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Ahadzie, D K, Proverbs, D G and Olomolaiye, P O (2008) Model for Predicting the Performance of Project Managers at the Construction Phase of Mass House Building Projects. Journal of Construction Engineering and Management, 134(08), 618–29.

Easa, S M and Hossain, K M A (2008) New Mathematical Optimization Model for Construction Site Layout. Journal of Construction Engineering and Management, 134(08), 653–62.

Giritli, H and Civan, I (2008) Personality Study of Construction Professionals in the Turkish Construction Industry. Journal of Construction Engineering and Management, 134(08), 630–4.

Hegazy, T and Menesi, W (2008) Delay Analysis under Multiple Baseline Updates. Journal of Construction Engineering and Management, 134(08), 575–82.

Imriyas, K, Low, S P, Teo, A L and Chan, S L (2008) Premium-Rating Model for Workers’ Compensation Insurance in Construction. Journal of Construction Engineering and Management, 134(08), 601–17.

Kataoka, M (2008) Automated Generation of Construction Plans from Primitive Geometries. Journal of Construction Engineering and Management, 134(08), 592–600.

Koo, D and Ariaratnam, S T (2008) Application of a Sustainability Model for Assessing Water Main Replacement Options. Journal of Construction Engineering and Management, 134(08), 563–74.

Leung, M, Chan, Y and Olomolaiye, P (2008) Impact of Stress on the Performance of Construction Project Managers. Journal of Construction Engineering and Management, 134(08), 644–52.

Leung, M, Chan, Y, Chong, A and Sham, J F (2008) Developing Structural Integrated Stressor–Stress Models for Clients’ and Contractors’ Cost Engineers. Journal of Construction Engineering and Management, 134(08), 635–43.

Walters, R, Jaselskis, E, Zhang, J, Mueller, K and Kaewmoracharoen, M (2008) Using Scanning Lasers to Determine the Thickness of Concrete Pavement. Journal of Construction Engineering and Management, 134(08), 583–91.

  • Type: Journal Article
  • Keywords: Concrete pavements; Thickness; Nondestructive tests; Process control; Quality control; Lasers;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)0733-9364(2008)134:8(583)
  • Abstract:
    Due to limited budgets and reduced inspection staff, state departments of transportation are in need of innovative approaches for providing more efficient quality assurance on concrete paving projects. In Iowa, the current technique is to take core samples of the pavement, which is a labor intensive, destructive process. Due to these limitations, a limited number of cores are used to estimate the pavement thickness. Any method that can reduce or eliminate cores and increase the statistical accuracy of the thickness estimate will be beneficial. One method, which uses a laser to scan the surface of the base prior to paving and then to scan the surface after paving can determine the thickness at any point. Also, scanning lasers provide thorough data coverage that can be used to calculate thickness variance accurately and identify any areas where the thickness is below tolerance. The laser scanning methodology for this study involved the following: (1) investigating characteristics of the paving process; (2) using a laser scanner on three different sites; (3) processing the data to create clean surface models; (4) performing statistical analyses to determine thickness variability; and (5) summarizing the results.