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Appendix C: The Rocket Development Program
Pages 90-98

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From page 90...
... These efforts are complicated by the following facts: the rocket development program is extremely expensive; only one or two are built and flown, and they are usually destroyed in the process; and the engineers are rarely able to salvage subsystems for reuse in further iterations of the program. Because each system flown is unique, there are few direct performance or reliability data available for parts or subsystems on the test rocket.
From page 91...
... In order to operationalize metrics such as collecting sufficient data, Dying a correct trajectory, and mission success for the RDP, the analyst meets with the project leaders to identify specific goals for the rocket system, to describe an overview of how the rocket would function, and to find out which contractors were responsible for the major areas of the project. For example, flying a correct trajectory involves reaching apogee between 150 and 160 seconds after launch; and collecting sufficient data requires the forward cameras to operate with less than 10 seconds of data loss.
From page 92...
... . ROCKET DEVELOPMENT PROG RAM Z ,_ — iu In | EXPERTS | TEST PROCESS ~ \ ,g, ~ tests ~ | FAILURE | | MODES | 3` 'He | FUNCTIONS | FIGURE C-1 Ontology for RDP.
From page 93...
... Since the qualitative maps are graphical, it is often helpful to develop graphical representations for the quantitative models as well for example, reliability block diagrams, fault trees, and Bayesian networks. The Bayesian network shown
From page 96...
... The heterogeneity of the data requires statistical methodological development to integrate the data and achieve appropriate estimates of uncertainty. The extensive modeling described in previous sections of this report makes explicit where and how the diverse data sources are being used in TABLE C-1 Data Available for RDP Bayesian Network Engineering Judgment · The probability of the motor mount ring failing catastrophically is under .
From page 97...
... support of the analysis. The questions for the statistical analysis are standard: What are the appropriate techniques to combine the available data sources?
From page 98...
... with heterogeneous data sources, the development of a common set of representations has many advantages: the representations provide a common language for all communities to interact with the problem, they can be used to explicitly identify the heterogeneous data sources, and they show an explicit mapping from the problem to the data to the metrics of interest.


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