Research Publications

Now showing 1 - 3 of 3

Open Access
Development of Roughness Prediction Model for Sri Lankan Expressways
(Sri Lanka Institute of Information Technology, 2023-03-25) Nilawfer, S; Madushani, S; Sandamal, K; Gomes, A
Expressways play a pivotal role in industrial and export development in Sri Lanka by providing access to the production sector in addition to the passenger transport in between transport hubs. A reliable pavement performance prediction model is essential for pavement management systems to optimize the cost of maintenance and rehabilitation planning. In this study, pavement roughness prediction of expressways in the long-term performance was conducted using International Roughness Index (IRI) which is used as a global parameter to measure the ride comfort of road users and the unevenness of pavement. Firstly, initial IRI values for Sri Lankan expressways were established by using current data and found that, it varies between 0.90 to 1.45 m/km. Secondly, IRI prediction model developed with cumulative traffic volume, considering outer lane IRI as the dependent variable due to higher deterioration rate compared to inner lane. Moreover, it was found that, there is a good relationship between IRI with cumulative traffic with R-squared of 0.60. Further, it can be concluded that, the outcomes of this study can be effectively used for Sri Lankan context in long term performance evaluation and expressway maintenance planning.
Open Access
Performance Prediction Models for Flexible Pavements in Sri Lanka
(SLIIT, 2022-02-11) Amarasingha, N; Opanayake, P
The pavement prediction model forecasts the future PCI ratings based on pavement category, thickness, traffic, pavement life period and existing PCI rating. Nevertheless, with time and inclusion of newer pavement types, there was a need to adjust the prevailing pavement performance models. In addition to, pavements management systems need to develop new models for newer pavement types as well. Some developed pavement performance models in the earlier for the Road Development Authority (RDA) Sri Lanka is used by the roadway segments to predict the future condition and rehabilitations of its network. The available data collections in the roadway agencies in Sri Lanka was used for the research study and the methodology and the analysis section depended on that data collection. Probably we were given the IRI data collections which were done in southern expressway section in Sri Lanka. Based on that data, the analysis part was done for determine the pavement roughness deterioration curves. With a comparison of the developed models, the most suitable model was taken at 95% confidence level with 0.8009 R2 value. This study displays outcomes about of standardizing the present performance models, and creating unused models for the different asphalt forms within the roadway network in Sri Lanka. A comparison of IRI progression with pavement age and traffic volume is also conducted to see if there are major differences between such models developed in other countries. The anticipated expectations condition of the asphalts is utilized in assessing its outstanding benefit life to disappointment, which is of prompt utilize in prescribing future upkeep and recovery necessities for the arrange.
Open Access
A Framework for Network Level Pavement Maintenance Planning for Low Volume Roads
(Spriger Link, 2020) Pasindu, H. R; Sandamal, R. M. K; Perera, M. Y. I
Low volume roads (LVRs) play a pivotal role in the economic development of rural areas especially by providing connectivity for the communities to access markets, education and social needs in an efficient manner. They serve as the link between the local road network to the arterial and collector road network designed at providing accessibility to residential, agricultural or industrial areas. Lack of funding, subjective and ad hoc decision making has resulted in an inefficent utilization of resources in the local road agencies. Lack of a sound analytical process is a major impediment to maintain these roads in cost effective manner under the resource constraints prevalent. Existing pavement management systems (PMS) require extensive data collection and complex analysis processes, which makes them impractical to be deployed in local agencies. The core attributes of the proposed system are, reduced the data requirements, simplified the analytical tools and allowing users to customize considering the resource constraints. In this study, a relationship between International Roughness Index (IRI) and relevant distresses for LVR is established and based on that cost estimation model is developed for distress repair. Furthermore, the strategy which provide maximum condition for preventive maintenance is found by using decision tree approach in the network level optimization. A case study illustrated that the use of proposed PMS provides better overall network condition with compare to conventional decision making for same budget level.

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