Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Structural and Multidisciplinary Optimization
Erschienen in: Structural and Multidisciplinary Optimization 3/2019

26.10.2018 | Research Paper

Response analysis and reliability-based design optimization of structural-acoustic system under evidence theory

verfasst von: Rugao Gao, Shengwen Yin, Feng Xiong

Erschienen in: Structural and Multidisciplinary Optimization | Ausgabe 3/2019

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Evidence theory has a strong ability to deal with epistemic uncertainties whose precise probability distributions cannot be determined according to limited information. For response analysis of the structural-acoustic system under evidence theory, a numerical method named as vertex Taylor expansion moment method (VTPEMM) is proposed. In VTPEMM, the response of the structural-acoustic system in each focal element combination of evidence variables is expanded by the first-order Taylor series and its variational range is evaluated at vertexes of focal elements of evidence variables. Then, a moment method of probability theory is developed to calculate variational ranges of expectation and variance of response. For optimization of the structural-acoustic system under evidence theory, an evidence reliability-based design optimization (RBDO) strategy is developed. In the evidence RBDO, the objective function is efficiently estimated by VTPEMM. To efficiently evaluate the reliability constraint condition, an evidence-based reliability analysis technique (EBRAT) is proposed. A numerical example is provided to investigate the effectiveness of the proposed numerical analysis and optimization techniques.
Vorheriger Artikel Topology optimization of piezoelectric macro-fiber composite patches on laminated plates for vibration suppression
Nächster Artikel Multi-information source constrained Bayesian optimization

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

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!

Jetzt informieren

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!

Jetzt informieren
Literatur
Agarwal H, Renaud JE, Preston EL, Padmanabhan D (2004) Uncertainty quantification using evidence theory in multidisciplinary design optimization. Reliab Eng Syst Saf 85(1–3):281–294CrossRef
Alyanak E, Grandhi R, Bae HR (2008) Gradient projection for reliability-based design optimization using evidence theory. Eng Optim 40(10):923–935CrossRef
Bae HR, Grandhi RV, Canfield RA (2003) Uncertainty quantification of structural response using evidence theory. AIAA J 41(10):2062–2068CrossRef
Bae HR, Grandhi RV, Canfield RA (2004a) Epistemic uncertainty quantification techniques including evidence theory for large-scale structures. Comput Struct 82(13–14):1101–1112CrossRef
Bae HR, Grandhi RV, Canfield RA (2004b) An approximation approach for uncertainty quantification using evidence theory. Reliab Eng Syst Saf 86(3):215–225CrossRef
Bai YC, Han X, Jiang C, Liu J (2012) Comparative study of metamodeling techniques for reliability analysis using evidence theory. Adv Eng Softw 53:61–71CrossRef
Bai YC, Jiang C, Han X et al (2013) Evidence-theory-based structural static and dynamic response analysis under epistemic uncertainties. Finite Elem Anal Des 68(3):52–62CrossRef
Beer M, Ferson S, Kreinovich V (2013) Imprecise probabilities in engineering analyses. Mech Syst Signal Process 37(1–2):4–29CrossRef
Chen N, Yu D, Xia B (2015) Evidence-theory-based analysis for the prediction of exterior acoustic field with epistemic uncertainties. Eng Anal Bound Elem 50:402–411CrossRef
Cicirello A, Langley RS (2014) Efficient parametric uncertainty analysis within the hybrid finite element/statistical energy analysis method. J Sound Vib 333(6):1698–1717CrossRef
Du, X.P., Uncertainty analysis with probability and evidence theory, Proceedings of ASME 2006 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (DETC/CIE), Philadelphia, PA, USA, 2006
Du L, Choi KK, Youn BD (2006) Inverse possibility analysis method for possibility- based design optimization. AIAA J 44(11):2682–2690CrossRef
Goldberg DE (1989) Genetic algorithms in search, optimization & machine learning. Addison-Wesley, New YorkMATH
Helton JC, Johnson JD, Oberkampf WL (2004) An exploration of alternative approaches to the representation of uncertainty in model predictions. Reliab Eng Syst Saf 85(1–3):39–71CrossRef
Helton JC, Johnson JD, Oberkampf WL, Sallaberry CJ (2006) Sensitivity analysis in conjunction with evidence theory representations of epistemic uncertainty. Reliab Eng Syst Saf 91(10–11):1414–1434CrossRef
Helton JC, Johnson JD, Oberkampf WL, Storlie CB (2007) A sampling-based computational strategy for the representation of epistemic uncertainty in model predictions with evidence theory. Comput Methods Appl Mech Eng 196(37–40):3980–3998MathSciNetCrossRefMATH
Impollonia N, Muscolino G (2011) Interval analysis of structures with uncertain-but-bounded axial stiffness. Comput Methods Appl Mech Eng 220(21–22):1945–1962CrossRefMATH
Jiang C, Li WX, Han X, Liu LX, Le PH (2011) Structural reliability analysis based on random distributions with interval parameters. Comput Struct 89(23–24):2292–2302CrossRef
Jiang C, Zhang Z, Han X, Liu J (2013) A novel evidence-theory-based reliability analysis method for structures with epistemic uncertainty. Comput Struct 129:1–12CrossRef
Marburg S (2002) Developments in structural-acoustic optimization for passive noise control. Arch Comput Methods Eng 9(4):291–370CrossRefMATH
Moens D, Vandepitte D (2006) Recent advances in non-probabilistic approaches for non-deterministic dynamic finite element analysis. Arch Comput Methods Eng 13(3):389–464MathSciNetCrossRefMATH
Mourelatos ZP, Zhou J (2005) Reliability estimation and design with insufficient data based on possibility theory. AIAA J 43(8):1696–1705CrossRef
Mourelatos ZP, Zhou J (2006) A design optimization method using evidence theory. J Mech Des Trans ASME 128(4):901–908CrossRef
Oberguggenberger M, Fellin W (2008) Reliability bounds through random sets: non-parametric methods and geotechnical applications. Comput Struct 86(10):1093–1101CrossRef
Oberkampf WL, Helton JC (2002) Investigation of evidence theory for engineering applications, 43rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, Denver, Colorado
Ohayon, R., Soize, C., Structural acoustics and vibration: mechanical models, variational formulations and discretization, Academic press, San Diego, 1998
Shafer G (1976) A mathematical theory of evidence. Princeton University Press, PrincetonMATH
Soundappan P, Nikolaidis E, Haftka RT, Grandhi R, Canfield R (2004) Comparison of evidence theory and Bayesian theory for uncertainty modeling. Reliab Eng Syst Saf 85(1–3):295–311CrossRef
Tonon F, Bernardini A, Mammino A (2000) Reliability analysis of rock mass response by means of random set theory. Reliab Eng Syst Saf 70(3):263–282CrossRef
Vergote, K., Van Genechten, B., Vandepitte, D., Desmet, W., On the analysis of vibro-acoustic systems in the mid-frequency range using a hybrid deterministic-statistical approach, Comput Struct, Vol. 89, No2. 11–12, 2011, pp. 868–877
Wang C, Qiu Z (2014) An interval perturbation method for exterior acoustic field prediction with uncertain-but-bounded parameters. J Fluids Struct 49:441–449CrossRef
Wang C, Qiu Z, Wang X, Wu D (2014) Interval finite element analysis and reliability-based optimization of coupled structural-acoustic system with uncertain parameters. Finite Elem Anal Des 91:108–114CrossRef
Xia B, Yu D (2012) Interval analysis of acoustic field with uncertain-but-bounded parameters. Comput Struct 112-113:235–244CrossRef
Xia B, Yu D (2013) Modified interval perturbation finite element method for a structural-acoustic system with interval parameters. J Appl Mech Trans ASME 80(4):041027.1–041027.8CrossRef
Xia B, Yu D (2014a) An interval random perturbation method for structural-acoustic system with hybrid uncertain parameters. Int J Numer Methods Eng 97(3):181–206MathSciNetCrossRefMATH
Xia B, Yu D (2014b) Response analysis of acoustic field with convex parameters. J Vib Acoust 136(4):041017CrossRef
Xia B, Yu D, Liu J (2013) Hybrid uncertain analysis for structural-acoustic problem with random and interval parameters. J Sound Vib 332(11):2701–2720CrossRef
Xia B, Hui L, Yu D et al (2015) Reliability-based design optimization of structural systems under hybrid probabilistic and interval model. Comput Struct 160:126–134CrossRef
Yin S, Yu D, Yin H et al (2017) Hybrid evidence theory-based finite element/statistical energy analysis method for mid-frequency analysis of built-up systems with epistemic uncertainties. Mech Syst Signal Process 93:204–224CrossRef
Zissimos PM, Jun Z (2005) A design optimization method using evidence theory. J Mech Des 128(4):1153–1161
Metadaten
Titel
Response analysis and reliability-based design optimization of structural-acoustic system under evidence theory
verfasst von
Rugao Gao
Shengwen Yin
Feng Xiong
Publikationsdatum
26.10.2018
Verlag
Springer Berlin Heidelberg
Erschienen in
Structural and Multidisciplinary Optimization / Ausgabe 3/2019
Print ISSN: 1615-147X
Elektronische ISSN: 1615-1488
DOI
https://doi.org/10.1007/s00158-018-2112-2

Weitere Artikel der Ausgabe 3/2019

Structural and Multidisciplinary Optimization 3/2019 Zur Ausgabe

Industrial Application

Reliability-based design optimization of crane bridges using Kriging-based surrogate models

Research Paper

Multi-information source constrained Bayesian optimization

Research Paper

Topology optimization of piezoelectric macro-fiber composite patches on laminated plates for vibration suppression

Research Paper

Topology optimization framework for structures subjected to stationary stochastic dynamic loads

Research Paper

Multi-material topology optimization involving simultaneous structural and thermal analyses

Research Paper

Isogeometric sizing and shape optimization of thin structures with a solid-shell approach

Premium Partner

    Marktübersichten

    Die im Laufe eines Jahres in der „adhäsion“ veröffentlichten Marktübersichten helfen Anwendern verschiedenster Branchen, sich einen gezielten Überblick über Lieferantenangebote zu verschaffen. 

    Zur Marktübersicht
    Bildnachweise