Dr Daniel Poole
MEng, PhD
Expertise
Developing advanced optimisation technologies for simulation-driven engineering optimisation. Development includes global and gradient-based optimisation, multi-physics coupled simulation, application to aerospace, renewables, etc
Current positions
Senior Lecturer
School of Civil, Aerospace and Design Engineering
Contact
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Biography
Dr. Poole is currently a Senior Lecturer in the Department of Aerospace Engineering, where his research considers developing advanced techniques for simulation and design of multi-physics coupled engineering systems. He is the Deputy Programme Director in the Aerospace Engineering Department and a current member of the University of Bristol Senate. He is a Fellow of the Higher Education Academy and is enthusastic about engineering education. Dr. Poole obtained his PhD from the University of Bristol in 2017 under the supervision of Prof Chris Allen and Dr Tom Rendall. The body of this work involved developing methods to allow high-fidelity global optimisation of aerodynamic shapes (e.g. aerofoils, wings and turbine blades). He has collaborated externally with, for example, Leonardo Helicopters, DNV, Zenotech on simulation and optimisation projects.
Queries about postgraduate study or postdoctoral research can be made to d.j.poole@bristol.ac.uk.
Projects and supervisions
Thesis supervisions
Adaptive Sampling in Particle Image Velocimetry
Supervisors
Machine learning for wind flow modelling
Supervisors
Publications
Recent publications
10/06/2024Graph-based Deep Reinforcement Learning for Wind Farm Set-Point Optimisation
The Science of Making Torque from Wind (TORQUE 2024) 29/05/2024 - 31/05/2024 Florence, Italy
Deep Reinforcement Learning for Wind Farm Set-Point Optimisation
An Initial Study of Multimodality in Wind Farm Layout Optimization Problems
AIAA SciTech Forum 2022
Preliminary Investigation of Hessian Approximation with an Orthogonal Modal Parameterisation for Accelerated Shape Optimisation
AIAA AVIATION 2022 Forum
Efficient aeroelastic wing optimization through a compact aerofoil decomposition approach
Structural and Multidisciplinary Optimization
Thesis
Efficient Optimisation Methods for Generic Aerodynamic Shape Optimisation
Supervisors
Award date
06/11/2017