Experimental investigations on brass material and pin–fin based heat transfer system and its modeling by using adaptive neuro-fuzzy inference system

Bahl, Shashi; Singh, Sarva Jit; Goyal, Parveen; Bagha, Ashok Kumar

doi:10.1016/j.matpr.2021.01.910

Cited by 3 publications

(2 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Bahl et al [43] e predictions obtained by using the ANFIS model are found to be very close to the experimental findings which prove that the model proposed is capable to accurately predict the behavior of heat transfer system.…”

supporting

confidence: 64%

See 1 more Smart Citation

Analysis and Implementation of Thermal Heat Exchanger Tube Performance with Helically Pierced Twisted Tape Inserts Using ANFIS Model

Altarazi

Kumar

Gupta

et al. 2021

Mathematical Problems in Engineering

View full text Add to dashboard Cite

The present work used ANFIS, an adaptive neuro-fuzzy inference system modeling to analyze the effect of the variable parameters of helically pierced twisted tape inserts on the Nusselt number, friction factor, and thermo-hydraulic heat exchanger tube performance. The experimental data utilized for ANFIS modeling considered a diameter ratio ranging from 0.57 to 0.80, a relative pitch ratio ranging from 0.046 to 0.107, a perforation index ranging from 5% to 20% as variable twisted tape parameters and flow parameters. The Reynolds number varies from 4000 to 30000. The analysis showed that the maximum thermo-hydraulic performance was obtained at a diameter ratio of 0.65, a relative pitch ratio of 0.085, and a perforation index equal to 10%. The result predicts that the ANFIS model and experimental results are in good agreement as they have only ±0.53% deviations.

show abstract

supporting

confidence: 64%

“…e ANFIS predictions show a good agreement with the CFD results. Saee et al [39], Beiki [40], Bahiraei et al [41], Yashawantha and Vinod [42], Bahl et al [43], Safarzadeh et al [44], and Safarzadeh et al [44] used the ANFIS model for different heat transfer enhancement applications, and their major findings are listed in Table 1.…”

Section: Introductionmentioning

confidence: 99%