Enhancement of sustainable road design towards compatibility between pavement materials

Mapping Intimacies ◽

10.33593/jqo388gl ◽

2021 ◽

Author(s):

Larissa Strömberg ◽

Lev Khazanovich ◽

Staffan Hintze

Keyword(s):

Life Cycle ◽

Life Cycle Cost ◽

Climate Impact ◽

Life Cycle Cost Analysis ◽

Concrete Pavements ◽

Asphalt Mixes ◽

Environmental Product Declaration ◽

Pavement Materials ◽

Technical Performance ◽

Road Design

The need for correctly made comparisons of different pavement materials, regarding cost-efficiency to reduce the climate impact, is increasing, especially in connection with new types of climate-neutral materials, so that sub-optimizations and oblique competition do not arise. Both the Swedish and USA's authorities are beginning to demand the Environmental Product Declaration (EPDs) as a certificate of the pavements' environmental performances from the contractors. There are some methodological difficulties to use the EPDs for comparison of the environmental impacts between different asphalt mixes or between the asphalt- and concrete pavements. This paper has analyzed two new standards which propose to extend the declaration to several aspects of sustainability: technical, environmental and economic performance. In this article, we have investigated if these standards can be used to form a framework to create an extended sustainability declaration of road pavements allowed a multidisciplinary comparison of different materials based on technical performance, Life Cycle Assessment (LCA) and Life Cycle Cost Analysis (LCCA).

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Case Studies of the Life Cycle Cost Analysis for Rehabilitation of Deteriorated Expressway Concrete Pavements

International Journal of Highway Engineering ◽

10.7855/ijhe.2016.18.3.033 ◽

2016 ◽

Vol 18 (3) ◽

pp. 33-45 ◽

Cited By ~ 1

Author(s):

Young-Chan Suh ◽

Ji-Won Park ◽

Chan-Woo Kim

Keyword(s):

Life Cycle ◽

Cost Analysis ◽

Case Studies ◽

Life Cycle Cost ◽

Life Cycle Cost Analysis ◽

Concrete Pavements

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Enhancing Decision-Making on Maintenance, Rehabilitation, and Reconstruction of Jointed Plain Concrete Pavements using Slab-Based Cracking Data and Life-Cycle Cost Analysis

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198120925068 ◽

2020 ◽

Vol 2674 (8) ◽

pp. 511-522 ◽

Cited By ~ 1

Author(s):

Ryan Salameh ◽

Yichang (James) Tsai

Keyword(s):

Life Cycle ◽

Cost Analysis ◽

Life Cycle Cost ◽

Plain Concrete ◽

Cost Effective ◽

The United States ◽

Life Cycle Cost Analysis ◽

Concrete Pavements ◽

Slab Replacement ◽

Transportation Agencies

Many jointed plain concrete pavements (JPCP) on critical roads in the United States are aged and have reached the end of their design lives. They thus require maintenance, rehabilitation, and reconstruction (MR&R) actions, which mainly involve slab replacement or lane reconstruction. Limited budgets challenge transportation agencies to determine the most cost-effective MR&R strategies, especially when life-cycle cost analysis (LCCA) is limited by the unreliable prediction of the pavement’s future needs. This paper proposes an enhanced LCCA-based methodology that utilizes slab-based cracking data collected using 3D laser technology, to select the best strategy for MR&R of JPCP by determining the timing and cost of slab replacement and lane reconstruction. By predicting pavement performance based on the current slab-based condition state using a Markov chain forecasting model, slab replacement projects are scheduled, and their feasibility is evaluated to determine the proper timing for lane reconstruction within the analysis period. LCCA is then conducted to select the alternative with the most cost-effective strategy for scheduling slab replacement and lane reconstruction projects. A case study is conducted on two 1-mi segments of I-16 in Georgia to validate the proposed methodology, followed by a sensitivity analysis to identify the input variables having a significant impact on the LCCA results. The developed framework proved its strength in determining the best MR&R strategy based on segment-level need assessment, which is utilized to perform “what if” analyses that evaluate different scenarios of project scheduling and accommodate the requirements and limitations defined by transportation agencies.

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Development of a Statistical Model to Predict Materials’ Unit Prices for Future Maintenance and Rehabilitation in Highway Life Cycle Cost Analysis

10.31979/mti.2020.1806 ◽

2020 ◽

Author(s):

Changmo Kim ◽

Ghazan Khan ◽

Brent Nguyen ◽

Emily L. Hoang

Keyword(s):

Life Cycle ◽

Cost Analysis ◽

Statistical Models ◽

Life Cycle Cost ◽

Unit Price ◽

Life Cycle Cost Analysis ◽

Pavement Materials ◽

Project Costs ◽

Maintenance And Rehabilitation ◽

The Future

The main objectives of this study are to investigate the trends in primary pavement materials’ unit price over time and to develop statistical models and guidelines for using predictive unit prices of pavement materials instead of uniform unit prices in life cycle cost analysis (LCCA) for future maintenance and rehabilitation (M&R) projects. Various socio-economic data were collected for the past 20 years (1997–2018) in California, including oil price, population, government expenditure in transportation, vehicle registration, and other key variables, in order to identify factors affecting pavement materials’ unit price. Additionally, the unit price records of the popular pavement materials were categorized by project size (small, medium, large, and extra-large). The critical variables were chosen after identifying their correlations, and the future values of each variable were predicted through time-series analysis. Multiple regression models using selected socio-economic variables were developed to predict the future values of pavement materials’ unit price. A case study was used to compare the results between the uniform unit prices in the current LCCA procedures and the unit prices predicted in this study. In LCCA, long-term prediction involves uncertainties due to unexpected economic trends and industrial demand and supply conditions. Economic recessions and a global pandemic are examples of unexpected events which can have a significant influence on variations in material unit prices and project costs. Nevertheless, the data-driven scientific approach as described in this research reduces risk caused by such uncertainties and enables reasonable predictions for the future. The statistical models developed to predict the future unit prices of the pavement materials through this research can be implemented to enhance the current LCCA procedure and predict more realistic unit prices and project costs for the future M&R activities, thus promoting the most cost-effective alternative in LCCA.

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