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In this paper the Particle Finite Element Method (PFEM) is applied to the simulation of the sea-landing of an unmanned aerial vehicle (UAV). The problem of interest consists in modelling the impact of the vehicle against the water surface, analyzing the main kinematic and dynamic quantities (such as loads exerted upon the capsule at the moment of the impact). The PFEM, a methodology well-suited for free-surface flow simulation is used for modelling the water while a rigid body model is chosen for the vehicle. The vehicle under consideration is characterized by low weight. This leads to difficulties in modelling the fluid–structure interaction using standard Dirichlet–Neumann coupling. We apply a modified partitioned strategy introducing the interface Laplacian into the pressure Poisson's equation for obtaining a convergent FSI solution. The paper concludes with an industrial example of a vehicle sea-landing modelled using PFEM.

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The aim of the paper is to analyze practical aspects with use of 3D Model for accurate building condition assessment. Use of fully interactive visualization methods from a technical condition assessment platform going to be, especially taking into consideration current COVID-19 scenarios, a very supportive tool for the massive inspection of building stocks, particularly in big residential areas. The authors present the approach based on high-performance images that were captured by Unmanned Aerial Vehicles (UAVs). The next step is the generation of a 3D model and orthophotos of building facades. The graphical information together with tables of attributes will allow the interactive geo-referenced management and assessment, that is proposed as a form of interactive cooperation. The idea of this approach corresponds widely with the Building Information Modeling aims. The authors introduce the methodology, stages of the inventory and follow-up process carried out within the platform requirements together with advantages of the visualization techniques, basing on a particular case study. Technical details about the information system and the analysis connected with the visualization utility will be presented and illustrated.

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Unmanned Aerial Vehicles (UAVs) are flying robots that require little or no human control while flying. The number of UAV has growth exponentially due to rise in applications such as video taking, surveillance and delivering cargo to customers. Despite the promise of the technology, UAV are not very reliable currently, either civil or military. They lack of sensing mechanisms to detect issues in operation, such impacts, hard landings and overload, together with the difficulties to detect structural problems during the UAV operation could compromise not only the safety of the UAV, also all along the entire flying area. This paper presents the design, development implementation, and validation of a Structural Health Monitoring (SHM) system applied to the rear fuselage of the UAV developed by INTA for R&D activities (MILANO). The rear fuselage, a 2.5 meters carbon/epoxy structure with frames and stringers, was instrumented with fiber optic sensors and PZT. Two different types of fiber optic sensors were considered: Fiber Bragg Gratings and distributed fiber sensing based on Rayleigh backscatter. The objective of the fiber optic sensor network is to detect the changes induced on the strain field due to damage appearance. This information will be employed to train a neural network which provides the self-diagnosis of the structural integrity. Additionally, the PZT network will be used as active system for structure interrogation through elastic waves.