Showing papers by "Italian Aerospace Research Centre published in 2022"

Status and Perspectives of Commercial Aircraft Morphing

Abstract: In a previous paper, the authors dealt with the current showstoppers that inhibit commercial applicability of morphing systems. In this work, the authors express a critical vision of the current status of the proposed architectures and the needs that should be accomplished to make them viable for installation onboard of commercial aircraft. The distinction is essential because military and civil issues and necessities are very different, and both the solutions and difficulties to be overcome are widely diverse. Yet, still remaining in the civil segment, there can be other differences, depending on the size of the aircraft, from large jets to commuters or general aviation, which are classifiable in tourism, acrobatic, ultralight, and so on, each with their own peculiarities. Therefore, the paper aims to trace a common technology denominator, if possible, and envisage a future perspective of actual applications.

Acceptance, Safety and Sustainability Recommendations for Efficient Deployment of UAM - Outline of H2020 CSA Project

Abstract: Abstract The vision of a third dimension added to hitherto nearly flat urban/metropolitan transport system gained the potential to become a mobility revolution for both logistics operators and, in the near future, for passengers as well. In spite of the expected emergence of this new form of transport and respective benefits for the efficiency of the mobility system at urban and suburban scale, UAM implementation also involves unprecedented and numerous challenges for cities and for all local public and private stakeholders. The local governing bodies are expected to provide policy, regulations and guidance for the implementation of UAM and to assure its integration with the ground mobility systems as well as with other urban functionalities. Taking into account both potential benefits and associated challenges related to UAM implementation, ASSURED-UAM (Acceptance, Safety and SUstainability Recommendations for Efficient Deployment of UAM) project, funded by the H2020 Programme, aims to support that effort, by providing a multidisciplinary study on operational and policy frameworks for the process of the introduction of unmanned modes of UAM.

Cross-Correlation Based Algorithm for SHM De-bonding Analysis of Typical Aeronautical Structures via OFDR

Abstract: AbstractAn SHM algorithm to detect damage size and location without the need of either strain or load reference was proposed and tested. The proposed methodology is based on the physical connection between the local signal scattering and the structural discontinuity, with respect to both geometrical distribution and time evolution. In detail, first order derivative is first applied, followed by a classical cross-correlation process to estimate the degree of relationship between the analysed signals. Deviations are quantified with respect to auto-correlation values. This approach was tested on a complex beam, made of two flat unidirectional carbon-epoxy tape skins and two C-shaped profile spars bonded together by a structural paste adhesive. Experiments consisted of making that test article undergo a 3-point bending by a dedicated tool, equipped with a linear actuator. In order to detect the debonding occurrences within the bonding line of the spar cap, optical fibres were integrated in the primary structure. Optical Frequency Domain Reflectometry (OFDR) was applied, implementing a 2 m long fibre optic having a spatial resolution of 2.6 mm and interrogating at a max sampling rate of 250 Hz, to monitor the spar bonding line. The results showed that the SHM algorithm provided reliable measurements for both position and size of the disbonding, and pose the right bases for further investigations on larger aeronautic scale.KeywordsFiber opticDamage detectionComposite beamCrosscorrelation

In-flight icing: a remote detection tool based on satellite data

Abstract: <p>One of the most severe weather hazards to aviation is in-flight airframe icing, i.e. the accretion of ice on airplane’s surfaces during flight. In order to increase margins of aviation safety, the early detection of regions affected by icing conditions is a challenging and desirable goal. In the framework of the H2020 EU project SENS4ICE (SENSors and certifiable hybrid architectures for safer aviation in ICing Environment), CIRA has developed a remote detection tool of icing conditions based on satellite data. Specifically, high-resolution satellite products, based on Meteosat Second Generation (MSG) data, have been considered, with spatial and temporal resolutions of about 3 km and 15 minutes respectively. The aim of this tool is to identify areas potentially affected by in-flight icing hazard, giving information about the severity of the phenomenon (light, moderate or severe) and an estimate of the altitude at which this hazard can occur. The developed algorithm also takes into account supercooled large droplets (SLD), which pose a serious threat to aviation and have been the cause of tragic accidents over the last decades. The tool relies on satellite data, to remotely infer the properties of clouds, and a set of experimental curves and envelopes that describe the interrelationship of cloud liquid water content, mean effective diameter of the cloud droplets and ambient air temperature. These curves, provided by the Federal Aviation Administration (FAA), define the atmospheric icing conditions and represent the reference legislation in this field. Furthermore, a nowcasting algorithm based on the extrapolation in time of the current icing conditions has been implemented, in order to perform a forecast over a short period ahead, responding to the great need for timely and location-specific forecasts that are relevant for aviation, e.g. for safety reasons or for planning and routing air traffic. This presentation will provide a preliminary analysis of the performance of the implemented tools, which will be evaluated in relevant icing conditions in the framework of SENS4ICE flight campaigns, planned for 2023.</p><p><em>Acknowledgment: This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement N° 824253 (SENS4ICE project).</em></p>

Database of the Italian disdrometer network

Abstract: Abstract. In 2021, a group of seven italian institutions decided to bring together their know-how, experience, and instruments for measuring the drop size distribution (DSD) of atmospheric precipitation giving birth to the Italian Group of Disdrometry (in Italian named: Gruppo Italiano Disdrometria, GID, https://www.gid-net.it/). The GID has made freely available a database of 1-minute records of DSD collected by the disdrometer network along the Italian peninsula. At the time of writing, the disdrometer network is composed of eight laser disdrometers belonging to six different Italian institutions (including research centers, universities and environmental regional agencies). This work aims to document the technical aspects of the italian DSD database consisting of 1-minute sampling data from 2012 to 2021 in a uniform standard format defined within GID. Although not all the disdrometers have the same length of the data record, the DSD data collection effort is the first of its kind in Italy, and from here onwards, it opens new opportunities in the surface characterization of microphysical properties of precipitation in the perspective of climate records. The GID database can be downloaded here https://doi.org/10.5281/zenodo.6875801 (Adirosi et al., 2022).

Analysis of vulnerability of ATM to weather phenomena

Abstract: Abstract Weather conditions and Air Traffic Management (ATM) operations are strongly related, due to the relevant influence that the observed and forecasted weather conditions into assigned airspace have on the operational conditions that are therefore possible for such airspace. In the framework of the SESAR JU funded project CREATE (Innovative operations and climate and weather models to improve ATM resilience and reduce impacts), therefore, a dedicated study has been carried out in order to investigate the relation between weather and ATM. Such study both investigated the consequences that adverse weather conditions can have on ATM and, on the other side, addressed the currently and future available tools that can support ATM in the prediction and management of weather conditions from the aeronautical operations point of view. In this paper, the results of such literature study are outlined. More in details, in the paper first the main outcomes of the study are summarized, in terms of identification of the most relevant weather phenomena that affect the ATM operations, indication of their main impacts on them in terms of operational disruptions and, finally, identification of the associated level of severity. In particular, the above indicated aspects are addressed by taking into specific consideration the enroute and the TMA (Terminal Manoeuvring Area) flight phases and, for each of them, the main affecting weather phenomena and the main affected operations are identified. Then, in the paper the results of the study are summarized about the identification of the most relevant meteo tools that are expressed by state-of-the-art technologies to support the ATM operations in order to properly take into account the weather conditions in a precise and timely manner. This study addresses both the review of available and perspective tools for weather reporting and of the available and perspective numerical models supporting ATM in terms of weather models and air quality models.

A sensitivity study on high resolution ICON-LAM and comparison with COSMO over Southern Italy 

Abstract: <p>The ICON (ICOsahedral Nonhydrostatic) is a joint project between the Deutscher Wetterdienst (DWD) and the Max-Planck-Institute for Meteorology (MPI-M) for the development of a unified global numerical weather prediction system. In 2018, COSMO (COnsortium for Small-scale Modeling) started the migration from the COSMO-LM to the ICON-LAM (ICON Limited Area Model) as the operational model. The main aim of this work is the presentation of a sensitivity study performed over a domain located in southern Italy (including the northern part of the Campania region and the southern part of Lazio) aimed to provide a contribution to the definition of a model configuration suitable for accurate weather forecasts over this area. Following the work performed by the authors with COSMO on a similar domain, the week 19-25 November 2018 has been selected as test case, when a low-pressure system coming from Western Mediterranean determined intense storms and gusts.</p><p>A computational grid R2B11, characterized by a very high resolution (about 1.2 km), has been adopted. Initial and boundary conditions are provided by the ECMWF IFS model at a spatial resolution of about 8.5 km. The sensitivity was carried out starting from a model configuration optimized by the authors (in a joint effort with the CMCC Foundation, Italy) over the whole Italian area, employing a grid with different resolution (R2B10, about 2.5 km). The reference configuration assumes that the shallow convection parameterization is active whereas the parts treating deep and mid-level convection are switched off. Moreover, a single moment cloud microphysics scheme and a diagnostic Kohler cloud cover scheme are employed.</p><p>A first sensitivity was performed with respect to the domain size, considering a reference domain (11.38° – 15.38° E; 40.25° - 42.25° N) and two additional domains respectively larger (in both directions) than 50% and 100% with respect to the original one. Then, a sensitivity to the numerical parameters, which have been shown to play a significant role in determining model response, has been carried out, e.g tkhmin (minimal diffusion coefficient for heat), rlam_heat (factor for laminar resistance for heat) and v0snow (factor for vertical velocity of snow).</p><p>Model evaluation has been conducted against ground observation data provided by CIRA instrumentation and by the SCIA system developed by ISPRA (Italy). Moreover, a comparison with forecasts provided by the COSMO model at 0.009° (about 1 km resolution) forced by the same driving data has been performed, in order to highlight the differences between the performances of the two models.</p>

Mapping soil texture with airborne gamma ray spectroscopy

Abstract: <p>Soil texture is a key information in precision agriculture for improving soil knowledge and crop performances. A precise mapping of its variability is thereby imperative for rationally planning cultivations and targeting interventions. Unlike direct soil texture measurements that are punctual, destructive, and time-consuming, remote sensing surveys can give widespread, non-invasive, and fast indirect evidence of clay, silt, and sand content. In this study we investigate the performance of Airborne Gamma Ray Spectroscopy (AGRS) for discriminating different texture classes in the ternary diagram of soil texture.</p><p>The Mezzano valley (Ferrara, Italy), a 180 km<sup>2</sup> rural area reclaimed in the last century, represents an extraordinary benchmark for validating our method. This area, for which a public soil texture map at 1:50000 scale and a spatial resolution of 500 m is available, was scanned by an AGRS system mounted on a dedicated aircraft. The aircraft flew over the study area in a grid-like path of ~500 m spacing, collecting 1469 geolocalized spectra. The K and Th punctual measurements were spatially interpolated by Ordinary Kriging to elaborate K and Th maps with the identical spatial resolution of the soil texture map. Simple and multiple linear correlations, as well as a non‑linear Machine Learning algorithm, were then performed between gamma and soil texture data.</p><p>The obtained results by a simple linear regression analysis highlight a moderate positive (negative) correlation between clay (sand) content and K and Th abundances. Multiple linear regressions show a similar trend, with the limitation that the calculated clay, silt, and sand values populate the soil texture ternary diagram in a straight line. Finally, we demonstrate that the most accurate reconstruction of soil texture values is obtained by a non-linear fitting based on the Machine Learning algorithm.</p>

A multiscale approach for discovery of illegal micro-dumps based on satellite detections

Abstract: <p>Satellite remote sensing allows for large scale monitoring with low cost and high revisit time. However, in some applications, it does not provide all the information needed by the analyst for the full characterization of the problem due to, as an example, insufficient resolution or lack of specific measurements. This can lead to inaccuracies in classification and/or detection tasks. Nevertheless, satellite data can be used to guide subsequent discovery, recognition and characterization actions, defining potential areas of interest of limited extension that can be furtherly investigated with on-site strategies. This work presents an innovative framework showing how to use incomplete and inaccurate information extracted by satellite images in order to address on-ground discovery actions aimed to the mapping and the characterization of illegal micro-dumps in Campania Region (Italy). In particular, high-resolution images up to 50 cm resolution are exploited to detect potential micro-dumps by means of a statistical learning method based on spatial features. The detection map is then used to create a priority map based on environmental risk considerations, such as the extension of the area interested by the dump and its proximity to urban settlements, and previous risk mitigation actions. This information is ingested by a planning system in order to allocate and calculate patrolling routes based on the available manpower and vehicles for on-site surveying. The survey is implemented by means of drones equipped with payloads and software allowing for real-time three-dimensional reconstruction of the scene and volumetric estimations. This provides further data to assess the real dangerousness of the site giving to decision makers essential information to plan remediation actions. The system is demonstrated through a case study showing all the stages of the decision process.</p>

Discovery and characterization of environmental hazards by means of dynamic coordination of drones driven by satellite detection maps

Abstract: <p>In some environmental applications, satellite acquisitions could not be able to provide all the information necessary to characterize the problem at hand due, for example, to limited spatial resolution or inadequate revisit time. However, in these cases, they can be used for preliminary investigation of the area of interest with the purpose to guide subsequent acquisitions with higher spatial resolution made by means of aerial sensing. This work presents an innovative application combining both satellite acquisitions and aerial close-range sensing implemented via drones in autonomous and coordinated flight. The case study concerns the discovery of illegal micro-dumps and other environmental hazards in Campania Region (Italy). The envisioned workflow includes the detection of target environmental criticalities in very high-resolution optical satellite images and a methodology to plan and adaptively re-plan a survey mission of a team of drones aimed at confirming the presence of a micro-dump and at its characterization. The processing of satellite images is validated on real data in a significative application context, while the performance of the acquisition strategy performed by the drone team are characterized trough simulations on a pre-analysed geographical area.</p>

Using disdrometers data to evaluate GPM-DPR products over Italy

Abstract: <p>Remote sensing measurements provided by satellite-borne radars play a fundamental role in estimating precipitation distribution worldwide. However, they are subjected to a variety of potential errors and need continuous validation with ground-based measurements. Validating satellite products using measurements collected by sensors at the ground has been addressed in the literature, but it is still challenging due to intrinsic differences in the measuring principle and viewing geometries of the instrument being compared each other. To date, the Dual-frequency Precipitation Radar (DPR) aboard the Core Satellite of the Global Precipitation Measurement (GPM) mission is the only active sensor able to provide, at the global scale, vertical profiles of rainfall rate, radar reflectivity, and Drop Size Distribution (DSD) parameters from space. After the launch of the GPM Core Satellite, on February 2014, an extensive Ground Validation (GV) program was established with the aim of evaluating the performance of the retrieval algorithms, over long periods and in different climatic regions across the world. Since the free availability of GPM data, many studies have been conducted to compare and validate the available version of satellite precipitation products with data collected by ground-based instrumentations such as radars and rain gauges, however very few published studies used networked disdrometers data on national scale.</p><p>For the first time, we used disdrometers to evaluate near surface GPM-DPR products (Version V06A) against long time series of measurements collected by seven laser disdrometers dislocated along the Italian peninsula and networked thanks to a cooperation effort of seven institutions (including research centers, universities and environmental regional agencies). The comparison was made in terms of rainfall and DSD parameters: rainfall rate, radar reflectivity, mass-weighted mean diameter (D<sub>m</sub>), and normalized gamma DSD intercept (N<sub>w</sub>). The comparison showed limited differences between single- or dual-frequency GPM algorithms, although the former presents better performance in most cases. The conclusions suggest that the agreement was good for rain rate, reflectivity factor, and D<sub>m</sub>, while N<sub>w</sub> satellite estimates need to be improved. Same method is used for evaluating current V07A of precipitation products.</p><p>Given the collaborative nature that has allowed the validation analysis presented, this study also represents an opportunity to consolidate cooperation between Institutions managing disdrometers in Italy and set the stage for future plans aimed at improving the use of disdrometer data in Italy.</p>

RadHawk: a smart UAV for hunting radioactivity

Abstract: <p>Vertical take-off and landing Unmanned Aerial Vehicles (UAVs) for Gamma-Ray Surveys (GRS) provide a cost-effective and timely approach tool for environmental radioactivity mapping. The UAV technique combines the advantages of ground and airborne measurements:  there is no need for an airport for take-off and landing, and high spatial resolution surveys can also be performed in dangerous areas without endangering the operators.</p><p>The main limitation of existing UAVs for GRS is the lack of software and hardware integration between avionics systems and radiation detectors. RadHawk fills this gap with an advanced mechanical, electronic, and software connection between a specifically developed quadcopter and a digital Multi-Channel Analyzer GammaStream (GS). The GS is coupled with a 2” CeBr<sub>3</sub> scintillator having spectral energy resolution ~60% better than that of a NaI for <sup>137</sup>C detection. Communication between the GS onboard microcomputer and the drone’s autopilot Pixhawk is achieved through a custom protocol which allows sharing telemetry updates and executing commands.</p><p>The best spatial resolution of radiometric data is achieved through a list mode real-time processing that generates, with optimized acquisition time, energy calibrated georeferenced gamma spectra. A radio frequency transceiver module sends data to a control station, where the user can easily control the flight path and check the artificial radionuclides warning for real-time identifying of hotspots.</p><p>A post-processing algorithm based on a Full Spectrum Analysis – Maximum Likelihood Estimation was developed to enhance the identification capability of anthropogenic radionuclides and to produce maps of the K, Th and U abundances of the investigated areas.</p>