TECHNICAL PAPERS
Jun 1, 2000

Optimal Life-Cycle Costing with Partial Observability

Publication: Journal of Infrastructure Systems
Volume 6, Issue 2

Abstract

Optimal costing of structures requires taking into account lifetime management (inspection and maintenance) costs in addition to initial construction cost. Recently published papers on lifetime costing have used Markov decision process models to incorporate management policies into structural reliability analysis. In this paper, an optimization model is described based on partially observable Markov decision processes. The model depicts varying levels of uncertainty inherent in differing inspection techniques. The costs and inherent uncertainties of these techniques are related to environmental degradation from fatigue and corrosion processes. The mathematical approach leads to a management policy that explicitly includes frequency and type of inspection and extent of repair. The model is demonstrated in an example involving the management of a steel girder highway bridge.

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References

1.
Albrecht, P., and Naeemi, A. H. (1984). “Performance of weathering steel in bridges.” NCHRP Rep. 272, Transportation Research Board, Washington, D.C.
2.
Albrecht, P., and Yamada, K. (1977). “Rapid calculation of stress intensity factors.”J. Struct. Div., ASCE, 103(2), 377–389.
3.
American Association of State Highway and Transformation Officials (AASHTO). ( 1989). Standard specifications for highway bridges. Washington, D.C.
4.
Barsom, J. M. (1993). “Structural problems in search of fracture mechanics solutions.” Fracture mechanics: 23rd Symp., ASTM STP 1189, R. Chona, ed., ASTM, West Conshohocken, Pa., 5–34.
5.
Beck, J. L., and Katafygiotis, L. S. (1998). “Updating models and their uncertainties. I: Bayesian statistical framework.”J. Engrg. Mech., ASCE, 124(4), 455–461.
6.
Ben-Akiva, M., Humplick, F., Madanat, S., and Ramaswamy, R. (1993). “Infrastructure management under uncertainty: Latent performance approach.”J. Transp. Engrg., ASCE, 119(1), 43–58.
7.
Ben-Akiva, M., Humplick, F., Madanat, S., and Ramaswamy, R. (1991). “Latent performance approach to infrastructure management.” Transp. Res. Record 1311, Washington, D.C., 188–195.
8.
Ben-Akiva, M., and R. Ramaswamy. (1993). “An approach for predicting latent infrastructure facility deterioration.” Transp. Sci., 27(2), 174–193.
9.
Berke, N. S., and Hicks, M. C. (1994). “Predicting chloride profiles in concrete.” Corrosion, 50(3), 234–239.
10.
Bogdanoff, J. L., and Kozin, F. (1985). Probabilistic models of cumulative damage, Wiley, New York.
11.
Cassandra, A. (1994). “Optimal policies for partially observable Markov decision processes.” Tech. Rep. CS-94-14, Dept. of Comp. Sci., Brown University, Providence, R.I.
12.
Cesare, M. A., Santamarina, J. C., Turstra, C. J., and Vanmarcke, E. (1992). “Modeling bridge deterioration with Markov chains.”J. Transp. Engrg., ASCE, 118(6), 821–833.
13.
Chen, H.-J., and Perl, J. (1988). “Application of the microeconomics concepts of production and cost functions to the analysis of highway maintenance efficiency.” Transp. Res. Record 1215, Washington, D.C., 43–52.
14.
Cheng, H.-T. ( 1988). “Algorithms for partially observable Markov decision processes.” PhD thesis, University of British Columbia, Vancouver.
15.
Chua, K. H., and Monismith, C. L. (1994). “Mechanistic model for transition probabilities.”J. Struct. Engrg., ASCE, 120(1), 144–159.
16.
Congleton, J., and Craig, I. H. ( 1982). “Corrosion fatigue.” Corrosion processes, R. N. Parkins, ed., Applied Science Publishers, New York.
17.
DeStefano, P. D., and Grivas, D. A. (1998). “Method for estimating transition probability in bridge deterioration models.”J. Infrastruct. Sys., ASCE, 4(2), 56–62.
18.
Ellis, H., Jiang, M., and Corotis, R. B. (1995). “Inspection, maintenance, and repair with partial observability.”J. Infrastruct. Sys., ASCE, 1(2), 92–99.
19.
Estes, A. C., Frangopol, D. M., and Lin, K.-Y. (1997). “Minimum expected life-cycle cost design for bridges.” Proc., 7th IFIP WG7.5 Working Conf., Reliability and Optimization of Struct. Sys., Pergamon, Terrytown, N.Y., 133–140.
20.
Fisher, J. W. (1984). Fatigue and fracture in steel bridges—Case studies. Wiley, New York.
21.
Fisher, J. W., Nussbaumber, A., Keating, P. B., and Yen, B. T. (1993). “Resistance of welded details under variable amplitude long-life fatigue loading.” NCHRP Rep. 354, Transportation Research Board, Washington, D.C.
22.
Frankel, E. G. (1984). System reliability and risk analysis, Martinus Nijhoff, Dordrecht, The Netherlands.
23.
Golabi, K., and Thompson, P. ( 1990). “A network optimization system for maintenance and improvement of California's bridges.” Bridge evaluation, repair and rehabilitation, A. S. Nowak, ed., Kluwer, Dordrecht, The Netherlands, 41–55.
24.
Glass, G. K., Zhang, J.-Z., and Buenfeld, N. R. (1995). “Chloride ion barrier properties of small electric fields in the protection of steel in concrete.” Corrosion, 51(9), 721–726.
25.
Harlow, D. G., and Wei, R. P. (1994). “Probability approach for prediction of corrosion and corrosion fatigue life.” AIAA J., 32(10), 2073–2079.
26.
Hearn, G., and Shim, H.-S. (1998). “Integration of bridge management systems and nondestructive evaluations.”J. Infrastruct. Sys., ASCE, 4(2), 49–55.
27.
Humplick, F. (1992a). “Highway pavement distress evaluation: Modeling measurement error.” Transp. Res.-B, 26B(2), 135–154.
28.
Humplick, F. (1992b). “Identifying error-generating factors in infrastructure condition evaluations.” Transp. Res. Record 1344, Washington, D.C., 106–115.
29.
Jessop, T. J., Mudge, P. J., and Harrison, J. D. (1981). “Ultrasonic measurement of welded flaw size.” NCHRP Rep. 242, Transportation Research Board, Washington, D.C.
30.
Jiang, M. ( 1995). “Partially observable Markov decision process models for structural management policies and design.” PhD thesis, Dept. of Civ. Engrg., The Johns Hopkins University, Baltimore.
31.
Jiang, X.-C., and Staehle, R. W. (1997). “On the activation energy in the chemical-mechanical correlation model.” Corrosion, 53(11), 869–879.
32.
Kayser, J. R. ( 1988). “The effects of corrosion on the reliability of steel girder bridges.” PhD thesis, University of Michigan, Ann Arbor.
33.
Littman, M. L. (1994). “The witness algorithm: Solving partially observable Markov decision processes.” Tech. Rep. CS-94-40, Dept. of Comp. Sci., Brown University, Providence, R.I.
34.
Lovejoy, W. S. (1991). “Computationally feasible bounds for partially observed Markov decision processes.” Operations Res., 39(1), 162–175.
35.
Lovejoy, W. S. (1993). “Suboptimal policies with bounds for parameter adaptive decision processes.” Operations Res., 41(3), 583–599.
36.
Madanat, S. (1993a). “Incorporating inspection decisions in pavement management.” Transp. Res., 27B(6), 425–438.
37.
Madanat, S. (1993b). “Optimal infrastructure management decisions under uncertainty.” Transp. Res. C, 1C(1), 77–88.
38.
Madanat, S., and Ben-Akiva, M. (1994). “Optimal inspection and repair policies for infrastructure facilities.” Transp. Sci., 28(1), 55–62.
39.
Madanat, S. M., Karlaftis, M. G., and McCartley, P. S. (1997). “Probabilistic infrastructure deterioration models with panel data.”J. Infrastruct. Sys., ASCE, 3(1), 4–9.
40.
Madanat, S., Mishalani, R., and Wan Ibrahim, W.-H. (1995). “Estimation of infrastructure transition probabilities from condition rating data.”J. Infrastruct. Sys., ASCE, 1(2), 120–125.
41.
Madsen, H. O., Sorensen, J. D., and Olesen, R. ( 1990). “Optimal inspection planning for fatigue damage of offshore structures.” Struct. safety and reliability, A. H.-S. Ang, M. Shinozuka, and G. I. Schuëller, eds., ASCE, New York, 2099–2106.
42.
Monahan, G. E. (1982). “A survey of partially observable Markov decision processes: Theory, models and algorithms.” Mgmt. Sci., 28(1), 1–16.
43.
Nowak, A. S. (1993). “Calibration of LRFD bridge design code.” Final Rep. Prepared for NCHRP, TRB, National Research Council, Dept. of Civ. Engrg., University of Michigan, Ann Arbor.
44.
Scherer, W. T., and Glagola, D. M. (1994). “Markovian models for bridge maintenance management.”J. Transp. Engrg., ASCE, 120(1), 37–51.
45.
Schilling, C. G., Klippstein, K. H., Barsom, J. M., and Blake, G. T. (1978). “Fatigue of welded steel bridge members under variable-amplitude loadings,” NCHRP Rep. 188, TRB, National Research Council, Washington, D.C.
46.
Sobanjo, J. O., Stukhart, G., and James, R. W. (1994). “Evaluation of projects for rehabilitation of highway bridges.”J. Struct. Engrg., ASCE, 120(1), 81–99.
47.
Soltani, M., and Corotis, R. B. (1988). “Failure cost design of structural systems.” Struct. Safety, Amsterdam, 5(4), 238–252.
48.
Sommer, A. M., Nowak, A. S., and Thoft-Christensen, P. (1993). “Probability-based bridge inspection strategy.”J. Struct. Engrg., ASCE, 119(12), 3520–3536.
49.
Sondik, E. J. (1978). “The optimal control of partially observable Markov process over infinite horizon: Discounted costs.” Operations Res., 26(2), 282–304.
50.
Sorensen, J. D., and Faber, M. H. ( 1991). “Optimal inspection and repair strategies for structural systems.” Reliability and optimization of structural systems, P. Thoft-Christensen and R. Rackwitz, eds., Springer, Berlin, 383–394.
51.
Tabsh, S. W. (1994). “Simple live load distribution factors for girder bridges.” Proc., Struct. Congr. XII, N. C. Baker, and B. J. Goodno, eds., ASCE, New York, 497–502.
52.
Tao, Z., Corotis, R. B., and Ellis, J. H. (1995). “Reliability-based structural design with Markov decision processes.”J. Struct. Engrg., ASCE, 121(6), 971–980.
53.
Thoft-Christensen, P., and Sørensen, J. D. (1987). “Optimal strategy for inspection and repair of structural systems.” Civ. Engrg. Sys., 4(2), 94–100.
54.
Wirsching, P. H., and Ortiz, K. (1990). “Optimal economic strategies with considerations of reliability of fatigue-sensitive structural systems.” Struct. Safety, Amsterdam, Vol. 7, 199–206.
55.
Yazdani, N., and Albrecht, P. (1987). “Risk analysis of fatigue failure of highway steel bridges.”J. Struct. Engrg., ASCE, 113(3), 483–500.
56.
Zhao, Z., Haldar, A., and Breen, Jr., F. L. (1994). “Fatigue-reliability evaluation of steel bridges.”J. Struct. Engrg., ASCE, 120(5), 1608–1623.

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Go to Journal of Infrastructure Systems
Journal of Infrastructure Systems
Volume 6Issue 2June 2000
Pages: 56 - 66

History

Received: Oct 15, 1996
Published online: Jun 1, 2000
Published in print: Jun 2000

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Authors

Affiliations

Associate Member, ASCE
Fellow, ASCE
Associate Member, ASCE
Sr. Des. Engr., Caterpillar Inc., 100 NE Adams, AB8700, Peoria, IL 61629.
Dean, Coll. of Engrg. and Appl. Sci., Campus Box 422, Univ. of Colorado, Boulder, CO 80309.
Chair., Dept. of Geography and Envir. Engrg., Johns Hopkins Univ., Baltimore, MD 21218.

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