Date of Award
Doctor of Philosophy
Reza S. Ashtiani
Operation of non-conventional Super Heavy Load (SHL) vehicles is an ongoing challenge for transportation stakeholders and the traveling public across the nation. Despite facilitating the movement of heavy, large, and non-divisible loads, passages of such vehicles with complex loading configurations that typically weigh several folds of the permissible weight limits set forth by regulatory agencies have been adversely affecting the structural integrity of pavement facilities. This translates into accelerated damage of pavement structures, which in turn poses safety concerns for users of the transportation facilities. Accurate quantification of such detrimental impacts is the precursor to preserve the existing transportation facilities. Having an accurate account of SHL effects is also the key step for further incorporation of these non-generic loads into the mechanistic-empirical (ME) pavement design systems. Current procedures commonly deployed by state highway agencies for evaluation of SHLs are primarily empirical in nature and need major overhaul to accommodate taxing loading conditions associated with SHLs. Furthermore, there is a knowledge gap in mechanistic quantification of the damages imparted on pavements by super heavy trucks. Therefore, this study was designed to bridge this gap by identifying the distresses and damage mechanisms pertinent to SHLs.The primary goal of this study was to mechanistically quantify the damages and structural impacts imparted on transportation facilities due to SHL applications. The secondary goal of the research was to synthesize the results to provide further insights on necessary adjustments to upgrade the current ME pavement design protocols for accommodating SHLs. To achieve the research objectives, initially, two comprehensive databases of SHLs in demanding corridors in Texas were developed based on (1) the calibrated axle load spectra data collected by P-WIM units in ten representative sites, and (2) the most recent permit records issued by TxDMV Motor Carrier Division in both Eagle Ford and Permian Basin regions. The research team then developed a methodology for clustering unconventional trucks carrying super heavy loads, and further developed an algorithm for the determination of the number of influencing tires extrapolated outside of the nucleus axle of the multi-axle trailers. Along with the traffic characterization efforts, a series of non-destructive tests such as GPR and FWD was conducted in the field to better understand the structural capacity of pavement sections. Subsequently, the relevant information on traffic loading conditions and site-specific pavement material properties were in turn incorporated in a series of 3D finite element modeling for advanced modeling of moving SHLs to accurately calculate the induced pavement responses under extremely heavy loads. Ultimately, a methodologically sound and robust protocol was devised for the mechanistic characterization of the SHL structural impacts on transportation infrastructure. The devised multi-level approach consists of the following analysis procedures: (1) quantification of pavement damage, (2) prediction of pavement service life, (3) characterization of loss of pavement life, (4) analysis of slow-moving nature of SHLs, (5) analysis of acceleration/deceleration forces, (6) analysis of roadway geometric features, (7) stability analysis of sloped pavement shoulders, and (8) buried utility risk assessment. The multi-tier framework developed in this study consisted of provisions to account for the non-generic nature of super heavy trucks, unique features of the transportation network, site-specific axle load spectra, and climatic factors for realistic assessment of the SHL effects. The numerical simulation results, cross validated by field visual observations and distress records, underscored the significance of SHL vehicles and their role to jeopardize the longevity, structural integrity, and stability of pavement facilities in overload corridors with large volume of heavy truck traffic operations. The analysis of pavement life reduction indicated that operation of SHLs can impart substantial loss of service life as high as 55% for Farm-to-Market (FM) roadways, 33% for State Highways (SH), and 25% for US highways. Furthermore, the results showed that the inclusion of ÃÂ¢??slow-moving natureÃÂ¢?? and ÃÂ¢??acceleration/decelerationÃÂ¢?? of SHLs in the analysis resulted in substantially higher pavement life consumption. It was also found that the accumulated damage under SHLs was more pronounced at horizontal curves with high super-elevation rates. Accordingly, analysis and design protocols of pavements servicing the overload corridors should also manifest such sensitivity to the vehicle speed, SHL dynamics, and roadway geometric features for accurate assessment of the pavement damage and loss of service life. Realistic simulation of tire-pavement interactions is the prelude for proper quantification of the damages imparted by SHLs. The numerical analyses revealed that overlooking the variations of tire-pavement contact stresses during vehicle maneuvering at roadway curved segments or vehicle speeding/braking scenarios at intersections leads to significant underestimation of damages imparted by super heavy loads. Consequently, case-specific contact stresses with non-uniform distribution patterns, in lieu of an all-purpose uniformly distributed load, better represent the taxing stress paths imposed by SHL trailer units. A comprehensive sensitivity analysis showed that increasing the wheel load from 6 kips to 10 kips leads to drastic increase in the imparted damages on pavements by 5-7 times. The results also indicated that operation of SHLs adversely affected FM roads with less robust pavement profile, more than evaluated SH and US highways. The detrimental impact of SHLs was also more pronounced when combined with poor moisture management capabilities under demanding environmental scenarios such as flooding conditions. Similarly, the damages imposed by SHLs during hot summer months were found to be appreciably higher, as compared to cold winter months. Consequently, damage quantification mechanisms for pavement facilities accommodating SHLs should properly account for the synergistic influence of key components such as wheel load magnitude, SHL axle assembly, pavement profile, and climatic conditions for accurate assessment of the pavement distresses. Another noteworthy finding of this study pertains to the potential failure risk of roadway shoulders subjected to SHLs. Based on the parametric analysis results, unpaved shoulders with narrow widths and steep slopes were sensitive to the demanding loading conditions imposed by wide multi-axle trailers. The probabilistic slope stability analysis devised in this study indicated that considerations of the complex and unique nature of SHLs, inherent aleatory variability of influencing parameters, and incorporation of epistemic uncertainties in the slope stability analyses can protect pavement shoulders from failure under SHL movement. The synthesized results of this research can provide insights to improve current protocols for the analysis and design of pavements subjected to taxing loading conditions imposed by SHLs. Additionally, the research findings and risk management heat maps provided in this study facilitate the characterization of the detrimental impacts of non-conventional SHL units on transportation infrastructures in OW networks. The developed color-coded maps can be further instrumental for stakeholders/state DOTs to have a mechanistic means for the approval (or rejection) of SHL permits across overload corridors. The best practice recommendations presented in this study can also guide highway agencies to make provisions of safe traffic passage, and to adopt proper M&R strategies to preserve the transportation infrastructure facilities against expedited deterioration.
Recieved from ProQuest
Morovatdar, Ali, "Structural Impacts of Super Heavy Load (SHL) Vehicles on Transportation Infrastructure" (2021). Open Access Theses & Dissertations. 3437.