Asymptotic analysis: Working note {number_sign}3, boundary layers

Technical Report · Wed Sep 01 00:00:00 EDT 1993

DOI:https://doi.org/10.2172/10192561· OSTI ID:10192561

Garbey, M ^[1]; Kaper, H G ^[2]

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1. Universite Claude Bernard Lyon 1, Villeurbanne (France). Laboratoire d`Analyse Numerique
2. Argonne National Lab., IL (United States)

In this chapter the authors discuss the asymptotic approximation of functions that display boundary-layer behavior. The purpose here is to introduce the basic concepts underlying the phenomenon, to illustrate its importance, and to describe some of the fundamental tools available for its analysis. To achieve their purpose in the clearest way possible, the authors will work with functions that are assumed to be given explicitly -- that is, functions f : (0,{epsilon}{sub 0}) {yields} X whose expressions are known, at least in principle. Only in the following chapter will they begin the study of functions that are given implicitly as solutions of boundary value problems -- the real stuff of which singular perturbation theory is made. Boundary-layer behavior is associated with asymptotic expansions that are regular {open_quotes}almost everywhere{close_quotes} -- that is, expansions that are regular on every compact subset of the domain of definition, but not near the boundary. These regular asymptotic expansions can be continued in a certain sense all the way up to the boundary, but a separate analysis is still necessary in the boundary layer. The boundary-layer analysis is purely local and aims at constructing local approximations in the neighborhood of each point of the singular part of the boundary. The problem of finding an asymptotic approximation is thus reduced to matching the various local approximations to the existing regular expansion valid in the interior of the domain. The authors are thinking, for example, of fluid flow (viscosity), combustion (Lewis number), and superconductivity (Ginzburg-Landau parameter) problems. Their solution may remain smooth over a wide range of parameter values, but as the parameters approach critical values, complicated patterns may emerge.

• Research Organization: Argonne National Lab. (ANL), Argonne, IL (United States)
• Sponsoring Organization: USDOE, Washington, DC (United States)
• DOE Contract Number: W-31109-ENG-38
• OSTI ID: 10192561
• Report Number(s): ANL/MCS-TM-181; ON: DE94002299; TRN: 93:003981
• Resource Relation: Other Information: PBD: Sep 1993
• Country of Publication: United States
• Language: English

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