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Plausible petri nets as self-adaptive expert systems: a tool for infrastructure asset monitoring (2018)
Journal Article
Chiachío, M., Chiachío, J., Prescott, D., & Andrews, J. (2019). Plausible petri nets as self-adaptive expert systems: a tool for infrastructure asset monitoring. Computer-Aided Civil and Infrastructure Engineering, 34(4), 281-298. https://doi.org/10.1111/mice.12427

This paper provides a computational framework to model self-adaptive expert systems using the Petri net (PN) formalism. Self-adaptive expert systems are understood here as expert systems with the ability to autonomously learn from external inputs, li... Read More about Plausible petri nets as self-adaptive expert systems: a tool for infrastructure asset monitoring.

A Bayesian time-of-flight estimation for ultrasonic damage detection (2018)
Conference Proceeding
Cantero-Chinchilla, S., Chiachío-Ruano, J., Chiachío-Ruano, M., Jones, A., Essa, Y., & Martín de la Escalera, F. (2018). A Bayesian time-of-flight estimation for ultrasonic damage detection.

SHM methods for damage detection and localisation in plate-like structures have typically relied on post-processing of ultrasonic guided waves (GWs) features. The time-of-flight is one of these features, which has been extensively used by the SHM com... Read More about A Bayesian time-of-flight estimation for ultrasonic damage detection.

A methodology for railway track maintenance modelling using Plausible Petri nets (2018)
Presentation / Conference
Chiachio, M., Chiachio, J., Prescott, D., & Andrews, J. (2018, September). A methodology for railway track maintenance modelling using Plausible Petri nets. Paper presented at Probabilistic Safety Assessment and Management PSAM 14

This paper proposes a new mathematical methodology to model expert systems with the ability to sequentially learn from data. To this end, the Plausible Petri nets (PPNs) methodology, first developed in M. Chiachío et al. [Proceedings of the Future Te... Read More about A methodology for railway track maintenance modelling using Plausible Petri nets.

Modelling adaptive systems using plausible Petri nets (2018)
Conference Proceeding
Chiachío, J., Chiachío, M., Prescott, D., & Andrews, J. (2018). Modelling adaptive systems using plausible Petri nets. In 8th International Workshop on Reliable Engineering Computing, “ Computing with Confidence ”

One of the main challenges when analyzing and modelling complex systems using Petri nets is to deal with uncertain information, and moreover, to be able to use such uncertainty to dynamically adapt the modelled system to uncertain (changing) contextu... Read More about Modelling adaptive systems using plausible Petri nets.

A knowledge-based prognostics framework for railway track geometry degradation (2018)
Journal Article
Chiachío, J., Chiachío, M., Prescott, D., & Andrews, J. (2019). A knowledge-based prognostics framework for railway track geometry degradation. Reliability Engineering and System Safety, 181, 127-141. https://doi.org/10.1016/j.ress.2018.07.004

This paper proposes a paradigm shift to the problem of infrastructure asset management modelling by focusing towards forecasting the future condition of the assets instead of using empirical modelling approaches based on historical data. The proposed... Read More about A knowledge-based prognostics framework for railway track geometry degradation.

Lamb wave-based damage indicator for plate-like structures (2018)
Journal Article
Cantero-Chinchilla, S., Chiachío-Ruano, J., Chiachío-Ruano, M., Etxaniz, J., Aranguren, G., Jones, A., …Martin De La Escalera, F. (2018). Lamb wave-based damage indicator for plate-like structures. European Conference of the Prognostics and Health Management Society, 4(1),

Structural health monitoring based on ultrasonics typically involves complex data analysis. Ultrasound monitoring based on Lamb waves techniques are extensively used nowadays due to their efficiency in exploring large areas with relatively small atte... Read More about Lamb wave-based damage indicator for plate-like structures.

A Bayesian assessment for railway track geometry degradation prognostics (2018)
Conference Proceeding
Chiachío, J., Chiachío, M., Prescott, D., & Andrews, J. (2018). A Bayesian assessment for railway track geometry degradation prognostics. In Proceedings of the 4th European Conference of the Prognostics and Health Management Society

Advanced PHM techniques have the potential to substantially reduce railway track maintenance costs while increasing safety and availability. However, there is still a significant lack of knowledge and experience in relation to suitable PHM models and... Read More about A Bayesian assessment for railway track geometry degradation prognostics.

A Bayesian Assessment of an Approximate Model for Unconfined Water Flow in Sloping Layered Porous Media (2018)
Journal Article
Chiachío, J., Chiachío, M., Sankararaman, S., & Prescott, D. (2019). A Bayesian Assessment of an Approximate Model for Unconfined Water Flow in Sloping Layered Porous Media. Transport in Porous Media, 126(1), 177-197. https://doi.org/10.1007/s11242-018-1094-2

© 2018, The Author(s). The prediction of water table height in unconfined layered porous media is a difficult modelling problem that typically requires numerical simulation.This paper proposes an analytical model to approximate the exact solution bas... Read More about A Bayesian Assessment of an Approximate Model for Unconfined Water Flow in Sloping Layered Porous Media.

A new paradigm for uncertain knowledge representation by Plausible Petri nets (2018)
Journal Article
Chiachío, M., Chiachío, J., Prescott, D., & Andrews, J. (2018). A new paradigm for uncertain knowledge representation by Plausible Petri nets. Information Sciences, 453, https://doi.org/10.1016/j.ins.2018.04.029

This paper presents a new model for Petri nets (PNs) which combines PN principles with the foundations of information theory for uncertain knowledge representation. The resulting framework has been named Plausible Petri nets (PPNs). The main feature... Read More about A new paradigm for uncertain knowledge representation by Plausible Petri nets.