Designing of pavement maintenance management system using cumulative damage model
By: Katkar, Surendrakumar
.
Contributor(s): Nagrale, Prashant.
Publisher: Pune NICMAR 2014Edition: Vol.29(2), Apr-Jun.Description: 37-48p.Subject(s): Construction Engineering and Management (CEM)Online resources: Click here
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NICMAR Journal of construction managementSummary: The probabilistic model to find pavement deterioration helps to predict pavement condition and decide / prioritise the allocation of maintenance funds. To develop such model probability of change in pavement condition state from one to other with respect to time is necessary which is known as transition probability. The main focus of this research study is to estimate the transition probabilities from current available frequencies of pavements in a particular condition state, at a particular age, and to formulate Transition Probability Matrix (TPM). Pavement deterioration is then predicted by using Markovian approach. Considering limitations and unavailability of runtime database, in a developing country like India having huge road network, an attempt is made to develop a model that can give transition probabilities by analysing a group of pavements having similar characteristics of different age groups at single point of time. The model can be termed as Cumulative Damage Model (CDM) as it considers the pavement deterioration at any particular time from its construction, as a cumulative effect with respect to time. It is observed that CDM predicts pavement deterioration with more than 95% accuracy and with little effort. Difference between observed and predicted pavement frequencies by CDM is found due to chance only. Line by line minimization using Mean Square Test between relative pavement frequencies and assumed transition probabilities is found to be very useful technique to estimate optimum transition probabilities. Model is tested using Chi-square test and is found fit for the intended purpose.
| Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
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Articles Abstract Database
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School of Engineering & Technology (PG) Archieval Section | Not for loan | 2024-0865 |
The probabilistic model to find pavement deterioration helps to predict pavement condition and decide / prioritise the allocation of maintenance funds. To develop such model probability of change in pavement condition state from one to other with respect to time is necessary which is known as transition probability. The main focus of this research study is to estimate the transition probabilities from current available frequencies of pavements in a particular condition state, at a particular age, and to formulate Transition Probability Matrix (TPM). Pavement deterioration is then predicted by using Markovian approach. Considering limitations and unavailability of runtime database, in a developing country like India having huge road network, an attempt is made to develop a model that can give transition probabilities by analysing a group of pavements having similar characteristics of different age groups at single point of time. The model can be termed as Cumulative Damage Model (CDM) as it considers the pavement deterioration at any particular time from its construction, as a cumulative effect with respect to time. It is observed that CDM predicts pavement deterioration with more than 95% accuracy and with little effort. Difference between observed and predicted pavement frequencies by CDM is found due to chance only. Line by line minimization using Mean Square Test between relative pavement frequencies and assumed transition probabilities is found to be very useful technique to estimate optimum transition probabilities. Model is tested using Chi-square test and is found fit for the intended purpose.
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