Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Multidisciplinary System Modeling and Optimization Read chapter Read first chapter

2020 | OriginalPaper | Chapter

6. Uncertainty Propagation for Multidisciplinary Problems

Authors : Loïc Brevault, Mathieu Balesdent

Published in: Aerospace System Analysis and Optimization in Uncertainty

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

In Chapter 3, several uncertainty propagation techniques for black-box functions have been introduced. In order to take into account the specific features of multidisciplinary design problems, these methodologies have to be adapted accordingly. This chapter reviews various alternatives described in the literature to efficiently propagate uncertainty in the case of coupled multidisciplinary systems (Figure 6.1).

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter Overview of Problem Formulations and Optimization Algorithms in the Presence of Uncertainty
next chapter Uncertainty-Based Multidisciplinary Design Optimization (UMDO)
Literature
Ahn, J. and Kwon, J.-H. (2004). Sequential approach to reliability analysis of multidisciplinary analysis systems. Structural and Multidisciplinary Optimization, 28(6):397–406.CrossRef
Amaral, S., Allaire, D., and Willcox, K. (2014). A decomposition-based approach to uncertainty analysis of feed-forward multicomponent systems. International Journal for Numerical Methods in Engineering, 100(13):982–1005.MathSciNetCrossRef
Arnst, M., Ghanem, R., Phipps, E., and Red-Horse, J. (2012). Dimension reduction in stochastic modeling of coupled problems. International Journal for Numerical Methods in Engineering, 92(11):940–968.MathSciNetCrossRef
Arnst, M., Ghanem, R., Phipps, E., and Red-Horse, J. (2014). Reduced chaos expansions with random coefficients in reduced-dimensional stochastic modeling of coupled problems. International Journal for Numerical Methods in Engineering, 97(5):352–376.MathSciNetCrossRef
Arnst, M., Soize, C., and Ghanem, R. (2013). Hybrid sampling/spectral method for solving stochastic coupled problems. SIAM/ASA Journal on Uncertainty Quantification, 1(1):218–243.MathSciNetCrossRef
Chaudhuri, A., Lam, R., and Willcox, K. (2017). Multifidelity uncertainty propagation via adaptive surrogates in coupled multidisciplinary systems. AIAA Journal, pages 235–249.
Chiralaksanakul, A. and Mahadevan, S. (2007). Decoupled approach to multidisciplinary design optimization under uncertainty. Optimization and Engineering, 8(1):21–42.MathSciNetCrossRef
Du, X. (2002). Efficient methods for engineering design under uncertainty. PhD thesis, Graduate College, University of Illinois at Chicago.
Du, X. (2008). Unified uncertainty analysis by the first order reliability method. Journal of Mechanical Design, 130(9):091401.CrossRef
Du, X. and Chen, W. (2002a). Collaborative reliability analysis for multidisciplinary systems design. In 9th AIAA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, Atlanta, GA, USA.
Du, X. and Chen, W. (2002b). Efficient uncertainty analysis methods for multidisciplinary robust design. AIAA Journal, 40(3):545–552.CrossRef
Du, X. and Chen, W. (2005). Collaborative reliability analysis under the framework of multidisciplinary systems design. Optimization and Engineering, 6(1):63–84.MathSciNetCrossRef
Felippa, C. A., Park, K., and Farhat, C. (2001). Partitioned analysis of coupled mechanical systems. Computer methods in applied mechanics and engineering, 190(24–25):3247–3270.CrossRef
Friedman, S., Isaac, B., Ghoreishi, S. F., and Allaire, D. L. (2018). Efficient decoupling of multiphysics systems for uncertainty propagation. In 2018 AIAA Non-Deterministic Approaches Conference, Kissimmee, FL, USA.
Geman, S. and Geman, D. (1984). Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Transactions on pattern analysis and machine intelligence, (6):721–741.CrossRef
Ghoreishi, S. and Allaire, D. (2017). Adaptive uncertainty propagation for coupled multidisciplinary systems. AIAA Journal, pages 3940–3950.
Ghoreishi, S. F. (2016). Uncertainty analysis for coupled multidisciplinary systems using sequential importance resampling. Master’s thesis, Texas A&M University, College Station.
Ghosh, S. and Mavris, D. N. (2016). A Methodology for Probabilistic Analysis of Distributed Multidisciplinary Architecture (PADMA). In 17th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Washington, DC, USA.
Glynn, P. W. and Iglehart, D. L. (1989). Importance sampling for stochastic simulations. Management Science, 35(11):1367–1392.MathSciNetCrossRef
Gu, X., Renaud, J. E., Batill, S. M., Brach, R. M., and Budhiraja, A. S. (2000). Worst case propagated uncertainty of multidisciplinary systems in robust design optimization. Structural and Multidisciplinary Optimization, 20(3):190–213.CrossRef
Gu, X. S., Renaud, J. E., and Penninger, C. L. (2006). Implicit uncertainty propagation for robust collaborative optimization. Journal of Mechanical Design, 128(4):1001–1013.CrossRef
Guo, J. and Du, X. (2010). Reliability analysis for multidisciplinary systems with random and interval variables. AIAA Journal, 48(1):82–91.CrossRef
Haldar, A. and Mahadevan, S. (2000). Probability, reliability, and statistical methods in engineering design, volume 1. Wiley New York.
Hastings, W. K. (1970). Monte Carlo sampling methods using Markov chains and their applications. Oxford University Press.CrossRef
Isaac, B., Friedman, S., and Allaire, D. L. (2018). Efficient approximation of coupling variable fixed point sets for decoupling multidisciplinary systems. In 2018 AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, Kissimmee, FL, USA.
Jiang, Z., Chen, S., Apley, D. W., and Chen, W. (2015). Resource allocation for reduction of epistemic uncertainty in simulation-based multidisciplinary design. In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Boston, MA, USA.
Jiang, Z., Li, W., Apley, D. W., and Chen, W. (2014). A system uncertainty propagation approach with model uncertainty quantification in multidisciplinary design. In ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Buffalo, NY, USA.
Joyce, J. M. (2011). Kullback-Leibler divergence. In International encyclopedia of statistical science, pages 720–722. Springer.
Kokkolaras, M., Mourelatos, Z. P., and Papalambros, P. Y. (2004). Design optimization of hierarchically decomposed multilevel systems under uncertainty. In ASME 2004 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Salt Lake City, UT, USA.
Liang, C. and Mahadevan, S. (2016). Stochastic multidisciplinary analysis with high-dimensional coupling. AIAA Journal, 54(2):1209–1219.CrossRef
Liang, C., Mahadevan, S., and Sankararaman, S. (2015). Stochastic multidisciplinary analysis under epistemic uncertainty. Journal of Mechanical Design, 137(2):021404.CrossRef
Liu, H., Chen, W., Kokkolaras, M., Papalambros, P. Y., and Kim, H. M. (2006). Probabilistic analytical target cascading: a moment matching formulation for multilevel optimization under uncertainty. Journal of Mechanical Design, 128(4):991–1000.CrossRef
Mahadevan, S. and Smith, N. (2006). Efficient first-order reliability analysis of multidisciplinary systems. International Journal of Reliability and Safety, 1(1–2):137–154.CrossRef
McDonald, M. and Mahadevan, S. (2008). Uncertainty quantification and propagation in multidisciplinary analysis and optimization. In 12th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Victoria, Canada.
Padmanabhan, D. and Batill, S. (2002). Decomposition strategies for reliability based optimization in multidisciplinary system design. In 9th AIAA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, Atlanta, GA, USA.
Park, K., Felippa, C., and DeRuntz, J. (1977). Stabilization of staggered solution procedures for fluid-structure interaction analysis. Computational methods for fluid-structure interaction problems, 26(94–124):51.MATH
Sankararaman, S. and Mahadevan, S. (2012). Likelihood-based approach to multidisciplinary analysis under uncertainty. Journal of Mechanical Design, 134(3):031008.CrossRef
Tao, Y., Han, X., Duan, S., and Jiang, C. (2014). Reliability analysis for multidisciplinary systems with the mixture of epistemic and aleatory uncertainties. International Journal for Numerical Methods in Engineering, 97(1):68–78.MathSciNetCrossRef
Metadata
Title
Uncertainty Propagation for Multidisciplinary Problems
Authors
Loïc Brevault
Mathieu Balesdent
Copyright Year
2020
Book
Aerospace System Analysis and Optimization in Uncertainty

Print ISBN: 978-3-030-39125-6

Electronic ISBN: 978-3-030-39126-3

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-39126-3_6