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The University of Southampton
Engineering
Phone:
(023) 8059 4787
Email:
A.Da-Ronch@soton.ac.uk

Dr Andrea Da Ronch 

Associate Professor, Director of the University Flight Simulator, Academic Integrity Officer

Dr Andrea Da Ronch's photo

I joined the Engineering and Physical Sciences at the University of Southampton, Southampton UK, in April 2013. As an Academic, I am fortunate to have the opportunity to work on interesting research projects, both nationally and internationally, and to teach students developing their skills and ambitions in engineering.

I have developed an outstanding profile in teaching and research forged by a number of unique multi-cultural experiences (BSc and MSc degrees in Italy, Double MSc degree in Sweden, PhD degree in UK), which mark my modus operandi.

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Education Contribution. I am committed to delivering high-quality Education for our students and to helping them find their ambitions and passions in Engineering. To this goal, I ensure: 1) access to up-to-date teaching and learning resources that I personally write for our students; 2) industrial input and participation in the Module delivery, either as an invited guest lecture or a multi-day workshop; and 3) enrich classical teaching through research and current real-world issues. I have been successful in this as evidenced by the students’ feedbacks on the 2 Modules I lead, a statistically relevant information as drawn from a large (170) and a small (15) cohort of students, and by nominations to “Outstanding Lecturer” at the Excellence in Teaching Awards 2014 and 2015.

Research interests

Summary of Current Research

The research team I lead focuses on multi-disciplinary computational aero-sciences driven by the technologies needed on next-generation aerospace systems. Research activities complement, without overlaps, work undertaken by other Members of the Department and the Faculty. At the extremes of the dimensionality spectrum, I investigate: 1) physics-based, high-fidelity computational models aimed at further improving our understanding of complex phenomena relevant to aerospace engineering; and 2) reduced-order models for applications requiring real-time simulation responses, such as optimisation and control.

Simulation of multi-disciplinary, multi-physics problems

  • Reliable use of Computational Fluid Dynamics has remained confined to a small region of the aircraft operating envelope due to the inability of current methods to predict turbulent/separated flows. To sustain further advances in Computational Fluid Dynamics, I investigate sources of model-based uncertainty in turbulence models and employ machine learning to improve turbulence models by assimilation of space- and time-accurate experimental data. I developed an open-source toolbox for Kriging-enhanced gradient that enables efficient and robust generation of surrogate models. The work is supported by the European Commission in the framework of the Horizon 2020 (HOMER Project, “Holistic Optical Metrology for Aero-Elastic Research”).
  • The sensitivity of the optimal aerodynamic shape to model parameters is critical for design robustness, yet this has received little or no attention to date. I investigate this problem using Computational Fluid Dynamics as source of the aerodynamic predictions. In addition to a strong sensitivity of the final shape to model parameters for transonic flows, I found the problem of the non-uniqueness of weak solutions of the Navier-Stokes equations for certain flows and geometries relevant to aerospace applications. This represents a virtually unexplored research area.
  • The performance of a wind turbine at typical operating conditions is assessed routinely. This is not the case for off-design conditions due to the complexities arising from modelling and computation. I investigate the performance degradation when the wind turbine operates in rainy conditions, and its sensitivity to realistic rainfall rates. Multi-phase simulations include the actual physical process of rain droplets forming a water layer over the blades by coupling the Lagrangian Discrete Phase Model and the Eulerian Volume of Fluid model.

Reduced order modelling for optimisation, control and real-time computing

  • Structural sizing requires accurate predictions of the critical loading cases. Loading cases at hundreds of flight points must be recomputed for different mass cases. For industrial aircraft design, the process takes several months. I support Airbus Operations Ltd. to create appropriate numerical approaches and computational tools to better address this challenge and to unify the aerodynamic and aeroelastic analyses at low- and high-speeds of flight.
  • High-fidelity aero-structural optimisation is limited to small changes around a reference aircraft configuration. The wing design is driven by the high-lift system, which has been discarded to date from the optimisation process. In cooperation with Airbus Operations Ltd. and Moog Inc., I develop a concurrent framework that extends the aero-structural optimisation to include physics-based prediction methods for the sizing of the high-lift system and the weight of the corresponding actuators. This enables wings to be optimised for a specific mission rather than a single flight point.
  • Turbulent solutions of the Navier-Stokes equations involve a deep hierarchy of coherent structures, with a wide range of spatio-temporal scales. The objective is to develop a framework, which is both model- and data-driven, to extract a compact, reduced representation of the flow dynamics. Sparsity features of the resulting model are maximised by appropriate machine learning algorithms that identify the relevant interactions between the hierarchy of fluid modes. The work is supported by the U.S. Air Force Office of Scientific Research (“l1-based sparsification of reduced order models of high Reynolds number turbulent flows”).
  • Next-generation aerospace systems call for disruptive technologies. To understand the challenges underlying these technologies, physics-based models are needed. The objective is to create a virtual aircraft design environment that enables: a) rapid exploration of the design space for configuration selection; b) uncertainties in sensor measurements and actuator performances to be accounted for; and c) pilot-in-the-loop to assist the flight control system design. The work is performed in cooperation with ONERA, The French Aerospace Centre, co-sponsoring the project.

Research Contribution

I have been successful in implementing a sustained research programme. I attracted research grants internationally from major research organisations in the UK (Royal Academy of Engineering - RAEng; Engineering and Physical Sciences Research Council - EPSRC), the EU (Horizon 2020 programme; Clean Sky Joint Undertaking – CS2; The French Aerospace Lab – ONERA) and the USA (Air Force Office of Scientific Research), and from Industry (Airbus Operations Ltd.; Noesis Solutions N.V.). I contribute to the University Impact Case Study of REF 2021 for the development of a novel computational fluid dynamics tool. The key innovation is the extreme efficiency and robustness of the aerodynamic analysis, reducing design cycle times for some components by 80 to 97%. This technology is currently implemented by Airbus Operations Ltd. into their existing design processes and applied across their product ranges (Tau flow solver, and Odilila suite).

Currently, I lead a team of 5 members, of which 4 PhD students, and I co-supervise 2 PhD students externally (one in Brazil and one in Italy). I have supervised 2 other PhD students who went on a successful career: one is a Research Associate at the University of Bristol (graduated in November 2019) and one is a Research Scientist at the French-German Research Institute of Saint-Louis (viva set for January 2020).

In the last 3 years, I have published over 20 international, peer-reviewed journals and edited a book published by Wiley-Blackwell. My work has attracted more than 1,000 citations, and I am the Corresponding Author of the Top 4 most cited journals in my portfolio. The quality of my research is exemplified by the awards that my team received. These include the Best Technical Paper Award at AIAA Aviation 2018 Forum and the Best MSc Thesis awarded by Politecnico of Turin in memory of Aldo Muggia.

 

Wing section in the University of Liverpool wind tunnel
Wind Tunnel wing section
Vortical flows around X-31 aircraft
Vortical flows around X-31 aircraft
Surface pressure coefficient distribution around a UAV configuration at high subsonic  speed
Surface pressure coefficient
Flow around the TCR tunnel model at α=18.0 deg and M=0.12 computed using the PMB code (k-ω turbulence model)
TCR wind tunnel model

Research group

Aerodynamics and Flight Mechanics

Affiliate research group

Airbus Noise Technology Centre

Research project(s)

Energy Harvesting for Active Aeroelastic Control

In addition to traditional control, the project will investigate the use of inverse simulation as a tool to bypass control system design.The objectives of the project are two-fold. The first is to investigate novel control strategies to control highly non-linear aero-servo-elastic systems by using the appropriate level of fidelity. The second objective is to investigate, design, test, and manufacture a mechanism to harvest energy from ambient sources and structural vibrations.

Evaluation of CFD Methods on Slender Missile Configurations

The project will focus on two configurations from the experimental database, both based on the same axisymmetric body with and without wings at M=2.5 and AoA=14. The project will look at different meshing strategies, numerical schemes and turbulence models.

Aspects of Reduced Order Modelling in Nonlinear Systems

The objective is the development and assessment of reduction techniques to drastically reduce the computational cost of simulations for engineering problems.

Impact of Aerodynamic and Structural Nonlinearities on Gust Loads Prediction

The objective is to provide a robust and efficient numerical framework for the aero-servo-elastic assessment of highly flexible aircraft which can be adopted to design next-generation aircraft.  This would allow to bridge the gap between present capabilities and those required to develop future aircraft concepts.

Influence of Aerodynamic Models on Flight Simulation

The work will be developed around the CEASIOM software which is a very extensive package for aircraft conceptual design. The objective of this project is to integrate, develop, and validate the aerodynamic module which is the core of the entire software.

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Since the 2013/2014 Academic Year when I joined the University, I have been Module Lead for Aircraft Structural Design SESA3026. In this role, I achieved consistently good student ratings (“Excellent lecturer. No more need to be said”; “He’s a great lecturer that really cares and goes the extra mile”) and 2 nominations for “Outstanding Lecturer”. I have also persuaded a Senior Airliner Pilot to get involved in the Module. This reflects the impact that my approach to Education and Training has on the external world, and provides students with a direct experience of aviation professionals.

Supported by the completion of PGCAP Module 1 and 2 in November 2014, I then went on contributing to the Aerospace Programme development by designing a new Module, Aeroelasticity SESA6077. This research-informed module builds upon my well-proved expertise in the area, and: 1) incorporates current research activities into teaching as part of examples and summative assessment; 2) has a strong industrial participation (Noesis Solutions N.V.MSC.Software) to support students developing the right skillsets needed in their future workplace; and 3) is used externally for Continuing Professional Development. Students praise for the teaching and learning resources (“his book was a valuable help throughout the course”) and methods (“[…] content of the coursework is good […] It makes you think about what we have learnt rather than just regurgitating information”) that were developed to promote deep learning.

My approach to Education extends beyond teaching: 1) I regularly engage in recruitment events (UCAS, Open Days) to make prospective students aware of the wide range of exciting jobs that are available across the broad spectrum of aerospace and aviation; 2) I provide guidance and support as Personal Academic Tutor to 14 UG and 4 PG students; and 3) to date, I have supervised over 30 Individual Projects and 3 Group Design Projects, some in collaboration with Industry (Cobham plc). These projects have a certain impact, as their design products are adopted for teaching and engagement activities in the following years.

July 2019

Aeronautics, Astronautics and Computational Engineering Department Award

June 2019

Best Technical Paper Award at AIAA Aviation 2018 Forum
Kharlamov, D., Drofelnik, J., Da Ronch, A., and Walker, S., “Rapid Load Calculations Using an Efficient Unsteady Aerodynamics Solver

May 2015

Award: "Excellence in Teaching Award", University of Southampton Students' Union

Nov 2014

Fellow of the Higher Education Academy

Sep 2014

Award: "La Penna Alpina per la Nostra Montagna", Associazione Nazionale Alpini di Feltre.

May 2014

Award: "Excellence in Teaching Award", University of Southampton Students' Union

Dec 2013

Grant: "Annual Adventures in Research Grant", University of Southampton

Dec 2012

Award: "Speciale Riconoscimento ai Ricercatori Bellunesi all'Estero", Rotary International

Aug 2010

Grant: "Aerospace Speakers Travel Grants", Royal Aeronautical Society

Oct 2008

Award: "T.I.M.E. Double Degree", Politecnico di Milano (Italy) & Royal Institute of Technology (Sweden) 

 

Dr Andrea Da Ronch
Southampton Boldrewood Innovation Campus
University of Southampton
Building 176
Burgess Road
Southampton
SO16 7QF

Room Number: 176/5049

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