400 Appendix B.   Consolidated Validity Evaluations f or RWA IV Datasets f or Orbital IV Values   The CMG program data has several specific attributes as well as deficiencies  listed below:   1) it measured effects (spin- axis reorientations) with established bases in HST RWA I V data,   2) it is a large enough body of data to provide valid statistical insights (where available and relevant for  the specific effect being addressed), and   3) it is similar enough to the HST RWA design and contemporaneous configuration to provide applicable or extrapolate- able data and/or insights .    1) it does not directly address all variation effects sought,   2) it only measures effects on the radial direction 1.0 harmonic ( i.e., unbalance/asymmetry) so inferences  are needed for estimating effects on other harmonics and directions,   3) CMG program is classified, so it is limits access to analyze in a more detailed quantitative fashion data directly obtained; therefore, reliance turns towards supplier expertise and overall extrapolated guidelines from that database, and   4) CMG  is not purely  identical to the HST RW A design/configuration, creating some added uncertainty for  full validity of applyin g extrapolations and engineering judgments.   The high value for accumulated CMG program data is to allow assessment of dataset variatio n due to:    1) change in spin- axis orientation in a 1- g gravitational field,   2) change from 1- g ambient to 0- g (or microgravity) orbital force field,   3) change from 1- atmosphere ambient to vacuum external -internal housing pressures, and   4) change from 70 deg F ambi ent to 50- 90 degree F orbital operating temperatures .   Although the CMG data collected is the most  relevant data available, it has noted constraints/caveats  for  directly -appli cable data sought due to gaps  in some key areas ( i.e., no higher -ratio harmonics).   A) HST RWA Ac ceptance Test Procedure (ATP) I V test dataset collection is most directly applicable to  the issue ( i.e., design similarity), possessing the following attributes to allow investigating  variabilities/causes:    1) it is precisely measured data on flight configured and realistically -tested RWAs,   2) it is a relatively large consistently -controlled sampling, implying decent statistical validity, and   3) it manifests negligible influence from some effects which alter I V outp ut (e.g., wide swings in  temperature or stress distribution changes during the test intervals).   It also has the following specific deficiencies :    1) each RWA is subjected to environmental exposures (random vibration or thermal -vacuum tests)  between I V tests , so different dataset curve val ues solely due to fundamental I V test -to-test variations  cannot be separately accounted for, and   2) amount of datasets for each RWA (3- 4 typically, a lone exception being 6 on RWA 1004), is not  sufficiently large for very high statistical significance if scatter is large (sometimes occurred).   The predominant value for I V test data collected is to provide the assessment basis for variations due to:    1) inherent RWA -to-RWA unit variation ( i.e., determining which RWA will generally produce more or less  jitter relative to another or the average, and how different the jitter variation would be),   2) test-to-test variations caused by inherent randomness and/or test setup/method limitations, and   3) test-to-test variations caused by exposure t o environmental test conditions ( i.e., Random Vibration and  Thermal -Vacuum) plus inter -test handling/transport (believed to be much less significant).   The major restriction to more effective use of this body of data for m ore precise evaluation is that there is  no definitive method for separating the last two effects:  no data has been taken on an RWA without  havin g both effects present;  data scatter from both effects is notable . 

Acknowledgements  

The author gratefully acknowledges  support and encouragement  from SMEs  and colleagues,  specifically  Gary Beals, Eugene Skelton, Stu Loewenthal, Larry McGovern, Gary Goble, Rob Peabody, Ed Boesiger,  Jon Kirschenbaum, and Tara Somerday.