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On-Line, Self-Learning, Predictive Tool for Determining Payload Thermal ResponseThis paper will present the results of a joint ManTech / Goddard R&D effort, currently under way, to develop and test a computer based, on-line, predictive simulation model for use by facility operators to predict the thermal response of a payload during thermal vacuum testing. Thermal response was identified as an area that could benefit from the algorithms developed by Dr. Jeri for complex computer simulations. Most thermal vacuum test setups are unique since no two payloads have the same thermal properties. This requires that the operators depend on their past experiences to conduct the test which requires time for them to learn how the payload responds while at the same time limiting any risk of exceeding hot or cold temperature limits. The predictive tool being developed is intended to be used with the new Thermal Vacuum Data System (TVDS) developed at Goddard for the Thermal Vacuum Test Operations group. This model can learn the thermal response of the payload by reading a few data points from the TVDS, accepting the payload's current temperature as the initial condition for prediction. The model can then be used as a predictive tool to estimate the future payload temperatures according to a predetermined shroud temperature profile. If the error of prediction is too big, the model can be asked to re-learn the new situation on-line in real-time and give a new prediction. Based on some preliminary tests, we feel this predictive model can forecast the payload temperature of the entire test cycle within 5 degrees Celsius after it has learned 3 times during the beginning of the test. The tool will allow the operator to play "what-if' experiments to decide what is his best shroud temperature set-point control strategy. This tool will save money by minimizing guess work and optimizing transitions as well as making the testing process safer and easier to conduct.
Document ID
20000120475
Acquisition Source
Goddard Space Flight Center
Document Type
Conference Paper
Authors
Jen, Chian-Li
(ManTech International Corp. Fairfax, VA United States)
Tilwick, Leon
(ManTech International Corp. Fairfax, VA United States)
Date Acquired
August 19, 2013
Publication Date
October 1, 2000
Publication Information
Publication: Twenty-first Space Simulation Conference: The Future of Space Simulation Testing in the 21st Century
Subject Category
Ground Support Systems And Facilities (Space)
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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