Donato Laura

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LinkedIn: www.linkedin.com/in/laura-donato-3676bb159

Researchgate: https://www.researchgate.net/profile/Laura-Donato-2

Joint Ph.D. in Sciences de l'ingénieur et technologie at Université Libre de Bruxelles and in Industrial Engineering at University of Pisa

Title of the PhD Project: Data-driven analysis and modelling of turbulent reactive flows

Supervisor(s): Prof. Alessandro PARENTE, Prof. Chiara GALLETTI

Abstract of the PhD project: The EU Climate Action asks for a 55% reduction of greenhouse gas emissions by 2030 with respect to 1990 levels to reach a carbon-neutral society by 2050. To meet these requirements, renewable energies will play a key role toward the decarbonisation process for energy efficiency and fuel flexibility, while limiting pollutants emissions. However, all scenarios foresee that combustion will still account for a large share of energy production, especially in those industrial sectors which require a high amount of energy and are thus more difficult to electrify. It is therefore necessary to develop new combustion technologies to ensure a clean environment. In this regard, Moderate or Intense Low-oxygen Dilution (MILD) combustion represents an interesting technology, since it can combine very high combustion efficiency with fuel flexibility, and low formation of pollutants. So, there is a need to better understand combustion systems for technological advancement. In this perspective, Computational Fluid Dynamics (CFD) tools are essential to design and optimize these processes, but they have a high computational cost, which has driven the research community to the analysis of low computational and multi-fidelity alternatives, i.e. physics-based, reduced-order models, and data-driven models. However, numerical models can be affected by uncertainties, which drift them from reality. In this context, data assimilation (DA) provides a promising step in optimizing numerical model predictions considering experimental data and their uncertainties. Data assimilation is a set of mathematical techniques in which observations and a numerical model are combined to generate more accurate predictions and provide an optimized estimate of the system’s state compared to the one that could be obtained using the data or the model alone.

The current Ph.D. program aims at establishing a novel, automatic DA framework by coupling different numerical models and experimental data, which can be employed for the design of new combustion systems, in order to improve the effectiveness and accuracy of the numerical predictions. As a result, a reliable, physics-based and time-effective tool, suited for combustion monitoring and real-time optimization and control will be provided. Thanks to the DA framework we will be able to reduce uncertainties in numerical predictions, determine unknown model parameters through a learning method, and develop a self-learning model. The DA scheme will integrate results from combustion experiments and predictions of three types of numerical models: physics-based (white-box), data-driven (black-box), and hybrid (theory-guided data science). In this way, we will produce a unique and generalized frame that will learn from any data set and provide more reliable predictions for realistic combustion processes.

Publications

• Antognoli M., Donato L., Galletti C., Stocklein D., Di Carlo D., Brunazzi E. ‘’Pre-arranged sequences of micropillars for passive mixing control of water and ethanol’’. Chemical Engineering Journal, April 2023.
• Procacci A., Donato L., Amaduzzi R., Coussement A., Galletti C., Parente A. ‘’Parameter estimation using a gpr-based rom and sparse sensing: application to a methane/air lifted jet flame’’. Flow, Turbulence and Combustion, June 2023.
• Donato L., Galletti C., Parente A. ‘’Self-updating digital twin of a hydrogen-powered furnace using data assimilation’’. Applied Thermal Engineering, August 2023.
• Lubrano Lavadera M., Kamal M. M, Sharma S., Donato L., Coussement A., Galletti C., A. Parente A. ‘’A combined experimental, numerical and data consistency approach for the characterization of temperature distribution in a MILD combustion furnace’’.  Applied Thermal Engineering, September 2023.
• Donato L., Kamal M. M., Procacci A., Cafiero M., Sharma S., Galletti C., Coussement A., Parente A. Integrating Data Assimilation and Sparse Sensing for Updating Digital Twins of a Semi-industrial Furnace. Submitted to Proceedings of the Combustion Institute, 2024.

ORCID ID: https://orcid.org/0000-0002-4172-5804

Conferences

• 18^th International Conference on Numerical Combustion, San Diego, United States of America, May 8^th-11^th, 2022. Donato L., Procacci A., Coussement A., Galletti C., Parente A. ‘’Adjusted sparse sensing-based digital twins of combustion systems via data assimilation’’ (oral presentation).
• 44^th Meeting of the Italian Section of the Combustion Institute, Naples, Italy, June 5^th-8^th, 2022. Donato L., Galletti C., Parente A. ‘’Self-updating digital twin of a semi-industrial furnace via data assimilation approach’’ (oral presentation).
• 2^nd International Workshop on MILD Combustion: modelling challenges, experimental configurations and diagnostic tools, Naples, Italy, June 8^th-9^th, 2022 (oral presentation).
• 12^th Mediterranean Combustion Symposium (MCS-12), Luxor, Egypt, 23^rd-26^th January 2023. Procacci A., Donato L., Amaduzzi R., Coussement A., Galletti C., Parente A. ‘’Parameter estimation using a gpr-based rom and Sparse sensing: application to a methane/air lifted Jet flame’’.
• 11^th European Combustion Meeting (ECM 2023), Rouen, France, 26-28^th April 2023. Donato L., Parente A., Mariotti A., Salvetti M. V., and Galletti C. ‘’Quantification of the uncertainty due to combustion model for the digital twin of a semi-industrial furnace’’ (poster session).
• Joint Meeting of the Belgian and Italian Sections of The Combustion Institute (45^th Meeting of the Italian Section of the Combustion Institute), Florence, Italy, May 28^th-31^st, 2023.

• Donato L., Procacci A., Coussement A., Galletti C., Parente A. ‘’Self-learning Digital Twin of a combustion furnace through the Kalman Filter method’’ (oral presentation);
• Lubrano Lavadera , Kamal M. M, Sharma S., Donato L., Bellacima G., Coussement A., Galletti C., A. Parente A. ‘’A combined experimental and numerical approach for the characterization of temperature distribution in a MILD combustion furnace’’ (poster session).

• 1^st Italian Workshop on Ammonia Energy, Florence, 31^st May, 2023.
• 2^nd Symposium on Ammonia Energy, Orléans, France, 11-13^th July 2023.
• 1^st Workshop on Machine Learning for Fluid Dynamics, Sorbonne University, Paris, France, 6^th – 8^th March 2024. Donato L., Kamal M. M., Procacci A., Cafiero M., Sharma S., Galletti C., Coussement A., Parente A. “Data Assimilation for Updating a Numerical Model of a semi-industrial furnace’’.
• 27th “JOURNEES D’ETUDES” of the Belgian Section of the Combustion Institute, Université libre de Bruxelles, Brussels, Belgium, April 3-5, 2024. Donato L., Kamal M. M., Procacci A., Cafiero M., Sharma S., Galletti C., Coussement A., Parente A. “Data Assimilation for Updating a Numerical Model of a semi-industrial furnace’’.
• Cost Action, 1st General Cypher Meeting, Ljubljana, Slovenia, 10-12th April 2024. Donato L., Kamal M. M., Procacci A., Cafiero M., Sharma S., Galletti C., Coussement A., Parente A. “Data Assimilation for Updating a Numerical Model of a semi-industrial furnace’’ (Poster session).

Courses attended 

• “Introduction to uncertainty quantification and stochastic sensitivity analysis” held by Prof. Alessandro Mariotti. Start of the course: January 2021. End of the course: February 2021 (12 h). Online.
• Italian GRICU PhD School 2021 | ‘’Digitalization Tools for the Chemical and Process Industries’’. Start of the course: 11^th March 2021. End of the course: 19^th March 2021 (16 h). Online.
• “Heat transfer and combustion” held by Prof. Alessandro Parente. Start of the course: March 2021. End of the course: May 2021 (30 h). Online.
• “Turbulent combustion” held by Von Karman Institute. Start of the course: 17^th May 2021. End of the course: 21^st May 2021 (26 h). Online.
• “Neural Networks and Deep Learning” held by Prof. Beatrice Lazzerini. Start of the course: June 2021. End of the course: July 2021 (11 h). Online.
• ERCOFTAC/JMBC Combustion Winter School: ‘’Towards carbon-neutral combustion systems’’. Start of the course: 31^st January 2022. End of the course: 4^th February 2022 (26h). University of Technology, Eindhoven, The Netherlands.
• Italian GRICU PhD School 2022 | ‘’Catalysis and Catalytic Reaction Engineering, Electrochemical Energy Conversion and Storage: from thermodynamics and kinetics to devices’’. Start of the course: 6^th July 2022. End of the course: 9^th July 2022 (21 h). Ischia, Italy.
• ‘’Introduction to Python Programming’’ held by Cineca Academy. Start of the course: 5^th October 2022. End of the course: 7^th October 2022 (18 h). Online.
• ‘’Understanding and Predicting Hydrogen Combustion’’, Barcelona Supercomputing Center. Start of the course: 30^th November 2022. End of the course: 2^nd December 2022. Barcelona Supercomputing Center, Barcelona, Spain.

Awards

Best oral presentation at the 44^th Meeting of the Italian Section of the Combustion Institute, Naples, Italy, June 5^th-8^th, 2022. Donato L., Galletti C., Parente A. ‘’Self-updating digital twin of a semi-industrial furnace via data assimilation approach’’

Support to master thesis students in Chemical Engineering

Candidate: Giorgia Bellacima. Start of the support activity: June 2022. Thesis title: “A combined experimental/numerical approach for the characterization of temperature distribution in sustainable combustion technologies”.

Support to ULB students

Candidate: a team of ULB students attending master’s degree of science in Electromechanical Engineering. Start of the support activity: April 2022. End of the support activity: June 2022. Support for the project related to Prof. Parente’s course ‘’Heat Transfer and combustion’’.

Candidate: a team of ULB students attending master’s degree of science in Electromechanical Engineering. Start of the support activity: April 2024. End of the support activity: June 2024. Support for the project related to Prof. Parente’s course ‘’Heat Transfer and combustion’’.

Reviewing activities

Reviewing scientific article submitted for publication in Applied Thermal Engineering.