Developments in unsteady pipe flow friction modelling

This paper reviews a number of unsteady friction models for transient pipe flow. Two distinct unsteady friction models, the Zielke and the Brunone models, are investigated in detail. The Zielke model, originally developed for transient laminar flow, has been selected to verify its effectiveness for "low Reynolds number" transient turbulent flow. The Brunone model combines local inertia and wall friction unsteadiness. This model is verified using the Vardy's analytically deduced shear decay coefficient C* to predict the Brunone's friction coefficient k rather than use the traditional trial and error method for estimating k. The two unsteady friction models have been incorporated into the method of characteristics water hammer algorithm. Numerical results from the quasi-steady friction model and the Zielke and the Brunone unsteady friction models are compared with results of laboratory measurements for water hammer cases with laminar and low Reynolds number turbulent flows. Conclusions about the range of validity for the three friction models are drawn. In addition, the convergence and stability of these models are addressed.Anton Bergant, Angus Ross Simpson, John Vìtkovsk

Source control options for reducing emission of priority pollutants from urban areas.

The overall aim of the ScorePP project is to develop comprehensive and appropriate source control strategies that authorities, cities, water utilities and the chemical industry can employ to reduce emissions of priority pollutants (PPs) from urban areas into the receiving water environment. Focus is on the 33 priority and priority hazardous substances and substance groups identified in the European Water Framework Directive. However, this list may be expanded to include emerging pollutants or reduced if appropriate model compounds can be identified. The initial work focuses on 67 substances, including substances identified in the proposed European environmental quality standard (EQS) directive as well as the defined example compounds and several organometallic derivatives. Information on inherent properties, environmental presence and fate, and legislative issues is made available in open database format, and a data management system combining chemical identification (CAS#), NACE economic activity classifications and NOSE-P emission source classifications has been developed as a basis for spatial characterisation of PP sources using GIS. Further work will focus on dynamic urban scale source-flux models, identifying emission patterns and optimising monitoring programmes in case studies and multi-criteria comparison of source control versus end-of-pipe mitigation options in relation to their economic, social and environmental impacts

Estimating environmental pollution by xenobiotic chemicals using QSAR (QSBR) models based on artificial intelligence

An attempt was made to construct QSAR (Quantitative Structure-Activity Relationships) or QSBR (Quantitative Structure-Biodegradation Relationships) formulae and models for predicting biodegradability of chemicals in aqueous aerobic environment with machine learning (ML) tools of artificial intelligence (AI). Inverse of biodegradability is environmental persistence, from which possible dynamics of soil, groundwater and water pollution can be inferred. We tried to predict the biodegradability with several programs that can learn from examples and construct decision or regression trees and/or can construct equations. Besides the given basic topological properties, the main contribution was inclusion of connectivity indices. Above all, normalization of properties to molecular weight or the number of carbon atoms significantly improved prediction. The obtained results are comparable (or better) to the best achieved results with other approaches. Contrary to the statistical methods, ML tools present the information (learned knowledge) in a compact, easily understandable manner which can help identify and understand the key properties of chemicals and mechanisms important for assessing biodegradation (and thus possible environmental contamination) from chemical structure only.</jats:p

Computational assemblage of ordinary differential equations for Chlorophyll-a using a lake process equation library and measured data of Lake Kasumigaura

The software LAGRAMGE for computational assemblage and adaptation of ODE by using the expert knowledge and measured data has been applied for the simulation of chl-a in Lake Kasumigaura. As a result two types of chl-a models were discovered: (1) chl-a equations without considering zooplankton grazing assembled and trained by data of consecutive years were data of the last year was used for testing, and (2) chl-a equations considering zooplankton grazing assembled and trained by data of the years 1986 to 1989. The test results of the different models have demonstrated that LAGRAMGE can discover ODE that allow to simulate chl-a in Lake Kasumigaura for a variety of years. However the generalisation of discovered equations for unseen data of consecutive years was unsatisfactory, and the accuracy of calculated trajectories with regards to timing and magnitudes of peak events was moderate. The results have highlighted the importance of nutrients as growth limiting factors, and the need for considering functional algae groups in order to appropriately represent their selective grazing by zooplankton. © 2006 Springer-Verlag Berlin Heidelberg.N. Atanasova; F. Recknagel; L. Todorovski; S. Dzeroski; B. Kompar