The Aircraft Classification Number/Pavement Classification Number (ACN/PCN) method has been adopted by the International Civil Aviation Organization (ICAO) as the standard for reporting airfield pavement bearing strength.Although it has been clearly recommended that the engineer should simultaneously consider the mean and standard deviation in the selection of an evaluation or design input value, many evaluation and design procedures currently only use the mean value in the analysis (AC 150/5370-11A). This study will first illustrate its definitions, possible applications, and potential problems in arriving at a consistent and repeatable value based on theresults of nondestructive testing. A goodness study of the existing backcalculation results using the Long-Term Pavement Performance (LTPP) database was conducted. For a more conservative evaluation and design approach, the mean value minus one standard deviation (or the so-called 85% confidence level) may be used for obtaining evaluation or design inputs in general (AC 150/5320-6D). Nevertheless, it was found that this proposed procedure is not based on sound statistical principles especially when its probability distribution function of the population is almost always unknown. In engineering practice, a subset of the population or a random sample is oftencollected to represent the population characteristics of interest. Consequently, the concepts of random sampling, central limit theorem, and confidence intervals for hypothesis testing were adopted. It was proposed that asingle representative design input for the entire runway pavement be determined by the lower limit of 95% confidence level (1-tail) to derive a more consistent and repeatable PCN value. A case study was conducted to illustrate the potential problems of the existing ACN/PCN procedures and the benefits of the proposed revisions.
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