Dr Robert Barthorpe
MEng, CEng, PhD
Department of Mechanical Engineering
Lecturer
r.j.barthorpe@sheffield.ac.uk
+44 114 222 7762
+44 114 222 7762
+44 114 222 7890
(Fax)
D213, Central Wing, Sir Frederick Mappin Building
Full contact details
Dr Robert Barthorpe
Department of Mechanical Engineering
D213, Central Wing
Sir Frederick Mappin Building
Mappin Street
Sheffield
S1 3JD
Department of Mechanical Engineering
D213, Central Wing
Sir Frederick Mappin Building
Mappin Street
Sheffield
S1 3JD
- Profile
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Rob is a Lecturer in the Department of Mechanical Engineering. He completed his MEng in Mechanical Engineering with German at the University of Sheffield in 2005 and his PhD in 2010. His research interests span dynamics, structural health monitoring and, more recently, energy applications.
- Research interests
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The underlying theme of Rob's research is the development of tools for integrating experimental and numerical data to overcome challenging engineering problems. This encompasses techniques for model validation, uncertainty quantification, machine learning, and optimal decision making under uncertainty.
His research has historically focused on application to a range of problems within structural dynamics, and particularly Structural Health Monitoring. Within SHM, this has included developing methods for overcoming the lack-of-data problem that acts as key barrier to wider adoption of machine learning based approaches to damage identification.
In recent years, his focus has moved to applications with the energy field, and in particular the role that distributed thermal and electrical energy storage may play as part of the transition to a low-carbon energy grid. This work has included the development of hierarchical control methodologies incorporating model predictive control, and evaluation of how they may be employed for optimal decision making over differing time horizons such that the potential of novel storage technologies may be fully exploited.
- Publications
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Books
- Topics in Model Validation and Uncertainty Quantification, Volume 4. Springer New York.
Journal articles
- Robust equation discovery considering model discrepancy: a sparse Bayesian and Gaussian process approach. Mechanical Systems and Signal Processing, 168. View this article in WRRO
- On risk-based active learning for structural health monitoring. Mechanical Systems and Signal Processing, 167, 108569-108569. View this article in WRRO
- On sensor optimisation for structural health monitoring robust to environmental variations. Wind Energy Science, 6(5), 1107-1116. View this article in WRRO
- Learning model discrepancy: A Gaussian process and sampling-based approach. Mechanical Systems and Signal Processing, 152. View this article in WRRO
- A probabilistic risk-based decision framework for structural health monitoring. Mechanical Systems and Signal Processing, 150. View this article in WRRO
- On Treed Gaussian Processes and piecewise-linear NARX modelling. Mechanical Systems and Signal Processing, 144. View this article in WRRO
- Emerging trends in optimal structural health monitoring system design: From sensor placement to system evaluation. Journal of Sensor and Actuator Networks, 9(3). View this article in WRRO
- Bayesian history matching for structural dynamics applications. Mechanical Systems and Signal Processing, 143. View this article in WRRO
- On digital twins, mirrors and virtualisations: Frameworks for model verification and validation. ASCE - ASME Journal of Risk and Uncertainty in Engineering Systems, Part B. Mechanical Engineering, 6(3). View this article in WRRO
- Digital twins: State-of-the-art future directions for modelling and simulation in engineering dynamics applications. ASCE - ASME Journal of Risk and Uncertainty in Engineering Systems, Part B. Mechanical Engineering, 6(3). View this article in WRRO
- A unifying framework for probabilistic validation metrics. Journal of Verification, Validation and Uncertainty Quantification, 4(3). View this article in WRRO
- Sparse Gaussian Process Emulators for surrogate design modelling. Applied Mechanics and Materials, 885, 18-31. View this article in WRRO
- On evolutionary system identification with applications to nonlinear benchmarks. Mechanical Systems and Signal Processing, 112, 194-232. View this article in WRRO
- On multi-site damage identification using single-site training data. Journal of Sound and Vibration, 409, 43-64. View this article in WRRO
- Robust methods for outlier detection and regression for SHM applications.. International Journal of Sustainable Materials and Structural Systems. View this article in WRRO
- N−1 modal interactions of a three-degree-of-freedom system with cubic elastic nonlinearities. Nonlinear Dynamics, 83(1-2), 497-511. View this article in WRRO
- Robust methods of inclusive outlier analysis for structural health monitoring. Journal of Sound and Vibration, 333(20), 5181-5195.
- An SHM view of a CFD model of Lillgrund wind farm. Applied Mechanics and Materials, 564, 164-169.
- The use of pseudo-faults for damage location in SHM: An experimental investigation on a Piper Tomahawk aircraft wing. Journal of Sound and Vibration, 333(3), 971-990. View this article in WRRO
- Machine learning applications for a wind turbine blade under continuous fatigue loading. Key Engineering Materials, 588, 166-174.
- On damage diagnosis for a wind turbine blade using pattern recognition. Journal of Sound and Vibration.
- Comparative study of robust novelty detection techniques. Key Engineering Materials, 569-570, 1109-1115.
- Advanced tools for damage detection in wind turbines. Key Engineering Materials, 569-570, 547-554.
- The use of pseudo-faults for novelty detection in SHM. J SOUND VIB, 329(12), 2349-2366.
- Vibration-based structural health monitoring using large sensor networks. SMART STRUCTURES AND SYSTEMS, 6(3), 335-347.
- Advanced feature selection for simplified pattern recognition within the damage identification framework. SHOCK AND VIBRATION, 17(4-5), 589-599.
- Feature extraction from spectral data using the bayesian evidence framework. Key Engineering Materials, 413-414, 151-158.
- Hierarchical verification and validation in a forward model-driven structural health monitoring strategy. Structural Health Monitoring.
- On improved fail-safe sensor distributions for a structural health monitoring system. Data-Centric Engineering.
Chapters
- On the Selection and Validation of Component Damage Models for Prediction of Damage-State Behavior of a Truss Bridge, Model Validation and Uncertainty Quantification, Volume 3 (pp. 181-188). Springer Nature Switzerland
- Structural Health Monitoring and Damage Identification, Handbook of Experimental Structural Dynamics (pp. 989-1061). Springer New York
- Structural Health Monitoring and Damage Identification, Handbook of Experimental Structural Dynamics (pp. 1-72). Springer New York
- Structural Health Monitoring and Damage Identification, Handbook of Experimental Structural Dynamics (pp. 1-72). Springer New York
- Sensor placement optimisation for structural health monitoring In Boller C, Chang F & Fujino YZ (Ed.), Encyclopedia of structural health monitoring (pp. 1239-1250). Chichester: Wiley.
Conference proceedings papers
- Hierarchical Model Verification and Validation for Structural Health Monitoring Using Dynamic Substructuring (pp 533-542)
- The role of features in a hierarchical modelling strategy for forward model-driven structural health monitoring. Proceedings of ISMA2022 including USD2022
- Assessment criteria for optimal sensor placement for a structural health monitoring system. Proceedings of the 13th International Workshop on Structural Health Monitoring 2021: Enabling Next-Generation SHM for Cyber-Physical Systems (pp 365-375). 439 North Duke Street, Lancaster, Pennsylvania, 17602, U.S.A.
- On robustness of optimal sensor placement to environmental variation for SHM. Proceedings of the 13th International Workshop on Structural Health Monitoring 2021: Enabling Next-Generation SHM for Cyber-Physical Systems (pp 977-987). 439 North Duke Street, Lancaster, Pennsylvania, 17602, U.S.A.
- On Predicting Uncertainties in the Dynamic Response of a Welded Structure (pp 45-57)
- A Forward Model Driven Structural Health Monitoring Paradigm: Damage Detection (pp 119-126)
- A risk-based active learning approach to inspection scheduling. International Conference on Structural Health Monitoring of Intelligent Infrastructure: Transferring Research into Practice, SHMII, Vol. 2021-June (pp 671-682) View this article in WRRO
- On health-state transition models for risk-based structural health monitoring. Dynamics of Civil Structures, Volume 2: Proceedings of the 39th IMAC, A Conference and Exposition on Structural Dynamics, 2021 (pp 49-60). Orlando, Florida, 8 February 2021 - 11 February 2021. View this article in WRRO
- Real-Time Digital Twin Updating Strategy Based on Structural Health Monitoring Systems (pp 55-64)
- Modelling of Guided Waves in a Composite Plate Through a Combination of Physical Knowledge and Regression Analysis (pp 109-114)
- An augmented risk-based paradigm for structural health monitoring. Dynamics of Civil Structures : Proceedings of the 38th IMAC, Vol. 2 (pp 201-212). Houston, Texas, 10 February 2020 - 13 February 2020. View this article in WRRO
- On decision-making for adaptive models combining physics and data. Proceedings of ISMA 2020 - International Conference on Noise and Vibration Engineering and USD 2020 - International Conference on Uncertainty in Structural Dynamics (pp 3623-3637). Virtual Conference, Leuven, Belgium, 7 September 2020 - 9 September 2020. View this article in WRRO
- On robust equation discovery: A sparse Bayesian and Gaussian process approach. Proceedings of ISMA 2020 - International Conference on Noise and Vibration Engineering and USD 2020 - International Conference on Uncertainty in Structural Dynamics (pp 3599-3610)
- A PROBABILISTIC APPROACH TOWARDS UNCERTAINTY QUANTIFICATION IN JOINED STRUCTURES. XI International Conference on Structural Dynamics, 23 November 2020 - 26 November 2020.
- Sequential Bayesian History Matching for Model Calibration. ASME 2019 Verification and Validation Symposium, 15 May 2019 - 17 May 2019. View this article in WRRO
- Learning of model discrepancy for structural dynamics applications using Bayesian history matching. Journal of Physics : Conference Series, Vol. 1264(1), 15 April 2019 - 17 April 2019. View this article in WRRO
- On digital twins, mirrors and virtualisations. Model Validation and Uncertainty Quantification, Volume 3, Vol. 3 (pp 285-295). Reno, NV, USA, 3 June 2019 - 6 June 2019. View this article in WRRO
- On key technologies for realising digital twins for structural dynamics applications. Model Validation and Uncertainty Quantification, Volume 3, Vol. 3 (pp 267-272). Reno, NV, USA, 3 June 2019 - 6 June 2019. View this article in WRRO
- Bayesian History Matching for Forward Model-Driven Structural Health Monitoring (pp 175-183)
- A probabilistic framework for forward model-driven SHM. Proceedings of the 9th European Workshop on Structural Health Monitoring (EWSHM 2018)(2018-11). Manchester, UK, 10 July 2018 - 13 July 2018. View this article in WRRO
- An Evaluation of Validation Metrics for Probabilistic Model Outputs. ASME 2018 Verification and Validation Symposium, 16 May 2018 - 18 May 2018.
- On NARX models using treed Gaussian processes. Proceedings of ISMA 2018 - International Conference on Noise and Vibration Engineering and USD 2018 - International Conference on Uncertainty in Structural Dynamics (pp 2775-2782)
- A multi-level uncertainty integration strategy for forward model-driven SHM. Proceedings of ISMA 2018 - International Conference on Noise and Vibration Engineering and USD 2018 - International Conference on Uncertainty in Structural Dynamics (pp 3681-3692) View this article in WRRO
- Experimental evaluation of environmental effects on a polymer-coated aluminium structure: A time-series analysis and pattern recognition approach. Proceedings of ISMA 2016 - International Conference on Noise and Vibration Engineering and USD2016 - International Conference on Uncertainty in Structural Dynamics (pp 3295-3307) View this article in WRRO
- Bayesian Inference and RJMCMC in Structural Dynamics: On Experimental Data (pp 23-36)
- Linear and Nonlinear System Identification Using Evolutionary Optimisation (pp 325-345)
- The development of a damage model for the use in machine learning driven SHM and comparison with conventional SHM Methods. Proceedings of ISMA 2016 - International Conference on Noise and Vibration Engineering and USD2016 - International Conference on Uncertainty in Structural Dynamics (pp 3333-3346) View this article in WRRO
- On the validation of nonlinear MDOF system models. Proceedings of ISMA 2016 - International Conference on Noise and Vibration Engineering and USD2016 - International Conference on Uncertainty in Structural Dynamics (pp 2785-2796)
- Nonlinear Modal Interaction Analysis for a Three Degree-of-Freedom System with Cubic Nonlinearities (pp 123-131)
- System Identification of an MDOF Experimental Structure with a View Towards Validation and Verification (pp 57-65)
- An Experimental Investigation of Feature Availability in Nominally Identical Structures for Population-Based SHM (pp 185-191)
- Bayesian parameter estimation and model selection of a nonlinear dynamical system using reversible jump Markov chain Monte Carlo. Proceedings of ISMA 2014 - International Conference on Noise and Vibration Engineering and USD 2014 - International Conference on Uncertainty in Structural Dynamics (pp 1253-1266) View this article in WRRO
- Bayesian System Identification of Dynamical Systems Using Reversible Jump Markov Chain Monte Carlo (pp 277-284) View this article in WRRO
- Aircraft parametric structural load monitoring using Gaussian process regression. 7th European Workshop on Structural Health Monitoring, EWSHM 2014 - 2nd European Conference of the Prognostics and Health Management (PHM) Society (pp 1933-1940)
- Towards an ontology for verification and validation in structural dynamics. Proceedings of ISMA 2014 - International Conference on Noise and Vibration Engineering and USD 2014 - International Conference on Uncertainty in Structural Dynamics (pp 1171-1178)
- Autoregressive Gaussian processes for structural damage detection. Proceedings of ISMA 2014 - International Conference on Noise and Vibration Engineering and USD 2014 - International Conference on Uncertainty in Structural Dynamics (pp 469-483)
- An experimental investigation of feature complexity and diversity in nominally similar test structures. Proceedings of ISMA 2014 - International Conference on Noise and Vibration Engineering and USD 2014 - International Conference on Uncertainty in Structural Dynamics (pp 4665-4674)
- An approach to fault detection using a unified linear Gaussian framework. Structural Health Monitoring 2013: A Roadmap to Intelligent Structures - Proceedings of the 9th International Workshop on Structural Health Monitoring, IWSHM 2013, Vol. 2 (pp 2752-2759)
- Auto-Association and Novelty Detection: Truths and Myths?. STRUCTURAL HEALTH MONITORING 2013, VOLS 1 AND 2 (pp 243-250)
- The effect of attenuation on the identification of impact damage in CFRP laminates. Proceedings of the 6th European Workshop - Structural Health Monitoring 2012, EWSHM 2012, Vol. 1 (pp 698-706)
- Impact damage detection for composite material typical of wind turbine blades using novelty detection. Proceedings of the 6th European Workshop - Structural Health Monitoring 2012, EWSHM 2012, Vol. 2 (pp 1287-1296)
- Novelty detection applied to vibration data from a CX-100 wind turbine blade under fatigue loading.. MODERN PRACTICE IN STRESS AND VIBRATION ANALYSIS 2012 (MPSVA 2012), Vol. 382
- Some recent developments in structural health monitoring. Key Engineering Materials, Vol. 518 (pp 298-318)
- Structural Health Monitoring of composite material typical of wind turbine blades by novelty detection on vibration response. Key Engineering Materials, Vol. 518 (pp 319-327)
- Damage detection in carbon composite material typical of wind turbine blades using auto-associative neural networks. Proceedings of SPIE - The International Society for Optical Engineering, Vol. 8348
- Identification of hysteretic systems using NARX models, part II: A Bayesian approach. Conference Proceedings of the Society for Experimental Mechanics Series, Vol. 4 (pp 57-65)
- Identification of hysteretic systems using NARX models, part I: Evolutionary identification. Conference Proceedings of the Society for Experimental Mechanics Series, Vol. 4 (pp 49-56)
- Multiple-site damage location using single-site training data. Conference Proceedings of the Society for Experimental Mechanics Series, Vol. 1 (pp 195-201)
- Bayesian sensitivity analysis of numerical models for structural health monitoring. Structural Health Monitoring 2011: Condition-Based Maintenance and Intelligent Structures - Proceedings of the 8th International Workshop on Structural Health Monitoring, Vol. 1 (pp 1300-1308)
- Classification of Multi-Site Damage using Support Vector Machines. 9th International Conference on Damage Assessment of Structures. Oxford, UK
- Damage location using added masses in a Piper Tomahawk aircraft wing. Proceedings of ISMA 2010: International Conference on Noise and Vibration Engineering. Leuven, Belgium
- Finite Element Model-based Feature Generation for Structural Health Monitoring. IMAC-XXVII: Conference & Exposition on Structural Dynamics. Orlando, FL
- Selecting Features for Damage Identification without Damaging the Structure. IWSHM2009, 7th International Workshop on Structural Engineering Dynamics. Stanford, CA
- Identification of robust damage-sensitive features for model-based structural health monitoring: an effect screening approach. USD2009 2nd International Conference on Uncertainty in Structural Dynamics. Sheffield, UK
- A comparative study of approaches to damage detection. XIX Congresso AIMETA. Ancona, Italy
- A forward approach to model-based structural health monitoring. ICEDyn 2009, International Conference on Structural Engineering Dynamics. Ericeira, Portugal
- An Investigation into the Necessary Model Fidelity for SHM Feature Selection. PROCEEDINGS OF THE FOURTH EUROPEAN WORKSHOP ON STRUCTURAL HEALTH MONITORING 2008 (pp 980-989)
- The Use of Pseudo-Faults for SHM Feature Selection and Pattern Recognition. PROCEEDINGS OF THE FOURTH EUROPEAN WORKSHOP ON STRUCTURAL HEALTH MONITORING 2008 (pp 1104-1112)
- Fault induction using added masses for structural damage identification. PROCEEDINGS OF ISMA 2008: INTERNATIONAL CONFERENCE ON NOISE AND VIBRATION ENGINEERING, VOLS. 1-8 (pp 3333-3344)
- On Current Trends in Forward Model-driven SHM. Structural Health Monitoring 2019, 24 October 2018 - 26 October 2018. View this article in WRRO
- Health Monitoring of Composite Structures by Combining Ultrasonic Wave Data. Structural Health Monitoring 2019, 24 October 2018 - 26 October 2018.
- Structural Health Monitoring: A Review of Uncertainty Quantification Methods in Wind Turbine Systems. Structural Health Monitoring 2019, 24 October 2018 - 26 October 2018.
- On an Application of Probabilistic Risk Assessment to Structural Health Monitoring. Structural Health Monitoring 2019, 24 October 2018 - 26 October 2018. View this article in WRRO
- A Simplified Treed Gaussian Process Approach to the Modelling of Bridge Data for Structural Health Monitoring. Structural Health Monitoring 2017, 12 September 2017 - 14 September 2017.
- Bayesian Calibration and Bias Correction for Forward Model-driven SHM. Structural Health Monitoring 2017, 12 September 2017 - 14 September 2017. View this article in WRRO
- EACS 2016 paper - QUANTIFICATION OF UNCERTAINTY FOR EXPERIMENTALLY OBTAINED MODAL PARAMETERS IN THE CREATION OF A ROBUST DAMAGE MODEL
- Multiple Damage Identification Using the Reversible Jump Markov Chain Monte Carlo. Structural Health Monitoring 2015
Other
- Preface. Conference Proceedings of the Society for Experimental Mechanics Series, v.
- Preface. Conference Proceedings of the Society for Experimental Mechanics Series, 3, v.
- Preface. Conference Proceedings of the Society for Experimental Mechanics Series, 3 Part F2, v.
- A report on the 6th European Conference on Structural Control. Structural Control and Health Monitoring, 24(1), e1970-e1970. View this article in WRRO
- Conference Proceedings of the Society for Experimental Mechanics Series: Preface. Conference Proceedings of the Society for Experimental Mechanics Series, 4.
Preprints
- On sensor optimisation for structural health monitoring robust to environmental variations, Copernicus GmbH. View this article in WRRO
- On risk-based active learning for structural health monitoring, arXiv.
- A probabilistic risk-based decision framework for structural health
monitoring, arXiv.
- Topics in Model Validation and Uncertainty Quantification, Volume 4. Springer New York.
- Grants
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Selected Grants:
- BEIS Net Zero Innovation Portfolio, ADSorB (Advanced Distributed Storage for grid Benefits), 2022-24, £2.59M (PI)
- Horizon 2020, DyVirt (Dynamic virtualisation: modelling performance of engineering structures), 2018-23, £556k (CoI)
- EPSRC, Structural Dynamics Laboratory for Verification and Validation (LVV) Across Scales and Environments, 2016-22, £4.15M (CoI)
- ERDF, Laboratory for Verification & Validation (LVV), 2017-19, £3.2M (CoI)
- EPSRC/Wellcome Trust, Doctoral Prize Fellowship, 2010-11, £40k (PI)
- Teaching activities
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Dr Barthorpe currently teaches MEC321 Control Engineering for Mechanical Engineers