A summary of the data obtained from the Mayport inspection is 

 presented in Table 9. From these data it is apparent that most of the 

 facilities were overinspected when even a 98-percent confidence level 

 was desired. Only three sections of the facility required more samples 

 than were available from the data collected (bulkhead C1-B3 at the mean 

 water line and the small boat berth at both the mean water and midwater 

 inspection elevations). For each of the other facilities and elevations, 

 the number of samples taken exceeded the requirement by a factor of from 

 3 to 10. 



A Chi-square analysis of the data was attempted. However, it was 

 found that there were insufficient data at each elevation of the various 

 facilities to allow an accurate prediction of the type of distribution 

 that would best fit the entire population. 



RECOMMENDED SAMPLING PROCEDURES 



The St. Helena and Mayport inspections contributed valuable information 

 regarding the inspection of timber piers and steel sheet piles using statis- 

 tical samples. The results of statistical analysis on the measurement data 

 confirmed certain assumptions and refined sampling procedures . The assump- 

 tion that the pile diameters can be modeled using the normal distribution 

 was confirmed using the Chi-square test on the larger sample sets from the 

 St. Helena inspection. 



The sampling procedure requires the following steps to be performed 

 in the planning and execution of an underwater inspection for a timber 

 structure: 



1. Identify the structure to be inspected and determine the type 

 of materials used in construction and other related factors, such as age 

 of the structure and repair and replacement history information. 



2. Establish a critical structural measurement parameter (such as 

 the effective piling diameter) to be used as a measure of the condition 

 of the structure. 



3. Determine if an attribute parameter will be recorded as pertnent 

 to this type of structure (e.g., borer activity for timber structures). 

 This attribute will be recorded and the percentage level will be predicted. 



4. Identify the maintenance and repair criteria. An example is a 

 set of remaining-area percentages used to designate the type of remedial 

 action to be taken. 



5. Specify the precision and confidence levels for the inspection. 

 The selection of this controlling parameter is dependent upon economic 

 as well as mission requirements and structural factors. For attribute 

 sampling a confidence level of 95 percent with a precision of ±10 percent 

 normally will be adequate. For variables sampling, the initial selection 

 of these parameters should be based on structural and mission requirements 

 as shown in the table below. It can then be modified based on economic 

 constraints imposed by the available funding. 



38 



