Multidisciplinary Design Optimization Method Research Articles

Method of Genetic Algorithm Optimization Design of Permanent Magnet Retarder

This paper introduced the method of multidisciplinary design optimization based on genetic algorithm. The basic structure and new auxiliary braking mechanism of permanent magnet retarder was analyzed. The influences of magnetic field parameters, structural design parameters, rotor parameters and permanent magnet temperature parameters on the behaviors performance of the permanent magnet retarder were discussed. The conceptual model of permanent magnet retarder was developed to maximize the brake torque of the permanent magnet retarder. The design variables included the radial width and the axis length of permanent magnet, the number of permanent magnet, the radius of rotor, the thickness of rotor, and the air gas. The constraint conditions included permitting temperature of rotor, saturation magnetic flux density of magnet material, and relation of structural geometry. The results of design optimization variables were obtained by applying genetic algorithm. The multidisciplinary design optimization in this paper is an effective method for the global design optimization of the permanent magnet retarder.

New multidisciplinary design optimization approaches for launch vehicle design

Launch vehicle design is a complex problem involving a series of disciplines. These disciplines present conflicting objectives and require multidisciplinary design optimization methods in order to ...

Application of Multidisciplinary Design Optimization to a Resource Satellite

Satellite system design is a process involving various branches of knowledge, in which the designer usually needs to tradeoff many essentials and takes remarkable time. While multidisciplinary design optimization (MDO) method provides an effective approach for complicated system design, it seems especially suitable for such kind design purpose. By applying MDO in satellite system design, the efficiency of design can be expected to be improved and powerful technical supports can be obtained, which means better performance, faster design process and lower cost. According to the Resource satellite mission, width of ground cover and ground resolution are taken as the performance measurement, which combined with total mass of satellite is accounted in the optimization objective in system level. The design variables and constraints of the problem are dealt with disciplines or subsystems such as GNC, power, structure and thermal control. Corresponding analysis modules close to practical engineering are modeled. A MDO program system is developed by integrating collaborative optimization (CO) methods in iSIGHT. The result shows that the comprehensive objective can be improved, which also indicates MDO is feasible and efficient to solve the spacecraft design problem. The technology can be consulted for further research work.

다정밀도 해석기법을 이용한 무인항공기 다분야통합 최적설계

In this study, Multi-fidelity analysis is performed to improve the accuracy of analysis result during conceptual design stage. Multidisciplinary Design Optimization(MDO) method is also considered to satisfy the total system requirements. Low-fidelity analysis codes which are based on empirical equations are developed and validated for analyzing the Unmanned Aerial Vehicle(UAV) which have unconventional configurations. Analysis codes consist of initial sizing, aerodynamics, propulsion, mission, weight, performance, and stability modules. Design synthesis program which is composed of those modules is developed. To improve the accuracy of the design method for UAV, Vortex Lattice Method is used for the strategy of MFA. Multi-Disciplinary Feasible(MDF) method is used for MDO technique. To demonstrate the validity of presented method, the optimization results of both methods are compared. According to those results, the presented method is demonstrated to be applicable to improve the accuracy of the analyses during conceptual design stage.

LOcal Uncertainty Processing (LOUP) method for multidisciplinary robust design optimization

In this paper, we develop an easy-to-implement approximate method to take uncertainties into account during a multidisciplinary optimization. Multidisciplinary robust design usually involves setting up a full uncertainty propagation within the system, requiring major modifications in every discipline and on the shared variables. Uncertainty propagation is an expensive process, but robust solutions can be obtained more easily when the disciplines affected by uncertainties have a significant effect on the objectives of the problem. A heuristic method based on local uncertainty processing (LOUP) is presented here, allowing approximate solving of specific robust optimization problems with minor changes in the initial multidisciplinary system. Uncertainty is processed within the disciplines that it impacts directly, without propagation to the other disciplines. A criterion to verify a posteriori the applicability of the method to a given multidisciplinary system is provided. The LOUP method is applied to an aircraft preliminary design industrial test case, in which it allowed to obtain robust designs whose performance is more stable than the one of deterministic solutions, relatively to uncertain parameter variations.

Multidisciplinary Object Compatibility Design Optimization Based on Simulated Annealing Algorithm

In studying Multidisciplinary Object Compatibility Design Optimization method for non-hierarchic system, Simulated Annealing algorithm is introduced to establish system level model , and the basic ideas and working principle is given. In the optimization of system level, the coupling relationship between different subsystems is improved by state accepting function which is embedded in constraint. In this way, abnormal program termination and premature convergence will be avoided and ideal global optimal solution will be achieved effectually. Then the method is proved by used in the optimization design of pendulous micromechanical accelerometer

Finite Element Analysis and Multidisciplinary Design Optimization of Diesel Engine Connecting Rod Based on ISIGHT

Based on the multidisciplinary design optimization method and the MDO software ISIGHT, the 16PA6STC diesel engine connecting rod was taken to the model, used the Pro/engineer software to build the 3D model of connecting rod. The software ANSYS and Nastran was taken to complete the static analysis and modal analysis to get the maximum equivalent stress and the first and second modal frequencies. the software including Pro/Engineer、ANSYS、Nastran, was combined on the ISIGHT to complete the structural optimization work on the condition of restrain the stress and modal of the connecting rod, to explore the application of the MDO design method in the diesel engine connecting rod structure optimization field, offer a reference for the further improvement design study.

Multidisciplinary design optimization for air-condition production system based on multi-agent technique

In order to guarantee the overall production performance of the multiple departments in an air-condition production industry, multidisciplinary design optimization model for production system is established based on the multi-agent technology. Local operation models for departments of plan, marketing, sales, purchasing, as well as production and warehouse are formulated into individual agents, and their respective local objectives are collectively formulated into a multi-objective optimization problem. Considering the coupling effects among the correlated agents, the optimization process is carried out based on self-adaptive chaos immune optimization algorithm with mutative scale. The numerical results indicate that the proposed multi-agent optimization model truly reflects the actual situations of the air-condition production system. The proposed multi-agent based multidisciplinary design optimization method can help companies enhance their income ratio and profit by about 33% and 36%, respectively, and reduce the total cost by about 1.8%.

A New Multidisciplinary Design Optimization Method Accounting for Discrete and Continuous Variables under Aleatory and Epistemic Uncertainties

Abstract Various uncertainties are inevitable in complex engineered systems and must be carefully treated in design activities. Reliability-Based Multidisciplinary Design Optimization (RBMDO) has been receiving increasing attention in the past decades to facilitate designing fully coupled systems but also achieving a desired reliability considering uncertainty. In this paper, a new formulation of multidisciplinary design optimization, namely RFCDV (random/fuzzy/continuous/discrete variables) Multidisciplinary Design Optimization (RFCDV-MDO), is developed within the framework of Sequential Optimization and Reliability Assessment (SORA) to deal with multidisciplinary design problems in which both aleatory and epistemic uncertainties are present. In addition, a hybrid discrete-continuous algorithm is put forth to efficiently solve problems where both discrete and continuous design variables exist. The effectiveness and computational efficiency of the proposed method are demonstrated via a mathematical proble...

Automated multi-objective and multidisciplinary design optimization of a transonic turbine stage

An automated multi-objective and multidisciplinary design optimization (MDO) of a transonic turbine stage to maximize the isentropic efficiency and minimize the maximum stress of the rotor with constraints on mass flowrate and dynamic frequencies is presented in this article. The self-adaptive multi-objective differential evolution (SMODE) algorithm is studied and developed to seek Pareto solutions of the optimization, and a new constraint-handling method based on multi-objective optimization concept is applied for constraint handling. The optimization performance of the presented SMODE is demonstrated using the typical mathematical tests. By applying SMODE as an optimizer and integrating three-dimensional (3D) blade modelling method based on non-uniform B-spline, load-fitting transfer algorithm in parameter space, 3D Navier–Stokes solution technique, and finite element analysis method as well, seven Pareto solutions are obtained. Two Pareto solutions are analysed in detail. One is the highest isentropic efficiency individual, while the other is a compromise between efficiency and mechanical stress in the blade. The aerodynamic performance and strength characteristics of the optimized turbine stage are significantly improved. The analysis results indicate that the presented multi-objective and MDO method has a potential in the optimization of blade performance and can be applied as a promising method for the optimization design of axial turbomachinery blades

Designing Complex Engineered Systems

Designing Complex Engineered Systems

A survey of multidisciplinary design optimization methods in launch vehicle design

Optimal design of launch vehicles is a complex problem which requires the use of specific techniques called Multidisciplinary Design Optimization (MDO) methods. MDO methodologies are applied in various domains and are an interesting strategy to solve such an optimization problem. This paper surveys the different MDO methods and their applications to launch vehicle design. The paper is focused on the analysis of the launch vehicle design problem and brings out the advantages and the drawbacks of the main MDO methods in this specific problem. Some characteristics such as the robustness, the calculation costs, the flexibility, the convergence speed or the implementation difficulty are considered in order to determine the methods which are the most appropriate in the launch vehicle design framework. From this analysis, several ways of improvement of the MDO methods are proposed to take into account the specificities of the launch vehicle design problem in order to improve the efficiency of the optimization process.

Multidisciplinary Design Optimization for Complex Engineered Systems: Report From a National Science Foundation Workshop

Complex engineered systems are typically designed using a systems engineering framework that is showing its limitations. Multidisciplinary design optimization (MDO), which has evolved remarkably since its inception 25 years ago, offers alternatives to complement and enhance the systems engineering approach to help address the challenges inherent in the design of complex engineered systems. To gain insight into these challenges, a one-day workshop was organized that gathered 48 people from industry, academia, and government agencies. The goal was to examine MDO’s current and future role in designing complex engineered systems. This paper summarizes the views of five distinguished speakers on the “state of the research” and discussions from an industry panel comprised of representatives from Boeing, Caterpillar, Ford, NASA Glenn Research Center, and United Technologies Research Center on the “state of the practice.” Future research topics to advance MDO are also identified in five key areas: (1) modeling and the design space, (2) metrics, objectives, and requirements, (3) coupling in complex engineered systems, (4) dealing with uncertainty, and (5) people and workflow. Finally, five overarching themes are offered to advance MDO practice. First, MDO researchers need to engage disciplines outside of engineering and target opportunities outside of their traditional application areas. Second, MDO problem formulations must evolve to encompass a wider range of design criteria. Third, effective strategies are needed to put designers “back in the loop” during MDO. Fourth, the MDO community needs to do a better job of publicizing its successes to improve the “buy in” that is needed to advance MDO in academia, industry, and government agencies. Fifth, students and practitioners need to be better educated on systems design, optimization, and MDO methods and tools along with their benefits and drawbacks.

Multidisciplinary Design Optimization Method and Algorithm Based on iSIGHT

Basing on the introduction of Multidisciplinary Design Optimization (MDO), Multidisciplinary Design Optimization method based on iSIGHT is given, which includes one general process model and one optimization algorithm. Optimization of one bearing is selected as one example. According to its application, it approves that MDO methods can solve practical engineering problems more effectively because of comprehensive consideration of the internal problems in all disciplines.

An Alternative Formulation of Collaborative Optimization Based on Geometric Analysis

Collaborative optimization (CO) is a multidisciplinary design optimization (MDO) method with bilevel computational structure, which decomposes the original optimization problem into one system-level problem and several subsystem problems. The strategy of decomposition in CO is a useful way for solving large engineering design problems. However, the computational difficulties caused by the system-level consistency equality constraints hinder the development of CO. In this paper, an alternative formulation of CO called CO with combination of linear approximations (CLA-CO) is presented based on the geometric analysis of CO, which is more intuitive and direct than the previous algebraic analysis. In CLA-CO, the consistency equality constraints in CO are replaced by linear approximations to the subsystem responses. As the iterative process goes on, more linear approximations are added into the system level. Consequently, the combination of these linear approximations makes the system-level problem gradually approximate the original problem. In CLA-CO, the advantages of the decomposition strategy are maintained while the computational difficulties of the conventional CO are avoided. However, there are still difficulties in applying the presented CLA-CO to problems with nonconvex constraints. The application of CLA-CO to three optimization problems, a numerical test problem, a composite beam design problem, and a gear reducer design problem, illustrates the capabilities and limitations of CLA-CO.

103 積層パラメータを用いたスマート複合材の統合最適設計

A multidisciplinary design optimization method is presented to improve performance of vibration control for smart laminated composites. The smart structure consists of a graphite-epoxy laminated plate and piezoelectric (PZT) actuators. Design variables of the multidisciplinary design optimization method are actuator placements, weight parameters in the H_2 control system, and lamination parameters which describe lay-up configurations of plates in simple form. A genetic algorithm method is employed as an optimizer. The results of the multidisciplinary design optimization agree well with the results of the real-time control experiment, and the present results indicate improved performance in vibration control whey they are compared to the plates composed of typical lay-up configurations.

The Multidisciplinary Design Optimization Methods for Torpedo Shape

The Multidisciplinary Design Optimization Methods for Torpedo Shape

인공신경망 이론을 적용한 3단 축류압축기의 다분야 통합 최적설계

The demands for small, high performance and high loaded aircraft compressor are increased in the world. But the design requirements become increasingly complex to design these high technical engines, the requirement of the design optimization become increased. The optimal design result of several disciplines show different tendencies and nonlinear characteristics of the compressor design, the multidisciplinary design optimization method must be considered in compressor design. Therefore, the artificial Neural Net method is adapted to make the approximation model of 3-stage axial compressor design optimization for considering the nonlinear characteristic. At last, the optimal result of this study is compared to that of previous study.

Implementation and Validation of an Improved Collaborative Optimization Method

Collaborative optimization (CO) is the most widely used Multidisciplinary design optimization (MDO) method for the design of complex engineering system. But some serious computational difficulties are found in its application. Reasons that cause computational difficulties in original CO were analyzed and a new improved collaborative optimization method (ICO) was presented. The L1 norm was used to improve subsystem consistency constraint and to avoid discontinuities in subsystem object function derivatives. Penalty function was added to system-level object function to convert constrained optimization into unconstrained optimization. A quick-start strategy was used to make the best use of optimal solution of system-level optimization in subsystem-level optimization. Experimental results show that the robustness, reliability and computing efficiency of ICO are higher than CO.

On the development of Bi-Level Integrated System Collaborative Optimization

Bi-Level Integrated System Collaborative Optimization (BLISCO) is a new multidisciplinary design optimization (MDO) method based on Bi-Level Integrated System Synthesis (BLISS) and Collaborative Optimization (CO). The key ideas of BLISCO are to replace compatibility constraint with the sum of coupled outputs as an integrated objective of subsystems and to decompose design variables into system design variables and subsystem design variables, while maintaining the collaborative mechanism of CO. One mathematical example and two engineering problems are used to test the effectiveness of BLISCO under the platform of iSIGHTTM. Results from the test cases show that BLISCO has satisfactory convergence, accurate result and reliable robustness.