An experimental study of air–steam condensation on the exterior surface of a vertical tube under natural convection conditions

Lee, Yeon-Gun; Jang, Yeong-Jun; Choi, Dong-Jae

doi:10.1016/j.ijheatmasstransfer.2016.09.016

Cited by 71 publications

(18 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The reference test for this study [20], which provides the rate of heat transfer for the bare tube, has measured the condensation heat transfer coefficients in the presence of air on a vertical cylinder under natural convection conditions. The experiments were conducted in a pressure range of 2-5 bar and an air mass fraction ranging from 0.10 to 0.88.…”

Section: Methodsmentioning

confidence: 99%

“…The experimental work of this study was also conducted at the Jeju National University (JNU) condensation test facility of reference [20], with an exception that the test section was replaced to encompass the annular finned tube. Details of the experimental apparatus, including the newly fabricated finned tube, and the data reductions are as follows.…”

Section: Methodsmentioning

confidence: 99%

“…From a sufficiently thick tube with the same diameter as the designed annular disk, the portions other than the fins (hatched region in Figure 4) were cut off through a lathe turning so that the perfect contact of fins to the base surface can be assured. The diameter of the base tube was determined to be 40 mm, which is the same as that of the condenser tube used in reference [20], and its effective length was 1000 mm. The diameter of the outer edge of the designed annular fin was 80 mm; it is the maximum diameter when the PCCS tube bundle is designed to have the pitch-to-diameter of 2.0.…”

Section: Experimental Apparatusmentioning

confidence: 99%

“…The rate of condensation heat transfer was measured in the pressure range from 2 to 5 bar, and the air mass fraction was adjusted from 30% to 70%. The mean temperature of the base surface was also controlled to establish the similar thermal conditions on which the condensation tests with the bare tube [20] were performed. …”

Section: Data Reductionmentioning

confidence: 99%

“…In all of the tests, the mass flow rate of the coolant was quite high to maintain the temperature of the outer wall uniform [20]. As the rise of the coolant temperature is low, the uncertainty in evaluation of the heat removal rate, represented by Equation (7), could be fairly high.…”

Section: Data Reductionmentioning

confidence: 99%

See 4 more Smart Citations

Enhancement of Condensation Heat Transfer Rate of the Air-Steam Mixture on a Passive Condenser System Using Annular Fins

et al. 2017

Self Cite

View full text Add to dashboard Cite

This paper presents an experimental investigation on the enhancement of the heat transfer rate of steam condensation on the external surfaces of a vertical tube with annular fins. A cylindrical condenser tube, which is 40 mm in outer diameter and 1000 mm in length, with annular disks of uniform cross-sectional area is fabricated in the manner of ensuring perfect contact between the base surface and fins. A total of 13 annular fins of 80 mm diameter were installed along the tube height in order to increase the effective heat transfer area by 85%. Through a series of condensation tests for the air-steam mixture under natural convection conditions, the heat transfer data was measured in the pressure range of between 2 and 5 bar, and the air mass fraction from 0.3 to 0.7. The rates of heat transfer of the finned tube are compared to those that are measured on a bare tube to demonstrate the enhanced performance by extended surfaces. In addition, based on the experimental results and the characteristics of steam condensation, the applicability of finned tubes to a large condenser system with a bundle layout is evaluated.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Experimental Apparatusmentioning

confidence: 99%

Section: Data Reductionmentioning

confidence: 99%

Section: Data Reductionmentioning

confidence: 99%

See 3 more Smart Citations

Enhancement of Condensation Heat Transfer Rate of the Air-Steam Mixture on a Passive Condenser System Using Annular Fins

et al. 2017

Self Cite

View full text Add to dashboard Cite

show abstract

Derivation of a Condensation Heat Transfer Model for Light Water Reactor Applications Using Machine Learning Techniques

Albdour,

Addad,

Afgan

2024

Lecture Notes in Mechanical Engineering

View full text Add to dashboard Cite

A Predictive Machine Learning-Based Analysis for In-Tube Co-current Steam Condensation Heat Transfer in the Presence of Non-condensable Gases

Albdour,

Addad,

Afgan

2024

Arab J Sci Eng

View full text Add to dashboard Cite

The primary objective of this study is to develop a predictive model that accurately estimates the condensation heat transfer coefficient (HTC) in the context of in-tube co-current flow condensation, with specific consideration given to the influence of non-condensable gases (NCGs). The need to find useful models and/or correlations that can accurately predict how well a passive condenser in the Economic Simplified Boiling Water Reactor will transfer heat during condensation is greatly warranted. This innovative cooling system utilizes gravity to condense water vapor, effectively dissipating heat from the containment vessel in the event of an accident and transferring the heat into the secondary cooling system. For the development of the forecasting model, we employed Multi-Gens Genetic Programming implemented in MATLAB. This approach possesses the capability of enabling visualization and articulating a transparent mathematical expression that directly establishes the connection between inputs and outputs. This model was specifically developed for forecasting the HTC during the condensation process, considering two distinct types of NCG: air, helium, and a mixture of air and helium, in addition to data for pure steam. The model was trained using a dataset comprising 2913 data points gathered from five experimental references. The model's input comprises a varied range of parameters, including local location ($$z$$ z ), temperature of the steam/NCG mixture ($${T}_{mix}$$ T mix ), condenser wall temperature ($${T}_{wall}$$ T wall ), coolant flow rate ($$\beta_{c}$$ β c ), total pressure ($${P}_{tot}$$ P tot ), condenser inner diameter ($${D}_{1}$$ D 1 ), condenser outer diameter ($${D}_{2}$$ D 2 ), molecular weight (MM), NCG mass fraction ($${w}_{NCG}$$ w NCG ), and mixture Reynolds number ($${Re}_{mix}$$ Re mix ). The output of our model corresponds to the condensation HTC ($$h$$ h ). Four specific correlations were examined with the third correlation attaining the highest anticipated values within a deviation range of ± 30, reaching 90.9%, exhibiting good performance in terms of both performance index and coefficient of determination. This correlation was validated, and its accuracy assessed by employing an unused training dataset that included nitrogen as a NCG. The outcomes showed that 92.94% of the predicted data fell within a deviation range of ± 30%. The findings of this study signify a notable advancement in the analysis of datasets obtained from experiments. Particularly, it delves into the impact of NCGs by considering their molecular weight and mass fraction.

show abstract

An experimental study of air–steam condensation on the exterior surface of a vertical tube under natural convection conditions

Cited by 71 publications

References 20 publications

Enhancement of Condensation Heat Transfer Rate of the Air-Steam Mixture on a Passive Condenser System Using Annular Fins

Enhancement of Condensation Heat Transfer Rate of the Air-Steam Mixture on a Passive Condenser System Using Annular Fins

Derivation of a Condensation Heat Transfer Model for Light Water Reactor Applications Using Machine Learning Techniques

A Predictive Machine Learning-Based Analysis for In-Tube Co-current Steam Condensation Heat Transfer in the Presence of Non-condensable Gases

Contact Info

Product

Resources

About