Isogeometric iFEM Analysis of Thin Shell Structures

Shape sensing is one of most crucial components of typical structural health monitoring systems and has become a promising technology for future large-scale engineering structures to achieve significant improvement in their safety, reliability, and affordability. The inverse finite element method (i...

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Main Authors: Adnan Kefal, Erkan Oterkus
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/20/9/2685
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spelling doaj-2fdff8e17845457e97aefb0315fa87392020-11-25T03:10:03ZengMDPI AGSensors1424-82202020-05-01202685268510.3390/s20092685Isogeometric iFEM Analysis of Thin Shell StructuresAdnan Kefal0Erkan Oterkus1Faculty of Engineering and Natural Sciences, Sabanci University, Tuzla, Istanbul 34956, TurkeyPeriDynamics Research Centre, Department of Naval Architecture, Ocean and Marine Engineering, University of Strathclyde, Glasgow G4 0LZ, UKShape sensing is one of most crucial components of typical structural health monitoring systems and has become a promising technology for future large-scale engineering structures to achieve significant improvement in their safety, reliability, and affordability. The inverse finite element method (iFEM) is an innovative shape-sensing technique that was introduced to perform three-dimensional displacement reconstruction of structures using in situ surface strain measurements. Moreover, isogeometric analysis (IGA) presents smooth function spaces such as non-uniform rational basis splines (NURBS), to numerically solve a number of engineering problems, and recently received a great deal of attention from both academy and industry. In this study, we propose a novel “isogeometric iFEM approach” for the shape sensing of thin and curved shell structures, through coupling the NURBS-based IGA together with the iFEM methodology. The main aim is to represent exact computational geometry, simplify mesh refinement, use smooth basis/shape functions, and allocate a lower number of strain sensors for shape sensing. For numerical implementation, a rotation-free isogeometric inverse-shell element (isogeometric Kirchhoff–Love inverse-shell element (iKLS)) is developed by utilizing the kinematics of the Kirchhoff–Love shell theory in convected curvilinear coordinates. Therefore, the isogeometric iFEM methodology presented herein minimizes a weighted-least-squares functional that uses membrane and bending section strains, consistent with the classical shell theory. Various validation and demonstration cases are presented, including Scordelis–Lo roof, pinched hemisphere, and partly clamped hyperbolic paraboloid. Finally, the effect of sensor locations, number of sensors, and the discretization of the geometry on solution accuracy is examined and the high accuracy and practical aspects of isogeometric iFEM analysis for linear/nonlinear shape sensing of curved shells are clearly demonstrated.https://www.mdpi.com/1424-8220/20/9/2685inverse finite element method (iFEM)isogeometric analysisthin and curved shellsshape sensingstructural health monitoringstrain sensors
collection DOAJ
language English
format Article
sources DOAJ
author Adnan Kefal
Erkan Oterkus
spellingShingle Adnan Kefal
Erkan Oterkus
Isogeometric iFEM Analysis of Thin Shell Structures
Sensors
inverse finite element method (iFEM)
isogeometric analysis
thin and curved shells
shape sensing
structural health monitoring
strain sensors
author_facet Adnan Kefal
Erkan Oterkus
author_sort Adnan Kefal
title Isogeometric iFEM Analysis of Thin Shell Structures
title_short Isogeometric iFEM Analysis of Thin Shell Structures
title_full Isogeometric iFEM Analysis of Thin Shell Structures
title_fullStr Isogeometric iFEM Analysis of Thin Shell Structures
title_full_unstemmed Isogeometric iFEM Analysis of Thin Shell Structures
title_sort isogeometric ifem analysis of thin shell structures
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2020-05-01
description Shape sensing is one of most crucial components of typical structural health monitoring systems and has become a promising technology for future large-scale engineering structures to achieve significant improvement in their safety, reliability, and affordability. The inverse finite element method (iFEM) is an innovative shape-sensing technique that was introduced to perform three-dimensional displacement reconstruction of structures using in situ surface strain measurements. Moreover, isogeometric analysis (IGA) presents smooth function spaces such as non-uniform rational basis splines (NURBS), to numerically solve a number of engineering problems, and recently received a great deal of attention from both academy and industry. In this study, we propose a novel “isogeometric iFEM approach” for the shape sensing of thin and curved shell structures, through coupling the NURBS-based IGA together with the iFEM methodology. The main aim is to represent exact computational geometry, simplify mesh refinement, use smooth basis/shape functions, and allocate a lower number of strain sensors for shape sensing. For numerical implementation, a rotation-free isogeometric inverse-shell element (isogeometric Kirchhoff–Love inverse-shell element (iKLS)) is developed by utilizing the kinematics of the Kirchhoff–Love shell theory in convected curvilinear coordinates. Therefore, the isogeometric iFEM methodology presented herein minimizes a weighted-least-squares functional that uses membrane and bending section strains, consistent with the classical shell theory. Various validation and demonstration cases are presented, including Scordelis–Lo roof, pinched hemisphere, and partly clamped hyperbolic paraboloid. Finally, the effect of sensor locations, number of sensors, and the discretization of the geometry on solution accuracy is examined and the high accuracy and practical aspects of isogeometric iFEM analysis for linear/nonlinear shape sensing of curved shells are clearly demonstrated.
topic inverse finite element method (iFEM)
isogeometric analysis
thin and curved shells
shape sensing
structural health monitoring
strain sensors
url https://www.mdpi.com/1424-8220/20/9/2685
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