Sort by
Refine Your Search
-
and associated events, alongside the formation of a novel multi-physic digital twin to support future forensic identification of UAS fingerprint profiles. The main objectives are: 1. Identify, evaluate
-
community. We welcome students and staff from all backgrounds from over 100 countries and support our staff and students to realise their full potential, from academic achievement to mental and physical
-
-efficient research that prevents fatigue failures has pushed towards integrated computational materials engineering approaches that improve competitiveness. These approaches rely on physics-based models
-
of first or second class UK honours degree or equivalent in a related discipline, science (chemistry/physics) or engineering. The ideal candidate should have some understanding in the area of materials
-
of representative failure models for gear failures causes difficulties in their useful lifetime prediction. Critical operational parameters such as loading, speed and lubrication affect the physics of gear meshing
-
models and physics-based models. More recently, hybrid prognostics approaches have been presented, attempting to leverage the advantages of combining the prognostics models in the aforementioned different
-
from over 100 countries and support our staff and students to realise their full potential, from academic achievement to mental and physical wellbeing. Cranfield Doctoral Network Research students
-
Verification Tools: Develop AI algorithms that automate the verification process, ensuring systems meet required safety and performance standards. Health Monitoring Algorithms: Implement AI-based monitoring
-
community. We welcome students and staff from all backgrounds from over 100 countries and support our staff and students to realise their full potential, from academic achievement to mental and physical
-
, embedded intelligence, and adaptive cyber-physical systems that operate safely under uncertainty and dynamic conditions. This PhD at Cranfield University explores the development of resilient, AI-enabled