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 4/2012

01.10.2012 | Industrial Application

Hydroelastic optimization of a keel fin of a sailing boat: a multidisciplinary robust formulation for ship design

Erschienen in: Structural and Multidisciplinary Optimization | Ausgabe 4/2012

Einloggen

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

search-config
loading …

Abstract

The paper presents a formulation for multidisciplinary design optimization of vessels, subject to uncertain operating conditions. The formulation couples the multidisciplinary design analysis with the Bayesian approach to decision problems affected by uncertainty. In the present context, the design specifications are no longer given in terms of a single operating design point, but in terms of probability density function of the operating scenario. The optimal configuration is that which maximizes the performance expectation over the uncertain parameters variation. In this sense, the optimal solution is “robust” within the stochastic scenario assumed. Theoretical and numerical issues are addressed and numerical results in the hydroelastic optimization of a keel fin of a sailing yacht are presented.
Vorheriger Artikel Topology optimization considering material and geometric uncertainties using stochastic collocation methods

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
Fußnoten
1
The symbol * is used in the present formulation to denote a specific designer choice.
 
2
The reader is warned that for instance, in many real-life problems, the Mangasarian–Fromowitz constraint qualification condition (MFCQ, e.g., Nocedal and Wright 1999) does not hold at the solution points, the latter being a critical issue for the algorithm adopted.
 
Literatur
Allaire D, Willcox K (2010) Surrogate modeling for uncertainty assessment with application to aviation environmental system models. AIAA J 48:1791–1803CrossRef
Alexandrov NM, Lewis RM (2001) An overview of first-order model management for engineering optimization. Optim Eng 2:413–430MATHCrossRef
Alexandrov NM, Lewis RM (2002) Analytical and computational aspects of collaborative optimization for multidisciplinary design. AIAA J 40:301–309CrossRef
Agarwal H (2004) Reliability based design optimization: formulations and methodologies. PhD dissertation, Univ of Notre Dame, South Bend, IN, USA
Agarwal H, Renaud J (2004) Reliability based design optimization using response surfaces in application to multidisciplinary systems. Eng Optim 36:291–311CrossRef
Agarwal H, Renaud J, Preston EL, Padmanabhan D (2004) Uncertainty quantification using evidence theory in multidisciplinary design optimization. Reliab Eng Syst Saf 85:281–294CrossRef
Baumal AE, McPhee JJ, Calamai PH (1998) Application of genetic algorithms to the design optimization of an active vehicle suspension system. Comput Methods Appl Math 163:87–94MATH
Beyer HG, Sendhoff B (2007) Robust optimization—a comprehensive survey. Comput Methods Appl Math 196:3190–3218MathSciNetMATH
Campana EF, Fasano G, Peri D (2006) Issues on nonlinear programming for Multidisciplinary Design Optimization (MDO), in ship design frameworks. In: Mota Soares CA et al (eds) III European conference on computational mechanics solids, structures and coupled problems in engineering. Lisbon, Portugal
Campana EF, Fasano G, Peri D (2007a) Nonlinear programming approaches in the Multidisciplinary Design Optimization (MDO) of a sailing yacht keel Fin. In: 9th intl conf on numerical ship hydrodynamics, Ann Arbor, MI, USA
Campana EF, Peri D, Pinto A (2007b) Multiobjective optimization of a containership using deterministic particle swarm optimization. J Ship Res 51:217–228
Campana EF, Liuzzi G, Lucidi S, Peri D, Piccialli V, Pinto A (2009) New global optimization methods for ship design problems. Optim Eng 10:533–555CrossRef
De Groot MH (1970) Optimal statistical decisions. McGraw Hill, New York
Diez M, Peri D (2009) Global optimization algorithms for robust optimization in naval design. In: 8th intl conf on computer applications and information technology in the maritime industries, COMPIT 2009. Budapest, Hungary
Diez M, Peri D (2010a) Robust optimization for ship conceptual design. Ocean Eng 37:966–977CrossRef
Diez, M, Peri D (2010b) Two-stage stochastic programming formulation for ship design optimization under uncertainty. Ship Technol Res 57:172–181
Diez M, Peri D, Campana EF, Iemma U (2010) Robust decision making in aerial and marine vehicles optimization: a designer’s viewpoint. Ent Risk Mgmt 2:68–86
Du X, Chen W (2000a) Methodology for managing the effect of uncertainty in simulation-based design. AIAA J 38:1471–1478CrossRef
Du X, Chen W (2000b) Towards a better understanding of modeling feasibility robustness in engineering design. J Mech Des 122:385–394CrossRef
Du X, Chen W (2002) Efficient uncertainty analysis methods for multidisciplinary robust design. AIAA J 40:545–552CrossRef
Giassi A, Bennis F, Maisonneuve, J-J (2004) Multidisciplinary design optimisation and robust design approaches applied to concurrent design. Struct Multidisc Optim 28:356–371CrossRef
Hicks RM, Henne PA (1978) Wing design by numerical optimization. J Aircr 15:407–412CrossRef
Iaccarino G (2008) Quantification of uncertainty in flow simulations using probabilistic methods. Non-equilibrium gas dynamics: from physical models to supersonic flights. In: VKI lecture series
Iemma U, Diez M (2006) Optimal conceptual design of aircraft including community noise prediction. In: Collection of technical papers—12th AIAA/CEAS aeroacoustics conference, vol 5, pp 2855–2864
Jameson A, Leoviriyakit K, Shankaran S (2007) Multi-point aero-structural optimization of wings including planform variations. In: 45th aerospace sciences meeting and exhibit, Reno, NV, USA
Kennedy J, Eberhart R (1995) Particle swarm optimization. In: IEEE intl conf on neural networks. Perth, Australia
Kodiyalam S, Sobieszczanski-Sobieski J (2001) Multidisciplinary design optimization—some formal methods, framework requirements, and application to vehicle design. Int J Veh Des 25:3–22CrossRef
Kugele SC, Trosset MW, Watson LT (2008) Numerical integration is statistical decision-theoretic methods for robust design optimization. Struct Multidisc Optim 36:457–475MathSciNetCrossRef
Marczyk J (2000) Stochastic multidisciplinary improvement: beyond optimization. In: 8th AIAA/USAF/NASA/ISSMO symposium on multidisciplinary analysis and optimization. Long Beach, CA, USA
Mavris DN, Bandte O, Delaurentis DA (1999) Robust design simulation: a probabilistic approach to multidisciplinary design. J Aircr 36:298–307CrossRef
Mirzaei M, Hosseini SN, Roshanian J (2007) Single and multi-point optimization of an airfoil using gradient method. Aircr Eng Aerosp Tec 70:611–620CrossRef
Mohammadi B, Pironneau O (2001) Applied shape optimization for fluids. Clarendon, OxfordMATH
Morino L, Bernardini G, Mastroddi F (2006) Multi-disciplinary optimization for the conceptual design of innovative aircraft configurations. Comput Model Eng Sci 13:1–18
Najm HN (2009) Uncertainty quantification and polynomial chaos techniques in computational fluid dynamics. Annu Rev Fluid Mech 41:35–52MathSciNetCrossRef
Papanikolaou A (2010) Holistic ship design optimization. Comput Aided Des 42:1028–1044CrossRef
Park GJ, Lee TH, Wang, KH (2006) Robust design: an overview. AIAA J 44:181–191CrossRef
Parsons MG, Scott RL (2004) Formulation of multicriterion design optimization problems for solution with scalar numerical optimization methods. J Ship Res 48:61–76
Peri D, Campana EF (2003) Multidisciplinary design optimization of a naval surface combatant. J Ship Res 47:1–12
Peri D, Campana EF (2005) High-fidelity models in global optimization. Lect Notes Comput Sci 3478:112–126CrossRef
Pinto A, Peri D, Campana EF (2004) Global optimization algorithms in naval hydrodynamics. Ship Technol Res 51:123–133
Ray T, Gokarn RP, Sha OP (1995) A global optimization model for ship design. Comput Ind 26:175–192CrossRef
Reuther JJ, Jameson A, Alonso JJ, Rimlinger MJ, Saunders D (1999a) Constrained multipoint aerodynamic shape optimization using an adjoint formulation and parallel computers, part 1. J Aircr 36:51–60CrossRef
Reuther JJ, Jameson A, Alonso JJ, Rimlinger MJ, Saunders D (1999b) Constrained multipoint aerodynamic shape optimization using an adjoint formulation and parallel computers, part 2. J Aircr 36:61–74CrossRef
Smith N, Mahadevan S (2005) Integrating system-level and component-level designs under uncertainty. J Spacecr Rockets 42:752–760CrossRef
Sobieszczanski-Sobieski J, Haftka RT (1997) Multidisciplinary aerospace design optimization: survey of recent developments. Struct Optim 14:1–23CrossRef
Sues RH, Oakley DR, Rhodes GS (1995) Multidisciplinary stochastic optimization. Proc Eng Mech 2:934–937
Sues RH, Cesare MA, Pageau S, Wu JY-T (2001) Reliability-based optimization considering manufacturing and operational uncertainties. J Aerosp Eng 14:166–174CrossRef
Taguchi G (1986) Quality engineering through design optimization. Krauss International Publications, White Plains
Trosset MW, Alexandrov NM., Watson, LT (2003) New methods for robust design using computer simulations. In: Proceedings of the section on physical and engineering sciences, American Statistical Association
Tu J, Choi KK, Park YH (1999) A new study on reliability-based design optimization. J Mech Des 121:557–564CrossRef
Willcox K, Wakayama S (2003) Simultaneous optimization of a multiple-aircraft family. J Aircr 40:616–622CrossRef
Zang C, Friswell MI, Mottershead JE (2005) A review of robust optimal design and its application in dynamics. Comput Struct 83:315–326CrossRef
Metadaten
Titel
Hydroelastic optimization of a keel fin of a sailing boat: a multidisciplinary robust formulation for ship design
Publikationsdatum
01.10.2012
Erschienen in
Structural and Multidisciplinary Optimization / Ausgabe 4/2012
Print ISSN: 1615-147X
Elektronische ISSN: 1615-1488
DOI
https://doi.org/10.1007/s00158-012-0783-7

Weitere Artikel der Ausgabe 4/2012

Structural and Multidisciplinary Optimization 4/2012 Zur Ausgabe

Research Paper

Efficient reliability analysis based on Bayesian framework under input variable and metamodel uncertainties

Brief Note

Sensitivity filtering from a continuum mechanics perspective

Research Paper

Approximation of the critical buckling factor for composite panels

Research Paper

Enhanced analysis of design sensitivities in topology optimization

Research Paper

Multiobjective topology optimization of truss structures with kinematic stability repair

Research Paper

Planar contraction design with specified fibre orientation distribution at the outlet

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