Publications

A physics informed machine learning framework towards density prediction of additively manufactured components

Puthanveettil Madathil Abhilash, Bylya Olga, Sherlock Andrew

Key Engineering Materials Vol 1047, pp. 73-82 (2026)

https://doi.org/10.4028/p-vvwf5p

ESAFORM Benchmark 2025 : predicting stainless steel PBF-LB part density using statistical, data-driven, and physics-informed machine learning models derived from process parameters and in-situ monitoring data

Monu Medad Chiedozie C, McCarthy Eanna, Madathil Abhilash Puthanveettil, Chekotu Josiah C, Ilic Irina, Doğu Merve Nur, Hughes Cian, Juan Rongfei, Amini Ehsan, Lian Junhe, Vassiades Constantinos, Bylya Olga, Darosa Kim, Kromer Robin, Seidou Abdul Herrim, Mohanty Sankhya, Habraken Anne Marie, Mertens Anne, Laitinen Otto, Tucker Michael R, Brabazon Dermot

International Journal of Material Forming Vol 19 (2026)

https://doi.org/10.1007/s12289-026-01995-y

The ESAFORM benchmark 2023 : interlaboratory comparison benchmark for the characterization of microstructural grain growth and dynamic recrystallization kinetics of a single-phase Ni-base superalloy

Agirre Julen, Bernal Daniel, Flipon Baptiste, Bernacki Marc, Brüggemann Holger, Bailly David, Merklein Marion, Hagenah Hinnerk, Risse Jan Henning, Madej Łukasz, Muszka Krzysztof, Cichocki Kamil, Poloczek Łukasz, Bylya Olga, Reshetov Aleksey, De Micheli Pascal, Barlier Julien, Stark Andreas, Suhuddin Uceu F H, Staron Peter, Klusemann Benjamin, Galdos Lander

International Journal of Material Forming Vol 18 (2025)

https://doi.org/10.1007/s12289-025-01893-9

Establishing computer-based engineering analysis tools in existing civil engineering curriculum: a case study

Moghaddasi Hamed, Tarantino Alessandro, Bylja Olga, Krishnamurthy Bhaskaran, Bridget Bridget, Shirsath Ravindra

UK and Ireland Engineering Education Research
Network Annual Symposium (2024)

Benchmarking mean-field models available in commercial FE software in application to two-blow forging of IN718 alloy

Reshetov Aleksey, Bylya Olga

Material Forming - The 26th International ESAFORM Conference on Material Forming – ESAFORM 2023 26th International ESAFORM Conference on Material Forming, ESAFORM 2023 Materials Research Proceedings Vol 28, pp. 683-692 (2023)

https://doi.org/10.21741/9781644902479-74

Influence of mesh in modelling of flow forming process

Krishnamurthy Bhaskaran, Shitikov Andrei, Blackwell Paul, Bylya Olga

Materials Research Proceedings International ESAFORM Conference 2023, pp. 1583-1592 (2023)

https://doi.org/10.21741/9781644902479-171

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Professional Activities

Trust in AI for NDT: Mitigating Risks by Building in Knowledge

Contributor

27/8/2025

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Projects

D3M-CoLab 2

Sherlock, Andrew (Principal Investigator) Bylya, Olga (Researcher) Reshetov, Aleksey (Researcher) Wilson, David (Fellow) Puthanveettil Madathil, Abhilash (Researcher) Vassiades, Constantinos (Researcher) Azim, Safi Sohail (Researcher) Kasarapu, Satya (Researcher)

The D3M_CoLab2 project is exploring the potential of data science to solve real-world manufacturing problems and boost productivity by upskilling local engineers. Project allows companies to safely explore ideas to drive forward data-driven transformation within their businesses by enabling them to replicate their physical and digital infrastructure without impacting daily business operations.
The project aims to share knowledge, resources, and expertise in data-driven manufacturing, as well as providing training and education to equip the workforce with the necessary skills to leverage data-driven technologies.

01-Jan-2025 - 19-Jan-2026

CTA AI in Manufacturing Programme

Sherlock, Andrew (Principal Investigator) Reshetov, Aleksey (Principal Investigator) Wilson, David (Fellow) Bylya, Olga (Fellow)

The CTA programme seeks to target, identify, down select Canadian technology solutions providers specialising in Artificial Intelligence (AI) software and mentor those companies in how to market and deploy their software solutions within the UK manufacturing sector.
NMIS and appropriate sub-contractors will assist in this process ensuring that the chosen companies have appropriate maturity in their solutions and seek to provide engagements to manufacturing organisations across various sectors i.e. automative, aerospace, renewable energy and etc.

31-Jan-2024 - 21-Jan-2025

Incorporating ANSYS into the Undergraduate/Postgraduate curriculum of the Department of Civil and Environmental Engineering at the University of Strathclyde.

Moghaddasi Kelishomi, Hamed (Principal Investigator) Tarantino, Alessandro (Co-investigator) Bylya, Olga (Co-investigator)

The ANSYS programme will be used to enhance teaching and learning in various undergraduate (UG) and postgraduate (MEng/MSc) modules in the Department of Civil and Environmental Engineering (CEE). The ANSYS software is comprehensive FEA/CFD package that encompasses wide spectrum of physics, multiphysics simulations and extensive material database. The incorporation of ANSYS into educational programs can have a transformative impact on both students and the broader community, aligning with Strathclyde University’s strategic plan for 2025(Strathclyde Vision 2025).
Total Funding: $20k

01-Jan-2024 - 01-Jan-2025

Optimising the microstructure and mechanical properties of Titanium Alloys developed for aero engines and landing gears

Sivaswamy, Giribaskar (Principal Investigator) Bylya, Olga (Researcher) Reshetov, Aleksey (Researcher) Tamimi, Saeed (Researcher) Platts, Andrew (Researcher)

This project was part of the Core program, which is funded by CATAPULT jointly with AFRC Tier1 members.
In this project, efforts are made to identify processing window for manufacturing defect free components out of near-α (Ti-6242) and α+β (Ti-407, Ti-412, Ti-6246) alloys through hot forging route.

22-Jan-2023 - 15-Jan-2024

Data-driven Manufacturing Colab (D3M Colab project)

Sherlock, Andrew (Principal Investigator) Reshetov, Aleksey (Researcher) Wilson, David (Fellow) Bylya, Olga (Researcher) Puthanveettil Madathil, Abhilash (Researcher) Vassiades, Constantinos (Researcher) Azim, Safi Sohail (Researcher) Kasarapu, Satya (Researcher)

The project aims to share knowledge, resources, and expertise in data-driven manufacturing, as well as providing training and education to equip the workforce with the necessary skills to leverage data-driven technologies. Project partners include Babcock, BAE systems, Infor, and Anaconda. The project aims to bridge the gap between manufacturing and data science by growing a cohort of individuals, embedded in industry, who can apply data science to solve industrial problems and then supporting them to deploy solutions.

03-Jan-2023 - 31-Jan-2025

Experimental study of recovery effect in IN718 during two-blow forging trials

Reshetov, Aleksey (Project Lead) Bylya, Olga (Fellow)

This project was part of the Core program, which is funded by CATAPULT jointly with AFRC Tier1 members.
This project is devoted to two-blow forging trials of IN718 geometry on a hydraulic press at conditions tailored for studying the recovery effect.
Goal: to obtain experimental data for studying the effect of recovery in IN718 during multiple blow forging with intermediate reheating. It is assumed that the experimental data obtained will facilitate the improvement of both mean-field and full-field models by adding/improving recovery effects to them.

22-Jan-2023 - 12-Jan-2023

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