Journal of Hydraulic Engineering

Solid pipeline deposits can be mapped by analyzing reflections of hydraulic pressure pulse waves in the low-frequency range. To determine the amount and position of the deposits, an inverse problem is solved: the pressure pulse is measured in one or several positions, and the pipeline that generated this pulse must be determined. To solve this problem, estimates of the pressure pulse velocity are essential. This study implements a finite-element axisymmetric model for fluid-filled pipelines and applies it to numerically study low-frequency estimates of the pressure wave velocity in pipes with deposits that appear frequently in pipelines of the petroleum industry. Finite-element simulations include deposit thicknesses in the range up to and covering 90% of the internal diameter of the pipe. The results show how deposits with different stiffness affect the pressure wave velocity. Inputs to the model are the geometry and parameters (thickness, Young’s modulus, and Poisson’s ratio) of the pipe and the deposits.

In river hydraulics, there is a continuing need for characterizing bed elevations to arrive at quantitative roughness measures that can be used in flow depth calculations and for improved prediction of fine-sediment transport over and through coarse beds. Recently published prediction methods require a method for estimating the cumulative distribution function (CDF) of bed elevations. Representing the distribution of elevations for rough beds requires a correct choice for the number and spacing of measurement locations. Laboratory experiments over a screeded flat gravel bed with sand having median diameter $D_{50}=35\mathrm{mm}$ were used to determine the number and spatial coverage of measurements needed to define the elevation field for a range of uncertainty levels. Approximately 1,000–5,000 randomly collected single elevation measurements were needed to quantify the distribution of elevations for the gravel bed. Relative error in estimating the standard deviation of elevations was insensitive to the number and spacing of elevation measurements when the spacing exceeded $D_{50}$ (35 mm). The standard deviation of bed elevations was found to be proportional to the median bed material size for several different gravel beds. A method is presented for generating a CDF for bed elevations using the elevation-distribution standard deviation with a randomly sampled distribution function.

Upper Mississippi River flow and sediment characteristics downstream of St. Louis are presented in this study. Available and measured data were used to assess a harbor siltation case and dredging needs. Such data are also useful to researchers and engineers conducting work in the Mississippi River and large rivers in general. Flows were characterized in terms of the mean annual hydrograph, flow duration curve, and mean annual, dominant, and effective discharges. Suspended and bed material sediments were characterized by grain-size distributions (GSDs). Suspended-sediment concentrations were characterized with a sediment rating curve, mean annual sediment graph, and duration curve. The results of the analyses were used to assess harbor sedimentation by comparing GSDs of harbor bed samples with those observed in the river. Bathymetric surveys were used to determine rates and occurrence of sedimentation. The analyses showed that harbor siltation correlates with river conditions and is driven by wash load in the river, which enters the harbor in suspension and deposits along the bottom due to the lack of flow-through velocities high enough to keep the fine sediments in suspension.

Experimental analyses and prototype observations of a debris flow drainage channel with energy dissipation structures were performed in this study. On the basis of 160 groups of experiments, a simple empirical relationship was proposed to determine the roughness coefficient of an energy dissipation structure section in a drainage channel. The experimental results suggest that the comprehensive roughness coefficient gradually increases with increases in the area of the energy dissipation structure section. Meanwhile, the comprehensive roughness coefficient gradually approaches the roughness coefficient of the smooth channel as the area of the energy dissipation structure section decreases to less than 10% of the channel area. Moreover, the debris flow velocity measured in the prototype drainage channel validated the effectiveness of the empirical relationship. Therefore, this calculation method is beneficial in optimizing the design of drainage channels with energy dissipation structures.