FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2783169789> ?p ?o ?g. }

• W2783169789 endingPage "186" @default.
• W2783169789 startingPage "179" @default.
• W2783169789 abstract "Fast computation of demagnetization curves is essential for the computational design of soft magnetic sensors or permanent magnet materials. We show that a sparse preconditioner for a nonlinear conjugate gradient energy minimizer can lead to a speed up by a factor of 3 and 7 for computing hysteresis in soft magnetic and hard magnetic materials, respectively. As a preconditioner an approximation of the Hessian of the Lagrangian is used, which only takes local field terms into account. Preconditioning requires a few additional sparse matrix vector multiplications per iteration of the nonlinear conjugate gradient method, which is used for minimizing the energy for a given external field. The time to solution for computing the demagnetization curve scales almost linearly with problem size." @default.
• W2783169789 created "2018-01-26" @default.
• W2783169789 creator A5005460667 @default.
• W2783169789 creator A5007673346 @default.
• W2783169789 creator A5046146996 @default.
• W2783169789 creator A5049767059 @default.
• W2783169789 creator A5034930923 @default.
• W2783169789 creator A5079740895 @default.
• W2783169789 date "2019-02-01" @default.
• W2783169789 modified "2023-10-04" @default.
• W2783169789 title "Preconditioned nonlinear conjugate gradient method for micromagnetic energy minimization" @default.
• W2783169789 cites W1971148162 @default.
• W2783169789 cites W1978913015 @default.
• W2783169789 cites W1983865093 @default.
• W2783169789 cites W1987753869 @default.
• W2783169789 cites W1994127443 @default.
• W2783169789 cites W1997972181 @default.
• W2783169789 cites W2000389939 @default.
• W2783169789 cites W2003755503 @default.
• W2783169789 cites W2012231377 @default.
• W2783169789 cites W2014851363 @default.
• W2783169789 cites W2042306825 @default.
• W2783169789 cites W2049385523 @default.
• W2783169789 cites W2061416268 @default.
• W2783169789 cites W2093461480 @default.
• W2783169789 cites W2105593918 @default.
• W2783169789 cites W2112632437 @default.
• W2783169789 cites W2114386378 @default.
• W2783169789 cites W2127387539 @default.
• W2783169789 cites W2137502144 @default.
• W2783169789 cites W2147463309 @default.
• W2783169789 cites W2148945406 @default.
• W2783169789 cites W2150531183 @default.
• W2783169789 cites W2155305863 @default.
• W2783169789 cites W2161759370 @default.
• W2783169789 cites W2169789373 @default.
• W2783169789 cites W2273737868 @default.
• W2783169789 cites W2316564661 @default.
• W2783169789 cites W2333170276 @default.
• W2783169789 cites W2418954983 @default.
• W2783169789 cites W2464660301 @default.
• W2783169789 cites W2470148438 @default.
• W2783169789 cites W2472474713 @default.
• W2783169789 cites W2605666738 @default.
• W2783169789 cites W2606581466 @default.
• W2783169789 cites W3099053142 @default.
• W2783169789 cites W3100590914 @default.
• W2783169789 cites W3104879333 @default.
• W2783169789 doi "https://doi.org/10.1016/j.cpc.2018.09.004" @default.
• W2783169789 hasPublicationYear "2019" @default.
• W2783169789 type Work @default.
• W2783169789 sameAs 2783169789 @default.
• W2783169789 citedByCount "22" @default.
• W2783169789 countsByYear W27831697892019 @default.
• W2783169789 countsByYear W27831697892020 @default.
• W2783169789 countsByYear W27831697892021 @default.
• W2783169789 countsByYear W27831697892022 @default.
• W2783169789 countsByYear W27831697892023 @default.
• W2783169789 crossrefType "journal-article" @default.
• W2783169789 hasAuthorship W2783169789A5005460667 @default.
• W2783169789 hasAuthorship W2783169789A5007673346 @default.
• W2783169789 hasAuthorship W2783169789A5034930923 @default.
• W2783169789 hasAuthorship W2783169789A5046146996 @default.
• W2783169789 hasAuthorship W2783169789A5049767059 @default.
• W2783169789 hasAuthorship W2783169789A5079740895 @default.
• W2783169789 hasBestOaLocation W27831697892 @default.
• W2783169789 hasConcept C11413529 @default.
• W2783169789 hasConcept C115260700 @default.
• W2783169789 hasConcept C119835096 @default.
• W2783169789 hasConcept C119857082 @default.
• W2783169789 hasConcept C121332964 @default.
• W2783169789 hasConcept C126255220 @default.
• W2783169789 hasConcept C134306372 @default.
• W2783169789 hasConcept C153258448 @default.
• W2783169789 hasConcept C158622935 @default.
• W2783169789 hasConcept C167431342 @default.
• W2783169789 hasConcept C203616005 @default.
• W2783169789 hasConcept C26362088 @default.
• W2783169789 hasConcept C28826006 @default.
• W2783169789 hasConcept C32546565 @default.
• W2783169789 hasConcept C33923547 @default.
• W2783169789 hasConcept C41008148 @default.
• W2783169789 hasConcept C45374587 @default.
• W2783169789 hasConcept C50644808 @default.
• W2783169789 hasConcept C60434167 @default.
• W2783169789 hasConcept C62520636 @default.
• W2783169789 hasConcept C6802819 @default.
• W2783169789 hasConcept C81184566 @default.
• W2783169789 hasConceptScore W2783169789C11413529 @default.
• W2783169789 hasConceptScore W2783169789C115260700 @default.
• W2783169789 hasConceptScore W2783169789C119835096 @default.
• W2783169789 hasConceptScore W2783169789C119857082 @default.
• W2783169789 hasConceptScore W2783169789C121332964 @default.
• W2783169789 hasConceptScore W2783169789C126255220 @default.
• W2783169789 hasConceptScore W2783169789C134306372 @default.
• W2783169789 hasConceptScore W2783169789C153258448 @default.
• W2783169789 hasConceptScore W2783169789C158622935 @default.
• W2783169789 hasConceptScore W2783169789C167431342 @default.

• next