Comparison of Setting Time Measured Using Ultrasonic Wave Propagation with Saw-Cutting Times on Pavements, TR-675, 2015

At present, there is little fundamental guidance available to assist contractors in choosing when to schedule saw cuts on joints. To conduct pavement finishing and sawing activities effectively, however, contractors need to know when a concrete mixture is going to reach initial set, or when the sawing window will open. Previous research investigated the use of the ultrasonic pulse velocity (UPV) method to predict the saw-cutting window for early entry sawing. The results indicated that the method has the potential to provide effective guidance to contractors as to when to conduct early entry sawing. The aim of this project was to conduct similar work to observe the correlation between initial setting and conventional sawing time. Sixteen construction sites were visited in Minnesota and Missouri over a two-year period. At each site, initial set was determined using a p-wave propagation technique with a commercial device. Calorimetric data were collected using a commercial semi-adiabatic device at a majority of the sites. Concrete samples were collected in front of the paver and tested using both methods with equipment that was set up next to the pavement during paving. The data collected revealed that the UPV method looks promising for early entry and conventional sawing in the field, both early entry and conventional sawing times can be predicted for the range of mixtures tested.

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.

Seismic Wave Velocity as a Means of In-Place Density Measurement, Part 1, HR-114

Velocity-density tests conducted in the laboratory involved small 4-inch diameter by 4.58-inch-long compacted soil cylinders made up of 3 differing soil types and for varying degrees of density and moisture content, the latter being varied well beyond optimum moisture values. Seventeen specimens were tested, 9 with velocity determinations made along two elements of the cylinder, 180 degrees apart, and 8 along three elements, 120 degrees apart. Seismic energy was developed by blows of a small tack hammer on a 5/8-inch diameter steel ball placed at the center of the top of the cylinder, with the detector placed successively at four points spaced 1/2-inch apart on the side of the specimen involving wave travel paths varying from 3.36 inches to 4.66 inches in length. Time intervals were measured using a model 217 micro-seismic timer in both laboratory and field measurements. Forty blows of the hammer were required for each velocity determination, which amounted to 80 blows on 9 laboratory specimens and 120 blows on the remaining 8 cylinders. Thirty-five field tests were made over the three selected soil types, all fine-grained, using a 2-foot seismic line with hammer-impact points at 6-inch intervals. The small tack hammer and 5/8-inch steel ball was, again, used to develop seismic wave energy. Generally, the densities obtained from the velocity measurements were lower than those measured in the conventional field testing. Conclusions were reached that: (1) the method does not appear to be usable for measurement of density of essentially fine-grained soils when the moisture content greatly exceeds the optimum for compaction, and (2) due to a gradual reduction in velocity upon aging, apparently because of gradual absorption of pore water into the expandable interlayer region of the clay, the seismic test should be conducted immediately after soil compaction to obtain a meaningful velocity value.