基于响应面近似模型的双层喷孔参数优化研究

在共轨柴油机上采用双层交错布置喷孔油嘴可以改善柴油机的经济性和排放性能。针对双层交错布置喷孔油嘴与燃烧室优化匹配问题,采用CFD软件,运用中心组合试验设计方法设计燃油系统参数的试验计算矩阵并进行数值计算;再以响应面近似模型构造燃烧和排放的优化目标函数;最后运用多岛遗传算法对该近似模型进行全局寻优,确定燃油系统参数的优化组合,并在试验台架上进行了优化方案的配机试验。结果表明:小的喷孔直径、较多的喷孔以及适当的上下层喷孔喷射夹角可提高油束的雾化质量。     

基于LSSVM-RSM的边坡可靠度研究

由于岩土体材料复杂多变,边坡稳定的功能函数往往具有高度非线性,常规的二次多项式响应面法(RSM)往往很难对其拟合。对此,利用最小二乘支持向量(LSSVM)的小样本优良的拟合能力,提出了基于LSSVM-RSM的可靠度分析方法对边坡稳定的功能函数进行拟合,并通过网格搜索法优化LSSVM参数,最后通过两个算例进行对比验证。计算结果表明,与传统二次多项式响应面法相比,该方法能更好地拟合抗剪强度参数与边坡稳定性之间的非线性关系,有效地扩展了响应面法在边坡稳定的可靠度分析中的应用。     

早期受冻损伤混凝土强度预测模型研究及其配比优化

针对严寒地区水工混凝土建筑物在浇筑施工时易受早期冻害，并可能影响后期健康服役的问题，为研究早冻混凝土强度损伤规律并对其配比进行优化，利用RSM响应面法Box-Behnken(RSM-BBD)优化试验设计，并建立以水胶比、粉煤灰掺量、引气剂掺量为变量的RSM响应面模型；同时，构建一种GA-BPNN强度预测模型，实现早冻混凝土强度的精确预测。结果表明，与RSM模型相比，GA-BPNN模型有更精确的预测性能，且能更高效地优化配比设计；GA-BPNN强度预测模型的拟合优度R²和平均相对误差e_MRE分别为0.998 5、2.13%,最优配比强度预测值与试验值的相对误差约为1%,应用该模型可实现混凝土受冻强度推演及其配比的高效优化。     

基于近似模型的共轨柴油机喷射系统参数优化研究

基于试验设计理论和响应面近似模型对高压共轨柴油机喷射系统参数进行了优化设计。对FIRE软件中的喷雾与燃烧仿真模型进行了校核与验证,得到了KH-RT喷雾破碎模型参数C2与喷嘴结构参数的关系式,提高了模型的仿真精度。运用中心复合法设计了优化参数的试验计算矩阵,利用FIRE软件进行数值计算。用响应面近似模型技术构造了以经济性为主的综合优化目标函数。利用全局优化与局部优化相结合的优化方法对该近似模型进行了寻优,得到了喷射系统参数的最优组合,大幅度减少了共轨柴油机喷射系统参数设计试验的工作量。与原机相比,经过优化的柴油机燃油消耗率降低了5%,NOx和碳烟排放分别降低了10%和18%。     

模拟退火算法在三维气动优化设计中的应用

首先对所开发的模拟退火算法进行函数验证,然后与实验设计、三维流场求解程序、二次多项式响应面近似模型结合,提出了一套省时的气动优化设计体系。应用该优化方法对跨音压气机动叶以绝热效率最大为目标进行气动优化设计,优化后叶片绝热效率提高约1.58%,并且具有良好的变工况性能。结果表明了所开发优化设计体系省时、高效的特点。     

基于网格变形法的风机翼型气动性能优化

提出了一种基于网格变形的翼型优化方法.运用该方法对风力机翼型FFA-W3-301进行了单目标和多目标优化,得到了光顺的优化翼型曲线,显著提高了翼型的升阻比.该文优化计算中采用自适应响应面算法,能得到与遗传算法相当的优化效果,而效率则明显提高.     

基于响应面法的圆盘泵叶轮优化研究

为了提高圆盘泵的水力性能,以径向直叶片圆盘泵为研究对象,结合计算流体动力学方法(CFD)与响应面分析法,研究叶轮结构参数对泵扬程和效率的影响。以叶片高度、叶片数量和盘间距为优化设计变量,泵的扬程和效率为响应变量,基于Box-Behnken样本点设计法进行三因素三水平设计,建立17组样本点。通过ANSYS CFX数值计算软件对各个样本点的设计模型进行数值模拟,并基于二阶响应面回归方程拟合了叶轮结构参数与扬程和效率之间的关系表达式。研究结果表明:叶片高度、叶片数量和盘间距均对泵的水力性能有明显的影响。多因素交互作用中叶片高度和盘间距的组合影响最为显著。通过响应面方程找到了最优参数组合,优化后的圆盘泵扬程在各流量工况下平均提升了22 m,最高效率提升了15%。     

基于响应面模型涡轮叶片冷却性能的数值研究

为了给我国自主研发涡轮叶片提供理论基础,基于试验设计和响应面模型对某型叶片的冷却性能进行了数值研究。对某型涡轮叶片的设计参数进行了试验设计,数值研究了主流出口压力、主流进出口压比、冷气与主流温度比及流量比对叶片表面的无量纲温度分布的影响规律,并根据响应面模型拟合得到了叶片平均无量纲温度的经验公式。结果表明：根据试验设计和响应面模型拟合得到的叶片平均无量纲温度的经验公式有较高的精度;在设计参数范围内,涡轮叶片的平均无量纲温度随着主流出口压力(120～140 kPa)和冷气与主流温度比(0.6～0.7)的增大分别提高了0.57%和2.81%,随着主流进出口压比(1.3～1.5)和冷气与主流流量比(3～8)的增大分别降低了1.14%和3.68%。     

地铁轴箱吊耳疲劳寿命预估与优化

针对某型地铁轴箱吊耳在服役期内发生疲劳断裂的问题,采用虚拟激励法计算吊耳的随机振动响应,应用Dirlik法和三区间法预估吊耳的疲劳寿命,预估结果与实际发生断裂时的运行里程相符.为提高吊耳的疲劳寿命,对吊耳的设计尺寸进行了优化.首先采用灵敏度分析方法确定了主要的优化变量,之后以全局响应面法对吊耳的设计尺寸进行优化,优化后...     

基于响应面法的土石坝参数随机反演分析

针对常规随机反演过程中需多次进行数值模拟与优化方法耦合存在的计算量过大的问题,提出基于响应面法的土石坝参数反演方法。在有限元分析的基础上,利用中心复合设计进行有限次试验,建立可反映土石坝参数与位移之间非线性隐式关系的响应面方程,以代替有限元计算;结合内点法及Monte-Carlo随机抽样,对响应面方程的目标函数进行迭代寻优,从而实现土石坝参数的随机反演分析。数值算例表明,该方法计算结果误差小,求解效率高;随机反演得到的参数能更准确地反映材料的真实情况,其统计特性还可用于土石坝稳定计算和风险评估。研究成果为实际土石坝工程的参数确定提供了参考。     

A new synthetic metamodel methodology for liquid‐propellant engine's cooling system optimization

The present paper strives for optimization of the cooling system of a liquid‐propellant engine (LPE). To this end, the new synthetic metamodel methodology utilizing the design of experiment method and the response surface method was developed and implemented as two effective means of designing, analyzing, and optimizing. The input variables, constraints, objective functions, and their surfaces were identified. Hence, the design and development strategy of combustion chamber and nozzle was clarified, and 64 different experiments were carried out on the RD‐161 propulsion system, of which 47 experiments were approved and compatible with the problem constraints. This engine used all three modes of cooling: the radiation cooling, the regenerative cooling, and the film cooling. The response surface curves were drawn and the related objective function equations were obtained. The analysis of variance results indicate that the developed synthetic model is capable to predict the responses adequately within the limits of input parameters. The three‐dimensional response surface curves and contour plots have been developed to find out the combined effects of input parameters on responses. In addition, the precision of the models was assessed and the output was interpreted and analyzed, which showed high accuracy. Therefore, the desirability function analysis has been applied to LPE's cooling system for multiobjective optimization to maximize the total heat transfer and minimize the cooling system pressure loss simultaneously. Finally, confirmatory tests have been conducted with the optimum parametric conditions to validate the optimization techniques. In conclusion, this methodology optimizes the LPE's cooling system, a 2% increase in the total heat transfer, and a 38% decrease in the pressure loss of the cooling system. These values are considerably large for the LPE design.     

Study on Aerodynamic Design Optimization of Turbomachinery Blades

This paper describes the study on aerodynamics design optimization of turbomachinery blading developed by the authors at the Institute of Engineering Thermophysics, Chinese Academy of Sciences, during the recent few years. The present paper describes the aspects mainly on how to use a rapid approach of profiling a 3D blading and of grid generation for computation, a fast and accurate viscous computation method and an appropriate optimization methodology including a blade parameterization algorithm to optimize turbomachinery blading aerodynamically. Any blade configuration can be expressed by three curves, they are the camber lines, the thickness distributions and the radial stacking line, and then the blade geometry can be easily parameterized by a number of parameters with three polynomials. A gradient-based parameterization analytical method and a response surface method were applied herein for blade optimization. It was found that the optimization process provides reliable design for turbomachinery with reasonable computing time.     

Optimization of biodiesel production from Annona squamosa seed oil using response surface methodology and its characterization

In the present study, Annona squamosa seed oil has been evaluated as a potential feedstock for biodiesel production. The response surface methodology was used to determine the optimal conditions for the biodiesel production using a central composite design. A quadratic polynomial was developed to predict the response as a function of independent variables and their interactions and only the significant factors affecting the yield were fitted to a second-order response surface reduced 2 factor interaction (2FI) model. Four process variables were assessed at five levels. A biodiesel yield of 98.19% was obtained at optimum conditions: 7.53:1 methanol to oil molar ratio, 1.18 wt% catalyst concentration, reaction temperature of 59.55°C, and reaction time of 47.29 min.     

Shape Optimization of Inclined Ribs as Heat Transfer Augmentation Device

This work presents numerical optimization techniques for the design of a rectangular channel with inclined ribs toenhance turbulent heat transfer.The response surface method with Reynolds-averaged Navier-Stokes analysis isused for optimization.Shear stress transport turbulence model is used as a turbulence closure.Computational re-sults for local heat transfer rate show a reasonable agreement with the experimental data.Width-to-rib height ratioand attack angle of the rib are chosen as design variables.The objective function is defined as a linear combina-tion of heat-transfer and friction-loss related terms with the weighting factor.Full-factorial experimental designmethod is used to determine the data points.Optimum shapes of the channel have been obtained in a range of theweighting factor.     

Investigation on multi-objective performance optimization algorithm application of fan based on response surface method and entropy method

A multi-objective performance optimization method is proposed,and the problem that single structural parameters of small fan balance the optimization between the static characteristics and the aerodynamic noise is solved.In this method,three structural parameters are selected as the optimization variables.Besides,the static pressure efficiency and the aerodynamic noise of the fan are regarded as the multi-objective performance.Furthermore,the response surface method and the entropy method are used to establish the optimization function between the optimization variables and the multi-objective performances.Finally,the optimized model is found when the optimization function reaches its maximum value.Experimental data shows that the optimized model not only enhances the static characteristics of the fan but also obviously reduces the noise.The results of the study will provide some reference for the optimization of multi-objective performance of other types of rotating machinery.     

Optimization of Process Parameters for the Preparation of CaO/CaSO4/Coal Fly Ash Sorbent for Sulfur Dioxide (SO2) Removal: Part II

A two-step optimization strategy was employed to optimize the surface area of sorbent prepared from coal fly ash, calcium oxide (CaO) and calcium sulfate (CaSO₄) for flue gas desulfurization. In the first step, a 3 level full factorial design of experiment was used to develop a regression model equation to correlate the significant experimental sorbent preparation variables to the surface area of the resulting sorbent. The three experimental sorbent preparation variables studied are hydration period (x ₁), ratio of CaO to fly ash (x ₂) and amount of CaSO₄ (x ₃). In the subsequent step, response surface methodology was used to identify the experimental sorbent preparation variables that maximize the surface area of the sorbent. Through this two-step optimization strategy, it was found that at a hydration period of 10 hrs and drying temperature of 100°C, optimum surface area of 67.0 m²/g could be attained by using 5 grams of CaO, 13.7 grams of fly ash, and 7.4 grams of CaSO₄ in the preparation mixture. The prediction was verified with experimental runs.     

An inverse problem methodology for design and optimization of an interior permanent magnetic BLDC motor

In the theory of inverse problem, the parameters identification by optimization is considered as one of its main applications. This paper presents an optimal design of a slotted permanent magnet Brushless DC (BLDC) motor with surface mounted magnets. The inverse problem method is applied by using a thriving solver afforded by the nonlinear optimization toolbox of Matlab ‘Fmincon’, this function is based on Active-Set and Sequential Quadratic Programming approaches with calculation of the Hessian from Quasi-Newton algorithm. The optimal magnetic field density considered as the main objective is obtained by picking several parameters and analyzing their effects. The proposed approach is highlighted by using the obtained parameters in the design of the motor. The Finite element method is applied on the motor for numerical analysis by using FEMM magnetic coupled with Matlab code. Effectiveness and robustness of the proposed approach are verified by a comparison between the initial and optimized design.     

Optimal design of transverse ribs in tubes for thermal performance enhancement

We conducted an optimization using the second-order response surface method to determine the transverse rib geometry required to achieve the highest cooling performance in a circular channel. The best rib geometry was based on three design variables; rib height, rib width, and rib pitch. The turbulent heat transfer coefficients and friction losses were first calculated and then used to determine the thermal performance. We constructed the response surfaces of the three design variables as functions of the average Nusselt number ratio, friction loss, and thermal performance. These functions led to the optimum design point at the highest heat transfer rate in the special case of an actual turbine cooling passage with a constant friction loss.     

Optimization of fermentative hydrogen production process using genetic algorithm based on neural network and response surface methodology

A central composite design was carried out to investigate the effect of temperature, initial pH and glucose concentration on fermentative hydrogen production by mixed cultures in batch test. The modeling abilities of the response surface methodology model and neural network model, as well as the optimizing abilities of response surface methodology and the genetic algorithm based on a neural network model were compared. The results showed that the root mean square error and the standard error of prediction for the neural network model were much smaller than those for the response surface methodology model, indicting that the neural network model had a much higher modeling ability than the response surface methodology model. The maximum hydrogen yield of 289.8 mL/g glucose identified by response surface methodology was a little lower than that of 360.5 mL/g glucose identified by the genetic algorithm based on a neural network model, indicating that the genetic algorithm based on a neural network model had a much higher optimizing ability than the response surface methodology. Thus, the genetic algorithm based on a neural network model is a better optimization method than response surface methodology and is recommended to be used during the optimization of fermentative hydrogen production process.