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On off-line and on-line Bayesian filtering for uncertainty quantification of structural deterioration
- Antonios Kamariotis, Luca Sardi, Iason Papaioannou, Eleni Chatzi, Daniel Straub
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- Journal:
- Data-Centric Engineering / Volume 4 / 2023
- Published online by Cambridge University Press:
- 13 July 2023, e17
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- Article
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Data-informed predictive maintenance planning largely relies on stochastic deterioration models. Monitoring information can be utilized to update sequentially the knowledge on model parameters. In this context, on-line (recursive) Bayesian filtering algorithms typically fail to properly quantify the full posterior uncertainty of time-invariant model parameters. Off-line (batch) algorithms are—in principle—better suited for the uncertainty quantification task, yet they are computationally prohibitive in sequential settings. In this work, we adapt and investigate selected Bayesian filters for parameter estimation: an on-line particle filter, an on-line iterated batch importance sampling filter, which performs Markov Chain Monte Carlo (MCMC) move steps, and an off-line MCMC-based sequential Monte Carlo filter. A Gaussian mixture model approximates the posterior distribution within the resampling process in all three filters. Two numerical examples provide the basis for a comparative assessment. The first example considers a low-dimensional, nonlinear, non-Gaussian probabilistic fatigue crack growth model that is updated with sequential monitoring measurements. The second high-dimensional, linear, Gaussian example employs a random field to model corrosion deterioration across a beam, which is updated with sequential sensor measurements. The numerical investigations provide insights into the performance of off-line and on-line filters in terms of the accuracy of posterior estimates and the computational cost, when applied to problems of different nature, increasing dimensionality and varying sensor information amount. Importantly, they show that a tailored implementation of the on-line particle filter proves competitive with the computationally demanding MCMC-based filters. Suggestions on the choice of the appropriate method in function of problem characteristics are provided.
Contributors
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- By Jane E. Adcock, Yahya Aghakhani, A. Anand, Eva Andermann, Frederick Andermann, Alexis Arzimanoglou, Sandrine Aubert, Nadia Bahi-Buisson, Carman Barba, Agatino Battaglia, Geneviève Bernard, Nadir E. Bharucha, Laurence A. Bindoff, William Bingaman, Francesca Bisulli, Thomas P. Bleck, Stewart G. Boyd, Andreas Brunklaus, Harry Bulstrode, Jorge G. Burneo, Laura Canafoglia, Laura Cantonetti, Roberto H. Caraballo, Fernando Cendes, Kevin E. Chapman, Patrick Chauvel, Richard F. M. Chin, H. T. Chong, Fahmida A. Chowdhury, Catherine J. Chu-Shore, Rolando Cimaz, Andrew J. Cole, Bernard Dan, Geoffrey Dean, Alessio De Ciantis, Fernando De Paolis, Rolando F. Del Maestro, Irissa M. Devine, Carlo Di Bonaventura, Concezio Di Rocco, Henry B. Dinsdale, Maria Alice Donati, François Dubeau, Michael Duchowny, Olivier Dulac, Monika Eisermann, Brent Elliott, Bernt A. Engelsen, Kevin Farrell, Natalio Fejerman, Rosalie E. Ferner, Silvana Franceschetti, Robert Friedlander, Antonio Gambardella, Hector H. Garcia, Serena Gasperini, Lorenzo Genitori, Gioia Gioi, Flavio Giordano, Leif Gjerstad, Daniel G. Glaze, Howard P. Goodkin, Sidney M. Gospe, Andrea Grassi, William P. Gray, Renzo Guerrini, Marie-Christine Guiot, William Harkness, Andrew G. Herzog, Linda Huh, Margaret J. Jackson, Thomas S. Jacques, Anna C. Jansen, Sigmund Jenssen, Michael R. Johnson, Dorothy Jones-Davis, Reetta Kälviäinen, Peter W. Kaplan, John F. Kerrigan, Autumn Marie Klein, Matthias Koepp, Edwin H. Kolodny, Kandan Kulandaivel, Ruben I. Kuzniecky, Ahmed Lary, Yolanda Lau, Anna-Elina Lehesjoki, Maria K. Lehtinen, Holger Lerche, Michael P. T. Lunn, Snezana Maljevic, Mark R. Manford, Carla Marini, Bindu Menon, Giulia Milioli, Eli M. Mizrahi, Manish Modi, Márcia Elisabete Morita, Manuel Murie-Fernandez, Vivek Nambiar, Lina Nashef, Vincent Navarro, Aidan Neligan, Ruth E. Nemire, Charles R. J. C. Newton, John O'Donavan, Hirokazu Oguni, Teiichi Onuma, Andre Palmini, Eleni Panagiotakaki, Pasquale Parisi, Elena Parrini, Liborio Parrino, Ignacio Pascual-Castroviejo, M. Scott Perry, Perrine Plouin, Charles E. Polkey, Suresh S. Pujar, Karthik Rajasekaran, R. Eugene Ramsey, Rahul Rathakrishnan, Roberta H. Raven, Guy M. Rémillard, David Rosenblatt, M. Elizabeth Ross, Abdulrahman Sabbagh, P. Satishchandra, Swati Sathe, Ingrid E. Scheffer, Philip A. Schwartzkroin, Rod C. Scott, Frédéric Sedel, Michelle J. Shapiro, Elliott H. Sherr, Michael Shevell, Simon D. Shorvon, Adrian M. Siegel, Gagandeep Singh, S. Sinha, Barbara Spacca, Waney Squier, Carl E. Stafstrom, Bernhard J. Steinhoff, Andrea Taddio, Gianpiero Tamburrini, C. T. Tan, Raymond Y. L. Tan, Erik Taubøll, Robert W. Teasell, Mario Giovanni Terzano, Federica Teutonico, Suzanne A. Tharin, Elizabeth A. Thiele, Pierre Thomas, Paolo Tinuper, Dorothée Kasteleijn-Nolst Trenité, Sumeet Vadera, Pierangelo Veggiotti, Jean-Pierre Vignal, J. M. Walshe, Elizabeth J. Waterhouse, David Watkins, Ruth E. Williams, Yue-Hua Zhang, Benjamin Zifkin, Sameer M. Zuberi
- Edited by Simon D. Shorvon, Frederick Andermann, Renzo Guerrini
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- Book:
- The Causes of Epilepsy
- Published online:
- 05 March 2012
- Print publication:
- 14 April 2011, pp ix-xvi
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The gears of the Antikythera Mechanism: an educational pathfinder to the solar system
- Xenophon Moussas, Georgios Bampasidis, Yanis Bitsakis, Theodosios Tassios, Magdalini Anastasiou, Kyriakos Efstathiou, Georgios Fasoulopoulos, Isidoros Kioleoglou, Mike Edmunds, Mary Zafeiropoulou, Manos Roumeliotis, Tom Malzbender, Andrew Ramsey, Dionysios Kriaris, Evangelos Spandagos, Nikos Giannopoulos, Amalia Porligi, Eleni Daniels, Michael T. Wright, Reem Sabry, Hoda El-Mikaty, Göran Henriksson, Ing-Marie Munktell, Flora Vafea, Stratos Koufos, Dimitrios Prassopoulos, Vasili Zafiropoulos, Andreas Karakonstantis, Katerina Aggeioplasti, Eleni Delidou, Costas Papoulias, George Papoulias, Paul Haley, Jamal Mimouni, David Valls-Gabaud, Matt Biggs, Drahomir Chochol, Jacek Szubiakowski, Ela Plucinska, Anna Jacyno, Alexandros Kakouris, Pavel Pal'uš, Danica Jančušková, Mária Feriančiková, Krystof Czart, Nikos Xenakis, Magda Evgenia Gkini, Eva Perpyraki, Leonidas Tziannoudakis, Panagiotis Antoniou
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- Journal:
- Proceedings of the International Astronomical Union / Volume 5 / Issue S260 / January 2009
- Published online by Cambridge University Press:
- 29 June 2011, E1
- Print publication:
- January 2009
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The Antikythera Mechanism is the most sophisticated extant ancient astronomical instrument and analogue computer known and was assembled sometime between 150 and 100 BCE, almost a century after the death of Archimedes. The mechanism has a great educational potential as it appeals to inquiring minds as an astonishing artefact of science and technology. The latest research findings reveal significant cultural and social functions in its operations. This astonishing astronomical instrument has a clear interdisciplinary valueand it has that it may be used as an educational medium, to engage the general public, and especially to attract students both to/from exact sciences and to/from the humanities. The astronomical and technical knowledge embedded in the mechanism can also be used to introduce some aspects of modern science through the unknown technological achievements of Hellenic antiquity.