A study of frost growth and densification on flat surfaces
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Both the data and the model indicate that frost growth increases with a decrease in the cold plate temperature.
“Both the data and the model indicate that the frost growth increases with a decrease in the cold plate temperature, as is to be expected.”
From Frost growth and densification in laminar flow over flat surfaces (2011) · cites this paper as [9]
The present model favorably compares with the measurements of Hermes et al. [9] for frost thickness for various wall temperatures, except for T = 257 K where the error is relatively large.
“The present model favorably compares with the measurements for various wall temperatures, except for T = 257 K where the error is relatively large.”
From Frost growth and densification in laminar flow over flat surfaces (2011) · cites this paper as [9]
In the early frost growth period, the predicted frost thickness generally exceeds the test data for relatively high wall temperatures, while for the low wall temperature the trend is opposite.
“It is noticed that in the early frost growth period, the predicted frost thickness generally exceeds the test data for relatively high wall temperatures, while for the low wall temperature the trend is opposite.”
From Frost growth and densification in laminar flow over flat surfaces (2011) · cites this paper as [9]
This effect arises due to an augmentation in the supercooling degree that results in a higher overall mass flux and a lower frost density.
“This effect arises due to an augmentation in the supercooling degree that results in a higher overall mass flux and a lower frost density (Hermes [9]).”
From Frost growth and densification in laminar flow over flat surfaces (2011) · cites this paper as [9]
With a decrease in wall temperature, frost thickness increases, while frost surface temperature and frost density decrease.
“The results suggest that with a decrease in wall temperature, the frost thickness increases, while the frost surface temperature and the frost density decrease.”
From Frost growth and densification in laminar flow over flat surfaces (2011) · cites this paper as [9]
In general, the model satisfactorily describes the data for frost growth, frost surface temperature and frost density for t = 60 min and 120 min.
“In general, the model satisfactorily describes the data for frost growth, frost surface temperature and frost density for t = 60 min and 120 min.”
From Frost growth and densification in laminar flow over flat surfaces (2011) · cites this paper as [9]
As relative humidity increases, frost thickness increases with an accompanying increase in frost surface temperature and frost density.
“It is also noticed form the data that as the relative humidity increases, the frost thickness increases with an accompanying increase in frost surface temperature and frost density.”
From Frost growth and densification in laminar flow over flat surfaces (2011) · cites this paper as [9]
Compared with Wong's model [57], the present model exhibits closer agreement with the experimental data reported in Ref. [51], yielding an average deviation of only 10.43% for δfr.
“Compared with Wong ' s model [57], the present model exhibits closer agreement with the experimental data reported in Ref. [51], yielding an average deviation of only 10.43% for δ fr.”
From A physics-informed quasi-steady frosting model with coupled heat–mass transfer for predicting frost layer growth (2026) · cites this paper as [51]
When the datasets of Hermes et al. [51] and Kwon et al. [63] are considered together, most predictions fall within the ±15% error band.
“most predictions fall within the ± 15% error band”
From A physics-informed quasi-steady frosting model with coupled heat–mass transfer for predicting frost layer growth (2026) · cites this paper as [51]
This behavior can be rationalized by δfr increasing with Ta when Fp is fixed; combining Eqs. (7) and (8) shows that higher air-flow temperature elevates both the moisture flux qtot and the frost-layer temperature Tfs, and their coupling constrains the variation range of m''ρ, potentially stabilizing it.
“This behavior can be rationalized by δ fr increasing with T a when F p is fixed [51,62]; combining Eqs. (7) and (8) shows that higher air-flow temperature el evates both the moisture flux q tot and t and the frost-layer temperature T fs, and their coupling constrains the variation range of m”
From A physics-informed quasi-steady frosting model with coupled heat–mass transfer for predicting frost layer growth (2026) · cites this paper as [51]
Existing simulation models rely on empirical information for frost properties, particularly frost density.
“In general, such models assume a quasi-static growth of the frost layer, invoke the Lewis analogy for the sake of mass transfer calculations, and rely on empirical information for the frost properties, particularly the frost density (Hermes et al., 2009).”
From Algebraic modeling and thermodynamic design of fan-supplied tube-fin evaporators running under frosting conditions (2014) · cites this paper as Hermes et al., 2009
Existing simulation models invoke the Lewis analogy for mass transfer calculations.
“In general, such models assume a quasi-static growth of the frost layer, invoke the Lewis analogy for the sake of mass transfer calculations, and rely on empirical information for the frost properties, particularly the frost density (Hermes et al., 2009).”
From Algebraic modeling and thermodynamic design of fan-supplied tube-fin evaporators running under frosting conditions (2014) · cites this paper as Hermes et al., 2009
Existing simulation models assume quasi-static growth of the frost layer.
“In general, such models assume a quasi-static growth of the frost layer, invoke the Lewis analogy for the sake of mass transfer calculations, and rely on empirical information for the frost properties, particularly the frost density (Hermes et al., 2009).”
From Algebraic modeling and thermodynamic design of fan-supplied tube-fin evaporators running under frosting conditions (2014) · cites this paper as Hermes et al., 2009
A similar real-time frost accumulation measurement method was used by Sengupta et al., Hermes et al., and Sommers et al.
“A similar method was used for the measurement of real-time frost accumulation by Sengupta et al. [83], Hermes et al. [52], and Sommers et al. [126].”
From Review on the measurement and calculation of frost characteristics (2018) · cites this paper as [52]
Using new experimental data obtained by Hermes et al. in 2009, Kandula proposed a more complete dimensionless density correlation that took into account wall temperature and air velocity.
“Using these new experimental data obtained by Hermes et al. in 2009 [52], Kandula [54] proposed a more complete dimensionless density correlation, and took into account the wall temperature and the air velocity.”
From Review on the measurement and calculation of frost characteristics (2018) · cites this paper as [52]
Based on Hayashi et al.'s correlation, a third coefficient was further introduced.
“Based on this correlation, they further introduced a third coefficient [52].”
From Review on the measurement and calculation of frost characteristics (2018) · cites this paper as [52]
Hermes et al. [50] believed that not only frost surface temperature, but also cold surface temperature should be considered in developing the correlation of average frost density; their correlation fitted well with their own experimental data.
“considered in developing the correlation of average frost density. Their correlation also fitted well with their own experimental data.”
From Frosting mechanism and behaviors on surfaces with simple geometries: A state-of-the-art literature review (2022) · cites this paper as Hermes et al. [50]
Kandula [51] proposed a correlation of average frost density based on dimensionless analysis; it was a function of dimensionless temperature based on frost and cold surface temperatures, and Reynolds number, and was determined from Hermes et al.'s experimental data [50].
“Kandula [51] proposed another correlation of average frost density based on dimensionless analysis. The correlation was a function of dimensionless temperature based on frost and cold surface temperatures, and Reynolds number, and was determined from Hermes et al. ' s experimental data [50].”
From Frosting mechanism and behaviors on surfaces with simple geometries: A state-of-the-art literature review (2022) · cites this paper as Hermes et al. [50]
The water vapor density gradient inside the frost layer near the plate surface was significantly smaller than that near the frost surface.
“For water vapor density, its gradient inside the frost layer near the plate surface was significantly smaller than that near the frost surface [50,80,86,88,90,91].”
From Frosting mechanism and behaviors on surfaces with simple geometries: A state-of-the-art literature review (2022) · cites this paper as [50]
Hermes et al., Benitez and Sherif, and You et al. all presented a linear temperature distribution characteristic inside the frost layer on a flat plate with a fixed surface temperature.
“Hermes et al. [50], Benitez and Sherif [88], and You et al. [93] all presented a linear temperature distribution charac teristic.”
From Frosting mechanism and behaviors on surfaces with simple geometries: A state-of-the-art literature review (2022) · cites this paper as [50]
Frost density increases with an increase in air moisture content.
“density was increased with an increase in air moisture content [50,54]”
From Frosting mechanism and behaviors on surfaces with simple geometries: A state-of-the-art literature review (2022) · cites this paper as [50]
In some studies, the average frost thickness on flat plates with a fixed surface temperature decreases with an increase in air temperature.
“In some studies, the average frost thickness was decreased with an increase in air temperature [50,54,61,80].”
From Frosting mechanism and behaviors on surfaces with simple geometries: A state-of-the-art literature review (2022) · cites this paper as [50]
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“The active area interested by the mass transfer is Aact(j), evaluated as the sum of the fin area Afin(j) and of the tube area At(j), with both of them varying with the row due to the variation of frost thickness df(j): AtðjÞ ¼ Nt 2 p ðre þ df ðjÞÞ þ ½Lev Nfin ðdfin þ 2 df ðjÞÞ ð17Þ AfinðjÞ ¼ 2 Nr Bev Hev Nt p 4 ð2 re…”
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Frosting in heat pump evaporators part A: experimental investigation
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Negrelli, S., Cardoso, R. P., & Hermes, C. J. L. (2016) · International Journal of Heat and Mass Transfer · doi:10.1016/j.ijheatmasstransfer.2016.05.135 · Cited by 35 · see citing works
Sommers, A. D., Napora, A. C., Truster, N. L., Caraballo, E. J., & Hermes, C. J. L. (2016) · International Journal of Refrigeration · doi:10.1016/j.ijrefrig.2016.10.025 · Cited by 33 · see citing works
Moradkhani, M., Hosseini, S. H., Lei, S., & Song, M. (2022) · Applied Thermal Engineering · doi:10.1016/j.applthermaleng.2022.119258 · Cited by 30 · see citing works
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Bulk water freezing dynamics on superhydrophobic surfaces
Chavan, S., Carpenter, J., Nallapaneni, M., Chen, J. Y., & Miljkovic, N. (2017) · Applied Physics Letters · doi:10.1063/1.4974296 · Cited by 32 · see citing works
Lee, S.-H., Lee, M., Yoon, W., & Kim, Y. (2013) · International Journal of Heat and Mass Transfer · doi:10.1016/j.ijheatmasstransfer.2013.04.018 · Cited by 29 · see citing works
Chen, G., Deng, X., Zhang, G., & Yan, X. (2019) · International Journal of Heat and Mass Transfer · doi:10.1016/j.ijheatmasstransfer.2018.12.133 · Cited by 31 · see citing works
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Chang, S., Song, H., & Wu, K. (2021) · Sustainable Energy Technologies and Assessments · doi:10.1016/j.seta.2021.101128 · Cited by 30 · see citing works
Shangwen, L., Mengjie, S., Chaobin, D., Yingjie, X., & Keke, S. (2022) · Applied Thermal Engineering · doi:10.1016/j.applthermaleng.2022.118470 · Cited by 34 · see citing works
Three dimensional reconstruction of frost structure by replica method
Takayashiki, M., Nishimura, K., Ściążko, A., Okabe, T., Taniguchi, J., & Shikazono, N. (2022) · International Journal of Heat and Mass Transfer · doi:10.1016/j.ijheatmasstransfer.2022.123280 · Cited by 30 · see citing works
Choi, S.-G., & Kim, S. (2017) · International Journal of Heat and Mass Transfer · doi:10.1016/j.ijheatmasstransfer.2017.05.033 · Cited by 25 · see citing works
A semi-empirical model for predicting frost accretion on hydrophilic and hydrophobic surfaces
Hermes, C., Sommers, A., Gebhart, C. W., & Nascimento, V. (2017) · International Journal of Refrigeration · doi:10.1016/j.ijrefrig.2017.09.022 · Cited by 31 · see citing works
Evaporator Frosting in Refrigerating Appliances: Fundamentals and Applications
Hermes, C., Boeng, J., da Silva, D. D., Knabben, F. T., & Sommers, A. (2021) · Energies · doi:10.3390/en14185991 · Cited by 26 · see citing works
“The frost formation over a flat surface can be divided into several steps [17], as schematized in Figure 7.”
BackgroundInfluentialYoo, J., Chung, Y., Kim, G. T., Song, C.-W., Yoon, P., Sa, Y., & Kim, M. S. (2018) · International journal of refrigeration · doi:10.1016/j.ijrefrig.2018.08.014 · Cited by 22 · see citing works
Frosting in a heat pump evaporator part B: Numerical analysis
Popovac, M., Emhofer, J., & Reichl, C. (2021) · Applied Thermal Engineering · doi:10.1016/j.applthermaleng.2021.117488 · Cited by 26 · see citing works
de Loyola, F. R., Junior, V. S. D. N., & Hermes, C. J. L. (2014) · International Journal of Heat and Mass Transfer · doi:10.1016/j.ijheatmasstransfer.2014.08.055 · Cited by 26 · see citing works
Real-time frost porosity detection using capacitance sensing approach
Shen, Y., & Wang, X. (2019) · International Journal of Heat and Mass Transfer · doi:10.1016/j.ijheatmasstransfer.2019.02.060 · Cited by 26 · see citing works
An experimental study on the frost formation over a flat plate: Effect of frosting on heat transfer
Saygin, A., Başol, A. M., & Arık, M. (2023) · Experimental Thermal and Fluid Science · doi:10.1016/j.expthermflusci.2023.110862 · Cited by 26 · see citing works
Hosseini, S., Rezaei, M., Bag-Mohammadi, M., Zendehboudi, A., & Ahmadi, G. (2019) · Applied Thermal Engineering · doi:10.1016/j.applthermaleng.2018.11.022 · Cited by 26 · see citing works
Fixed grid numerical modelling of frost growth and densification
Bartrons, E., Galione, P., & Perez-Segarra, C. (2019) · International Journal of Heat and Mass Transfer · doi:10.1016/j.ijheatmasstransfer.2018.10.080 · Cited by 24 · see citing works
A frost model based on the frost layer's supporting function
Xu, Z., Wang, Z., Liang, Z., Chen, H., & Han, Z. (2023) · International Journal of Heat and Mass Transfer · doi:10.1016/j.ijheatmasstransfer.2022.123741 · Cited by 26 · see citing works
Frost formation and freeze protection with bypass for counter-flow recuperators
Jedlikowski, A., Anisimov, S., Danielewicz, J., KARPUK, M. M., & Pandelidis, D. (2016) · International Journal of Heat and Mass Transfer · doi:10.1016/j.ijheatmasstransfer.2016.12.047 · Cited by 24 · see citing works
Abbas, S., & Park, C. (2021) · International Journal of Heat and Mass Transfer · doi:10.1016/j.ijheatmasstransfer.2020.120883 · Cited by 25 · see citing works
Heat and mass transfer inside the rotary heat exchanger operating under high speed rotor conditions
Jedlikowski, A., Kanaś, P., & Anisimov, S. (2020) · International Journal of Heat and Mass Transfer · doi:10.1016/j.ijheatmasstransfer.2020.119558 · Cited by 24 · see citing works
Predictive models on the frost formation for plain surface - a review and comparative study
Li, S.-M., & Wang, C.-C. (2021) · International Communications in Heat and Mass Transfer · doi:10.1016/j.icheatmasstransfer.2021.105670 · Cited by 24 · see citing works
Optimal defrost cycle for air coolers revisited: A study of fan-supplied tube-fin evaporators
da Silva, D. L., & Hermes, C. J. L. (2018) · International Journal of Refrigeration · doi:10.1016/j.ijrefrig.2018.02.009 · Cited by 22 · see citing works
Wong, J. C. Q., Pareek, V. K., & Sun, B. (2022) · International Journal of Heat and Mass Transfer · doi:10.1016/j.ijheatmasstransfer.2022.123396 · Cited by 23 · see citing works
Study of frosting on a cryogenic surface from a perspective of thermal resistance analysis
Qi, Y., Ye, H., Hu, Q., Zhi, X., & Qiu, L. (2022) · Applied Thermal Engineering · doi:10.1016/j.applthermaleng.2022.118158 · Cited by 21 · see citing works
Condensation frosting detection and characterization using a capacitance sensing approach
Shen, Y., & Wang, S. (2019) · International Journal of Heat and Mass Transfer · doi:10.1016/j.ijheatmasstransfer.2019.118968 · Cited by 20 · see citing works
Lei, S., Song, M.-J., Dai, W., Zhan, T.-Z., & Shao, K.-K. (2022) · Experimental Thermal and Fluid Science · doi:10.1016/j.expthermflusci.2022.110684 · Cited by 8 · see citing works
Ribeiro, R. S., & Hermes, C. J. L. (2014) · Applied Thermal Engineering · doi:10.1016/j.applthermaleng.2014.05.012 · Cited by 19 · see citing works
Liang, X.-Y., & Wu, L. (2022) · Energy and Buildings · doi:10.1016/j.enbuild.2022.112366 · Cited by 18 · see citing works
Analysis of the frost formation and freeze protection with bypass for cross-flow recuperators
Jedlikowski, A., & Anisimov, S. (2017) · Applied Thermal Engineering · doi:10.1016/j.applthermaleng.2017.01.105 · Cited by 19 · see citing works
- Authors
- Hermes, C. J. L., Piucco, R. O., Barbosa, J. R., & Melo, C.
- Affiliations
- Universidade Federal de Santa Catarina (BR)
- Corresponding author
- Hermes, Christian J.L.
- Venue
- Experimental Thermal and Fluid Science
- Publisher
- Elsevier BV
- Published
- 2009-01
- Volume
- 33
- Issue
- 2
- Pages
- 371-379
- ISSN
- 0894-1777 (ISSN-L)
- OpenAlex
- W2041674410
- Cited by
- 257
- References
- 12
- Citations by year
- 2026: 12 · 2025: 22 · 2024: 24 · 2023: 18 · 2022: 27 · 2021: 23 · 2020: 11 · 2019: 15 · 2018: 20 · 2017: 21 · 2016: 13 · 2015: 14 · 2014: 11 · 2013: 7 · 2012: 9
- FWCI
- 6.49
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Experimental Thermal and Fluid Science (publishedVersion)
- Funders
- Financiadora de Estudos e Projetos
- Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
- Conselho Nacional de Desenvolvimento Científico e Tecnológico
- Topics
- Physical Sciences › Engineering › Aerospace Engineering › Icing and De-icing Technologies
- Physical Sciences › Engineering › Mechanical Engineering › Refrigeration and Air Conditioning Technologies
- Physical Sciences › Engineering › Mechanical Engineering › Heat Transfer and Optimization
- Keywords
- frost growth, frost thickness, porous media, supersaturation, mass and energy balance, air humidity, air velocity, surface temperature
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