in a minimal number of experimental runs,within the constraints of the design and without the need for liquid-handling robots.In doing so,we were able to estimate the main effects impacting productivity in the system and increased the protein synthesis of firefly luciferase and the biopharmaceutical HSA by 4.8-fold and 3.5-fold,respectively.This study highlights the P.pastoris-based cell-free system as a highly productive eukaryotic platform and displays the value of minimised DOE designs.展开更多
Many studies,both experimental and numerical,were devoted to the electric current of corona discharge and some mathematical models were proposed to express it.As it depends on several parameters,it is diffi cult to fi...Many studies,both experimental and numerical,were devoted to the electric current of corona discharge and some mathematical models were proposed to express it.As it depends on several parameters,it is diffi cult to find a theoretical or an experimental formula,which considers all the factors.So we opted for the methodology of experimental designs,also called Tagushi’s methodology,which represents a powerful tool generally employed when the process has many factors to consider.The objective of this paper is to model current using this experimental methodology.The factors considered were geometrical factors(interelectrode interval,surface of the grounded plane electrode,curvature radius of the point electrode),climatic factors(temperature and relative humidity),and applied high voltage.Results of experiments made it possible to obtain mathematical models and to analyse the interactions between all factors.展开更多
Paper and pulp mills generate substantial volumes of wastewater containing lignin-derived compounds that are challenging to degrade using conventional wastewater treatment methods.This study presents a novel biofilm-b...Paper and pulp mills generate substantial volumes of wastewater containing lignin-derived compounds that are challenging to degrade using conventional wastewater treatment methods.This study presents a novel biofilm-based process for enhanced lignin removal in wastewater using the fungus Neurospora discreta,which effectively degrades lignin and forms robust biofilms at the air–liquid interface under specific conditions.The process was optimised using the Taguchi design of experiments approach,and three factors including pH,copper sulphate concentration,and trace element concentration were evaluated at three levels.Experimental data were analysed against three responses:lignin degradation efficiency and the activities of two ligninolytic enzymes(polyphenol oxidase and versatile peroxidase).The results indicated that wastewater pH was the most significant parameter affecting lignin degradation efficiency and enzyme activities.Over 70%lignin degradation was achieved at pH levels of 5 and 6 with copper sulphate concentrations above 4 mg/L,while degradation efficiency drastically dropped to 45%at a pH value of 7.Reversed-phase high-performance liquid chromatography analysis demonstrated the effects of the three factors on the polar and non-polar components of lignin in wastewater,revealing a clear decrease in all peak areas after treatment.Additionally,significant relationships were observed between biofilm properties(including porosity,water retention value,polysaccharide content,and protein content)and lignin removal efficiency.This study also reported for the first time the presence of versatile peroxidase,a ligninolytic enzyme,in Neurospora sp.展开更多
The operation of complex systems can drift away from the initial design conditions,due to environmental condi-tions,equipment wear or specific restrictions.Steam generators are complex equipment and their proper opera...The operation of complex systems can drift away from the initial design conditions,due to environmental condi-tions,equipment wear or specific restrictions.Steam generators are complex equipment and their proper opera-tion relies on the identification of their most relevant parameters.An approach to rank the operational parameters of a subcritical steam generator of an actual 360 MW power plant is presented.An Artificial Neural Network-ANN delivers a model to estimate the steam generator efficiency,electric power generation and flue gas outlet temperature as a function of seven input parameters.The ANN is trained with a two-year long database,with training errors of 0.2015 and 0.2741(mean absolute and square error)and validation errors of 0.32%and 2.350(mean percent and square error).That ANN model is explored by means of a combination of situations proposed by a Design of Experiment-DoE approach.All seven controlled parameters showed to be relevant to express both steam generator efficiency and electric power generation,while primary air flow rate and speed of the dynamic classifier can be neglected to calculate flue gas temperature as they are not statistically significant.DoE also shows the prominence of the primary air pressure in respect to the steam generator efficiency,electric power generation and the coal mass flow rate for the calculation of the flue gas outlet temperature.The ANN and DoE combined methodology shows to be promising to enhance complex system efficiency and helpful whenever a biased behavior must be brought back to stable operation.展开更多
Tolerance design plays an important role in reliability design for electronic circuits. The traditional method only focuses on the consistency of output response. It is not able to meet the needs of increasing develop...Tolerance design plays an important role in reliability design for electronic circuits. The traditional method only focuses on the consistency of output response. It is not able to meet the needs of increasing development of electronic products. This paper researches the state of related fields and proposes a method of multi-objective reliability tolerance design. The characteristics of output response and operating stresses on critical components are both defined as design objectives. Critical components and their operating stresses are determined by failure mode and effect analysis （FMEA） and fault tree analysis （FTA）. Sensitivity analysis is carried out to determine sensitive parameters that affect the design objectives significantly. Monte Carlo and worst-case analysis are utilized to explore the tolerance levels of sensitive parameters. Design of experiment and regression analysis are applied in this method. The optimal tolerance levels are selected in accord with a quality-cost model to improve consistency of output response and reduce failure rates of critical components synchronously. The application in light-emitting diode （LED） drivers indicates details and potential. It shows that the proposed method provides a more effective way to improve performance and reliability of electronic circuits.展开更多
Electromagnetic stir casting process of A357-Si C nanocomposite was discussed using the D-optimal design of experiment(DODOE) method. As the main objective, nine random experiments obtained by DX-7 software were perfo...Electromagnetic stir casting process of A357-Si C nanocomposite was discussed using the D-optimal design of experiment(DODOE) method. As the main objective, nine random experiments obtained by DX-7 software were performed. By this method, A357-Si C nanocomposites with 0.5, 1.0 and 1.5 wt.% Si C were fabricated at three different frequencies(10, 35 and 60 Hz) in the experimental stage. The microstructural evolution was characterized by scanning electron and optical microscopes, and the mechanical properties were investigated using hardness and roomtemperature uniaxial tensile tests. The results showed that the homogeneous distribution of Si C nanoparticles leads to the microstructure evolution from dendritic to non-dendritic form and a reduction of size by 73.9%. Additionally, based on DODOE, F-values of 44.80 and 179.64 were achieved for yield stress(YS) and ultimate tensile strength(UTS), respectively, implying that the model is significant and the variables(Si C fraction and stirring frequency) were appropriately selected. The optimum values of the Si C fraction and stirring frequency were found to be 1.5 wt.% and 60 Hz, respectively. In this case, YS and UTS for A357-Si C nanocomposites were obtained to be 120 and 188 MPa(57.7% and 57.9 % increase compared with those of the as-cast sample), respectively.展开更多
Lattice structures are three-dimensional structures composed of repeated geometrical shapes with multiple interconnected nodes,providing high strength-to-weight ratios,customizable properties,and efficient use of mate...Lattice structures are three-dimensional structures composed of repeated geometrical shapes with multiple interconnected nodes,providing high strength-to-weight ratios,customizable properties,and efficient use of materials.A smart use of materials leads to reduced fuel consumption and lower operating costs,making them highly desirable for aircraft manufacturers.Furthermore,the customizable properties of lattice structures allow for tailoring to specific design requirements,leading to improved performance and safety for aircraft.These advantages make lattice structures an important focus for research and development in the aviation industry.This paper presents an experimental evaluation of the mechanical compression properties of lattice trusses made with Ti6Al4V,designed for use in an anti-ice system.The truss structures were manufactured using additive manufacturing techniques and tested under compressive loads to determine mechanical properties.Results showed that lattice trusses exhibited high levels of compressive strength,making them suitable for use in applications where mechanical resistance and durability are critical,such as in anti-ice systems.We also highlight the potential of additive manufacturing techniques for the fabrication of lattice trusses with tailored mechanical properties.The study provides valuable insights into the mechanical behavior of Ti6Al4V lattice trusses and their potential applications in anti-ice systems,as well as other areas where high strength-to-weight ratios are required.The results of this research contribute to the development of lightweight,efficient,and durable anti-ice systems for use in aviation and other industries.展开更多
Neural networks are being used to construct meta-models in numerical simulation of structures.In addition to network structures and training algorithms,training samples also greatly affect the accuracy of neural netwo...Neural networks are being used to construct meta-models in numerical simulation of structures.In addition to network structures and training algorithms,training samples also greatly affect the accuracy of neural network models.In this paper,some existing main sampling techniques are evaluated,including techniques based on experimental design theory, random selection,and rotating sampling.First,advantages and disadvantages of each technique are reviewed.Then,seven techniques are used to generate samples for training radial neural networks models for two benchmarks:an antenna model and an aircraft model.Results show that the uniform design,in which the number of samples and mean square error network models are considered,is the best sampling technique for neural network based meta-model building.展开更多
The paper deals with factorial experimental design models decoding.For the ease of calculation of the experimental mathematical models,it is convenient first to code the independent variables.When selecting independen...The paper deals with factorial experimental design models decoding.For the ease of calculation of the experimental mathematical models,it is convenient first to code the independent variables.When selecting independent variables,it is necessary to take into account the range covered by each.A wide range of choices of different variables is presented in this paper.After calculating the regression model,its variables must be returned to their original values for the model to be easy recognized and represented.In the paper,the procedures of simple first order models,with interactions and with second order models,are presented,which could be a very complicated process.Models without and with the mutual influence of independent variables differ.The encoding and decoding procedure on a model with two independent first-order parameters is presented in details.Also,the procedure of model decoding is presented in the experimental surface roughness parameters models’determination,in the face milling machining process,using the first and second order model central compositional experimental design.The simple calculation procedure is recommended in the case study.Also,a large number of examples using mathematical models obtained on the basis of the presented methodology are presented throughout the paper.展开更多
Recent advances in automation and digitization enable the close integration of physical devices with their virtual counterparts, facilitating the real-time modeling and optimization of a multitude of processes in an a...Recent advances in automation and digitization enable the close integration of physical devices with their virtual counterparts, facilitating the real-time modeling and optimization of a multitude of processes in an automatic way. The rich and continuously updated data environment provided by such systems makes it possible for decisions to be made over time to drive the process toward optimal targets. In many man- ufacturing processes, in order to achieve an overall optimal process, the simultaneous assessment of mul- tiple objective functions related to process performance and cost is necessary. In this work, a multi- objective optimal experimental design framework is proposed to enhance the ef ciency of online model-identi cation platforms. The proposed framework permits exibility in the choice of trade-off experimental design solutions, which are calculated online that is, during the execution of experiments. The application of this framework to improve the online identi cation of kinetic models in ow reactors is illustrated using a case study in which a kinetic model is identi ed for the esteri cation of benzoic acid and ethanol in a microreactor.展开更多
Due to operational or physical considerations, standard factorial and response surface method （RSM） design of experiments （DOE） often prove to be unsuitable. In such cases a computer-generated statistically-optima...Due to operational or physical considerations, standard factorial and response surface method （RSM） design of experiments （DOE） often prove to be unsuitable. In such cases a computer-generated statistically-optimal design fills the breech. This article explores vital mathematical properties for evaluating alternative designs with a focus on what is really important for industrial experimenters. To assess ＂goodness of design＂ such evaluations must consider the model choice, specific optimality criteria （in particular D and I）, precision of estimation based on the fraction of design space （FDS）, the number of runs to achieve required precision, lack-of-fit testing, and so forth. With a focus on RSM, all these issues are considered at a practical level, keeping engineers and scientists in mind. This brings to the forefront such considerations as subject-matter knowledge from first principles and experience, factor choice and the feasibility of the experiment design.展开更多
文摘Due to the complex chemical composition of nickel ores, the requests for the decrease of production costs, and the increase of nickel extraction in the existing depletion of high-grade sulfide ores around the world, computer modeling of nickel ore leaching process be- came a need and a challenge. In this paper, the design of experiments （DOE） theory was used to determine the optimal experimental design plan matrix based on the D optimality criterion. In the high-pressure sulfuric acid leaching （HPSAL） process for nickel laterite in ＂Rudjinci＂ ore in Serbia, the temperature, the sulfuric acid to ore ratio, the stirring speed, and the leaching time as the predictor variables, and the degree of nickel extraction as the response have been considered. To model the process, the multiple linear regression （MLR） and response surface method （RSM）, together with the two-level and four-factor full factorial central composite design （CCD） plan, were used. The proposed re- gression models have not been proven adequate. Therefore, the artificial neural network （ANN） approach with the same experimental plan was used in order to reduce operational costs, give a better modeling accuracy, and provide a more successful process optimization. The model is based on the multi-layer neural networks with the back-propagation （BP） learning algorithm and the bipolar sigmoid activation function.
文摘One promising joining method for NiTi-SMA （shape memory alloy）-components is laser welding. This joining technology bears huge potential regarding process automation and mechanical properties as well as durability, especially within the field of small- and medium-sized actuators. However, there is still need for research due to unsolved issues influencing the microstructure and thus effecting mechanical properties as well as SMA-characteristics of these joints. Therefore, the purpose of this paper is the evaluation of quality parameters of NiTi-NiTi-wire-joints. For this purpose, design of experiments with a fractional factorial design is used for the investigation, because of its high potential to decrease experimental effort. This paper provides a basis for future research in the field of SMA-actuators and joining.
文摘The design of new Satellite Launch Vehicle （SLV） is of interest, especially when a combination of Solid and Liquid Propulsion is included. Proposed is a conceptual design and optimization technique for multistage Low Earth Orbit （LEO） bound SLV comprising of solid and liquid stages with the use of Genetic Algorithm （GA） as global optimizer. Convergence of GA is improved by introducing initial population based on the Design of Experiments （DOE） Technique. Latin Hypercube Sampling （LHS）-DOE is used for its good space filling properties. LHS is a stratified random procedure that provides an efficient way of sampling variables from their multivariate distributions. In SLV design minimum Gross Lift offWeight （GLOW） concept is traditionally being sought. Since the development costs tend to vary as a function of GLOW, this minimum GLOW is considered as a minimum development cost concept. The design approach is meaningful to initial design sizing purpose for its computational efficiency gives a quick insight into the vehicle performance prior to detailed design.
文摘In this study, a design of experiments (DoE) approach was used to develop a PLA open-cell foam morphology using the compression molding technique. The effect of three molding parameters (foaming time, mold opening temperature, and weight concentration of the ADA blowing agent) on the cellular structure was investigated. A regression equation relating the average cell size to the above three processing parameters was developed from the DoE and the analysis of variance (ANOVA) was used to find the best dimensional fitting parameters based on the experimental data. With the help of the DoE technique, we were able to develop various foam morphologies having different average cell size distribution levels, which is important in the development of open-cell PLA scaffolds for bone regeneration for which the control of cell morphology is crucial for osteoblasts proliferation. For example, at a constant ADA weight concentration of 5.95 wt%, we were able to develop a narrow average cell size distribution ranging between 275 and 300 μm by varying the mold opening temperature between 106°C and 112°C, while maintaining the foaming time constant at 8 min, or by varying the mold foaming time between 6 and 11 min and maintaining the mold opening temperature at 109°C.
基金supported by the National Key R&D Program of China(2020YFB1505703)the National Natural Science Foundation of China(22072101,22075193)+2 种基金supported by the Natural Science Foundation of Jiangsu Province(BK20211306)the Six Talent Peaks Project in Jiangsu Province(TD-XCL-006)the Priority Academic Program Development(PAPD)of Jiangsu Higher Education Institutions。
文摘As a highly tempting technology to close the carbon cycle,electrochemical CO_(2)reduction calls for the development of highly efficient and durable electrocatalysts.In the current study,Design of Experiments utilizing the response surface method is exploited to predict the optimal process variables for preparing high-performance Cu catalysts,unraveling that the selectivity towards methane or ethylene can be simply modulated by varying the evaporation parameters,among which the Cu film thickness is the most pivotal factor to determine the product selectivity.The predicted optimal catalyst with a low Cu thickness affords a high methane Faradaic efficiency of 70.6%at the partial current density of 211.8 m A cm^(-2),whereas that of a high Cu thickness achieves a high ethylene selectivity of 66.8%at267.2 m A cm^(-2)in the flow cell.Further structure-performance correlation and in-situ electrospectroscopic measurements attribute the high methane selectivity to isolated Cu clusters with low packing density and monotonous lattice structure,and the high ethylene efficiency to coalesced Cu nanoparticles with rich grain boundaries and lattice defects.The high Cu packing density and crystallographic diversity is of essence to promoting C–C coupling by stabilizing*CO and suppressing*H coverage on the catalyst surface.This work highlights the implementation of scientific and mathematic methods to uncover optimal catalysts and mechanistic understandings toward selective electrochemical CO_(2)reduction.
文摘Objective:Quality by design integration is exceedingly imperative for industries dealing with pharmaceuticals,but it diminishes product variability and delivers an extraordinary degree of assurance that the product would achieve the purpose for which it was formulated.The objective of the manuscript is to strengthen the understanding of the design of experimentation approach from the primary level.Hence,this review paper aims to get one experience with a course emphasizing product quality during its development process.Methods:The present work describes how experimental statistical designs can optimize the process.It is a strategy to improve the manufacturing of products and discuss the main factors involved in the production.The review describes different designs,advantages,disadvantages and design of experiments requirements concerning regulatory submissions.Results:Quality by design encourages the pharmaceutical industry to deal with risk management and proper understanding of products and manufacturing processes,assuring a good quality product.Having knowledge of quality by design and design of experiments in the formulation and process development will be beneficial for the optimization of drug delivery systems in upcoming times.Conclusion:Implementing quality by design at different phases in pharmaceutical manufacturing,the final product with a great degree of reproducible quality may be assured,depending upon experimental data.This contains valuable information in guiding new researchers about the importance and ways of using the design of experiments.
文摘Spraying parameters during particle agglomeration processes can affect the agglomeration kinetics and particle growth.This study was conducted to better understand the influence of the spraying parameters in a fluidized bed wet agglomeration process,and the influence on the stability characteristics of carbon tablets.A formulation based on fine carbon and peroxide powder,as well as carboxymethyl cellulose as a binder,was used to produce agglomerates in a first production step.Thereafter in a second production step carbon tablets with a high porosity were molded for the customer goods industry.The optimization of the compressive strength of these carbon tablets was the goal of the trials.Carbon agglomerates were produced with a laboratory scale granulator called“ProCell”and were compressed with a five-cavity mechanical press.The screening of the agglomeration process parameters and their influence on the agglomerates quality,as well as the performance characteristics of the carbon tablets,were investigated using a multilevel factorial design.The experimental runs were done by varying atomized air pressure and feed rate of the fluid.This was determined by the design model.The findings of the statistical trials showed that low atomized air pressure and a low feed rate lead to a higher tablet compressive strength.
文摘The study is focused on the use of nanofluids in a micro-open tall cavity,which is a type of micro heat exchanger(MHE).The cavity is heated from the bottom sidewall in a sinusoidal pattern,and the effects of four input parameters(Ra,Ha,Kn,and Vf)on heat transfer and irreversibility are investigated using numerical simulations based on Lattice Boltzmann Method(LBM).The findings of the study suggest that the local heat transfer on the bottom sidewall is strongly influenced by Ra and Ha,while the surface distribution of entropy generation is mainly dependent on Kn.The study also shows that the optimization of the magnitude and wavelength of the sinusoidal temperature can improve both local heat transfer and surface distribution of entropy generation.The results of the study provide valuable insights into the design of micro heat exchangers and suggest that the optimization of micro-porous geometries using DOE could lead to increased energy efficiency.The study contributes to our understanding of the complex interactions between input parameters in micro heat exchangers and highlights the importance of considering multiple parameters in the design process.
基金the Marine Renewable Energy Special Fund of China(No.QDME2013ZB01)the National Research Program for High Technology Ship Development of China(No.MIIT 2014-498)。
文摘The present work is aimed at determining the optimal geometry layout of a wave energy converter platform for plate energy harvesting performance.A linear potential fluid theory method was applied to analyzing the interaction between the platform and plate.Three factors of layout geometry were tested and the performance of the plate was analyzed.The methodology of design of experiments was used to confirm factor significance and build response surface model.The 1st order model and the 2nd order model were built to describe the relation between factors and plate performance.The significance of two factors and their interactions were revealed,and an optimal parameter set was found.The wave form in front of the plate confirmed the interactions.It is clear that a wide entrance and enclosing channel for waves can maximize the plate performance.
基金This research is funded by the Department of Health and Social Care using UK Aid funding and is managed by the Engineering and Physical Sciences Research Council(EPSRC,grant number:EP/R013764/1).
文摘A renaissance in cell-free protein synthesis(CFPS)is underway,enabled by the acceleration and adoption of synthetic biology methods.CFPS has emerged as a powerful platform technology for synthetic gene network design,biosensing and on-demand biomanufacturing.Whilst primarily of bacterial origin,cell-free extracts derived from a variety of host organisms have been explored,aiming to capitalise on cellular diversity and the advantageous properties associated with those organisms.However,cell-free extracts produced from eukaryotes are often overlooked due to their relatively low yields,despite the potential for improved protein folding and posttranslational modifications.Here we describe further development of a Pichia pastoris cell-free platform,a widely used expression host in both academia and the biopharmaceutical industry.Using a minimised Design of Experiments(DOE)approach,we were able to increase the productivity of the system by improving the composition of the complex reaction mixture.This was achieved in a minimal number of experimental runs,within the constraints of the design and without the need for liquid-handling robots.In doing so,we were able to estimate the main effects impacting productivity in the system and increased the protein synthesis of firefly luciferase and the biopharmaceutical HSA by 4.8-fold and 3.5-fold,respectively.This study highlights the P.pastoris-based cell-free system as a highly productive eukaryotic platform and displays the value of minimised DOE designs.
基金supported partly within the frame work of a TASSILI project,jointly financed by the French and Alge rian Governments.
文摘Many studies,both experimental and numerical,were devoted to the electric current of corona discharge and some mathematical models were proposed to express it.As it depends on several parameters,it is diffi cult to find a theoretical or an experimental formula,which considers all the factors.So we opted for the methodology of experimental designs,also called Tagushi’s methodology,which represents a powerful tool generally employed when the process has many factors to consider.The objective of this paper is to model current using this experimental methodology.The factors considered were geometrical factors(interelectrode interval,surface of the grounded plane electrode,curvature radius of the point electrode),climatic factors(temperature and relative humidity),and applied high voltage.Results of experiments made it possible to obtain mathematical models and to analyse the interactions between all factors.
基金supported by the Leverhulme Trust Research Project(Grant No.RPG-2020-021).
文摘Paper and pulp mills generate substantial volumes of wastewater containing lignin-derived compounds that are challenging to degrade using conventional wastewater treatment methods.This study presents a novel biofilm-based process for enhanced lignin removal in wastewater using the fungus Neurospora discreta,which effectively degrades lignin and forms robust biofilms at the air–liquid interface under specific conditions.The process was optimised using the Taguchi design of experiments approach,and three factors including pH,copper sulphate concentration,and trace element concentration were evaluated at three levels.Experimental data were analysed against three responses:lignin degradation efficiency and the activities of two ligninolytic enzymes(polyphenol oxidase and versatile peroxidase).The results indicated that wastewater pH was the most significant parameter affecting lignin degradation efficiency and enzyme activities.Over 70%lignin degradation was achieved at pH levels of 5 and 6 with copper sulphate concentrations above 4 mg/L,while degradation efficiency drastically dropped to 45%at a pH value of 7.Reversed-phase high-performance liquid chromatography analysis demonstrated the effects of the three factors on the polar and non-polar components of lignin in wastewater,revealing a clear decrease in all peak areas after treatment.Additionally,significant relationships were observed between biofilm properties(including porosity,water retention value,polysaccharide content,and protein content)and lignin removal efficiency.This study also reported for the first time the presence of versatile peroxidase,a ligninolytic enzyme,in Neurospora sp.
文摘The operation of complex systems can drift away from the initial design conditions,due to environmental condi-tions,equipment wear or specific restrictions.Steam generators are complex equipment and their proper opera-tion relies on the identification of their most relevant parameters.An approach to rank the operational parameters of a subcritical steam generator of an actual 360 MW power plant is presented.An Artificial Neural Network-ANN delivers a model to estimate the steam generator efficiency,electric power generation and flue gas outlet temperature as a function of seven input parameters.The ANN is trained with a two-year long database,with training errors of 0.2015 and 0.2741(mean absolute and square error)and validation errors of 0.32%and 2.350(mean percent and square error).That ANN model is explored by means of a combination of situations proposed by a Design of Experiment-DoE approach.All seven controlled parameters showed to be relevant to express both steam generator efficiency and electric power generation,while primary air flow rate and speed of the dynamic classifier can be neglected to calculate flue gas temperature as they are not statistically significant.DoE also shows the prominence of the primary air pressure in respect to the steam generator efficiency,electric power generation and the coal mass flow rate for the calculation of the flue gas outlet temperature.The ANN and DoE combined methodology shows to be promising to enhance complex system efficiency and helpful whenever a biased behavior must be brought back to stable operation.
基金supported by National Defense Basic Research Program (No. 20112060303)
文摘Tolerance design plays an important role in reliability design for electronic circuits. The traditional method only focuses on the consistency of output response. It is not able to meet the needs of increasing development of electronic products. This paper researches the state of related fields and proposes a method of multi-objective reliability tolerance design. The characteristics of output response and operating stresses on critical components are both defined as design objectives. Critical components and their operating stresses are determined by failure mode and effect analysis （FMEA） and fault tree analysis （FTA）. Sensitivity analysis is carried out to determine sensitive parameters that affect the design objectives significantly. Monte Carlo and worst-case analysis are utilized to explore the tolerance levels of sensitive parameters. Design of experiment and regression analysis are applied in this method. The optimal tolerance levels are selected in accord with a quality-cost model to improve consistency of output response and reduce failure rates of critical components synchronously. The application in light-emitting diode （LED） drivers indicates details and potential. It shows that the proposed method provides a more effective way to improve performance and reliability of electronic circuits.
文摘Electromagnetic stir casting process of A357-Si C nanocomposite was discussed using the D-optimal design of experiment(DODOE) method. As the main objective, nine random experiments obtained by DX-7 software were performed. By this method, A357-Si C nanocomposites with 0.5, 1.0 and 1.5 wt.% Si C were fabricated at three different frequencies(10, 35 and 60 Hz) in the experimental stage. The microstructural evolution was characterized by scanning electron and optical microscopes, and the mechanical properties were investigated using hardness and roomtemperature uniaxial tensile tests. The results showed that the homogeneous distribution of Si C nanoparticles leads to the microstructure evolution from dendritic to non-dendritic form and a reduction of size by 73.9%. Additionally, based on DODOE, F-values of 44.80 and 179.64 were achieved for yield stress(YS) and ultimate tensile strength(UTS), respectively, implying that the model is significant and the variables(Si C fraction and stirring frequency) were appropriately selected. The optimum values of the Si C fraction and stirring frequency were found to be 1.5 wt.% and 60 Hz, respectively. In this case, YS and UTS for A357-Si C nanocomposites were obtained to be 120 and 188 MPa(57.7% and 57.9 % increase compared with those of the as-cast sample), respectively.
文摘Lattice structures are three-dimensional structures composed of repeated geometrical shapes with multiple interconnected nodes,providing high strength-to-weight ratios,customizable properties,and efficient use of materials.A smart use of materials leads to reduced fuel consumption and lower operating costs,making them highly desirable for aircraft manufacturers.Furthermore,the customizable properties of lattice structures allow for tailoring to specific design requirements,leading to improved performance and safety for aircraft.These advantages make lattice structures an important focus for research and development in the aviation industry.This paper presents an experimental evaluation of the mechanical compression properties of lattice trusses made with Ti6Al4V,designed for use in an anti-ice system.The truss structures were manufactured using additive manufacturing techniques and tested under compressive loads to determine mechanical properties.Results showed that lattice trusses exhibited high levels of compressive strength,making them suitable for use in applications where mechanical resistance and durability are critical,such as in anti-ice systems.We also highlight the potential of additive manufacturing techniques for the fabrication of lattice trusses with tailored mechanical properties.The study provides valuable insights into the mechanical behavior of Ti6Al4V lattice trusses and their potential applications in anti-ice systems,as well as other areas where high strength-to-weight ratios are required.The results of this research contribute to the development of lightweight,efficient,and durable anti-ice systems for use in aviation and other industries.
基金Specialized Research Fund for the Doctoral Program of Higher Education,China (No.20010227012)
文摘Neural networks are being used to construct meta-models in numerical simulation of structures.In addition to network structures and training algorithms,training samples also greatly affect the accuracy of neural network models.In this paper,some existing main sampling techniques are evaluated,including techniques based on experimental design theory, random selection,and rotating sampling.First,advantages and disadvantages of each technique are reviewed.Then,seven techniques are used to generate samples for training radial neural networks models for two benchmarks:an antenna model and an aircraft model.Results show that the uniform design,in which the number of samples and mean square error network models are considered,is the best sampling technique for neural network based meta-model building.
文摘The paper deals with factorial experimental design models decoding.For the ease of calculation of the experimental mathematical models,it is convenient first to code the independent variables.When selecting independent variables,it is necessary to take into account the range covered by each.A wide range of choices of different variables is presented in this paper.After calculating the regression model,its variables must be returned to their original values for the model to be easy recognized and represented.In the paper,the procedures of simple first order models,with interactions and with second order models,are presented,which could be a very complicated process.Models without and with the mutual influence of independent variables differ.The encoding and decoding procedure on a model with two independent first-order parameters is presented in details.Also,the procedure of model decoding is presented in the experimental surface roughness parameters models’determination,in the face milling machining process,using the first and second order model central compositional experimental design.The simple calculation procedure is recommended in the case study.Also,a large number of examples using mathematical models obtained on the basis of the presented methodology are presented throughout the paper.
文摘Recent advances in automation and digitization enable the close integration of physical devices with their virtual counterparts, facilitating the real-time modeling and optimization of a multitude of processes in an automatic way. The rich and continuously updated data environment provided by such systems makes it possible for decisions to be made over time to drive the process toward optimal targets. In many man- ufacturing processes, in order to achieve an overall optimal process, the simultaneous assessment of mul- tiple objective functions related to process performance and cost is necessary. In this work, a multi- objective optimal experimental design framework is proposed to enhance the ef ciency of online model-identi cation platforms. The proposed framework permits exibility in the choice of trade-off experimental design solutions, which are calculated online that is, during the execution of experiments. The application of this framework to improve the online identi cation of kinetic models in ow reactors is illustrated using a case study in which a kinetic model is identi ed for the esteri cation of benzoic acid and ethanol in a microreactor.
文摘Due to operational or physical considerations, standard factorial and response surface method （RSM） design of experiments （DOE） often prove to be unsuitable. In such cases a computer-generated statistically-optimal design fills the breech. This article explores vital mathematical properties for evaluating alternative designs with a focus on what is really important for industrial experimenters. To assess ＂goodness of design＂ such evaluations must consider the model choice, specific optimality criteria （in particular D and I）, precision of estimation based on the fraction of design space （FDS）, the number of runs to achieve required precision, lack-of-fit testing, and so forth. With a focus on RSM, all these issues are considered at a practical level, keeping engineers and scientists in mind. This brings to the forefront such considerations as subject-matter knowledge from first principles and experience, factor choice and the feasibility of the experiment design.
