000079354 001__ 79354
000079354 005__ 20200117221655.0
000079354 0247_ $$2doi$$a10.1016/j.cma.2018.05.031
000079354 0248_ $$2sideral$$a107045
000079354 037__ $$aART-2018-107045
000079354 041__ $$aeng
000079354 100__ $$0(orcid)0000-0002-6773-6667$$aAriza-Gracia, M.
000079354 245__ $$aFluid–structure simulation of a general non-contact tonometry. A required complexity?
000079354 260__ $$c2018
000079354 5060_ $$aAccess copy available to the general public$$fUnrestricted
000079354 5203_ $$aUnderstanding corneal biomechanics is important for applications regarding refractive surgery prediction outcomes and the study of pathologies affecting the cornea itself. In this regard, non-contact tonometry (NCT) is gaining interest as a non-invasive diagnostic tool in ophthalmology, and is becoming an alternative method to characterize corneal biomechanics in vivo. In general, identification of material parameters of the cornea from a NCT test relies on the inverse finite element method, for which an accurate and reliable modelization of the test is required. This study explores four different modeling strategies ranging from pure structural analysis up to a fluid–structure interaction model considering the air–cornea and humor–cornea interactions. The four approaches have been compared using clinical biomarkers commonly used in ophthalmology. Results from the simulations indicate the importance of considering the humors as fluids and the deformation of the cornea when determining the pressure applied by the air-jet during the test. Ignoring this two elements in the modeling lead to an overestimation of corneal displacement and therefore an overestimation of corneal stiffness when using the inverse finite element method.
000079354 536__ $$9info:eu-repo/grantAgreement/ES/MINECO/DPI2014-54981-R$$9info:eu-repo/grantAgreement/ES/MINECO/DPI2017-84047-R
000079354 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000079354 590__ $$a4.821$$b2018
000079354 591__ $$aMECHANICS$$b6 / 134 = 0.045$$c2018$$dQ1$$eT1
000079354 591__ $$aMATHEMATICS, INTERDISCIPLINARY APPLICATIONS$$b2 / 105 = 0.019$$c2018$$dQ1$$eT1
000079354 591__ $$aENGINEERING, MULTIDISCIPLINARY$$b6 / 88 = 0.068$$c2018$$dQ1$$eT1
000079354 592__ $$a2.996$$b2018
000079354 593__ $$aComputational Mechanics$$c2018$$dQ1
000079354 593__ $$aComputer Science Applications$$c2018$$dQ1
000079354 593__ $$aPhysics and Astronomy (miscellaneous)$$c2018$$dQ1
000079354 593__ $$aMechanics of Materials$$c2018$$dQ1
000079354 593__ $$aMechanical Engineering$$c2018$$dQ1
000079354 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000079354 700__ $$aWu, W.
000079354 700__ $$0(orcid)0000-0001-9713-1813$$aCalvo, B.$$uUniversidad de Zaragoza
000079354 700__ $$aMalvè, M.
000079354 700__ $$aBüchler, P.
000079354 700__ $$aRodriguez Matas, J.F.
000079354 7102_ $$15004$$2605$$aUniversidad de Zaragoza$$bDpto. Ingeniería Mecánica$$cÁrea Mec.Med.Cont. y Teor.Est.
000079354 773__ $$g340 (2018), 202-215$$pComput. methods appl. mech. eng.$$tCOMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING$$x0045-7825
000079354 8564_ $$s480181$$uhttps://zaguan.unizar.es/record/79354/files/texto_completo.pdf$$yPostprint
000079354 8564_ $$s59999$$uhttps://zaguan.unizar.es/record/79354/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000079354 909CO $$ooai:zaguan.unizar.es:79354$$particulos$$pdriver
000079354 951__ $$a2020-01-17-22:11:12
000079354 980__ $$aARTICLE