Hybrid search multi-discipline feasible design optimization of a typical Space Launch Vehicle

Bataleblu, Ali Asghar; Roshanian, Jafar

doi:10.1109/rast.2015.7208388

Cited by 2 publications

(3 citation statements)

References 16 publications

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“…Environment routines use 1962 U.S. Standard atmosphere model and this model is an appropriate model that can be used for conceptual design. 18 An appropriate polynomial equation 5and a parametric pitch rate program are employed as the first stage and second stage offline guidance program, respectively (see Figure 11)…”

Section: Trajectory Estimation Modulementioning

confidence: 99%

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A novel metamodel management strategy for robust trajectory design of an expendable launch vehicle

Roshanian

Bataleblu

2019

Proceedings of the Institution of Mechanical Engineers, Part G:

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Uncertainty-based design optimization has been widely acknowledged as an advanced methodology to address competing objectives of aerospace vehicle design, such as reliability and robustness. Despite the usefulness of uncertainty-based design optimization, the computational burden associated with uncertainty propagation and analysis process still remains a major challenge of this field of study. The metamodeling is known as the most promising methodology for significantly reducing the computational cost of the uncertainty propagation process. On the other hand, the nonlinearity of the uncertainty-based design optimization problem's design space with multiple local optima reduces the accuracy and efficiency of the metamodels prediction. In this article, a novel metamodel management strategy, which controls the evolution during the optimization process, is proposed to alleviate these difficulties. For this purpose, a combination of improved Latin hypercube sampling and artificial neural networks are involved. The proposed strategy assesses the created metamodel accuracy and decides when a metamodel needs to be replaced with the real model. The metamodeling and metamodel management strategy are conspired to propose an augmented strategy for robust design optimization problems. The proposed strategy is applied to the multiobjective robust design optimization of an expendable launch vehicle. Finally, based on non-dominated sorting genetic algorithm-II, a compromise between optimality and robustness is illustrated through the Pareto frontier. Results illustrate that the proposed strategy could improve the computational efficiency, accuracy, and globality of optimizer convergence in uncertainty-based design optimization problems.

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Section: Trajectory Estimation Modulementioning

confidence: 99%

“…Trajectory optimization has been applied to aerospace vehicles ranging from rockets to aircraft. 18 The problem can be simply stated as the determination of an ascent phase trajectory for an LV that satisfies specified initial, path (i.e. during the flight) and terminal conditions.…”

Section: Introductionmentioning

confidence: 99%

A novel metamodel management strategy for robust trajectory design of an expendable launch vehicle

Roshanian

Bataleblu

2019

Proceedings of the Institution of Mechanical Engineers, Part G:

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“…Environment routines use Standard atmosphere model and this model is the most accurate and perfect model that can be used for conceptual design. 53 The translational motion equations in body frame (equation (4)) are numerically integrated (4th order Runge-Kutta) from initial state conditions to the injection condition.…”

Section: Trajectory Simulation Modulementioning

confidence: 99%

Robust ascent trajectory design and optimization of a typical launch vehicle

Roshanian

Bataleblu

2018

Proceedings of the Institution of Mechanical Engineers, Part C:

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Robustness and reliability of the designed trajectory are crucial for flight performance of launch vehicles. In this paper, robust trajectory design optimization of a typical LV is proposed. Two formulations of robust trajectory design optimization problem using single-objective and multi-objective optimization concept are presented. Both aleatory and epistemic uncertainties in model parameters and operational environment characteristics are incorporated in the problem, respectively. In order to uncertainty propagation and analysis, the improved Latin hypercube sampling is utilized. A comparison between robustness of the single-objective robust trajectory design optimization solution and deterministic design optimization solution is illustrated using probability density functions. The multi-objective robust trajectory design optimization is executed through NSGA-II and a set of feasible design points with a good spread is obtained in the form of Pareto frontier. The final Pareto frontier presents a trade-off between two conflicting objectives namely maximizing injection robustness and minimizing gross lift-off mass of launch vehicle. The resulted Pareto frontier of the multi-objective robust trajectory design optimization shows that with 1% increase in gross mass, the robustness of the design point to the considered uncertainties can be increased about 80%. Also, numerical simulation results show that the multi-objective formulation is a necessary approach to achieve a good trade-off between optimality and robustness.

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Hybrid search multi-discipline feasible design optimization of a typical Space Launch Vehicle

Cited by 2 publications

References 16 publications

A novel metamodel management strategy for robust trajectory design of an expendable launch vehicle

A novel metamodel management strategy for robust trajectory design of an expendable launch vehicle

Robust ascent trajectory design and optimization of a typical launch vehicle

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