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Pervious concrete pavement (PCP) is of significant importance in the field of stormwater management in terms of reducing runoff volume. Stormwater managers should initially ensure that PCP adequately performs over time to be able to implement it in a stormwater management system. Performance models are intended to predict the performance of an asset over its service life. To develop a performance model commonly long-term performance data are essential. No performance model has been developed for PCP to date because PCP long-term performance data are rarely available. In such a case, expert knowledge is an alternative method to collect data for developing a performance model. This research aims to develop performance models for PCP for the first time by using an integrated Markov chain technique (combination of homogenous and non-homogenous techniques) through incorporation of expert knowledge. Both deterministic and stochastic approaches are applied to build up Markov models by using expected values and the Latin hypercube simulation technique, respectively. Both approaches provide consistent results although the stochastic Markov model provides more detailed results. Short-term experimental field data are also incorporated to validate the Markov performance models. [ABSTRACT FROM AUTHOR]

Because pervious concrete pavement (PCP) has a porous structure and can percolate water to an underground layer, it has been proposed as a stormwater best management practice (BMP), an environmentally friendly product, and sustainable paving materials. This porosity makes PCP susceptible to freeze-thaw damage in cold climates. Therefore, PCP has not been widely applied and investigated in such a climate. Long-term performance data are rarely available, and no performance model has been developed for PCP to date. The main objective of this research is to integrate expert knowledge (using the Markov-chain process) and experimental data (PCP field investigations) to build a performance model for PCP through incorporation of the Bayesian technique. The combination of these sources of data is an efficient and effective approach to build a performance model for a new type of pavement, such as PCP, which has not had a long-term performance database. As a result, a robust linear performance model is developed and applied to predict the service life of PCP. The service life of PCP is estimated to be approximately nine years using the developed performance model. In general, the expert knowledge leads to more conservative results rather than experimental data. [ABSTRACT FROM AUTHOR]

Pervious concrete pavement (PCP) has the potential to provide significant technical, economical, and environmental benefits. To better understand the beneficial impacts of PCP, its performance must be comprehensively evaluated and quantified. To evaluate the PCP performance, its pavement condition should be assessed. The primary aim of this research is to evaluate the PCP condition through incorporation of an adequate panel rating method. Two panel rating methods are evaluated for this purpose: visual digital inspection and in situ inspection. Field investigations are also conducted to record the surface distresses by describing their severity and density using the Ministry of Transportation of Ontario protocol. Finally, a model is developed and validated which relates mean panel rating (i.e., surface distress rating) to a pavement distress. It is concluded that the only significant variable (i.e., distress) in this model is raveling. [ABSTRACT FROM AUTHOR]

Development of an adequate performance model based on an appropriate condition index has been a major challenge for engineers particularly in case of a new type of design such as pervious concrete pavement structures (PCPSs) which suffer from limited long term performance data sets especially in colder climates. Soft computing techniques are significantly efficient at dealing with subjective, incomplete, and limited data. This paper proposes three most effective soft computing methods: fuzzy sets, the Latin Hypercube Simulation technique, and the Markov Chain process. A novel comprehensive condition index based on severity, density, and weighting factors of distresses occurring on PCPS has been developed incorporating fuzzy sets. A combination of homogeneous and nonhomogeneous Markov Chain has been applied to develop performance models. Transition probability matrices are presented using probability distribution functions rather than single values. A simulation technique is then used to incorporate the probability distribution function operations to compute the future condition of the pavements. The future performance of the pavements is expressed by both single expected values and suitable probability distribution functions. Ultimately, a probabilistic versus deterministic performance curve is presented. [ABSTRACT FROM AUTHOR]

Two types of analysis were conducted to examine the impacts of midcentury scenarios of anthropogenic climate change on flexible pavement infrastructure in southern Canada. An analysis of deterioration-relevant climate indicators at 17 southern Canadian sites revealed that over the next 50 years low temperature cracking will become less problematic, structures will freeze later and thaw earlier with correspondingly shorter freeze season lengths, and higher extreme in-service pavement temperatures will raise the potential for rutting. Pavement performance simulations conducted using the mechanistic-empirical pavement design guide and data from the Canadian long term pavement performance program for six of these sites also suggest that rutting issues will be exacerbated by climate change and that maintenance, rehabilitation, or reconstruction will be required earlier in the design life. While the simulated effect of climate change was found to be modest, both in absolute terms and relative to variability in pavement structure and baseline traffic loads, pavement engineers would benefit by incorporating longer time series of weather and climate in their designs. Although the analysis was conducted for southern Canada, many of the findings and impacts may be similar for the northern United States. [ABSTRACT FROM AUTHOR]