Skip to main content

Modeling and Processing of Uncertainty in Civil Engineering by Means of Fuzzy Randomness

  • Conference paper
  • First Online:
Managing Safety of Heterogeneous Systems

Part of the book series: Lecture Notes in Economics and Mathematical Systems ((LNE,volume 658))

Abstract

The paper focuses on the adequate quantification of uncertainty which usually influences all numerical simulations of structures in the field of civil engineering. Fuzzy randomness provides adequate modeling of specific uncertainty phenomena, not only in the field of civil engineering. In this paper, approaches for modeling of data and model uncertainty by means of convex fuzzy random variables, including fuzzy variables and random variables as special cases, are presented. Numerical processing of those uncertain variables succeeds with the help of fuzzy stochastic structural analysis. By means of fuzzy stochastic analysis, it is possible to map fuzzy random input variables onto fuzzy random result variables. Thus, safety assessment of structures under precise distinction of the different kinds of uncertainty is feasible. The principal approaches are illustrated by means of two model problems in the field of civil engineering in order to show the significance and the applicability of the methods.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Feng, Y. (2001). The variance and covariance of fuzzy random variables and their applications. Fuzzy Sets and Systems, 120, 487–497.

    Article  Google Scholar 

  • Franke, D., Arnold, M., Bartl, U., & Vogt, L. (2003). Erddruckmessungen an der Kelleraußenwand eines mehrgeschossigen Massivbaus. Bauingenieur, 78, 125–130.

    Google Scholar 

  • Klir, G. J. (2006). Uncertainty and Information: Foundations of Generalized Information Theory. Hoboken: Wiley-Interscience.

    Google Scholar 

  • Körner, R. (1997). Linear Models with Random Fuzzy Variables. Bergakademie Freiberg: Dissertation.

    Google Scholar 

  • Krätschmer, V. (2001). A unified approach to fuzzy random variables. Fuzzy Sets and Systems, 123, 1–9.

    Article  Google Scholar 

  • Kwakernaak, H. (1978). Fuzzy random variables – I. Definitions and theorems. Information Sciences, 15, 1–29.

    Google Scholar 

  • Möller, B., & Beer, M. (2004). Fuzzy Randomness – Uncertainty in Civil Engineering and Computational Mechanics. Berlin: Springer.

    Google Scholar 

  • Möller, B., & Beer, M. (2008). Engineering computation under uncertainty – Capabilities of non-traditional models. Computers & Structures, 86, 1024–1041.

    Article  Google Scholar 

  • Möller, B., Beer, M., Graf, W., & Sickert, J.-U. (2006). Time-dependent reliability of textile strengthened RC structures under consideration of fuzzy randomness. Computers & Structures, 84, 585–903.

    Article  Google Scholar 

  • Möller, B., Graf, W., & Kluger, J. (1997). Endochronic material modelling in nonlinear FE-analysis of folded plates. In P. Anagnostopoulos, G. M. Carlomagno, & C. A. Brebbia (Eds.), CMEM VIII, Computational Mechanics Publ., 97–106. Southampton.

    Google Scholar 

  • Möller, B., Graf, W., Hoffmann, A., & Steinigen, F. (2005). Numerical simulation of RC structures with textile reinforcement. Computers & Structures, 83, 1659–1688.

    Article  Google Scholar 

  • Möller, B., & Reuter, U. (2007). Uncertainty Forecasting in Engineering. Berlin: Springer.

    Google Scholar 

  • Ortlepp, R., Weiland, S., & Curbach, M. (2008). Restoration of a hypar concrete shell using carbon-fibre textile reinforcement concrete. In M.C. Limbachiya, & H.Y. Kew (Eds.), Proceedings of the International Conference Excellence in Concrete Construction Through Innovation, pp. 357–364. London: Taylor & Francis.

    Google Scholar 

  • Pannier, S., Sickert, J.-U., & Graf, W. (2009). Patchwork approximation scheme for reliability assessment and optimization. In H. Furuta, D. M. Frangopol, M. Shinozuka (Eds.), Safety, Reliability and Risk of Structures, Infrastructures and Engineering Systems, Proceedings of the 10th Int. Conference on Structural Safety and Reliability, 482–489. London: Taylor & Francis.

    Google Scholar 

  • Papadrakakis, M., Papadopoulos, V., & Lagaros, N. D. (1996). Structural reliability analysis of elastic-plastic structures using neural networks and Monte Carlo simulation. Computer Methods in Applied Mechanics and Engineering, 136, 145–163.

    Article  Google Scholar 

  • Puri, M. L., & Ralescu, D. A. (1986). Fuzzy random variables. Journal of Mathematical Analysis and Applications, 114, 409–422.

    Article  Google Scholar 

  • Reuter, U. (2008). Application of non-convex fuzzy variables to fuzzy structural analysis. In D. Dubois, et al. (Eds.), Soft Methods for Handling Variability and Imprecision, Advances in Soft Computing vol. 48, pp. 369–375. Berlin: Springer.

    Chapter  Google Scholar 

  • Sickert, J.-U. (2005). Fuzzy Random Functions and their Application in Structural Analysis and Safety Assessment (in german). TU Dresden, Veröffentlichungen Institut für Statik und Dynamik der Tragwerke, Heft 9, Dresden: Dissertation.

    Google Scholar 

  • Thoft-Christensen, P., & Baker, M.J. (1982). Structural Reliability Theory and Its Applications. Berlin: Springer.

    Book  Google Scholar 

  • Viertl, R. (2008). Fuzzy models for precision measurements. Mathematics and Computers in Simulation, 79, 874–878.

    Article  Google Scholar 

  • Viertl, R. (2011). Statistical Methods for Fuzzy Data. Chichester: Wiley.

    Book  Google Scholar 

  • Walley, P. (1991). Statistical Reasoning with Imprecise Probabilities. New York: Chapman Hall.

    Google Scholar 

  • Wang, G., & Zhang, Y. (1992). The theory of fuzzy stochastic processes. Fuzzy Sets and Systems, 51, 161–178.

    Article  Google Scholar 

  • Zimmermann, H.-J. (1992). Fuzzy Set Theory and Its Applications. Boston: Kluwer.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Uwe Reuter .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Reuter, U., Sickert, JU., Graf, W., Kaliske, M. (2012). Modeling and Processing of Uncertainty in Civil Engineering by Means of Fuzzy Randomness. In: Ermoliev, Y., Makowski, M., Marti, K. (eds) Managing Safety of Heterogeneous Systems. Lecture Notes in Economics and Mathematical Systems, vol 658. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22884-1_14

Download citation

Publish with us

Policies and ethics