FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W124735174> ?p ?o ?g. }

• W124735174 abstract "This paper is concerned with the implementation and numerical study of a discrete negative norm least-squares method for the Navier-Stokes equations proposed in (2) and (3). The main focus of the paper is on the algorithmic development and computational analysis of this method, including design of efficient preconditioners, numerical estimates of convergence rates, etc. Our experiments indicate that the negative norm method yields results that are in agreement with the theoretical error estimates o f (3) and compare favorably with the benchmark studies of (11). 1. Introduction. In this paper we examine algorithmic and computational issues re- lated to a negative norm least-squares method for the numerical solution of the stationary, incompressible Navier-Stokes equations. In the recent years methods of l east-squares type for fluid flow problems have been receiving increasing attention; see e.g., ( 1)-(9), (15), (16), (17), and (18) among others. This interest is largely caused by the attracti ve analytic and computational features of least-squares methods that are not present in other discretization schemes, such as mixed Galerkin methods. Most of these features stem from the fact that weak variational problems in least-squares methods represent necessary minimum conditions for problem-dependent functionals which are defined by summing up residu al norms of the differential equations. The guiding principle in the choice of the no rms is to obtain norm- equivalent functionals. Then, corresponding weak problems are in general coercive and th eir discretization leads to symmetric and positive definite algebraic systems . Specifically, in the context of the Navier-Stokes equations application of least-squares vari ational principles of- fers the following advantages: • methods are not subject to the inf-sup (LBB) stability condition; s ee (12) and (14); • used in conjunction with Newton linearization least-squares lead to symmetric, pos- itive definite linear systems, at least in a neighborhood of the soluti on; • essential boundary conditions can be enforced in a weak, variational sense. As a result, • a single approximating space can be used for both the velocity and the pressure leading to simplified and more efficient algorithmic design; • solution of the linearized problems can be accomplished by robust and efficien t iter- ative methods without assembling the discretization matrix; • approximating spaces are not subject to the essential boundary conditions . However, without a thorough examination of the settings for the least-squares method many of these advantages may be lost or utilized incompletely. For example, a least -squares method based on the primitive variable Navier-Stokes equations may require conforming discretiza- tions by continuously differentiable finite element spaces, i.e., it wil l be impractical. Further- more, if the least-squares functional is not norm-equivalent then result ing methods may fail to be optimally accurate." @default.
• W124735174 created "2016-06-24" @default.
• W124735174 creator A5022276974 @default.
• W124735174 date "1997-01-01" @default.
• W124735174 modified "2023-09-24" @default.
• W124735174 title "EXPERIENCES WITH NEGATIVE NORM LEAST-SQUARE METHODS FOR THE NAVIER-STOKES EQUATIONS" @default.
• W124735174 cites W1674659126 @default.
• W124735174 cites W1724250621 @default.
• W124735174 cites W1965034652 @default.
• W124735174 cites W1969951488 @default.
• W124735174 cites W1984858501 @default.
• W124735174 cites W2020684044 @default.
• W124735174 cites W2021041911 @default.
• W124735174 cites W2041523977 @default.
• W124735174 cites W2044691832 @default.
• W124735174 cites W2052229944 @default.
• W124735174 cites W2059537627 @default.
• W124735174 cites W2063848312 @default.
• W124735174 cites W2065920748 @default.
• W124735174 cites W2088093787 @default.
• W124735174 cites W2169872314 @default.
• W124735174 cites W3131881974 @default.
• W124735174 hasPublicationYear "1997" @default.
• W124735174 type Work @default.
• W124735174 sameAs 124735174 @default.
• W124735174 citedByCount "4" @default.
• W124735174 crossrefType "journal-article" @default.
• W124735174 hasAuthorship W124735174A5022276974 @default.
• W124735174 hasConcept C127413603 @default.
• W124735174 hasConcept C134306372 @default.
• W124735174 hasConcept C146978453 @default.
• W124735174 hasConcept C17744445 @default.
• W124735174 hasConcept C191795146 @default.
• W124735174 hasConcept C199539241 @default.
• W124735174 hasConcept C2781278361 @default.
• W124735174 hasConcept C28826006 @default.
• W124735174 hasConcept C33923547 @default.
• W124735174 hasConcept C48753275 @default.
• W124735174 hasConcept C73000952 @default.
• W124735174 hasConcept C84655787 @default.
• W124735174 hasConcept C9376300 @default.
• W124735174 hasConceptScore W124735174C127413603 @default.
• W124735174 hasConceptScore W124735174C134306372 @default.
• W124735174 hasConceptScore W124735174C146978453 @default.
• W124735174 hasConceptScore W124735174C17744445 @default.
• W124735174 hasConceptScore W124735174C191795146 @default.
• W124735174 hasConceptScore W124735174C199539241 @default.
• W124735174 hasConceptScore W124735174C2781278361 @default.
• W124735174 hasConceptScore W124735174C28826006 @default.
• W124735174 hasConceptScore W124735174C33923547 @default.
• W124735174 hasConceptScore W124735174C48753275 @default.
• W124735174 hasConceptScore W124735174C73000952 @default.
• W124735174 hasConceptScore W124735174C84655787 @default.
• W124735174 hasConceptScore W124735174C9376300 @default.
• W124735174 hasLocation W1247351741 @default.
• W124735174 hasOpenAccess W124735174 @default.
• W124735174 hasPrimaryLocation W1247351741 @default.
• W124735174 hasRelatedWork W1965034652 @default.
• W124735174 hasRelatedWork W1965727018 @default.
• W124735174 hasRelatedWork W1972268912 @default.
• W124735174 hasRelatedWork W1977672079 @default.
• W124735174 hasRelatedWork W2059537627 @default.
• W124735174 hasRelatedWork W2061179077 @default.
• W124735174 hasRelatedWork W2693440781 @default.
• W124735174 hasRelatedWork W2781631139 @default.
• W124735174 hasRelatedWork W2896584966 @default.
• W124735174 hasRelatedWork W2903914808 @default.
• W124735174 hasRelatedWork W2908674015 @default.
• W124735174 hasRelatedWork W2953277468 @default.
• W124735174 hasRelatedWork W2963670608 @default.
• W124735174 hasRelatedWork W2999161263 @default.
• W124735174 hasRelatedWork W302817991 @default.
• W124735174 hasRelatedWork W3205500484 @default.
• W124735174 hasRelatedWork W37586201 @default.
• W124735174 hasRelatedWork W569025978 @default.
• W124735174 hasRelatedWork W609749637 @default.
• W124735174 hasRelatedWork W838618887 @default.
• W124735174 isParatext "false" @default.
• W124735174 isRetracted "false" @default.
• W124735174 magId "124735174" @default.
• W124735174 workType "article" @default.