Reliability Based Design Optimization of A Solid Rocket Motor Using Surrogate Models

2007 ◽  
Author(s):  
Bayindir Kuran
Keyword(s):  
Design Optimization ◽  
Surrogate Models ◽  
Rocket Motor ◽  
Solid Rocket Motor ◽  
Reliability Based Design Optimization ◽  
Reliability Based Design ◽  
Solid Rocket

Efficient Global Surrogate Modeling for Reliability-Based Design Optimization

2012 ◽  
Vol 135 (1) ◽  
Author(s):  
Barron J. Bichon ◽  
Michael S. Eldred ◽  
Sankaran Mahadevan ◽  
John M. McFarland
Keyword(s):  
Global Optimization ◽  
Design Optimization ◽  
Reliability Analysis ◽  
Optimization Problem ◽  
Wide Spectrum ◽  
Surrogate Models ◽  
Efficient Global Optimization ◽  
Test Problems ◽  
Reliability Based Design Optimization ◽  
Reliability Based Design

Determining the optimal (lightest, least expensive, etc.) design for an engineered component or system that meets or exceeds a specified level of reliability is a problem of obvious interest across a wide spectrum of engineering fields. Various formulations and methods for solving this reliability-based design optimization problem have been proposed, but they typically involve accepting a tradeoff between accuracy and efficiency in the reliability analysis. This paper investigates the use of the efficient global optimization and efficient global reliability analysis methods to construct surrogate models at both the design optimization and reliability analysis levels to create methods that are more efficient than existing methods without sacrificing accuracy. Several formulations are proposed and compared through a series of test problems.

Reliability Based Design Optimization Using a Single Constraint Approximation Point

2011 ◽  
Vol 133 (3) ◽  
Author(s):  
Tomas Dersjö ◽  
Mårten Olsson
Keyword(s):  
Design Optimization ◽  
Solid Mechanics ◽  
Surrogate Models ◽  
Computational Effort ◽  
Fe Model ◽  
Reliability Based Design Optimization ◽  
Reliability Based Design ◽  
Constrained Problems ◽  
Single Constraint ◽  
Starting Point

The computational effort for reliability based design optimization (RBDO) is no longer prohibitive even for detailed studies of mechanical integrity. The sequential approximation RBDO formulation and the use of surrogate models have greatly reduced the amount of computations necessary. In RBDO, the surrogate models need to be most accurate in the proximity of the most probable point. Thus, for multiply constrained problems, such as fatigue design problems, where each finite element (FE)-model node constitutes a constraint, the computational effort may still be considerable if separate experiments are used to fit each constraint surrogate model. This paper presents an RBDO algorithm that uses a single constraint approximation point (CAP) as a starting point for the experiments utilized to establish all surrogate models, thus reducing the computational effort to that of a single constraint problem. Examples of different complexities from solid mechanics applications are used to present the accuracy and versatility of the proposed method. In the studied examples, the ratio of the computational effort (in terms of FE-solver calls) between a conventional method and the single CAP algorithm was approximately equal to the number of constraints and the introduced error was small. Furthermore, the CAP-based RBDO is shown to be capable of handling over 10,000 constraints and even an intermittent remeshing. Also, the benefit of considering other objectives than volume (mass) is shown through a cost optimization of a truck component. In the optimization, fatigue-specific procedures, such as shot peening and machining to reduce surface roughness, are included in the cost as well as in the constraints.

Solid Rocket Motor Design Optimization Using Genetic Algorithm

2014 ◽  
Vol 905 ◽  
pp. 502-506 ◽  
Author(s):  
Fredy M. Villanueva ◽  
Lin Shu He ◽  
Da Jun Xu
Keyword(s):  
Genetic Algorithm ◽  
Design Optimization ◽  
Optimal Solution ◽  
Optimization Method ◽  
Rocket Motor ◽  
Design Parameters ◽  
Optimization Approach ◽  
Solid Rocket Motor ◽  
Conceptual Design Phase ◽  
Solid Rocket

A design optimization approach of a solid propellant rocket motor is considered. A genetic algorithm (GA) optimization method has been used. The optimized solid rocket motor (SRM) is intended to use as a booster of a flight vehicle, and delivering a specific payload following a predefined prescribed trajectory. Sensitivity analysis of the optimized solution has been conducted using Monte Carlo method to evaluate the effect of uncertainties in design parameters. The results show that the proposed optimization approach was able to find the convergence of the optimal solution with highly acceptable value for conceptual design phase.

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