CFD investigation of balcony spill plumes in atria

Smoke management in buildings during fire events often uses mechanical ventilation systems to maintainsmoke layer elevation above a safe evacuation path. Design of these systems requires accuratecorrelations for the smoke production rate of the buoyant fire plume. One design issue is the smokeproduction rate of fire plumes which spill out from a fire compartment, under a balcony and up through anatrium or other large volume. Current engineering correlations for these balcony spill plumes are basedon a combination of one-tenth scale test data and theoretical analysis. Questions have arisen over thesuitability of these correlations for real-scale designs. A combined program of full-scale experimentationand CFD modeling is being conducted to analyze the accuracy of these correlations.Dans la gestion de la fum\ue9e dans les \ue9difices o\uf9 \ue9clate un incendie, c'est souvent un syst\ue8me d'extraction m\ue9canique qui sert \ue0 maintenir les couches de fum\ue9e \ue0 un niveau plus haut qu'une voie d'\ue9vacuation s\ue9curitaire donn\ue9e. La conception de tels syst\ue8mes requiert que soient \ue9tablies des corr\ue9lations pr\ue9cises relativement au taux de production de fum\ue9e du panache de flammes flottant. Le taux de production de fum\ue9e des panaches que d\ue9gage un compartiment o\uf9 un feu a \ue9clat\ue9 et qui l\ue8chent le dessous d'un balcon pour s'\ue9lever \ue0 l'int\ue9rieur d'un atrium ou autre espace \ue0 fort volume constitue un probl\ue8me pour la conception. Les corr\ue9lations d'ing\ue9nierie actuelles pour ces panaches d\ue9gag\ue9s sous les balcons sont fond\ue9es sur une utilisation combin\ue9e de donn\ue9es d'essais \ue0 l'\ue9chelle d'un dixi\ue8me et d'analyses th\ue9oriques. La pertinence de telles corr\ue9lations pour des conceptions en vraie grandeur a soulev\ue9 des questions. On dirige actuellement un programme mixte d'exp\ue9rimentation en vraie grandeur et de mod\ue9lisation de m\ue9canique des fluides computationnelle (CFD) dans le but d'analyser le degr\ue9 de pr\ue9cision de ces corr\ue9lations.Peer reviewed: YesNRC publication: Ye

CFD investigation of balcony spill plumes in atria

This paper demonstrates an integrated method for using experimental data and computational fluid dynamics modeling to design smoke management for atriums and other large building volumes. By means of full-scale experimentation and computational fluid dynamics modeling, the research correlated the combination of one-tenth scale experimental data and theoretical analysis used for simulating fire conditions to full-scale designs.Dans ce rapport, on d\ue9crit une m\ue9thode int\ue9gr\ue9e permettant d'utiliser les donn\ue9es exp\ue9rimentales et la mod\ue9lisation de la dynamique des fluides computationnelle pour g\ue9rer la fum\ue9e dans les atriums et d'autres grands volumes de b\ue2timents. \uc0 partir d'exp\ue9riences en vraie grandeur et d'une mod\ue9lisation de dynamique des fluides computationnelle, les chercheurs ont \ue9tabli une corr\ue9lation entre les donn\ue9es exp\ue9rimentales \ue0 l'\ue9chelle 1 : 10 combin\ue9es \ue0 l'analyse th\ue9orique utilis\ue9e pour simuler les conditions d'incendie et les mod\ue8les en vraie grandeur.Peer reviewed: YesNRC publication: Ye

FEDSM2002-31171 VECTOR POSTIONING FOR CROSS CORRELATION PIV

ABSTRACT Continuing advances in digital imaging technology stimulate greater interest in applying particle image velocimetry (PIV) over increasingly larger fields of view. Unfortunately when larger fields of view are analyzed, velocity gradients in the image become more localized. In addition, non-uniformities in image illumination and particle number density become more prevalent. These factors, coupled with the requirement that large areas of interest (AOIs) must be employed to measure the full range of velocity, cause degradation of correlation results (i.e. broadening and/or splintering of the cross correlation peak) which leads to positional bias errors in the measured velocity field. More advanced super resolution strategies that employ an iterative AOI reduction process inherently reduce positional bias in PIV results but these strategies can break down in complex flows where velocity gradients are steep and particle dispersion does not remain uniformly random. To mitigate these problems a simple but effective technique is presented that enables individual velocity vectors to be placed within an AOI at locations toward which the cross correlation plane is biased. The method involves analysis of the correlation plane to extract the dominant features that are matched in two successive AOIs. To demonstrate the utility of the methodology results obtained from synthetic images are compared against results obtained using the conventional PIV approach