of the subsurface systems were given smaller scores because of the inherent 

 complications in positioning the loads once they were on the bottom. A 

 weighting factor of two is felt appropriate for this measure of system 

 effectiveness. 



The values of the figures of merit and system dependability were 

 subjectively estimated on an arbitrary scale of 1 to 10. The higher the value 

 the better the system meets TDP standards and/or standards set by the design 

 team. A score of 5 indicates that a system does not have any apparent 

 strong or weak points in that particular category. It is important to 

 emphasize that this procedure is a measure of the levels of confidence 

 associated with the selection criteria. 



In this study, the rate of increase in favorable evidence with 

 expenditures of time and effort is the equivalent of confidence that a design 

 is physically realizable and operationally acceptable. The more favorable 

 the evidence, the higher the level of confidence that can be assigned to a 

 concept. The purpose of the analysis discussed is to put the levels of 

 confidence into a quasi-quantitative framework and to force the participants 

 of the design team to specify factors which they consider important. This 

 approach or something similar to it is the only way the systems can be 

 compared. While some uncertainty remains for all of the confidence 

 measures, it will remain until the system is built and tested. The numbers, 

 then, are really subjective confidence measures that help establish the 

 relative ranking of the alternative systsms based on the evidence accrued on 

 the advantages, benefits, and liabilities of each system's operational and 

 structural qualities. 



Costs 



The cost analysis of a system is one of the major sources of 

 uncertainty. This is unfortunate since the financial feasibility of a system 

 is ultimately the factor with the greatest control in planning future system 

 configuration. This fact is particularly true in this study because the levels 

 of effectiveness of the candidates are similar in many respects. 



Variations in the accuracy of cost estimates can be attributed to 

 differences in cost analyses, errors in the basic data, errors in extrapolation, 

 and similar factors. 



While uncertainties about major article costs are by no means 

 trivial, the uncertainties about system specifications and operating assump- 

 tions are, at this point in time, deserving of careful scrutiny. Thus, some 

 time and effort were alloted during the course of this study to assure that all 

 possible, yet realistic, variations of a candidate system's functional 



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