Transmission or 'creative fidelity'? The institutional communicator's role in the Church today

The role of the institutional communicator in the Church today has a special relevance derived from the credibility crisis suffered by this institution. A greatly increased awareness to this theme leads to the discovery of profound and essential dimensions of this role, which are discussed in this article. The focus is on the credibility of the communicator, who, on one hand is called to take full responsibility for what he says, but on the other hand speaks in the name of and through a collective subject—the Church or one of its specific constituent parts—that doesn't always receive much appreciation from its numerous audiences; it is actually often perceived to be "biased" as an institution, it is widely opposed and criticized. An in-depth analysis regarding the role of credibility from a sociological point of view is illustrated by the application of the three roles identified by Erving Goffman—animator, author and principal—to the figure of the institutional communicator, underlining his responsibilities as communication co-leader. A comparison with the concept of translator as a mediator illuminates other characteristics of the communicator, and functions as a basis to comment on some of the virtues (both personal and professional), which he must possess, enhancing both his credibility and efficiency. The application of the concept of creative fidelity (fidélité créatrice) from the French philosopher Gabriel Marcel, together with the interrelation between comprehension and exposition in a comprehensible manner (hermeneutics and creativity), highlights the necessity of reconsidering the importance of communication and of the communicator within the decision-making process

2D Closed-Form Solution for the Measurement of the Angle of Attack and Sideslip Angle

At the beginning of 2021, the measurement of the Angle of Attack and of the Angle of Sideslip is still mainly conducted with physical protruding probes. Although several alternative methods have been proposed in literature, the attention is generally focused on data-driven methods and little discussion is conducted on the mathematical problem. If the formulation that allows to associate the aerodynamic angles to other flight parameters has a closed-form solution is still an open question in the field. This paper provides a closed-form solution for a restricted problem where one of the two angle is known. Moreover, a linearized solution is provided. The result section gives evidence of the approach in simulated environment, showing the advantages of the nonlinear solution with respect to the linear one

Sensitivity Analysis of a Certifiable Synthetic Sensor for Aerodynamic Angle Estimation

Nowadays, some alternative methods exist for the replacement of physical vanes (or probes) for aerodynamic angles (angle of attack and sideslip) with synthetic solutions. The results are promising and there is a growing interest for the industry in this particular solution. However, a lack of methods has been observed to estimate their performance and to compare them. The MIDAS project, funded in the Clean Sky 2 frame, will provide the aerospace community with an innovative modular digital air data system (ADS) based on synthetic sensors for aerodynamic angles. To meet the system requirement specifications given by the project leader, a method of uncertainty estimation must be implemented. This paper proposes a method of estimation of the overall uncertainty based on a consolidated metrological procedure. This method holds a certain degree of generality because it can be applied to different kinds of architecture of the synthetic sensor. In this paper, it has been applied to the preliminary design of the synthetic sensor of the MIDAS air data system and the results have been reported as example

Sensitivity Analysis of a Neural Network based Avionic System by Simulated Fault and Noise Injection

The application of virtual sensor is widely discussed in literature as a cost effective solution compared to classical physical architectures. RAMS (Reliability, Availability, Maintainability and Safety) performance of the entire avionic system seem to be greatly improved using analytical redundancy. However, commercial applications are still uncommon. A complete analysis of the behavior of these models must be conducted before implementing them as an effective alternative for aircraft sensors. In this paper, a virtual sensor based on neural network called Smart-ADAHRS (Smart Air Data, Attitude and Heading Reference System) is analyzed through simulation. The model simulates realistic input signals of typical inertial and air data MEMS (Micro Electro-Mechanical Systems) sensors. A procedure to define the background noise model is applied and two different cases are shown. The first considers only the sensor noise whereas the latter uses the same procedure with the operative flight noise. Flight tests have been conducted to measure the disturbances on the inertial and air data sensors. Comparison of the Power Spectral Density function is carried out between operative and background noise. A model for GNSS (Global Navigation Satellite System) receiver, complete with constellation simulator and atmospheric delay evaluation, is also implemented. Eventually, a simple multi-sensor data fusion technique is modeled. Results show good robustness of the Smart-ADAHRS to the sensor faults and a marginal sensitivity to the temperature-related faults. Solution for this kind of degradation is indicated at the end of the paper. Influences of noise on input signals is also discussed

A Data-Driven Approach to Identify Flight Test Data Suitable to Design Angle of Attack Synthetic Sensor for Flight Control Systems

Digital avionic solutions enable advanced flight control systems to be available also on smaller aircraft. One of the safety-critical segments is the air data system. Innovative architectures allow the use of synthetic sensors that can introduce significant technological and safety advances. The application to aerodynamic angles seems the most promising towards certified applications. In this area, the best procedures concerning the design of synthetic sensors are still an open question within the field. An example is given by the MIDAS project funded in the frame of Clean Sky 2. This paper proposes two data-driven methods that allow to improve performance over the entire flight envelope with particular attention to steady state flight conditions. The training set obtained is considerably undersized with consequent reduction of computational costs. These methods are validated with a real case and they will be used as part of the MIDAS life cycle. The first method, called Data-Driven Identification and Generation of Quasi-Steady States (DIGS), is based on the (i) identification of the lift curve of the aircraft; (ii) augmentation of the training set with artificial flight data points. DIGS’s main aim is to reduce the issue of unbalanced training set. The second method, called Similar Flight Test Data Pruning (SFDP), deals with data reduction based on the isolation of quasi-unique points. Results give an evidence of the validity of the methods for the MIDAS project that can be easily adopted for generic synthetic sensor design for flight control system applications

Advantages of Neural Network Based Air Data Estimation for Unmanned Aerial Vehicles

Redundancy requirements for UAV (Unmanned Aerial Vehicle) are hardly faced due to the generally restricted amount of available space and allowable weight for the aircraft systems, limiting their exploitation. Essential equipment as the Air Data, Attitude and Heading Reference Systems (ADAHRS) require several external probes to measure significant data as the Angle of Attack or the Sideslip Angle. Previous research focused on the analysis of a patented technology named Smart-ADAHRS (Smart Air Data, Attitude and Heading Reference System) as an alternative method to obtain reliable and accurate estimates of the aerodynamic angles. This solution is based on an innovative sensor fusion algorithm implementing soft computing techniques and it allows to obtain a simplified inertial and air data system reducing external devices. In fact, only one external source of dynamic and static pressures is needed. This paper focuses on the benefits which would be gained by the implementation of this system in UAV applications. A simplification of the entire ADAHRS architecture will bring to reduce the overall cost together with improved safety performance. Smart-ADAHRS has currently reached Technology Readiness Level (TRL) 6. Real flight tests took place on ultralight aircraft equipped with a suitable Flight Test Instrumentation (FTI). The output of the algorithm using the flight test measurements demonstrates the capability for this fusion algorithm to embed in a single device multiple physical and virtual sensors. Any source of dynamic and static pressure can be integrated with this system gaining a significant improvement in terms of versatility

Ill-conditioned problems improvement adapting Joseph covariance formula to non-linear Bayesian filters

Integration of Unmanned Aerial Vehicles (UAVs) into civil airspace is becoming a fundamental requirement to satisfy the even more consumer growing demand. The limiting issues for this integration are related to the development of a reliable Sense and Avoid (SAA) system able to equate the human eye performances. Multisensor data fusion techniques are generally used in order to overcome single sensor shortcomings. Although much research addresses toward the realisation of better performing sensors, system degradation could arise from bad numerical behaviours injected by the specific fusion algorithm. Bayesian estimators are the most widely used techniques to perform this task but they could be affected by round-off errors. To improve filter instabilities, induced by ill-conditioned matrices, an alternative numerical approach, based on the Joseph form of the state covariance matrix update applied to non-linear systems is presented. The novelty of this technique lies on taking advantage from the higher order accuracy ensured by Sigma-Point Kalman Filters for solving non-linear inference problems, and using the more numerically robust Joseph update equation

DEFINITION OF THE FLEXIBLE AIRCRAFT LONGITUDINAL MODEL FOR A PRELIMINARY CONTROL DESIGN

Developing control system of high aspect ratio aircraft can be challenging due to flexibility involved in the control loop design. A model based approach can be straightforward to tune the control system parameters and, to this aim, a reliable aircraft flexible model is necessary. This paper aims to present the approach followed to design the longitudinal control strategy considering the aircraft simulator in the loop. The elastic modes are calculated from the lumped mass geometrical model and an aerodynamic properties from a reference aircraft. The approach and the model validation have been done in partnership with Leonardo Aircraft, as a thesis topic. Beginning with verification of the trim conditions, the flexible dynamic modes are compared to the rigid ones in order to highlight the relevant changes in the aircraft modes. A preliminary design of the longitudinal control strategy is herein proposed to achieve the dynamic response objectives