COMPARISON OF NEAR-FIELD MIXING ZONE MODELS FOR MULTIPORT DIFFUSERS IN THE GREAT-LAKES

Citation
Ik. Tsanis et al., COMPARISON OF NEAR-FIELD MIXING ZONE MODELS FOR MULTIPORT DIFFUSERS IN THE GREAT-LAKES, Canadian journal of civil engineering, 21(1), 1994, pp. 141-155
Citations number
73
Categorie Soggetti
Engineering, Civil
ISSN journal
03151468
Volume
21
Issue
1
Year of publication
1994
Pages
141 - 155
Database
ISI
SICI code
0315-1468(1994)21:1<141:CONMZM>2.0.ZU;2-W
Abstract
This paper presents a review of near-field mixing zone models and comp ares their performance with common outfall diffuser examples in the Gr eat Lakes. The results of initial dilutions for three types of multipo rt diffusers, based on the Ontario Ministry of Environment (MOE) guide lines and recommendations, are compared with those calculated by using the U.S. Environmental Protection Agency (EPA) models. These models i nclude five integral-type models (UPLUME, UOUTPLM, UDKHDEN, UMERGE, an d ULINE) and a ''length scale'' type expert system (CORMIX2). Results based on the first four EPA integral models give higher initial diluti ons when compared to results based on CORMIX2 and the MOE guidelines. ULINE gives unrealistically low dilutions. Excluding UPLUME, the initi al dilutions given by the other EPA models increase with increasing am bient current. Alternating diffusers generally give lower initial dilu tions than the staged and unidirectional diffusers, while unidirection al diffusers produce the highest of the three. Results from the comput ation tests based on the mixing models can aid in more reasonable and economical diffuser designs that still meet the requirement of initial dilution criteria. While all the models selected for this study have limitations, CORMIX2 is preferred for most Great Lakes applications. I t can be applied to all four types of multiport diffusers and can hand le different types of ambient stratification, bottom and shore attachm ent, wake effects and dead zones, plume trapping and far-field behavio ur. CORMIX2 predictions compare well with laboratory data and very lim ited field data. Given the complexity of the problem, more field studi es should be performed for further validation of the models.