Value of structural health information

The value of structural health information is the expected utility gain of a built environment system by information provided by structural health monitoring (SHM). The quantification of the value of structural health information is based on decision analysis adapted to built environment engineering. The value of structural health information can be significant for the risk and integrity management of built environment systems.

Background

The value of structural health information takes basis in the framework of the decision analysis and the value of information analysis as introduced by Raiffa and Schlaifer^[1] and adapted to civil engineering by Benjamin and Cornell.^[2] Decision theory itself is based upon the expected utility hypothesis by Von Neumann and Morgenstern.^[3] The concepts for the value of structural health information in built environment engineering were first formulated by Pozzi and Der Kiureghian^[4] and Faber and Thöns.^[5]

Formulation

The value of structural health information is quantified with a normative decision analysis. The value of structural health monitoring $V$ is calculated as the difference between the optimized expected utilities of performing and not performing structural health monitoring (SHM), $U_{1}$ and $U_{0}$ , respectively:

$V=U_{1}-U_{0}$

The expected utilities are calculated with a decision scenario involving (1) interrelated built environment system state, utility and consequence models, (2) structural health information type, precision and cost models and (2) structural health action type and implementation models. The value of structural health information quantification facilitates an optimization of structural health information system parameters and information dependent actions.^[6]^[7]

Application

The value of structural health information provides a quantitative decision basis for (1) implementing SHM or not, (2) the identification of the optimal SHM strategy and (3) for planning optimal structural health actions, such as e.g., repair and replacement. The value of structural health information presupposes relevance of SHM information for the built environment system performance. A significant value of structural health information has been found for the risk and integrity management of engineering structures.^[6]^[8]^[7]

References

^ Raiffa, Howard, 1924-2016. (2000). Applied statistical decision theory. Schlaifer, Robert. (Wiley classics library ed.). New York: Wiley. ISBN 047138349X. OCLC 43662059.{{cite book}}: CS1 maint: multiple names: authors list (link) CS1 maint: numeric names: authors list (link)
^ Benjamin, J. R. Cornell, C. A. (1970). Probability, Statistics, and Decision for Civil Engineers. McGraw-Hill. OCLC 473420360.{{cite book}}: CS1 maint: multiple names: authors list (link)
^ von Neumann, John; Morgenstern, Oskar (2007-12-31). Theory of Games and Economic Behavior (60th Anniversary Commemorative ed.). Princeton: Princeton University Press. doi:10.1515/9781400829460. ISBN 9781400829460.
^ Pozzi, Matteo; Der Kiureghian, Armen (2011-03-24). Kundu, Tribikram (ed.). "Assessing the value of information for long-term structural health monitoring". Health Monitoring of Structural and Biological Systems 2011. 7984. SPIE: 79842W. Bibcode:2011SPIE.7984E..2WP. doi:10.1117/12.881918. S2CID 3057973.
^ Faber, M; Thöns, S (2013-09-18), "On the value of structural health monitoring", Safety, Reliability and Risk Analysis, CRC Press, pp. 2535–2544, doi:10.1201/b15938-380, ISBN 9781138001237
^ ^a ^b "TU1402 Guidelines - Quantifying the Value of Structural Health Monitoring - COST Action TU 1402". www.cost-tu1402.eu. Retrieved 2019-10-21.
^ ^a ^b Thöns, Sebastian. "Background documentation of the Joint Committee of Structural Safety (JCSS): Quantifying the value of structural health information for decision support" (PDF).
^ Sohn, H.; Farrar, C. R.; Hemez, F. M.; Shunk, D. D.; Stinemates, D. W.; Nadler, B. R.; Czarnecki, J. J. (2001). A Review of Structural Health Monitoring Literature: 1996–2001. Los Alamos: Los Alamos National Laboratory report LA-13070-MS.{{cite book}}: CS1 maint: multiple names: authors list (link)

[1] Raiffa, Howard, 1924-2016. (2000). Applied statistical decision theory. Schlaifer, Robert. (Wiley classics library ed.). New York: Wiley. ISBN 047138349X. OCLC 43662059.{{cite book}}: CS1 maint: multiple names: authors list (link) CS1 maint: numeric names: authors list (link)

[2] Benjamin, J. R. Cornell, C. A. (1970). Probability, Statistics, and Decision for Civil Engineers. McGraw-Hill. OCLC 473420360.{{cite book}}: CS1 maint: multiple names: authors list (link)

[3] von Neumann, John; Morgenstern, Oskar (2007-12-31). Theory of Games and Economic Behavior (60th Anniversary Commemorative ed.). Princeton: Princeton University Press. doi:10.1515/9781400829460. ISBN 9781400829460.

[4] Pozzi, Matteo; Der Kiureghian, Armen (2011-03-24). Kundu, Tribikram (ed.). "Assessing the value of information for long-term structural health monitoring". Health Monitoring of Structural and Biological Systems 2011. 7984. SPIE: 79842W. Bibcode:2011SPIE.7984E..2WP. doi:10.1117/12.881918. S2CID 3057973.

[5] Faber, M; Thöns, S (2013-09-18), "On the value of structural health monitoring", Safety, Reliability and Risk Analysis, CRC Press, pp. 2535–2544, doi:10.1201/b15938-380, ISBN 9781138001237

[:0-6] "TU1402 Guidelines - Quantifying the Value of Structural Health Monitoring - COST Action TU 1402". www.cost-tu1402.eu. Retrieved 2019-10-21.

[:1-7] Thöns, Sebastian. "Background documentation of the Joint Committee of Structural Safety (JCSS): Quantifying the value of structural health information for decision support" (PDF).

[8] Sohn, H.; Farrar, C. R.; Hemez, F. M.; Shunk, D. D.; Stinemates, D. W.; Nadler, B. R.; Czarnecki, J. J. (2001). A Review of Structural Health Monitoring Literature: 1996–2001. Los Alamos: Los Alamos National Laboratory report LA-13070-MS.{{cite book}}: CS1 maint: multiple names: authors list (link)

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