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A Method for Calculating the Probability of Successfully Completing a Rocket Propulsion Ground TestPropulsion ground test facilities face the daily challenges of scheduling multiple customers into limited facility space and successfully completing their propulsion test projects. Due to budgetary and schedule constraints, NASA and industry customers are pushing to test more components, for less money, in a shorter period of time. As these new rocket engine component test programs are undertaken, the lack of technology maturity in the test articles, combined with pushing the test facilities capabilities to their limits, tends to lead to an increase in facility breakdowns and unsuccessful tests. Over the last five years Stennis Space Center's propulsion test facilities have performed hundreds of tests, collected thousands of seconds of test data, and broken numerous test facility and test article parts. While various initiatives have been implemented to provide better propulsion test techniques and improve the quality, reliability, and maintainability of goods and parts used in the propulsion test facilities, unexpected failures during testing still occur quite regularly due to the harsh environment in which the propulsion test facilities operate. Previous attempts at modeling the lifecycle of a propulsion component test project have met with little success. Each of the attempts suffered form incomplete or inconsistent data on which to base the models. By focusing on the actual test phase of the tests project rather than the formulation, design or construction phases of the test project, the quality and quantity of available data increases dramatically. A logistic regression model has been developed form the data collected over the last five years, allowing the probability of successfully completing a rocket propulsion component test to be calculated. A logistic regression model is a mathematical modeling approach that can be used to describe the relationship of several independent predictor variables X(sub 1), X(sub 2),..,X(sub k) to a binary or dichotomous dependent variable Y, where Y can only be one of two possible outcomes, in this case Success or Failure. Logistic regression has primarily been used in the fields of epidemiology and biomedical research, but lends itself to many other applications. As indicated the use of logistic regression is not new, however, modeling propulsion ground test facilities using logistic regression is both a new and unique application of the statistical technique. Results from the models provide project managers with insight and confidence into the affectivity of rocket engine component ground test projects. The initial success in modeling rocket propulsion ground test projects clears the way for more complex models to be developed in this area.
Document ID
20040086566
Acquisition Source
Stennis Space Center
Document Type
Preprint (Draft being sent to journal)
Authors
Messer, Bradley P.
(NASA Stennis Space Center Stennis Space Center, MS, United States)
Date Acquired
August 21, 2013
Publication Date
January 5, 2004
Subject Category
Spacecraft Propulsion And Power
Report/Patent Number
EB-2003-12-00007-SSC
Meeting Information
Meeting: 24th AIAA Aerodynamic Measurement Technology and Ground Testing Conference
Location: Portland, OR
Country: United States
Start Date: June 28, 2004
End Date: July 1, 2004
Sponsors: American Inst. of Aeronautics and Astronautics
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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