Professor Matthew Juniper



Professor of Thermofluid Dynamics
Fellow of Trinity College
ORCID 0000-0002-8742-9541
Scopus 6602882661

2021 Member of EPSRC Strategic Advisory Network.
2018 Associate Editor, J. Fluid Mech.
2016 PI UK Fluids Network
2016 Head of Energy Group
2015 Professor of Thermofluid Dynamics
2012 Reader in Mechanical Engineering
2008 Senior Lecturer
2006 Fellow of Trinity College
2003 Lecturer, University of Cambridge
2002 Associate, McKinsey & Co.
2001 PhD, Ecole Centrale de Paris
1998 DEA, Ecole Centrale de Paris
1997 MEng, University of Cambridge

Research Summary

My group and I model flows, investigate their physics, and optimize their behaviour.

We start from a physics-based model of a flow inside or around a device. If the model contains unknown parameters then we infer these from experiments using Bayesian Inference or adjoint methods. This turns a qualitative model into a quantitative model.

We investigate the behaviour of the model and seek to understand the phenomena it predicts. If the model does not capture all the relevant physics, we revise the model.

We set targets and constraints and thereby derive the adjoint of the model. This shows, in a single calculation, how the targets are affected by all the model parameters.

We then use gradient-based algorithms to optimize the flow through or around the device.

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