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Francois Clemens

Bio: Francois Clemens is an academic researcher from Delft University of Technology. The author has contributed to research in topics: Sanitary sewer & Combined sewer. The author has an hindex of 23, co-authored 170 publications receiving 2032 citations. Previous affiliations of Francois Clemens include Norwegian University of Science and Technology & City University of New York.


Papers
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Proceedings ArticleDOI
15 May 2001
TL;DR: In this article, the authors discuss the potential of the use of genetic algorithms for optimisation of wastewater systems and conclude that GAs are capable of solving the very complex optimisation problems related to improvement of total wastewater systems.
Abstract: The optimisation of complete wastewater systems receives more and more attention, since it has become clear that the current approach of optimising the subsystems of sewerage and wastewater treatment separately often results in sub-optimal solutions. This optimisation, however, shows to be very troublesome in practice due to its complexity. The complexity of a wastewater system optimisation problem is related to the many variables involved (multi-dimensional search) and to the optimisation goal, defined by an objective function. Optimisation with respect to multiple objectives, e.g. overall costs as well as environmental performance, is often suggested but increases the complexity. One of the optimisation or search techniques which is capable of dealing with such a complex surrounding is a genetic algorithm (GA). This paper discusses the potential of the use of genetic algorithms for optimisation of wastewater systems. The definition of the objective function and the characteristics of the GA, especially mutation probability, proved to be key-elements for a successful application of a GA for this type of problems. Finally, it is concluded that GAs are capable of solving the very complex optimisation problems related to improvement of total wastewater systems.

5 citations

Journal ArticleDOI
TL;DR: Decision-making for sewer asset management is partially based on intuition and often lacks explicit argumentation, hampering decision transparency and reproducibility, and decision-making in practice is more likely to be steered by other mechanisms than purely combining information sources.

5 citations

Journal ArticleDOI
13 Dec 2018-Water
TL;DR: In this paper, an emulator is developed to predict the upcoming daily time series of the total wastewater volume in a storage tank and the corresponding Combined Sewer Overflow (CSO) volume.
Abstract: In this study, applicability of a data-driven Gaussian Process Emulator (GPE) technique to develop a dynamic surrogate model for a computationally expensive urban drainage simulator is investigated. Considering rainfall time series as the main driving force is a challenge in this regard due to the high dimensionality problem. However, this problem can be less relevant when the focus is only on short-term simulations. The novelty of this research is the consideration of short-term rainfall time series as training parameters for the GPE. Rainfall intensity at each time step is counted as a separate parameter. A method to generate synthetic rainfall events for GPE training purposes is introduced as well. Here, an emulator is developed to predict the upcoming daily time series of the total wastewater volume in a storage tank and the corresponding Combined Sewer Overflow (CSO) volume. Nash-Sutcliffe Efficiency (NSE) and Volumetric Efficiency (VE) are calculated as emulation error indicators. For the case study herein, the emulator is able to speed up the simulations up to 380 times with a low accuracy cost for prediction of the total storage tank volume (medians of NSE = 0.96 and VE = 0.87). CSO events occurrence is detected in 82% of the cases, although with some considerable accuracy cost (medians of NSE = 0.76 and VE = 0.5). Applicability of the emulator for consecutive short-term simulations, based on real observed rainfall time series is also validated with a high accuracy (NSE = 0.97, VE = 0.89).

5 citations

Proceedings ArticleDOI
21 Nov 2001
TL;DR: In this paper a design method for measuring networks aiming at obtaining information for model calibration is proposed, based upon the application of a hydrodynamic model for initial design.
Abstract: When designing a measuring network several questions must be answered. Basic properties like defining sampling interval and the exact locations for measuring sites are mostly based upon expert's judgement. In this paper a design method for measuring networks aiming at obtaining information for model calibration is proposed. This method is based upon the application of a hydrodynamic model for initial design. Based on a rain-max approach for the sampling fiequancy, a first estimate is obtained. Based on a mathematical analysis of the model parameterization and information content of potential measuring locations it is possible to judge measuring networks objectively. Moreover, by applying some optimization technique (e.g. a genetic algorithm) an automated optimization of the measuring network is possible.

5 citations

31 Dec 2013
TL;DR: In this article, the authors studied the extent to which rainfall data can be used to explain variations in insurance claim data and addressed the issue of time lag between claim date and time of the damaging rainfall event, which may lead to underestimation of correlations between rainfall and damage variables.
Abstract: Sewer flooding due to extreme rainfall may result in considerable damage. Damage data to quantify costs of cleaning, drying, and replacing materials and goods are rare in literature. In this study, insurance claim data related to property damages were analysed for the municipality of Aarhus, Denmark. The aim of this paper was to study the extent to which rainfall data can be used to explain variations in insurance claim data. In particular, the paper addresses the issue of time-lag between claim date and time of the damaging rainfall event, which may, if not taken into account, lead to underestimations of correlations between rainfall and damage variables. Rainfall data from two rain gauges were used to extract rainfall characteristics. From cross correlations between time series of rainfall and claim data, it can be concluded that rainfall events induce claims mostly on the same day, but also on the three days after. A linear model that takes into account rainfall data from previous days slightly improves correlations between rainfall and damage variables compared to a simple linear model. Best correlation coefficients were found between maximum hourly rainfall intensity and daily number of claims (0.47-0.57) and daily total damage (0.43-0.53).

5 citations


Cited by
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Journal ArticleDOI

6,278 citations

Journal Article
TL;DR: In this article, the authors present a document, redatto, voted and pubblicato by the Ipcc -Comitato intergovernativo sui cambiamenti climatici - illustra la sintesi delle ricerche svolte su questo tema rilevante.
Abstract: Cause, conseguenze e strategie di mitigazione Proponiamo il primo di una serie di articoli in cui affronteremo l’attuale problema dei mutamenti climatici. Presentiamo il documento redatto, votato e pubblicato dall’Ipcc - Comitato intergovernativo sui cambiamenti climatici - che illustra la sintesi delle ricerche svolte su questo tema rilevante.

4,187 citations

Book
01 Jun 1976

2,728 citations

Book ChapterDOI
01 Jan 1997
TL;DR: The boundary layer equations for plane, incompressible, and steady flow are described in this paper, where the boundary layer equation for plane incompressibility is defined in terms of boundary layers.
Abstract: The boundary layer equations for plane, incompressible, and steady flow are $$\matrix{ {u{{\partial u} \over {\partial x}} + v{{\partial u} \over {\partial y}} = - {1 \over \varrho }{{\partial p} \over {\partial x}} + v{{{\partial ^2}u} \over {\partial {y^2}}},} \cr {0 = {{\partial p} \over {\partial y}},} \cr {{{\partial u} \over {\partial x}} + {{\partial v} \over {\partial y}} = 0.} \cr }$$

2,598 citations