TL;DR: In this article, the grain-size distribution of the suspended load above a sand bed is computed using the Gessler method and the Rouse suspension equation, and a new formula has also been developed in partial modification of Hunt's method for direct computation of bed load and suspended load from a bed's grain size distribution and flow parameters.
Abstract: Computation of the grain-size distribution of the suspended load above a sand bed must take into consideration: (1) sorting processes from the bed to the bed layer and (2) sorting between the bed layer and suspension. Grain-size distributions of the bed layers above sand beds of three different types have been computed in this work, both by the Einstein and the Gessler methods. Using these as references, suspended load distributions have been obtained in each case by the Rouse suspension equation. A new formula has also been developed in partial modification of Hunt's method for direct computation of bed load and suspended load from a bed's grain-size distribution and flow parameters.
Comparison of the computed data with actual observations in laboratory flumes show that no one method is particularly superior to the others, but the present method is advantageous because it affords direct computation of the suspended load from a bed's grain-size distribution, without going through an intermediate stage (bed load). The possible sources of error in each of the methods have been discussed.
TL;DR: In this article, the rate of fuel flow and bed depth are simultaneously controlled in response to variations in a load demand signal representing the need for steam output from the system, and the system changes the flow of limestone to the bed to change the bed depth to respond more slowly to the change in the demand signal.
Abstract: In a fluidized boiler system, the rate of fuel flow and bed depth are simultaneously controlled in response to variations in a load demand signal representing the need for steam output from the system. When the load demand changes, the rate of fuel flow is varied accordingly to provide a change in the bed temperature to thus provide a rapid response to the change in the demand signal. At the same time, the system changes the rate of flow of limestone to the bed and the rate of removal of spent particulate material of the bed to change the bed depth to respond more slowly to the change in the demand signal. As the depth of the fluidized bed approaches a value corresponding to the demand signal, the temperature of the bed will change back toward a median value.
TL;DR: In this paper, a one-dimensional numerical model designed to simulate sediment transport in natural channels is described, and the physical processes associated with the sediment movement are reproduced using a variety of algorithms.
Abstract: : This report describes a one-dimensional numerical model designed to simulate sediment transport in natural channels. The physical processes associated with the sediment movement are reproduced using a variety of algorithms. These algorithms incorporate sets of equations that operate on input data in a predetermined sequence to generate output data reproducing the actual physical process. A satisfactory model must include the more relevant aspects of that process. Sediment moves driven by hydrodynamic forces exerted by the flow of water which in many instances is highly time dependent. The sediment transport model must, therefore, account for unsteadiness in sediment movement. The dependence of sediment motion on flow conditions makes it also dependent on the longitudinal variations the flow experiences as a result of stream boundary irregularities. These variations are reflected in the spatial variability of the sediment load distribution. Depending on particle size, some particles may be carried primarily in suspension, while others move entirely as bed load. In addition, depending on flow conditions, particles moving in suspension at one place may be moving as bed load farther downstream.