Efficient Tools for Managing Uncertainties in Design and Operation of Engineering Structures
Actual load, material characteristics and other
quantities often differ from the design values. This can cause worse
function, shorter life or failure of a civil engineering structure, a
machine, vehicle or another appliance. The paper shows main causes
of the uncertainties and deviations and presents a systematic
approach and efficient tools for their elimination or mitigation of
consequences. Emphasis is put on the design stage, which is most
important for reliability ensuring. Principles of robust design and
important tools are explained, including FMEA, sensitivity analysis
and probabilistic simulation methods. The lifetime prediction of
long-life objects can be improved by long-term monitoring of the
load response and damage accumulation in operation. The condition
evaluation of engineering structures, such as bridges, is often based
on visual inspection and verbal description. Here, methods based on
fuzzy logic can reduce the subjective influences.
[1] IEC 61025. Fault Tree Analysis. 2006.
[2] IEC 60812. Analysis techniques for system reliability - Procedure for
failure mode and effects analysis (FMEA). 2006.
[3] G. Taguchi, Taguchi on Robust Technology Development. ASME Press,
New York, 1993.
[4] W. Y. Fowlkes, and C. M. Creveling, Engineering methods for robust
product design. (Using Taguchi methods in technology and product
development.) Addison-Wesley, New York, 1995.
[5] D. Novák, B. TeplÛ, and N. Shiraishi, Sensitivity Analysis of Structures:
A Review. Proc. Int. Conf. CIVIL COMP'93, August 1993, Edinburgh,
Scotland, pp. 201-207.
[6] J. Menčík, Reliability-based parameter optimization and tolerancing in
structural design. In: Structural Safety and Reliability (ICOSSAR '01,
Newport Beach). Editors: R.B. Corotis, G.I. Schuëller, and M.
Shinozuka. A.Balkema Publishers, Lisse, 2001. Abstract: p.188, full text
CD-ROM.
[7] P. Marek, M. Guštar, and T. Anagnos, Simulation-Based Reliability
Assessment for Structural Engineers, CRC Press, Inc., Boca Raton,
Florida, 1995.
[8] P. Marek and M. Guštar, Ant-Hill and M-Star programs for Monte Carlo
simulations, Prague, 1995 - 2006. www.noise.cz/sbra .
[9] D. Novák et al., FREET - Feasible Reliability Engineering Efficient
Tool, Program documentation. Brno University of Technology, Faculty
of Civil Engineering, Institute of Structural Mechanics/─îervenka
Consulting, Prague, 2002 - 2009. www.freet.cz .
[10] VaP - Variable Processor, software. Petschacher Consulting,
Feldkirchen, Austria, 2003.
[11] R. L. Iman and W. J. Conover, "Small sample sensitivity analysis
technique for computer models, with an application to risk assessment."
Communications in Statistics A9-(17), pp. 1749- 1874, 1980.
[12] A. Florian, Modern numerical simulation methods - an overview.
Stavební obzor 7, 1998, No. 2, pp. 60-64.
[13] A. H. S. Ang and W. H. Tang, Probabilistic concepts in engineering
planning and design. John Wiley & Sons, New York, 1975.
[14] ISO 12491. Statistical methods for quality control of building materials
and components. 1997.
[15] J. Menčík, The use of Bayesian methods for quality and reliability
assessment in civil engineering. Proc. III. Int. Sci. Conf. Quality and
Reliability in Building Industry. Levo─ìa, October 22-24, 2003.
Technical University of Košice, 2003, pp. 379 - 384.
[16] L. Beran, Reliability and load carrying capacity of existing steel railway
bridge structures. PhD thesis. University of Pardubice, Pardubice, 2004.
[17] B. Culek, Jr. and B. Culek, Probabilistic assessment of the lifetime of the
railway steel bridge across river Labe. 24th Danubia-Adria Symposium
on Developments in Experimental Mechanics. Sibiu, 19-22 September
2007. University Lucian Blaga, Sibiu, 2007, pp. 59 - 60.
[18] J. Menčík, H. Šertler, L. Beran, and B. Culek, jr., Methods for improved
assessment of load-carrying kapacity and fatigue life of existing steel
bridges In: G. Augusti, G. I. Schueller, and M. Ciampoli (editors): Safety
and Reliability of Engineering Structures and Systems (ICOSSAR 2005),
Rome. Millpress, Rotterdam, 2005, p. 126 + CD ROM.
[19] Fuzzy Logic Toolbox User's Guide. The MathWorks, Inc., 2008.
http://www.mathworks.com/access/helpdesk/help/pdf_doc/fuzzy/fuzzy.p
df
[20] Z. Kala, Fuzzy-random analysis of steel structures. Engineering
Mechanics, 14, 2007, No. 1, pp. 1-12.
[21] B. Möller and M. Beer, Fuzzy randomness: uncertainty in civil
engineering and computational mechanics. Springer Verlag, Berlin -
Heidelberg, 2004.
[22] P. Rudolf, Reliability and service life of existing bridges and their
assessment using modern computational tools. PhD thesis, University of
Pardubice, Pardubice, 2009.
[1] IEC 61025. Fault Tree Analysis. 2006.
[2] IEC 60812. Analysis techniques for system reliability - Procedure for
failure mode and effects analysis (FMEA). 2006.
[3] G. Taguchi, Taguchi on Robust Technology Development. ASME Press,
New York, 1993.
[4] W. Y. Fowlkes, and C. M. Creveling, Engineering methods for robust
product design. (Using Taguchi methods in technology and product
development.) Addison-Wesley, New York, 1995.
[5] D. Novák, B. TeplÛ, and N. Shiraishi, Sensitivity Analysis of Structures:
A Review. Proc. Int. Conf. CIVIL COMP'93, August 1993, Edinburgh,
Scotland, pp. 201-207.
[6] J. Menčík, Reliability-based parameter optimization and tolerancing in
structural design. In: Structural Safety and Reliability (ICOSSAR '01,
Newport Beach). Editors: R.B. Corotis, G.I. Schuëller, and M.
Shinozuka. A.Balkema Publishers, Lisse, 2001. Abstract: p.188, full text
CD-ROM.
[7] P. Marek, M. Guštar, and T. Anagnos, Simulation-Based Reliability
Assessment for Structural Engineers, CRC Press, Inc., Boca Raton,
Florida, 1995.
[8] P. Marek and M. Guštar, Ant-Hill and M-Star programs for Monte Carlo
simulations, Prague, 1995 - 2006. www.noise.cz/sbra .
[9] D. Novák et al., FREET - Feasible Reliability Engineering Efficient
Tool, Program documentation. Brno University of Technology, Faculty
of Civil Engineering, Institute of Structural Mechanics/─îervenka
Consulting, Prague, 2002 - 2009. www.freet.cz .
[10] VaP - Variable Processor, software. Petschacher Consulting,
Feldkirchen, Austria, 2003.
[11] R. L. Iman and W. J. Conover, "Small sample sensitivity analysis
technique for computer models, with an application to risk assessment."
Communications in Statistics A9-(17), pp. 1749- 1874, 1980.
[12] A. Florian, Modern numerical simulation methods - an overview.
Stavební obzor 7, 1998, No. 2, pp. 60-64.
[13] A. H. S. Ang and W. H. Tang, Probabilistic concepts in engineering
planning and design. John Wiley & Sons, New York, 1975.
[14] ISO 12491. Statistical methods for quality control of building materials
and components. 1997.
[15] J. Menčík, The use of Bayesian methods for quality and reliability
assessment in civil engineering. Proc. III. Int. Sci. Conf. Quality and
Reliability in Building Industry. Levo─ìa, October 22-24, 2003.
Technical University of Košice, 2003, pp. 379 - 384.
[16] L. Beran, Reliability and load carrying capacity of existing steel railway
bridge structures. PhD thesis. University of Pardubice, Pardubice, 2004.
[17] B. Culek, Jr. and B. Culek, Probabilistic assessment of the lifetime of the
railway steel bridge across river Labe. 24th Danubia-Adria Symposium
on Developments in Experimental Mechanics. Sibiu, 19-22 September
2007. University Lucian Blaga, Sibiu, 2007, pp. 59 - 60.
[18] J. Menčík, H. Šertler, L. Beran, and B. Culek, jr., Methods for improved
assessment of load-carrying kapacity and fatigue life of existing steel
bridges In: G. Augusti, G. I. Schueller, and M. Ciampoli (editors): Safety
and Reliability of Engineering Structures and Systems (ICOSSAR 2005),
Rome. Millpress, Rotterdam, 2005, p. 126 + CD ROM.
[19] Fuzzy Logic Toolbox User's Guide. The MathWorks, Inc., 2008.
http://www.mathworks.com/access/helpdesk/help/pdf_doc/fuzzy/fuzzy.p
df
[20] Z. Kala, Fuzzy-random analysis of steel structures. Engineering
Mechanics, 14, 2007, No. 1, pp. 1-12.
[21] B. Möller and M. Beer, Fuzzy randomness: uncertainty in civil
engineering and computational mechanics. Springer Verlag, Berlin -
Heidelberg, 2004.
[22] P. Rudolf, Reliability and service life of existing bridges and their
assessment using modern computational tools. PhD thesis, University of
Pardubice, Pardubice, 2009.
@article{"International Journal of Mechanical, Industrial and Aerospace Sciences:49214", author = "J. Menčík", title = "Efficient Tools for Managing Uncertainties in Design and Operation of Engineering Structures", abstract = "Actual load, material characteristics and other
quantities often differ from the design values. This can cause worse
function, shorter life or failure of a civil engineering structure, a
machine, vehicle or another appliance. The paper shows main causes
of the uncertainties and deviations and presents a systematic
approach and efficient tools for their elimination or mitigation of
consequences. Emphasis is put on the design stage, which is most
important for reliability ensuring. Principles of robust design and
important tools are explained, including FMEA, sensitivity analysis
and probabilistic simulation methods. The lifetime prediction of
long-life objects can be improved by long-term monitoring of the
load response and damage accumulation in operation. The condition
evaluation of engineering structures, such as bridges, is often based
on visual inspection and verbal description. Here, methods based on
fuzzy logic can reduce the subjective influences.", keywords = "Design, fuzzy methods, Monte Carlo, reliability,robust design, sensitivity analysis, simulation, uncertainties.", volume = "4", number = "2", pages = "128-6", }
