The optimal design of offshore structures is formulated as a decision theoretical problem. The objective is to maximize the expected net present value of the life cycle benefit. The general optimization problem is simplified by taking into account the cost impacts of a possible reconstruction of the structure. The analytical solution to this problem has been derived for the case, where failure events follow a stationary Poisson process. The life cycle benefit is formulated in terms of the production profile, the design and construction costs, failure costs and reconstruction costs. In order to assess the effect of potential loss of lives, the costs of fatalities are included applying the concept of the Implied Costs of Averting a Fatality ICAF. The suggested approach to optimal design, which can be applied for any type of offshore structure, is exemplified considering the special case of steel structures. Here, it is standard to represent the ultimate structural capacity in terms of the Reserve Strength Ratio RSR. For the purpose of illustration, the relation between material usage and RSR, which is valid for monopod structures, is applied. Optimal RSR’s and corresponding annual failure rates are assessed for both manned and unmanned structures covering a wide range of different realistic ratios between the potential revenues and costs for construction, failure and reconstruction.

Issue Section:
Technical Papers
Keywords:
design, offshore installations, civil engineering
Topics:
Construction, Design, Failure, Ocean engineering, Cycles
1.
Stahl, B., Aune, S., Gebara, J. M., and Cornell, C. A., 1998, “Acceptance Criteria for Offshore Platforms,” 1463, Proc. 17th Int. Conference on Offshore Mechanic and Artic Engineering, ASME.
2.
Skjong, R., and Ronold, K. O., 1998, “Societal Indicators and Risk Acceptance,” 1488, Proc. 17th Int. Conference on Offshore Mechanic and Artic Engineering, ASME.
3.
Vinnem, J. E., 1996, “Quantified Risk Assessment for Offshore Petroleum Installations—a Decision Support Tool,” Kompendium UK-97-61, Department of Marine Structures, Norwegian University of Science and Technology, Trondheim, Norway.
4.
Pinna R., Ronalds, B. F., and Andrich, M. A., 2001, “Cost Effective Design for Australian Monopods,” 2121, Proc. 20th Int. Conference on Offshore Mechanic and Artic Engineering, ASME.
5.
Nathwani, J. S., Lind, N. C., and Pandey, M. D., 1997, Affordable Safety by Choice: The Life Quality Method, Institute for Risk Research, University of Waterloo, Canada.
6.
Rackwitz, R., 2001, “A New Approach for Setting Target Reliabilities,” Proc. Int. Conference on Safety, Risk and Reliability-Trends in Engineering, IABSE.
7.
Rosenblueth
,
E.
, and
Mendoza
,
E.
,
1997
, “
Reliability Optimization in Isostatic Structures
,”
J. Eng. Mech. Div.
,
97
(
EM6
), pp.
1625
–
1642
.
8.
Rackwitz
,
R.
,
2000
, “
Optimization—the Basis of Code-Making and Reliability Verification
,”
Struct. Safety
,
22
, pp.
27
–
60
.
9.
Almlund, J., 1991, “Life Cycle Model for Offshore Installations for Use in Prospect Evaluation,” Ph.D.-Thesis, Dept. of Building Technology and Structural Engineering, University of Aalborg, Denmark.
10.
Sorensen
,
J. D.
,
Kroon
,
I. B.
, and
Faber
,
M. H.
,
1994
, “
Optimal Reliability-Based Code Calibration
,”
Struct. Safety
,
15
, pp.
197
–
208
.
11.
Raiffa, H., and Schlaifer, R., 1961, Applied statistical decision theory, Harvard Business School.
12.
Benjamin, J. R., and Cornell, C. A., 1970, Probability Statistics and Decision for Civil Engineers, McGraw-Hill.
13.
Faber, M. H., and Sorensen, J. D., 1999, “Aspects of Inspection Planning—Quality and Quantity,” Proc. ICASP8, Sydney.
14.
Parzen, E., 1965, Stochastic Processes, Holden-Day, San Francisco.
15.
Lind, N. C., 1994, “Target Reliability Levels From Social Indicators,” Proc. of ICOSSAR’93, Balkema, Rotterdam, pp. 1897–1904.
Copyright © 2004
 by ASME
You do not currently have access to this content.