Sensitivity Analysis for Electrical Detection of Aortic Dissection. Issue 1 (8th October 2019)

• Record Type: Journal Article
• Authors: Melito, Gian Marco; Badeli, Vahid; Reinbacher-Köstinger, Alice; Ellermann, Katrin
• Other Names: Eberhardsteiner J. guestEditor.; Schöberl M. guestEditor.
• Is Part Of: Proceedings in applied mathematics and mechanics. Volume 19:Issue 1(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-10-08
• Subjects: Applied mathematics -- Periodicals; Engineering mathematics -- Periodicals; Mathematical physics -- Periodicals; 519
• DOI: 10.1002/pamm.201900062
• Languages: English
• ISSNs: 1617-7061

Abstract

Abstract: In medical and patient‐specific applications, uncertainty quantification and sensitivity analysis are indispensable in the process of diagnosis and decision‐making. For the identification of an aortic dissection, a 3D FEM model is used to simulate an appropriate measurement setup. Based on this model, a method to evaluate the uncertainty distribution of a pre‐defined parameter set is proposed. In particular, sensitivity analysis is divided into two steps. The first step involves an initial screening using the Morris method. In the second step, a sensitivity analysis is performed through a variance‐based setting. Here, Polynomial Chaos Expansion (PCE) surrogate model is used. Subsequent post‐processing on the study allows the computation of the representative sensitivity indices.