Risk assessment modelling of microbiology-related solids separation

Disponible uniquement sur Etudier
  • Pages : 11 (2586 mots )
  • Téléchargement(s) : 0
  • Publié le : 13 décembre 2010
Lire le document complet
Aperçu du document
Environmental Modelling & Software 23 (2008) 1250–1261

Contents lists available at ScienceDirect

Environmental Modelling & Software
journal homepage: www.elsevier.com/locate/envsoft

Risk assessment modelling of microbiology-related solids separation problems in activated sludge systems
´ J. Comas a, *, I. Rodrıguez-Roda a, K.V. Gernaey b, C. Rosen c, U. Jeppsson c, M. Poch a
aChemical and Environmental Engineering Laboratory (LEQUiA), University of Girona, Campus Montilivi s/n, E-17071 Girona, Catalonia, Spain Department of Chemical and Biochemical Engineering, Technical University of Denmark (DTU), Building 229, DK-2800 Kgs. Lyngby, Denmark c Department of Industrial Electrical Engineering and Automation (IEA), Lund University, P.O. Box 118, SE-22100 Lund, Sweden

ar t i c l e i n f o
Article history: Received 21 May 2007 Received in revised form 4 January 2008 Accepted 19 February 2008 Available online 19 May 2008 Keywords: Risk assessment Activated sludge Filamentous bulking Foaming Rising sludge Modelling Qualitative knowledge Benchmark simulation

a b s t r a c t
This paper proposes a risk assessment model for settling problems of microbiologicalorigin in activated sludge systems (filamentous bulking, foaming and rising sludge). The aim of the model is not to diagnose microbiology-related solids separation problems with absolute certainty but to quantify in dynamic scenarios whether simulated operational procedures and control strategies lead to favourable conditions for them to arise or not. The rationale behind the model (which integratesthe mechanisms of standard activated sludge models with empirical knowledge), its implementation in a fuzzy rule-based system and the details of its operation are illustrated in the different sections of the paper. The performance of the risk assessment model is illustrated by evaluating a number of control strategies facing different shortterm influent conditions as well as long-term variabilityusing the IWA/COST simulation benchmark. The results demonstrate that some control strategies, although performing better regarding operating costs and effluent quality, induce a higher risk for solids separation problems. In view of these results, it is suggested to integrate empirical knowledge into mechanistic models to increase reliability and to allow assessment of potential side-effects whensimulating complex processes. Ó 2008 Elsevier Ltd. All rights reserved.

1. Introduction Biological wastewater treatment systems, and specifically activated sludge systems, are complex systems. The complexity is a consequence of the presence of a dynamic multi-species microorganism population whose composition is changing continuously under the influence of factors such as influent flow rate andcomposition, temperature variations and plant operational parameters such as the sludge retention time, the ratio between aerobic and anoxic time, etc. Development of tools to support control and operation of activated sludge systems was primarily focused on introducing and improving deterministic models until the late 1970s. The considerable number of literature references on the topic reveals thatgreat efforts have been made in this research field. Simulation of mechanistic models has been used for plant design, for control and for optimization purposes (e.g. Coen et al., 1996; Salem et al., 2002), often leading to more cost-effective solutions. Progress in mechanistic modelling has meant a great leap forward by improving

* Corresponding author. Tel.: þ34 972 418 804; fax: þ34 972 418 150.E-mail addresses: quim@lequia.udg.cat (J. Comas), ignasi@lequia.udg.cat (I. Ro´ drıguez-Roda), kvg@kt.dtu.dk (K.V. Gernaey), christian.rosen@vaing.se (C. Rosen), ulf.jeppsson@iea.lth.se (U. Jeppsson), manel@lequia.udg.cat (M. Poch). 1364-8152/$ – see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.envsoft.2008.02.013

activated sludge process descriptions during normal...
tracking img