TY - GEN
T1 - Study of turbulence models application in crossflow turbine analysis
AU - Gunadi, Gun Gun R.
AU - Siswantara, Ahmad Indra
AU - Budiarso,
AU - Daryus, Asyari
AU - Pujowidodo, Hariyotejo
N1 - Funding Information:
The authors would like to thanks DRPM Universitas Indonesia for funding this research and to PT. CCIT Group Indonesia for CFDSOF® software license.
Publisher Copyright:
© 2019 Author(s).
PY - 2019/1/25
Y1 - 2019/1/25
N2 - The CFD method, as the initial analysis has more benefits regarding experiments, including saving time and costs. Variable of flow parameters and geometry can be developed easily to get the desired results. However, research is needed to improve the accuracy of the results and the efficiency of the calculation process. The study of complex turbulent flow modeling becomes very important. The k-ϵ model, and renormalization group (RNG) k-ϵ model are widely used in research, to produce the appropriate models and develop the value of constants. This turbulent flow modeling research was conducted to improve the accuracy of the results and the efficiency of the calculation process in turbulent flow of crossflow turbine. Research is done by comparing the simulation results of k-ϵ model and RNG k-ϵ model. The comparison of the k-ϵ model and RNG k-ϵ model results shows different results for predicting the average pressure and velocity distribution in turbulent flow of crossflow turbine. Likewise for turbulent parameters. It can be concluded for complex fluid flow recommending RNG k-ϵ model.
AB - The CFD method, as the initial analysis has more benefits regarding experiments, including saving time and costs. Variable of flow parameters and geometry can be developed easily to get the desired results. However, research is needed to improve the accuracy of the results and the efficiency of the calculation process. The study of complex turbulent flow modeling becomes very important. The k-ϵ model, and renormalization group (RNG) k-ϵ model are widely used in research, to produce the appropriate models and develop the value of constants. This turbulent flow modeling research was conducted to improve the accuracy of the results and the efficiency of the calculation process in turbulent flow of crossflow turbine. Research is done by comparing the simulation results of k-ϵ model and RNG k-ϵ model. The comparison of the k-ϵ model and RNG k-ϵ model results shows different results for predicting the average pressure and velocity distribution in turbulent flow of crossflow turbine. Likewise for turbulent parameters. It can be concluded for complex fluid flow recommending RNG k-ϵ model.
UR - http://www.scopus.com/inward/record.url?scp=85061114653&partnerID=8YFLogxK
U2 - 10.1063/1.5086561
DO - 10.1063/1.5086561
M3 - Conference contribution
AN - SCOPUS:85061114653
T3 - AIP Conference Proceedings
BT - 10th International Meeting of Advances in Thermofluids, IMAT 2018 - Smart City
A2 - Yatim, Ardiyansyah
A2 - Nasruddin, null
A2 - Budiyanto, Muhammad Arif
A2 - Aisyah, Nyayu
A2 - Alhamid, Muhamad Idrus
PB - American Institute of Physics Inc.
T2 - 10th International Meeting of Advances in Thermofluids - Smart City: Advances in Thermofluid Technology in Tropical Urban Development, IMAT 2018
Y2 - 16 November 2018 through 17 November 2018
ER -