Dr Josh Hoole
PhD, MEng
Expertise
Development of data-driven probabilistic and statistical simulations to support engineering design and assessment. My focus is on real-time aircraft tracking and capturing manufacturing variability in electrical machines.
Current positions
Lecturer in Systems Engineering
School of Civil, Aerospace and Design Engineering
Contact
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Biography
Following the completion of an Aerospace Engineering (MEng) degree at the University of Bristol, I conducted a PhD within the Aerospace Engineering department focusing on the development and application of probabilistic methods for the fatigue analysis of safety-critical aerospace components. I then went on to apply this background in characterising manufacturing variability in electrical machine windings with the Electrical Energy Management Group (EEMG), before taking on the role of Lecturer in Systems Engineering within the Department of Aerospace Engineering in 2021. Going forward, I have a specific interest in researching how novel data sources, data analytics and probabilsitic/statistical simulation can be better integrated into industrial environments and design processes.
Research interests
Probabilistic design, statistical simulation, aircraft tracking, ADS-B trajectories, landing gear design, electric propulsion.
Projects and supervisions
Research projects
Data-Driven Aerospace Design through the Statistical Characterisation of the Search and Rescue Environment
Principal Investigator
Description
This project, funded by the Jean Golding Institute Seed Corn Call 2021-2022, aims to characterise the mission profile and environment for Search And Rescue (SAR) in the United Kingdom. This…Managing organisational unit
Department of Aerospace EngineeringDates
25/01/2022 to 05/07/2022
Publications
Recent publications
21/06/2023Remote Sensing of Aerospace Usage Profiles via Air Traffic Data
Review of aeronautical fatigue and structural integrity investigations in the UK during the period May 2021 - April 2023
Statistical Simulation of Conductor Lay in Random Windings via X-ray Computed Tomography of Electric Vehicle Stators
2023 IEEE Energy Conversion Congress and Exposition (ECCE)
Verifying Strand Transposition in Stator Windings via X-ray Computed Tomography derived Three-Dimensional Models
2023 IEEE Workshop on Electrical Machines Design, Control and Diagnosis (WEMDCD)
Characterisation of Compressed Windings via High Resolution X-ray Computed Tomography and Semi-Automatic Segmentation
IECON 2022
A methodological approach to virtual prototype development using strip wound inductor subassemblies
Thesis
Probabilistic Fatigue Methodology for Aircraft Landing Gear
Supervisors
Award date
23/06/2020
Teaching
AVDASI4 Group Design Project
Undergraduate Research Projects
Related people
Dr Nick Simpson
Associate Professor of Advanced Electrical Machine Design
School of Electrical, Electronic and Mechanical Engineering
Professor Jonathan Cooper
RAEng Airbus Sir George White Professor of Aerospace Engineering
School of Civil, Aerospace and Design Engineering
Professor Julian Booker
Professor of Mechanical Design Engineering
School of Electrical, Electronic and Mechanical Engineering
Professor Phil Mellor
Professor of Electrical Engineering
School of Electrical, Electronic and Mechanical Engineering
Mr Dominic North
Research Support Assistant
School of Electrical, Electronic and Mechanical Engineering