Multiple objective optimal control of integrated urban wastewater systems

Copyright © 2008 Elsevier. NOTICE: this is the author’s version of a work that was accepted for publication in Environmental Modelling and Software. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Environmental Modelling and Software, Vol. 23 Issue 2 (2008). DOI: 10.1016/j.envsoft.2007.06.003Integrated modelling of the urban wastewater system has received increasing attention in recent years and it has been clearly demonstrated, at least at a theoretical level, that system performance can be enhanced through optimized, integrated control. However, most research to date has focused on simple, single objective control. This paper proposes consideration of multiple objectives to more readily tackle complex real world situations. The water quality indicators of the receiving water are considered as control objectives directly, rather than by reference to surrogate criteria in the sewer system or treatment plant. A powerful multi-objective optimization genetic algorithm, NSGA II, is used to derive the Pareto optimal solutions, which can illustrate the whole trade-off relationships between objectives. A case study is used to demonstrate the benefits of multiple objective control and a significant improvement in each of the objectives can be observed in comparison with a conventional base case scenario. The simulation results also show the effectiveness of NSGA 11 for the integrated urban wastewater system despite its complexity

Reliable, resilient and sustainable urban drainage systems: an analysis of robustness under deep uncertainty (article)

This is the author accepted manuscript. The final version is available from the American Chemical Society via the DOI in this record.The dataset associated with this article is available in ORE at: https://doi.org/10.24378/exe.563Reliability, resilience and sustainability are key goals of any urban drainage system. However, only a few studies have recently focused on measuring, operationalizing and comparing such concepts in a world of deep uncertainty. In this study, these key concepts are defined and quantified for a number of gray, green and hybrid strategies, aimed at improving the capacity issues of an existing integrated urban wastewater system. These interventions are investigated by means of a regret-based approach, which evaluates the robustness (that is the ability to perform well under deep uncertainty conditions) of each strategy in terms of the three qualities through integration of multiple objectives (i.e. sewer flooding, river water quality, combined sewer overflows, river flooding, greenhouse gas emissions, cost and acceptability) across four different future scenarios. The results indicate that strategies found to be robust in terms of sustainability were typically also robust for resilience and reliability across future scenarios. However, strategies found to be robust in terms of their resilience and, in particular, for reliability did not guarantee robustness for sustainability. Conventional gray infrastructure strategies were found to lack robustness in terms of sustainability due to their unbalanced economic, environmental and social performance. Such limitations were overcome, however, by implementing hybrid solutions that combine green retrofits and gray rehabilitation solutions.This study was funded by the UK Engineering and Physical Sciences Research Council through STREAM (EP/G037094/1) with Northumbrian Water Limited, BRIM (EP/N010329/1) and the final author’s fellowship Safe & SuRe (EP/K006924/1)

Soziale und strukturelle Integration junger Aussiedler

Zdun S. Soziale und strukturelle Integration junger Aussiedler. In: Tagungsband der Fachveranstaltung für Multiplikatoren: "Forderkonzepte für junge Aussiedler in Schule und Jugendhilfe". Bochum; 2006

Model structure identification for wastewater treatment simulation based on computational fluid dynamics

Available from TIB Hannover: DtF QN1(98,6) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEBundesministerium fuer Bildung und Forschung, Berlin (Germany)DEGerman