Multi-modular design optimization and multidisciplinary design optimization

2015 ◽  
Vol 3 (2/3) ◽  
pp. 156-170
Author(s):  
Amirhossein Adami ◽  
Mahda Mortazavi ◽  
Mehran Nosratollahi
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Modular Design ◽  
Estimation Error ◽  
Propulsion System ◽  
Performance Estimation ◽  
System Level ◽  
Multidisciplinary Design ◽  
Mass Model ◽  
Content Type

Purpose – For complex engineering problems, multidisciplinary design optimization (MDO) techniques use some disciplines that need to be run several times in different modules. In addition, mathematical modeling of a discipline can be improved for each module. The purpose of this paper is to show that multi-modular design optimization (MMO) improves the design performances in comparison with MDO technique for complex systems. Design/methodology/approach – MDO framework and MMO framework are developed to optimum design of a complex system. The nonlinear equality and inequality constrains are considered. The system optimizers included Genetic Algorithm and Sequential Quadratic Programming. Findings – As shown, fewer design variables (optimization variables) are needed at the system level for MMO. Unshared variables are optimized in the related module when shared variables are optimized at the system level. The results of this research show that MMO has lower elapsed times (14 percent) with lower F-count (16 percent). Practical implications – The monopropellant propulsion upper-stage is selected as a case study. In this paper, the efficient model of the monopropellant propulsion system is proposed. According to the results, the proposed model has acceptable accuracy in mass model (error < 2 percent), performance estimation (error < 6 percent) and geometry estimation (error < 10 percent). Originality/value – The monopropellant propulsion system is broken down into the three important modules including propellant tank (tank and propellant), pressurized feeding (tank and gas) and thruster (catalyst, nozzle and catalysts bed) when chemical decomposition, aerothermodynamics, mass and configuration, catalyst and structure have been considered as the disciplines. The both MMO and MDO frameworks are developed for the monopropellant propulsion system.

Multidisciplinary design optimization using knowledge management applied to an electronic throttle

2020 ◽  
Vol 39 (2) ◽  
pp. 353-362 ◽  
Author(s):  
Mehdi Mcharek ◽  
Toufik Azib ◽  
Moncef Hammadi ◽  
Cherif Larouci ◽  
Jean-Yves Choley
Keyword(s):  
Knowledge Management ◽  
Design Optimization ◽  
Design Process ◽  
Multidisciplinary Design Optimization ◽  
Setting Time ◽  
Multidisciplinary Design ◽  
Electronic Throttle ◽  
Content Type ◽  
Industrial Environment ◽  
Design Cycle

Purpose Within the current industrial context, companies aim to decrease the design process time and cost. The multidisciplinary design optimization (MDO) appears as a solution to accelerate the process and support designers in different stages of the design cycle. However, this relatively new concept needs to be integrated efficiently in the industrial environment and issues related to collaboration, data management, traceability and reuse need to be overcome. Design/methodology/approach The aim of this work is to efficiently integrate the MDO in the industrial design cycle by means of knowledge management (KM) techniques. To take into account the industrial environment, the methodology was applied in a collaborative software. Findings An example of collaborative design and optimization of an electronic throttle body (ETB) controller is presented with industrial requirements. The design problem was solved successfully and demonstrates the efficiency of the methodology in collaborative environments. Originality/value The contributions of this work lie in the structuration of the knowledge to support MDO and the definition of a general way to connect the existent MDO tools to the knowledge base. This methodology will enable to freely link different steps of the design process and reduce considerably the setting time of MDO in industries.

Application of Multidisciplinary Design Optimization to a Resource Satellite

2012 ◽  
Vol 195-196 ◽  
pp. 1066-1077
Author(s):  
Wen Rui Wu ◽  
Hai Huang ◽  
Bei Bei Wu
Keyword(s):  
Design Optimization ◽  
System Design ◽  
Multidisciplinary Design Optimization ◽  
Research Work ◽  
Thermal Control ◽  
Satellite System ◽  
Collaborative Optimization ◽  
System Level ◽  
Multidisciplinary Design ◽  
Satellite Mission

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.

Multidisciplinary Design Optimization on Conceptual Design of Aero-engine

2016 ◽  
Vol 33 (2) ◽  
Author(s):  
Xiao-bo Zhang ◽  
Zhan-xue Wang ◽  
Li Zhou ◽  
Zeng-wen Liu
Keyword(s):  
Design Optimization ◽  
Conceptual Design ◽  
Multidisciplinary Design Optimization ◽  
System Level ◽  
Multidisciplinary Design ◽  
Design Stage ◽  
Surface Model ◽  
Coupled Problem ◽  
Aero Engine ◽  
Integrated Performance

AbstractIn order to obtain better integrated performance of aero-engine during the conceptual design stage, multiple disciplines such as aerodynamics, structure, weight, and aircraft mission are required. Unfortunately, the couplings between these disciplines make it difficult to model or solve by conventional method. MDO (Multidisciplinary Design Optimization) methodology which can well deal with couplings of disciplines is considered to solve this coupled problem. Approximation method, optimization method, coordination method, and modeling method for MDO framework are deeply analyzed. For obtaining the more efficient MDO framework, an improved CSSO (Concurrent Subspace Optimization) strategy which is based on DOE (Design Of Experiment) and RSM (Response Surface Model) methods is proposed in this paper; and an improved DE (Differential Evolution) algorithm is recommended to solve the system-level and discipline-level optimization problems in MDO framework. The improved CSSO strategy and DE algorithm are evaluated by utilizing the numerical test problem. The result shows that the efficiency of improved methods proposed by this paper is significantly increased. The coupled problem of VCE (Variable Cycle Engine) conceptual design is solved by utilizing improved CSSO strategy, and the design parameter given by improved CSSO strategy is better than the original one. The integrated performance of VCE is significantly improved.

A Multidisciplinary Design Optimization Approach to Relating Affordability and Performance in a Conceptual Submarine Design

2010 ◽  
Vol 26 (04) ◽  
pp. 273-289 ◽  
Author(s):  
N. Vlahopoulos ◽  
C. G. Hart
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Geometric Model ◽  
Multidisciplinary Optimization ◽  
System Level ◽  
Multidisciplinary Design ◽  
Manufacturing Cost ◽  
Optimization Approach ◽  
And Performance ◽  
The Impact

A multidisciplinary design optimization (MDO) framework is used for a conceptual submarine design study. Four discipline-level performances—internal deck area, powering, maneuvering, and structural analysis—are optimized simultaneously. The four discipline-level optimizations are driven by a system level optimization that minimizes the manufacturing cost while at the same time coordinates the exchange of information and the interaction among the discipline-level optimizations. Thus, the interaction among individual optimizations is captured along with the impact of the physical characteristics of the design on the manufacturing cost. A geometric model for the internal deck area of a submarine is created, and resistance, structural design, and maneuvering models are adapted from theoretical information available in the literature. These models are employed as simulation drivers in the discipline-level optimizations. Commercial cost-estimating software is leveraged to create a sophisticated, automated affordability model for the fabrication of a submarine pressure hull at the system level. First, each one of the four discipline optimizations and also the cost-related top level optimization are performed independently. As expected, five different design configurations result, one from each analysis. These results represent the "best" solution from each individual discipline optimization, and they are used as reference for comparison with the MDO solution. The deck area, resistance, structural, maneuvering, and affordability models are then synthesized into a multidisciplinary optimization statement reflecting a conceptual submarine design problem. The results from this coordinated MDO capture the interaction among disciplines and demonstrate the value that the MDO system offers in consolidating the results to a single design that improves the discipline-level objective functions while at the same time produces the highest possible improvement at the system level.

Performance Measure Approach Based Multidisciplinary Design Optimization of Gear Transmission

2013 ◽  
Vol 694-697 ◽  
pp. 868-871
Author(s):  
Jun Zhang ◽  
Bing Zhang
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Performance Measure ◽  
Collaborative Optimization ◽  
Gear Transmission ◽  
System Level ◽  
Multidisciplinary Design ◽  
Engineering Systems ◽  
Performance Measure Approach ◽  
Design Cost

In order to reduce the influence of uncertainties on complicated engineering systems performance, a new method is proposed based on the performance measure approach and collaborative optimization (PMA-CO) to implement the reliability-based multidisciplinary design optimization of gear transmission. Both the mathematical model and procedures of PMA-CO are presented. With the adoption of slack factors in the system-level of collaborative optimization, both CO and PMA-CO are applied to the optimization of gear transmission. The proposed PMA-CO improves the reliability of the gear transmission and gained a tradeoff solution between design cost and reliability. Therefore, the PMA-CO is effective and practical in engineering design.

Improved Multidisciplinary Design Optimization Based on Genetic Algorithm and Artificial Neural Networks and Its Application

2016 ◽  
Vol 13 (10) ◽  
pp. 6501-6508
Author(s):  
Yi Su ◽  
Fa-Yin Wang ◽  
Jian-Yu Zhao
Keyword(s):  
Genetic Algorithm ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Computational Cost ◽  
System Level ◽  
Multidisciplinary Design ◽  
Local Optimum ◽  
Artificial Neural

Multidisciplinary Design Optimization (MDO) is an algorithm widely used in the engineering field currently. However, traditional MDO often leads to the failure of convergence or local optimum problems caused by convergence. In such cases, a multidisciplinary design optimization based on genetic algorithm (GA) and artificial neural networks (ANN) (GA-ANN-MDO) is presented in the paper. Under the thought of parallel distribution of traditional MDO, the real sub-disciplinary model is replaced by a highly precise ANN model dependent on the Latin Hypercube experimental design method in the GA-ANN-MDO, so as to reduce the computational cost and smooth the value noise. The GA optimization system level is applied to decline the possibility of partial solution involved in the optimization. As shown from the optimization results of two classic mathematical examples, GA-ANN-MDO is presented good robustness, which could quickly and effectively converge to the global optimal solution. In addition, a project example was employed finally to verify the feasibility of GA-ANN-MDO in the engineering.

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