Artificial Intelligence - How can water planning and management benefit from?

IAHR White Papers Online: https://www.iahr.org/index/detail/6

A multi-objective optimisation model for sewer rehabilitation considering critical risk of failure

Copyright © 2012 IWA Publishing. The definitive peer-reviewed and edited version of this article is published in Water Science & Technology, Vol 66 No 11, pp. 2410–2417 (2012), DOI: 10.2166/wst.2012.393 and is available at www.iwapublishing.com.A unique methodology for the optimal specification of sewer rehabilitation investment is presented in this paper. By accounting for the critical risk of asset failure, this methodology builds on previously successful work which explored the application of multi-objective optimisation tools to assist engineers with the specification of optimal rehabilitation strategies. The conventional sewerage rehabilitation specification process relies on the expertise of professional engineers to manually evaluate CCTV inspection information when determining the nature and extent of the rehabilitation solution. This process is not only tedious and subjective but it has no quantifiable means of identifying optimal solutions or possible combinations of optimal solutions in the delivery of catchment wide rehabilitation programmes. Therefore, the purely manual process of sewer rehabilitation design leaves a number of unanswered questions, such as: (1) Does the solution offer the greatest structural benefit to the network? (2) Is the solution the most cost-effective solution available? (3) Does the solution most greatly reduce the risk of critical asset failure? The application of a multi-objective genetic algorithm optimisation model, coupled with an enhanced critical risk methodology, has successfully answered these questions when applied to a case study data set provided by South West Water (UK)

Advances in data-driven analyses and modelling using EPR-MOGA.

Evolutionary Polynomial Regression (EPR) is a recently developed hybrid regression method that combines the best features of conventional numerical regression techniques with the genetic programming/symbolic regression technique. The original version of EPR works with formulae based on true or pseudo-polynomial expressions using a single-objective genetic algorithm. Therefore, to obtain a set of formulae with a variable number of pseudo-polynomial coefficients, the sequential search is performed in the formulae space. This article presents an improved EPR strategy that uses a multi-objective genetic algorithm instead. We demonstrate that multi-objective approach is a more feasible instrument for data analysis and model selection. Moreover, we show that EPR can also allow for simple uncertainty analysis (since it returns polynomial structures that are linear with respect to the estimated coefficients). The methodology is tested and the results are reported in a case study relating groundwater level predictions to total monthly rainfall

A symbolic data-driven technique based on evolutionary polynomial regression

This paper describes a new hybrid regression method that combines the best features of conventional numerical regression techniques with the genetic programming symbolic regression technique. The key idea is to employ an evolutionary computing methodology to search for a model of the system/process being modelled and to employ parameter estimation to obtain constants using least squares. The new technique, termed Evolutionary Polynomial Regression (EPR) overcomes shortcomings in the GP process, such as computational performance; number of evolutionary parameters to tune and complexity of the symbolic models. Similarly, it alleviates issues arising from numerical regression, including difficulties in using physical insight and over-fitting problems. This paper demonstrates that EPR is good, both in interpolating data and in scientific knowledge discovery. As an illustration, EPR is used to identify polynomial formulæ with progressively increasing levels of noise, to interpolate the Colebrook-White formula for a pipe resistance coefficient and to discover a formula for a resistance coefficient from experimental data

An investigation of the efficient implementation of Cellular Automata on multi-core CPU and GPU hardware

Copyright © 2015 Elsevier. NOTICE: this is the author’s version of a work that was accepted for publication in Journal of Parallel and Distributed Computing . 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 Journal of Parallel and Distributed Computing Vol. 77 (2015), DOI: 10.1016/j.jpdc.2014.10.011Cellular automata (CA) have proven to be excellent tools for the simulation of a wide variety of phenomena in the natural world. They are ideal candidates for acceleration with modern general purpose-graphical processing units (GPU/GPGPU) hardware that consists of large numbers of small, tightly-coupled processors. In this study the potential for speeding up CA execution using multi-core CPUs and GPUs is investigated and the scalability of doing so with respect to standard CA parameters such as lattice and neighbourhood sizes, number of states and generations is determined. Additionally the impact of ‘Activity’ (the number of ‘alive’ cells) within a given CA simulation is investigated in terms of both varying the random initial distribution levels of ‘alive’ cells, and via the use of novel state transition rules; where a change in the dynamics of these rules (i.e. the number of states) allows for the investigation of the variable complexity within.Engineering and Physical Sciences Research Council (EPSRC

An optimised total expenditure approach to sewerage management

Copyright © 2014 Thomas Telford Ltd.It is generally accepted by Ofwat, the water industry regulator for England and Wales, that the current investment planning system whereby capital and operational expenditure are accounted for separately is complex and burdensome. In a move towards realising a total expenditure approach, a previously successful sewer rehabilitation optimisation model has been adapted to provide a mechanism for users to evaluate the trade-offs that exist between the capital and operational benefits associated with different sewer rehabilitation schemes. A series of geographic information system tools has been integrated within the model to help prioritise high-benefit sewer rehabilitation schemes by evaluating the potential serviceability improvements that can be realised in addition to the purely structural condition improvements. As a result, the new sewer rehabilitation model can be referred to as a strategic decision support tool that is capable of helping sewerage engineers and planners in the evaluation of different intervention programmes of work. The benefits of adopting this approach are demonstrated in a UK sewerage case study that uses a multi-objective genetic algorithm to consider the three-way trade-off that exists between minimising investment cost against maximising asset life (capital benefit) compared with proactively addressing serviceability problems (operational benefit).EPSRC (Engineering and Physical Sciences Research Council

Graph-theoretic approach and sound engineering principles for design of district metered areas

Copyright © 2014 American Society of Civil EngineersThe design of district metered areas (DMAs) in existing water distribution networks, especially in urban areas, involves a high number of decision variables, and the effects of implementing them in districts have to be evaluated in order not to affect the quality of the service to customers. A new methodology for designing a given number of districts in looped water distribution networks is proposed here. It is based on graph theory and takes into account some important DMA design criteria: the maximum and minimum size recommended for a district, the connectedness of each district to the water supply source, and the absence of links between the districts. Therefore, it allows the creation of DMAs that are independent from each other. A recursive bisection procedure has been applied to create districts, while an algorithm for graph traversal has been used to verify whether each district can be reached from the water source and connectivity between the nodes. The successful application of the proposed methodology to a case study has proven its effectiveness for district metered areas design in real urban water distribution networks

Decision support for optimal design of water distribution networks: A real options approach

12th International Conference on Computing and Control for the Water Industry, CCWI2013There is a growing concern about how the technical, managerial and financial capacity of drinking water systems can be sustained in the long run with future uncertainties. A water supply system is critical for the well- being of a community and it must provide water in sufficient quantity, of appropriate quality and without interruption. People have high expectations for the proper functioning of these systems but the future is uncertain and it is very difficult to conceive an infallible infrastructure. This work proposes a real options (ROs) approach that takes into account future uncertainty associated with water distribution networks. The ROs methodology extends traditional analysis to include flexible strategic implementation. This work describes a decision support methodology to design water networks that are adaptable over a long-term planning horizon. Representing design strategies as decision trees allows decision makers to easily adapt the system according to future circumstances. Results show that the ROs solution makes it possible to save on resources through an analysis based on an extended and uncertain planning horizonPrograma Operacional Factores de Competitividade – COMPETEFCT – Fundação para a Ciência e Tecnologi

Using real options for an eco-friendly design of water distribution systems

Copyright © 2015 IWA Publishing. The definitive peer-reviewed and edited version of this article is published in Journal of Hydroinformatics volume 17 (1), pp. 20-35 (2015), DOI 10.2166/hydro.2014.122 and is available at www.iwapublishing.com.This paper presents a real options approach to handling uncertainties associated with the long-term planning of water distribution system development. Furthermore, carbon emissions associated with the installation and operation of water distribution networks are considered. These emissions are computed by taking an embodied energy approach to the different materials used in water networks. A simulated annealing heuristic is used to optimise a flexible eco-friendly design of water distribution systems for an extended life horizon. This time horizon is subdivided into different time intervals in which different possible decision paths can be followed. The proposed approach is applied to a case study and the results are presented according to a decision tree. Lastly, some comparisons and results are used to demonstrate the quality of the results of this approach.Programa Operacional Factores de Competitividade – COMPETEFCT – Fundação para a Ciência e Tecnologi