EVALUATION OF DEFLECTION DATA CONSISTENCY FROM LWD MEASUREMENT

Currently, LWD (Light Weight Deflectometer) has been developed in Indonesia that is used to measure the characteristics of flexible pavement on low-volume road. To be able to reliably be used as a tool for evaluating pavement structures, the LWD must have a good level of precision and be sensitive e...

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Bibliographic Details
Main Author: Chaliqi Taufiq, Luthfi
Format: Theses
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/46804
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Institution: Institut Teknologi Bandung
Language: Indonesia
Description
Summary:Currently, LWD (Light Weight Deflectometer) has been developed in Indonesia that is used to measure the characteristics of flexible pavement on low-volume road. To be able to reliably be used as a tool for evaluating pavement structures, the LWD must have a good level of precision and be sensitive enough so that it can read changes in the pavement characteristics in the field due to changes in environmental factors such as temperature changes. This study examines the consistency of deflection data from LWD measurements on several factors such as differences in pavement temperature, differences in survey load levels, differences in operators, and differences in the pavement characteristics tested. It also examine the effect of the level of deflection data variation on the variation of the characteristics of the pavement modulus values generated using a particular method. Data was collected by a certain number of repetitions at three points in the field test segment three times a day with a time interval of ± 10 hours to assess variations in data on pavement temperature differences. The same test configuration is repeated using a different level of load. One set of tests was designed to be carried out by two operators so that the effect of different operators on the variation of data can be assessed. From the research conducted it was concluded that differences in temperature, level of survey loads, and operators did not significantly influence the level of data variation.