Project highlights

  • Monitoring wastewater in real time to optimise storage in the wastewater network, wastewater treatment performance and ensure river protection.
  • The parameters of interest (e.g. flow rate, water quality, pipeline structural integrity) will be collected by a self-powered sensing node that will be developed.
  • The self-powered sensing node will combine a bespoke flow-induced vibration energy harvester integrated with wireless sensing for distributed self-sustained monitoring.

Overview

The 2050 wastewater destination for the UK Water Industry is an environmentally sustainable wastewater service that works as one end-to-end system, from customer drain to the river, collecting and treating wastewater within the system with zero spills to the environment. A critical step in achieving this goal is to develop intelligent wastewater systems that self-monitor, self-assess and self-regulate, to optimise storage in the wastewater network, wastewater treatment performance and river protection. This will require unprecedented levels of monitoring, using new wireless sensing systems, often in inaccessible locations (including thousands online sensors in rivers), which will benefit from being able to self-power to minimise maintenance, energy costs and carbon footprint.

This project aims to design appropriate self-sustainable solution that will enable the implementation of the Internet of Things (IoT) within wastewater network, including rivers. It is envisaged that a combination of traditional wastewater network and IoT will form an accurate and low-cost solution for continuous and long-term monitoring of water quality to deliver sustainable wastewater treatment systems. One of the critical aspects for IoT is the deployment of robust self-powered sensing nodes, forming a network for data collection and transmission to establish a detailed picture of the water quality and distribution within the network.

Self-powered sensing systems have two key advantages: (i) they do not require batteries, since they harvest energy from the environment (e.g. water-flow induced vibration) to power sensing and data transmission and (ii) they do not require wiring, since data are transmitted wirelessly. Thus, they can enable wastewater monitoring in hard-to-reach areas (e.g. rivers), leading to significant reduction of the human intervention, since it is no longer necessary to physically visit inhospitable environments to obtain measurements.

The proposed study will develop a self-powered sensing node for wastewater monitoring within one end-to-end system from customer drain to the river. The whole solution consists of a bespoke energy harvester integrated with water quality monitoring sensors. These self-powered wireless sensing nodes will be autonomous, self-sustained with marginal human involvement. A hardware demonstrator (self-powered sensing node) assessed in real operating conditions will be the main deliverable to facilitate environmentally-sustainable wastewater monitoring.

Two panels showing a photograph of the energy harvester turbine (about the size of a £2 coin) and a figure showing sensing data over a 6 hour period (temperature and humidity).

Figure 1: Airflow Energy Harvesting and Self-powered Wireless Environmental Sensing.

CENTA Flagship

This is a CENTA Flagship Project

Case funding

This project is suitable for CASE funding

Host

Loughborough University

Theme

  • Climate and Environmental Sustainability

Supervisors

Project investigator

Co-investigators

How to apply

Methodology

Understanding of the expected flow-induced vibration conditions of the self-powered sensing node (using the ambient energy) will drive the energy balance equation, where the input and output energy amounts will be considered. The Energy Harvester (EH) principle (piezoelectric versus electromagnetic) will be explored in combination with power management solutions for self-powered sensing.

The EH will be modelled using numerical analysis (combination of Matlab and 3D software) and parametric studies will be conducted to predict the most attractive set of design parameters. This will lead to the design and manufacture of the self-powered sensing node, considering all the components (EH, capacitor, power management, micro-controller, data communication protocol and sensor types). Component level testing of the EH and data communication will be done in the Laboratory for validation. The self-powered sensing node will be assembled and will be tested in the Laboratory, as well as at an actual wastewater network.

Training and skills

Students will be awarded CENTA2 Training Credits (CTCs) for participation in CENTA2-provided and ‘free choice’ external training. One CTC equates to 1⁄2 day session and students must accrue 100 CTCs across the three years of their PhD.

The Researcher will be trained on:

i) energy harvesting principles (comprising VEH and fluid-induced vibration)

ii) multiphysics numerical modelling of EH using commercial software

iii) miniaturised self-powered sensing hardware design

iv) experimental setup and measurements for validation of the design in the Laboratory, as well as field testing. They will be supported by a Group of Academics (Loughborough) and Industry (Severn Trent Water) in order to develop expertise in self-powered sensing for wastewater network monitoring.

Partners and collaboration

CASE partner Severn Trent participates with Dr Cynthia Carliell-Marquet (Innovation Architect – Waste Systems) and Mr James Ballard (Innovation Architect, ICA) who lead the company’s innovation activity on Intelligent Waste Systems. They will provide strategic direction on self-powered sensing development to ensure that the outcomes best meet the strategic needs of the Water Industry with respect to river water quality protection. The participation of Specialists in regular meetings and time spent to steer the project is estimated at £15,000. If appropriate, Severn Trent will provide locations for prototype testing. An additional £3,500 cash contribution in total is provided (CASE studentship).

Further details

For further information about this project, please contact Dr Hailing Fu ([email protected]), Dr Amal Hajjej-Ep-Zemni ([email protected]) or Prof Stephanos Theodossiades ([email protected]). For general information about CENTA and the application process, please visit the CENTA website: https://centa.ac.uk/. For enquiries about the application process, please contact the Wolfson School of Mechanical, Electrical and Manufacturing Engineering ([email protected]).

If you wish to apply to the project, applications should include:

  • A CV with the names of at least two referees (preferably three and who can comment on your academic abilities)

Applications to be received by the end of the day on Wednesday 11th January 2023. 

Possible timeline

Year 1

The PhD Researcher will conduct a thorough review of the energy harvesting literature for wastewater monitoring applications and flow-induced oscillations. The energy requirements for the self-powered sensing node will be estimated and the energy balance equation will be drafted. The potential setup of a flow-induced vibration energy harvester will be assessed. Reduced order numerical models of the energy harvester will be developed using commercial software (Matlab and/or 3D electromagnetics).

Year 2

Parametric studies of the energy harvesting models will be conducted to select the key design features favouring energy harvesting. The energy harvester will be designed, and the prototype will be manufactured and tested in the laboratory for validation purposes. The other components of the node will be selected off-the shelf (sensor(s), power management board, capacitor, micro-controller and communication protocol). The protocol will be tested in the Lab and any discrepancies will be refined.

Year 3

The self-powered sensing node will be assembled combining all the necessary components selected in Year 2. The complete system will be validated in the Laboratory and at a wastewater network. Refinements will be identified and implemented.

Further reading

Fu, H, Theodossiades, S, Gunn, B, Abdallah, I, Chatzi, E (2020) Ultra-low frequency energy harvesting using bi-stability and rotary-translational motion in a magnet-tethered oscillator, Nonlinear Dynamics, 101(4), pp.2131-2143, ISSN: 0924-090X. DOI: 10.1007/s11071-020-05889-9.

Fu, H, Mei, X, Yurchenko, D, Zhou, S, Theodossiades, S, Nakano, K, Yeatman, EM (2021) Rotational energy harvesting for self-powered sensing, Joule, ISSN: 2542-4351. DOI: 10.1016/j.joule.2021.03.006

Gunn, BE, Alevras, P, Flint, J, Fu, H, Rothberg, S, Theodossiades, S (2021) A self-tuned rotational vibration energy harvester for self-powered wireless sensing in powertrains, Applied Energy, 302, 117479, ISSN: 0306-2619. DOI: 10.1016/j.apenergy.2021.117479.

Hajjaj, A, Ruzziconi, L, Alfosail, F, Theodossiades, S (2022) Combined internal resonances at crossover of slacked micromachined resonators, Nonlinear Dynamics, ISSN: 0924-090X

Singh, P., Kansal, A. & Carliell-Marquet, C. Energy and carbon footprints of sewage treatment methods, Journal of Environmental Management, 165, 2016, 22-30, https://doi.org/10.1016/j.jenvman.2015.09.017.

COVID-19

The project involves a mixture of numerical modelling, analysis, hardware design and experimental measurements. Remote access to software and design tools can be provided if UK National lockdowns occur in the future. The hardware design and experimental work will start as early as possible in the project so that there are sufficient time margins ahead for activities to be shifted without affecting the project aim and objectives. Access to the University Labs was provided during covid pandemic for most of the time via a booking system in order to limit the number of people working in the same room.