Deflection bowl parameters for falling weight deflectometer testing: data collection and threshold benchmarking

References

• AASHTO, 2012. Pavement Management guide, Second edition. Washington, DC: American Association of State Highway and Transportation Officials.
   Google Scholar
• arrb, 2005. Sealed Roads Best Practice Guide. Vermont South, VIC: The Australian Road Research Board.
   Google Scholar
• Aschuri, I., 2004. The stiffness modulus of asphalt concrete for design life prediction of pavement under tropical condition. Proceeding The 1st PhD Seminar on Civil Engineering. http://lib.itenas.ac.id/kti/?p=1659
   Google Scholar
• Bryce, J., et al., 2013. Developing a network-level structural capacity index for asphalt pavements. Journal of Transportation Engineering, 139 (2), 123–129.
   Google Scholar
• Drenth, K., et al., 2020. LCMS-2 Measurements of the quality of road markings. In: Raab C. (eds) Proceedings of the 9th International Conference on Maintenance and Rehabilitation of Pavements—Mairepav9. Lecture Notes in Civil Engineering (Vol. 76 Cham: Springer.
   Google Scholar
• Federal Aviation Administration (FAA), 2011. Use of non-destructive Testing in the Evaluation of Airport Pavements. In: Micheal J. (eds) Advisory Circular AC 150/5370-11B, 1-86. Washington, DC: Federal Aviation Administration. https://www.faa.gov/documentLibrary/media/Advisory_Circular/150_5370_11b.pdf.
   Google Scholar
• Federal Aviation Administration (FAA), 2014. Standardised method of reporting airport pavement strength - PCN. In: Micheal J. (eds) Advisory circular AC 150/5335-5C, 1-113. Washington, DC: Federal Aviation Administration. https://www.faa.gov/documentlibrary/media/advisory_circular/150-5335-5c.pdf.
   Google Scholar
• Flora, W.F., 1969. Development of a structural index for pavement management: An exploratory analysis [Purdue University, West Lafayette, Indiana]. In Purdue University.
   Google Scholar
• Fuentes, L., et al., 2020. A probabilistic approach to detect structural problems in flexible pavement sections at network level assessment. International Journal of Pavement Engineering.
   Web of Science ®Google Scholar
• Garg, N. and Thompson, M.R., 1998. Mechanistic-empirical evaluation of the Mn/road low volume road test sections. https://rosap.ntl.bts.gov/view/dot/15578.
   Google Scholar
• Haa, R., Hudson, W.R., and Falls, L. C., 2015. Pavement Asset Management. Beverly, MA: Scrivener Publishing LLC.
   Google Scholar
• Highways England, 2001. Design Manual for Roads and Bridges - Volume 7 Pavement design and maintenance (Vol. 2, Issue August 1999).
   Google Scholar
• Hoffman, M.S., 1980. Mechanistic interpretation of non-destructive pavement testing deflections [University of Illinois at Urbana-Champaign]. https://www.proquest.com/docview/303016812?pq-origsite=gscholar&fromopenview=true.
   Google Scholar
• Horak, E., 1987. Aspects of Deflection Basin Parameters Used in a Mechanistic Rehabilitation Design Procedure for Flexible Pavements in South Africa [University of Pretoria]. In University of Pertoria, Pertoria, PhD Publication. https://repository.up.ac.za/handle/2263/23960.
   Google Scholar
• Horak, E, 2008. Benchmarking the structural condition of flexible pavements with deflection bowl parameters. Journal of the South African Institution of Civil Engineering, 50 (2), 2–9.
   Web of Science ®Google Scholar
• Horak, E., Emery, S., and Maina, J., 2015. Review of falling weight deflectometer deflection benchmark analysis on roads and airfield. In: Conference on asphalt pavement for South Africa (CAPSA-2015).
   Google Scholar
• Hubert, M. and Vandervieren, E, 2008. An adjusted boxplot for skewed distributions. Computational Statistics & Data Analysis, 52 (12), 5186–5201.
   Web of Science ®Google Scholar
• J. W. Tukey, 1977. Exploratory Data Analysis. In Addison-Wesley, Reading, MA. http://www.jstor.org/stable/2529486.
   Google Scholar
• Kilareski, W.P. and Anani, B.A., 1982. Evaluation of in-situ moduli and pavement life from deflection basins. In: Proceedings ofthe fifth International Conference on the structural design of asphalt pavements held deflt University of Technology, 349–366.
   Google Scholar
• Kuna, K. and Kelly, K., 2019. Flexible pavement design for hot climates – a case study. Proceedings of the Institution of Civil Engineers - Transport, 172 (3), 164–173.
   Web of Science ®Google Scholar
• LTA, 2019. Standard details of Road Elements: Chapter 1 Pavement of Road. Land Transport Authorithy Singapore. https://www.lta.gov.sg/content/dam/ltagov/upcoming_projects/SDRE/Revised/SDRE14-1_PAV_1-5-MAY_2019.pdf.
   Google Scholar
• Lukanen, E.O., et al., 2000. Temperature Predictions and Adjustment Factors for Asphalt Pavement (No. FHWA-RD-98-085) (Issue June). Turner-Fairbank Highway Research Center. https://www.fhwa.dot.gov/publications/research/infrastructure/pavements/ltpp/fwdcd/index.cfm#toc.
   Google Scholar
• Mabrouk, G.M., et al., 2022. Using ANN modeling for pavement layer moduli backcalculation as a function of traffic speed deflections. Construction and Building Materials, 315.
   Web of Science ®Google Scholar
• Mehta, Y. and Roque, R, 2003. Evaluation of FWD data for determination of layer moduli of pavements. Journal of Materials in Civil Engineering, 15 (1), 25–31.
   Web of Science ®Google Scholar
• Mosale Ramanath, A., et al., 2020. Benchmarking Falling Weight Deflectometer deflection bowl parameters: Case study for Indian conditions and the applications to rehabilitation design. Journal of Transportation Engineering, Part B: Pavements, 146 (3), 05020003.
   Web of Science ®Google Scholar
• Nguyen, T., Lechner, B., and Yiik Diew, W, 2019. Response-based methods to measure road surface irregularity: a state-of-the-art review. European Transport Research Review, 11, 43.
   Web of Science ®Google Scholar
• NguyenDinh, N., 2016. Precast ultra-thin whitetopping (PUTW) in Singapore and its application for electrified roadways. In: Technische Universität München (eds) PhD Dissertation, 1-151. Munich, Germany: Technische Universität München. https://mediatum.ub.tum.de/node?id=1296505.
   Google Scholar
• Pereira, P., and Pais, J, 2017. Main flexible pavement and mix design methods in Europe and challenges for the development of an European method. Journal of Traffic and Transportation Engineering (English Edition), 4 (4), 316–346.
   Google Scholar
• Pierce, L.M., et al., 2017. Using Falling Weight Deflectometer Data with Mechanistic-Empirical Design and Analysis, volume 3 (No. FHWA-HRT-16-011) (Vol. 2, Issue November). USA: Federal Highway Administration.
   Google Scholar
• Pszczola, M, 2019. Equivalent temperature for design of asphalt pavements in Poland. MATEC Web of Conferences, 262, 05010.
   Google Scholar
• Rabbi, M.F. and Mishra, D, 2021. Using FWD deflection basin parameters for network-level assessment of flexible pavements. International Journal of Pavement Engineering, 22 (2), 147–161.
   Web of Science ®Google Scholar
• Rada, G.R., et al., 2016. Pavement structural evaluation at the network level: Final Report (No. FHWA-HRT-15-074) (Issue September, p. 286p). United States: Federal Highway Administration.
   Google Scholar
• Rakesh, N., et al., 2006. Artificial neural networks—genetic algorithm based model for backcalculation of pavement layer moduli. International Journal of Pavement Engineering, 7 (3), 221–230.
   Google Scholar
• Saleh, M., 2015. Multi-scale criteria for structural capacity evaluation of flexible pavements at network level. In: Transportation Research Board 94th annual meeting. Washington DC, United States.
   Google Scholar
• SANRAL, 2014. The South African Pavement Engineering Manual (SAPEM): Chapter 10 Pavement Design (Issue 2). South African National Road Agency SOC Limited.
   Google Scholar
• Schwertman, N.C., Owens, M.A., and Adnan, R., 2004. A simple more general boxplot method for identifying outliers. Computational Statistics & Data Analysis, 47 (1), 165–174.
   Web of Science ®Google Scholar
• Sharma, S. and Das, A, 2008. Backcalculation of pavement layer moduli from falling weight deflectometer data using an artificial neural network. Canadian Journal of Civil Engineering, 35 (1), 57–66.
   Web of Science ®Google Scholar
• Smith, K. D., et al., 2017. Using falling weight deflectometer data with mechanistic-empirical design and analysis, volume I: Final Report (No. FHWA-HRT-16-009). In: Federal highway administration: Vol. I (Issue march). USA: Federal Highway Administration.
   Google Scholar
• Tan, J. Y., et al., 2022. Automatic pavement crack rating for network-level pavement management system. In: H.R Pasind et al., eds. Road and airfield pavement technology. Lecture notes in civil engineering. vol. 193. Cham: Springer. doi:10.1007/978-3-030-87379-0_6.
   Google Scholar
• Weligamage, J., Piyatrapoomi, N., and Gunapala, L, 2010. Traffic speed deflectometer: Queensland trial. In Queensland Roads (Issue), 9.
   Google Scholar
• Xu, B., Ranjithan, S. R., and Kim, Y. R, 2002. New relationships between falling weight deflectometer deflections and asphalt pavement layer condition indicators. Transportation Research Record: Journal of the Transportation Research Board, 1806, 48–56.
   Google Scholar
• Zhang, Z., et al., 2003. Development of a New methodology for characterizing pavement structural condition for network-level applications. In Federal Highway Administration (Vol. 7, Issue 100).
   Google Scholar