Ontario Ministry of Transportation

About: Ontario Ministry of Transportation is a government organization based out in Toronto, Ontario, Canada. It is known for research contribution in the topics: Poison control & Asphalt. The organization has 4652 authors who have published 3882 publications receiving 59011 citations.

Dissolved butyltins in marine waters of the netherlands three years after the ban

Abstract: In 1990 the Dutch government banned the use of tributyltin-containing antifouling paint for ships up to 25m long. Concentrations of dissolved (<0.45 μm) tributyltin and its degradation products di- and mono-butyltin were determined in six selected marinas during three consecutive years with a frequency of five times a year, starting in 1990. The highest butyltin concentrations were found in Scharendijke located in the salt water lake Grevelingen: up to 2500 ng dm−3. In tidal-water marinas butyltin concentrations were in the order of 50–300 ng dm−3, depending on the boating and dredging activity. In some marinas higher butyltin concentrations were found during the summer period, probably indicating the illegal use of tributyltin-containing antifouling paints. No clear trend of decrease in dissolved tributyltin concentrations in the different marinas has been found. Due to the equilibrium between the butyltins dissolved in the water and the butyltins adsorbed onto the sediment, water concentrations will remain more or less constant.

In situ measurements of sediment settling characteristics in floodplains using a LISST-ST

Abstract: Due to a lack of data on settling velocities (ws) and grain size distributions (GSDs) in floodplain environments, sedimentation models often use calibrated rather than measured parameters. Since the characteristics of suspended matter differ from those of deposited sediment, it is impossible to derive the ws and GSD from the latter. Therefore, one needs to measure in situ suspended sediment concentrations (SSCs), settling velocities, effective grain sizes and sedimentation fluxes. For this purpose we used the LISST-ST, a laser particle sizer combined with a settling tube. In 2002 (twice) and 2004, we located the LISST-ST with an optical backscatter sensor and sediment traps in two floodplains in The Netherlands: one along the unembanked IJssel River, another along the embanked Waal River. Measurements revealed that the SSC in the floodplains varied in relation to the SSC in the river channel. Smaller flocs dominated the SSC, while larger flocs dominated the potential sedimentation fluxes. The in situ GSD in the IJssel floodplain was significantly coarser than in the Waal floodplain, while the dispersed median grain sizes were equal for both floodplains. Therefore, the dispersed median grain size was two to five times smaller than the effective one. The in situ grain size exhibited a significant positive relationship with ws, although the ws for the largest flocs showed high variability. Consequently, the variability in sedimentation fluxes was also large. In the actual sedimentation fluxes, and hence in sedimentation models, in situ grain sizes up to about 20 µm can be neglected. In floodplain sedimentation models the relation between settling velocity and in situ grain size can be used instead of Stokes's law, which is only valid for dispersed grain sizes. These models should also use adequate data on flow conditions as input, since these strongly influence the suspended sediment characteristics. Copyright © 2005 John Wiley & Sons, Ltd.

Canadian experience with the micro-Deval test for aggregates

Abstract: Several aggregate test methods used in evaluating the mechanical strength and predicting the performance of aggregate have been in use since the 1930s. Today there is a need for precise tests that have a demonstrated correlation with field performance. The micro-Deval test has good multi-laboratory precision and is a suitable replacement for the sulphate soundness test for fine aggregate. A micro-Deval test on coarse aggregate is a useful means of predicting performance of aggregate in concrete, bituminous pavement and as granular base.

Pavement Crack Classification via Spatial Distribution Features

Abstract: Pavement crack types provide important information for making pavement maintenance strategies. This paper proposes an automatic pavement crack classification approach, exploiting the spatial distribution features (i.e., direction feature and density feature) of the cracks under a neural network model. In this approach, a direction coding (D-Coding) algorithm is presented to encode the crack subsections and extract the direction features, and a Delaunay Triangulation technique is employed to analyze the crack region structure and extract the density features. As regarding skeletonized crack sections rather than crack pixels, the spatial distribution features hold considerable feature significance for each type of cracks. Empirical study indicates a classification precision of over 98% of the proposed approach.