Four-Stage Multi-Physics Simulations to Assist Temperature Sensor Design for Industrial-Scale Coal-Fired Boiler

Gupta, Tanuj; Rahman, Mahabubur; Jiao, Xinyu; Wu, Yongji; Acharya, Chethan K.; Houston, Dock R.; Maley, Susan; Dong, Junhang; Xiao, Hai; Zhao, Huijuan

doi:10.3390/s24010154

Four-Stage Multi-Physics Simulations to Assist Temperature Sensor Design for Industrial-Scale Coal-Fired Boiler

Journal Article · Wed Dec 27 00:00:00 EST 2023 · Sensors

DOI:https://doi.org/10.3390/s24010154· OSTI ID:2263390

^[1]; ^[1]; Jiao, Xinyu ^[1]; ^[1]; Acharya, Chethan K. ^[2]; Houston, Dock R. ^[1]; Maley, Susan ^[3]; Dong, Junhang ^[4]; Xiao, Hai ^[1]; ^[1]

Clemson University, SC (United States)
Southern Company, Birmingham, AL (United States)
Electric Power Research Institute, Charlotte, NC (United States)
University of Cincinnati, OH (United States)

The growth of renewable energy sources presents a pressing challenge to the operation and maintenance of existing fossil fuel power plants, given that fossil fuel remains the predominant fuel source, responsible for over 60% of electricity generation in the United States. One of the main concerns within these fossil fuel power plants is the unpredictable failure of boiler tubes, resulting in emergency maintenance with significant economic and societal consequences. A reliable high-temperature sensor is necessary for in situ monitoring of boiler tubes and the safety of fossil fuel power plants. In this study, a comprehensive four-stage multi-physics computational framework is developed to assist the design, optimization installation, and operation of the high-temperature stainless-steel and quartz coaxial cable sensor (SSQ-CCS) for coal-fired boiler applications. With the consideration of various operation conditions, we predict the distributions of flue gas temperatures within coal-fired boilers, the temperature correlation between the boiler tube and SSQ-CCS, and the safety of SSQ-CCS. With the simulation-guided sensor installation plan, the newly designed SSQ-CCSs have been employed for field testing for more than 430 days. The computational framework developed in this work can guide the future operation of coal-fired plants and other power plants for the safety prediction of boiler operations.

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Research Organization:: Clemson Univ., SC (United States); Clemson University, SC (United States)

Sponsoring Organization:: USDOE; USDOE Office of Fossil Energy and Carbon Management (FECM)

Grant/Contract Number:: FE0031765

OSTI ID:: 2263390

Alternate ID(s):: OSTI ID: 2471841
OSTI ID: 2479526

Journal Information:: Sensors, Journal Name: Sensors Journal Issue: 1 Vol. 24; ISSN 1424-8220

Publisher:: MDPI AGCopyright Statement

Country of Publication:: United States

Language:: English

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