S. Khodadadiyan; R. Farokhi; D. Ramesh
Volume 7, Issue 2 , July 2014, , Pages 75-83
Abstract
The aim of the paper is to describe a methodology of damage detection in the liquid propellant engine which is based on artificial neural networks in combination with stochastic analysis. It is assumed that the liquid propellant engine have faulty data collection system. Then a filtering algorithm for ...
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The aim of the paper is to describe a methodology of damage detection in the liquid propellant engine which is based on artificial neural networks in combination with stochastic analysis. It is assumed that the liquid propellant engine have faulty data collection system. Then a filtering algorithm for elimination perturbation data has been applied .The damage is defined as fuel and oxidizer channels clogging up. The key stone of the method is feed-forward multi layer network with back propagation algorithm. It is impossible to obtain appropriate training set for real engine, therefore stochastic analysis using mathematical model is carried out and dynamic simulation is made to get training set virtually. Engine channels clogging up leads to unwanted variation of pressure, flow rate of oxidizer and fuel and other main parameters of engine. Then variations considered as best input data for damage detection. The methodology was carried out using laboratory test.
H. R. Ali Mohammadi; D. Ramesh; M. R. Heidary; R. Farrokhi; H. Karimi
Volume 6, Issue 3 , October 2013, , Pages 1-13
Abstract
In this paper, a particular propulsion system including, liquid rocket engine, fuel and oxidizer tank and related pressurizing system, have been surveyed. The procedure is based on a nonlinear mathematical model which has been simulated in Matlab Simulation environment. In propulsion systems, identifying ...
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In this paper, a particular propulsion system including, liquid rocket engine, fuel and oxidizer tank and related pressurizing system, have been surveyed. The procedure is based on a nonlinear mathematical model which has been simulated in Matlab Simulation environment. In propulsion systems, identifying system performance is essential, because if we can accept ability describe the dynamic behavior of the system components in nominal and transient regimes, we can reduce the associated costs during design and development. Following, results of Propulsion system hot test are compared with model that shows acceptable accuracy of simulator code. In addition to leading research, how to use this model to identify the causes of failure is shown. Match analysis and compatibility testing, after disassembling objective observations show considerable performance model for similar applications.
H. R. Ali Mohammady; D. Ramesh; M. R. Heidary; R Farrokhi; H. Karimi
Volume 6, Issue 1 , April 2013, , Pages 11-19
Abstract
Providing of sufficient input pressure of pumps is Pressurizing system tank mission. In structure of objective propulsion system, pressurizing system of fuel tank is hot gas kind that is feeding with engine which caused of operation relational. In this paper, interaction of pressurizing system of fuel ...
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Providing of sufficient input pressure of pumps is Pressurizing system tank mission. In structure of objective propulsion system, pressurizing system of fuel tank is hot gas kind that is feeding with engine which caused of operation relational. In this paper, interaction of pressurizing system of fuel tank and liquid rocket engine has been surveyed. Objective system consists of four main subsystems: liquid rocket engine, fuel tank, gas mixer and pipes. The procedure is based on a nonlinear mathematical model that dynamically describes operation of favorite system by regard to interaction of subsystems. Then all of the equations have been simulated in Matlab Simulation environment. Finally, results of propulsion system hot test are compared with model that shows acceptable accuracy of simulator code.
