2024
Predicting product quality in continuous manufacturing processes using a scalable robust Gaussian Process approach (Journal article)
Echeverria-Rios, D., & Green, P. L. (2024). Predicting product quality in continuous manufacturing processes using a scalable robust Gaussian Process approach. Engineering Applications of Artificial Intelligence, 127, 107233. doi:10.1016/j.engappai.2023.107233DOI: 10.1016/j.engappai.2023.107233
2023
Jayasinghe, S., Paoletti, P., Jones, N., & Green, P. L. (n.d.). Predicting gas pores from photodiode measurements in laser powder bed fusion builds. Progress in Additive Manufacturing. doi:10.1007/s40964-023-00489-6DOI: 10.1007/s40964-023-00489-6
2022
Ensemble Kalman filter based sequential Monte Carlo sampler for sequential Bayesian inference (Journal article)
Wu, J., Wen, L., Green, P. L., Li, J., & Maskell, S. (2022). Ensemble Kalman filter based sequential Monte Carlo sampler for sequential Bayesian inference. STATISTICS AND COMPUTING, 32(1). doi:10.1007/s11222-021-10075-xDOI: 10.1007/s11222-021-10075-x
2021
Devlin, L., Horridge, P., Green, P., & Maskell, S. (n.d.). The No-U-Turn Sampler as a Proposal Distribution in a Sequential Monte Carlo Sampler with a Near-Optimal L-Kernel. arxiv.
Increasing the efficiency of Sequential Monte Carlo samplers through the use of approximately optimal L-kernels (Journal article)
Green, P., Devlin, L., Moore, R., Jackson, R., Li, J., & Maskell, S. (2021). Increasing the efficiency of Sequential Monte Carlo samplers through the use of approximately optimal L-kernels. Mechanical Systems and Signal Processing. doi:10.1016/j.ymssp.2021.108028DOI: 10.1016/j.ymssp.2021.108028
2020
Roberts, J. W., Sutcliffe, C. J., Green, P. L., & Black, K. (2020). Modelling of metallic particle binders for increased part density in binder jet printed components. ADDITIVE MANUFACTURING, 34. doi:10.1016/j.addma.2020.101244DOI: 10.1016/j.addma.2020.101244
Jackson, R. D., Jump, M., & Green, P. L. (2020). Predicting On-axis Rotorcraft Dynamic Responses Using Machine Learning Techniques. Journal of the American Helicopter Society, 65(3), 1-12. doi:10.4050/jahs.65.032004DOI: 10.4050/jahs.65.032004
Le Carrer, N., & Green, P. L. (2020). A possibilistic interpretation of ensemble forecasts: experiments on the imperfect Lorenz 96 system. Advances in Science and Research, 17, 39-45. doi:10.5194/asr-17-39-2020DOI: 10.5194/asr-17-39-2020
Automatic quality assessments of laser powder bed fusion builds from photodiode sensor measurements (Journal article)
Jayasinghe, S., Paoletti, P., Sutcliffe, C., Dardis, J., Jones, N., & Green, P. L. (2022). Automatic quality assessments of laser powder bed fusion builds from photodiode sensor measurements. PROGRESS IN ADDITIVE MANUFACTURING, 7(2), 143-160. doi:10.1007/s40964-021-00219-wDOI: 10.1007/s40964-021-00219-w
Optimising cargo loading and ship scheduling in tidal areas (Journal article)
Le Carrer, N., Ferson, S., & Green, P. L. (2020). Optimising cargo loading and ship scheduling in tidal areas. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 280(3), 1082-1094. doi:10.1016/j.ejor.2019.08.002DOI: 10.1016/j.ejor.2019.08.002
2019
Predicting On-Axis Rotorcraft Dynamic Responses Using Machine Learning Techniques (Journal article)
Jackson, R., Jump, M., & Green, P. (2019). Predicting On-Axis Rotorcraft Dynamic Responses Using Machine Learning Techniques. doi:10.20944/preprints201907.0348.v1DOI: 10.20944/preprints201907.0348.v1
Automatic Fault Detection for Selective Laser Melting using Semi-Supervised Machine Learning (Journal article)
Okaro, I., Jayasinghe, S., Sutcliffe, C., Black, K., Paoletti, P., & Green, P. (2019). Automatic Fault Detection for Selective Laser Melting using Semi-Supervised Machine Learning. Additive Manufacturing, 27, 42-53. doi:10.1016/j.addma.2019.01.006DOI: 10.1016/j.addma.2019.01.006
2018
Mendoza-Puchades, M., Green, P. L., & Judge, R. (2018). Variability in masonry behaviour and modelling under blast and seismic actions. PROCEEDINGS OF THE INSTITUTION OF CIVIL ENGINEERS-STRUCTURES AND BUILDINGS, 171(10), 768-777. doi:10.1680/jstbu.17.00088DOI: 10.1680/jstbu.17.00088
Green, P., Chodora, E., Zhu, Z., & Atamturktur, S. (2018). Towards the Validation of Dynamical Models in Regions where there is no Data. doi:10.20944/preprints201809.0389.v1DOI: 10.20944/preprints201809.0389.v1
Jackson, R., Jump, M., & Green, P. (2018). Towards Gaussian Process Models of Complex Rotorcraft Dynamics. In HS International’s 74th Annual Forum and Technology Display; The Future of Vertical Flight. Phoenix, Arizona, USA.
2017
Estimating the parameters of dynamical systems from Big Data using Sequential Monte Carlo samplers (Journal article)
Green, P. L., & Maskell, S. (2017). Estimating the parameters of dynamical systems from Big Data using Sequential Monte Carlo samplers. Mechanical Systems and Signal Processing, 93, 379-396. doi:10.1016/j.ymssp.2016.12.023DOI: 10.1016/j.ymssp.2016.12.023
Ahmed, T. M., Green, P. L., & Khalid, H. A. (2017). Predicting fatigue performance of hot mix asphalt using artificial neural networks. Road Materials and Pavement Design, 18(sup2), 141-154. doi:10.1080/14680629.2017.1306928DOI: 10.1080/14680629.2017.1306928
A machine learning approach to nonlinear modal analysis. (Journal article)
Worden, K., & Green, P. (2017). A machine learning approach to nonlinear modal analysis.. Mechanical Systems and Signal Processing, 84(Part B), 34-53. doi:10.1016/j.ymssp.2016.04.029DOI: 10.1016/j.ymssp.2016.04.029
2016
Scott, M., Green, P. L., O’Driscoll, D., Worden, K., & Sims, N. (2016). Sensitivity analysis of an Advanced Gas-cooled Reactor control rodmodel. Nuclear Engineering and Design.
Probabilistic modelling of a rotational energy harvester (Journal article)
Green, P. L., Hendijanizadeh, M., Simeone, L., & Elliott, S. J. (2016). Probabilistic modelling of a rotational energy harvester. JOURNAL OF INTELLIGENT MATERIAL SYSTEMS AND STRUCTURES, 27(4), 528-536. doi:10.1177/1045389X15573343DOI: 10.1177/1045389X15573343
Fast Bayesian identification of a class of elastic weakly nonlinear systems using backbone curves (Journal article)
Hill, T. L., Green, P. L., Cammarano, A., & Neild, S. A. (2016). Fast Bayesian identification of a class of elastic weakly nonlinear systems using backbone curves. JOURNAL OF SOUND AND VIBRATION, 360, 156-170. doi:10.1016/j.jsv.2015.09.007DOI: 10.1016/j.jsv.2015.09.007
2015
Green, P. L., & Worden, K. (2015). Bayesian and Markov chain Monte Carlo methods for identifying nonlinear systems in the presence of uncertainty. PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 373(2051). doi:10.1098/rsta.2014.0405DOI: 10.1098/rsta.2014.0405
Green, P. L. (2015). Bayesian system identification of dynamical systems using large sets of training data: A MCMC solution. PROBABILISTIC ENGINEERING MECHANICS, 42, 54-63. doi:10.1016/j.probengmech.2015.09.010DOI: 10.1016/j.probengmech.2015.09.010
Friction estimation in wind turbine blade bearings (Journal article)
Stevanović, N., Green, P. L., Worden, K., & Kirkegaard, P. H. (2016). Friction estimation in wind turbine blade bearings. Structural Control and Health Monitoring, 23(1), 103-122. doi:10.1002/stc.1752DOI: 10.1002/stc.1752
Green, P. L., Cross, E. J., & Worden, K. (2015). Bayesian system identification of dynamical systems using highly informative training data. Mechanical Systems and Signal Processing, 56-57, 109-122. doi:10.1016/j.ymssp.2014.10.003DOI: 10.1016/j.ymssp.2014.10.003
Green, P. L. (2015). Bayesian system identification of a nonlinear dynamical system using a novel variant of Simulated Annealing. Mechanical Systems and Signal Processing, 52-53(February 2019), 133-146. doi:10.1016/j.ymssp.2014.07.010DOI: 10.1016/j.ymssp.2014.07.010
2013
Green, P. L., Worden, K., & Sims, N. D. (2013). On the identification and modelling of friction in a randomly excited energy harvester. Journal of Sound and Vibration, 332(19), 4696-4708. doi:10.1016/j.jsv.2013.04.024DOI: 10.1016/j.jsv.2013.04.024
Green, P. L., Papatheou, E., & Sims, N. D. (2013). Energy harvesting from human motion and bridge vibrations: An evaluation of current nonlinear energy harvesting solutions. Journal of Intelligent Material Systems and Structures, 24(12), 1494-1505. doi:10.1177/1045389x12473379DOI: 10.1177/1045389x12473379
2012
Green, P. L., Worden, K., Atallah, K., & Sims, N. D. (2012). The effect of Duffing-type non-linearities and Coulomb damping on the response of an energy harvester to random excitations. Journal of Intelligent Material Systems and Structures, 23(18), 2039-2054. doi:10.1177/1045389x12446520DOI: 10.1177/1045389x12446520
Green, P. L., Worden, K., Atallah, K., & Sims, N. D. (2012). The benefits of Duffing-type nonlinearities and electrical optimisation of a mono-stable energy harvester under white Gaussian excitations. Journal of Sound and Vibration, 331(20), 4504-4517. doi:10.1016/j.jsv.2012.04.035DOI: 10.1016/j.jsv.2012.04.035
