Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- University of Nottingham
- ;
- ; University of Nottingham
- University of Manchester
- ; University of Birmingham
- ; University of Bristol
- AALTO UNIVERSITY
- Harper Adams University
- University of Newcastle
- ; Swansea University
- ; The University of Manchester
- ; University of Southampton
- University of Sheffield
- ; Brunel University London
- ; Cranfield University
- ; The University of Edinburgh
- ; University of Leeds
- Imperial College London
- ; Aston University
- ; Loughborough University
- ; University of Oxford
- ; University of Reading
- ; University of Surrey
- ; University of Warwick
- Abertay University
- Newcastle University
- THE HONG KONG POLYTECHNIC UNIVERSITY
- University of Leicester
- 19 more »
- « less
-
Field
-
that deliver high power density and exceptional efficiency at reasonable cost. However, most existing machines, particularly high-speed, radial-flux permanent magnet motors, are reaching their performance
-
platforms at both locations, providing the student with hands-on industrial experience as well as cutting-edge research insight. Description The global drive towards electrification in high-performance
-
embrittlement. However, the immiscibility between Cu and W leads to poor bonding, whilst during high temperature manufacturing/operation embrittlement of steel-W joints occurs due to the formation of brittle
-
-box techniques in the industry is still high. One of the main reasons is that the performance of such techniques highly depends on a large amount of good-quality data. Unfortunately, the availability
-
environment. Accurately predicting flow and heat transfer in these systems is critical for safety, performance, and design assessments, yet direct high-fidelity simulations, such as Large Eddy Simulation (LES
-
fuel, but its high reactivity makes it vulnerable to pre-ignition. The presence of lubricating oil droplets can worsen this risk by evaporating, altering chemical pathways, and producing nanoscale soot
-
on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine
-
Tandem Industry-Academy funded project https://www.vaikuttavuussaatio.fi/en/funded-projects/tandem-industry-academia-tia-seed-2024/ . developing next-generation optical computing technologies for ultra
-
Research Group at the Faculty of Engineering which conducts cutting edge research into experimental and computational heat and mass transfer, multiphase flows, thermal management, refrigeration, energy
-
be used effectively as a performance digital twin to generate high-quality engine performance models and produce required training data for the proposed project. This could be a good starting point for