Infrastructure Condition Prediction Models for Sustainable Sewer Pipelines

The Federation of Canadian Municipalities reported that approximately 55% of sewer infrastructure in Canada did not meet current standards. Therefore, the burden on Canadian municipalities to maintain and prioritize sewers is increasing. One of the major challenges is to develop a framework to standardize the condition assessment procedures for sewer pipelines. Lack of detailed knowledge on the condition of sewer networks escalates vulnerability to catastrophic failures. This research presents a proactive methodology of assessing the existing condition of sewers by considering various physical, environmental, and operational influence factors. Based on historic data collected from two municipalities in Canada, structural and operational condition assessment models for sewers are developed using the multiple regression technique. The developed regression models show 82 to 86% accuracy when they are applied to the validation data set. These models are utilized to generate deterioration curves for concrete, asbestos cement, and polyvinyl chloride sewers in relation to traffic loads, bedding materials, and other pipe characteristics. The developed models are expected to assist municipal engineers in identifying critical sewers, prioritizing sewer inspections, and rehabilitation requirements.     

Shape-Based Retrieval of Construction Site Photographs

Digital photographs of construction site activities are gradually replacing their traditional paper based counterparts. Existing digital imaging technologies in hardware and software make it easy for site engineers to take numerous photographs of “interesting” processes and activities on a daily basis. The resulting photographic data are evidence of the “as-built” project, and can therefore be used in a number of project life cycle tasks. However, the task of retrieving the relevant photographs needed in these tasks is often burdened by the sheer volume of photographs accumulating in project databases over time and the numerous objects present in each photograph. To solve this problem, the writers have recently developed a number of complementary techniques that can automatically classify and retrieve construction site images according to a variety of criteria (materials, time, date, location, etc.). This paper presents a novel complementary technique that can automatically identify linear (i.e., beam, column) and nonlinear (i.e., wall, slab) construction objects within the image content and use that information to enhance the performance of the writers’ existing construction site image retrieval approach.     

Evaluation of Characterization Techniques for Iron Pipe Corrosion Products and Iron Oxide Thin Films

A common problem faced by drinking water studies is that of properly characterizing the corrosion products (CP) in iron pipes or synthetic Fe (hydr)oxides used to simulate the iron pipe used in municipal drinking-water systems. The present work compares the relative applicability of a suite of imaging and analytical techniques for the characterization of CPs and synthetic Fe oxide thin films and provide an overview of the type of data that each instrument can provide as well as their limitations to help researchers and consultants choose the best technique for a given task. Crushed CP from a water distribution system and synthetic Fe oxide thin films formed on glass surfaces were chosen as test samples for this evaluation. The CP and synthetic Fe oxide thin films were analyzed by atomic force microscopy (AFM), scanning electron microscopy (SEM), energy-dispersive spectroscopy, time-of-flight secondary ion mass spectrometry (ToF-SIMS), X-ray powder diffractometry (XRD), grazing incident diffractometry (GID), transmission electron microscopy (TEM), selected area electron diffraction, X-ray photoelectron spectroscopy (XPS), Fourier transform infrared, M?ssbauer spectroscopy, Brunauer–Emmett–Teller N2 adsorption and Fe concentration was determined by the ferrozine method. XRD and GID were found to be the most suitable techniques for identification of the mineralogical composition of CP and synthetic Fe oxide thin films, respectively. AFM and a combined ToF-SIMS–AFM approach proved excellent for roughness and depth profiling analysis of synthetic Fe oxide thin films, respectively. Corrosion products were difficult to study by AFM due to their surface roughness, while synthetic Fe oxide thin films resisted most spectroscopic methods due to their limited thickness (118?nm). XPS analysis is not recommended for mixtures of Fe (hydr)oxides due to their spectral similarities. SEM and TEM provided great detail on mineralogical morphology.     

At-Rest Earth Pressure of Overconsolidated Cohesionless Soil

Earth pressure theories occupy a paramount position in the field of geotechnical engineering. An experimental investigation of the at-rest earth pressure of overconsolidated cohesionless soil acting on retaining walls was conducted. A prototype model of a vertical rough wall, retaining horizontal backfill, was developed in the laboratory. The model was instrumented to measure the earth pressure at selected points on the wall, the total earth force acting on the wall, and the overconsolidation ratio (OCR) in the sand mass. Tests were conducted on walls retaining homogeneous overconsolidated dense, medium, or loose sands. Test results showed that the coefficient of at-rest earth pressure increases with the increase of the OCR. The present experimental results were used to examine the empirical formulas available in the literature. It can be reported that these formulas compared well with the experimental results for OCR values up to 3. An empirical formula is proposed to predict the coefficient of at-rest earth pressure for overconsolidated cohesionless soils. The results obtained by this formula agreed well with the present experimental results for all values of overconsolidation ratios.     

A comparison between the advection-dispersion and the Kolmogorov-Dmitriev model for groundwater contaminant transport

The growing interest of the scientific and public community in environmental problems has sparked the undertaking of several activities of protection from pollutants, of remediation of contaminated sites and of design of deposits for toxic or radioactive waste. The implementation and management of these activities require the use of mathematical models for predicting the behaviour of the pollutant in the geosphere; of particular interest is the study of the transport of contaminants in the groundwater system, which provides an important pathway of return of the hazard to the biosphere.In this paper a comparison is made between the traditional advection-dispersion model, which is the most widely used model of groundwater contaminant transport, and a stochastic model based on the Kolmogorov-Dmitriev theory of branching processes. The behaviour of the two models is analysed in the case of transport with and without retardation of contaminant in the solid matrix and, in the latter case, both equilibrium and non-equilibrium processes are considered.The results obtained show that for non-reactive contaminant and for reactive contaminant under equilibrium, the Kolmogorov-Dmitriev parameters are related by simple relations with the advection-dispersion parameters. Moreover, the Kolmogorov-Dmitriev model is capable of describing more realistic non-equilibrium phenomena, that the advection-dispersion cannot treat. This capability arises from the fact of treating explicitly the reactions of contaminant interchange between the liquid and solid phases.     

Factors affecting sorption of pentachlorophenol to suspended microbial biomass

Sorption and desorption of pentachlorophenol (PCP) to microbial biomass was studied in a series of laboratory experiments. Equilibrium conditions for sorption and desorption were established within 5 min after a step change in concentrations. Linear sorption isotherms were observed at up to 80 μg/l of dissolved PCP at pH 6, and up to 160 μg/l at pH 8. Linear sorption coefficients were primarily influenced by pH, although ionic strength (owing to pH-buffering) and the concentration of dissolved organic matter also had an impact. The influence of these factors was quantified by a simple mathematical model, which included separate sorption coefficients for the neutral and dissociated fraction of PCP.     

Field thermal performance of naturally ventilated solar roof with PCM heat sink

For decades, residential and commercial roofs have been considered a prime location for installation of building integrated solar systems. In climatic conditions of East Tennessee, USA, an experimental solar roof was tested during 2009/2010, by a research team representing Metal Construction Association (MCA), and a consortium of building insulation companies, photovoltaic (PV) manufacturers, and energy research centers. The main objective was to thermally evaluate a new roofing technology utilizing amorphous silicon PV laminates integrated with the metal roof panels. In order to mitigate thermal bridging and reduce roof-generated thermal loads, this novel roof/attic assembly contained a phase change material (PCM) heat sink, a ventilated air cavity over the roof deck, and thermal insulation with an integrated reflective surface. During winter, the experimental roof was expected to work as a passive solar collector storing solar heat absorbed during the day, and increasing overall attic air temperature during the night. During summer, the PCM was expected to act as a heat sink, reducing the heat gained by the attic and consequently, lowering the building cooling-loads.In this paper, field thermal performance data of the experimental PV-PCM roof/attic system are presented and discussed. Performance of the PV-PCM roof/attic is evaluated by comparing it to a control asphalt shingle roof. The test results showed about 30% heating and 50% cooling load reductions are possible with the experimental roof configuration.     

Using Soft Computing to Analyze Inspection Results for Bridge Evaluation and Management

The national bridge inventory (NBI) system, a database of visual inspection records that tallies the condition of bridge elements, is used by transportation agencies to manage the rehabilitation of the aging U.S. highway infrastructure. However, further use of the database to forecast degradation, and thus improve maintenance strategies, is limited due to its complexity, nonlinear relationship, unbalanced inspection records, subjectivity, and missing data. In this study, soft computing methods were applied to develop damage prediction models for bridge abutment walls using the NBI database. The methods were multilayer perceptron network, radial basis function network, support vector machine, supervised self-organizing map, fuzzy neural network, and ensembles of neural networks. An ensemble of neural networks with a novel data organization scheme and voting process was the most efficient model, identifying damage with an accuracy of 86%. Bridge deterioration curves were derived using the prediction models and compared with inspection data. The results show that well developed damage prediction models can be an asset for efficient rehabilitation management of existing bridges as well as for the design of new ones.