| Reliability in composites–A selective review and survey of current development M Chiachio, J Chiachio, G Rus Composites Part B: Engineering 43 (3), 902-913, 2012 | 128 | 2012 |
| Approximate Bayesian computation by subset simulation M Chiachio, JL Beck, J Chiachio, G Rus SIAM Journal on Scientific Computing 36 (3), A1339-A1358, 2014 | 60 | 2014 |
| Condition-based prediction of time-dependent reliability in composites J Chiachío, M Chiachío, S Sankararaman, A Saxena, K Goebel Reliability Engineering & System Safety 142, 134-147, 2015 | 55 | 2015 |
| Bayesian model selection and parameter estimation for fatigue damage progression models in composites J Chiachío, M Chiachío, A Saxena, S Sankararaman, G Rus, K Goebel International Journal of Fatigue 70, 361-373, 2015 | 47 | 2015 |
| Predicting fatigue damage in composites: A Bayesian framework M Chiachío, J Chiachío, G Rus, JL Beck Structural Safety 51, 57-68, 2014 | 32 | 2014 |
| An Energy-Based Prognostic Framework to Predict Fatigue Damage Evolution in Composites J Chiachío, M Chiachío, A Saxena, G Rus, K Goebel Annual Conference of the Prognostics and Health Management Society, 2013, 2013 | 27 | 2013 |
| A robust Bayesian methodology for damage localization in plate-like structures using ultrasonic guided-waves S Cantero-Chinchilla, J Chiachío, M Chiachío, D Chronopoulos, A Jones Mechanical Systems and Signal Processing 122, 192-205, 2019 | 23 | 2019 |
| A new algorithm for prognostics using Subset Simulation M Chiachío, J Chiachío, S Sankararaman, K Goebel, J Andrews Reliability Engineering & System Safety 168, 189-199, 2017 | 18 | 2017 |
| A multilevel Bayesian method for ultrasound-based damage identification in composite laminates J Chiachío, N Bochud, M Chiachío, S Cantero, G Rus Mechanical Systems and Signal Processing 88, 462-477, 2017 | 17 | 2017 |
| Logical inference for inverse problems G Rus, J Chiachío, M Chiachío Inverse Problems in Science and Engineering 24 (3), 448-464, 2016 | 15 | 2016 |
| Prognostics design for structural health management J Chiachío, M Chiachío, S Sankararaman, A Saxena, K Goebel Emerging Design Solutions in Structural Health Monitoring Systems, 234-273, 2015 | 11 | 2015 |
| Fatigue damage prognosis in FRP composites by combining multi-scale degradation fault modes in an uncertainty Bayesian framework M Chiachio, J Chiachio, A Saxena, G Rus, K Goebel Proceedings of Structural Health Monitoring 1, 2013 | 10 | 2013 |
| A new paradigm for uncertain knowledge representation by Plausible Petri nets M Chiachío, J Chiachío, D Prescott, J Andrews Information Sciences 453, 323-345, 2018 | 9 | 2018 |
| An efficient simulation framework for prognostics of asymptotic processes-a case study in composite materials. M Chiachıo, J Chiachıo, A Saxena, G Rus, K Goebel European Conference of the Prognostics and Health Management Society, Nantes …, 2014 | 8 | 2014 |
| A reliability-based prognostics framework for railway track management J Chiachío, M Chiachío, D Prescott, J Andrews | 7 | 2017 |
| An energy-based prognostic framework to predict evolution of damage in composite materials M Chiachío, J Chiachío, A Saxena, K Goebel Structural Health Monitoring (SHM) in Aerospace Structures, 447-477, 2016 | 7 | 2016 |
| An information theoretic approach for knowledge representation using Petri nets M Chiachío, J Chiachío, D Prescott, J Andrews | 5 | 2016 |
| A Model-Based Prognostics Framework to Predict Fatigue Damage Evolution and Reliability in Composites J Chiachio, M Chiachio, A Saxena, G Rus, K Goebel European Conference of the Prognostics and Health Management Society (Nantes …, 2014 | 5 | 2014 |
| Optimal sensor configuration for ultrasonic guided-wave inspection based on value of information S Cantero-Chinchilla, J Chiachío, M Chiachío, D Chronopoulos, A Jones Mechanical Systems and Signal Processing 135, 106377, 2020 | 3 | 2020 |
| Nonlinear ultrasonics for early damage detection R Munoz, G Rus, N Bochud, DJ Barnard, J Melchor, JC Ruano, ... Virtual and Mobile Healthcare: Breakthroughs in Research and Practice, 697-732, 2020 | 3 | 2020 |
Guillermo RusUniversity of GranadaVerified email at ugr.es
