Grants
EnAble: Developing and Exploiting Intelligent Approaches for Turbulent Drag Reduction
Whenever air flows over a commercial aircraft or a high-speed train, a thin layer of turbulence is generated close to the surface of the vehicle. This region of so-called wall-turbulence generates a resistive force known as skin-friction drag which is responsible for more than half of the vehicle's energy consumption. Taming the turbulence in this region reduces the skin-friction drag force, which in turn reduces the vehicle's energy consumption and thereby reduces transport emissions, leading to economic savings and wider health and environmental benefits through improved air quality. To place this into context, just a 3% reduction in the turbulent skin-friction drag force experienced by a single long-range commercial aircraft would save £1.2M in jet fuel per aircraft per year and prevent the annual release of 3,000 tonnes of carbon dioxide. There are currently around 23,600 aircraft in active service around the world. Active wall-turbulence control is seen as a key upstream technology currently at very low technology readiness level that has the potential to deliver a step change in vehicle performance. Yet despite this significance and well over 50 years of research, the complexity of wall-turbulence has prevented the realisation of any functional and economical fluid-flow control strategies which can reduce the turbulent skin-friction drag forces of industrial air flows of interest. The EnAble project aims to develop, implement and exploit machine intelligence paradigms to enable a new approach to wall-turbulence control. This new form of intelligent fluid-flow control will be used to develop practical wall-turbulence control strategies that can rapidly and autonomously optimise the aerodynamic surface with minimal power input whilst being adaptive to changes in flow speed. This new capability will open up the opportunity to discover new ways to tame wall-turbulence and exploit the latest drag reduction mechanisms to generate significant levels of turbulent skin-friction drag reduction.
Funder: Engineering and Physical Sciences Research Council (EPSRC)
Grant Reference: EP/T020946/1 & EP/T021144/1
Value: £1,414,166
Start: 01 March 2021
End: 16 January 2025
Principle Investigators: Dr Richard Whalley (Newcastle University) & Dr Sylvain Laizet (Imperial College London)
Co-Investigators: Dr Kevin Wilson (Newcastle University), Dr Yu Guan (Newcastle University), Dr Andrew Wynn (Imperial College London)
Grant Reference: EP/T020946/1 & EP/T021144/1
Value: £1,414,166
Start: 01 March 2021
End: 16 January 2025
Principle Investigators: Dr Richard Whalley (Newcastle University) & Dr Sylvain Laizet (Imperial College London)
Co-Investigators: Dr Kevin Wilson (Newcastle University), Dr Yu Guan (Newcastle University), Dr Andrew Wynn (Imperial College London)
OCULUS: Flow variation during vitrectomy with vacuum versus fluid flow controlled aspiration systems
Vitrectomy is an established and effective therapy for a range of blinding retinal diseases. The number of operations carried out is rapidly rising with a reduction in threshold for surgery and new indications including gene therapy being investigated. Being attached to the retina, safe vitrectomy requires low traction removal to avoid retinal break formation. This is particularly important in cases with mobile detached retinas, where the risk of iatrogenic retinal holes is particularly high and associated with higher failure rates. To facilitate low traction vitreous cutting, a number of innovations have been made including narrower gauge surgery, and high-speed cutters. Traction is related to vitreous acceleration during cutting and dual blade cutters have further reduced acceleration by maximising port open time. This has also allowed increased flow and reduced traction, but it hasn’t reduced the need for steady flow rates during vitrectomy, which are of key importance. Flow is generated in vitrectomy by pumps which are typically flow or vacuum (peristaltic or venturi) controlled, connected to the aspiration tubing of vitreous cutters. Theoretically, flow based pumps offer advantages in terms of even flow but there are also limitations in their use during vitrectomy, including the frequent requirement to operate at interfaces with widely different viscosities including for example, air and dense lens material. There are also reasons why their theoretical advantages may not be manifest during use. The vitrectomy cutter is attached typically to the pump by approximately 3-4 foot of elastomeric tubing, which modulates aspirational flow with an applied vacuum. Furthermore, high-speed cutting creates port-based flow limitation and smooths flow with smaller bite sizes of vitreous, perhaps making the effect of flow control less important. Understanding the effects of flow or vacuum-based pumps on vitreous flow would allow their more logical use, and ultimately maximise safe vitrectomy.
Funder: Dutch Ophthalmic Research Centre (DORC)
Value: £383,905
Start: 01 November 2021
End: 30 April 2023
Principle Investigators: Dr Richard Whalley (Newcastle University) & Professor David Steel (Newcastle University)
Value: £383,905
Start: 01 November 2021
End: 30 April 2023
Principle Investigators: Dr Richard Whalley (Newcastle University) & Professor David Steel (Newcastle University)
AURORA: Testing super-miniature micro sensors for aircraft applications
The Fluid Dynamics Laboratory at Newcastle University has developed a range of super-miniature micro sensors which can obtain accurate, instantaneous measurements of skin-friction drag for aircraft applications. Our sensor systems are protected by two patents filed in January 2021. The innovative micro-sensor systems that have been developed will be pivotal in realising the next-generation of technology which can monitor and tame the effects of turbulence on aircraft: successful implementation could yield a potential saving of $100M per annum for the aviation sector. Ultimately, the super-miniature micro sensor systems will be used within an aircraft’s control system to sense when turbulence has been suppressed (i.e. in a feedback loop. Specific objectives of AURORA are as follows: (i) develop relevant industrial demonstrators, (ii) gain validation and use of the sensor technology external to Newcastle University and (iii) publish high-quality articles to showcase and publicise the new micro-sensing technology.
Funder: Northern Accelerator
Value: £116,599
Start: 01 April 2022
End: 31 May 2023
Principle Investigator: Dr Richard Whalley (Newcastle University)
Value: £116,599
Start: 01 April 2022
End: 31 May 2023
Principle Investigator: Dr Richard Whalley (Newcastle University)
SPECTRA: Super-miniature micro sensors for wall-turbulence measurements
Whenever air flows over a commercial aircraft or a high-speed train, or when water flows around the hull of an ocean-going ship liner, a thin layer of turbulence is generated close to the surface of the vehicle. This region of turbulence generates a resistive force (i.e. a drag force) which creates a wall-shear stress across the entire surface of the aircraft, train or ship. This wall-shear stress is responsible for more than half of the vehicle’s energy consumption. Taming the turbulence in this region reduces the wall-shear stress, which in turn reduces the vehicle’s energy consumption and thereby reduces transport emissions, leading to economic savings and wider health and environmental benefits through improved air quality. To place this into context, just a 3% reduction in the wall-shear stress experienced by a single long-range commercial aircraft would save £1.2M in jet fuel per aircraft per year and prevent the annual release of 3,000 tonnes of carbon dioxide. There are around 23,600 aircraft in active service around the world: a billion pound problem. Wall-shear stress sensor systems will be pivotal in realising the next-generation of technology that is capable of reducing the energy consumption and transport emissions across the global transportation sector by sensing when control has been successfully applied (i.e. in a feedback loop). Therefore, wall-shear stress sensors systems have a place in R&D, and commercially, across numerous institutions that conduct wind tunnel, water flume and towing-tank testing and companies who specialise in the design and manufacture of transportation vehicles (airplanes, trains, ships, cars etc.). Obtaining accurate measurements of wall-shear stresses is also of great fundamental importance, making these sensors an essential and next-generation tool for many fluid dynamics laboratories around the world. Much more research is required to develop our understanding on turbulent flows to enable the technology to tame turbulence and reap the benefits outlined above, opening up commercial opportunities within Universities worldwide. Specific objectives of SPECTRA are as follows: (i) develop a series of professional-looking prototypes to enable future pitches with interested and invested commercial partners, (ii) develop demonstrators to showcase the market potential of the sensor technology, (iii) further develop the technology for market needs identified through a Northern Accelerator market assessment and (iv) build strong and trusting relationships with future business partners.
Funder: Engineering and Physical Science Research Council (EPSRC) Impact Acceleration Award
Grant Reference: EP/R511584/1
Value: £117,231
Start: 15 May 2021
End: 15 March 2022
Principle Investigator: Dr Richard Whalley (Newcastle University)
Grant Reference: EP/R511584/1
Value: £117,231
Start: 15 May 2021
End: 15 March 2022
Principle Investigator: Dr Richard Whalley (Newcastle University)
Hibernating turbulence in boundary-layer flows
This proposal will focus on detecting and characterising the recently discovered phenomena of hibernating turbulence in boundary-layer flows. This may lead to ultimately transformative technology which would increase overall vehicle energy efficiency. The skin-friction drag force is a major source of fuel consumption across all major transportation modes. Hibernating turbulence is a unique form of intermittent flow behaviour, which causes the skin-friction drag force experienced by an aero- or hydrodynamic body to temporarily reduce by up to 70%. Nominally 50% of the total drag on aircraft is due to skin-friction drag, this increases to 90% for hydrodynamic vehicles such as submarines. Consequently, minimising drag by maintaining intervals of hibernating turbulence would reduce fuel consumption and, in turn, lower cost and improve vehicle performance.
Funder: United States Air Force Office of Scientific Research
Grant Reference: FA9550-17-1-0231
Value: $159,526
Start: 1 September 2017
End: 28 February 2023
Principle Investigator: Dr Richard Whalley (Newcastle University)
Grant Reference: FA9550-17-1-0231
Value: $159,526
Start: 1 September 2017
End: 28 February 2023
Principle Investigator: Dr Richard Whalley (Newcastle University)
PhD Projects
Project "tip-top": Harvesting more power from the wind with smart closed-loop rotor control
Leading edge technologies and flow control strategies are currently being developed to optimise wind turbine power production with Newcastle University and the EPSRC ReNU. Between 6:30pm and 7:00pm on 10th January 2023 British wind farms averaged a record 21.69GW of power generation, and produced 30% of the UK energy requirements in 2022. Modern turbines are pushing working efficiency close to the Betz limit of 59.3%, which is the maximum energy transfer possible from the wind. Even with these achievements that supply renewable energy to the grid, down time still occurs as there are limitations in operational range. Development of highly efficient control methods to minimise flow separation and drag will be tested within our wind tunnel in the fluid dynamics lab. Once the control system is complete, integration into a working wind turbine model will then be tested and evaluated in Newcastle Universities wind, wave and current facility. The controller will be in a closed loop configuration that receives feedback from the system to indicate the flow conditions over the blades. From this the controller can apply air jet actuators on the low-pressure side of the turbine blade to manipulate the boundary layer for increased performance and to minimise drag.
Leading edge technologies and flow control strategies are currently being developed to optimise wind turbine power production with Newcastle University and the EPSRC ReNU. Between 6:30pm and 7:00pm on 10th January 2023 British wind farms averaged a record 21.69GW of power generation, and produced 30% of the UK energy requirements in 2022. Modern turbines are pushing working efficiency close to the Betz limit of 59.3%, which is the maximum energy transfer possible from the wind. Even with these achievements that supply renewable energy to the grid, down time still occurs as there are limitations in operational range. Development of highly efficient control methods to minimise flow separation and drag will be tested within our wind tunnel in the fluid dynamics lab. Once the control system is complete, integration into a working wind turbine model will then be tested and evaluated in Newcastle Universities wind, wave and current facility. The controller will be in a closed loop configuration that receives feedback from the system to indicate the flow conditions over the blades. From this the controller can apply air jet actuators on the low-pressure side of the turbine blade to manipulate the boundary layer for increased performance and to minimise drag.
PhD Student: Ian Mills
PhD Supervisors: Dr Richard Whalley (Principal Supervisor, Newcastle University), Dr Kevin Wilson (Co-Supervisor, Newcastle University)
Start Date: October 2022
End Date: September 2026
Funder: EPSRC Centre for Doctoral Training in Renewable Energy Northeast Universities (ReNU)
Grant Reference: EP/S023836/1
Value: £100,744
PhD Supervisors: Dr Richard Whalley (Principal Supervisor, Newcastle University), Dr Kevin Wilson (Co-Supervisor, Newcastle University)
Start Date: October 2022
End Date: September 2026
Funder: EPSRC Centre for Doctoral Training in Renewable Energy Northeast Universities (ReNU)
Grant Reference: EP/S023836/1
Value: £100,744
Project INTEL: Taming turbulence with the Cloud
Active control strategies in the form of low-amplitude wall-normal blowing have proven to reduce the turbulent drag over a surface, such as an aerofoil, in the past. However, the question of how to find optimal strategies that maximise the drag reduction , while simultaneously achieving net energy savings remains unanswered. This turns out to be a literal £1 million question as even a small reduction in drag has the potential to save millions every year in fuel costs and in environmental damages due to fewer emissions. Complex problems like these that cannot be represented by mathematical expressions, are commonly known as black box functions, and due to their expensive nature, demand a cost-effective optimisation strategy. In this project, we develop an advanced Bayesian Optimisation framework that (a) incorporates data from multiple sources (experiments, simulations, etc.), (b) maximises for drag reduction and net energy savings, and (c) scales efficiently via parallel and asynchronous evaluations. Our vision is a cloud-based solution that automatically improves with each data point it gathers simultaneously, from computer simulations and physical experiments.
Active control strategies in the form of low-amplitude wall-normal blowing have proven to reduce the turbulent drag over a surface, such as an aerofoil, in the past. However, the question of how to find optimal strategies that maximise the drag reduction , while simultaneously achieving net energy savings remains unanswered. This turns out to be a literal £1 million question as even a small reduction in drag has the potential to save millions every year in fuel costs and in environmental damages due to fewer emissions. Complex problems like these that cannot be represented by mathematical expressions, are commonly known as black box functions, and due to their expensive nature, demand a cost-effective optimisation strategy. In this project, we develop an advanced Bayesian Optimisation framework that (a) incorporates data from multiple sources (experiments, simulations, etc.), (b) maximises for drag reduction and net energy savings, and (c) scales efficiently via parallel and asynchronous evaluations. Our vision is a cloud-based solution that automatically improves with each data point it gathers simultaneously, from computer simulations and physical experiments.
PhD Student: Mike Diessner
PhD Supervisors: Dr Richard Whalley (Principal Supervisor, Newcastle University), Dr Kevin Wilson (Co-Supervisor, Newcastle University)
Start Date: October 2021
End Date: September 2024
Funder: EPSRC Centre for Doctoral Training in Cloud Computing for Big Data
Grant Reference: EP/L015358/1
Value: £68,481
PhD Supervisors: Dr Richard Whalley (Principal Supervisor, Newcastle University), Dr Kevin Wilson (Co-Supervisor, Newcastle University)
Start Date: October 2021
End Date: September 2024
Funder: EPSRC Centre for Doctoral Training in Cloud Computing for Big Data
Grant Reference: EP/L015358/1
Value: £68,481
OCULUS: Flow variation during vitrectomy with vacuum versus fluid flow controlled aspiration systems
This project aims to assess the fluidic performance of two vitrectomy systems made by the company DORC. With numerous combinations of system settings, the task of optimizing aspiration flow rates while maintaining precise tissue cutting, can be challenging. To safely utilize new-generation instruments, surgeons require detailed knowledge of the fluidics effects of the instruments. For this, both macro particle image velocimetry (PIV) at the cutter port and micro PIV in the tubing proximal to the cutter have been utilised to investigate flow characteristics in a variety of scenarios including the effect of cut rate, vacuum and flow settings, intraocular pressure and instrument gauge size. Furthermore, novel vitreous mimics have been investigated to assess the flow in Newtonian conditions with saline solution and will be investigated in non-Newtonian conditions. The primary aim of this project is to study variability of flow and influence of the surgical instruments and operational conditions on the surgery fluidics during vitrectomy with different types of pumps, namely vacuum and flow-controlled pumps. Alongside this, I will also examine the effects of intraocular pressure (IOP) and IOP fluctuations with and without infusion flow control systems on aspirational flow. Overall, understanding more fully the effects of flow or vacuum-based pumps on vitreous flow, with the combined effects of cut rate, port shape, cutter size and cutting action on vitreous flow will allow enhancements to their design to reduce traction, thereby reducing retinal tear formation, making vitrectomy safer with improved visual results.
This project aims to assess the fluidic performance of two vitrectomy systems made by the company DORC. With numerous combinations of system settings, the task of optimizing aspiration flow rates while maintaining precise tissue cutting, can be challenging. To safely utilize new-generation instruments, surgeons require detailed knowledge of the fluidics effects of the instruments. For this, both macro particle image velocimetry (PIV) at the cutter port and micro PIV in the tubing proximal to the cutter have been utilised to investigate flow characteristics in a variety of scenarios including the effect of cut rate, vacuum and flow settings, intraocular pressure and instrument gauge size. Furthermore, novel vitreous mimics have been investigated to assess the flow in Newtonian conditions with saline solution and will be investigated in non-Newtonian conditions. The primary aim of this project is to study variability of flow and influence of the surgical instruments and operational conditions on the surgery fluidics during vitrectomy with different types of pumps, namely vacuum and flow-controlled pumps. Alongside this, I will also examine the effects of intraocular pressure (IOP) and IOP fluctuations with and without infusion flow control systems on aspirational flow. Overall, understanding more fully the effects of flow or vacuum-based pumps on vitreous flow, with the combined effects of cut rate, port shape, cutter size and cutting action on vitreous flow will allow enhancements to their design to reduce traction, thereby reducing retinal tear formation, making vitrectomy safer with improved visual results.
PhD Student: Daria Vedeniapina
PhD Supervisors: Dr Richard Whalley (Principal Supervisor, Newcastle University), Professor David Steel (Co-Supervisor, Newcastle University), Dr Piergiorgio Gentile (Co-Supervisor, Newcastle University), Dr Ana Ferreira-Duarte (Co-Supervisor, Newcastle University)
Start Date: October 2021
End Date: September 2025
Funder: EPSRC iCASE and Dutch Ophthalmic Research Centre (DORC)
Grant Reference: EP/W52203X/1
Value: £88,881
PhD Supervisors: Dr Richard Whalley (Principal Supervisor, Newcastle University), Professor David Steel (Co-Supervisor, Newcastle University), Dr Piergiorgio Gentile (Co-Supervisor, Newcastle University), Dr Ana Ferreira-Duarte (Co-Supervisor, Newcastle University)
Start Date: October 2021
End Date: September 2025
Funder: EPSRC iCASE and Dutch Ophthalmic Research Centre (DORC)
Grant Reference: EP/W52203X/1
Value: £88,881
Super-miniature engineering: MEMS wall-shear stress sensor systems
With wall-turbulence and skin-friction drag being a key focus of research in not only the research group but also the wider fluid dynamic community, being able to make accurate measurements of wall-shear stress with both high temporal and spatial resolution becomes of great importance. With the spatial and temporal requirements needed for measuring the finer structures created by wall-turbulence, micro-electro-mechanical-systems (MEMS) based sensors become an obvious candidate due to fabrication techniques allowing sensors to be of order 10s to 100s of microns. A key focus of my project is to reduce the spatial averaging effects seen in larger sensors, to allow the finer details of wall-turbulence to be studied. During the course of my PhD, a range of sensors will be designed and developed to achieve these sensing requirements, initially focussing on proof-of-concept single dimension wall-shear stress sensors with the scope and potential to expand these to not only make two dimensional, orthogonal wall-shear sensors but also arrays of these sensors with multiple being fabricated onto a single silicon chip.
PhD Student: Joe Barrow
PhD Supervisors: Dr Richard Whalley (Principal Supervisor, Newcastle University), Dr Barry Gallacher (Co-Supervisor, Newcastle University)
Start Date: October 2020
End Date: September 2024
Funder: EPSRC Doctoral Training Partnership
Grant Reference: EP/R51309X/1
Value: £88,881
PhD Supervisors: Dr Richard Whalley (Principal Supervisor, Newcastle University), Dr Barry Gallacher (Co-Supervisor, Newcastle University)
Start Date: October 2020
End Date: September 2024
Funder: EPSRC Doctoral Training Partnership
Grant Reference: EP/R51309X/1
Value: £88,881
EnAble: Developing and Exploiting Intelligent Approaches for Turbulent Drag Reduction
PhD Student: Jodi Reeve
PhD Supervisors: Dr Richard Whalley (Principal Supervisor, Newcastle University), Dr Kevin Wilson (Co-Supervisor, Newcastle University)
Start Date: October 2019
End Date: May 2022
Funder: EPSRC Doctoral Training Partnership
Grant Reference: EP/R51309X/1
Value: £83,481
PhD Supervisors: Dr Richard Whalley (Principal Supervisor, Newcastle University), Dr Kevin Wilson (Co-Supervisor, Newcastle University)
Start Date: October 2019
End Date: May 2022
Funder: EPSRC Doctoral Training Partnership
Grant Reference: EP/R51309X/1
Value: £83,481
Optical MEMS sensors for wall-shear stress measurements
PhD Student: Nima Ebrahimzade
PhD Supervisors: Dr Richard Whalley (Principal Supervisor, Newcastle University), Professor Peter Cumpson (Co-Supervisor, Newcastle University)
Start Date: January 2017
End Date: June 2021
Funder: EPSRC Doctoral Training Partnership
Grant Reference: EP/M5079X/1
Value: £83,481
PhD Supervisors: Dr Richard Whalley (Principal Supervisor, Newcastle University), Professor Peter Cumpson (Co-Supervisor, Newcastle University)
Start Date: January 2017
End Date: June 2021
Funder: EPSRC Doctoral Training Partnership
Grant Reference: EP/M5079X/1
Value: £83,481
Get in touch
Dr Richard Whalley
School of Engineering, Newcastle University, UK
School of Engineering, Newcastle University, UK