TY - GEN
T1 - Reliability of engineering systems combining structural health monitoring with state-of-the-art deterioration models
AU - Iannacone, L.
AU - Gardoni, P.
N1 - Funding Information:
This work was supported by the National Institute of Standards and Technology (NIST) through the Center for Risk-Based Community Resilience Planning under Award No 70NANB15H044. Opinions and findings presented are those of the writers.
Publisher Copyright:
© 11th National Conference on Earthquake Engineering 2018, NCEE 2018: Integrating Science, Engineering, and Policy. All rights reserved.
PY - 2018
Y1 - 2018
N2 - The probability of failure of engineering systems is typically time variant due to the effects of environmental conditions and operational loads. Such effects affect the system properties (state variables) that define the system ability to sustain future demands and the demands they might be facing. Therefore, it is of primary importance to estimate values of the state variables over time. Structural Health Monitoring (SHM) and Non-Destructive Evaluation (NDE) can be used in estimating the state variables at different times. However, typically this identification process is an ill-defined problem, i.e. different combination of the state variables can be possible to achieve the same values from SHM or NDE. Also SHM and NDE values cannot be used directly to obtain estimates of the probability of failure of the system at future times. To address these issues, this paper couples SHM and NDE with physics-based probabilistic models of the state variables that capture the physics of the deterioration process. The models can be calibrated using SHM and NDE data in a well-defined problem and can be used to estimate the values of the state variables at future times.
AB - The probability of failure of engineering systems is typically time variant due to the effects of environmental conditions and operational loads. Such effects affect the system properties (state variables) that define the system ability to sustain future demands and the demands they might be facing. Therefore, it is of primary importance to estimate values of the state variables over time. Structural Health Monitoring (SHM) and Non-Destructive Evaluation (NDE) can be used in estimating the state variables at different times. However, typically this identification process is an ill-defined problem, i.e. different combination of the state variables can be possible to achieve the same values from SHM or NDE. Also SHM and NDE values cannot be used directly to obtain estimates of the probability of failure of the system at future times. To address these issues, this paper couples SHM and NDE with physics-based probabilistic models of the state variables that capture the physics of the deterioration process. The models can be calibrated using SHM and NDE data in a well-defined problem and can be used to estimate the values of the state variables at future times.
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M3 - Conference contribution
AN - SCOPUS:85085525930
T3 - 11th National Conference on Earthquake Engineering 2018, NCEE 2018: Integrating Science, Engineering, and Policy
SP - 4463
EP - 4467
BT - 11th National Conference on Earthquake Engineering 2018, NCEE 2018
PB - Earthquake Engineering Research Institute
T2 - 11th National Conference on Earthquake Engineering 2018: Integrating Science, Engineering, and Policy, NCEE 2018
Y2 - 25 June 2018 through 29 June 2018
ER -