Abstract
The benefits of structural health monitoring (SHM) within the life-cycle of a structure include reducing risk, quantifying uncertainties and hence prevention of unnecessary maintenance actions. Value of information (VoI) is one such indicator that has been frequently used to formally quantify the benefit of SHM. Adopting a life-cycle perspective of the incurred costs typically due to failure and maintenance, VoI is defined as the difference between the costs with and without SHM information. Hence, VoI can also be used to compare different SHM strategies and instruments. However, the application of VoI to realistic problems has so far been restricted due to a number of issues, of which the computational complexity is the most significant. As the structural model and the maintenance strategy become more comprehensive (and realistic), the evaluation of VoI becomes intractable due to the increasing number of decision/event possibilities. Metamodeling or surrogate modelling strategies are widely adopted to approximate complex models into simpler functional forms using a limited number of simulations. In this paper, we investigate polynomial chaos expansion (PCE) and a kriging metamodelling framework for VoI computation and demonstrate it for a structural component undergoing linear degradation. The efficiency of the metamodelling strategies is evaluated against a crude Monte Carlo sampling based approach. The reduction in computation costs can enable the implementation of VoI in realistic scenarios. Options for further improvement in the metamodel efficiency are also discussed.
| Original language | English |
|---|---|
| Title of host publication | Life-Cycle Analysis and Assessment in Civil Engineering |
| Subtitle of host publication | Towards an Integrated Vision - Proceedings of the 6th International Symposium on Life-Cycle Civil Engineering, IALCCE 2018 |
| Editors | Dan M. Frangopol, Robby Caspeele, Luc Taerwe |
| Publisher | CRC Press |
| Pages | 2169-2174 |
| Number of pages | 6 |
| ISBN (Print) | 9781138626331 |
| Publication status | Published - 1 Jan 2019 |
| Event | International Symposium on Life-Cycle Civil Engineering 2018 - Ghent, Belgium Duration: 28 Oct 2018 → 31 Oct 2018 Conference number: 6th http://www.ialcce2018.org/ |
Publication series
| Name | Life-Cycle Analysis and Assessment in Civil Engineering: Towards an Integrated Vision - Proceedings of the 6th International Symposium on Life-Cycle Civil Engineering, IALCCE 2018 |
|---|
Conference
| Conference | International Symposium on Life-Cycle Civil Engineering 2018 |
|---|---|
| Abbreviated title | IALCCE 2018 |
| Country | Belgium |
| City | Ghent |
| Period | 28/10/18 → 31/10/18 |
| Internet address |
Cite this
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Metamodeling strategies for value of information computation. / Khan, M. S.; Ghosh, S.; Ghosh, J.; Caprani, C.
Life-Cycle Analysis and Assessment in Civil Engineering: Towards an Integrated Vision - Proceedings of the 6th International Symposium on Life-Cycle Civil Engineering, IALCCE 2018. ed. / Dan M. Frangopol; Robby Caspeele; Luc Taerwe. CRC Press, 2019. p. 2169-2174 (Life-Cycle Analysis and Assessment in Civil Engineering: Towards an Integrated Vision - Proceedings of the 6th International Symposium on Life-Cycle Civil Engineering, IALCCE 2018).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Other
TY - GEN
T1 - Metamodeling strategies for value of information computation
AU - Khan, M. S.
AU - Ghosh, S.
AU - Ghosh, J.
AU - Caprani, C.
PY - 2019/1/1
Y1 - 2019/1/1
N2 - The benefits of structural health monitoring (SHM) within the life-cycle of a structure include reducing risk, quantifying uncertainties and hence prevention of unnecessary maintenance actions. Value of information (VoI) is one such indicator that has been frequently used to formally quantify the benefit of SHM. Adopting a life-cycle perspective of the incurred costs typically due to failure and maintenance, VoI is defined as the difference between the costs with and without SHM information. Hence, VoI can also be used to compare different SHM strategies and instruments. However, the application of VoI to realistic problems has so far been restricted due to a number of issues, of which the computational complexity is the most significant. As the structural model and the maintenance strategy become more comprehensive (and realistic), the evaluation of VoI becomes intractable due to the increasing number of decision/event possibilities. Metamodeling or surrogate modelling strategies are widely adopted to approximate complex models into simpler functional forms using a limited number of simulations. In this paper, we investigate polynomial chaos expansion (PCE) and a kriging metamodelling framework for VoI computation and demonstrate it for a structural component undergoing linear degradation. The efficiency of the metamodelling strategies is evaluated against a crude Monte Carlo sampling based approach. The reduction in computation costs can enable the implementation of VoI in realistic scenarios. Options for further improvement in the metamodel efficiency are also discussed.
AB - The benefits of structural health monitoring (SHM) within the life-cycle of a structure include reducing risk, quantifying uncertainties and hence prevention of unnecessary maintenance actions. Value of information (VoI) is one such indicator that has been frequently used to formally quantify the benefit of SHM. Adopting a life-cycle perspective of the incurred costs typically due to failure and maintenance, VoI is defined as the difference between the costs with and without SHM information. Hence, VoI can also be used to compare different SHM strategies and instruments. However, the application of VoI to realistic problems has so far been restricted due to a number of issues, of which the computational complexity is the most significant. As the structural model and the maintenance strategy become more comprehensive (and realistic), the evaluation of VoI becomes intractable due to the increasing number of decision/event possibilities. Metamodeling or surrogate modelling strategies are widely adopted to approximate complex models into simpler functional forms using a limited number of simulations. In this paper, we investigate polynomial chaos expansion (PCE) and a kriging metamodelling framework for VoI computation and demonstrate it for a structural component undergoing linear degradation. The efficiency of the metamodelling strategies is evaluated against a crude Monte Carlo sampling based approach. The reduction in computation costs can enable the implementation of VoI in realistic scenarios. Options for further improvement in the metamodel efficiency are also discussed.
UR - http://www.scopus.com/inward/record.url?scp=85063970484&partnerID=8YFLogxK
M3 - Conference Paper
SN - 9781138626331
T3 - Life-Cycle Analysis and Assessment in Civil Engineering: Towards an Integrated Vision - Proceedings of the 6th International Symposium on Life-Cycle Civil Engineering, IALCCE 2018
SP - 2169
EP - 2174
BT - Life-Cycle Analysis and Assessment in Civil Engineering
A2 - Frangopol, Dan M.
A2 - Caspeele, Robby
A2 - Taerwe, Luc
PB - CRC Press
ER -