| Prediction of blast loading in an internal environment using artificial neural networks AA Dennis, JJ Pannell, DJ Smyl, SE Rigby International Journal of Protective Structures 12 (3), 287-314, 2021 | 63 | 2021 |
| Physics-informed regularisation procedure in neural networks: An application in blast protection engineering JJ Pannell, SE Rigby, G Panoutsos International Journal of Protective Structures 13 (3), 555-578, 2022 | 48 | 2022 |
| Predicting specific impulse distributions for spherical explosives in the extreme near-field using a Gaussian function JJ Pannell, G Panoutsos, SB Cooke, DJ Pope, SE Rigby International Journal of Protective Structures 12 (4), 437-459, 2021 | 39 | 2021 |
| Application of transfer learning for the prediction of blast impulse JJ Pannell, SE Rigby, G Panoutsos International Journal of Protective Structures 14 (2), 242-262, 2023 | 34 | 2023 |
| Predicting near-field specific impulse distributions using machine learning JJ Pannell, SE Rigby, G Panoutsos, A Tyas, SB Cooke, DJ Pope 18th international symposium on interaction of the effects of munitions with …, 2019 | 13 | 2019 |
| Surrogate modelling strategies for the prediction of near-field blast impulse JJ Pannell University of Sheffield, 2022 | 4 | 2022 |
| Predicting specific impulse distributions for spherical explosives J Pannell, G Panoutsos, SB Cooke, DJ Pope, SE Rigby | 1 | 2024 |
| Near-field blast load predictions using machine learning S Rigby, J Pannell, G Panoutsos IAPS Newsletter 14, 2022 | | 2022 |
| A physics-guided machine learning approach to understanding loading distributions from explosive events J Pannell, S Rigby, G Panoutsos 22nd IStructE Young Researchers Conference, 2020 | | 2020 |
| Quantifying agglomeration productivity in long-term infrastructure planning H Arbabi, J Pannell, S Hincks, G Punzo Productivity Insights Network, 2020 | | 2020 |
Samuel E RigbyUniversity of SheffieldVerified email at sheffield.ac.uk
