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Research Papers

Characterization of a Computational Fluid Dynamics Thermocouple Model Subjected to Stochastic Environmental Forcing Using Moment Based Analysis

[+] Author and Article Information
Craig G. Weinschenk

e-mail: craigweinschenk@gmail.com

O. A. Ezekoye

e-mail: dezekoye@mail.utexas.edu
Department of Mechanical Engineering,
The University of Texas at Austin,
204 E. Dean Keeton Street, Stop C2200,
Austin, TX 78712

1Corresponding author.

Manuscript received October 29, 2012; final manuscript received April 5, 2013; published online October 9, 2013. Assoc. Editor: Ranganathan Kumar.

J. Thermal Sci. Eng. Appl 5(4), 041012 (Oct 09, 2013) (10 pages) Paper No: TSEA-12-1191; doi: 10.1115/1.4024703 History: Received October 29, 2012; Revised April 05, 2013

With increasing requirements for model validation when comparing computational and experimental results, there is a need to incorporate detailed representations of measurement devices within the computational simulations. Thermocouples are the most common temperature measurement transducers in flames and fire environments. Even for the relatively simple thermocouple transducer, the coupling of heat transfer mechanisms particularly under unsteady flow conditions leads to interesting dynamics. As experimentalists are well aware, the experimentally determined thermocouple values are not the same as the local gas temperatures and corrections are often required. From the computational perspective, it is improper then to assume that the predicted gas temperatures should be the same as the temperatures that an experimentalist might measure since the thermal characteristics of the thermocouple influence the indicated temperature. The thermal characteristics of simulated thermocouples in unsteady flame conditions are investigated. Validation exercises are presented to test the underlying thermocouple model. The thermocouple model problem is examined for a quasi-steady problem in which the gas temperature and surrounding walls are assumed to be random and described by probability density functions (PDFs). Differences are noted between the predicted thermocouple response and expected response. These differences are interpreted from the perspective of what modeling artifacts might drive the differences.

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Figures

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Fig. 1

Flow chart showing the connection between experimental gas temperature and experimental measurements

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Fig. 2

Illustration of deriving a functional value, z, based on representative mean values, x and y

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Fig. 3

Smokeview rendering of thermocouple modeling test configuration

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Fig. 4

FDS thermocouple response comparison to FDS gas temperature with a bead diameter of 1 mm at z = 0.5 m from a 400  °C hot air source

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Fig. 5

FDS thermocouple response comparison to FDS gas temperature with a bead diameter of 1 mm at z = 1.5 m from a 400  °C hot air source

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Fig. 6

FDS thermocouple response comparison to FDS gas temperature with a bead diameter of 3 mm at z = 0.5 m from a 400  °C hot air source

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Fig. 7

FDS thermocouple response comparison to FDS gas temperature with a bead diameter of 3 mm at z = 1.5 m from a 400  °C hot air source

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Fig. 8

Schematic of the convection simulation

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Fig. 9

FDS comparison to analytical model in convection

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Fig. 10

Schematic of the radiation simulation

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Fig. 11

FDS comparison to analytical model in radiation

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Fig. 12

FDS thermocouple model comparison to experiments at an elevation of 1.6 m with a 400 kW source fire

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Fig. 13

FDS thermocouple model comparison to experiments at an elevation of 1.6 m with a 400 kW source fire

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Fig. 14

Representation of PDFs of gas temperature (Tg) and wall temperature (Tw) being combined to find the unknown distribution for thermocouple temperature (TTC)

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Fig. 15

PDFs of gas temperature (α = 1.0, β = 1.0) and wall temperature (α = 2.0, β = 0.1)

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Fig. 16

Representation of the quadrature points and weights of gas temperature (Tg) and wall temperature (Tw) distributions being combined to find the unknown distribution for thermocouple temperature (TTC)

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