Projects
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| Reference Number | UKRI1494 | |
| Title | Towards data-driven turbulence control: saving energy in pipelines by suppressing turbulence | |
| Status | Started | |
| Energy Categories | Fossil Fuels: Oil Gas and Coal (Oil and Gas, Other oil and gas) 10%; Not Energy Related 80%; Other Power and Storage Technologies (Electricity transmission and distribution) 10%; |
|
| Research Types | Basic and strategic applied research 100% | |
| Science and Technology Fields | PHYSICAL SCIENCES AND MATHEMATICS (Physics) 50%; ENGINEERING AND TECHNOLOGY (Mechanical, Aeronautical and Manufacturing Engineering) 50%; |
|
| UKERC Cross Cutting Characterisation | Not Cross-cutting 100% | |
| Principal Investigator |
Elena Marensi University of Sheffield |
|
| Award Type | Standard | |
| Funding Source | EPSRC | |
| Start Date | 03 November 2025 | |
| End Date | 03 November 2028 | |
| Duration | 36 months | |
| Total Grant Value | £435,188 | |
| Industrial Sectors | Unknown | |
| Region | Yorkshire & Humberside | |
| Programme | NC : Engineering | |
| Investigators | Principal Investigator | Elena Marensi , University of Sheffield |
| Web Site | ||
| Objectives | ||
| Abstract | An enormous amount of fluids — from water to oil and natural gas — is transported across the globe through pipes and ducts. In the United Kingdom alone there is over 215,277 miles of water pipelines, enough to travel the circumference of the world 8 times. Most often these flows are turbulent, and the associated frictional losses are much larger than those of laminar flows, making it a far less energy-efficient way of transporting fluids. According to estimates, around 10% of the global electric power consumption is spent by pumping systems to overcome frictional drag in pipelines, including not only large-scale oil/gas pipelines, but also domestic networks. Fighting against climate change, the most desirable, yet challenging, outcome that a flow control method could achieve is to completely extinguish turbulence, hence zeroing the associated frictional losses. Even when relaminarisation has been achieved in lab experiments and numerical simulations, it was not possible to explain on a theoretical basis why the control strategy worked, and under which conditions. This lack of understanding has so far prevented up-scaling of relaminarising control strategies for deployment and implementation in practical engineering systems. To overcome these limitations, this project will exploit recent advances in machine-learning and data-driven methods to unravel the physical mechanisms underlying the phenomenon of forced relaminarisation and to provide a mathematical description of its dynamics through the theory of dynamical systems. The understanding gained in this way will be leveraged to develop novel control strategies, based on the same principle, to completely suppress turbulence in pipeline flows of industrial interest. Such vision has important societal and economic implications because vanishing turbulence will massively curb carbon emissions, thus leading to improved air quality and contributing to meeting the net-zero-by-2050 target. This achievement is also of great fundamental interest as it would provide a better understanding of the universal mechanisms sustaining wall-bounded turbulence. As this knowledge applies not only to pipelines but to many other flows of industrial relevance (e.g. flows over the wing of an aeroplane or a turbine blade), it will enable us to control and improve efficiency of these systems in a variety of engineering and technological applications | |
| Data | No related datasets |
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| Projects | No related projects |
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| Publications | No related publications |
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| Added to Database | 14/01/26 | |
