Identification of process parameters,their effects and contributions to the outcomes of the system using experimental approach could be a daunting,time consuming,and costly course.Using proper statistical methods,i.e....Identification of process parameters,their effects and contributions to the outcomes of the system using experimental approach could be a daunting,time consuming,and costly course.Using proper statistical methods,i.e.,Taguchi method,could significantly reduce the number of required experiments and statistical significance of the parameter can be identified.Friction stir welding is one of those welding techniques with many parameters which have different effects on the quality of the welds.In friction stir welding the tool rotational speed(RPM)and transverse speed(mm/min)influence the strength(i.e.,hardness distribution)of the stirred zone.In this study,these two factors are investigated to determine the effect they will have on the hardness in the stirred zone of the friction stir welds and how the two factors are related to one another for as-cast magnesium alloy AM60 with nominal chemical composition of Mg-(5.5-6.5)Al-(0.24-0.6)Mn-0.22Zn-0.1Si.Experimental data was taken at three different tool rotational speeds and three different transverse speeds.The data obtained was then analyzed using a 32 factorial design to find the contribution of these parameters.It was determined that both tool rotational speed and transverse speed possess significant effects on the stir zone hardness.Also,the interactions between the two factors were statistically assessed.展开更多
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
This research introduces a novel approach to enhancing bucket elevator design and operation through the integration of discrete element method(DEM)simulation,design of experiments(DOE),and metaheuristic optimization a...This research introduces a novel approach to enhancing bucket elevator design and operation through the integration of discrete element method(DEM)simulation,design of experiments(DOE),and metaheuristic optimization algorithms.Specifically,the study employs the firefly algorithm(FA),a metaheuristic optimization technique,to optimize bucket elevator parameters for maximizing transport mass and mass flow rate discharge of granular materials under specified working conditions.The experimental methodology involves several key steps:screening experiments to identify significant factors affecting bucket elevator operation,central composite design(CCD)experiments to further explore these factors,and response surface methodology(RSM)to create predictive models for transport mass and mass flow rate discharge.The FA algorithm is then applied to optimize these models,and the results are validated through simulation and empirical experiments.The study validates the optimized parameters through simulation and empirical experiments,comparing results with DEM simulation.The outcomes demonstrate the effectiveness of the FA algorithm in identifying optimal bucket parameters,showcasing less than 10%and 15%deviation for transport mass and mass flow rate discharge,respectively,between predicted and actual values.Overall,this research provides insights into the critical factors influencing bucket elevator operation and offers a systematic methodology for optimizing bucket parameters,contributing to more efficient material handling in various industrial applications.展开更多
柴达木盆地西部地区的南翼山油田卤水锂资源丰富,共存元素复杂,传统的火焰原子吸收光谱法在测定该体系中锂含量时,基体干扰严重。而且油田卤水在各蒸发浓缩阶段的离子浓度变化幅度较大,一般的基体匹配法繁琐不便。研究采用Design of Exp...柴达木盆地西部地区的南翼山油田卤水锂资源丰富,共存元素复杂,传统的火焰原子吸收光谱法在测定该体系中锂含量时,基体干扰严重。而且油田卤水在各蒸发浓缩阶段的离子浓度变化幅度较大,一般的基体匹配法繁琐不便。研究采用Design of Experiments(DOE)实验设计,通过干扰元素的显著性分析、消电离剂的选择及干扰模型的建立,对传统的火焰原子吸收测定锂的分析方法进行了优化。运用部分因子实验设计研究了南翼山油田卤水中钙、锶、钾、钠、镁、铵、硼等主要共存离子及离子间交互作用对锂分析的影响规律,考察了各干扰元素的显著性程度。研究表明,钙、锶、镁、钠以及钙*硼在锂测定分析过程中存在显著干扰,其显著性从大到小排序为钙>锶>镁>钙*硼>钠。针对钙、锶、镁、钙*硼干扰,可加入消电离剂进行沉淀消除,通过比较分析,草酸钾作为消电离剂加入的除干扰效果最佳,锂测定相对误差从-20.75%降低至-12.15%;对于样品中的钠干扰,运用响应曲面实验设计,拟合方程建立干扰模型,通过方差分析及拟合度分析,回归方程各项p值均为0.000,方程的R-sq, R-sq(调整)与R-sq(预测)分别为99.96%, 99.96%以及99.95%,表明所建立的模型及方程各项显著,且回归方程拟合度较好。实验以各蒸发浓缩阶段的南翼山实际卤水与西藏龙木错实际卤水为样品,对消电离剂和干扰模型进行实验验证。结果显示,加入草酸钾消电离剂后,锂加标回收率在89.30%~98.60%之间;使用钠干扰模型校正后,锂加标回收率可提升至98.88%~101.40%,表明锂测定的准确度得到大幅提高。该方法不仅适用于南翼山油田卤水分离的整个过程,也同样适用于其他盐湖卤水,可以为盐湖企业锂元素的准确测定提供技术支持。展开更多
Automotive torque converters have recently been designed with an increasingly narrower profile for the purpose of achieving a smaller axial size and reducing weight. Design of experiment(DOE) and computational fluid d...Automotive torque converters have recently been designed with an increasingly narrower profile for the purpose of achieving a smaller axial size and reducing weight. Design of experiment(DOE) and computational fluid dynamics(CFD) techniques are applied to improve the performance of a flat torque converter. Four torque converters with different flatness ratios(0.204, 0.186, 0.172, and 0.158) are designed and simulated first to investigate the effects of flatness ratio on their overall performance, including efficiency, torque ratio, and impeller torque factor. The simulation results show that the overall performance tends to deteriorate as the flatness ratio decreases. Then a parametric study covering six geometric parameters, namely, inlet and outlet angles of impeller, turbine, and stator is carried out. The results demonstrate that the inlet and outlet angles play an important role in determining the performance characteristics of a torque converter. Furthermore, the relative importance of the six design parameters is investigated using DOE method for each response(stall torque ratio and peak efficiency). The turbine outlet angle is found to exert the greatest influence on both responses. After DOE analysis, an optimized design for the flat torque converter geometry is obtained. Compared to the conventional product, the width of the optimized flat torque converter torus is reduced by about 20% while the values of stall torque ratio and peak efficiency are only decreased by 0.4% and 1.7%, respectively.The proposed new optimization strategy based on DOE method together with desirability function approach can be used for performance enhancement in the design process of flat torque converters.展开更多
The sample preparation of samples conlaining bovine serum albumin（BSA）,e.g..as used in transdermal Franz diffusion cell（FDC） solutions,was evaluated using an analytical qualily-by-design（QbD）approach.Traditional...The sample preparation of samples conlaining bovine serum albumin（BSA）,e.g..as used in transdermal Franz diffusion cell（FDC） solutions,was evaluated using an analytical qualily-by-design（QbD）approach.Traditional precipitation of BSA by adding an equal volume of organic solvent,often successfully used with conventional HPLC-PDA,was found insufficiently robust when novel fused-core HPLC and/or UPLC-MS methods were used.In this study,three factors（acetonitrile（%）.formic acid（%） and boiling time（min）） were included in the experimental design to determine an optimal and more suitable sample treatment of BSAcontaining FDC solutions.Using a QbD and Derringer desirability（D） approach,combining BSA loss,dilution factor and variability,we constructed an optimal working space with the edge of failure defined as D〈0.9.The design space is modelled and is confirmed to have an ACN range of 83 ± 3% and FA content of 1 ±0.25%.展开更多
In this paper,size and shape optimization problem of a machine gun system is addressed with an efficient hybrid method,in which a novel and flexible mesh morphing technique is employed to achieve fast parameterization...In this paper,size and shape optimization problem of a machine gun system is addressed with an efficient hybrid method,in which a novel and flexible mesh morphing technique is employed to achieve fast parameterization and modification of complexity structure without going back to CAD for reconstruction of geometric models or to finite element analysis（ FEA） for remodeling. Design of experiments（ DOE） and response surface method（ RSM） are applied to approximate the constitutive parameters of a machine gun system based on experimental tests. Further FEA,secondary development technique and genetic algorithm（ GA） are introduced to find all the optimal solutions in one go and the optimal design of the demonstrated machine gun system is obtained. Results of the rigid-flexible coupling dynamic analysis and exterior ballistics calculation validate the proposed methodology,which is relatively time-saving,reliable and has the potential to solve similar problems.展开更多
Simulation and optimization are the key points of virtual product development (VPD). Traditional engineering simulation software and optimization methods are inadequate to analyze the optimization problems because of ...Simulation and optimization are the key points of virtual product development (VPD). Traditional engineering simulation software and optimization methods are inadequate to analyze the optimization problems because of its computational inefficiency. A systematic design optimization strategy by using statistical methods and mathematical optimization technologies is proposed. This method extends the design of experiments (DOE) and the simulation metamodel technologies. Metamodels are built to in place of detailed simulation codes based on effectively DOE, and then be linked to optimization routines for fast analysis, or serve as a bridge for integrating simulation software across different domains. A design optimization of composite material structure is used to demonstrate the newly introduced methodology.展开更多
The use of Live, Virtual and Constructive (LVC) simulations are increasingly being examined for potential analytical use particularly in test and evaluation. In addition to system-focused tests, LVC simulations provid...The use of Live, Virtual and Constructive (LVC) simulations are increasingly being examined for potential analytical use particularly in test and evaluation. In addition to system-focused tests, LVC simulations provide a mechanism for conducting joint mission testing and system of systems testing when fiscal and resource limitations prevent the accumulation of the necessary density and diversity of assets required for these complex and comprehensive tests. LVC simulations consist of a set of entities that interact with each other within a situated environment (i.e., world) each of which is represented by a mixture of computer-based models, real people and real physical assets. The physical assets often consist of geographically dispersed test assets which are interconnected by persistent networks and augmented by virtual and constructive entities to create the joint test environment under evaluation. LVC experiments are generally not statistically designed, but really should be. Experimental design methods are discussed followed by additional design considerations when planning experiments for LVC. Some useful experimental designs are proposed and a case study is presented to illustrate the benefits of using statistical experimental design methods for LVC experiments. The case study only covers the planning portion of experimental design. The results will be presented in a subsequent paper.展开更多
Surface coating is a critical procedure in the case of maintenance engineering. Ceramic coating of the wear areas is of the best practice which substantially enhances the Mean Time between Failure (MTBF). EN24 is a co...Surface coating is a critical procedure in the case of maintenance engineering. Ceramic coating of the wear areas is of the best practice which substantially enhances the Mean Time between Failure (MTBF). EN24 is a commercial grade alloy which is used for various industrial applications like sleeves, nuts, bolts, shafts, etc. EN24 is having comparatively low corrosion resistance, and ceramic coating of the wear and corroding areas of such parts is a best followed practice which highly improves the frequent failures. The coating quality mainly depends on the coating thickness, surface roughness and coating hardness which finally decides the operability. This paper describes an experimental investigation to effectively optimize the Atmospheric Plasma Spray process input parameters of Al<sub>2</sub>O<sub>3</sub>-40% TiO<sub>2</sub> coatings to get the best quality of coating on EN24 alloy steel substrate. The experiments are conducted with an Orthogonal Array (OA) design of experiments (DoE). In the current experiment, critical input parameters are considered and some of the vital output parameters are monitored accordingly and separate mathematical models are generated using regression analysis. The Analytic Hierarchy Process (AHP) method is used to generate weights for the individual objective functions and based on that, a combined objective function is made. An advanced optimization method, Teaching-Learning-Based Optimization algorithm (TLBO), is practically utilized to the combined objective function to optimize the values of input parameters to get the best output parameters. Confirmation tests are also conducted and their output results are compared with predicted values obtained through mathematical models. The dominating effects of Al<sub>2</sub>O<sub>3</sub>-40% TiO<sub>2</sub> spray parameters on output parameters: surface roughness, coating thickness and coating hardness are discussed in detail. It is concluded that the input parameters variation directly affects the characteristics of output parameters and any number of input as well as output parameters can be easily optimized using the current approach.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
In the present study,a response optimization method using Extreme Vertices Mixer Design(EVMD)approach is proposed for stress optimization in a thermomechanically processed Mg-Li-Al alloy.Experimentation was planned as...In the present study,a response optimization method using Extreme Vertices Mixer Design(EVMD)approach is proposed for stress optimization in a thermomechanically processed Mg-Li-Al alloy.Experimentation was planned as per mixed design proportions of Mg,Li and Al and process variables(i.e.temperature and strain rate).Each experiment has been performed under different conditions of factors proportions and process variables.The response,particularly stress has been considered for each experiment.The response is optimized to find an optimum condition when the contributing factors influence material characteristics in such a way,to achieve better strength,ductility and corrosion resistance.Estimated regression coefficient table for response has been observed to identify the important factors in this process and significantly high variance inflation factor has been observed.Most importantly,an optimum condition is achieved from this analysis which fulfills the experimental observations and theoretical assumptions.展开更多
文摘Identification of process parameters,their effects and contributions to the outcomes of the system using experimental approach could be a daunting,time consuming,and costly course.Using proper statistical methods,i.e.,Taguchi method,could significantly reduce the number of required experiments and statistical significance of the parameter can be identified.Friction stir welding is one of those welding techniques with many parameters which have different effects on the quality of the welds.In friction stir welding the tool rotational speed(RPM)and transverse speed(mm/min)influence the strength(i.e.,hardness distribution)of the stirred zone.In this study,these two factors are investigated to determine the effect they will have on the hardness in the stirred zone of the friction stir welds and how the two factors are related to one another for as-cast magnesium alloy AM60 with nominal chemical composition of Mg-(5.5-6.5)Al-(0.24-0.6)Mn-0.22Zn-0.1Si.Experimental data was taken at three different tool rotational speeds and three different transverse speeds.The data obtained was then analyzed using a 32 factorial design to find the contribution of these parameters.It was determined that both tool rotational speed and transverse speed possess significant effects on the stir zone hardness.Also,the interactions between the two factors were statistically assessed.
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.
基金This research was funded by the Faculty of Engineering,King Mongkut’s University of Technology North Bangkok.Contract No.ENG-NEW-66-39.
文摘This research introduces a novel approach to enhancing bucket elevator design and operation through the integration of discrete element method(DEM)simulation,design of experiments(DOE),and metaheuristic optimization algorithms.Specifically,the study employs the firefly algorithm(FA),a metaheuristic optimization technique,to optimize bucket elevator parameters for maximizing transport mass and mass flow rate discharge of granular materials under specified working conditions.The experimental methodology involves several key steps:screening experiments to identify significant factors affecting bucket elevator operation,central composite design(CCD)experiments to further explore these factors,and response surface methodology(RSM)to create predictive models for transport mass and mass flow rate discharge.The FA algorithm is then applied to optimize these models,and the results are validated through simulation and empirical experiments.The study validates the optimized parameters through simulation and empirical experiments,comparing results with DEM simulation.The outcomes demonstrate the effectiveness of the FA algorithm in identifying optimal bucket parameters,showcasing less than 10%and 15%deviation for transport mass and mass flow rate discharge,respectively,between predicted and actual values.Overall,this research provides insights into the critical factors influencing bucket elevator operation and offers a systematic methodology for optimizing bucket parameters,contributing to more efficient material handling in various industrial applications.
文摘柴达木盆地西部地区的南翼山油田卤水锂资源丰富,共存元素复杂,传统的火焰原子吸收光谱法在测定该体系中锂含量时,基体干扰严重。而且油田卤水在各蒸发浓缩阶段的离子浓度变化幅度较大,一般的基体匹配法繁琐不便。研究采用Design of Experiments(DOE)实验设计,通过干扰元素的显著性分析、消电离剂的选择及干扰模型的建立,对传统的火焰原子吸收测定锂的分析方法进行了优化。运用部分因子实验设计研究了南翼山油田卤水中钙、锶、钾、钠、镁、铵、硼等主要共存离子及离子间交互作用对锂分析的影响规律,考察了各干扰元素的显著性程度。研究表明,钙、锶、镁、钠以及钙*硼在锂测定分析过程中存在显著干扰,其显著性从大到小排序为钙>锶>镁>钙*硼>钠。针对钙、锶、镁、钙*硼干扰,可加入消电离剂进行沉淀消除,通过比较分析,草酸钾作为消电离剂加入的除干扰效果最佳,锂测定相对误差从-20.75%降低至-12.15%;对于样品中的钠干扰,运用响应曲面实验设计,拟合方程建立干扰模型,通过方差分析及拟合度分析,回归方程各项p值均为0.000,方程的R-sq, R-sq(调整)与R-sq(预测)分别为99.96%, 99.96%以及99.95%,表明所建立的模型及方程各项显著,且回归方程拟合度较好。实验以各蒸发浓缩阶段的南翼山实际卤水与西藏龙木错实际卤水为样品,对消电离剂和干扰模型进行实验验证。结果显示,加入草酸钾消电离剂后,锂加标回收率在89.30%~98.60%之间;使用钠干扰模型校正后,锂加标回收率可提升至98.88%~101.40%,表明锂测定的准确度得到大幅提高。该方法不仅适用于南翼山油田卤水分离的整个过程,也同样适用于其他盐湖卤水,可以为盐湖企业锂元素的准确测定提供技术支持。
基金Supported by National Natural Science Foundation of China(Grant No.51575393)
文摘Automotive torque converters have recently been designed with an increasingly narrower profile for the purpose of achieving a smaller axial size and reducing weight. Design of experiment(DOE) and computational fluid dynamics(CFD) techniques are applied to improve the performance of a flat torque converter. Four torque converters with different flatness ratios(0.204, 0.186, 0.172, and 0.158) are designed and simulated first to investigate the effects of flatness ratio on their overall performance, including efficiency, torque ratio, and impeller torque factor. The simulation results show that the overall performance tends to deteriorate as the flatness ratio decreases. Then a parametric study covering six geometric parameters, namely, inlet and outlet angles of impeller, turbine, and stator is carried out. The results demonstrate that the inlet and outlet angles play an important role in determining the performance characteristics of a torque converter. Furthermore, the relative importance of the six design parameters is investigated using DOE method for each response(stall torque ratio and peak efficiency). The turbine outlet angle is found to exert the greatest influence on both responses. After DOE analysis, an optimized design for the flat torque converter geometry is obtained. Compared to the conventional product, the width of the optimized flat torque converter torus is reduced by about 20% while the values of stall torque ratio and peak efficiency are only decreased by 0.4% and 1.7%, respectively.The proposed new optimization strategy based on DOE method together with desirability function approach can be used for performance enhancement in the design process of flat torque converters.
基金the Special Research Fund of Ghent University(BOF 01D23812 to Lien Taevernier and BOF O1J22510 to Evelien Wynendaele and Professor Bart De Spiegeleer)the Institute for the Promotion of Innovation through Science and Technology in Flanders(IWT 101529 to Matthias D'Hondt)for their financial funding
文摘The sample preparation of samples conlaining bovine serum albumin（BSA）,e.g..as used in transdermal Franz diffusion cell（FDC） solutions,was evaluated using an analytical qualily-by-design（QbD）approach.Traditional precipitation of BSA by adding an equal volume of organic solvent,often successfully used with conventional HPLC-PDA,was found insufficiently robust when novel fused-core HPLC and/or UPLC-MS methods were used.In this study,three factors（acetonitrile（%）.formic acid（%） and boiling time（min）） were included in the experimental design to determine an optimal and more suitable sample treatment of BSAcontaining FDC solutions.Using a QbD and Derringer desirability（D） approach,combining BSA loss,dilution factor and variability,we constructed an optimal working space with the edge of failure defined as D〈0.9.The design space is modelled and is confirmed to have an ACN range of 83 ± 3% and FA content of 1 ±0.25%.
基金Supported by the National Natural Science Foundation of China(51376090,51676099)
文摘In this paper,size and shape optimization problem of a machine gun system is addressed with an efficient hybrid method,in which a novel and flexible mesh morphing technique is employed to achieve fast parameterization and modification of complexity structure without going back to CAD for reconstruction of geometric models or to finite element analysis（ FEA） for remodeling. Design of experiments（ DOE） and response surface method（ RSM） are applied to approximate the constitutive parameters of a machine gun system based on experimental tests. Further FEA,secondary development technique and genetic algorithm（ GA） are introduced to find all the optimal solutions in one go and the optimal design of the demonstrated machine gun system is obtained. Results of the rigid-flexible coupling dynamic analysis and exterior ballistics calculation validate the proposed methodology,which is relatively time-saving,reliable and has the potential to solve similar problems.
文摘Simulation and optimization are the key points of virtual product development (VPD). Traditional engineering simulation software and optimization methods are inadequate to analyze the optimization problems because of its computational inefficiency. A systematic design optimization strategy by using statistical methods and mathematical optimization technologies is proposed. This method extends the design of experiments (DOE) and the simulation metamodel technologies. Metamodels are built to in place of detailed simulation codes based on effectively DOE, and then be linked to optimization routines for fast analysis, or serve as a bridge for integrating simulation software across different domains. A design optimization of composite material structure is used to demonstrate the newly introduced methodology.
文摘The use of Live, Virtual and Constructive (LVC) simulations are increasingly being examined for potential analytical use particularly in test and evaluation. In addition to system-focused tests, LVC simulations provide a mechanism for conducting joint mission testing and system of systems testing when fiscal and resource limitations prevent the accumulation of the necessary density and diversity of assets required for these complex and comprehensive tests. LVC simulations consist of a set of entities that interact with each other within a situated environment (i.e., world) each of which is represented by a mixture of computer-based models, real people and real physical assets. The physical assets often consist of geographically dispersed test assets which are interconnected by persistent networks and augmented by virtual and constructive entities to create the joint test environment under evaluation. LVC experiments are generally not statistically designed, but really should be. Experimental design methods are discussed followed by additional design considerations when planning experiments for LVC. Some useful experimental designs are proposed and a case study is presented to illustrate the benefits of using statistical experimental design methods for LVC experiments. The case study only covers the planning portion of experimental design. The results will be presented in a subsequent paper.
文摘Surface coating is a critical procedure in the case of maintenance engineering. Ceramic coating of the wear areas is of the best practice which substantially enhances the Mean Time between Failure (MTBF). EN24 is a commercial grade alloy which is used for various industrial applications like sleeves, nuts, bolts, shafts, etc. EN24 is having comparatively low corrosion resistance, and ceramic coating of the wear and corroding areas of such parts is a best followed practice which highly improves the frequent failures. The coating quality mainly depends on the coating thickness, surface roughness and coating hardness which finally decides the operability. This paper describes an experimental investigation to effectively optimize the Atmospheric Plasma Spray process input parameters of Al<sub>2</sub>O<sub>3</sub>-40% TiO<sub>2</sub> coatings to get the best quality of coating on EN24 alloy steel substrate. The experiments are conducted with an Orthogonal Array (OA) design of experiments (DoE). In the current experiment, critical input parameters are considered and some of the vital output parameters are monitored accordingly and separate mathematical models are generated using regression analysis. The Analytic Hierarchy Process (AHP) method is used to generate weights for the individual objective functions and based on that, a combined objective function is made. An advanced optimization method, Teaching-Learning-Based Optimization algorithm (TLBO), is practically utilized to the combined objective function to optimize the values of input parameters to get the best output parameters. Confirmation tests are also conducted and their output results are compared with predicted values obtained through mathematical models. The dominating effects of Al<sub>2</sub>O<sub>3</sub>-40% TiO<sub>2</sub> spray parameters on output parameters: surface roughness, coating thickness and coating hardness are discussed in detail. It is concluded that the input parameters variation directly affects the characteristics of output parameters and any number of input as well as output parameters can be easily optimized using the current approach.
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.
文摘In the present study,a response optimization method using Extreme Vertices Mixer Design(EVMD)approach is proposed for stress optimization in a thermomechanically processed Mg-Li-Al alloy.Experimentation was planned as per mixed design proportions of Mg,Li and Al and process variables(i.e.temperature and strain rate).Each experiment has been performed under different conditions of factors proportions and process variables.The response,particularly stress has been considered for each experiment.The response is optimized to find an optimum condition when the contributing factors influence material characteristics in such a way,to achieve better strength,ductility and corrosion resistance.Estimated regression coefficient table for response has been observed to identify the important factors in this process and significantly high variance inflation factor has been observed.Most importantly,an optimum condition is achieved from this analysis which fulfills the experimental observations and theoretical assumptions.
