
handle: 11367/65364
Abstract The structural health monitoring (SHM) plays an essential role in system health management applications for aeronautic and space transportation vehicles, manned and unmanned. The unmanned aircraft systems (UAS) are also extremely needed in various fields of interest, from military to civilian (search and rescue, environmental surveillance and monitoring, entertainment). This work presents an innovative UAS fixed-wing design and control through an inverse finite element method-based, which compute the full-field displacements reconstruction of a three-dimensional shell/plate deformations from experimentally measured surface strains. The full-field displacements are useful for the preliminary design and inspections of the UAS loads, caused by maneuvers or gusts. Goal of this paper was to validate the high accuracy predictions of deformations afforded due to the inverse finite element method (iFEM). Overall formulation was based on the minimization of a least-squares functional that uses and compares the strains extracted due to embedded sensors with the strains of linear, first order shear-deformation theory. The test article was a thin plate equipped with embedded sensors (strain gauge sensors) which permit to extract surface strains in real-time, used as input data for shape sensing. The plate was used to approximate an UAS wing box section, in further work analyzed.
Aircraft design; Finite element method; Flight mechanics; Inverse problem; Structural health monitoring; UAS; Aerospace Engineering
Aircraft design; Finite element method; Flight mechanics; Inverse problem; Structural health monitoring; UAS; Aerospace Engineering
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 91 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
