TY - JOUR
T1 - Value of structural health information in partially observable stochastic environments
AU - Andriotis, Charalampos P.
AU - Papakonstantinou, Konstantinos G.
AU - Chatzi, Eleni N.
N1 - Funding Information:
This material is based upon work supported by the U.S. National Science Foundation under CAREER Grant No. 1751941, and by CIAMTIS, the 2018 U.S. DOT Region 3 University Transportation Center. The authors would like to thank Hongda Gao for his early assistance on the first numerical application, during his stay at Penn State as a visiting doctoral student from the Beijing Institute of Technology. Prof. Chatzi would further like to acknowledge the support of the ERC Starting Grant WINDMIL on the topic of “Smart Monitoring, Inspection and Life-Cycle Assessment of Wind Turbines”.
Funding Information:
This material is based upon work supported by the U.S. National Science Foundation under CAREER Grant No. 1751941, and by CIAMTIS, the 2018 U.S. DOT Region 3 University Transportation Center. The authors would like to thank Hongda Gao for his early assistance on the first numerical application, during his stay at Penn State as a visiting doctoral student from the Beijing Institute of Technology. Prof. Chatzi would further like to acknowledge the support of the ERC Starting Grant WINDMIL on the topic of ?Smart Monitoring, Inspection and Life-Cycle Assessment of Wind Turbines?.
Publisher Copyright:
© 2021 Elsevier Ltd
PY - 2021/11
Y1 - 2021/11
N2 - Efficient integration of uncertain observations with decision-making optimization is key for prescribing informed intervention actions, able to preserve structural safety of deteriorating engineering systems. To this end, it is necessary that scheduling of inspection and monitoring strategies be objectively performed on the basis of their expected value-based gains that, among others, reflect quantitative metrics such as the Value of Information (VoI) and the Value of Structural Health Monitoring (VoSHM). In this work, we introduce and study the theoretical and computational foundations of the above metrics within the context of Partially Observable Markov Decision Processes (POMDPs), thus alluding to a broad class of decision-making problems of partially observable stochastic deteriorating environments that can be modeled as POMDPs. Step-wise and life-cycle VoI and VoSHM definitions are devised and their bounds are analyzed as per the properties stemming from the Bellman equation and the resulting optimal value function. It is shown that a POMDP policy inherently leverages the notion of VoI to guide observational actions in an optimal way at every decision step, and that the permanent or intermittent information provided by SHM or inspection visits, respectively, can only improve the cost of this policy in the long-term, something that is not necessarily true under locally optimal policies, typically adopted in decision-making of structures and infrastructure. POMDP solutions are derived based on point-based value iteration methods, and the various definitions are quantified in stationary and non-stationary deteriorating environments, with both infinite and finite planning horizons, featuring single- or multi-component engineering systems.
AB - Efficient integration of uncertain observations with decision-making optimization is key for prescribing informed intervention actions, able to preserve structural safety of deteriorating engineering systems. To this end, it is necessary that scheduling of inspection and monitoring strategies be objectively performed on the basis of their expected value-based gains that, among others, reflect quantitative metrics such as the Value of Information (VoI) and the Value of Structural Health Monitoring (VoSHM). In this work, we introduce and study the theoretical and computational foundations of the above metrics within the context of Partially Observable Markov Decision Processes (POMDPs), thus alluding to a broad class of decision-making problems of partially observable stochastic deteriorating environments that can be modeled as POMDPs. Step-wise and life-cycle VoI and VoSHM definitions are devised and their bounds are analyzed as per the properties stemming from the Bellman equation and the resulting optimal value function. It is shown that a POMDP policy inherently leverages the notion of VoI to guide observational actions in an optimal way at every decision step, and that the permanent or intermittent information provided by SHM or inspection visits, respectively, can only improve the cost of this policy in the long-term, something that is not necessarily true under locally optimal policies, typically adopted in decision-making of structures and infrastructure. POMDP solutions are derived based on point-based value iteration methods, and the various definitions are quantified in stationary and non-stationary deteriorating environments, with both infinite and finite planning horizons, featuring single- or multi-component engineering systems.
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U2 - 10.1016/j.strusafe.2020.102072
DO - 10.1016/j.strusafe.2020.102072
M3 - Article
AN - SCOPUS:85113976415
VL - 93
JO - Structural Safety
JF - Structural Safety
SN - 0167-4730
M1 - 102072
ER -