Development of a semi-parametric stochastic model of asphalt pavement crack initiation

Shin, Hee Cheol

doi:10.1007/bf02824060

Cited by 11 publications

(8 citation statements)

References 2 publications

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“…Shin (2006) proposed a semi-parametric stochastic duration model for asphalt pavement crack initiation and Loizos and Karlaftis (2005) also tried to develop pavement surface distress prediction models based on the stochastic duration principles. Other studies have developed models based on dynamical mechanics to forecast the deterioration of infrastructure facilities (Cesare et al, 1992).…”

Section: Related Literaturementioning

confidence: 99%

“…Considering traffic volume and maintenance history for use as basic data for maintenance, the pavement management system annually collects pavement-related data such as longitudinal roughness, rut-depth, cracks etc. for deciding the pavement status rating for homogeneous sections in many countries and regions (Madanat et al, 1995;Prozzi and Madanat, 2004;Shin, 2006;Wee and Kim, 2006). However, some problems for accurate prediction of road deterioration remain.…”

Section: Introductionmentioning

confidence: 99%

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Estimation of Markovian transition probabilities for pavement deterioration forecasting

Kobayashi

Han

2010

KSCE Journal of Civil Engineering

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While it is impossible to estimate when a road section will collapse, the understanding of road section deterioration can help asset managers predict the condition of road sections and take appropriate actions for rehabilitations. Deterioration forecasting modeling is an essential element for an efficient pavement management system. Although the Pavement Management System (PMS) has been introduced and operated for optimal road maintenance since the late 1980s in Korea, some problems for accurate prediction of road deterioration remain due to the quality of pavement performance data and the different pavement structural, material and environmental conditions. In this paper, a methodology to estimate the Markov transition probability model is presented to forecast the deterioration process of road sections. The deterioration states of the road sections are categorized into several ranks and the deterioration processes are characterized by hazard models. The Markov transition probabilities between the deterioration states, which are defined by the non-uniform or irregular intervals between the inspection points in time, are described by the exponential hazard models. Furthermore, in order to verify the validity of the proposed method, the applicability of the estimation methodology presented in this paper is investigated by using the empirical surface data set of the national highway in Korea.

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Section: Related Literaturementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Estimation of Markovian transition probabilities for pavement deterioration forecasting

Kobayashi

Han

2010

KSCE Journal of Civil Engineering

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“…Studies on the estimation of performance for pavement sections, on the other hand, have been mainly focused on the topics about the deterioration speeds on pavement surface such as crack, rut depth and roughness and relationship between used materials and lifetime (Yang et al, 2005;Shin, 2006). As far as the author knows, there are few trials on the relationship between the functional classification of roads and the estimation of mean life at the same time (Wang et al, 1994).…”

Section: Introductionmentioning

confidence: 98%

Comparative analysis on mean life reliability with functionally classified pavement sections

2011

KSCE Journal of Civil Engineering

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The estimation of mean life reliability of highway pavement plays a central role in road maintenance and pavement management. In this paper, a methodology to estimate the mean life and failure probability in consideration of road functional characteristics based on parametric and non-parametric estimation models are presented. Based on the three types of functionally classified roads: urban, rural and recreation roads, five different lifetime distributions were tested: Normal, lognormal, exponential, Weibull, and loglogistic to select the appropriate probability distribution and to estimate mean life and failure rates. For functional classification of roads, the permanent traffic counters located along the national highway in 2007 are used. Furthermore, national highway pavement databases from 1999 to 2008 are also used for selection of optimal probability distribution and estimation of mean life for pavement. The goodness-of-fit test, such as the Anderson-Darling test, was performed to select optimal probability distribution. As a result, an appropriate distribution of each case was selected: lognormal distribution for rural roads and Weibull distribution for recreation roads. The non-parametric estimation method for rural roads was applied because there is no appropriate probability distribution for rural roads. Furthermore, in order to verify the validity of the proposed parametric and non-parametric estimation models, the applicability of the estimation methodology presented in this paper is investigated by using the empirical lifetime data of the national highway in Korea.

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“…Other testing proposed method for determining the material parameters of a fatigue cracking model based on Accelerated Pavement Testing were identified by [5] and [22]. Tests are also essential to determine several features that may influence the time at which the pavement starts to crack, as an essential component of pavement management for planning of maintenance and rehabilitation, where three major features are relevant in terms of the performance of an asphalt pavement [9]: permanent deformation or rutting results, fatigue cracking, and low temperature cracking.…”

Section: Introductionmentioning

confidence: 99%

Workflow Automation in a Risk Management Framework for Pavement Maintenance Projects

Benţa

Rusu

Manolescu

2017

INT J COMPUT COMMUN

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This paper presents a Workflow Management System (WfMS) for procurement process automation in road pavement maintenance and management. It fits information infrastructure for monitoring and maintenance of pavements and roads. Through the two roles of administrator and major users (builder and subcontractors), the solution models the entire process. This way, risks of exceeding allocated budget, time consuming tasks, overcoming deadline, and time consuming quality control, as main issues in risk management, are reduced and controlled.

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Development of a semi-parametric stochastic model of asphalt pavement crack initiation

Cited by 11 publications

References 2 publications

Estimation of Markovian transition probabilities for pavement deterioration forecasting

Estimation of Markovian transition probabilities for pavement deterioration forecasting

Comparative analysis on mean life reliability with functionally classified pavement sections

Workflow Automation in a Risk Management Framework for Pavement Maintenance Projects

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