Pavement maintenance and rehabilitation planning optimisation under budget and pavement deterioration uncertainty

2020 ◽  
pp. 1-11
Author(s):  
Amirhossein Fani ◽  
Amir Golroo ◽  
S. Ali Mirhassani ◽  
Amir H. Gandomi
Keyword(s):  
Pavement Maintenance ◽  
Rehabilitation Planning ◽  
Pavement Deterioration ◽  
Maintenance And Rehabilitation

A semi-Markov formulation of the pavement maintenance optimization problem

1993 ◽  
Vol 20 (3) ◽  
pp. 436-447 ◽  
Author(s):  
Dale M. Nesbit ◽  
Gordon A. Sparks ◽  
Russell D. Neudorf
Keyword(s):  
Pavement Management ◽  
Maintenance Optimization ◽  
Infrastructure Management ◽  
Pavement Maintenance ◽  
Pavement Deterioration ◽  
Maintenance And Rehabilitation ◽  
Computationally Intensive ◽  
Asset Depreciation ◽  
Special Case ◽  
Project Level

The problem of determining optimal pavement maintenance and rehabilitation strategies is a special case of a more general problem termed the asset depreciation problem. Perhaps the most general formulation and solution of the asset depreciation problem is the semi-Markov formulation. This paper illustrates how the semi-Markov formulation and solution of the general asset depreciation problem can be applied to pavements. The semi-Markov formulation, like the Markov formulation, characterizes pavement deterioration probabilistically and represents human intervention (maintenance and rehabilitation) as slowing or modifying the basic probabilities of deterioration. The Markov formulation, first implemented for the state of Arizona, is shown to be a special case of the more general, less computationally intensive semi-Markov formulation. The application of the semi-Markov formulation is illustrated at the project level for a heavy-duty pavement in Manitoba. Key words: asset depreciation, infrastructure management, pavement management, probabilistic modelling, Markov, semi-Markov, maintenance optimization, project level.

scholarly journals A Two-Stage Stochastic Model for Maintenance and Rehabilitation Planning of Pavements

2019 ◽  
Vol 2019 ◽  
pp. 1-15
Author(s):  
Mahmoud Ameri ◽  
Armin Jarrahi ◽  
Farshad Haddadi ◽  
Mohammad Hasan Mirabimoghaddam
Keyword(s):  
Stochastic Model ◽  
Deterministic Model ◽  
Two Stage ◽  
Total Cost ◽  
Pavement Maintenance ◽  
Rehabilitation Planning ◽  
Maintenance And Rehabilitation ◽  
Unrealistic Assumption ◽  
Planning Problems

Pavement maintenance and rehabilitation (M&R) plan for maintaining the pavement quality in an acceptable level has direct influence on the required budget. Deterministic budgeting is an unrealistic assumption, so, in this study, a two-stage stochastic model using integer programming is developed to address uncertainty in budgeting. Another aim of this study is to develop an executive model that considers a broad range of parameters at network level maintenance and rehabilitation planning. While having too many details in planning problems makes them more complicated, some restrictions called “technical constraints” were considered to reduce solution time of solving procedure as well as improve M&R activities assignment efficiency. Comparing results of the stochastic model with a deterministic model for a case study revealed that the two-stage stochastic model led to increased total cost compared to the deterministic one due to considering probability in budgeting. However, the developed model provides several M&R plans that are compatible with budget variation.

Finite element analysis of fire-damaged flexible pavement deterioration

2017 ◽  
Vol 8 (2) ◽  
pp. 106-116
Author(s):  
Rudi van Staden ◽  
Sam Fragomeni
Keyword(s):  
Finite Element ◽  
Fatigue Cracking ◽  
Element Analysis ◽  
Content Type ◽  
Operational Conditions ◽  
Pavement Maintenance ◽  
Pavement Deterioration ◽  
Maintenance And Rehabilitation ◽  
The Impact ◽  
Cent Decrease

Purpose This research aims to use the finite element method to examine critical distress modes in the pavement layers due to changes in the structural properties brought upon by fire damage. Design/methodology/approach A full dynamic analysis is performed to replicate heavy vehicle axle wheel loads travelling over a pavement section. Findings Results show a 72 per cent decrease in the number of load repetitions which a fire-damaged pavement can experience before fatigue cracking of the asphalt. Further, there is a 51 per cent decrease in loading cycles of the subgrade before rutting of the fire-damaged system. Originality/value Fatigue of asphalt and deformation of subgrade from repeated vehicular loading are the most common failure mechanisms, and major attributors to pavement maintenance and rehabilitation costs. Pavement analysis has always been concentrated on evaluating deterioration under regularly occurring operational conditions. However, the impact of one-off events, such as vehicle petroleum fires, has not been evaluated for the effects on deterioration.

Establishing optimal project-level strategies for pavement maintenance and rehabilitation – A framework and case study

2012 ◽  
Vol 44 (5) ◽  
pp. 565-589 ◽  
Author(s):  
Muhammad Irfan ◽  
Muhammad Bilal Khurshid ◽  
Qiang Bai ◽  
Samuel Labi ◽  
Thomas L. Morin
Keyword(s):  
Pavement Maintenance ◽  
Maintenance And Rehabilitation ◽  
Project Level

Detection of Pavement Maintenance Treatments using Deep-Learning Network

2021 ◽  
pp. 036119812110078
Author(s):  
Lu Gao ◽  
Yao Yu ◽  
Yi Hao Ren ◽  
Pan Lu
Keyword(s):  
Deep Learning ◽  
Measurement Errors ◽  
Short Term Memory ◽  
Learning Networks ◽  
Pavement Maintenance ◽  
Time Period ◽  
Learning Techniques ◽  
Maintenance And Rehabilitation ◽  
History Of ◽  
Deep Learning Network

Pavement maintenance and rehabilitation (M&R) records are important as they provide documentation that M&R treatment is being performed and completed appropriately. Moreover, the development of pavement performance models relies heavily on the quality of the condition data collected and on the M&R records. However, the history of pavement M&R activities is often missing or unavailable to highway agencies for many reasons. Without accurate M&R records, it is difficult to determine if a condition change between two consecutive inspections is the result of M&R intervention, deterioration, or measurement errors. In this paper, we employed deep-learning networks of a convolutional neural network (CNN) model, a long short-term memory (LSTM) model, and a CNN-LSTM combination model to automatically detect if an M&R treatment was applied to a pavement section during a given time period. Unlike conventional analysis methods so far followed, deep-learning techniques do not require any feature extraction. The maximum accuracy obtained for test data is 87.5% using CNN-LSTM.

scholarly journals Performance and Microstructure of Cold Recycled Mixes Using Asphalt Emulsion with Different Contents of Cement

Materials ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 2548 ◽  
Author(s):  
Yanhai Yang ◽  
Ye Yang ◽  
Baitong Qian
Keyword(s):  
Low Temperature ◽  
Temperature Stability ◽  
Hydration Products ◽  
High Temperature Stability ◽  
Asphalt Emulsion ◽  
Moisture Susceptibility ◽  
Pavement Maintenance ◽  
Maintenance And Rehabilitation ◽  
Low Temperature Cracking ◽  
Temperature Crack

Cold recycled mixes using asphalt emulsion (CRME) is an economical and environmentally-friendly technology for asphalt pavement maintenance and rehabilitation. In order to determine the optimum range of cement contents, the complex interaction between cement and asphalt emulsion and the effects of cement on performance of CRME were investigated with different contents of cement. The microstructure and chemical composition of the fracture surface of CRME with different contents of cement were analyzed in this paper as well. Results show that the high-temperature stability and moisture susceptibility of CRME increased with the contents of cement increasing. The low-temperature crack resistance ability gradually increased when the content of cement is increased from 0% to 1.5%. However, it gradually decreased when the content of cement is increased from 1.5% to 4%. Cold recycled mixes had better low-temperature cracking resistance when the contents of cement were in the range from 1% to 2%. The results of microstructure and energy spectrum analysis show that the composite structure is formed by hydration products and asphalt emulsion. The study will be significant to better know the effects of cement and promote the development of CRME.

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