Publications
Journal Articles
2022
On robust risk-based active-learning algorithms for enhanced decision support
A.J. Hughes, L.A. Bull, P. Gardner, N. Dervilis, and K. Worden
Mechanical Systems and Signal Processing, vol. 181, pp. 109502, July 2022
DOI:
10.1016/j.ymssp.2022.109502
On statistic alignment for domain adaptation in structural health monitoring
J. Poole, P. Gardner, N. Dervilis, L.A. Bull, and K. Worden
Structural Health Monitoring, July 2022
DOI:
10.1177/14759217221110441
Domain‑adapted Gaussian mixture models for population‑based structural health monitoring
P. Gardner, L.A. Bull, N. Dervilis, and K. Worden
Journal of Civil Structural Health Monitoring, March 2022
DOI:
10.1007/s13349-022-00565-5
[Code]
A population-based SHM methodology for heterogeneous structures: Transferring damage localisation knowledge between different aircraft wings
P. Gardner, L.A. Bull, J. Gosliga, J. Poole, N. Dervilis, and K. Worden
Mechanical Systems and Signal Processing, vol. 172, pp.108918, June 2022
DOI:
10.1016/j.ymssp.2022.108918
[Code]
Robust equation discovery considering model discrepancy: A sparse Bayesian and Gaussian process approach
Y.-C. Zhu, P. Gardner, D.J. Wagg, R.J. Barthorpe, E.J. Cross, and R. Fuentes
Mechanical Systems and Signal Processing, vol. 168, pp.108717, April 2022
DOI:
10.1016/j.ymssp.2021.108717
Bayesian modelling of multivalued power curves from an operational wind farm
L.A. Bull, P. Gardner, T.J. Rogers, N. Dervilis, E.J. Cross, E. Papatheou, A.E. Maguire, C. Campos and K. Worden
Mechanical Systems and Signal Processing, pp.108530, 2022
DOI:
10.1016/j.ymssp.2021.108530
On risk-based active learning for structural health monitoring
A.J. Hughes, L.A. Bull, P. Gardner, R.J. Barthorpe, N. Dervilis, and K. Worden
Mechanical Systems and Signal Processing, vol. 167b, pp.108569, March 2022
DOI:
10.1016/j.ymssp.2021.108569
On the application of kernelised Bayesian transfer learning to population-based structural health monitoring
P. Gardner, L.A. Bull, N. Dervilis, and K. Worden
Mechanical Systems and Signal Processing, vol. 167b, pp.108519, March 2022
DOI:
10.1016/j.ymssp.2021.108519
[Code]
2021
Overcoming the problem of repair in structural health monitoring: Metric-informed transfer learning
P. Gardner, L.A. Bull, N. Dervilis, and K. Worden
Journal of Sound and Vibration, vol. 510, pp.116245, October 2021
DOI:
10.1016/j.jsv.2021.116245
[Code]
On the transfer of damage detectors between structures: An experimental case study
L.A. Bull, P. Gardner, N. Dervilis, E. Paptheou, M. Haywood-Alexander, R.S. Mills and K. Worden
Journal of Sound and Vibration, vol. 501, pp.116072, June 2021
DOI:
10.1016/j.jsv.2021.116072
Equation discovery for nonlinear dynamical systems: A Bayesian viewpoint
R. Fuentes, R. Nayek, P. Gardner, N. Dervilis, T.J. Rogers, K. Worden and E.J. Cross
Mechanical Systems and Signal Processing, vol. 154, pp.107528, June 2021
DOI:
10.1016/j.ymssp.2020.107528
Learning model discrepancy: A Gaussian process and sampling-based approach
P. Gardner, T.J. Rogers, C. Lord and R.J. Barthorpe
Mechanical Systems and Signal Processing, vol. 152, pp.107381, May 2021
DOI:
10.1016/j.ymssp.2020.107381
Probabilistic inference for structural health monitoring: new modes of learning from data
L.A. Bull, P. Gardner, T.J. Rogers, E.J. Cross, N. Dervilis and K. Worden
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, vol. 7, pp.03120003, March 2021
DOI:
10.1061/AJRUA6.0001106
Foundations of population-based SHM, Part I: Homogeneous populations and forms
L.A. Bull, P. Gardner, J. Gosliga, T.J. Rogers, N. Dervilis, E.J. Cross, E. Papatheou, A.E. Magiure, C. Campos, and K. Worden
Mechanical Systems and Signal Processing, vol. 148, pp.107141, Feb 2021
DOI:
10.1016/j.ymssp.2020.107141
Foundations of population-based SHM, Part II: Heterogenous populations - Graphs, networks, and communities
J. Gosliga, P. Gardner, L.A. Bull, N. Dervilis, and K. Worden
Mechanical Systems and Signal Processing, vol. 148, pp.107144, Feb 2021
DOI:
10.1016/j.ymssp.2020.107144
Foundations of population-based SHM, Part III: Heterogenous populations - Mapping and transfer
P. Gardner, L.A. Bull, J. Gosliga, N. Dervilis, and K. Worden
Mechanical Systems and Signal Processing, vol. 149, pp.107142, Feb 2021
DOI:
10.1016/j.ymssp.2020.107142
2020
Autonomous ultrasonic inspection using Bayesian optimisation and robust outlier analysis
R. Fuentes, P. Gardner, C. Mineo, T.J. Rogers, S.G. Pierce, K. Worden, N. Dervilis and E.J. Cross
Mechanical Systems and Signal Processing, vol. 145, pp.106897, November-December 2020
DOI:
10.1016/j.ymssp.2020.106897
Bayesian history matching for structural dynamics appliciations
P. Gardner, C. Lord and R.J. Barthorpe
Mechanical Systems and Signal Processing, vol. 143, pp.106828, September 2020
DOI:
10.1016/j.ymssp.2020.106828
Machine learning at the interface of structural health monitoring and non-destructive evaluation
P. Gardner, R. Fuentes, N. Dervilis, C. Mineo, S.G. Pierce, E.J. Cross and K. Worden
Philosophical transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, vol. 378, pp.20190581, September 2020
DOI:
10.1098/rsta.2019.0581
Towards the development of an operational Digital Twin
P. Gardner, M. Dal Borgo, V. Ruffini, A.J. Hughes, Y. Zhu and D.J. Wagg
Vibration, vol. 3, pp.235-265, September 2020
DOI:
10.3390/vibration3030018
A brief introduction to recent developments in population-based structural health monitoring
K. Worden, L.A. Bull, P. Gardner, J. Gosliga, T.J. Rogers, E.J. Cross, E. Paptheou, W. Lin and N. Dervilis
Frontiers in Built Environment, vol. 6, pp.146, September 2020
DOI:
10.3389/fbuil.2020.00146
Digital twins: State-of-the-art and future directions for modeling and simulation in engineering dynamics applications
D.J. Wagg, K. Worden, R.J. Barthorpe and P. Gardner
ASCE-ASME Jounral of Risk and Uncertainty in Engineering Systems, Part B: Mechancial Engineering, vol. 6, pp.030901, May 2020
DOI:
10.1115/1.4046739
On Digital Twins, mirrors, and virtualizations: Frameworks for model verification and validation
K. Worden, E.J. Cross, R.J. Barthorpe, D.J. Wagg and P. Gardner
ASCE-ASME Jounral of Risk and Uncertainty in Engineering Systems, Part B: Mechancial Engineering, vol. 6, pp.030902, May 2020
DOI:
10.1115/1.4046740
On the application of domain adaptation in structural health monitoring
P. Gardner, X. Liu, and K. Worden
Mechanical Systems and Signal Processing, vol. 138, pp.106550, April 2020
DOI:
10.1016/j.ymssp.2019.106550
Probabilistic modelling of wind turbine power curves with application of heteroscedastic Gaussian process regression
T.J. Rogers, P. Gardner, N. Dervilis, K. Worden, A.E. Maguire E. Papatheou and E.J. Cross
Renewable Energy, vol. 148, pp.1124-1136, April 2020
DOI:
10.1016/j.renene.2019.09.145
2019
A unifying framework for probabilistic validation metrics
P. Gardner, C. Lord and R.J. Barthorpe
Journal of Verification, Validation and Uncertainty Quantification, vol. 4, pp.031005, November 2019
DOI:
10.1115/1.4045296
2018
Sparse Gaussian process emulators for surrogate design modelling
P. Gardner, T.J. Rogers, C. Lord and R.J. Barthorpe
Applied Mechanics and Materials, vol. 885, pp.18-31, November 2018
DOI:
10.4028/www.scientific.net/AMM.885.18
Book Chapters
2021
Population-based structural health monitoring
P. Gardner, L.A. Bull, J. Gosliga, N. Dervilis, E.J. Cross, E. Papatheou and K. Worden
in the Structural health monitoring based on data science techniques, 2021, Springer, pp.413-435
DOI:
10.1007/978-3-030-81716-9_20
Partially supervised learning for data-driven structural health monitoring
L.A. Bull, A.J. Hughes, T.J. Rogers, P. Gardner, K. Worden and N. Dervilis
in the Structural health monitoring based on data science techniques, 2021, Springer, pp.389-411
DOI:
10.1007/978-3-030-81716-9_19
2020
Structural health monitoring and damage identificaiton
R. Fuentes, E.J. Cross, P. Gardner, L.A. Bull, T.J. Rogers, R.J. Barthorpe, H. Shi, N. Dervilis, C.R. Farrar and K. Worden
in the Handbook of Experimental Structural Dynamics, 2020, Springer New York
DOI:
10.1007/978-1-4939-6503-8_23-1
Thesis
On novel approaches to model-based structural health monitoring
P. Gardner
University of Sheffield
etheses.whiterose.ac.uk/23376