Traditionally, two methods have been commonly used for in-situ asphalt mixture density measurement: laboratory testing on field-extracted cores and in-situ nuclear gauge testing. ii EXCUTIVE SUMMARY In-situ asphalt mixture density is critically important to the performance of flexible airport pavements: density that is too high, or too low, may cause early pavement distresses. This paper does not constitute a standard, specification, or regulation. The research was conducted at the Advanced Transportation Research and Engineering Laboratory (ATREL) at the University of Illinois at Urbana-Champaign. The contents do not necessarily reflect the official views or policies of the CEAT or FAA. The contents of this study reflect the views of the authors, who are responsible for the facts and the accuracy of the data presented herein. The FAA project was conducted in cooperation with the Center of Excellence for Airport Technology (CEAT) and the University of Illinois at Urbana-Champaign. This report is based on the results of an FAA project, Nondestructive Testing and Evaluation (NDTE) Technologies for Airport Pavement Acceptance and Quality Assurance Activities. Keywords-Airfield pavements, ANN, backcalculation, new generation aircraft The changes in ANN-based backcalculated pavement moduli with trafficking were used to compare the relative severity effects of the aircraft landing gears on the NAPTF test pavements. The synthetic database generated using an advanced non-linear pavement finite-element program was used to train the ANN to overcome the limitations associated with conventional pavement moduli backcalculation. In this study, a multi-layer, feed-forward network which uses an error-backpropagation algorithm was trained to approximate the HWD backcalculation function. HWD tests were periodically conducted at the Federal Aviation Administration’s (FAA’s) National Airport Pavement Test Facility (NAPTF) to monitor the effect of Boeing 777 (B777) and Beoing 747 (B747) test gear trafficking on the structural condition of flexible pavement sections.
The elastic moduli of the individual pavement layers backcalculated from the HWD deflection profiles are effective indicators of layer condition and are used for estimating the pavement remaining life. The HWD test is one of the most widely used tests for routinely assessing the structural integrity of airport pavements in a non-destructive manner. Abstract-This paper describes the use of artificial neural networks (ANN) for predicting non-linear layer moduli of flexible airfield pavements subjected to new generation aircraft (NGA) loading, based on the deflection profiles obtained from Heavy Weight Deflectometer (HWD) test data.
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