Optimal Experiment Design for the Identification of the Interfacial Heat Transfer Coefficient in Sand Casting

The interfacial heat transfer coefficient(IHTC)is one of the main input parameters required by casting simulation software.It plays an important role in the accurate modeling of the solidification process.However,its value is not easily identifiable by means of experimental methods requiring temperature measurements during the solidification process itself.For these reasons,an optimal experiment design was performed in this study to determine the optimal position for the temperature measurement and the optimal thickness of the rectangular cast iron part.This parameter was identified using an inverse technique.In particular,two different algorithms were used:Levenberg Marquard(LM)and Monte Carlo(MC).A numerical model of the solidification process was associated with the optimization algorithm.The temperature was measured at different positions from the mould/metal interface at d=0 mm(mould/metal interface),30 mm,60 mm and 90 mm.the thicknesses of the cast part were:L1=40 mm,60 mm and 80 mm.A comparative study on the IHTC identification was then carried out by varying the initial value of the IHTC between 500 Wm^(-2)K^(-1) and 1050 Wm^(-2)K^(-1).Results showed that the MC algorithm used for estimating the IHTC gives the best results,and the optimal position was at d=30 mm,the position closest to the mould/metal interface,for the lowest thickness L1=40 mm.

Orthogonal experiment design of EMI of security monitoring system in coal mines

Security monitoring system of coal mines is indispensable to ensure the safe and efficient production of colliery. Due to the special and narrow underground field of the coal mine, the electromagnetic interference can cause a series of misstatements and false positives on the monitoring system, which will severely hamper the safe production of coal industry. In this paper, first, the frequency characteristics of the interference source on the power line are extracted when equipment runs normally. Then the finite difference time domain method is introduced to analyze the effects of the electromagnetic interference parameters on the security monitoring signal line. And the interference voltage of the two terminal sides on the single line is taken as evaluating indexes. Finally, the electromagnetic interference parameters are optimized by orthogonal experimental design based on the MATLAB simulation on the normal operation of equipment.

Investigation of the optimum differential gear ratio for real driving cycles by experiment design and genetic algorithm

Experiment statistical method and genetic algorithms based optimization method are used to obtain the optimum differential gear ratio for heavy truck that provides best fuel consumption when changing the working condition that affects its torque and speed range. The aim of the study is to obtain the optimum differential gear ratio with fast and accurate optimization calculation without affecting drivability characteristics of the vehicle according to certain driving cycles that represent the new working conditions of the truck. The study is carried on a mining dump truck YT3621 with 9 for- ward shift manual transmission. Two loading conditions, no load and 40 t, and four on road real driving cycles have been discussed. The truck powertrain is modeled using GT-drive, and DOE -post processing tool of the GT-suite is used for DOE analysis and genetic algorithm optimization.

Experiment Design for the Location-Allocation Problem

The allocation of facilities and customers is a key problem in the design of supply chains of companies. In this paper, this issue is approached by partitioning the territory in areas where the distribution points are allocated. The demand is modelled through a set of continuous functions based on the population density of the geographic units of the territory. Because the partitioning problem is NP hard, it is necessary to use heuristic methods to obtain reliable solutions in terms of quality and response time. The Neighborhood Variable Search and Simulated Annealing heuristics have been selected for the study because of their proven efficiency in difficult combinatorial optimization problems. The execution time is the variable chosen for a factorial experimental design to determine the best-performing heuristics in the problem. In order to compare the quality of the solutions in the territorial partition, we have chosen the execution time as the common parameter to compare the two heuristics. At this point, we have developed a factorial statistical experimental design to select the best heuristic approaches to this problem. Thus, we generate a territorial partition with the best performing heuristics for this problem and proceed to the application of the location-allocation model, where the demand is modelled by a set of continuous functions based on the population density of the geographical units of the territory.

Virtual Simulation Experiment Design under the Guidance of Emotional Design Theory

In recent years, virtual simulation experiments have been widely used in education. However, at present, academic research on virtual simulation experiments mostly focuses on key technologies, and there are few emotional studies on virtual experiments. Based on the three-layer model of emotional design theory, this paper puts forward the method strategy of emotional simulation design in virtual simulation experiment, in order to provide some reference value for the design of virtual simulation experiment.

A Mixed-Variable Experimental Design Method

Mixed-variable problems are inevitable in engineering. However, few researches pay attention to discrete variables. This paper proposed a mixed-variable experimental design method (ODCD): first, the design variables were divided into discrete variables and continuous variables;then, the DVD method was employed for handling discrete variables, the LHD method was applied for continuous variables, and finally, a Columnwise-Pairwise Algorithm was used for the overall optimization of the design matrix. Experimental results demonstrated that the ODCD method outperforms in terms of the sample space coverage performance.

Designing an Experimental Device for Swinging Excitation Spray Cooling

In this paper,we introduce the design principle of the oscillating excited spray cooling experimental device.We then designed an oscillating excited spray cooling experimental device.By using the device,the swaying motion can be realized through the control system,and the motion of the droplet under different vibration frequencies can be observed.By measuring the liquid flow rate and pressure,the changes in liquid flow rate,pressure,and temperature with time under different vibration frequencies were studied.The trajectory of the droplet and the temperature distribution of the droplet under different vibration frequencies could be observed.The device has a simple structure,is easy to control,and can achieve continuous observation of the spray cooling process.

An adaptive sequential experiment design method for model validation

Efficient experiment design is of great significance for the validation of simulation model with high nonlinearity and large input space.Excessive validation experiment raises the cost while insufficient test increases the risks of accepting an invalid model.In this paper,an adaptive sequential experiment design method combining global exploration criterion and local exploitation criterion is proposed.The exploration criterion utilizes discrepancy metric to improve the space-filling property of the design points while the exploitation criterion employs the leave one out error to discover informative points.To avoid the clustering of samples in the local region,an adaptive weight updating approach is provided to maintain the balance between exploration and exploitation.Besides,the credibility distribution function characterizing the relationship between the input and result credibility is introduced to support the model validation experiment design.Finally,six benchmark problems and an engineering case are applied to examine the performance of the proposed method.The experiments indicate that the proposed method achieves satisfactory performance for function approximation in accuracy and convergence.

HIT-SEDAES: An integrated software environment for simulation experiment design, analysis and evaluation

Simulation is a powerful technique in evaluating and improving the performance of complex systems.In order to improve the efficiency of simulation experiment design,analysis and evaluation,auxiliary tools are required.Unfortunately,existing tools are usually not meeting the requirements of simulation.Moreover,the restricted interfaces,reusability and expandability influence their efficiency to a certain extent.In this paper,an integrated software environment,HIT-SEDAES,is designed for solving these problems.A process model of simulation experiment design,analysis and evaluation is introduced to guide the development of the software environment.And several solutions are proposed to solve key problems in this development.Finally,an application is used to illustrate how the software environment works for the problems of model validation,effectiveness evaluation and performance analysis.

Design of Calibration Experiments for Identification of Manipulator Elastostatic Parameters

The paper is devoted to the elastostatic calibration of industrial robots, which is used for precise machining of large-dimensional parts made of composite materials. In this technological process, the interaction between the robot and the workpiece causes essential elastic deflections of the manipulator components that should be compensated by the robot controller using relevant elastostatic model of this mechanism. To estimate parameters of this model, an advanced calibration technique is applied that is based on the non-linear experiment design theory, which is adopted for this particular application. In contrast to previous works, it is proposed a concept of the user-defined test-pose, which is used to evaluate the calibration experiments quality. In the frame of this concept, the related optimization problem is defined and numerical routines are developed, which allow generating optimal set of manipulator configurations and corresponding forces/torques for a given number of the calibration experiments. Some specific kinematic constraints are also taken into account, which insure feasibility of calibration experiments for the obtained configurations and allow avoiding collision between the robotic manipulator and the measurement equipment. The efficiency of the developed technique is illustrated by an application example that deals with elastostatic calibration of the serial manipulator used for robot-based machining.

Control-Relevant Identification Test Design for Open-Loop Experiment

An optimal experiment design (DED) with respect to the use of designing model-base controller was studied. The mean squared error at the setpoint is chosen as the performance criterion. Simple design formulas are derived based on the asymptotic theory. The signal is used for the open loop experiment. The design constraint is the power of the process signal or the process input signal. The results give guideline for identification application.

Combinatorial pooled sequencing： experiment design and decoding

Owing to rapid advances in the next-generation sequencing technology, the cost of DNA sequencing has been reduced by over several orders of magnitude. However, genomic sequencing of individuals at the population scale is still restricted to a few model species due to the huge challenge of constructing libraries for thousands of samples. Meanwhile, pooled sequencing provides a cost-effective alternative to sequencing individuals separately, which could vastly reduce the time and cost for DNA library preparation. Technological improvements, together with the broad range of biological research questions that require large sample sizes, mean that pooled sequencing will continue to complement the sequencing of individual genomes and become increasingly important in the foreseeable future. However, simply mixing samples together for sequencing makes it impossible to identify reads that belongs to each sample. Barcoding technology could help to solve this problem, nonetheless, currently, barcoding every sample is costly especially for large-scale samples. An alternative to barcoding is combinatorial pooled sequencing which employs pooling pattern rather than short DNA barcodes to encode each sample. In combinatorial pooled sequencing, samples are mixed into few pools according to a carefully designed pooling strategy which allows the sequencing data to be decoded to identify the reads that belongs to the sample that are unique or rare in the population. In this review, we mainly survey the experiment design and decoding procedure for the combinatorial pooled sequencing applied in rare variant and rare haplotype carriers screening, complex genome assembling and single individual haplotyping.

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.

Cavitation Optimization for a Centrifugal Pump Impeller by Using Orthogonal Design of Experiment

Cavitation is one of the most important performance of centrifugal pumps. However, the current optimization works of centrifugal pump are mostly focusing on hydraulic efficiency only, which may result in poor cavitation performance. Therefore, it is necessary to find an appropriate solution to improve cavitation performance with acceptable efficiency. In this paper, to improve the cavitation performance of a centrifugal pump with a vaned diffuser, the influence of impeller geometric parameters on the cavitation of the pump is investigated using the orthogonal design of experiment （DOE） based on computational fluid dynamics. The impeller inlet diameter D1, inlet incidence angle Aft, and blade wrap angle ~0 are selected as the main impeller geometric parameters and the orthogonal experiment of L9（3＂3） is performed. Three-dimensional steady simulations for cavitation are conducted by using constant gas mass fraction model with second-order upwind, and the predicated cavitation performance is validated by laboratory experiment. The optimization results are obtained by the range analysis method to improve cavitation performance without obvious decreasing the efficiency of the centrifugal pump. The internal flow of the pump is analyzed in order to identify the flow behavior that can affect cavitation performance. The results show that D1 has the greatest influence on the pump cavitation and the final optimized impeller provides better flow distribution at blade leading edge. The final optimized impeller accomplishes better cavitation and hydraulic performance and the NPSHR decreases by 0.63m compared with the original one. The presented work supplies a feasible route in engineering practice to optimize a centrifugal pump impeller for better cavitation performance.

Study on solder joint reliability of ceramic ball grid array component based on design of experiment method

Four process parameters, pad diameter, stencil thickness, ball diameter and stand-off were chosen as four control factors. By using an L25 （5^6 ） orthogonal array the ceramic ball grid array （ CBGA ） solder joints which have 25 different combinations of process parameters were designed. The numerical models of all the 25 CBGA solder joints were developed using the Sugrace Evolver. Utilizing the sugrace coordinate exported from the 25 CBGA solder joints numerical models, the finite element analysis models were set up and the nonlinear finite element analysis of the CBGA solder joints under thermal cycles were pegrormed by ANSYS. The thermal fatigue life of CBGA solder joint was calculated using Coffin-Manson equation. Based on the calculated thermal fatigue life results, the range analysis and the variance analysis were pegrormed. The results show that the fatigue life of CBGA solder joint is affected by the pad diameter, the stencil thickness, the ball diameter and the stand-off in a descending order, the best combination of process parameters results in the longest fatigue life is 0.07 mm stand-off, 0.125 mm stencil thickness of, 0.85 mm ball diameter and 0. 89 mm pad diameter. With 95% confidence the pad diameter has a significant effect on the reliability of CBGA solder joints whereas the stand-off, the stencil thickness and the ball diameter have little effect on the reliability of CBGA solder joints.

Optimization of rheological parameter for micro-bubble drilling fluids by multiple regression experimental design

In order to optimize plastic viscosity of 18 mPa·s circulating micro-bubble drilling fluid formula,orthogonal and uniform experimental design methods were applied,and the plastic viscosities of 36 and 24 groups of agent were tested,respectively.It is found that these two experimental design methods show drawbacks,that is,the amount of agent is difficult to determine,and the results are not fully optimized.Therefore,multiple regression experimental method was used to design experimental formula.By randomly selecting arbitrary agent with the amount within the recommended range,17 groups of drilling fluid formula were designed,and the plastic viscosity of each experiment formula was measured.Set plastic viscosity as the objective function,through multiple regressions,then quadratic regression model is obtained,whose correlation coefficient meets the requirement.Set target values of plastic viscosity to be 18,20 and 22 mPa·s,respectively,with the trial method,5 drilling fluid formulas are obtained with accuracy of 0.000 3,0.000 1 and 0.000 3.Arbitrarily select target value of each of the two groups under the formula for experimental verification of drilling fluid,then the measurement errors between theoretical and tested plastic viscosity are less than 5%,confirming that regression model can be applied to optimizing the circulating of plastic-foam drilling fluid viscosity.In accordance with the precision of different formulations of drilling fluid for other constraints,the methods result in the optimization of the circulating micro-bubble drilling fluid parameters.

Application of experimental design in optimization of crude oil adsorption from saline waste water using raw bagasse

Experimental design was applied in the optimization of crude oil adsorption from saline waste water using raw bagasse.The application of response surface methodology(RSM) was presented with temperature,salinity of water,pH,adsorbent dose,and initial oil content as factors.A quadratic model could be used to approximate the mathematical relationship of crude oil removal on the five significant independent variables.Predicted values and experimental values are found to be in good agreement with R2 of 97.44%.The result of optimization shows that the maximum crude oil removal is equal to 67.38% under the optimal condition of temperature of 46.53 °C,salinity of 37.2 g/L,pH of 3,adsorbent dose of 9 g/L and initial oil content of 300×10-6.

Hydrogen-based direct reduction of industrial iron ore pellets:Statistically designed experiments and computational simulation

As part of efforts to reduce anthropogenic CO_(2) emissions by the steelmaking industry,this study investigated the direct reduction of industrially produced hematite pellets with H_(2) using the Doehlert experimental design to evaluate the effect of pellet diameter(10.5-16.5 mm),porosity(0.36-0.44),and temperature(600-1200℃).A strong interactive effect between temperature and pellet size was observed,indicating that these variables cannot be considered independently.The increase in temperature and decrease in pellet size considerably favor the reduction rate,while porosity did not show a relevant effect.The change in pellet size during the reduction was negligible,except at elevated temperatures due to crack formation.A considerable decrease in mechanical strength at high temperatures suggests a maximum process operating temperature of 900℃.Good predictive capacity was achieved using the modified grain model to simulate the three consecutive non-catalytic gas-solid reactions,considering different pellet sizes and porosities,changes during the reaction from 800 to 900℃.However,for other temperatures,different mechanisms of structural modifications must be considered in the modeling.These results represent significant contributions to the development of ore pellets for CO_(2)-free steelmaking technology.

An iterated local coordinate-exchange algorithm for constructing experimental designs for multi-dimensional constrained spaces

Iterated local search(ILS)is used to construct the optimal experimental designs for multi-dimensional constrained spaces,in which the inner loop is based on the stochastic coordinate-exchange(SCE)algorithm.Every time a local optimal solution is found by the SCE algorithm,the perturbation operator is applied to it,and then a new solution is explored in the areas where the exchange of coordinates may produce improvement,so as to retain the features and attributes of the current optimal solution and avoid the defects of random restart.We implement the iterated local coordinate-exchange algorithm for experimental designs in the multi-dimensional constrained spaces.In addition,sensitivity analysis was conducted to analyze the impacts of the parameters on the performance of the proposed algorithm.Also we compared the performance of the proposed algorithm to the SCE algorithm using the random restart strategy.The analysis shows that the proposed algorithm is better than the SCE algorithm in terms of efficiency and quality,especially in the experimental designs for high-dimensional constrained space.

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.