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60 CHAPTER 4 CONCLUSIONS This research project developed the recommended method- ology for estimating bridge network costs as a result of truck weight limit changes. A software module implementing the methodology has also been developed. This methodologyâs targeted users are state transportation agencies in the United States. However, federal and local agencies may also find it useful. Four cost impact categories are covered in this method- ology, because their cost impact is found to be quantifiable based on the current state of knowledge. However, when the agency wishes to add other cost impact categories based on its experience, the recommended methodology and the soft- ware have a flexible structure to accept such an addition. Thus, the recommended methodology can be improved with increase of knowledge in related areas. The methodology has been designed to be flexible to meet the needs of various agencies, in terms of its required data input. A set of default data is also provided to facilitate application. The procedure of the recommended methodology is pre- sented in Appendix A along with a set of default data, and the concept of the methodology is presented in Chapter 3. Two application examples of the methodology are presented in Appendix B for illustration. The attachments include the soft- ware module and its users manual, which can stand alone with- out this report for routine application. The manual has a chap- ter of tutorial including Scenario 2 of the Idaho example and the Michigan example, as illustration examples. The following conclusions can be drawn based on the results of this research effort. 1. Based on the two examples of application for the rec- ommended methodology and previous research results, the cost impact category for deficient existing bridges is likely the dominant contributor to the total cost impact of a change in truck weight limits. This is mainly because there are no general effective methods to strengthen existing bridges for increasing the load rat- ings. The possible options of replacement and posting plus enforcement both could be costly. 2. The current AASHTO fatigue truck model is found valid based on the current WIM data used. The model can be still valid under the considered scenario of legalizing the 3S3 configuration for a GVW of 431 kN (97 kips) because the envisioned 3S3 configurations are similar to the AASHTO fatigue truck model. Thus this conclusion can be extended to that if the considered scenario legal- izes truck types similar to the AASHTO truck model (i.e., typical 3S2 configurations); that model would still be valid for steel fatigue assessment. 3. The models for assessing structural material fatigue (for both steel components and reinforced concrete decks) have more uncertainty than the strength assessing mod- els. Essentially it is because fatigue accumulation largely depends on microscopic original discontinuities and acquired damages, which are randomly distributed in location and severity. Predicting failure originating from such sources is inherently involved with notable uncer- tainty. Thus, more research work is recommended to reduce the uncertainty in the modeling and prediction. Such effort should focus on modeling loading, because it plays a dominant role, due to the loadâs higher pow- ered term (cubic power for steel fatigue and the close to 18th power for the reinforced concrete deck fatigue). This also includes predicting the available strength of the material (e.g., shear capacity Pu for RC decks), the stress range for steel members subjected to out-of-plane bending, etc. 4. Wheel loads have a very significant effect on RC deck fatigue accumulation, according to the fatigue model introduced herein. This result has important implica- tions to wheel load limit development and enforcement. More research is recommended to better understand the mechanism of RC deck deterioration due to combined efforts of load and steel corrosion.
