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Published on: April 30, 2018
Comparison of Models for Heat Transfer in High-Density Fibrous Insulation
Sergio A Carvajal1, Edward J Garboczi2, Robert R Zarr3
1Instituto Nacional de Metrología de Colombia, Bogotá, DC 111321 Colombia.
This study compares thermal conductivity models for fibrous insulation, validating them against certified data. It highlights the importance of accurately modeling coupled radiation and conduction heat transfer for effective insulation performance.
Area of Science:
- Materials Science
- Thermal Engineering
- Heat Transfer
Background:
- Accurate calculation of effective thermal conductivity is crucial for fibrous insulation performance.
- Coupled radiation and conduction heat transfer significantly influence insulation properties.
- Standard Reference Material 1450c provides a benchmark for evaluating thermal models.
Purpose of the Study:
- To evaluate and compare various models for calculating the effective thermal conductivity of fibrous insulation.
- To assess the impact of coupled radiation and conduction heat transfer on model accuracy.
- To validate model predictions using certified values of Standard Reference Material 1450c.
Main Methods:
- Fiber diameter distribution was measured using X-ray computed tomography.
- Radiative heat transfer was evaluated using diffusion, Schuster-Schwarzschild, and Milne-Eddington approximations.
- Conduction was modeled using kinetic theory for gas and a semi-empirical model for fibers.
- Radiative properties were assessed using large specular reflecting and Mie theory approaches.
Main Results:
- Model predictions were compared against certified values for Standard Reference Material 1450c.
- The study analyzed the coupled effects of radiation and conduction heat transfer.
- The accuracy of different radiative and conductive heat transfer models was assessed.
Conclusions:
- The study provides a comparative evaluation of thermal conductivity models for fibrous insulation.
- Accurate characterization of fiber diameter distribution is essential for model inputs.
- The findings contribute to the development of more reliable insulation performance prediction methods.
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