Investigation of Deterioration of Joints in Concrete Pavements , TPF-5(224), 2012

Premature deterioration of concrete at the joints in concrete pavements and parking lots has been reported across the northern states. The distress is first observed as shadowing when microcracking near the joints traps water, later exhibiting as significant loss of material. Not all roadways are distressed, but the problem is common enough to warrant attention. The aim of the work being conducted under this and parallel contracts was to improve understanding of the mechanisms behind premature joint deterioration and, based on this understanding, develop training materials and guidance documents to help practitioners reduce the risk of further distress and provide guidelines for repair techniques. While work is still needed to understand all of the details of the mechanisms behind premature deterioration and prevention of further distress, the work in this report has contributed to advancing the state of knowledge.

Durability Study of Type II Cements, MLR-71-03 and R-247, 1971

A study of type II cements at the Iowa State Highway Commission concluded that the amount of tricalcium aluminate in the cement appears to have an inverse effect on concrete durability. This conclusion agrees with the results of the Kansas Highway Department's study to determine the combination of cement and aggregate which would produce the best possible durability factor. This study is a result of the questions raised following the completion of the project at the Iowa State Highway Commission. This project is being conducted on a larger scale so. that more definite conclusions can be drawn. The purpose of this project is to determine if the amount of tricalcium aluminate in type II cements has an inverse effect on the durability of concrete.

Development of Asphalt Dynamic Modulus Master Curve Using Falling Weight Deflectometer Measurements, TR-659

The asphalt concrete (AC) dynamic modulus (|E*|) is a key design parameter in mechanistic-based pavement design methodologies such as the American Association of State Highway and Transportation Officials (AASHTO) MEPDG/Pavement-ME Design. The objective of this feasibility study was to develop frameworks for predicting the AC |E*| master curve from falling weight deflectometer (FWD) deflection-time history data collected by the Iowa Department of Transportation (Iowa DOT). A neural networks (NN) methodology was developed based on a synthetically generated viscoelastic forward solutions database to predict AC relaxation modulus (E(t)) master curve coefficients from FWD deflection-time history data. According to the theory of viscoelasticity, if AC relaxation modulus, E(t), is known, |E*| can be calculated (and vice versa) through numerical inter-conversion procedures. Several case studies focusing on full-depth AC pavements were conducted to isolate potential backcalculation issues that are only related to the modulus master curve of the AC layer. For the proof-of-concept demonstration, a comprehensive full-depth AC analysis was carried out through 10,000 batch simulations using a viscoelastic forward analysis program. Anomalies were detected in the comprehensive raw synthetic database and were eliminated through imposition of certain constraints involving the sigmoid master curve coefficients. The surrogate forward modeling results showed that NNs are able to predict deflection-time histories from E(t) master curve coefficients and other layer properties very well. The NN inverse modeling results demonstrated the potential of NNs to backcalculate the E(t) master curve coefficients from single-drop FWD deflection-time history data, although the current prediction accuracies are not sufficient to recommend these models for practical implementation. Considering the complex nature of the problem investigated with many uncertainties involved, including the possible presence of dynamics during FWD testing (related to the presence and depth of stiff layer, inertial and wave propagation effects, etc.), the limitations of current FWD technology (integration errors, truncation issues, etc.), and the need for a rapid and simplified approach for routine implementation, future research recommendations have been provided making a strong case for an expanded research study.