An experimental study of critical heat flux with surface modification and its analytic prediction model development

Kim, Seung Jun

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https://hdl.handle.net/2142/34324 Copy

Description

Title

An experimental study of critical heat flux with surface modification and its analytic prediction model development

Author(s)

Kim, Seung Jun

Issue Date

2012-09-18T21:11:23Z

Director of Research (if dissertation) or Advisor (if thesis)

Jones, Barclay G.

Doctoral Committee Chair(s)

Jones, Barclay G.

Committee Member(s)

• Jones, Barclay G.
• Axford, Roy A.
• Uddin, Rizwan
• Newell, Ty A.

Department of Study

Nuclear, Plasma, & Rad Engr

Discipline

Nuclear Engineering

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• Critical heat flux (CHF)
• Sub-cooled flow boiling
• surface wettability
• correlation development

Abstract

The critical heat flux (CHF) condition causes a drastic reduction of heat transfer coefficient and sometimes involves physical failure of the heating surface in heat flux-controlled systems. Understanding of CHF phenomena and reliable CHF prediction model development are necessary to design various heat transfer systems including nuclear fission reactors, fossil-fueled boilers, thermo-nuclear fusion reactors, etc. Many aspects of CHF phenomena are well understood and reasonable prediction models have been developed. However, due to the complex natures of phenomena, CHF in sub-cooled flow boiling is still an active research topic. This experimental study examines the effects of various operating system conditions including; system pressure, mass flow rate, sub-cooled temperature, and surface wettability upon CHF under sub-cooled flow boiling conditions. An analytical CHF prediction model also has been proposed using the bubble force balance. Sub-cooled flow boiling is generally characterized by high heat transfer rate and low wall superheat, which is essential for cooling applications requiring high heat transfer rates, such as in nuclear reactors and fossil power plants. In this study, sub-cooled flow boiling tests were conducted using R-134a coolant in a rectangular channel (half inch by half inch) with one uniformly heated surface. This is a surface heat flux controlled system. This refrigerant is selected as a stimulant fluid for water due to its small surface tension, low latent heat, and low boiling temperature. The experiments were conducted under the following conditions: (1) inlet pressure (P) of 400 ~ 800 KPa, (2) specific mass flow rate (G) of 124 ~ 248 kg/m2-s, (3) inlet sub-cooling enthalpy ( ) of 9 ~ 45kJ/kg. By varying experimental operating conditions, CHF was identified by monitoring a sudden rise in heated wall temperature. It was found that CHF in a rectangular channel increases with increasing mass flow rate, increasing inlet sub-cooling, and increasing system pressure. The parametric trend of the CHF data using R-134a in a rectangular channel is consistent with classic understanding of CHF in round tubes using water in relatively low pressure (less than 0.2 reduced pressures). In addition, a Fluid-to-Fluid scaling model was utilized to convert the test data obtained in the simulant fluid (R-134a) into the prototypical fluid (water). The comparison between the converted CHF of equivalent water and CHF look-up table with same operation conditions were conducted, and show good agreement. In order to investigate heating surface feature effects on CHF, surface modification, applying Atmospheric Pressure Plasma (AP-Plasma) coating, was performed on the copper heating block. It is considered that the AP-Plasma treated surface does not affect boiling heat transfer directly, but rather via change in microscopic surface parameters such as wettability and static contact angle, parameters that the proposed CHF prediction model incorporates. The surface oxidation coating with AP-Plasma makes the surface features (static contact angle, oxidation layer thickness) become more hydrophilic and reduces the static contact angle from 80˚ to 10˚. 10~18% of CHF enhancement under flow boiling conditions were found with AP-Plasma treated heating surfaces compared to those of non-treated heating surfaces. To understand the different flow boiling characteristics on these modified heating surfaces, the surface features such as static contact angle at the solid-fluid interface, the coating layer thickness were observed and measured for different experimental conditions utilizing advanced goniometer [Rame-hart model 500] and oxidation layer thickness measurement device [Sloan Dektak3]. Liquid droplet contact angle reduction by AP-Plasma indicated that an 80˚ static contact angle with pure copper block and a 10˚ static contact angle with AP-Plasma treated surface. The thickness of oxidation layer ranges from 1 to 3 micro meters. The analytic CHF prediction model based on physical bubble force balance with consideration of surface characteristics is also developed in this study. A comparative study of the proposed model with a previous model (Katto et al., 1984) was conducted over the range of the current experimental conditions. The Katto model predicts the CHF within 30% of maximum deviation for current experiment CHF data; however, the proposed model predicts the CHF within only 8% maximum deviation. In order to validate with other researcher’s CHF measurement, author’s proposed model is utilized to predict the CHF value with various operating conditions (total number of 155 CHF data points: working fluid: R134-a, water, Freon-113, FC72) provided by different research group’s experimental CHF data. It shows good agreement. This proposed analytical model is the first correlation incorporating the surface feature variable (Static contact angle) into the CHF prediction in flow boiling conditions. In current experimental tests, as the contact angle becomes smaller, the CHF become enhanced in flow boiling conditions. The surface wettability effect on CHF observed in experimental test (AP-Plasma treated surface vs. Non-treated surface) is well captured in analytical CHF prediction model.

Graduation Semester

2012-08

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Copyright and License Information

Copyright 2012 Seung-Jun Kim

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