Summary
Office Hours: WED 1-2 PM
Prof Montomoli is a Professor in Computational Aerodynamics. His main research activities are on Heat Transfer, Gas Turbines, Uncertainty Quantification, Computational Fluid Dynamics, Rare Events, Aircraft Engines, Optimization. The two main areas of research of the UQLab are forward propagation of uncertainty and optimization/design under uncertainty for Aeronautics.
The UQLab is working on robust design for additive manufacturing and started a spinout licensing our code, Toffeex ltd
UNCERTAINTY QUANTIFICATION LAB
Short Bio:
Prof Montomoli read mechanical engineering at University of Florence where he obtained a MSc and a PhD (and he was visiting scholar at Texas AM University, Turbine Heat Transfer Laboratory, US). After the PhD he joined the R&D group of General Electric Oil&Gas.
In 2006 Dr Montomoli joined to the University of Cambridge, Whittle Laboratory and his researches were sponsored by Rolls-Royce and Mitsubishi Heavy Industries in the field of aerospace propulsion and power generation. In 2009 he becomes Mitsubishi Senior Fellow and College Lecturer at Girton College, Univ. of Cambridge
In 2011 Dr Montomoli was also Research Professor and leader of CFD group at the Basque Centre for Applied Mathematics. He is an external scientific member of BCAM.
In 2012 Dr Montomoli joined the University of Surrey as Senior Lecturer in Thermofluids.
In 2014 Dr Montomoli joined the Imperial College of London as Senior Lecturer
He is a Chartered Engineer of Ordine degli Ingegneri della Provincia di Firenze, Italy.
In 2017 he obtained the Italian qualification as Full Professor in Mechanical Engineering
In 2018 he was promoted to Reader and than, in 2021, to Professor at Imperial College London.
As technology transfer he is co-founder of two spinouts of Imperial College London
Selected Publications
Journal Articles
Li Z, Montomoli F, 2024, Aleatory uncertainty quantification based on multi-fidelity deep neural networks, Reliability Engineering & System Safety, Vol:245, ISSN:0951-8320
Baker CM, Blonda P, Casella F, et al., 2023, Using remote sensing data within an optimal spatiotemporal model for invasive plant management: the case of Ailanthus altissima in the Alta Murgia National Park, Scientific Reports, Vol:13, ISSN:2045-2322, Pages:1-14
Pepper N, Crespo L, Montomoli F, 2022, Adaptive learning for reliability analysis using Support Vector Machines, Reliability Engineering & System Safety, Vol:226, ISSN:0951-8320
Books
Montomoli F, 2018, Uncertainty Quantification in Computational Fluid Dynamics and Aircraft Engines, Springer, ISBN:978-3319146805
Conference
Gaymann A, Montomoli F, Pietropaoli M, Design for Additive Manufacturing: Valves Without Moving Parts, ASME IGTI Turbo Expo 2017