NASA Logo

NTRS

NTRS - NASA Technical Reports Server

Back to Results
Application of statistical distribution theory to launch-on-time for space construction logistic supportThe ability to launch-on-time and to send payloads into space has progressed dramatically since the days of the earliest missile and space programs. Causes for delay during launch, i.e., unplanned 'holds', are attributable to several sources: weather, range activities, vehicle conditions, human performance, etc. Recent developments in space program, particularly the need for highly reliable logistic support of space construction and the subsequent planned operation of space stations, large unmanned space structures, lunar and Mars bases, and the necessity of providing 'guaranteed' commercial launches have placed increased emphasis on understanding and mastering every aspect of launch vehicle operations. The Center of Space Construction has acquired historical launch vehicle data and is applying these data to the analysis of space launch vehicle logistic support of space construction. This analysis will include development of a better understanding of launch-on-time capability and simulation of required support systems for vehicle assembly and launch which are necessary to support national space program construction schedules. In this paper, the author presents actual launch data on unscheduled 'hold' distributions of various launch vehicles. The data have been supplied by industrial associate companies of the Center for Space Construction. The paper seeks to determine suitable probability models which describe these historical data and that can be used for several purposes such as: inputs to broader simulations of launch vehicle logistic space construction support processes and the determination of which launch operations sources cause the majority of the unscheduled 'holds', and hence to suggest changes which might improve launch-on-time. In particular, the paper investigates the ability of a compound distribution probability model to fit actual data, versus alternative models, and recommends the most productive avenues for future statistical work.
Document ID
19940004210
Document Type
Conference Paper
Authors
Morgenthaler, George W. (Colorado Univ. Boulder, CO, United States)
Date Acquired
August 16, 2013
Publication Date
October 1, 1989
Publication Information
Publication: First Annual Symposium. Volume 1: Plenary Session
Subject Category
SYSTEMS ANALYSIS
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
Document Inquiry