INTEGRATION SHAPE AND SIZING OPTIMIZATION OF COMPOSITE WING STRUCTURE BASED ON RESPONSE SURFACE METHOD

An effective optimization method for the shape/sizing design of composite wing structures is presented with satisfying weight-cutting results. After decoupling, a kind of two-layer cycled optimization strategy suitable for these integrated shape/sizing optimization is obtained. The uniform design method is used to provide sample points, and approximation models for shape design variables. And the results of sizing optimization are construct- ed with the quadratic response surface method （QRSM）. The complex method based on QRSM is used to opti- mize the shape design variables and the criteria method is adopted to optimize the sizing design variables. Compared with the conventional method, the proposed algorithm is more effective and feasible for solving complex composite optimization problems and has good efficiency in weight cutting.

Optimization of buckling load for laminated composite plates using adaptive Kriging-improved PSO:A novel hybrid intelligent method

An effective hybrid optimization method is proposed by integrating an adaptive Kriging(A-Kriging)into an improved partial swarm optimization algorithm(IPSO)to give a so-called A-Kriging-IPSO for maximizing the buckling load of laminated composite plates(LCPs)under uniaxial and biaxial compressions.In this method,a novel iterative adaptive Kriging model,which is structured using two training sample sets as active and adaptive points,is utilized to directly predict the buckling load of the LCPs and to improve the efficiency of the optimization process.The active points are selected from the initial data set while the adaptive points are generated using the radial random-based convex samples.The cell-based smoothed discrete shear gap method(CS-DSG3)is employed to analyze the buckling behavior of the LCPs to provide the response of adaptive and input data sets.The buckling load of the LCPs is maximized by utilizing the IPSO algorithm.To demonstrate the efficiency and accuracy of the proposed methodology,the LCPs with different layers(2,3,4,and 10 layers),boundary conditions,aspect ratios and load patterns(biaxial and uniaxial loads)are investigated.The results obtained by proposed method are in good agreement with the literature results,but with less computational burden.By applying adaptive radial Kriging model,the accurate optimal resultsebased predictions of the buckling load are obtained for the studied LCPs.

AN EFFICIENT PARALLEL PROCESSING OPTIMAL CONTROL SCHEME FOR A CLASS OF NONLINEAR COMPOSITE SYSTEMS

This article presents an efficient parallel processing approach for solving the opti- mal control problem of nonlinear composite systems. In this approach, the original high-order coupled nonlinear two-point boundary value problem （TPBVP） derived from the Pontrya- gin＇s maximum principle is first transformed into a sequence of lower-order deeoupled linear time-invariant TPBVPs. Then, an optimal control law which consists of both feedback and forward terms is achieved by using the modal series method for the derived sequence. The feedback term specified by local states of each subsystem is determined by solving a ma- trix Riccati differential equation. The forward term for each subsystem derived from its local information is an infinite sum of adjoint vectors. The convergence analysis and parallel processing capability of the proposed approach are also provided. To achieve an accurate feedforward-feedbaek suboptimal control, we apply a fast iterative algorithm with low com- putational effort. Finally, some comparative results are included to illustrate the effectiveness of the proposed approach.

RELIABILITY-BASED DESIGN OF COMPOSITES UNDER THE MIXED UNCERTAINTIES AND THE OPTIMIZATION ALGORITHM

This paper proposed a reliability design model for composite materials under the mixture of random and interval variables. Together with the inverse reliability analysis technique, the sequential single-loop optimization method is applied to the reliability-based design of composites. In the sequential single-loop optimization, the optimization and the reliability analysis are decoupled to improve the computational efficiency. As shown in examples, the minimum weight problems under the constraint of structural reliability are solved for laminated composites. The Particle Swarm Optimization （PSO） algorithm is utilized to search for the optimal solutions. The design results indicate that, under the mixture of random and interval variables, the method that combines the sequential single-loop optimization and the PSO algorithm can deal effectively with the reliability-based design of composites.

Parametric Optimization to Minimise the Surface Roughness on the Machining of GFRP Composites

The present investigation focuses on the parametric influence of machining parameters on the surface finish obtained in turning of glass fiber reinforced polymer （GFRP） composites. The experiments were conducted based on Taguchi＇s experimental design technique. Response surface methodology and analysis of variance （ANOVA） were used to evaluate the composite machining process to perform the optimization. The results revealed that the feed rate was main influencing parameter on the surface roughness. The surface roughness increased with increasing the feed rate but decreased with increasing the cutting speed. Among the other parameters, depth of cut was more insensitive. The predicted values and measured values were fairly close to each other, which indicates that the developed model can be effectively used to predict the surface roughness on the machining of GFRP composites with 95% confidence intervals. Using such model could remarkablely save the time and cost.

Hybrid multi-objective optimization of microstructural and mechanical properties of B_4C/A356 composites fabricated by FSP using TOPSIS and modified NSGA-Ⅱ

A356alloy was used as the base metal to produce boron carbide(B4C)/A356composites using friction stir processing(FSP).The microstructural and mechanical properties of B4C/A356composites were optimized using artificial neural network(ANN)and non-dominated sorting genetic algorithm-II(NSGA-II).Firstly,microstructural properties of the composites fabricated in different processing conditions were investigated.Results show that FSP parameters such as rotational speed,traverse speed and tool pin profile significantly affect the size of the primary silicon(Si)particles of the base metal,as well as the dispersion quality and volume fraction of reinforcing B4C particles in the composite layer.Higher rotational to traverse speeds ratio accompanied by threaded pin profile leads to better particles distribution,finer Si particles and smaller B4C agglomerations.Secondly,hardness and tensile tests were performed to study mechanical properties of the composites.FSP changes the fracture mechanism from brittle form in the as-received metal to very ductile form in the FSPed specimens.Then,a relation between the FSP parameters and microstructural and mechanical properties of the composites was established using ANN.A modified NSGA-II by incorporating diversity preserving mechanism called theεelimination algorithm was employed to obtain the Pareto-optimal set of FSP parameters.

Optimization of chemistry and process parameters for control of intermetallic formation in Mg sludges

Intermetallic formation in sludge during magnesium(Mg)melting,holding and high pressure die casting practices is a very important issue.But,very often it is overlooked by academia,original equipment manufacturers(OEM),metal ingot producers and even die casters.The aim of this study was to minimize the intermetallic formation in Mg sludge via the optimization of the chemistry and process parameters.The Al8Mn5 intermetallic particles were identified by the microstructure analysis based on the Al and Mn ratio.The design of experiment(DOE)technique,Taguchi method,was employed to minimize the intermetallic formation in the sludge of Mg alloys with various chemical compositions of Al,Mn,Fe,and different process parameters,holding temperature and holding time.The sludge yield(SY)and intermetallic size(IS)was selected as two responses.The optimum combination of the levels in terms of minimizing the intermetallic formation were 9 wt.%Al,0.15 wt.%Mn,0.001 wt.%(10 ppm)Fe,690℃ for the holding temperature and holding at 30 mins for the holding time,respectively.The best combination for smallest intermetallic size were 9 wt.%Al,0.15 wt.%Mn,0.001 wt.%(10 ppm)Fe,630℃ for the holding temperature and holding at 60 mins for the holding time,respectively.Three groups of sludge factors,Chemical Sludge(CSF),Physical Sludge(PSF)and Comprehensive Sludge Factors(and CPSF)were established for prediction of sludge yields and intermetallic sizes in Al-containing Mg alloys.The CPSF with five independent variables including both chemical elements and process parameters gave high accuracy in prediction,as the prediction of the PSF with only the two processing parameters of the melt holding temperature and time showed a relatively large deviation from the experimental data.The Chemical Sludge Factor was primarily designed for small ingot producers and die casters with a limited melting and holding capacity,of which process parameters could be fixed easily.The Physical Sludge Factor could be used for mass production with a single type of Mg alloy,in which the chemistry fluctuation might be negligible.In large Mg casting suppliers with multiple melting and holding furnaces and a number of Mg alloys in production,the Comprehensive Sludge Factor should be implemented to diminish the sludge formation.

Buckling optimization of curvilinear fiber-reinforced composite structures using a parametric level set method

Owing to their excellent performance and large design space,curvilinear fiber-reinforced composite structures have gained considerable attention in engineering fields such as aerospace and automobile.In addition to the stiffness and strength of such structures,their stability also needs to be taken into account in the design.This study proposes a level-set-based optimization framework for maximizing the buckling load of curvilinear fiber-reinforced composite structures.In the proposed method,the contours of the level set function are used to represent fiber paths.For a composite laminate with a certain number of layers,one level set function is defined by radial basis functions and expansion coefficients for each layer.Furthermore,the fiber angle at an arbitrary point is the tangent orientation of the contour through this point.In the finite element of buckling,the stiffness and geometry matrices of an element are related to the fiber angle at the element centroid.This study considers the parallelism constraint for fiber paths.With the sensitivity calculation of the objective and constraint functions,the method of moving asymptotes is utilized to iteratively update all the expansion coefficients regarded as design variables.Two numerical examples under different boundary conditions are given to validate the proposed approach.Results show that the optimized curved fiber paths tend to be parallel and equidistant regardless of whether the composite laminates contain holes or not.Meanwhile,the buckling resistance of the final design is significantly improved.

Seismic displacement demand prediction in non-linear domain: Optimization of the N2 method

In Europe, computation of displacement demand for seismic assessment of existing buildings is essentially based on a simplified formulation of the N2 method as prescribed by Eurocode 8(EC8). However, a lack of accuracy of the N2 method in certain conditions has been pointed out by several studies. This paper addresses the assessment of effectiveness of the N2 method in seismic displacement demand determination in non-linear domain. The objective of this work is to investigate the accuracy of the N2 method through comparison with displacement demands computed using non-linear timehistory analysis(NLTHA). Results show that the original N2 method may lead to overestimation or underestimation of displacement demand predictions. This may affect results of mechanical model-based assessment of seismic vulnerability at an urban scale. Hence, the second part of this paper addresses an improvement of the N2 method formula by empirical evaluation of NLTHA results based on EC8 ground-classes. This task is formulated as a mathematical programming problem in which coefficients are obtained by minimizing the overall discrepancy between NLTHA and modified formula results. Various settings of the mathematical programming problem have been solved using a global optimization metaheuristic. An extensive comparison between the original N2 method formulation and optimized formulae highlights benefits of the strategy.

Almost Sure Convergence of Proximal Stochastic Accelerated Gradient Methods

Proximal gradient descent and its accelerated version are resultful methods for solving the sum of smooth and non-smooth problems. When the smooth function can be represented as a sum of multiple functions, the stochastic proximal gradient method performs well. However, research on its accelerated version remains unclear. This paper proposes a proximal stochastic accelerated gradient (PSAG) method to address problems involving a combination of smooth and non-smooth components, where the smooth part corresponds to the average of multiple block sums. Simultaneously, most of convergence analyses hold in expectation. To this end, under some mind conditions, we present an almost sure convergence of unbiased gradient estimation in the non-smooth setting. Moreover, we establish that the minimum of the squared gradient mapping norm arbitrarily converges to zero with probability one.

Multifunctional graphene‐based composite photocatalysts oriented by multifaced roles of graphene in photocatalysis

Graphene(GR),a single‐layer carbon sheet with a hexagonal packed lattice structure,has displayed attractive potential and demonstrably become the research focus in artificial photocatalysis due to its enchanting properties in enhancing light absorption,electron transfer dynamics,and surface reactions.Currently,numerous efforts have shown that the properties of GR,which are closely correlated to the photocatalytic performance of GR‐based composites are significantly affected by the synthesis methods.Herein,we first introduce the optimization strategies of GR‐based hybrids and then elaborate the synthesis of GR‐based composite photocatalysts oriented by manifold roles of GR in photoredox catalysis,containing photoelectron mediator and acceptor,improving adsorption capacity,regulating light absorption range and intensity,as well as macromolecular photosensitizer.Beyond that,a brief outlook on the challenges in this burgeoning research field and potential evolution strategies for enhancing the photoactivity of GR‐based hybrids is presented and we anticipate that this review could provide some enlightenments for the rational construction and application of multifunctional GR‐based composite photocatalysts.

A NONMOTOTONE ALGORITHM FOR MINIMIZING NONSMOOTH COMPOSITE FUNCTIONS

In this paper, we present a nonmonotone algorithm for solving nonsmooth composite optimization problems. The objective function of these problems is composited by a nonsmooth convex function and a differentiable function. The method generates the search directions by solving quadratic programming successively, and makes use of the nonmonotone line search instead of the usual Armijo-type line search. Global convergence is proved under standard assumptions. Numerical results are given.

基于Kriging模型与FORM的钢板组合梁桥结构优化设计

考虑材料参数的不确定性以及设计变量多重约束条件的影响,提出了基于可靠性分析的钢板组合梁桥结构优化设计方法。首先,利用拉丁超立方试验设计(Latin hypercube design,LHD)构建试验组合方案,并通过有限元分析获取试验设计组合下的最大挠度响应值。基于获取的训练样本,构建能够表征结构最大挠度值与随机输入之间映射关系的Kriging代理模型。基于建立的代理模型,以钢结构截面积最小化为目标函数,建立符合规范要求与可靠度约束的优化数学模型,并采用一阶可靠性方法(first order reliability method,FORM),实现设计变量优化。通过比较具有相同设计变量上限,但下限分别为初始值的80%和70%两种优化设计方案,评估了两者在相同阈值以及不同阈值下设计变量的优化结果。最后对方案二在阈值为17 mm下的优化结果进行极限状态验算。结果表明:两个优化设计方案在阈值为17 mm下的优化结果更具合理性,并且方案二在同一阈值下具有更高的优化程度。随着阈值增加,优化程度增加,且腹板高度在较大阈值下对结果影响更大,而翼缘宽度在较小阈值下影响更大。

连续芳纶纤维增强PLA复合材料3D打印技术成型缺陷及工艺优化方法研究

连续纤维3D打印技术结合了复合材料高力学性能和3D打印灵活制造的优点,具有较大发展潜力。然而现有工艺制得的零件存在较多成型缺陷,影响了该技术的大规模应用。本文基于自行研制的3D打印设备制造芳纶纤维增强PLA试验件,研究试验件成型质量并提出了滑移缺陷发生条件,系统研究了纤维束滑移、剥离、断裂和层间孔隙等缺陷,最后提出优化打印速度、路径变化角、冷却系统和喷嘴外形四种工艺优化方法,设计了相关试验进行验证。结果表明,优化打印速度、路径变化角和增设冷却系统可将纤维束滑移距离分别降低45%、81%和50%,优化喷嘴设计可将纤维束断裂率降低90%。本研究为基于3D打印的复合材料设计和制造提供了新的思路和解决方案。

氧化石墨烯调控粉煤灰基硅酸锰/氧化锰复合材料的电化学性能机制

超级电容器是一种具有高功率密度、优秀循环性能、高安全性的高性能储能装置,然而其低能量密度限制其发展,为进一步提升超级电容器的能量密度,满足日益增长的储能需求,提升电极材料的电化学性能是关键。为提高粉煤灰基硅酸锰/氧化锰的电化学性能,采用静电组装法合成了氧化石墨烯与粉煤灰基硅酸锰/氧化锰的复合材料(FA@MS/MO/GO),通过调节氧化石墨烯加入量优化其电化学性能,并研究了氧化石墨烯对于粉煤灰基硅酸锰/氧化锰电化学性能的影响机制,通过XRD、SEM、XPS、FTIR表征材料的形貌与结构,并采用循环伏安法、恒电流充放电、交流阻抗测试对材料和器件性能进行测试。结果表明,优化后的FA@MS/MO/GO-2的电荷传输速率大幅提升,FA@MS/MO/GO-2在0.5 A/g电流密度下的比电容为737.4 F/g,高于未与氧化石墨烯复合的FA@MS/MO(293.4 F/g),电流密度由0.5 A/g升高至8.0 A/g,FA@MS/MO/GO-2容量保持率最好(67%),高于FA@MS/MO(44%)。FA@MS/MO/GO-2与商业活性炭分别为正负极组装为非对称超级电容器后,该器件能量密度达15.75 Wh/kg(功率密度375 W/kg),在5 A/g下循环10000次的容量保持率和库伦效率均可达100%,表明该电极材料拥有长期循环利用潜力,具有良好应用前景。

复合材料机翼多工况下的自适应优化设计

为获得具有优良气动性能且兼具结构强度及轻量化的复合材料飞机机翼,提出考虑气动分析和结构分析多目标多工况优化方法。分别对机翼进行气动分析及结构强度分析,以机翼展弦比、锥度比、后掠角为几何优化变量,以机翼上下机翼蒙皮的-45°、90°、45°、0°层厚度和夹芯厚度为结构优化变量,建立以应力、位移为约束,以升阻比最大化和质量最小化为目标的协同优化模型。针对复合材料机翼多目标优化设计存在的计算量大难以取舍的问题,提出基于多准则和物理规划的自适应约束Kriging模型多目标优化算法(adaptive constraint kriging model multi-objective optimization algorithm based on multi-criteria and physical programming,AKBCP)。该算法引入了物理规划法和多准则加点,通过测试算例对比分析表明该算法具有较好的优化效果。将该算法应用到机翼多目标优化中,与初始机翼相比,优化后机翼升阻比提高3.12%,质量减轻31%,研究结果可为复合材料机翼优化设计提供参考。

基于相关性分析和响应面法的复合旋流器结构参数优化

为了提高旋流器优化参数的准确性,得到其在结构优化中的最优解,以一种新型复合旋流器为研究对象,基于相关性的单因素分析寻优法,以相关性分析的结果来指导优化范围的选取,提高其结构参数优化范围的准确性。结合响应面优化方法,以分离效率为优化目标,确定旋流器的最优结构参数,建立了分离效率和结构参数之间的回归模型。结果表明:不同的结构参数和各性能指标之间的显著关系并不相同,根据相关性分析的结果确定各结构的优化范围为:上锥角为0°~4°,下锥角为8°~12°,底流口直径为12~16 mm;响应面优化得到旋流器最优结构为:上锥角为2.565°,下锥角为11.719°,底流口直径为12.889 mm,在本组参数下旋流器固体分离效率达到了99.945%,气体分离效率达到了93.807%。为旋流器的结构优化提供了一种新方法。

基于粒子群-细菌觅食混合优化算法的汽车碳纤维复合材料地板铺层设计

为提高白车身地板复合材料铺层优化设计的精度、效率及结构轻量化水平,提出了一种碳纤维复合材料地板铺层优化设计方法。首先建立了白车身有限元模型并验证了其有效性,然后通过力学性能测试获取了碳纤维复合材料的参数,并进行了地板铺层的概念设计和建模。接着,采用连续变量优化设计方法确定了地板的铺层厚度、铺块形状和铺层层数,并使用离散化圆整策略获得了各铺向角的离散铺层层数。优化结果表明,所提出的粒子群-细菌觅食混合优化(PSO-BFO)算法对地板质量、静态弯曲刚度和白车身轻量化系数的改善率分别为34.4%、6.0%和5.3%。

基于总安全系数法的甬舟铁路支护参数优化与试验研究

为解决传统复合式衬砌设计方法难以统一评价整体支护结构安全性的问题,结合支护参数优化理论和甬舟铁路实际工况,选取一个典型计算断面,采用数值模拟和总安全系数法对在不同围岩级别工况下优化后的支护参数进行安全性分析。结果表明,优化后的支护参数均满足安全性要求,说明总安全系数法用于支护参数的精细优化是可行的。

V/Nb基合金氢分离膜的制备与性能研究进展

目前,开发可再生能源已经成为全球可持续能源战略中的一个重要内容。氢能是世界上最清洁的能源,被认为是最有潜力的替代能源。目前工业制氢含有大量杂质,因此,氢的提纯是利用氢能不可或缺的一环。目前钯及其合金膜在氢分离上是最常见的材料,但它们过于昂贵和产量不足,我们需要去寻找新的性能优异的氢分离膜。研究发现V/Nb及其合金膜的氢渗透系数远大于Pd,且成本相比钯金属更为低廉,是替代Pd金属的最佳氢分离膜材料。目前对V/Nb基合金膜的研究已有许多,本文介绍了合金膜的透氢原理、氢分离膜的制备方法及其优缺点以及V/Nb基合金近年来的研究现状,并展望未来氢分离膜的研究发展趋势。