Reliability Analysis of a Solid Rocket Motor Based on Response Surface Method and Monte Carlo Simulation

2005 ◽  
Author(s):  
Kenan Bozkaya ◽  
Bulent Sumer ◽  
Bayindir Kuran ◽  
Mehmet Ak
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Reliability Analysis ◽  
Response Surface ◽  
Response Surface Method ◽  
Rocket Motor ◽  
Solid Rocket Motor ◽  
Surface Method ◽  
Solid Rocket

Comparison of Monte Carlo Simulation and Response Surface Method by Using ANSYS PDS

2014 ◽  
Vol 578-579 ◽  
pp. 1449-1453
Author(s):  
Chun Xue Song ◽  
Yi Zhang ◽  
Ying Yi Cao
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Reliability Analysis ◽  
Response Surface ◽  
Response Surface Method ◽  
Probabilistic Analysis ◽  
Limit State ◽  
Design System ◽  
State Function ◽  
Surface Method

Monte Carlo Simulation and Response Surface Method are two very powerful reliability analysis methods. Normally, in the reliability analysis of complex structures, the limit state function often can not be expressed in a closed-form. Usually, the codes for probabilistic analysis need to be combined with finite element models. ANSYS Probabilistic Design System (PDS) has provided a package to conduct probabilistic analysis automatically. This paper is going to compare the performance of these methods through an easy engineering problem in ANSYS. The results are going to be derived to show the feature of applying the corresponding reliability methods.

An Approach to Reliability Analysis Using the Response Surface Method and Monte Carlo Simulation

1999 ◽  
Author(s):  
Irfan Kaymaz ◽  
Chris A. McMahon
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Reliability Analysis ◽  
Response Surface ◽  
Response Surface Method ◽  
Actual Performance ◽  
Surface Method ◽  
Analysis System ◽  
Different Response ◽  
Response Surface Function

Abstract It is important in reliability evaluation to take an approach in which the required calculations can be performed efficiently in terms of time and cost. In this study, an approach is proposed whereby reliability analysis is carried out by means of Monte Carlo simulation in which the actual performance function is replaced by a function obtained using the response surface method (RSM). The common approach in the conventional RSM is to use a second-degree polynomial for the response surface function, but in many reliability problems this may not be the best choice. This paper first reviews the approaches and limitations of reliability methods, and then goes on to discuss a method of modelling error when using the response surface method for reliability analysis. It shows the errors obtained for different response functions under different circumstances, and then describes the application of a network-based analysis system to reliability problems.

Optimization Design for Contour of Pintle Nozzle in Solid Rocket Motor Based on Response Surface Method

2014 ◽  
Vol 1016 ◽  
pp. 640-645 ◽  
Author(s):  
Chen Cheng ◽  
Fu Ting Bao ◽  
Hao Xu
Keyword(s):  
Fluid Dynamics ◽  
Response Surface ◽  
Response Surface Method ◽  
Optimization Design ◽  
Specific Impulse ◽  
Rocket Motor ◽  
Shape Parameters ◽  
Solid Rocket Motor ◽  
Surface Method ◽  
Solid Rocket

In aim to gain the capability of providing variable thrust, the technology of an axial pintle inserted into the nozzle of the solid rocket motor had been used. As the pintle inserted into the nozzle, the loss of specific impulse will increase. In order to reduce the loss of fluid dynamics of the pintle nozzle, considering the interaction of the nozzle contour and the pintle contour, CFD method combined with the response surface method is used to optimize the contour of the pintle nozzle. The central composite design is used to introduce a design point; the Kriging algorithm is used to generate the response surface; and the Nonlinear Programming by Quadratic Lagrangian is used for optimization. After the optimization, the loss of fluid dynamics can be reduced significantly. To study the influence of the key parameters to the loss of specific impulse, the key parameters are optimized independently in this paper. It indicates that the main factor of the loss of specific impulse is the parameters of the nozzle. To reduce the computational consumption, the process of optimization has been improved. And the result shows that when optimizing a pintle nozzle, the nozzle part and the pintle part can be optimized separately. The method that bases on the response surface not only takes into account of the interactive effects of the shape parameters, but also works with less calculation. Additionally it maintains the high accuracy and reliability. It can be used to select the optimal shape parameters of the pintle nozzle quickly, which has certain engineering application value.

Robust Thermal Design for Power Device Package Using Response Surface Method and Monte Carlo Simulation

2007 ◽  
Author(s):  
Yasuyuki Yokono ◽  
Katsumi Hisano ◽  
Kenji Hirohata
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Thermal Resistance ◽  
Response Surface ◽  
Response Surface Method ◽  
Thermal Conduction ◽  
Thermal Design ◽  
Power Device ◽  
Design Parameters ◽  
Surface Method

In the present study, the robust thermal design of a power device package was accomplished using thermal conduction calculation, design of experiment, response surface method and Monte Carlo simulation. Initially, the effects of the design parameters on the solder strain were examined in terms of the thermal expansion difference as a result of unsteady thermal conduction simulation. From the factorial effects of design parameters, the design proposals were screened. Then, robustness of the thermal resistance was evaluated for the three design proposals obtained. The thermal resistances were calculated by solving the steady thermal conduction equation under the design of experiment conditions. The solder thickness, the substrate thickness, and the cooling fin performance were considered as the fluctuation factors, assuming the error associated with manufacturing process. Using a response surface method, the values of thermal resistance were expressed as a function of the design variables. The variances of the thermal resistance were examined based on Monte Carlo simulations. Related to the cooling fin design, the Pareto line showing the trade-off relation between the fin dimension and the fan velocity was obtained. By repeating the Monte Carlo simulations, the Pareto solution was calculated so that the thermal resistances satisfy the criteria in the position of 95 percrntile of the thermal resistance variation. Under the same flow velocity conditions, the fin dimensions become about 10% higher compared to the case where the manufacturing error was not taken into account. By carrying out the thermal design following this Pareto line, even if the manufacturing error was taken into consideration, the thermal resistance could satisfy the desired value.

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