2000
DOI: 10.2514/2.2613
|View full text |Cite
|
Sign up to set email alerts
|

Heat and Mass Transfer in the Case of Anti-Icing System Simulation

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

2
24
0

Year Published

2007
2007
2024
2024

Publication Types

Select...
6
3

Relationship

0
9

Authors

Journals

citations
Cited by 42 publications
(26 citation statements)
references
References 11 publications
2
24
0
Order By: Relevance
“…differences of the ice shapes obtained by the two methods were small, except when ΔT=1 K. Near the ends of the icing area, the ice thicknesses were relatively large with a high ice accretion rate, which was also found by Morency [33]. As shown in Figure 11, the temperature differences in the transverse direction were quite large near the ends of the icing area, so that extra heat flow was taken away to the downstream region by the heat conduction of the solid skin, and more water froze there to form peaks.…”
Section: Results Of Case 22bsupporting
confidence: 74%
“…differences of the ice shapes obtained by the two methods were small, except when ΔT=1 K. Near the ends of the icing area, the ice thicknesses were relatively large with a high ice accretion rate, which was also found by Morency [33]. As shown in Figure 11, the temperature differences in the transverse direction were quite large near the ends of the icing area, so that extra heat flow was taken away to the downstream region by the heat conduction of the solid skin, and more water froze there to form peaks.…”
Section: Results Of Case 22bsupporting
confidence: 74%
“…The initial freezing rate in both upper and lower surfaces was approximately 0:4 g=s m. Figure 11 shows the present model predictions, the experimental data, and the numerical results of ANTICE [16] solid surface temperature distribution for case 67A. The same predictions, experimental data, and CANICE A results [19] are presented in Fig. 12.…”
Section: Simulation Resultsmentioning
confidence: 62%
“…The second source of uncertainty affects the evaluation of deviation between numerical results and experimental data at locations with strong streamwise solid surface temperature gradients (dT wall =ds) such as the end of the liquid water film. Figure 9 shows the comparison between the present code predictions, Al-Khalil et al [16] experimental data, and CANICE A and CANICE B numerical results [19] for the airfoil solid surface temperatures of case 22A. In Fig.…”
Section: Simulation Resultsmentioning
confidence: 84%
“…Morency et al [24] implemented a numerical code for anti-ice simulation and validated its results with experimental data from Al-Khalil et al [21]. The authors published results of two versions of the main code: 1) CANICE A, which uses an experimental overall heat transfer coefficient; and 2) CANICE B, which uses an estimated by momentum and heat transfer analogy [11], a transition position arbitrarily imposed or estimated by Michel's classic correlation [25], and for fully the turbulent boundary layer, uses the turbulent expression developed by Ambrok [26].…”
Section: Previous Workmentioning
confidence: 99%