2010
DOI: 10.1016/j.oceaneng.2010.01.018
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The global structural response model for multi-deck ships in concept design phase

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Cited by 21 publications
(3 citation statements)
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“…Index space, see LS INGRID (1998), enables a very comprehensive design description; see Andric and Zanic (2010). It is a compact structural description particularly related to the support of different descriptors and criteria on the ship's 3D grid (spacing) level by, e.g., frame number, deck number etc.…”
Section: Design Descriptors/variables Control Structures Generic Momentioning
confidence: 99%
See 1 more Smart Citation
“…Index space, see LS INGRID (1998), enables a very comprehensive design description; see Andric and Zanic (2010). It is a compact structural description particularly related to the support of different descriptors and criteria on the ship's 3D grid (spacing) level by, e.g., frame number, deck number etc.…”
Section: Design Descriptors/variables Control Structures Generic Momentioning
confidence: 99%
“…The structural design is based on the generic ship 3D FEM models, of the CDP fidelity level, e.g. using gross elements/surrogates (see Andric and Zanic 2010) and analytically defined adequacy criteria. Loads and adequacy criteria are based on the BV Classification Society Rules.…”
Section: Pareto Supported Design Procedures Applied Tomentioning
confidence: 99%
“…This method is far simpler than the requirements for the detailed meshes needed in Nastran or Sesam software. Furthermore, based on the block of macro elements and gross-elements (Andric and Zanic, 2010), for preliminary design of multi-deck ships, a kind of generic ship model has been proposed which is good at fast investigation of ordinary scantling/material optimization as well as different structural topological/geometrical concepts. Presently, the use of statistical techniques to build approximations or meta models of expensive computer analysis codes pervades much of today's engineering design, such as the response surface methodology (RSM), Taylor series, Kriging Model (Martin and Simpson, 2005; and the powerful ANN method (Desai et al, 2008).…”
Section: Introductionmentioning
confidence: 99%