Edoardo Patelli

Search results

• 2021

  Robust data-driven human reliability analysis using credal networks

  Morais, C., Estrada-Lugo, H. D., Tolo, S., Jacques, T., Moura, R., Beer, M. & Patelli, E., 15 Oct 2021, (E-pub ahead of print) In: Reliability Engineering and System Safety. 107990.

  Research output: Contribution to journal › Article › peer-review

  • Reliability analysis 100%
  • Floating production storage and offloading 42%
  • Human engineering 34%
  • Bayesian networks 33%
  • Accidents 26%

• Sampling methods for solving Bayesian model updating problems: A tutorial

  Lye, A., Cicirello, A. & Patelli, E., 31 Oct 2021, In: Mechanical Systems and Signal Processing. 159, 43 p., 107760.

  Research output: Contribution to journal › Article › peer-review

  • Sampling 100%
  • Markov chains 69%
  • Monte Carlo methods 38%
  • Numerical methods 31%
  • Identification (control systems) 31%
  2 Citations (Scopus)

• Uncertainty propagation in SINBAD fusion benchmarks with total Monte Carlo and imprecise probabilities

  Gray, A., Davis, A. & Patelli, E., 4 Aug 2021, (E-pub ahead of print) In: Fusion Science and Technology. 11 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Neutron 100%
  • fusion 79%
  • Fusion reactions 78%
  • Simulation 62%
  • Isotopes 60%
• 2020

  Analytic probabilistic safety analysis under severe uncertainty

  Sadeghi, J., de Angelis, M. & Patelli, E., 31 Mar 2020, In: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering. 6, 1, 9 p., 04019019.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Engineers 37%
  3 Citations (Scopus)

  8 Downloads (Pure)

• An efficient approach for computing analytical non-parametric fragility curves

  Altieri, D. & Patelli, E., 31 Jul 2020, In: Structural Safety. 85, 12 p., 101956.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Earthquake engineering 100%
  • Earthquakes 67%
  • Polynomials 60%
  • Costs 29%
  1 Citation (Scopus)

  8 Downloads (Pure)

• A post-contingency power flow emulator for generalized probabilistic risks assessment of power grids

  Rocchetta, R. & Patelli, E., 31 May 2020, In: Reliability Engineering and System Safety. 197, 12 p., 106817.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Risk assessment 100%
  • Electric power systems 86%
  • Costs 31%
  • Outages 18%
  • Hazards 18%
  5 Citations (Scopus)

  1 Downloads (Pure)

• Dynamic and probabilistic multi-class prediction of tunnel squeezing intensity

  Chen, Y., Li, T., Zeng, P., Ma, J., Patelli, E. & Edwards, B., 31 Aug 2020, In: Rock Mechanics and Rock Engineering. 53, 8, p. 3521-3542 22 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • tunnel 100%
  • Tunnels 93%
  • prediction 55%
  • Decision trees 43%
  • Geologic models 39%
  2 Citations (Scopus)

  4 Downloads (Pure)

• Optimal regulation of the construction of reliable sea defenses

  Nieto-Cerezo, O., Wenzelburger, J., Patelli, E. & Beer, M., 30 Jun 2020, In: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering. 6, 2, 12 p., 04020023.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Risk management 100%
  • Civil engineering 97%
  • Costs 70%
  • Risk perception 69%
  • Risk assessment 45%
  1 Downloads (Pure)

• Robust propagation of probability boxes by interval predictor models

  Sadeghi, J., de Angelis, M. & Patelli, E., 31 Jan 2020, In: Structural Safety. 82, 10 p., 101889.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Sampling 100%
  13 Citations (Scopus)

  10 Downloads (Pure)

• Transient safety assessment and risk mitigation of a hydroelectric generation system

  Li, H., Xu, B., Arzaghi, E., Abbassi, R., Chen, D., Aggidis, G. A., Zhang, J. & Patelli, E., 1 Apr 2020, In: Energy. 196, 17 p., 117135.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Safety Assessment 100%
  • Safety 49%
  • mitigation 44%
  • safety 40%
  • Start-ups 31%
  5 Citations (Scopus)

  14 Downloads (Pure)
• 2019

  A multivariate interval approach for inverse uncertainty quantification with limited experimental data

  Faes, M., Broggi, M., Patelli, E., Govers, Y., Mottershead, J., Beer, M. & Moens, D., 1 Mar 2019, In: Mechanical Systems and Signal Processing. 118, p. 534-548 15 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Availability 75%
  • Markov chains 51%
  37 Citations (Scopus)

  2 Downloads (Pure)

• Approach to wide-frequency battery impedance measurements in commercial applications

  Sandschulte, A., Ferrero, R., Hardwick, L. & Patelli, E., 14 Nov 2019, (E-pub ahead of print) 2019 IEEE 10th International Workshop on Applied Measurements for Power Systems - Proceedings. Piscataway, NJ: IEEE, 6 p. 8897753

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

  Open Access

  File

  • Electrochemical impedance spectroscopy 100%
  • impedance measurement 94%
  • electric batteries 82%
  • impedance 61%
  • Acoustic impedance 59%
  1 Citation (Scopus)

  9 Downloads (Pure)

• A reinforcement learning framework for optimal operation and maintenance of power grids

  Rocchetta, R., Bellani, L., Compare, M., Zio, E. & Patelli, E., 1 May 2019, In: Applied Energy. 241, p. 291-301 11 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • Reinforcement learning 100%
  • reinforcement 98%
  • Electric power systems 84%
  • learning 81%
  • artificial neural network 68%
  54 Citations (Scopus)

• Bayesian network approach to fault diagnosis of a hydroelectric generation system

  Xu, B., Li, H., Pang, W., Chen, D., Tian, Y., Lei, X., Gao, X., Wu, C. & Patelli, E., 31 Oct 2019, In: Energy Science and Engineering. 7, 5, p. 1669-1677 9 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Bayesian networks 100%
  • Failure analysis 84%
  • Expert systems 45%
  • Hydraulics 18%
  5 Citations (Scopus)

  7 Downloads (Pure)

• Black-box propagation of failure probabilities under epistemic uncertainty

  De Angelis, M., Ferson, S., Patelli, E. & Kreinovich, V., 24 Jun 2019, Proceedings of the 3rd International Conference on Uncertainty Quantification in Computational Sciences and Engineering, UNCECOMP 2019. Papadrakakis, M., Papadopoulos, V. & Stefanou, G. (eds.). Athens, p. 713-723 11 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

  • Epistemic Uncertainty 100%
  • Failure Probability 79%
  • Black Box 67%
  • Propagation 53%
  • Strategy 31%
  2 Citations (Scopus)

• Correction to 'A probabilistic metric for the validation of computational models'

  Dvurecenska, K., Graham, S., Patelli, E. & Patterson, E. A., 4 Dec 2019, In: Royal Society Open Science. 6, 12, 1 p., 191986.

  Research output: Contribution to journal › Comment/debate › peer-review

  Open Access

  File

  • Computational Model 100%
  • Metric 56%
  • Line 33%
  • Text 31%
  • Repository 24%

• Dynamic safety assessment of a nonlinear pumped-storage generating system in a transient process

  Li, H., Chen, D., Arzaghi, E., Abbassi, R., Kilicman, A., Caraballo, T., Patelli, E., Gao, X. & Xu, B., 28 Feb 2019, In: Communications in Nonlinear Science and Numerical Simulation. 67, p. 192 - 202 11 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Safety Assessment 100%
  • Francis turbines 33%
  • Turbine 26%
  • Safety 21%
  • Linkage 21%
  8 Citations (Scopus)

  1 Downloads (Pure)

• Efficient training of interval neural networks for imprecise training data

  Sadeghi, J., de Angelis, M. & Patelli, E., 31 Oct 2019, In: Neural Networks. 118, p. 338-351 14 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Convergence of numerical methods 99%
  • Uncertainty 98%
  • Neural networks 96%
  • Constrained optimization 86%
  • Backpropagation 74%
  9 Citations (Scopus)

  2 Downloads (Pure)

• Extending the survival signature paradigm to complex systems with non-repairable dependent failures

  George-Williams, H., Feng, G., Coolen, F. PA., Beer, M. & Patelli, E., 1 Aug 2019, In: Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability. 233, 4, p. 505-519 15 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Complex Systems 100%
  • Paradigm 94%
  • Signature 91%
  • Large scale systems 82%
  • Dependent 64%
  7 Citations (Scopus)

  3 Downloads (Pure)

• Implications of uncertainties on European DEMO design

  Lux, H., Siccinio, M., Biel, W., Federici, G., Kembleton, R., Morris, A. W., Patelli, E. & Zohm, H., 26 Apr 2019, In: Nuclear Fusion. 59, 6, 7 p., 066012.

  Research output: Contribution to journal › Article › peer-review

  • fusion 100%
  • engineering 60%
  • physics 52%
  • power plants 49%
  • evaluation 26%
  2 Citations (Scopus)

• Inverse quantification of epistemic uncertainty under scarce data: Bayesian or Interval approach?

  Faes, M., Broggi, M., Patelli, E., Govers, Y., Mottershead, J., Beer, M. & Moens, D., 26 May 2019. 8 p.

  Research output: Contribution to conference › Paper › peer-review

  Open Access

  File

  • Epistemic Uncertainty 100%
  • Quantification 65%
  • Interval 34%
  • Markov chains 28%
  • Model Updating 24%
  6 Downloads (Pure)

• Machine-learning tool for human factors evaluation - application to lion air Boeing 737-8 max accident

  Morais, C., Yung, K. & Patelli, E., 24 Jun 2019, Proceedings of the 3rd International Conference on Uncertainty Quantification in Computational Sciences and Engineering, UNCECOMP 2019. Papadrakakis, M., Papadopoulos, V. & Stefanou, G. (eds.). Athens, p. 498-508 11 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

  Open Access

  File

  • Human Factors 100%
  • Accidents 78%
  • Machine Learning 65%
  • Human engineering 61%
  • Machine learning 43%
  1 Citation (Scopus)

  2 Downloads (Pure)

• Mathematical model and parametric uncertainty analysis of a hydraulic generating system

  Xu, B., Chen, D., Patelli, E., Shen, H. & Park, J. H., 30 Jun 2019, In: Renewable Energy. 136, p. 1217-1230 14 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Uncertainty analysis 100%
  • Hydraulics 63%
  • Mathematical models 56%
  • Conversion efficiency 34%
  14 Citations (Scopus)

  1 Downloads (Pure)

• On the robust estimation of small failure probabilities for strong non-linear models

  Faes, M., Sadeghi, J., Broggi, M., Angelis, M. D., Patelli, E., Beer, M. & Moens, D., 31 Dec 2019, In: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B - Mechanical Engineering. 5, 4, 8 p., 041007.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • non-linear model 100%
  • Failure Probability 89%
  • Robust Estimation 76%
  • Nonlinear Model 64%
  • Surrogate Model 50%
  12 Citations (Scopus)

  6 Downloads (Pure)

• Priority analysis for risk factors of equipment in a hydraulic turbine generator unit

  Xu, B., Chen, D., Li, H., Zhuang, K., Hu, X., Li, J., Skjelbred, H. I., Kong, J. & Patelli, E., 31 Mar 2019, In: Journal of Loss Prevention in the Process Industries. 58, p. 1-7 7 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • Hydroelectric generators 100%
  • Equipment Failure 87%
  • hydraulic systems 81%
  • Risk Factors 81%
  • generators (equipment) 76%
  7 Citations (Scopus)

• Probabilistic risk assessment of fire occurrence in residential buildings: application to the Grenfell tower

  Estrada-Lugo, H. D., De Angelis, M. & Patelli, E., 26 May 2019. 8 p.

  Research output: Contribution to conference › Paper › peer-review

  Open Access

  File

  • Risk Assessment 100%
  • Buildings 92%
  • Risk assessment 71%
  • Towers 67%
  • Fires 59%
  1 Citation (Scopus)

  4 Downloads (Pure)

• Pseudo credal networks for inference with probability intervals

  Estrada-Lugo, H. D., Tolo, S., De Angelis, M. & Patelli, E., 31 Dec 2019, In: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering. 5, 4, 12 p., 041010.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • NP-hard 100%
  • Probability distributions 97%
  • Costs 78%
  • costs 39%
  • evidence 28%
  5 Citations (Scopus)

  2 Downloads (Pure)

• Robust on-line diagnosis tool for the early accident detection in nuclear power plants

  Tolo, S., Tian, X., Bausch, N., Becerra, V., Santhosh, T. V., Vinod, G. & Patelli, E., 1 Jun 2019, In: Reliability Engineering and System Safety. 186, p. 110-119 10 p.

  Research output: Contribution to journal › Article › peer-review

  • Nuclear Power Plant 100%
  • Accidents 77%
  • Loss of coolant accidents 72%
  • Nuclear power plants 54%
  • Network Architecture 44%
  12 Citations (Scopus)

• Towards a Bayesian framework for model validation

  Gray, A. & Patelli, E., 26 May 2019. 8 p.

  Research output: Contribution to conference › Paper › peer-review

  Open Access

  File

  • Model Validation 100%
  • Experiment 53%
  • Framework 40%
  • Information Entropy 34%
  • Experiments 25%
  1 Downloads (Pure)

• Transient stability of a hydro-turbine governing system with different tailrace tunnels

  Zhang, H., Pang, W., Chen, D., Tian, Y., Patelli, E., Li, C. & Zhou, J., 14 Jan 2019, (E-pub ahead of print) In: Journal of Hydraulic Research . 58, 1, p. 60-69 10 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • turbine 100%
  • tunnel 95%
  • Tunnels 89%
  • Turbines 83%
  • Water levels 25%
  3 Citations (Scopus)

  16 Downloads (Pure)

• Uncertainty quantification of optimal threshold failure probability for predictive maintenance using confidence structures

  Lye, A., Cicirello, A. & Patelli, E., 24 Jun 2019, Proceedings of the 3rd International Conference on Uncertainty Quantification in Computational Sciences and Engineering, UNCECOMP 2019. Papadrakakis, M., Papadopoulos, V. & Stefanou, G. (eds.). Athens, p. 620-628 9 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

  Open Access

  File

  • Failure Probability 100%
  • Uncertainty Quantification 98%
  • Predictive maintenance 94%
  • Maintenance 85%
  • Confidence 78%
  3 Downloads (Pure)
• 2018

  An efficient computational strategy for robust maintenance scheduling: application to corroded pipelines

  Patelli, E. & de Angelis, M., 15 Jun 2018, Safety and Reliability - Safe Societies in a Changing World: Proceedings of the 28th International European Safety and Reliability Conference, ESREL 2018. Haugen, S., Barros, A., van Gulijk, C., Kongsvik, T. & Vinnem, J. E. (eds.). London, p. 2201-2209 9 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

  Open Access

  File

  • Pipelines 100%
  • Scheduling 90%
  • Reliability analysis 26%
  • Sampling 18%
  • Costs 10%
  2 Downloads (Pure)

• An efficient method for estimating conditional failure probabilities

  Altieri, D. & Patelli, E., 16 Jul 2018. 6 p.

  Research output: Contribution to conference › Paper › peer-review

  Open Access

  File

  • Failure Probability 100%
  • Conditional probability 79%
  • Probability density function 47%
  • Sampling 34%
  • Reliability analysis 24%
  3 Downloads (Pure)

• An efficient reliability analysis on complex non-repairable systems with common-cause failures

  Feng, G., George-Williams, H., Patelli, E., Coolen, F. P. A. & Beer, M., 1 Jan 2018, Safety and Reliability - Safe Societies in a Changing World - Proceedings of the 28th International European Safety and Reliability Conference, ESREL 2018. van Gulijk, C., Haugen, S., Barros, A., Vinnem, J. E. & Kongsvik, T. (eds.). p. 2531-2538 8 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

  Open Access

  File

  • Common Cause Failure 100%
  • Reliability Analysis 68%
  • Reliability analysis 55%
  • Large scale systems 47%
  • Complex Systems 45%
  5 Citations (Scopus)

  1 Downloads (Pure)

• An open toolbox for the reduction, inference computation and sensitivity analysis of Credal Networks

  Tolo, S., Patelli, E. & Beer, M., 1 Jan 2018, In: Advances in Engineering Software. 115, p. 126-148 23 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Bayesian networks 100%
  • Sensitivity analysis 86%
  • Costs 12%
  13 Citations (Scopus)

  2 Downloads (Pure)

• A power-flow emulator approach for resilience assessment of repairable power grids subject to weather-induced failures and data deficiency

  Rocchetta, R., Zio, E. & Patelli, E., 15 Jan 2018, In: Applied Energy. 210, p. 339-350 12 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Electric power systems 100%
  • weather 81%
  • severe weather 37%
  • Statistical Models 36%
  • Sensitivity analysis 34%
  40 Citations (Scopus)

  1 Downloads (Pure)

• A probabilistic metric for the validation of computational models

  Dvurecenska, K., Graham, S., Patelli, E. & Patterson, E. A., 21 Nov 2018, In: Royal Society Open Science. 5, 11, 14 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Computational Model 100%
  • Metric 56%
  • Structural analysis 43%
  • Relative Error 37%
  • Decomposition 30%
  7 Citations (Scopus)

  7 Downloads (Pure)

• Assessment of power grid vulnerabilities accounting for stochastic loads and model imprecision

  Rocchetta, R. & Patelli, E., 30 Jun 2018, In: Electrical Power and Energy Systems. 98, p. 219-232 14 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Vulnerability 100%
  • Imprecision 96%
  • Electric power systems 62%
  • Grid 59%
  • Attack 30%
  25 Citations (Scopus)

  4 Downloads (Pure)

• Attempt to predict human error probability in different industry sectors using data from major accidents and Bayesian networks

  Morais, C., Moura, R., Beer, M. & Patelli, E., 21 Sep 2018. 11 p.

  Research output: Contribution to conference › Paper › peer-review

  Open Access

  File

  • Bayesian networks 100%
  • Accidents 78%
  • Industry 42%
  • Engineers 34%
  • Chemical industry 27%
  2 Citations (Scopus)

  3 Downloads (Pure)

• Bayesian networks with imprecise datasets: application to oscillating water column

  Estrada-Lugo, H. D., Patelli, E., de Angelis, M. & Raj, D. D., 15 Jun 2018, Safety and Reliability - Safe Societies in a Changing World: Proceedings of the 28th International European Safety and Reliability Conference, ESREL 2018. Haugen, S., Barros, A., van Gulijk, C., Kongsvik, T. & Vinnem, J. E. (eds.). London, p. 2611-2618 8 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

  Open Access

  File

  • Bayesian networks 100%
  • Random variables 67%
  • Risk assessment 63%
  • Water 53%
  • Large scale systems 27%
  3 Citations (Scopus)

  3 Downloads (Pure)

• Comparison of Bayesian and interval uncertainty quantification: application to the AIRMOD test structure

  Broggi, M., Faes, M., Patelli, E., Govers, Y., Moens, D. & Beer, M., 5 Feb 2018, 2017 IEEE Symposium Series on Computational Intelligence. Piscataway, NJ, 8 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

  Open Access

  File

  • Uncertainty Quantification 100%
  • Interval 43%
  • Quantification 33%
  • Computational Cost 30%
  • Uncertainty 25%
  15 Citations (Scopus)

  1 Downloads (Pure)

• Do we have enough data? Robust reliability via uncertainty quantification

  Rocchetta, R., Broggi, M. & Patelli, E., 1 Feb 2018, In: Applied Mathematical Modelling. 54, p. 710-721 12 p.

  Research output: Contribution to journal › Article › peer-review

  File

  • Uncertainty Quantification 100%
  • Probabilistic Approach 93%
  • Epistemic Uncertainty 84%
  • Reliability Assessment 40%
  • Electric power transmission networks 27%
  18 Citations (Scopus)

  2 Downloads (Pure)

• Dynamic analysis of a pumped-storage hydropower plant with random power load

  Zhang, H., Chen, D., Xu, B., Patelli, E. & Tolo, S., 1 Feb 2018, In: Mechanical Systems and Signal Processing. 100, p. 524-533 10 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Dynamic analysis 100%
  • Penstocks 81%
  • Electric generators 75%
  • Dynamic response 47%
  • Dynamic models 44%
  31 Citations (Scopus)

  13 Downloads (Pure)

• Dynamic evolution of a hydraulic–mechanical–electric system with randomly fluctuating speed

  Xu, B., Chen, D., Gao, X., Tomas, C. & Patelli, E., 1 Jun 2018, In: Nonlinear Dynamics. 92, 4, p. 1801-1813 13 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Electric Power System 100%
  • Probabilistic Model 73%
  • Statistical Models 57%
  • Electric power systems 53%
  • Evaluation 46%
  8 Citations (Scopus)

  1 Downloads (Pure)

• Effect of load-generation variability on power grid cascading failures

  Rocchetta, R., Patelli, E., Bing, L. & Sansavini, G., 1 Jan 2018, Safety and Reliability - Safe Societies in a Changing World - Proceedings of the 28th International European Safety and Reliability Conference, ESREL 2018. van Gulijk, C., Haugen, S., Barros, A., Vinnem, J. E. & Kongsvik, T. (eds.). p. 2679-2686 8 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

  • Cascading Failure 100%
  • Electric power systems 45%
  • Grid 43%
  • Demand 27%
  • Overload 21%
  1 Citation (Scopus)

• Financially optimal solar power sizing and positioning in a power grid

  Cangul, O., Rocchetta, R., Patelli, E. & Fahrioglu, M., 27 Jun 2018, 2018 IEEE International Energy Conference, ENERGYCON 2018. Piscataway, N.J.: IEEE, 6 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

  • Renewable Energy 100%
  • Positioning 74%
  • Solar energy 49%
  • Electric power systems 46%
  • Renewable energy resources 44%
  3 Citations (Scopus)

• Frequentist history matching with interval predictor models

  Sadeghi, J., Angelis, M. D. & Patelli, E., 1 Sep 2018, In: Applied Mathematical Modelling. 61, p. 29-48 20 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • History Matching 100%
  • Predictors 50%
  • Interval 31%
  • Truth 18%
  • Model 17%
  10 Citations (Scopus)

  1 Downloads (Pure)

• Hamiltonian formulation and analysis for transient dynamics of multi-unit hydropower system

  Li, H., Chen, D., Tolo, S., Xu, B. & Patelli, E., 31 Oct 2018, In: Journal of Computational and Nonlinear Dynamics. 13, 10, 101004.

  Research output: Contribution to journal › Article › peer-review

  • Transient Dynamics 100%
  • Hamiltonian Formulation 87%
  • Hamiltonians 77%
  • Unit 44%
  • Penstocks 24%
  6 Citations (Scopus)

• Human reliability analysis-accounting for human actions and external factors through the project life cycle

  Morais, C., Moura, R., Beer, M. & Patelli, E., 15 Jun 2018, Safety and Reliability - Safe Societies in a Changing World: Proceedings of the 28th International European Safety and Reliability Conference, ESREL 2018. Haugen, S., Barros, A., van Gulijk, C., Kongsvik, T. & Vinnem, J. E. (eds.). London, p. 329-338 10 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

  Open Access

  File

  • Reliability analysis 100%
  • Life cycle 85%
  • Bayesian networks 16%
  • Nuclear power plants 15%
  • Error analysis 15%
  1 Citation (Scopus)

  1 Downloads (Pure)

• Modelling and simulation activities in support of the UK nuclear R&D programme on digital reactor design

  Lindley, B., Allen, D., Lillington, J., Smethurst, A., Smith, P., Bowman, D., Dwyer, L., Lai, K., Levers, A., Vikhorev, K., Litskevich, D., Merk, B., Patelli, E., Patterson, E., Bankhead, M., Peakman, A., de Haas, S., Jackson, C., Draup, J., Galenne, E. & 3 others, Parks, G., Shwageraus, E. & Eaton, M. D., 24 Oct 2018, 2018 26th International Conference on Nuclear Engineering: Volume 3: Nuclear Fuel and Material, Reactor Physics, and Transport Theory. New York, 7 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

  • Physics 100%
  • Reactor operation 79%
  • Nuclear reactors 63%
  • Brick 61%
  • Graphite 57%
  5 Citations (Scopus)