39 research outputs found

    Flexible pavements and climate change: impact of climate change on the performance, maintenance, and life-cycle costs of flexible pavements

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    Flexible pavements are environmentally sensitive elements of infrastructure and their performance can be influenced by climate. Climate change poses a challenge to design and management of flexible pavements in the future. Climate change can occur worldwide and thus all flexible pavements can be exposed to the impact. However, an assessment framework is not available to evaluate the impact of climate change on flexible pavements in terms of performance, maintenance decision-making and the subsequent life-cycle costs (LCC). This research has attempted to develop such a framework. Case studies on six flexible pavement sections from the United States were performed to demonstrate the application of the framework. The framework started with the investigation of climate change using IPCC’s (Inter-governmental Panel on Climate Change) climate change projections. Combinations of climate change projections and local historical climate were adopted as climatic inputs for the prediction of pavement performance. The Mechanistic-Empirical Pavement Design Guide (MEPDG) was used for prediction of pavement performance because it can provide reliable performance predictions with consideration of climatic factors. Pavement performance predictions were applied to schedule maintenance interventions. Maintenance effects of treatments were considered in maintenance decision-making. Maintenance effect models of International Roughness Index (IRI) and rutting were validated using pavement condition survey data from Virginia. With selected climate related LCC components, three maintenance interventions were optimised using a genetic algorithm to achieve the minimum LCC. Eventually the outputs of the system including pavement performance, intervention strategies, and LCC can be compared under various climate change and baseline scenarios. Hence, the differences in performance, decision-making, and LCC due to climate change can be derived. The conclusions were drawn based on the scheme of maintenance decision-making. If flexible pavements are not maintained (Alternative 0), an increase in LCC will be incurred by climate change due to an increase in road roughness (IRI). For pavements maintained with strict thresholds (Alternative 1), climate change may lead to a significant reduction in the service life when the maintenance is triggered by climate sensitive distress. However, benefit can be gained from decreasing LCC as the earlier triggered maintenance may result in less average IRI. As a consequence, user costs, which can be associated with IRI, can be reduced. Hence, LCC can be reduced as user costs usually dominate LCC. However, the net present value (NPV) of agency costs can be increased due to the early intervention. For pavements with optimised maintenance (Alternative 2), the LCC is almost unaffected by climate change. However, the type or application time of interventions may need to be changed in order to achieve this. Furthermore, the balance between agency and user costs did not seem to be influenced by climate change for Alternative 2. Agencies should be aware that maintenance optimisation can significantly reduce the LCC and make the best use of treatments to mitigate the effects of climate change on flexible pavements. Pavement maintained with strict triggers may require earlier interventions as a result of climate change but can gain benefit in LCC. However, this indicates that a responsive maintenance regime may not take full advantage of interventions and that maintenance could be planned to be performed earlier in order to achieve minimised LCC. Due to climate change, road users may spend more on fuels, lubricants and tyre wear on flexible pavement sections that do not receive any maintenance treatments

    Flexible pavements and climate change: impact of climate change on the performance, maintenance, and life-cycle costs of flexible pavements

    Get PDF
    Flexible pavements are environmentally sensitive elements of infrastructure and their performance can be influenced by climate. Climate change poses a challenge to design and management of flexible pavements in the future. Climate change can occur worldwide and thus all flexible pavements can be exposed to the impact. However, an assessment framework is not available to evaluate the impact of climate change on flexible pavements in terms of performance, maintenance decision-making and the subsequent life-cycle costs (LCC). This research has attempted to develop such a framework. Case studies on six flexible pavement sections from the United States were performed to demonstrate the application of the framework. The framework started with the investigation of climate change using IPCC’s (Inter-governmental Panel on Climate Change) climate change projections. Combinations of climate change projections and local historical climate were adopted as climatic inputs for the prediction of pavement performance. The Mechanistic-Empirical Pavement Design Guide (MEPDG) was used for prediction of pavement performance because it can provide reliable performance predictions with consideration of climatic factors. Pavement performance predictions were applied to schedule maintenance interventions. Maintenance effects of treatments were considered in maintenance decision-making. Maintenance effect models of International Roughness Index (IRI) and rutting were validated using pavement condition survey data from Virginia. With selected climate related LCC components, three maintenance interventions were optimised using a genetic algorithm to achieve the minimum LCC. Eventually the outputs of the system including pavement performance, intervention strategies, and LCC can be compared under various climate change and baseline scenarios. Hence, the differences in performance, decision-making, and LCC due to climate change can be derived. The conclusions were drawn based on the scheme of maintenance decision-making. If flexible pavements are not maintained (Alternative 0), an increase in LCC will be incurred by climate change due to an increase in road roughness (IRI). For pavements maintained with strict thresholds (Alternative 1), climate change may lead to a significant reduction in the service life when the maintenance is triggered by climate sensitive distress. However, benefit can be gained from decreasing LCC as the earlier triggered maintenance may result in less average IRI. As a consequence, user costs, which can be associated with IRI, can be reduced. Hence, LCC can be reduced as user costs usually dominate LCC. However, the net present value (NPV) of agency costs can be increased due to the early intervention. For pavements with optimised maintenance (Alternative 2), the LCC is almost unaffected by climate change. However, the type or application time of interventions may need to be changed in order to achieve this. Furthermore, the balance between agency and user costs did not seem to be influenced by climate change for Alternative 2. Agencies should be aware that maintenance optimisation can significantly reduce the LCC and make the best use of treatments to mitigate the effects of climate change on flexible pavements. Pavement maintained with strict triggers may require earlier interventions as a result of climate change but can gain benefit in LCC. However, this indicates that a responsive maintenance regime may not take full advantage of interventions and that maintenance could be planned to be performed earlier in order to achieve minimised LCC. Due to climate change, road users may spend more on fuels, lubricants and tyre wear on flexible pavement sections that do not receive any maintenance treatments

    Immediate effects of some corrective maintenance interventions on flexible pavements

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    Different maintenance interventions have different ability to address distresses on flexible pavements. Understanding the maintenance effects can benefit pavement maintenance decision-making. In this study, the immediate maintenance effects on roughness and rutting of three interventions including overlay, overlay with an additional base layer and mill and fill were studied and compared. A method was introduced to validate maintenance effect models, using the pavement management information from Virginia Department of Transportation. The method included a data mining process to extract data and apply regression analysis of maintenance effect models. The outliers in the analysis were detected and removed using the method of Cook’s distance. It was found that the immediate maintenance effects of overlay with base layer were greatest and mill and fill was least when treating pavements with moderate roughness (50–100 in/mi (≈ 0.8–1.6 m/km)). However, mill and fill was more useful for treating pavements with high roughness (>100 in/mi (≈1.6 m/km)). Furthermore, suggestions were proposed on data collection for road authorities to improve the prediction of maintenance effects

    Evaluating the effects of climate change on road maintenance intervention strategies and Life-Cycle Costs

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    Climate change has the potential to impact long-term road pavement performance. Consequently, to maintain pavements within the same ranges of serviceability as before, current pavement maintenance strategies need to be re assessed and, if necessary, changed. Changes in maintenance may lead to different agency costs and user costs as a consequence. This paper commences by defining an assessment procedure, showing how maintenance intervention strategies and Life-Cycle Costs (LCC) may be affected by future climate. A typical Virginia flexible pavement structure and anticipated climate change was used as an example. This example is believed to be representative for a great number of localities in the United States. A method using historical climatic data and climate change projections to predict pavement performance using Mechanistic-Empirical Pavement Design Guide (MEPDG) under current or future climate was introduced. Based on pavement performance prediction, maintenance interventions were planned and optimized. The maintenance effects of three treatments (thin overlay, thin overlay with an intermediate layer, and mill & fill) were considered. A Life-Cycle Cost analysis is reported that used binary non-linear programming to minimize the costs (either agency costs or total costs) by optimizing intervention strategies in terms of type and application time. By these means, the differences in maintenance planning and LCC under current and future climate can be derived. It was found, that for this simplified case study, pavement maintenance and LCC may be affected by climate change Optimized maintenance may improve resilience to climate change in terms of intervention strategy and LCC, compared to responsive maintenance

    State-of-the-art review of 3DPV technology: structures and models

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    © 2019 Elsevier Ltd Increasing energy conversion efficiency from sunlight to power is one of the key solutions for the world's energy shortage and greenhouse gas reduction, but the conventional flat photovoltaic module without sun tracking mechanism has the low sunlight energy collection ability. This paper presents the state-of-the-art three-dimensional photovoltaic (3DPV) technology with high photovoltaic energy conversion efficiency, which is able to absorb off-peak sunlight and reflected light more effectively, thereby it can generate more power. At first, this paper is to catalogue and critique different 3DPV structures and models, as well as assess their characteristics. Afterwards, the main influence factors on the 3DPV structures and models including shape, height and spacing of the solar cells, latitude of the installation, optimal device design and shadow cast, are reviewed. Finally, the challenges and future technological developments of 3DPV structures and models are highlighted. This study demonstrated that the 3DPV technology can increase the captured sunlight approximately 15–30% in comparison with the conventional flat PV technology

    Life cycle cost of flexible pavements and climate variability: case studies from Virginia

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    Climate factors have not become a typical metric to consider for pavement life cycle cost analysis (LCCA). Changes in climate may affect pavement rutting, roughness, and cracking and lead to consequent changes in maintenance decision-making and life cycle costs. This study develops a methodology to incorporate the effects of climate variability into flexible pavement LCCA and to derive the additional life cycle costs incurred due to changes in climate. Case studies were performed for three road sections in Virginia (US) to demonstrate the methodology, using approximate mean climate change trends predicted for the investigated regions. It is estimated that climate change will incur additional vehicle operating costs ranging between US2.30and2.30 and 4.40 on average per vehicle/annum if roads are used under a 2050 high greenhouse gas emission scenario and without being maintained. Assuming responsive maintenance, the budget demand for maintenance will arrive much earlier in the pavements' life cycles (7-11 years earlier under the 2050 high-emission scenario). This is found to add up to 64% of agency costs (net present value) to repair each kilometer of the investigated roads in a 40-year design life. Agencies need to be aware of earlier or more frequent demands on their maintenance budgets

    Energy performance and life cycle cost assessments of a photovoltaic/thermal assisted heat pump system

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    A photovoltaic/thermal module assisted heat pump system is investigated in this paper, which provides electrical and thermal energy for a domestic building. In-depth evaluation on the system energy production is conducted based on the finite difference method for a long-term operating period. The 25 years’ system life cycle cost is assessed via the Monte Carlo simulation under the Feed-in Tariff (FiT) and Renewable Heat Incentive schemes, the annual energy savings, income and payback period (PBP) are compared for the FiT and Smart Export Guarantee (SEG) schemes. The technical analysis results illustrate that the system is able to fulfil the building thermal and electrical energy demands from April to October and from May to August, respectively, and the extra electricity of 229.47 kWh is fed into the grid. The economic assessment results clarify that the system achieves a net present value (NPV) of £38,990 and has a PBP of 4.15 years. Meanwhile, the economic sensitive analyses reveal that the high discount rate reduces the system NPV whereas the high investment cost causes a long PBP to realize the positive NPV. Compared with the SEG scheme, the FiT is the most cost-effective method for renewable electricity generation and has the shortest PBP.N/

    Life Cycle Costs Analysis of Reclaimed Asphalt Pavement (RAP) Under Future Climate

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    Reclaimed asphalt pavement (RAP) has received wide application in asphalt pavement construction and maintenance and it has shown cost-effectiveness over virgin hot mix asphalt (HMA). HMA with a high content of reclaimed asphalt (RA) (e.g., 40%) is sometimes used in practice, however, it may have significant adverse effects on the life cycle performance and related costs. In particular, challenges may arise as the life cycle performance of RAP is also affected by local climatic conditions. Thus, it is important to investigate whether it is still economic to use RAP under future local climate, with consideration of life cycle performance. A case study was conducted for various road structures on Interstate 95 (I-95) in New Hampshire (NH), USA for the investigation. The case study utilized dynamic modulus testing results for local virgin HMA and HMA with 40% RA (as major material alternatives) to predict life cycle performance of the selected pavement structures, considering downscaled future climates. Then, a life cycle cost analysis (LCCA) was considered to estimate and compare the life cycle cash flow of the investigated road structures. Responsive maintenance (overlay) and effectiveness were also considered in this study. It was found that using 40% RA in HMA can reduce agency costs by up to approximately 18% under the 2020–2040 predicted climate and NH should consider this practice under predicted future climate to reduce agency costs

    Calculating rutting of some thin flexible pavements from repeated load triaxial test data

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    This paper describes parts of a Nordic pavement performance prediction model study (at the project level of the NordFoU project) where a material performance model, developed at VTT research centre in Finland, has been selected as a mean of calculating the permanently accumulated (plastic) deformation (i.e. rutting) of unbound granular materials (UGMs) in flexible pavements subjected to trafficking. The paper aims to assess the suitability of this VTT model application to Swedish roads comprising thin asphalt layers over a thick UGM base. To achieve this, the VTT model has been used to calculate the deformations of two tested road sections in Sweden. These calculations have been compared with another permanent deformation model for UGM (the Gidel model) and with rutting measurements from trafficked pavements. It is shown from this study that the applied rutting prediction method with VTT model is capable of predicting the development of rutting depth despite some overestimations

    Distributed Typhoon Track Prediction Based on Complex Features and Multitask Learning

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    Typhoons are common natural phenomena that often have disastrous aftermaths, particularly in coastal areas. Consequently, typhoon track prediction has always been an important research topic. It chiefly involves predicting the movement of a typhoon according to its history. However, the formation and movement of typhoons is a complex process, which in turn makes accurate prediction more complicated; the potential location of typhoons is related to both historical and future factors. Existing works do not fully consider these factors; thus, there is significant room for improving the accuracy of predictions. To this end, we presented a novel typhoon track prediction framework comprising complex historical features—climatic, geographical, and physical features—as well as a deep-learning network based on multitask learning. We implemented the framework in a distributed system, thereby improving the training efficiency of the network. We verified the efficiency of the proposed framework on real datasets
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