ANALYSIS OF HYPORHEIC FLOW INDUCED BY A BAR IN A GRAVEL STREAM: AN EXPERIMENTAL STUDY

Pipelines are one of the safest means to transport crude oil, but are not spill-free. This is of concern in North America, due to the large volumes of crude oil shipped by Canadian producers and the lengthy network of pipelines. Each pipeline crosses many rivers, supporting a wide variety of human activities, and rich aquatic life. However, there is a knowledge gap on the risks of contamination of river beds due to oil spills. This thesis addresses this knowledge gap by focussing on mechanisms that transport water (and contaminants) from the free surface flow to the bed sediments, and vice-versa. The work focuses on gravel rivers, in which bed sediments are sufficiently permeable that pressure gradients caused by the interactions of flow with topographic elements (gravel bars), or changes in direction induce exchanges of water between the free surface flow and the bed, known as hyporheic flows. The objectives of the thesis are: to present a new method to visualize and quantify hyporheic flows in laboratory experiments; to conduct a novel series of experiments on hyporheic flow induced by a gravel bar under different free surface flows. The new method to quantify hyporheic flows rests on injections of a solution of dye and water. The method yielded accurate flow lines, and reasonable estimates of the hyporheic flow velocities. The present series of experiments was carried out in a 11 m long, 0.39 m wide, and 0.41 m deep tilting flume. The gravel had a mean particle size of 7.7 mm. Different free surface flows were imposed by changing the flume slope and flow depth. Measured hyporheic flows were turbulent. Smaller free surface flow depths resulted in stronger hyporheic flows (higher velocities, and deeper dye penetration into the sediment). A significant finding is that different free surface flows (different velocities, Reynolds number, etc.) produce similar hyporheic flows as long as the downstream hydraulic gradients are similar. This suggests, that for a specified bar geometry, the characteristics of the hyporheic flows depend on the downstream hydraulic gradients, and not or only minimally on the internal dynamics of the free surface flow.

RELIBILITY ANALYSIS OF SIMPLE SLOPES AND SOIL-STRUCTURES WITH LINEAR LIMIT STATES

The first objective of this research was to develop closed-form and numerical probabilistic methods of analysis that can be applied to otherwise conventional methods of unreinforced and geosynthetic reinforced slopes and walls. These probabilistic methods explicitly include random variability of soil and reinforcement, spatial variability of the soil, and cross-correlation between soil input parameters on probability of failure. The quantitative impact of simultaneously considering the influence of random and/or spatial variability in soil properties in combination with cross-correlation in soil properties is investigated for the first time in the research literature. Depending on the magnitude of these statistical descriptors, margins of safety based on conventional notions of safety may be very different from margins of safety expressed in terms of probability of failure (or reliability index). The thesis work also shows that intuitive notions of margin of safety using conventional factor of safety and probability of failure can be brought into alignment when cross-correlation between soil properties is considered in a rigorous manner. The second objective of this thesis work was to develop a general closed-form solution to compute the true probability of failure (or reliability index) of a simple linear limit state function with one load term and one resistance term expressed first in general probabilistic terms and then migrated to a LRFD format for the purpose of LRFD calibration. The formulation considers contributions to probability of failure due to model type, uncertainty in bias values, bias dependencies, uncertainty in estimates of nominal values for correlated and uncorrelated load and resistance terms, and average margin of safety expressed as the operational factor of safety (OFS). Bias is defined as the ratio of measured to predicted value. Parametric analyses were carried out to show that ignoring possible correlations between random variables can lead to conservative (safe) values of resistance factor in some cases and in other cases to non-conservative (unsafe) values. Example LRFD calibrations were carried out using different load and resistance models for the pullout internal stability limit state of steel strip and geosynthetic reinforced soil walls together with matching bias data reported in the literature.