A probabilistic approach to detect structural problems in flexible pavement sections at network level assessment

Presently, most of the road agencies use Non-Destructive (NDT) tools to help them prioritise pavement maintenance and rehabilitation (M&R) activities at the network level, thus optimising the limited budgetary resources. One of the most widely used NDT techniques for pavement structural evaluati...

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Autores:: Fuentes, Luis
Taborda, Katherine
Hu, Xiaodi
Horak, Emile
Bai, Tao
Walubita, Lubinda F

Tipo de recurso:: Article of journal

Fecha de publicación:: 2020

Institución:: Corporación Universidad de la Costa

Repositorio:: REDICUC - Repositorio CUC

Idioma:: eng

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repository_id_str
dc.title.spa.fl_str_mv	A probabilistic approach to detect structural problems in flexible pavement sections at network level assessment
title	A probabilistic approach to detect structural problems in flexible pavement sections at network level assessment
spellingShingle	A probabilistic approach to detect structural problems in flexible pavement sections at network level assessment falling weight deflectometer deflection bowl parameters logistic model regression pavement rehabilitation non destructive testing
title_short	A probabilistic approach to detect structural problems in flexible pavement sections at network level assessment
title_full	A probabilistic approach to detect structural problems in flexible pavement sections at network level assessment
title_fullStr	A probabilistic approach to detect structural problems in flexible pavement sections at network level assessment
title_full_unstemmed	A probabilistic approach to detect structural problems in flexible pavement sections at network level assessment
title_sort	A probabilistic approach to detect structural problems in flexible pavement sections at network level assessment
dc.creator.fl_str_mv	Fuentes, Luis Taborda, Katherine Hu, Xiaodi Horak, Emile Bai, Tao Walubita, Lubinda F
dc.contributor.author.spa.fl_str_mv	Fuentes, Luis Taborda, Katherine Hu, Xiaodi Horak, Emile Bai, Tao Walubita, Lubinda F
dc.subject.spa.fl_str_mv	falling weight deflectometer deflection bowl parameters logistic model regression pavement rehabilitation non destructive testing
topic	falling weight deflectometer deflection bowl parameters logistic model regression pavement rehabilitation non destructive testing
description	Presently, most of the road agencies use Non-Destructive (NDT) tools to help them prioritise pavement maintenance and rehabilitation (M&R) activities at the network level, thus optimising the limited budgetary resources. One of the most widely used NDT techniques for pavement structural evaluations, at the network level assessment, is the Falling Weight Deflectometer (FWD). Using a database comprising of a wide array of typical layer moduli and thicknesses of traditional flexible pavements, that were generated based on multiple Monte Carlo numerical simulations, as a reference datum, this study successfully developed probabilistic models that allow for analysing the condition of a flexible pavement, at the network level, from FWD surface deflection data, namely the Deflection Bowl Parameters (DBPs), to identify which layers of the pavement structure present a probability of structural failure or damage.
publishDate	2020
dc.date.issued.none.fl_str_mv	2020-10-09
dc.date.accessioned.none.fl_str_mv	2021-03-10T19:33:46Z
dc.date.available.none.fl_str_mv	2021-03-10T19:33:46Z
dc.date.embargoEnd.none.fl_str_mv	2021-11-09
dc.type.spa.fl_str_mv	Artículo de revista
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dc.identifier.doi.spa.fl_str_mv	https://doi.org/10.1080/10298436.2020.1828586
dc.identifier.instname.spa.fl_str_mv	Corporación Universidad de la Costa
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url	https://hdl.handle.net/11323/7987 https://doi.org/10.1080/10298436.2020.1828586 https://repositorio.cuc.edu.co/
identifier_str_mv	Corporación Universidad de la Costa REDICUC - Repositorio CUC
dc.language.iso.none.fl_str_mv	eng
language	eng
dc.relation.references.spa.fl_str_mv	AASHTO, 1993. AASHTO guide for design of pavement structures 1993. Washington, DC: American 7 Association of State Highway and Transportation Officials. Abudinen, D., Fuentes, L., and Carvajal, J., 2017. Travel quality assessment of Urban Roads based on International roughness Index: case study in Colombia. Transportation Research Record: Journal of the Transportation Research Board, 2612 (1), 1–10. Adams, J. and Kim, R., 2014. Mean profile depth analysis of field and laboratory traffic-loaded chip seal surface treatments. International Journal of Pavement Engineering, 15 (7), 645–656. Alkasawneh, W., 2007. Backcalculation of pavement moduli using genetic algorithms. Ph.D. thesis, Department of Civil Engineering, University of Akron. Anderson, D., 1977. The design of asphalt concrete overlays for flexible highway pavements. Berkeley: Departament of civil Engineering. University of California. Dehlen, G., 1961. The use of the Benkelman beam for the measurement of deflections and curvatures of a road surface between dual wheels. Council for Scientific and Industrial Research (CSIR) special report, R.2. Pretoria. Dehlen, G., 1962. Flexure of a road surfacing, its relation to fatigue cracking, and factors determining its severity. HRB, Highway Research Board Boletin no. 321. FHWA, 2016. Pavement structural evaluation at the network level: final report. Federal Highway Administration. Publication no. FHWAHRT15/074. Fuentes, L., et al., 2012. Determination of pavement macrotexture limit for use in international friction index model. Transportation Research Record: Journal of the Transportation Research Board, 2306 (1), 138–143. Fuentes, L., et al., 2019. Modelling pavement serviceability of urban roads using deterministic and probabilistic approaches. International Journal of Pavement Engineering. doi:10.1080/10298436.2019.1577422. Fuentes, L. and Gunaratne, M., 2010. Evaluation of the Speed Constant and Its Effect on the Calibration of Friction-Measuring Devices. Transportation Research Record: Journal of the Transportation Research Board, 2155. Washington, DC: Transportation Research Board of the National Academies, 134–144. Fuentes, L. and Gunaratne, M., 2011. Revised Methodology for Computing International Friction Index Transportation Research Record: Journal of the Transportation Research Board, 2227. Washington, DC: Transportation Research Board of the National Academies, 129–137. Fuentes, L., Gunaratne, M., and Hess, D., 2010. Evaluation of the effect of pavement roughness on skid resistance. Journal of Transportation Engineering, 136 (7), 640–653. Garg, N. and Thompson, M., 1997. Mechanistic-empirical evaluation of the Mn/road low volume road test sections. ProQuest dissertations. Gopalakrishna, K. and Kumar, S., 2010. Finite element based adaptive neuro-fuzzy inference technique for parameter identification of multi-layered transportation structures. Transport, 25 (1), 58–65. Harrison, R., 2010. Introduction to Monte Carlo simulation. AIP Conference Proceedings, 1204, 17–21. Hoffman, M. and Thompson, M., 1981. Mechanistic interpretation of nondestructive pavement testing deflections. ProQuest dissertations. INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING 13 Horak, E., 1987a. The use of deflection basin measurments in the mechaninistic analysis of flexible pavements. Sixth international conference on the structural design of asphalt pavements, vol. 1. University of Michigan. Horak, E., 1987b. Aspects of deflection basin parameters used in a mechanistic rehabilitation design procedure for flexible pavements in South Africa. PhD thesis. Pretoria: Department of Civil Engineering, University of Pretoria. Horak, E., 2008. Benchmarking the structural condition of flexible pavements with deflection bowl parameters. Journal of the South African Institution of Civil Engineers, 50 (2), 2–9. Horak, E. and Emery, S., 2006. Falling weight deflectometer bowl parameters as analysis tool for pavement structural evaluations. In: Proceedings of 22nd ARRB conference. Canberra. Horak, E., Emery, S., and Maina, J., 2015a. Review of falling weight deflectometer deflection benchmark analysis on roads and airfields. In: 11th conference on asphalt pavements for Southern Africa: CAPSA15, 16–19 August 2015, Sun City. Horak, E., Hefer, A., and Maina, J., 2015b. Modified structural number determined from falling weight deflectometer bowl parameters and its porposed use ina Benchmark methodology. Journal of Traffic and Transportation Engineering, 3. doi:10.17265/2328-2142/2015.04.000. Hosmer, D., Lemeshow, S., and Sturdivant, R., 2013. Applied logistic regression. New York: Wiley. Incorporated. Hossain, M. and Zaniewski, J., 1991. Characterization of falling weight deflectometer deflection basin. Transportation Research Record: Journal of the Transportation Research Board, 1293. Washington, DC: Transportation Research Board of the National Academies, 1 – 11. Hu, X., et al., 2010. Proposed loading waveforms and loading time equations for mechanistic-empirical pavement design and analysis. Journal of Transportation Engineering, 136 (6), 518–527. INVIAS, 2018. Especificaciones generales de construcción de carreteras y normas de ensayo para materiales de carreteras. Insituto Nacional de Vias Ministerio de Transporte de la República de Colombia. Joubert, F., 1992. Structural Classification of granular base pavement using measured deflection bowl parameters. ProQuest dissertations. Rand Afrikaans University. Kennedy, C. and Lister, N., 1978. Deflection and pavement performance: the experimental evidence. TRRL Laboratory Report no. 833. Great Britain. Kilareski, W. and Anani, B., 1982. Evaluation of in situ moduli and pavement life from deflection basins. Proceedings of the Fifth International Conference on the Structural Design of Asphalt Pavements Held Deflt University of Technology, 1 (2), 349-366. Kim, Y., Ranjithan, S., Troxler, J., and Xu, B. 2000. Assessing pavement layer condition using deflection data. Final Report, NCHRP Project 10–48. North Carolina State University, Raleigh. Kim, R. and Park, H., 2002. Use of falling weight deflectometer multi-load level data for pavement strength estimation. ProQuest dissertations. Maree, J. and Bellekens, R., 1991. The effect of asphalt overlays on the resilient deflection bowl response of typical pavement structures. Research report RP 90/102 for the Department of Transport. Chief Directorate National Roads, Pretoria, 1991. Pencina, M. and D’Agostino, R., 2015. Evaluating discrimination of Risk Prediction models. JAMA The Journal of the American Medical Association, 314 (10), 1063–1064. doi:10.1001/jama.2015.11082. Rabbi, M. and Mishra, D., 2019. Using FWD deflection basin parameters for network-level assessment of flexible pavements. International Journal of Pavement Engineering, 1–15. doi:10.1080/10298436.2019. 1580366. Rohde, G. and Van Wijk, A., 1996. A mechanistic procedure to determine basin parameter criteria. Petroria: Southern African Transportation Conference. Saleh, M., 2015a. Multi-scale criteria for structural capacity evaluation of flexible pavements at network level. In: Transportation research board 94th annual meeting for both presentation and publications. Saleh, M., 2015b. Utilisation of the deflectograph data to evaluate pavement structural condition of the highway network. Road Materials and Pavement Design, 17 (1), 136–152. Saleh, M., 2016. A mechanistic empirical approach for the evaluation of the structural capacity and remaining service life of flexible pavements at the network level. Canadian Journal of Civil Engineering, 43, 749– 758. doi:10.1139/cjce-2016-0060. Shahin, M., 2005. Pavement management for airports, roads and parking lots (2nd ed.). New York, NY: Springer. Solanki, U., Gundalia, P., and Barasara, M., 2014. A review on structural evaluation of flexible pavements using falling weight deflectometer. Trends in Transport Engineering and Applications, 2 (1), 1–10. Stubstad, R. and Connor, B., 1983. Use of the falling weight deflectometer to predict damage potential on Alaskan highways during spring thaw. Transportation Research Record: Journal of the Transportation Research Board, 930. Washington, DC: Transportation Research Board of the National Academies, 46-51. Tarefder, R. and Mesbah, A., 2014. Modeling of the FWD deflection basin to evaluate airport pavements. International Journal of Geomechanics, 14 (2), 205–213. Team, R., 2019. RStudio: integrated development for R. RStudio. Obtenido de http://www.rstudio.com/. Terzi, S., et al., 2012. Backcalculation of pavement layer thickness using data mining. Neural Computing and Applications, 23 (5), 1369–1379. doi:10.1007/s00521-012-1083-2. Tutumluer, E., 2015. Development of improved pavement rehabilitation procedures based. NEXTRANS Project No. 094IY04. Vaswani, N., 1971. Method for separately evaluating structural performance of subgrades and overlaying flexible pavements. HRB, Highway Research Record No.362. Vrtis, M., 2017. Investigation of deflection basin to identify structural distresses within flexible pavements. ProQuest dissertations. Walubita, L.F., et al., 2012. Texas flexible pavements and overlays: year 1 report, test sections, data collection, analyses, and data storage system (No. FHWA/TX-12/0-6658-1). Texas Transportation Institute (TTI). National Technical Information Service Alexandria, Virginia 22312. Walubita, L.F., et al., 2017. Texas flexible pavements and overlays: year 5 report-complete data documentation (No. FHWA/TX-15/0-6658-3). Texas A&M Transportation Institute (TTI). National Technical Information Service Alexandria, Virginia 22312. Walubita, L.F., Liu, W., and Scullion, T., 2010. Texas perpetual pavements: experience overview and the way forward (No. FHWA/TX-10/0-4822- 3). College Station, TX: Texas Transportation Institute (TTI). Wang, Y. and Liu, Q., 2006. Comparison of Akaike information criterion (AIC) and Bayesian information criterion (BIC) in selection of stock–recruitment relationships. Fisheries Research, 77 (2), 220–225. Whitcomb, W., 1982. Surface deflections and pavement evaluation equipment and analysis techniques. Transportation Engineering Report 82-4. Cornwallis, OR: Oregon State University. Xu, B., Ranji Ranjithan, S., and Kim, 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 (1), 46–56. Zheng, Y., Zhang, P., and Liu, H., 2019. Correlation between pavement temperature and deflection basin form factors of asphalt pavement. International Journal of Pavement Engineering, 20 (8), 874–883. doi:10.1080/10298436.2017.1356172.
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spelling	Fuentes, Luis7512d340717745d0c33458fd7df00b62Taborda, Katherinea092fe3ab7e37c299dc43f1168747035300Hu, Xiaodi323828375282a1c44a6170d83aed3cef300Horak, Emilebc4bd60ae020271e7cc4d2b73ce3e5e8300Bai, Taoe7a8ab17a335f9aaafd7627529e51576300Walubita, Lubinda Ffcbca8c673ce3626323a2b368ba61c613002021-03-10T19:33:46Z2021-03-10T19:33:46Z2020-10-092021-11-09https://hdl.handle.net/11323/7987https://doi.org/10.1080/10298436.2020.1828586Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/Presently, most of the road agencies use Non-Destructive (NDT) tools to help them prioritise pavement maintenance and rehabilitation (M&R) activities at the network level, thus optimising the limited budgetary resources. One of the most widely used NDT techniques for pavement structural evaluations, at the network level assessment, is the Falling Weight Deflectometer (FWD). Using a database comprising of a wide array of typical layer moduli and thicknesses of traditional flexible pavements, that were generated based on multiple Monte Carlo numerical simulations, as a reference datum, this study successfully developed probabilistic models that allow for analysing the condition of a flexible pavement, at the network level, from FWD surface deflection data, namely the Deflection Bowl Parameters (DBPs), to identify which layers of the pavement structure present a probability of structural failure or damage.application/pdfengCorporación Universidad de la CostaCC0 1.0 Universalhttp://creativecommons.org/publicdomain/zero/1.0/info:eu-repo/semantics/embargoedAccesshttp://purl.org/coar/access_right/c_f1cfInternational Journal of Pavement Engineeringhttps://www.tandfonline.com/doi/abs/10.1080/10298436.2020.1828586falling weight deflectometerdeflection bowl parameterslogistic model regressionpavement rehabilitationnon destructive testingA probabilistic approach to detect structural problems in flexible pavement sections at network level assessmentArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersionAASHTO, 1993. AASHTO guide for design of pavement structures 1993. Washington, DC: American 7 Association of State Highway and Transportation Officials.Abudinen, D., Fuentes, L., and Carvajal, J., 2017. Travel quality assessment of Urban Roads based on International roughness Index: case study in Colombia. Transportation Research Record: Journal of the Transportation Research Board, 2612 (1), 1–10.Adams, J. and Kim, R., 2014. Mean profile depth analysis of field and laboratory traffic-loaded chip seal surface treatments. International Journal of Pavement Engineering, 15 (7), 645–656.Alkasawneh, W., 2007. Backcalculation of pavement moduli using genetic algorithms. Ph.D. thesis, Department of Civil Engineering, University of Akron.Anderson, D., 1977. The design of asphalt concrete overlays for flexible highway pavements. Berkeley: Departament of civil Engineering. University of California.Dehlen, G., 1961. The use of the Benkelman beam for the measurement of deflections and curvatures of a road surface between dual wheels. Council for Scientific and Industrial Research (CSIR) special report, R.2. Pretoria.Dehlen, G., 1962. Flexure of a road surfacing, its relation to fatigue cracking, and factors determining its severity. HRB, Highway Research Board Boletin no. 321.FHWA, 2016. Pavement structural evaluation at the network level: final report. Federal Highway Administration. Publication no. FHWAHRT15/074. Fuentes, L., et al., 2012. Determination of pavement macrotexture limit for use in international friction index model. Transportation Research Record: Journal of the Transportation Research Board, 2306 (1), 138–143.Fuentes, L., et al., 2019. Modelling pavement serviceability of urban roads using deterministic and probabilistic approaches. International Journal of Pavement Engineering. doi:10.1080/10298436.2019.1577422.Fuentes, L. and Gunaratne, M., 2010. Evaluation of the Speed Constant and Its Effect on the Calibration of Friction-Measuring Devices. Transportation Research Record: Journal of the Transportation Research Board, 2155. Washington, DC: Transportation Research Board of the National Academies, 134–144.Fuentes, L. and Gunaratne, M., 2011. Revised Methodology for Computing International Friction Index Transportation Research Record: Journal of the Transportation Research Board, 2227. Washington, DC: Transportation Research Board of the National Academies, 129–137.Fuentes, L., Gunaratne, M., and Hess, D., 2010. Evaluation of the effect of pavement roughness on skid resistance. Journal of Transportation Engineering, 136 (7), 640–653.Garg, N. and Thompson, M., 1997. Mechanistic-empirical evaluation of the Mn/road low volume road test sections. ProQuest dissertations. Gopalakrishna, K. and Kumar, S., 2010. Finite element based adaptive neuro-fuzzy inference technique for parameter identification of multi-layered transportation structures. Transport, 25 (1), 58–65.Harrison, R., 2010. Introduction to Monte Carlo simulation. AIP Conference Proceedings, 1204, 17–21.Hoffman, M. and Thompson, M., 1981. Mechanistic interpretation of nondestructive pavement testing deflections. ProQuest dissertations.INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING 13 Horak, E., 1987a. The use of deflection basin measurments in the mechaninistic analysis of flexible pavements. Sixth international conference on the structural design of asphalt pavements, vol. 1. University of Michigan.Horak, E., 1987b. Aspects of deflection basin parameters used in a mechanistic rehabilitation design procedure for flexible pavements in South Africa. PhD thesis. Pretoria: Department of Civil Engineering, University of Pretoria.Horak, E., 2008. Benchmarking the structural condition of flexible pavements with deflection bowl parameters. Journal of the South African Institution of Civil Engineers, 50 (2), 2–9.Horak, E. and Emery, S., 2006. Falling weight deflectometer bowl parameters as analysis tool for pavement structural evaluations. In: Proceedings of 22nd ARRB conference. Canberra.Horak, E., Emery, S., and Maina, J., 2015a. Review of falling weight deflectometer deflection benchmark analysis on roads and airfields. In: 11th conference on asphalt pavements for Southern Africa: CAPSA15, 16–19 August 2015, Sun City.Horak, E., Hefer, A., and Maina, J., 2015b. Modified structural number determined from falling weight deflectometer bowl parameters and its porposed use ina Benchmark methodology. Journal of Traffic and Transportation Engineering, 3. doi:10.17265/2328-2142/2015.04.000.Hosmer, D., Lemeshow, S., and Sturdivant, R., 2013. Applied logistic regression. New York: Wiley. Incorporated.Hossain, M. and Zaniewski, J., 1991. Characterization of falling weight deflectometer deflection basin. Transportation Research Record: Journal of the Transportation Research Board, 1293. Washington, DC: Transportation Research Board of the National Academies, 1 – 11.Hu, X., et al., 2010. Proposed loading waveforms and loading time equations for mechanistic-empirical pavement design and analysis. Journal of Transportation Engineering, 136 (6), 518–527.INVIAS, 2018. Especificaciones generales de construcción de carreteras y normas de ensayo para materiales de carreteras. Insituto Nacional de Vias Ministerio de Transporte de la República de Colombia.Joubert, F., 1992. Structural Classification of granular base pavement using measured deflection bowl parameters. ProQuest dissertations. Rand Afrikaans University.Kennedy, C. and Lister, N., 1978. Deflection and pavement performance: the experimental evidence. TRRL Laboratory Report no. 833. Great Britain.Kilareski, W. and Anani, B., 1982. Evaluation of in situ moduli and pavement life from deflection basins. Proceedings of the Fifth International Conference on the Structural Design of Asphalt Pavements Held Deflt University of Technology, 1 (2), 349-366.Kim, Y., Ranjithan, S., Troxler, J., and Xu, B. 2000. Assessing pavement layer condition using deflection data. Final Report, NCHRP Project 10–48. North Carolina State University, Raleigh.Kim, R. and Park, H., 2002. Use of falling weight deflectometer multi-load level data for pavement strength estimation. ProQuest dissertations.Maree, J. and Bellekens, R., 1991. The effect of asphalt overlays on the resilient deflection bowl response of typical pavement structures. Research report RP 90/102 for the Department of Transport. Chief Directorate National Roads, Pretoria, 1991.Pencina, M. and D’Agostino, R., 2015. Evaluating discrimination of Risk Prediction models. JAMA The Journal of the American Medical Association, 314 (10), 1063–1064. doi:10.1001/jama.2015.11082.Rabbi, M. and Mishra, D., 2019. Using FWD deflection basin parameters for network-level assessment of flexible pavements. International Journal of Pavement Engineering, 1–15. doi:10.1080/10298436.2019. 1580366.Rohde, G. and Van Wijk, A., 1996. A mechanistic procedure to determine basin parameter criteria. Petroria: Southern African Transportation Conference.Saleh, M., 2015a. Multi-scale criteria for structural capacity evaluation of flexible pavements at network level. In: Transportation research board 94th annual meeting for both presentation and publications.Saleh, M., 2015b. Utilisation of the deflectograph data to evaluate pavement structural condition of the highway network. Road Materials and Pavement Design, 17 (1), 136–152.Saleh, M., 2016. A mechanistic empirical approach for the evaluation of the structural capacity and remaining service life of flexible pavements at the network level. Canadian Journal of Civil Engineering, 43, 749– 758. doi:10.1139/cjce-2016-0060.Shahin, M., 2005. Pavement management for airports, roads and parking lots (2nd ed.). New York, NY: Springer.Solanki, U., Gundalia, P., and Barasara, M., 2014. A review on structural evaluation of flexible pavements using falling weight deflectometer. Trends in Transport Engineering and Applications, 2 (1), 1–10.Stubstad, R. and Connor, B., 1983. Use of the falling weight deflectometer to predict damage potential on Alaskan highways during spring thaw.Transportation Research Record: Journal of the Transportation Research Board, 930. Washington, DC: Transportation Research Board of the National Academies, 46-51.Tarefder, R. and Mesbah, A., 2014. Modeling of the FWD deflection basin to evaluate airport pavements. International Journal of Geomechanics, 14 (2), 205–213.Team, R., 2019. RStudio: integrated development for R. RStudio. Obtenido de http://www.rstudio.com/.Terzi, S., et al., 2012. Backcalculation of pavement layer thickness using data mining. Neural Computing and Applications, 23 (5), 1369–1379. doi:10.1007/s00521-012-1083-2.Tutumluer, E., 2015. Development of improved pavement rehabilitation procedures based. NEXTRANS Project No. 094IY04.Vaswani, N., 1971. Method for separately evaluating structural performance of subgrades and overlaying flexible pavements. HRB, Highway Research Record No.362.Vrtis, M., 2017. Investigation of deflection basin to identify structural distresses within flexible pavements. ProQuest dissertations.Walubita, L.F., et al., 2012. Texas flexible pavements and overlays: year 1 report, test sections, data collection, analyses, and data storage system (No. FHWA/TX-12/0-6658-1). Texas Transportation Institute (TTI). National Technical Information Service Alexandria, Virginia 22312.Walubita, L.F., et al., 2017. Texas flexible pavements and overlays: year 5 report-complete data documentation (No. FHWA/TX-15/0-6658-3).Texas A&M Transportation Institute (TTI). National Technical Information Service Alexandria, Virginia 22312.Walubita, L.F., Liu, W., and Scullion, T., 2010. Texas perpetual pavements: experience overview and the way forward (No. FHWA/TX-10/0-4822- 3). College Station, TX: Texas Transportation Institute (TTI).Wang, Y. and Liu, Q., 2006. Comparison of Akaike information criterion (AIC) and Bayesian information criterion (BIC) in selection of stock–recruitment relationships. Fisheries Research, 77 (2), 220–225.Whitcomb, W., 1982. Surface deflections and pavement evaluation equipment and analysis techniques. Transportation Engineering Report 82-4. Cornwallis, OR: Oregon State University.Xu, B., Ranji Ranjithan, S., and Kim, 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 (1), 46–56.Zheng, Y., Zhang, P., and Liu, H., 2019. Correlation between pavement temperature and deflection basin form factors of asphalt pavement. 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A probabilistic approach to detect structural problems in flexible pavement sections at network level assessment

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