Dr Rob 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 Rob 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
-
Rob Barthorpe is a lecturer in the Dynamics Research Group in the Department of Mechanical Engineering. He has a first degree in Mechanical Engineering with a Modern Language from the University of Sheffield and was awarded his PhD from the same university in 2010.
Rob's research is in the areas of structural health monitoring, uncertainty analysis and the verification and validation of numerical models.
- Research interests
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Dr Barthorpe's research covers a range of problems in the field of structural dynamics and beyond, with an underlying theme being the integration of numerical modelling and experimental data. Structural health monitoring is one of his major research themes. The broad aim of an SHM system is to be able to identify, at an early stage, occurrences of damage that may ultimately lead to the failure of the component or system being monitored.
Established approaches to this task typically fall into one of two categories: they are either based entirely on experimental data, or make use of a numerical model that is periodically updated as new data becomes available. Both of these approaches have distinct drawbacks: for the former, lack of appropriate experimental data is the major issue; for the latter, model-form uncertainty is among the challenges faced.
Part of Rob's work is in investigating ways to circumvent the lack of data problem through novel experimental and data-modelling techniques. A larger part is in developing new methods for integrating experimental and numerical methods, such that uncertainty in both the experimental measurements and the numerical model may be accounted for.
These methods are being developed for application to aerospace structures, wind turbines and civil infrastructure. However, the domain of applicability is much broader as the issues of handling uncertainty, solving inverse problems and overcoming test-model discrepancy are pervasive in many branches of science and engineering.
Applications being investigated include the energy performance of buildings and the modelling of human bones.
- Publications
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Books
- Topics in Model Validation and Uncertainty Quantification, Volume 4. Springer New York.
Journal articles
- Learning model discrepancy: A Gaussian process and sampling-based approach. Mechanical Systems and Signal Processing, 152, 107381-107381.
- A probabilistic risk-based decision framework for structural health monitoring. Mechanical Systems and Signal Processing, 150, 107339-107339.
- 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. 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. 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
- A report on the 6th European Conference on Structural Control. Structural Control and Health Monitoring, 24(1), e1970-e1970. 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.
- 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
- An SHM view of a CFD model of Lillgrund wind farm. Applied Mechanics and Materials, 564, 164-169.
- 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.
- Advanced tools for damage detection in wind turbines. Key Engineering Materials, 569-570, 547-554.
- Comparative study of robust novelty detection techniques. Key Engineering Materials, 569-570, 1109-1115.
- 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.
- 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.
Chapters
- Modelling of Guided Waves in a Composite Plate Through a Combination of Physical Knowledge and Regression Analysis, Rotating Machinery, Optical Methods & Scanning LDV Methods, Volume 6 (pp. 109-114). Springer International Publishing
- Bayesian History Matching for Forward Model-Driven Structural Health Monitoring, Model Validation and Uncertainty Quantification, Volume 3 (pp. 175-183). Springer International Publishing
- 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
- An Augmented Risk-Based Paradigm for Structural Health Monitoring (pp 201-212)
- A PROBABILISTIC APPROACH TOWARDS UNCERTAINTY QUANTIFICATION IN JOINED STRUCTURES. XI International Conference on Structural Dynamics, 23 November 2020 - 26 November 2020.
- Preface. Conference Proceedings of the Society for Experimental Mechanics Series (pp v)
- 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 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
- 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
- Preface. Conference Proceedings of the Society for Experimental Mechanics Series, Vol. 3 (pp v)
- 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
- 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
- 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)
- Preface. Conference Proceedings of the Society for Experimental Mechanics Series, Vol. 3 Part F2 (pp v)
- 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)
- 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
- Bayesian Inference and RJMCMC in Structural Dynamics: On Experimental Data (pp 23-36)
- Linear and Nonlinear System Identification Using Evolutionary Optimisation (pp 325-345)
- Nonlinear Modal Interaction Analysis for a Three Degree-of-Freedom System with Cubic Nonlinearities (pp 123-131)
- 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
- 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)
- 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)
- 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)
- 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)
- 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)
- 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 I: Evolutionary identification. Conference Proceedings of the Society for Experimental Mechanics Series, Vol. 4 (pp 49-56)
- 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
- Multiple-site damage location using single-site training data. Conference Proceedings of the Society for Experimental Mechanics Series, Vol. 1 (pp 195-201)
- Damage location using added masses in a Piper Tomahawk aircraft wing. Proceedings of ISMA 2010: International Conference on Noise and Vibration Engineering. Leuven, Belgium
- A comparative study of approaches to damage detection. XIX Congresso AIMETA. Ancona, Italy
- Selecting Features for Damage Identification without Damaging the Structure. IWSHM2009, 7th International Workshop on Structural Engineering Dynamics. Stanford, CA
- Finite Element Model-based Feature Generation for Structural Health Monitoring. IMAC-XXVII: Conference & Exposition on Structural Dynamics. Orlando, FL
- 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 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)
- 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)
- 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)
- 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.
- EACS 2016 paper - QUANTIFICATION OF UNCERTAINTY FOR EXPERIMENTALLY OBTAINED MODAL PARAMETERS IN THE CREATION OF A ROBUST DAMAGE MODEL
- 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
- Multiple Damage Identification Using the Reversible Jump Markov Chain Monte Carlo. Structural Health Monitoring 2015
Other
- Conference Proceedings of the Society for Experimental Mechanics Series: Preface. Conference Proceedings of the Society for Experimental Mechanics Series, 4.
- Topics in Model Validation and Uncertainty Quantification, Volume 4. Springer New York.
- Grants
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ESPRC/Wellcome Trust fellowship, 2010-11, £44k (PI)
- Teaching interests
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Dr Barthorpe currently teaches Signal Processing and Instrumentation (MEC409) to fourth year undergraduates and MSc students.