Journal of Infrastructure Systems

A review of the quality assurance practices of Alberta Transportation & Utilities was undertaken for each of three quality test measures: (1) Asphalt content; (2) percent compaction; and (3) aggregate gradation. The primary objective of the study was to determine how reducing the number of tests per lot affect the lot mean values and the degree of confidence in the quality results. The secondary objective was to determine the effect a change in the sample size would have on the quality-related price adjustments to the contractor. Two methods were used to compare the number of samples and their resulting mean values. First, the minimum number of samples required to stay within the variance allowed in the specifications, given the variance of the samples, was determined. Second, the mean values derived from sample sizes of five, four, and three were compared using one-way ANOVA and independent T-tests. The study found that the minimum number of tests for asphalt content, percent compaction, and aggregate gradation could be reduced. The effect on the price adjustments to the contractor given the reduced number of test samples was negligible.

This paper presents an approach for the joint optimization of maintenance and improvements of the components of a network of infrastructure facilities. In the literature, these two problems have often been handled separately, probably because the problems seem quite different. However, these decisions (maintenance and improvement) are not independent due to the presence of trade-offs between the two sets of policies. We develop a Markov decision model for the joint optimization of maintenance and improvement, thus improving the budget allocation among facilities in the network between the two sets of activities and within each set. The model is used to solve for steady-state policies, but relaxes the assumption of age-homogeneous condition-state transition probabilities, which has been criticized in the literature. Moreover, the model allows for the possibility of not exhausting the annual budget available every year, so that part of it can be spent more efficiently in later years. The paper includes a case study that demonstrates that substantial savings can be achieved through the joint optimization of maintenance and improvement policies.

The static dielectric constant and relaxation time of two asphalt aggregate mixes commonly used as the bearing and wearing courses of asphalt pavements are measured in the frequency range of 0.1 MHz to 1.5 GHz. The measurement is conducted on 70 laboratory-prepared asphalt aggregate specimens using a custom-designed complex permittivity measurement system. The results in the frequency range of 10 MHz and 1.5 GHz indicate that, under dry conditions, the static dielectric constant of the asphalt pavement materials tested in the range of 5–6, whereas the relaxation time is in the range of 100–400 picoseconds. The results show that within the range of field applications the static dielectric constant and relaxation time of asphalt pavement materials are independent of the mix type, density, and asphalt cement content. The moisture content is the predominant parameter controlling both the dielectric constant and relaxation time. When the moisture content of the asphalt samples increase above a characteristic moisture content of 1.2%, both dielectric constant and relaxation time increase considerably with further increase in moisture content.

Infrastructure condition throughout the lifetime of a facility is in part influenced by factors that are decided upon during initial design and construction. This paper presents a framework for exploring the sensitivity of the long-term infrastructure condition to changes in initital quality variables. Such variables, in addition to influencing design and construction costs, are expected to affect deterioration. Deterioration increases maintenance requirements and, consequently, the corresponding cost incurred in operating the system. Hence, there are two dimensions to the problem of interest. On the one hand, the economic perspective is concerned with the relationships among the costs associated with the various provision decisions and activities over the lifetime of a facility. On the other hand, the deterioration perspective is explicitly concerned with the actual initial quality and the physical degradation process. Two approaches aimed at exploring both dimensions are presented, and two corresponding example cases relating to light rail transit infrastructures and highway bridge decks are used for illustrative purposes. The value and limitations of both approaches along with their relationship are also discussed.

This paper documents the development, calibration, and evaluation of a novel simulation model for understanding and predicting failures of wastewater pipe systems. The model is presented and subsequently calibrated and evaluated, within the generalized likelihood uncertainty estimation framework, against a historical record of pipe failures in the Newcastle region. It is shown that the model has significant utility in many aspects of the operational management of the pipe system by providing a framework for disaggregation of the multiple environmental factors that contribute to the overall failure rate. The disaggregation is achieved within an uncertainty framework, thus providing quantified uncertainty estimates. Such analysis will be of significant use in life cycle analyses and costing of networks, and hence in optimizing replacement strategies, as well as in the assessment of regulatory compliance. Additionally, it is argued that the developed model can provide a rigorous basis for real-time forecasting of major trends in system failures through coupling to ENSO phenomena forecasts, thus providing valuable managerial insight into periods of expected high repair/replacement costs, to which current practice is largely reactive.