Aerospace Science and Technology
Hamid reza Ali mohamadi; Hassan Naseh; Fathollah Ommi
Abstract
The present paper strives for optimization of the Liquid-Propellant Engine (LPE)’s feed system. To this end, the new hybrid meta-model methodology by utilizing the Design of Experiment (DOE) method and the Response Surface Method (RSM) were developed and implemented as two effective means of designing, ...
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The present paper strives for optimization of the Liquid-Propellant Engine (LPE)’s feed system. To this end, the new hybrid meta-model methodology by utilizing the Design of Experiment (DOE) method and the Response Surface Method (RSM) were developed and implemented as two effective means of designing, analyzing and optimizing. The input design variables, constraints, objective function, and their surfaces were identified. Then, the design and development strategy was clarified by utilizing the combination of RSM, DOE and regression analysis. Hence, 64 different experiments were carried out on the RD-253 propulsion system. The response surface curves were drawn and the related objective function equation was obtained. The Analysis of Variance (ANOVA) results indicate that, the developed hybrid model is capable to predict the responses adequately within the limits of input parameters. In addition, the precision of the model was assessed by comparing with the existing samples and the output was interpreted and analyzed that shown highly accuracy. Therefore, desirability function analysis has been applied to LPE’s feed system for achieving to maximize the power and minimize the weight, simultaneously. Finally, confirmatory tests have been conducted with the optimum parametric conditions to validate the optimization techniques. In conclusion, the methodology capability is to optimize the LPE system, an 11% increase in the power to feed system weight ratio and a 2% increase the thrust to engine weight ratio. These values are considerably large for LPE design.
Aerospace Science and Technology
Hassan Naseh; Mehran MirShams; Hamid Reza Fazeley
Abstract
Recently, engineering systems are quite large and complicated. Conceptual design process of Space Transportation Systems (STSs) is a multidisciplinary task which must take into account interactions of various disciplines and analysis codes. Current approach for the conceptual design of STSs requires ...
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Recently, engineering systems are quite large and complicated. Conceptual design process of Space Transportation Systems (STSs) is a multidisciplinary task which must take into account interactions of various disciplines and analysis codes. Current approach for the conceptual design of STSs requires the evaluation of a large number of different configurations and concepts. With existing legacy codes, estimating the performance of all design combinations becomes very time consuming and computationally expensive. A possible solution to this problem could be employing of surrogates during design tasks. This paper describes an effort to optimize the design of an entire STS to achieve a low Earth orbit, consisting of multiple stages using an efficient surrogate-based Multidisciplinary Design Optimization (MDO) framework with the goal of minimizing vehicle weight and ultimately vehicle cost. Furthermore, a combination of Response Surface Methodology (RSM) and Kriging surrogates has been used for building surrogate models. The disciplines of aerodynamics, propulsion, trajectory simulation, geometry, and mass properties, have been integrated to produce an engineering system model of the entire vehicle. In addition, the system model has been validated using the existing design data of STS’s trajectory and their subsystems. For the design optimization, in order to ensure that the payload achieves the desired orbit, a hybrid algorithm has been used to minimize the deference between the actual and desired orbital parameters. The objective function of the optimization problem is to minimize the overall system mass, thus minimizing the system cost per launch. The proposed design and optimization methodology provides designers with an efficient and powerful approach in computation during designing space transportation systems and can also be developed for more complex industrial design problems with comparable characteristics.
