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An Integrated Approach to Predicting Ash Deposition and Heat Transfer in Coal-Fired Boilers

DOE

Source: doe_osti
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The overall goal of this project is to develop via measurements and simulations an advanced online technology to predict, monitor and manage fireside ash deposition in a coal-fired boiler allowing for more efficient operations under a range of load conditions and fuel property variability. With this in place fuel sorting and blending can be done upstream and operations can be optimized to compensate for load and fuel properties. In support of this objective, three experimental campaigns were undertaken during the course of the project to measure ash deposition rates within the boiler at different fuel flow rates and its ash composition variability. Simulations of the experimental conditions representing actual geometry, operational scenarios in terms of air flow rates, coal flow rates as well as coal compositions, heating values, and particle size distributions were also carried out. Deposition rates were predicted using a unique particle kinetic energy and viscosity based ash deposition methodology whose validity was ascertained by comparing against deposition rate measurements for widely varying operating conditions and ash compositions in a lab-scale furnace. With a unique end-to-end combustion modeling methodology established and different simulation scenarios carried out, the results from our computational fluid dynamic (CFD) simulations in conjunction with the plant data summarized in this report were used to refine Microbeam Technology Incorporated’s MTI CSPI-CT Tool to predict and monitor fire-side ash deposition under a range of load conditions and fuel property variability in real time.. Authors: Krishnamoorthy, Gautham [Univ. of North Dakota, Grand Forks, ND (United States)]; Benson, Steve A. [Microbeam Technologies, Inc., Grand Forks, ND (United States)]. DOE Contract: FE0031741. Subjects: 01 COAL, LIGNITE, AND PEAT; Ash Deposition; CFD; Cyclone-Fired; Lignite; Measurements; Variable Load

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