Industry Partners

Partnerships

We work alongside a number of industry partners. Please click on the different categories below to see who we have a partnership with:

Institution Project Collaborations
AECOM STREAM IDC
Arup WISE CDT
Aquobex OVERCOME
Cetaqua CORFU, RESCCUE
DHI Group CORFU, PEARL
Eurecat SIM4NEXUS, Fiware4Water
HR Wallingford FRMRC, FRMRC2, STREAM IDC
Innovyze WISE CDT, STREAM IDC
Jacobs SINATRA
JBA WISE CDT
KWR ARSINOE, ULTIMATE
Pell Frischmann  
Propelair  
Richard Allitt Associates CADDIES, UKWIR
RMS WISE CDT
Suez RESCCUE, aqua3S
Swiss Re  
Water Policy International  
WRC STREAM IDC
WSP  
Institution Project Collaborations
Bristol City Council RESCCUE
Environment Agency FRMRC, FRMRC2
Greater London Authority SWERVE
Natural Resources Wales WISE CDT
Torbay Council FRMRC, FRMRC2, EU-CIRCLE
Welsh Government WISE CDT
Organisation Project Collaborations
CIWEM  
CMCC  
FIWARE Foundation  
IAHR  
ICE  
ICT4Water  
Institute of Water STREAM IDC
IWA  
OFWAT  
SWAN WISE CDT
SWIG  
UKWIR  
Water Europe  
Water Industry Forum  
Water UK  
Institution Project Collaborations
Affinity Water  
Anglian Water
(including Hartlepool)
STREAM IDC
Bournemouth Water 
(part of South West Water)
 
Bristol Water WISE CDT
Dŵr Cymru WISE CDT
Hafren Dyfrdwy  
Northumbrian Water
(including Essex & Suffolk)
Real-time Decision Analytics for Smart Water Infrastructure, WISE CDT, STREAM IDC
Portsmouth Water  
Severn Trent Water Digital Solutions for Resilient Urban Water Systems, STREAM IDC
South East Water  
Southern Water  
South Staffs Water
(also trading as Cambridge Water)
 
South West Water SIM4NEXUS, Fiware4Water, WISE CDT
Sutton & East Surrey Water  
Thames Water STREAM IDC
United Utilities WISE CDT
Wessex Water RESCCUE, WISE CDT
Yorkshire Water  

 

Knowledge Transfer Partnerships

The Knowledge Transfer Partnership (KTP) project, 'A Digital Twin for Condition Assessment and Failure Prediction in Water Pipes', was a collaboration between the University of Exeter’s Centre for Water Systems and water technology firm Datatecnics. This innovative project aimed to enhance the monitoring and management of water pipes by developing 'Ground Truth', a digital twin designed to track pipe deterioration under various environmental and operational conditions. The project combined physical modelling of soil-pipe systems with advanced numerical models of buried pipes, considering a range of scenarios that impact the performance of both plastic and metallic pipes. 

A significant focus was the use of machine learning techniques to predict the mechanical behaviour of pipes over time, allowing for more accurate assessments of their condition and potential failures. The outcomes of the KTP resulted in the creation of a failure prediction and pipe condition assessment tool, developed for Datatecnics, which is now employed by multiple water utilities across the UK and Europe. This innovative approach improves the resilience of water infrastructure and contributes to more efficient, cost-effective maintenance practices across the sector.

This successful KTP has already demonstrated tangible business impacts, including improved operational efficiency and sustainability for water companies. Moreover, Ground Truth recently earned the prestigious Exeter Knowledge Exchange Award 2024 in the Bright Future Award: Early Career Research Impact category, showcasing the real-world significance of the work.

Exeter blog: High flying engineer develops intelligent new system for the water sector

YouTube video: Ground Truth: Simulating Performance of Underground Water Mains with AI and Sensors

Further information:

This KTP project was funded by Innovate UK, to support business-led innovation and access to university expertise. The KTP Associate was Milad Latifi. The University of Exeter’s academic supervisors were Prof Raziyeh Farmani, Professor of Water Engineering, and Prof Akbar Javadi, Professor of Geotechnical Engineering. 

Headquartered in Media City, Manchester, water technology firm Datatecnics builds condition assessment tools and failure prediction models for clean and wastewater pipes, helping utilities improve water systems management.

The aim of this project is to develop, implement, test/verify and hand over a Risk-based Decision Support System (DSS) to enable control room operators to react and remedy failures in the Yorkshire Water Services (YWS) water distribution system before they impact customers.

The DSS developed as part of this Knowledge Transfer Partnership (KTP) will maximise the benefit of collecting real-time data for rapid evaluation of bursts and leaks in a Water Distribution System (WDS). A number of models and data sources will be integrated and the synergetic effect of combining advanced technologies with experience of human operators will be exploited by the DSS. Moreover, the DSS will reduce the cognitive load of human operators by presenting processed and relevant information, ultimately helping YWS to improve customer experience and deliver world class service.

For more information see KTP with United Utilities poster

This project will develop further and customise the recently patented prototype Burst / Leak Detection System.  This system detects bursts, leaks and other anomoalies in a water distribution system by analysing pressure and flow data in real-time. 

Company: Unitied Utilities

KTP Associate: Dr Michele Romano

For more information please contact Prof Zoran Kapelan

Project Length: 3 years

STREAM is an Industrial Doctoral Centre (IDC) http://www.stream-idc.net/ for the Water Sector funded through the Engineering and Physical Sciences Research Council (EPSRC) together with sponsorship from companies.  It allows talented researchers to develop their skills and careers within an industrial environment through a four year postgraduate programme leading to the award of an EngD degree. 

The Centre for Water Systems has EngD students working on the following projects:

HR Wallingford

A project with HR Wallingford is investigating the potential for the application of AI-based optimisation tools (such as genetic algorithms) to the outputs of the SAM project. 

For more information see AI Techniques for FRM in Urban Environments

WRc Group (Water Research Centre)

Work with WRc is looking into why sewers block and developing an understanding of the formation factors in small diameter pipes.

HR Wallingford

A project to develop new decision making methods for flexible adaptation of water engineering systems to a changing climate, urbanisation and other future uncertainties. It will first develop a generic software system to implement a number of well known methods for decision making under uncertainty. Then, specific water system models will be developed to support adaptation decisions relating to urban drainage, fluvial and coastal flood related problems. These models will then be tested on a number of pilot sites and the results obtained will be used to determine the most suitable decision making methods.

For more information see STREAM EngD HRW poster

United Utilities (UU)

Working  to develop new methods for the effective and efficient real-time management of water distribution systems. The UU water company is currently upgrading its SCADA system by installing a large number of new data loggers in their water distribution systems. This will enable the reception of near real-time pressure and flow data from field sensors to the control room. Once developed, the new technology will be used in the UU control room to more effectively and efficiently manage their water distribution systems resulting in significant monetary savings and improved company PR.

For more information see STREAM EngD UU

Northumbrian Water

Working together to look into: 1) Application of multi-objective optimisation to develop optimal intervention, control and management strategies for wastewater systems; 2) Impact analysis of system and future uncertainties (such as climate change and urbanisation) on management strategies; 3) Integrated assessment of various options for the water companies with the aim of reducing energy use and GHG emissions; and 4) Integrated assessment of the impacts of SUDS on flood risk and water pollution risk by considering in detail the wider water cycle through a fully integrated urban wastewater model.

Hydro International

A project to establish protocols for the selection of flow attenuation mechanisms to prevent flooding, minimise treatment and maintenance requirements, and reduce detrimental effects on the environment as a result of pollutant transport and accumulation. This will lead to the development of decision support tools which can be used by drainage authorities, consultants, developers and other stakeholders for the selection of attenuation mechanisms that will provide more effective and resilient urban drainage systems.

AECOM

Working together to: (1) investigate processes and tools to maximise the potential benefits of using relational databases to enhance data collection and availability for strategic asset management; (2) develop customisable performance and risk based analysis platforms, driven by corporate data systems, which form the basis of asset management plans; (3) develop and implement tools to permit engineers to evaluate multiple intervention scenarios in terms of a variety of different criteria; (4) integrate optimisation tools into the decision making process to identify intervention strategies which are justifiable, auditable and quantifiable in their ability to deliver economically efficient and risk adverse solutions; (5) analyse and use data mining tools to extract and process useful information from real-time asset performance systems; (6) implement GIS and scenario modelling tools to better understand the consequence of asset failure.

Micro Drainage

This project aims to incorporate low impact developments (LIDs) or SUDS (sustainable urban drainage systems) and BMPs (best managment practices) into urban drainage system design. 

For more information see STREAM EngD Micro Drainage Poster and STREAM sustainable drainage poster

Current project partners

Please visit our project pages for further information.