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Sci. Comput."],"published-print":{"date-parts":[[2017,1]]},"abstract":"<jats:p>This work presents a data-driven nonintrusive model reduction approach for large-scale time-dependent systems with linear state dependence. Traditionally, model reduction is performed in an intrusive projection-based framework, where the operators of the full model are required either explicitly in an assembled form or implicitly through a routine that returns the action of the operators on a vector. Our nonintrusive approach constructs reduced models directly from trajectories of the inputs and outputs of the full model, without requiring the full-model operators. These trajectories are generated by running a simulation of the full model; our method then infers frequency-response data from these simulated time-domain trajectories and uses the data-driven Loewner framework to derive a reduced model. Only a single time-domain simulation is required to derive a reduced model with the new data-driven nonintrusive approach. We demonstrate our model reduction method on several benchmark examples and a finite element model of a cantilever beam; our approach recovers the classical Loewner reduced models and, for these problems, yields high-quality reduced models despite treating the full model as a black box.<\/jats:p>","DOI":"10.1137\/16m1094750","type":"journal-article","created":{"date-parts":[[2017,9,26]],"date-time":"2017-09-26T12:54:32Z","timestamp":1506430472000},"page":"A2152-A2178","source":"Crossref","is-referenced-by-count":58,"title":["Data-Driven Reduced Model Construction with Time-Domain Loewner Models"],"prefix":"10.1137","volume":"39","author":[{"given":"Benjamin","family":"Peherstorfer","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Serkan","family":"Gugercin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Karen","family":"Willcox","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"351","published-online":{"date-parts":[[2017,9,26]]},"reference":[{"key":"atypb1","doi-asserted-by":"publisher","DOI":"10.1049\/iet-spr.2008.0190"},{"key":"atypb2","doi-asserted-by":"publisher","DOI":"10.1137\/1.9780898718713"},{"key":"atypb3","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4419-5757-3_1"},{"key":"atypb4","doi-asserted-by":"publisher","DOI":"10.1016\/j.aml.2015.10.011"},{"key":"atypb5","doi-asserted-by":"publisher","DOI":"10.1093\/imamci\/3.2-3.61"},{"key":"atypb6","doi-asserted-by":"publisher","DOI":"10.1002\/nme.2100"},{"key":"atypb7","first-page":"4953","volume-title":"Proc. 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