Fundamental study on the effect of pulsative inflow on a small scale room model: Simulation of an innovative ventilation solution
Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Simulation of a wall jet in an enclosure performed to predict the effect of pulsation flow on improving the performance of mixing ventilation systems which are routine practices in industry. Comparing two flows with equal amount for constant and pulsation modes, it was found out that the same global airflow pattern exists for both of the cases but with generation of more eddies and local periodically velocity variations for pulsation mode. This periodic generation of turbulence at pulsatile ventilation flows happen despite the relatively low Reynolds numbers of such flows.Bigger size of boundary layer and higher turbulent kinetic energy for pulsation mode in comparisonwith the same flow rate in constant velocity mode could result in more ventilation capacity with no need to increase the use of energy. It was seen that while a higher constant velocity rate could produce the same acceptable results in terms of higher efficiency in ventilation, a lower pulsated flow could yields it without the risk of draught. Regarding the thesis procedure, the computational solution started with a grid independency study. 2-Dimensional simulation failed to simulate the results similar to the experimental data. No URANS model was able to yield good outcome in 2D mode. The study was continued with 3D SST-kω which yielded good prediction of velocity profiles near the wall regions. For predicting turbulence parameters in the center of the domain SST-URANS was not helpful so, simulation switched to SAS which was successful to some extent to get close to reality.
Place, publisher, year, edition, pages
2014. , 52 p.
CFD, Pulsative inflow, Mixing ventilation, Resolving stagnation zones
Building Technologies Energy Systems
IdentifiersURN: urn:nbn:se:hig:diva-16135OAI: oai:DiVA.org:hig-16135DiVA: diva2:689986
Subject / course
Sattari, Amir, PhD candidate
Cehlin, Mathias, Assistant professor