Reliability-based Robust Optimization Design of Automobile Components with Non-normal Distribution Parameters

In the reliability designing procedure of the vehicle components, when the distribution styles of the random variables are unknown or non-normal distribution, the result evaluated contains great error or even is wrong if the reliability value R is larger than 1 by using the existent method, in which case the formula is necessary to be revised. This is obviously inconvenient for programming. Combining reliability-based optimization theory, robust designing method and reliability based sensitivity analysis, a new method for reliability robust designing is proposed. Therefore the influence level of the designing parameters’ changing to the reliability of vehicle components can be obtained. The reliability sensitivity with respect to design parameters is viewed as a sub-objective function in the multi-objective optimization problem satisfying reliability constraints. Given the first four moments of basic random variables, a fourth-moment technique and the proposed optimization procedure can obtain reliability-based robust design of automobile components with non-normal distribution parameters accurately and quickly. By using the proposed method, the distribution style of the random parameters is relaxed. Therefore it is much closer to the actual reliability problems. The numerical examples indicate the following: (1) The reliability value obtained by the robust method proposed increases (】0.04%) comparing to the value obtained by the ordinary optimization algorithm; (2) The absolute value of reliability-based sensitivity decreases (】0.01%), and the robustness of the products’ quality is improved accordingly. Utilizing the reliability-based optimization and robust design method in the reliability designing procedure reduces the manufacture cost and provides the theoretical basis for the reliability and robust design of the vehicle components.

Optimal Design of Bicycle Frame Parameters Considering Biomechanics

With the development of technology and the change of market demands,the trend in middle and high grade bicycle manufacturing is developed toward small-volume,multi-species,and customer-oriented production.Therefore,human element should be fully considered in design so that the bicycle has the best cycling performance for the specific rider.Currently,customized design is difficult to achieve since feature parameters of the rider are not included in the design.The design of bicycle frame is the most important in bicycle design.The relative positions among the saddle,handlebar and central axis are defined as the bicycle three-pivot,they are the main parameters in bicycle frame design.In conventional bicycle design,frame parameters are merely relevant to bicycle types.On the basis of the principles of biomechanics and ergonomics knowledge,this paper presents a design method for bicycle three-pivot considering feature parameters of the rider by dynamic simulation.Firstly,a dynamic model of rider-bicycle system is built for a special rider,and a serial of simulation experiments is designed by uniform test method.Then,a mathematical model is built between the three-pivot position and the square of lower limb muscle stress by using simulation and regression analysis of the rider-bicycle system.The optimal three-pivot position parameters are obtained by setting the minimal of the square of the lower limb muscle stress as the objective.Therefore,the optimal parameters are gained for the specific rider.Finally,various results are gained for different riders based on the same design process.The function between feature parameters of the rider and the optimum three-pivot position parameters is built by regression.Bicycle design considering biomechanics can be divided into three main steps：calculating the three-pivot position,designing the geometrical structure of the bicycle frame and analyzing frame strength,and selecting appropriate parts and assembling the bicycle.Bicycle design considering biomechanics changes the conventional bicycle design and realizes customized design by considering human element in the design process.

Modeling Approach and Analysis of the Structural Parameters of an Inductively Coupled Plasma Etcher Based on a Regression Orthogonal Design

The geometry of an inductively coupled plasma （ICP） etcher is usually considered to be an important factor for determining both plasma and process uniformity over a large wafer. During the past few decades, these parameters were determined by the ＂trial and error＂ method, resulting in wastes of time and funds. In this paper, a new approach of regression orthogonal design with plasma simulation experiments is proposed to investigate the sensitivity of the structural parameters on the uniformity of plasma characteristics. The tool for simulating plasma is CFD-ACE＋, which is commercial multi-physical modeling software that has been proven to be accurate for plasma simulation. The simulated experimental results are analyzed to get a regression equation on three structural parameters. Through this equation, engineers can compute the uniformity of the electron number density rapidly without modeling by CFD-ACE＋. An optimization performed at the end produces good results.

Application of Uniform Experimental Design in Optimizing Excitation Parameters for Magnetic Frequency Mixing Measurements

Excitation parameter preferences are key factors a ecting the performance of magnetic frequency mixing detection.A uniform experimental design method was used to analyze this influence.Using fuzzy theory,a comprehensive model is established for evaluating the e ect of magnetic frequency mixing.A polynomial is selected as the regression function to express explicitly the correlation between the excitation parameters and the frequency-mixing e ect.The excitation parameters were then optimized using genetic algorithm.Magnetic frequency mixing experiments were conducted to measure the surface hardness of some ferromagnetic materials.Frequency mixing is further enhanced under the optimal settings,resulting in an improvement in the measurement sensitivity.The results of this study support the application of the magnetic frequency mixing technique in non-destructive testing.

Application of orthogonal experimental design and Tikhonov regularization method for the identification of parameters in the casting solidification process

The inverse heat conduction method is one of methods to identify the casting simulation parameters. A new inverse method was presented according to the Tikhonov regularization theory. One appropriate regularized functional was established, and the functional was solved by the sensitivity coefficient and Newtonaphson iteration method. Moreover, the orthogonal experimental design was used to estimate the appropriate initial value and variation domain of each variable to decrease the number of iteration and improve the identification accuracy and efficiency. It illustrated a detailed case of AlSiTMg sand mold casting and the temperature measurement experiment was done. The physical properties of sand mold and the interracial heat transfer coefficient were identified at the meantime. The results indicated that the new regularization method was efficient in overcoming the ill-posedness of the inverse heat conduction problem and improving the stability and accuracy of the solutions.

STRUCTURE PARAMETERS DESIGN AND PERFORMANCE TEST OF FUEL INJECTION SYSTEM

Based on the numerical simulation analysis, structure parameters of the high pressure fuel pump and common rail as well as flow limiter are designed and the GD-1 high pressure common rail fuel injection system is self-developed. Fuel injection characteristics experiment is performed on the GD-1 system. And double-factor variance analysis is applied to investigate the influence of the rail pressure and injection pulse width on the consistency of fuel injection quantity, thus to test whether the design of structure parameters is sound accordingly. The results of experiment and test show that rail pressure and injection pulse width as well as their mutual-effect have no influence on the injection quantity consistency, which proves that the structure parameters design is successful and performance of GD-1 system is sound.

Optimization design of resistance spot welding parameters of magnesium alloy

By means of the quadratic regression combination design process, the regression equations of nugget diameter and tensile shear load of spot welded joint were established. Effects of welding parameters on the nugget diameter and the tensile shear load were investigated. The results show that effect of welding current on nugget diameter is the most evident. And higher welding current will result in bigger nugget diameter. Besides, interaction effect of electrode force and welding current on tensile shear load is the most evident compared with others. The optimum welding parameters corresponding to the maximum of tensile shear load have been obtained by programming using Matlab software, which is 4, 7 kN electrode force, 28 kA welding current and 4 cycle welding time. Under the condition of the optimum welding parameters, the joint having no visible defects can be obtained, nugget diameter and tensile shear load being 6. 8 mm and 3 256 N, respectively.

Design of cavern blasting based on controllable parameters

After a thorough review of some controllable parameters,which included field investigations,cavern dimensions,explosive,rock strength etc.,cut,contour,lifters and stoping holes were introduced for blasting cavern of nucleus submarine.These design were conducted using a U.Langefors and B.Kihlstrom theory.

Application of Monte-Carlo statistical experiments in design of ocean engineering - Estimating the parameters, models and probabilities

Recently, some results have been acquired with the Monte- Carlo statistical experiments in the design of ocean en gineering. The results show that Monte-Carlo statistical experiments can be widely used in estimating the parameters of wave statistical distributions, checking the probability model of the long- term wave extreme value distribution under a typhoon condition and calculating the failure probability of the ocean platforms.

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.

Optimal design of the aerodynamic parameters for a supersonic two-dimensional guided artillery projectile

An optimization method is introduced to design the aerodynamic parameters of a dual-spin twodimensional guided projectile with the canards for trajectory correction. The nose guidance component contains two pairs of canards which can provide lift and despin with the projectile for stability. The optimal design algorithm is developed to decide the profiles both of the steering and spinning canards,and their deflection angles are also simulated to meet the needs of trajectory correction capabilities.Finally, the aerodynamic efficiency of the specific canards is discussed according to the CFD simulations.Results that obtained here can be further applied to the exterior ballistics design.

The Effects of Design Parameters on the Resistance of High Speed Monohull

The paper puts forward a method of predicting the calm water total resistance of the high speed displacement ship with transom stern.The hull surface is defined by mathematical function and design parameters.The effects of design parameters on the total resistance are discussed.

Influence of parental sample sizes on the estimating genetic parameters in cultured clam Meretrix meretrix based on factorial mating designs

The precise and accurate knowledge of genetic parameters is a prerequisite for making efficient selection strategies in breeding programs.A number of estimators of heritability about important economic traits in many marine mollusks are available in the literature,however very few research have evaluated about the accuracy of genetic parameters estimated with different family structures.Thus,in the present study,the effect of parent sample size for estimating the precision of genetic parameters of four growth traits in clam M.meretrix by factorial designs were analyzed through restricted maximum likelihood（REML） and Bayesian.The results showed that the average estimated heritabilities of growth traits obtained from REML were 0.23-0.32 for 9 and 16 full-sib families and 0.19-0.22 for 25 full-sib families.When using Bayesian inference,the average estimated heritabilities were0.11-0.12 for 9 and 16 full-sib families and 0.13-0.16 for 25 full-sib families.Compared with REML,Bayesian got lower heritabilities,but still remained at a medium level.When the number of parents increased from 6 to 10,the estimated heritabilities were more closed to 0.20 in REML and 0.12 in Bayesian inference.Genetic correlations among traits were positive and high and had no significant difference between different sizes of designs.The accuracies of estimated breeding values from the 9 and 16 families were less precise than those from 25 families.Our results provide a basic genetic evaluation for growth traits and should be useful for the design and operation of a practical selective breeding program in the clam M.meretrix.

Review of Design of Process Parameters for Squeeze Casting

Squeeze casting(SC)is an advanced net manufacturing process with many advantages for which the quality and properties of the manufactured parts depend strongly on the process parameters.Unfortunately,a universal efficient method for the determination of optimal process parameters is still unavailable.In view of the shortcomings and development needs of the current research methods for the setting of SC process parameters,by consulting and analyzing the recent research literature on SC process parameters and using the CiteSpace literature analysis software,manual reading and statistical analysis,the current state and characteristics of the research methods used for the determination of SC process parameters are summarized.The literature data show that the number of pub-lications in the literature related to the design of SC process parameters generally trends upward albeit with signifi-cant fluctuations.Analysis of the research focus shows that both“mechanical properties”and“microstructure”are the two main subjects in the studies of SC process parameters.With regard to materials,aluminum alloys have been extensively studied.Five methods have been used to obtain SC process parameters:Physical experiments,numeri-cal simulation,modeling optimization,formula calculation,and the use of empirical values.Physical experiments are the main research methods.The main methods for designing SC process parameters are divided into three categories:Fully experimental methods,optimization methods that involve modeling based on experimental data,and theoreti-cal calculation methods that involve establishing an analytical formula.The research characteristics and shortcomings of each method were analyzed.Numerical simulations and model-based optimization have become the new required methods.Considering the development needs and data-driven trends of the SC process,suggestions for the develop-ment of SC process parameter research have been proposed.

Design of Experiment (DoE): Implementation in Determining Optimum Design Parameters of Portable Workstation

In the modern era of manufacturing, it is important to optimize every design parameter in product development stage to reduce cost, material usage and to achieve the desired efficacy level. There are various models which serve those purposes, for instance, Design of Experiment (DoE) is used to check the parameters after adopting optimization tactics which results in reduced cost or saving operating time. In this regard, this research aims to construct a DoE model on a portable workstation to optimize its design parameters. The methodology of DOE would be a 2 level 3 factors full factorial DOE which is conducted to determine the optimal value for three design parameters (factors) which are material density, the length of the table and the length of the table stand in terms of the response which is the required time of fold ability function of the portable workstation. Based upon the evaluated interactions between the parameters, the optimized parameters are chosen for responses. Here, the resultant design parameters are at their lowest level, so the goal of time efficiency in fold ability function is achieved. This similar sort of DoE can be implemented in the furniture and other manufacturing industries who wish to optimize their material usage as well as increase efficiency and reduce cycle time.

Optimization of design parameters for controlled rocking steel braced dual-frames

A controlled rocking concentrically steel braced frame(CR-CSBF)is introduced as an alternative to conventional methods to prevent major structural damage during large earthquakes.It is equipped with elastic post-tensioned(PT)cables and replaceable devices or fuses to provide overturning resistance and dissipate energy,respectively.Although CR-CSBFs are not officially legalized in globally valid codes for new buildings,it is expected to be presented in them in the near future.The main goal of this study is to determine the optimal design parameters consist of the yield strength and modulus of elasticity of the fuse,the initial force of the PT cable,and the gravity load on the rocking column,considering different heights of the frame,spanning ratios and ground motion types for dual-configuration CR-CSBF.Nonlinear time-history analyses are performed in OpenSees.This study aims to define the optimal input variables as effective design parameters of CR-CSBFs by comparing four seismic responses consisting of story drift,roof displacement,roof acceleration and base shear,and also using the Euclidean metric optimization method.Despite the previous research,this study is innovative and first of its kind.The results demonstrate that the optimal design parameters are variable for various conditions.

Effect of the Design Parameters on the Performance of Inner-Recycling Continuous Sand Filter

A novel integrated water treatment facility, inner-recycling continuous sand filter, is discussed. The theory of micro-flocculation is applied in the sand-washing circulation system with continuous filtration and backwashing. The design and operation parameters, which affect the performance of the filter, are discussed. The key design parameters are provided as follows: diameter of filter material is 0.7 to 1.0 mm, depth of filter bed is 0.6 m, filtration velocity is less than 12 m/h, ratio of gas to water is 9:11 and sand recycling rate is 2 to 4 mm/min.

Determination of Some Design Parameters for Roller Type Seed Metering Device

There are many design parameters in precision planters to be considered such as cell diameter, peripheral speed of roller, number of cells, manner of feeding seeds into cell and travel speed. In precision planters each cell must contain only one seed. Therefore, sliding the seed to the cell is important and depends on several parameters such as seed repose angle, seed dimensions and physics of cell. To help the seed to repose in the cell, making a groove on the roller would be very useful. Dimensions of this groove are very important and are considered as basic design parameters. This research was performed to determine some design parameters such as roller speed, travel speed, length and depth of groove for tomato seeds precision planting. In this regard, seeds with a diameter of 4 mm were used. The range of variation was based on calculations obtained. A roller with 42 mm width, 118 mm diameter and 15 cells on the surface was used in the experiment. For each cell, a triangular groove was created on the roller. The groove depth varied from zero at the beginning to the maximum value where the groove connected to the cell. The test unit had a continued and wide belt with 1 l m length. In each replication, planter worked for 20 s to reach a stable state. Thereafter, seeds were allowed to drop on the grease belt. Number of seeds and their spacing were measured on the 4.5 m of the belt. Results showed that the roller speed of 41.5 rpm, the planter travel speed of approximately 1 km/h, groove length of 6-8 mm and groove depth of 1.5 mm can improve planter performance for tomato pelleted seed.

Uncertainty analysis for the calculation of marine environmental design parameters in the South China Sea

The calculation results of marine environmental design parameters obtained from different data sampling methods,model distributions,and parameter estimation methods often vary greatly.To better analyze the uncertainties in the calculation of marine environmental design parameters,a general model uncertainty assessment method is necessary.We proposed a new multivariate model uncertainty assessment method for the calculation of marine environmental design parameters.The method divides the overall model uncertainty into two categories:aleatory uncertainty and epistemic uncertainty.The aleatory uncertainty of the model is obtained by analyzing the influence of the number and the dispersion degree of samples on the information entropy of the model.The epistemic uncertainty of the model is calculated using the information entropy of the model itself and the prediction error.The advantages of this method are that it does not require many-year-observation data for the marine environmental elements,and the method can be used to analyze any specific factors that cause model uncertainty.Results show that by applying the method to the South China Sea,the aleatory uncertainty of the model increases with the number of samples and then stabilizes.A positive correlation was revealed between the dispersion of the samples and the aleatory uncertainty of the model.Both the distribution of the model and the parameter estimation results of the model have significant effects on the epistemic uncertainty of the model.When the goodness-of-fit of the model is relatively close,the best model can be selected according to the criterion of the lowest overall uncertainty of the models,which can both ensure a better model fit and avoid too much uncertainty in the model calculation results.The presented multivariate model uncertainty assessment method provides a criterion to measure the advantages and disadvantages of the marine environmental design parameter calculation model from the aspect of uncertainty,which is of great significance to analyze the uncertainties in the calculation of marine environmental design parameters and improve the accuracy of the calculation results.

A Comprehensive Review on Heat Transfer Design Parameters in MEMS through Experimentations and Numerical Modeling

Micro electro mechanical systems are studied in this paper along to comparing the design, fabrication, and operation of such devices especially in the electronic industry. The advancements of such systems are important as scale reduction is becoming more economical and also in heat dissipation efficiencies. Furthermore, the fabrication techniques are becoming more of a challenge in today’s industrial market. In this paper we will introduce a comparative study of experimental research in the micro scale heat exchanger with varieties of industrial application primarily cooling integrated circuits. Significant effect in the process of cooling electronic devices has showed experimentally that scale variations impact into this improvement. Numerical studies have been a leading technique in the development of thermal systems especially at the micro or small scales which helps the industry to cut cost and provide innovative products at high efficiencies. There are so many approaches to numerical analysis and research, where the availability of ready to use software and data acquisition modules is variant. Material selection is also a variable in the efficiency and operations of these micro channel thermal system and heat exchangers.