JUAN CHIACHIO RUANO
JUAN CHIACHIO RUANO
University of Granada
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα ugr.es
Τίτλος
Παρατίθεται από
Παρατίθεται από
Έτος
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
1342012
Approximate Bayesian computation by subset simulation
M Chiachio, JL Beck, J Chiachio, G Rus
SIAM Journal on Scientific Computing 36 (3), A1339-A1358, 2014
692014
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
582015
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
502015
Predicting fatigue damage in composites: A Bayesian framework
M Chiachío, J Chiachío, G Rus, JL Beck
Structural Safety 51, 57-68, 2014
332014
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
302013
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
292019
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
222017
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
172017
Logical inference for inverse problems
G Rus, J Chiachío, M Chiachío
Inverse Problems in Science and Engineering 24 (3), 448-464, 2016
172016
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
122018
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
112015
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
102013
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
92014
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
82016
A reliability-based prognostics framework for railway track management
J Chiachío, M Chiachío, D Prescott, J Andrews
PHM Society, 2017
72017
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
62020
Optimal sensor and actuator placement for structural health monitoring via an efficient convex cost-benefit optimization
S Cantero-Chinchilla, JL Beck, M Chiachío, J Chiachío, D Chronopoulos, ...
Mechanical Systems and Signal Processing 144, 106901, 2020
52020
An information theoretic approach for knowledge representation using Petri nets
M Chiachío, J Chiachío, D Prescott, J Andrews
IEEE, 2017
52017
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
52014
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