{"doi":"10.1002/gamm.201490036","title":"FETI Domain Decomposition Methods for Second Order Elliptic Partial Differential Equations","abstract":"<jats:title>Abstract</jats:title><jats:p>A survey on certain<jats:bold>F</jats:bold>inite<jats:bold>E</jats:bold>lement<jats:bold>T</jats:bold>earing and<jats:bold>I</jats:bold>nterconnecting (FETI) methods for second order elliptic partial differential equations is given. FETI methods are nonoverlapping domain decomposition algorithms where continuity across subdomain boundaries is treated, sometimes only in parts, by Lagrange multipliers. The family of FETI algorithms is among the best known and most severely tested domain decomposition methods for elliptic partial differential equations. In this article, an overview is given of the classical one‐level FETI method and the more recent dual‐primal FETI methods; both type of algorithms are considered for scalar, second order, elliptic equations and the system of linear elasticity, and are illustrated by some computational results. (© 2006 WILEY‐VCH Verlag GmbH &amp; Co. KGaA, Weinheim)</jats:p>","journal":"GAMM-Mitteilungen","year":2006,"id":22816,"datarank":0.6289300152381304,"base_score":2.639057329615259,"endowment":2.639057329615259,"self_citation_contribution":0.3958585994422889,"citation_network_contribution":0.23307141579584148,"self_endowment_contribution":0.3958585994422889,"citer_contribution":0.23307141579584148,"corpus_percentile":null,"corpus_rank":null,"citation_count":13,"citer_count":5,"citers_with_citation_signal":5,"citers_with_endowment":5,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":142203,"name":"Axel Klawonn","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"base_score":2.639057329615259,"endowment":2.639057329615259,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"21071399","pmcid":null,"openalex_id":"https://openalex.org/W1524668482","authors":[],"funders":[],"total_grants":0,"fwci":2.5474,"citation_percentile":0.87724247,"influential_citations":0,"citation_trend":[{"year":2012,"count":4},{"year":2015,"count":1},{"year":2016,"count":2}],"oa_status":"closed","license":"http://onlinelibrary.wiley.com/termsAndConditions#vor","oa_locations":[{"url":"https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fgamm.201490036","host_type":"publisher"},{"url":"https://onlinelibrary.wiley.com/doi/pdf/10.1002/gamm.201490036","host_type":"publisher"},{"url":"https://doi.org/10.1002/gamm.201490036","host_type":"journal"}],"fields_of_study":["Advanced Numerical Methods in Computational Mathematics","Numerical methods in engineering","Numerical methods for differential equations","Mathematics","Engineering"],"mesh_terms":[],"keywords":["FETI","Domain decomposition methods","Elliptic partial differential equation","Mortar methods","Partial differential equation","Mathematics","Applied mathematics","Scalar (mathematics)","Lagrange multiplier","Mathematical analysis","Finite element method","Mathematical optimization","Physics","Geometry"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-06-07T16:26:23.870659Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}