Multi-Stage Multidisciplinary Design Optimization Method for Enhancing Complete Artillery Internal Ballistic Firing Performance

To enhance the comprehensive performance of artillery internal ballistics—encompassing power,accuracy,and service life—this study proposed a multi-stage multidisciplinary design optimization(MS-MDO)method.First,the comprehensive artillery internal ballistic dynamics(AIBD)model,based on propellant combustion,rotation band engraving,projectile axial motion,and rifling wear models,was established and validated.This model was systematically decomposed into subsystems from a system engineering perspective.The study then detailed the MS-MDO methodology,which included Stage I(MDO stage)employing an improved collaborative optimization method for consistent design variables,and Stage II(Performance Optimization)focusing on the independent optimization of local design variables and performance metrics.The methodology was applied to the AIBD problem.Results demonstrated that the MS-MDO method in Stage I effectively reduced iteration and evaluation counts,thereby accelerating system-level convergence.Meanwhile,Stage II optimization markedly enhanced overall performance.These comprehensive evaluation results affirmed the effectiveness of the MS-MDO method.

An Efficient Method for Reliability-based Multidisciplinary Design Optimization

Design for modem engineering system is becoming multidisciplinary and incorporates practical uncertainties; therefore, it is necessary to synthesize reliability analysis and the multidisciplinary design optimization （MDO） techniques for the design of complex engineering system. An advanced first order second moment method-based concurrent subspace optimization approach is proposed based on the comparison and analysis of the existing multidisciplinary optimization techniques and the reliability analysis methods. It is seen through a canard configuration optimization for a three-surface transport that the proposed method is computationally efficient and practical with the least modification to the current deterministic optimization process.

Reliability-based multidisciplinary design optimization using incremental shifting vector strategy and its application in electronic product design

Use of multidisciplinary analysis in reliabilitybased design optimization(RBDO) results in the emergence of the important method of reliability-based multidisciplinary design optimization(RBMDO). To enhance the efficiency and convergence of the overall solution process,a decoupling algorithm for RBMDO is proposed herein.Firstly, to decouple the multidisciplinary analysis using the individual disciplinary feasible(IDF) approach, the RBMDO is converted into a conventional form of RBDO. Secondly,the incremental shifting vector(ISV) strategy is adopted to decouple the nested optimization of RBDO into a sequential iteration process composed of design optimization and reliability analysis, thereby improving the efficiency significantly. Finally, the proposed RBMDO method is applied to the design of two actual electronic products: an aerial camera and a car pad. For these two applications, two RBMDO models are created, each containing several finite element models(FEMs) and relatively strong coupling between the involved disciplines. The computational results demonstrate the effectiveness of the proposed method.

Application of the optimal Latin hypercube design and radial basis function network to collaborative optimization

Improving the efficiency of ship optimization is crucial for modem ship design. Compared with traditional methods, multidisciplinary design optimization （MDO） is a more promising approach. For this reason, Collaborative Optimization （CO） is discussed and analyzed in this paper. As one of the most frequently applied MDO methods, CO promotes autonomy of disciplines while providing a coordinating mechanism guaranteeing progress toward an optimum and maintaining interdisciplinary compatibility. However, there are some difficulties in applying the conventional CO method, such as difficulties in choosing an initial point and tremendous computational requirements. For the purpose of overcoming these problems, optimal Latin hypercube design and Radial basis function network were applied to CO. Optimal Latin hypercube design is a modified Latin Hypercube design. Radial basis function network approximates the optimization model, and is updated during the optimization process to improve accuracy. It is shown by examples that the computing efficiency and robustness of this CO method are higher than with the conventional CO method.

Multidisciplinary Design Optimization of A Human Occupied Vehicle Based on Bi-Level Integrated System Collaborative Optimization

The design of Human Occupied Vehicle （HOV） is a typical multidisciplinary problem, but heavily dependent on the experience of naval architects at present engineering design. In order to relieve the experience dependence and improve the design, a new Multidisciplinary Design Optimization （MDO） method ＂Bi-Level Integrated System Collaborative Optimization （BLISCO）＂ is applied to the conceptual design of an HOV, which consists of hull module, resistance module, energy module, structure module, weight module, and the stability module. This design problem is defined by 21 design variables and 23 constraints, and its objective is to maximize the ratio of payload to weight. The results show that the general performance of the HOV can be greatly improved by BLISCO.

Multidisciplinary Design Optimization with a New Effective Method

Collaborative optimization （CO） is one of the most widely used methods in multidisciplinary design optimization （MDO）, which is an effective methodology to solve modem complex engineering problems. CO consists of two-level optimization problems which are system optimization problem and subspace optimization problem. The architecture of CO can reserve the autonomy of individual disciplines in maximum, while providing a mechanism for coordinating design problem. However, CO has low computation efficiency and is easy to diverge. For the purpose of solving these problems, the former improved methods were studied. The relaxation factors were used to change the system consistency constraints to inequality constraints, or the response surface estimation was used to surrogate the system consistency constraints. However, these methods didn＇t avoid the computational difficulties very well, furthermore, some new problems arose. The concept of optimum constraint sensitivity was proposed, and the quadratic constraints in system level were reformed. Hence, a new collaborative optimization was developed, which is called system level dynamic constraint collaborative optimization （DCCO）. The novel method is able to increase the exchange of information between system level and disciplinary level. The optimization results of each disciplinary optimization can be feedback to system level with the optimum constraint sensitivity. On the basis of the information, the new system level linear dynamic constraints can be constructed; it is better to reflect the effect of disciplinary level optimizations. The system level optimizer can clearly capture the boundary where disciplinary objective functions become zero, and considerably enhance the convergence. Two standard MDO examples were conducted to verify the feasibility and effectiveness of DCCO. The results show that DCCO can save the solving time, and is much better in terms of convergence and robustness, hence, the new method is more efficient.

Applying the disciplinary relation matrix to multidisciplinary design optimization modeling and solving

A new efficient coupling relationship description method has been developed to provide an automated and visualized way to multidisciplinary design optimization (MDO) modeling and solving. The disciplinary relation matrix (DRM) is proposed to describe the coupling relationship according to disciplinary input/output variables, and the MDO definition has been reformulated to adopt the new interfaces. Based on these, a universal MDO solving procedure is proposed to establish an automated and efficient way for MDO modeling and solving. Through a simple and convenient initial configuration, MDO problems can be solved using any of available MDO architectures with no further effort. Several examples are used to verify the proposed MDO modeling and solving process. Result shows that the DRM method has the ability to simplify and automate the MDO procedure, and the related MDO framework can evaluate the MDO problem automatically and efficiently.

Synergetic Optimization of Missile Shapes for Aerodynamic and Radar Cross-Section Performance Based on Multi-objective Evolutionary Algorithm

A multiple-objective evolutionary algorithm (MOEA) with a new Decision Making (DM) scheme for MOD of conceptual missile shapes was presented, which is contrived to determine suitable tradeoffs from Pareto optimal set using interactive preference articulation. There are two objective functions, to maximize ratio of lift to drag and to minimize radar cross-section (RCS) value. 3D computational electromagnetic solver was used to evaluate RCS, electromagnetic performance. 3D Navier-Stokes flow solver was adopted to evaluate aerodynamic performance. A flight mechanics solver was used to analyze the stability of the missile. Based on the MOEA, a synergetic optimization of missile shapes for aerodynamic and radar cross-section performance is completed. The results show that the proposed approach can be used in more complex optimization case of flight vehicles.

Aeroelastic Optimization of the High Aspect Ratio Wing with Aileron

In aircraft wings,aileron mass parameter presents a tremendous effect on the velocity and frequency of the flutter problem.For that purpose,we present the optimization of a composite design wing with an aileron,using machine-learning approach.Mass properties and its distribution have a great influence on the multi-variate optimization procedure,based on speed and frequency of flutter.First,flutter speed was obtained to estimate aileron impact.Additionally mass-equilibrated and other features were investigated.It can deduced that changing the position and mass properties of the aileron are tangible following the speed and frequency of the wing flutter.Based on the proposed optimization method,the best position of the aileron is determined for the composite wing to postpone flutter instability and decrease the existed stress.The represented coupled aero-structural model is emerged from subsonic aerodynamics model,which has been developed using the panel method in multidimensional space.The structural modeling has been conducted by finite element method,using the p-k method.The fluid-structure equations are solved and the results are extracted.

Stability analysis of underground engineering based on multidisciplinary design optimization

Aiming at characteristics of underground engineering,analyzed the feasibility of Multidisciplinary Design Optimization (MDO) used in underground engineering,and put forward a modularization-based MDO method and the idea of MDO to resolve problems in stability analysis,proving the validity and feasibility of using MDO in underground engi- neering.Characteristics of uncertainty,complexity and nonlinear become bottle-neck to carry on underground engineering stability analysis by MDO.Therefore,the application of MDO in underground engineering stability analysis is still at a stage of exploration,which need some deep research.

Research on Approaches of Multidisciplinary Design Optimization for Non-hierarchic Systems

In complex engineering optimization, multilevel or two-level approaches are often applied. These approaches are carried out in assumption that there are no connections among sub problems at the same level. But it is difficult to construct the models that suit to this assumption. In recent years, the complexity of engineering systems has led to the rapid development in the field of Multidisciplinary Design Optimization (MDO). In MDO, two kinds of coupled factors, coupled variables (or functions) and system (or global) variables, always exist among all disciplines. These variable5 or functions make it disordered to solve the whole system. So, how to handle these variables is one of important studies in MDO. In this paper two approaches are discussed for handling these coupled factors in non-hierarchic system in MDO. And a test engineering example gives a demonstration about the implemeniation of these approaches.

基于MDO方法的车用三效催化转化器设计优化

以车用三效催化转化器(TWC)的转化效率、压力损失、质量以及抗热冲击性能为目标函数,建立了TWC多学科设计优化(MDO)模型。在充分考虑各学科之间的耦合效应基础上,通过采用自适应混沌优化算法与VB编程对MDO模型进行求解。优化结果表明,压力损失减少6.99%,质量减少11.68%,位移变形减少20.91%,TWC转化效率提高5.42%。试验证明该方法用于TWC是有效的。

基于matlab的飞行器并行MDO方法的研究与实现

在Parmatlab的基础上开发出适合网络通讯的matlab工具箱MDO504 toolbox,此工具箱提供了在matlab环境下进行并行计算的函数。在此工具箱的基础上开发出进行多学科设计优化的软件GSEOPT,GSEOPT在并行环境下实现了基于全局灵敏度方程(GSE)的单级优化算法,用并行的方法求得了全局灵敏度,在系统层进行优化。最后用此软件对某飞行器进行了并行优化设计,给出了计算结果,并与参考文献结果进行了比较,得到了更好的结果。

基于层次分析法的MDO算法性能评价

在互补判断矩阵排序理论的基础上,结合最优化方法,将互补判断矩阵特征向量法引入层次分析中,提出了一种基于互补判断矩阵特征向量法的层次分析方法。通过对几种常见MDO算法的设计变量、约束、计算精度和计算复杂度进行分析,给出了改良的序列二次规划算法(NLPQL)、自适应模拟退火算法(ASA)、多岛遗传算法(MIGA)和序列二次规划算法(DONLP)在涡轮叶片多学科优化中选择的实例说明,并与实际优化结果进行对比,验证了本文所采用方法的有效性。

MDO在汽车转向系统结构优化中的应用

转向系统刚度强度是影响汽车稳态特性的重要因素,转向系统NVH性能是影响汽车舒适性的重要指标,所以它的设计需要满足多个性能要求。针对转向系统利用HyperStudy优化软件,采用均匀拉丁方实验设计方法进行样本数据设计,利用最小二乘法构建了汽车转向系统的刚度、强度、NVH多学科系统的近似响应面优化模型,从而对转向系统结构进行了多学科优化。优化结果表明转向系统在刚度、强度及NVH性能有所提高的同时,重量得到较大程度的减轻。算例表明,多学科优化方法具有较高的工程实用性。

涡轮叶片MDO实现的进展

航空发动机涡轮叶片系统的设计涉及了空气动力学、热学等等诸多相互关联或耦合的学科,往往需要通过各学科之间反复的协调分析才能设计出性能优良的系统.为突破以往过分依赖经验的设计方法,近年来众多学者对发动机叶片的MDO技术进行了大量的研究和探索.我们借助国际上先进的MDO软件iSIGHT建立了集成不同数值模拟器的MDO平台,并将其成功地应用于涡轮叶片的MDO过程中.

面向MDO的复杂产品多学科视图建模技术

提出了面向MDO的复杂产品多学科视图建模技术,给出以主模型为导向的多学科并行建模技术路线。通过建立复杂产品设计过程的层次分解与映射模型,分析产品组成的多学科性;给出多学科并行的设计方法,以实现各学科子系统功能的独立性;通过多学科视图建模的一致性规则及多模型的协同运行策略,解决冲突的协调问题;采用面向对象方法,建立起多学科视图建模技术的层次实现结构;基于优化技术与CAD/CAE的技术集成,实现多模型协同仿真与优化。该技术应用于汽车车身的多学科建模与仿真优化,实现了设计信息的动态交互与多学科共享,有效改进了产品设计水平,提高了产品的设计效率。

基于MDO方法的离心式压气机设计系统

针对离心式压气机设计中存在流—热—固耦合的问题,文中进行离心式压气机的多学科设计优化研究,基于多学科可行方法,建立离心式压气机的多学科设计优化系统。利用非均匀有理B样条曲线和五次多项式,分别构建径流式叶片型线和扩压器叶片型线,通过特征造型技术,建立离心式压气机参数化模型。采用线性插值方法和网格重生成方法,完成对温度、气压和变形耦合信息传递。在压气机参数化建模和多学科耦合分析的基础上,以总压比、等熵效率和流量为优化目标,对某离心式压气机进行设计优化,实现其综合性能的改善。所建多学科设计优化系统可以推广到其他多场耦合系统的设计。

复杂工业产品多学科设计仿真优化平台(UniXDE)研究与应用

针对国内外已有的复杂工业产品多学科设计仿真优化框架与平台在多学科模型集成能力、计算能力、协同能力方面的不足,研究和开发国产自主的新一代复杂工业产品多学科设计仿真优化框架与平台UniXDE(unified exploration and design environment)。本平台基于微服务云架构技术构建整体框架,提供低代码仿真优化流程编排、组件化CAD/CAE参数化集成接口、丰富的多学科设计优化算法库、分布式高性能优化计算引擎、可视化计算监控和报告自动生成等功能。通过白车身轻量化、船型优化、飞行器起落架性能优化等工程应用,表明UniXDE可显著提升产品综合性能和设计成功率。

基于MDO体系的涡轮叶片热-结构耦合分析

在涡轮叶片参数化建模和气动分析基础上,开发了三维坐标插值程序,实现了学科间载荷信息传递;基于经验准则公式,开发了换热系数计算程序;在研究ANSYS软件参数化设计语言的基础上,利用插值及换热程序输出APDL参数化加载宏文件,实现了边界条件的精确加载;基于ANSYS软件APDL命令流,设计了涡轮叶片热分析模块及热-结构耦合分析模块,为建立涡轮叶片MDO体系奠定了基础。