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A research study evaluating piezoelectric sensors used for collecting Weigh-in-Motion (WIM) data is summarized. The evaluation was sponsored by the Highway Innovative Technology Evaluation Center and consisted of testing the WIM sensors under controlled laboratory and fieldloading conditions in both asphalt concrete (AC) and portland cement concrete (PCC) pavements. The field evaluation of piezoelectric WIM sensors is emphasized. The AC installation was performed at the WesTrack test facility near Reno, Nevada, and the PCC installation was performed at a California Department of Transportation (Caltrans) Heavy Vehicle Simulator test site near Palmdale, California. In addition, a compatibility study of the response of the WIM sensors with different data acquisition systems was conducted at the WesTrack facility. Also, various types of grouts were used in the WIM installations. Results indicated that WIM sensor performance was most dependent on the ability of data acquisition systems to process the raw sensor output accurately.

Modern pavement rehabilitation and design methodologies require an adequate evaluation of the functional capacity of pavements. A key component of this functional capacity is the roughness of the pavement. The current standard for characterization of a pavement’s roughness is the international roughness index (IRI). Pavement roughness measurements were conducted at regular intervals during the application of approximately 5 million equivalent single-axle loads at the WesTrack Project, a full-scale flexible pavement accelerated loading facility located near Reno, Nevada. The results are presented of an investigation into the relationship between pavement roughness and pavement surface distress using WesTrack data. With a sample population of 317 observations, a relationship was found among the roughness (IRI) and the initial IRI, percentage of fatigue cracking, and average rut depth. A test of the relationship with data collected as a part of the Long-Term Pavement Performance Program indicates favorable results.

Resilient modulus is a critical material property required for the characterization of pavement layers used in modern mechanistic-based pavement design. Because of its fundamental nature, resilient modulus provides a meaningful basis for simulating the effect that an individual layer has on pavement response and performance. Resilient modulus can be determined by laboratory testing or by an analytical procedure known as backcalculation involving the interpretation of nondestructive testing. Unfortunately, resilient modulus results determined from laboratory testing and those determined from backcalculation generally do not agree. The issue of characterizing in situ moduli is addressed by presenting the results of an analysis and comparison of resilient modulus values determined from laboratory testing and those established through backcalculation of falling weight deflectometer (FWD) data from the WesTrack experiment in northern Nevada. These two basic methodologies for resilient modulus determination are reviewed, and many of their known weaknesses and limitations are identified. The backcalculated modulus values were determined using Washington State Department of Transportation’s EVERCALC computer program and FWD data obtained from WesTrack pavement sections at the onset of truck loading. The laboratory-based resilient modulus values were determined using a combination of test results on remolded and recompacted WesTrack materials and the KENLAYER computer program to estimate the modulus under the state of stress created by the FWD during testing. The results of this investigation continue to support the suspicion that significant differences do exist between resilient moduli determined from backcalculation and those determined through laboratory testing. Accordingly, some general observations are made concerning possible improvements in each methodology and concerning which of the two methodologies is better suited for a thorough pavement evaluation and design process. Overall, a better understanding of the problems associated with accurately characterizing pavement support under in-situ conditions is presented.

The development and implementation of a remedial program usually is a costly process. Available scientific and engineering data should be used to optimize the investigation program which will lead to the development of a cost-effective remedial action. As part of the scope of the Remedial Investigation (RI), the data needs and significance of the key parameters as related to the final remedial design should be assessed and determined to obtain necessary data in a timely and cost-effective manner. Properly verified groundwater computer models are powerful tools for both identifying data gaps which must be filled before an appropriate design can be prepared and for assessing the significance of site features on the problem and solution. These models can be used effectively during both the RI and Feasibility Study (FS) phases. In the RI phase, the models can be used for optimization of field and laboratory testing programs and in data analysis to assess adequateness of the field investigation and provide basic data for