Propulsion
Mohammad Hossein mansouri Moghari; Hassan Naseh; Sahar Noori
Abstract
Accurate solving of complex systems such as spacecraft is very costly and time consuming. By building a surrogate model, the solution time and the cost can be reduced. The closer the surrogate model is to the actual model, the more accurate the solution and the lower the error rate. High-precision successor ...
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Accurate solving of complex systems such as spacecraft is very costly and time consuming. By building a surrogate model, the solution time and the cost can be reduced. The closer the surrogate model is to the actual model, the more accurate the solution and the lower the error rate. High-precision successor models are called metamodels. The basis of producing a high-precision meta-model is to perform high-precision sensitivity analysis with a suitable method. Sensitivity analysis can show the effect of input variables on output variables and produce a surrogate model by eliminating ineffective input variables. Therefore, sensitivity analysis is highly valuable in solving complex systems. The purpose of this article is to analyze the sensitivity of the multidisciplinary design of a monopropellant liquid propulsion system by the Latin Hypercube Sampling method. In this article, the topics related to the liquid monopropellant propulsion system are divided into six parts: High pressure gas tank, liquid fuel tank, injector, decomposition chamber, catalytic bed and nozzle. By determining the input and output variables of each subject, the results of sensitivity analysis are displayed in two ways: the sensitivity of the input variables to the output and the two-by-two correlation of the parameters with each other. In the results, as can be seen, the specific impulse input variable, in the high-pressure gas tank and the liquid fuel tank, has no effect on the output variables. In the injector, the number of grooves, groove angles and fuel tank pressure do not have a significant effect on the output variables. In the decomposition chamber sensitivity analysis diagram, the radius of the granule and for the catalyst bed, in addition to the radius of the granule, the percentage of ammonia decomposition are also ineffective. Finally, the sensitivity analysis for the nozzle shows that the ratio of specific heat has no effect on the output variables
Structure
hassan Naseh; Hadiseh Karimaei; mohammad lesani
Abstract
In this paper, the structural optimization of a space capsule has been discussed by approximating a thin-walled cylindrical shell with a certain length under the axial compression force and constant lateral pressure. Design variables include the outer diameter and cylinder thickness. The purpose of optimization ...
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In this paper, the structural optimization of a space capsule has been discussed by approximating a thin-walled cylindrical shell with a certain length under the axial compression force and constant lateral pressure. Design variables include the outer diameter and cylinder thickness. The purpose of optimization is to minimize the mass and maximize the frequency of the first vibration shape mode of the cylinder. The design constraints include the buckling load multiplier (buckling safety factor) above 1.5 and Von Mises stress below 100 MPa. In this article, first, according to the permissible limits of the design variables, a design of experiment (DOE) and then a sensitivity analysis was carried out to check the sensitivity of the objective functions and constraints to the design variables. After numerically solving the output values with the help of Ansys software and preparing the response surface, the optimal design point has been identified with the help of the two objectives optimization Genetic algorithm. Then, with the numerical simulation of the optimal point, the accuracy of the values obtained from the response surface method was checked and their accuracy was confirmed. The results show that at the selected design point, Von Mises stress becomes less than its allowed value, i.e. 100 MPa, and also the buckling load factor is more than twice its minimum allowed value. However, this point has the smallest distance from the origin and the optimum point has been chosen as the knee point
