The current bridge formula, Federal Bridge Formula B (BFB), established in 1974 to protect bridges against excessive overstress, is very restrictive on long combination vehicles due to an 80,000 lb gross vehicle weight limit. Without this limit the formula will not be able to protect bridges in the cases of longer trucks. A formula developed by the Texas Transportation Institute (T.T.I.) called the TTI-HS20 Formula addresses these issues. This formula, developed especially for bridges designed for the HS-20 truck, eliminates the need for the 80,000 lb limit. A generic formula developed to protect H15 and HS-20 bridges (James et al., 1986) was evaluated in a previous study (James and Zhang, 1991). The approach to evaluating the TTI-HS20 Formula follows the approach outlined in James and Zhang, 1991. Information was collected on two important elements: a set of test bridges representative of the lightest continuous bridges, and a set of test truck configurations representative of real truck traffic with a focus on long combination vehicles. Critical weights of the selected trucks for the representative bridges are calculated and plotted against the TTI-HS 20 formula and other proposed formulas. A final recommendation as to whether this formula should be adopted nationwide is made.

This research evaluates four options to produce quality axle load data for pavement design: piezoelectric WIM sites (corrected and uncorrected data), static weigh scales, and a piezo-quartz WIM site. The evaluation applies four data quality principles: data validity, spatial coverage, temporal coverage, and data availability. While all principles are considered, the research contributes in the development and application of an integrated and sequential approach to assess data validity of the options by performing analyses to determine the precision and accuracy of axle load measurements. Within the context of Manitoba, the evaluation reveals that data produced by piezo-quartz and static weigh scales have superior validity, with piezo-quartz data offering better temporal coverage, data availability, and future geographic coverage. Ultimately, the selection of the best option for providing quality axle load data depends on the relative importance of data quality principles for producing data supporting sound pavement designs and infrastructure management decisions. / May 2017