## 9A Systems modelling

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## Albert Chen

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## Generalising human heuristics in augmented evolutionary water distribution network design optimisation

Herman Mahmoud

Presenter:

Authors:

Herman Mahmoud, Matthew Johns, Edward Keedwell and Dragan Savic

The use of evolutionary algorithms (EAs) for finding near optimal water distribution network (WDN) designs is well-established in the literature. Even though these methods have the ability to generate mathematically promising solutions based on defined objective function(s), the resulting solutions are not necessarily suitable for real-world application. This is because of the size, complex and non-linear nature of WDNs, which make it difficult to define important factors that a water engineer or an expert needs to consider during the design process in an objective function. Incorporating an expert in the optimization process has been used to deal with this problem and to guide an EA’s search toward obtaining more practical solutions. Accordingly, this study proposes a methodology for capturing and generalizing engineering expertise in optimizing small/medium WDNs through machine learning techniques, and integrating the resultant heuristic into an EA through its mutation operator to find the optimum design for larger WDNs. The combined interaction from different users on four small /medium benchmark WDNs from the literature were collected and used to train a decision tree model. Seven input features including current pipe diameter, velocity, upstream and downstream head deficient, pipe influence, flow and length are used to train the decision tree for predicting new diameter for a selected pipe. The resultant decision tree model is then applied to a larger network namely Modena to assess the ability of the HDH method. The results demonstrate better performance in comparison with a standard EA approach for finding minimum network cost.

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## Analysing Heuristic Performance for Optimising Water Distribution Networks

William Yates

Presenter:

Authors:

William Yates and Edward Keedwell

A simple selection hyper-heuristic with 6 low level heuristics is used to optimise 12 water distribution networks of varying sizes. The objective is to explore the impact of individual heuristics and permutations or subsequences of heuristic operations on performance during the optimisation process.

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## Effects of Sampling Interval on Stability of Electronically Controlled Pressure Reducing Valves

Bogumil Ulanicki

Presenter:

Authors:

Tomasz Janus and Bogumil Ulanicki

This extended abstract discusses stability of closed-loop pressure control systems as a function of sampling interval. This issue has not yet been discussed in publications but nevertheless is very important and timely since a number of influential papers in the area of real time control (RTC) of WDNs quoted sampling (control) intervals as large as 5 minutes while, as will be shown here, sampling intervals as small as 30-40s will already yield the control scheme unstable. In the short document presented here a WDN was modelled using a simple third order transfer function describing a generalised Maxwell model of viscoelastic behaviour while the PRV control circuit was modelled using a well known behavioural PRV model of Prescott and Ulanicki. The simulations showed how at sampling intervals over 35s the control system becomes unstable. The lack of stability is then also demonstrated by pointing out that one of the poles at a sampling interval of 40s lies outside the unit circle in the z-plane, thus violating the well-known stability criterion. Last but not least, it was pointed out that sampling times can be made artificially large if static gain is sufficiently small. Although long-term horizon simulations may produce some stable results as the system will converge to new solution within lets say an hour, in practice such systems would be unresponsive to pressure and flow fluctuations, i.e. they would not be able to control the system. On the other hand, if gain was to be increased, the system at such long sampling interval would be unstable, as shown here. In the full paper the work will be extended to incorporate a more detailed network model and will feature rigorous analytical stability analysis. Finally, practical recommendations regarding the practical choice of sampling intervals for simulations and practical implementations will be given.

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## Modelling for the Identification of Mechanisms Driving Cholera Outbreaks in Endemic Regions

Debbie Shackleton

Presenter:

Authors:

Debbie Shackleton, Albert S. Chen and Fayyaz Ali Memon

Cholera is endemic in Bangladesh and causes an average of 4500 preventable deaths in the country every year. The country is home to the Ganges Delta, the largest delta in the world, and native homeland of the cholera causing bacteria Vibrio Cholerae. As such, cholera incidence in the region is hugely affected by weather and climate, and the relationships are nonlinear and interrelated. Many current approaches to cholera modelling focus on forecasting using statistical correlations, however these come with significant uncertainties and are short-term solutions. In endemic regions like Bangladesh, long-term approaches to cholera prevention are needed, and these require a holistic understanding of the mechanisms which drive cholera spread and the complex way in which they interact. We propose the development of a mathematical model based on systems thinking to explicitly describe the individual mechanisms and their relationships, with the aim of providing a validated understanding of these mechanisms – something currently lacking in the research community. Intended applications for the model are twofold. First, to simulate the relative effectiveness of different intervention options in a manner that is fast, cheap and ethical. Second, through applying climate forecasts as environmental inputs, to provide predictions of the long-term effects of climate change on cholera in the region, leading to valuable insights to the future challenges to be faced in the fight against cholera.

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## Modelling of a Stand-Alone, Solar Driven Agriculture Greenhouse Integrated With Photo Voltaic /Thermal (PV/T) Panels

Alaa H. Salah

Presenter:

Authors:

Alaa H. Salah, Hassan E. Fath, Abdelazim Negm, Mohammad Akrami and Akbar Javadi

This paper presents an analytical study of a new stand-alone agriculture greenhouse (GH) system. This system utilizes the excess solar radiation (more than that required by the plants for photosynthetic process) to generate electricity via a set of Photo Voltaic/Thermal (PV/T) units which are placed on the GH roof and south side. In addition to electricity generation, PV/Ts reduce the cooling load of the GH and help the system to be naturally ventilated. The system recovers the GH air humidity, including the plants transpiration, and uses it as irrigating water. Two coupled mathematical models are developed using MATLAB. The first model calculates the absorbed and transmitted solar radiation by/through each GH surface for a Clear Sky Day. The results of the first model are used as inputs to the second one that predicts the GH performance (GH surfaces and air temperatures, air relative humidity, air velocity, water production, electricity production and power consumption). These models are applied on climate conditions of Zagazig city, Sharqia, Egypt. The results show that the system presents a good solution for water shortage in Egypt as it has the ability to provide suitable climate conditions for plant growth (high quality and quantity) and produce enough water for irrigation purposes.