1999
DOI: 10.1016/s0165-2125(98)00027-4
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Scattering from submerged objects by a hybrid asymptotic-boundary integral equation method

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Cited by 3 publications
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“…Combined asymptotic-numerical methods have the advantage of removing the hard core of the problem, namely, the dependence on the small parameter, by using analytical tools. See, for example, the work of Zrahia et al (1997) on a hybrid spectral element asymptotic method for analyzing boundary-layer problems (where ϵ is the thickness of the boundary layer), Giladi and Kellery (2001) and Barbone et al (Montgomery and Barbone 1998;Barbone and Michael, 1999) on hybrid numerical asymptotic methods for wave scattering problems (where ϵ is a typical wave-length), Panasenko (1998) on a hybrid asymptotic-FE method for rod structures (where ϵ is the size of the region where the structure behaves as a three-dimensional solid), and Marigo and Pideri (Marigo, 2011) on representing a sequence of micro cracks on a surface (where ϵ is the ratio of the micro scale to the macro scale). In our case, the small parameter ϵ is the thickness τ of the layer.…”
Section: Introductionmentioning
confidence: 99%
“…Combined asymptotic-numerical methods have the advantage of removing the hard core of the problem, namely, the dependence on the small parameter, by using analytical tools. See, for example, the work of Zrahia et al (1997) on a hybrid spectral element asymptotic method for analyzing boundary-layer problems (where ϵ is the thickness of the boundary layer), Giladi and Kellery (2001) and Barbone et al (Montgomery and Barbone 1998;Barbone and Michael, 1999) on hybrid numerical asymptotic methods for wave scattering problems (where ϵ is a typical wave-length), Panasenko (1998) on a hybrid asymptotic-FE method for rod structures (where ϵ is the size of the region where the structure behaves as a three-dimensional solid), and Marigo and Pideri (Marigo, 2011) on representing a sequence of micro cracks on a surface (where ϵ is the ratio of the micro scale to the macro scale). In our case, the small parameter ϵ is the thickness τ of the layer.…”
Section: Introductionmentioning
confidence: 99%