Flush Air Data System Research Articles

Comparing a 3-d printed hemispherical-head and Rankine-body probe shapes for very low speed flush air data system (FADS) measurements

This study investigates the feasibility of using Flush Air Data Sensing (FADS) System technology for air data measurements at the very low-airspeeds, where many Unmanned Aerial Vehicles (UAVs) operate. FADS is a non-intrusive alternative to pitot probes, where the vehicle nosecone, wing leading edge, or other aerodynamic surfaces are configured with multiple pressure-ports distributed along the windward face. Although FADS technology has been used for a variety of high-speed aircraft, FADS has never been applied to very low-airspeed flight regimes. This study reports on wind tunnel tests of two 3-D printed shapes: 1) a cylindrical body with a hemispherical head, and 2) a Rankine-Body. These body shapes can act as a vehicle analog to a wide range of three-dimensional shapes and account for both blunt leading edge and trailing after body flow characteristics. For this study the "probes" were printed with 5 pressure ports and the associated flow channels aligned at 0o, +22.5o and +45o direction-angles along the vertical centerlines of the models. Sensed pressure data were curve-fit, developing quasi-potential flow calibration models for each probe, with coefficients compiled as a function of geometric angle-of-attack and tunnel airspeed. The calibration models account for end-to-end systematic effects, including the mounting sting flow compression, up wash, and tunnel blockage. Using the derived calibration models and the sensed pressure data, the effective angles-of-attack were re-calculated using the well-known "Triples" algorithm. The associated airspeed and dynamic pressure are estimated from the sensed pressure data using non-linear regression. The resulting estimates are compared to the tunnel reference conditions. Generally, both probe shapes performed well, with the redundant 5-port arrangement allowing for significant noise rejection. Both probes achieved RMS airspeed errors of less than 5%, angle-of-attack errors less than 1 deg., and dynamic pressure errors of less than 12 pascals, across airspeeds ranging from 5 to 25 m/sec. The sensed Airdata measurements at the lowest airspeeds (5 m/sec), exhibited similar accuracy to those sensed at the highest airspeeds (25 m/sec), verifying the applicability of FADS technology to very low airspeed flight regimes.

Flush Airdata System on a Flying Wing Based on Machine Learning Algorithms

By using an array of pressure sensors distributed on the surface of an aircraft to measure the pressure of each port, the flush airdata sensing (FADS) system is widely applied in many modern aircraft and unmanned aerial vehicles (UAVs). Normally, the pressure transducers of the FADS system should be mounted on the leading edge of the aircraft, where they are sensitive to changes in pressure. For UAVs, however, the leading edge of the nose and wing may not be available for pressure transducers. In addition, the number of transducers is limited to 8–10, making it difficult to maintain accuracy in the normal method for FADS systems. An FADS system model for an unmanned flying wing was developed, and the pressure transducers were all located outside the regions of the leading edge areas. The locations of the transducers were selected by using the mean impact value (MIV), and ensemble neural networks were developed to predict the airdata with a very limited number of transducers. Furthermore, an error detection method was also developed based on artificial neural networks and random forests. The FADS system model can accurately detect the malfunctioning port and use the correct pressure combination to predict the Mach number, angle of attack, and angle of sideslip with high accuracy.

Tianwen-1 Mars entry vehicle trajectory and atmosphere reconstruction preliminary analysis

The Tianwen-1 Mars entry vehicle successfully landed on the surface of Mars in southern Utopia Planitia on May 15, 2021, at 7:18 (UTC+8). To acquire valuable Martian flight data, a scientific instrumentation package consisting of a flush air data system and a multilayer temperature-sensing system was installed aboard the entry vehicle. A combined approach was applied in the entry, descent, and landing trajectory reconstruction using all available data obtained by the inertial measurement unit and the flush air data system. An aerodynamic database covering the entire flight regime was generated using computational fluid dynamics methods to assist in the reconstruction process. A preliminary analysis of the trajectory reconstruction result, along with the atmosphere reconstruction and aerodynamic performance, was conducted. The results show that the trajectory agrees closely with the nominal trajectory and the wind-relative attitude. Suspected wind occurred at the end of the trajectory.

Design and Verification of Flush Air Data Sensing Module with Navigation and Temperature Information

For aircraft which move in the atmosphere, the angle of attack and angle of sideslip cannot be measured precisely. This limits the precision of guidance and control systems, so the flush air data sensing system module with navigation and temperature information is designed for atmosphere parameter calculation. In this work the traditional parameter calculation method is improved, and a new algorithm which combines pressure data, temperature data and navigation data to calculate the atmosphere parameters is proposed. A ground experiment test scheme with a simulated flight environment is designed and the measured data is fitted and filtered to complete the experiments. The flush air data sensing module gets pressure data and temperature data of the atmosphere with sensors, and the measured data is integrated with navigation information to calculate the aircraft parameters of the angle of attack, angle of sideslip, dynamic pressure, static pressure, Mach number and so on. Calculated parameters can be transmitted to guidance and control systems to improve the attitude and trajectory precision for an aircraft. Experimental results show that the software and hardware of the flush air data system module with navigation and temperature information work well, and communication of various devices is normal. The flight status of aircraft can be precisely calculated online, which provides a useful reference for prospective wind tunnel experiments and flight tests.

Estimation of Angle of Attack in Satellite Launch Vehicle Using Flush Air Data Sensing Systems at Mach 0.5 to 3.0

This paper presents an inverse analysis to estimate angle of attack during ascent period of a satellite launch vehicle. Aerodynamic results are numerically computed by solving three dimensional, time dependent, compressible inviscid equations over payload shroud of a satellite launch vehicle. The flush air data system consists of four pressure ports flushed with conical-nose section of the payload fairing and connected to on board differential pressure transducers. The inverse algorithm uses calibrations charts which based on computed and measured data. A controlled random search method is used to predict pitch, yaw and total angle of attack of vehicle from measured transient differential pressure history in flight from Mach numbers range of 0.5 to 3.0. The algorithm predicts the flow direction stepwise with function of flight Mach numbers and can be termed as online method. Flow direction of the launch vehicle is compared with the reconstructed trajectory data. The estimated values of the flow direction are found in good agreement them.

FADS based aerodynamic parameters estimation for mars entry considering fault detection and tolerance

Flush air data system (FADS) is able to sense pressure distribution on the surface of the vehicle's forebody during Mars entry phase. Existing studies on the FADS-based aerodynamics data estimation for Mars entry have not attached adequate attention to the potential FADS fault, which should not be ignored in practice from a reliability viewpoint. In this paper, a hybrid method is proposed to simultaneously achieve aerodynamic parameters estimation of Mars entry vehicle and FADS fault detection and tolerance. The estimation procedure merges triples algorithm based coarse estimation with least-square based precise estimation. Meanwhile, a fault identifier matrix is embedded in the estimation procedure, which is worked out from chi-square detection algorithm. The estimation with FADS fault tolerance is realized by the fusion of chi-square detection, hybrid estimation, and random sample consensus algorithms. Comparison simulations demonstrate the effectiveness of the proposed technique.

Numerical Calibration of a Low-Speed sUAS Flush Air Data System

AbstractA method using computational fluid dynamics to numerically calibrate a flush air data system is presented. A small unmanned aircraft system (sUAS) has been equipped with a flush air data system and experimentally tested. The flush air data system uses computational fluid dynamics to train neural networks and is validated using the in-flight data that were previously collected. Results of the flight validation are presented, along with ways to improve the accuracy of the system. Several different calibration approaches are presented and compared with each other. The best-case results with the in-flight calibration are 0.59° and 0.66° for angle of attack and sideslip, respectively, whereas the best-case results when calibrated with computational fluid dynamics data are 0.78° and 0.90°. It is also possible to estimate other air data parameters, such as dynamic pressure, static pressure, and density, with neural networks, but the direct calculation is more accurate. Calibrating the system numerically, such as with the use of computational fluid dynamics, removes the need for any calibration flights. Although not as accurate as the in-flight calibration, numerical calibration is possible and can save the user time and expense.

ExoMars Flush Air Data System: Entry Simulation and Atmospheric Reconstruction Method

Flight data recorded during atmospheric entry with forebody pressure instrumentation, referred to as a flush air data system (FADS), provide valuable measurements for the reconstruction of the trajectory and in situ atmospheric conditions. We present a method to reconstruct the angle of attack; sideslip angle; and atmospheric density, pressure, and temperature in support of the postflight analysis for the ExoMars Entry, Descent, and Landing Demonstrator Module (EDM), named Schiaparelli. Numerical predictions of the forebody surface pressure distribution, required as input to the FADS reconstruction, were developed in a companion paper. Here, we demonstrate the FADS method in a hypersonic wind tunnel at Mach 5 to 7 and study theoretical FADS reconstruction performance along a simulated along a simulated entry trajectory. The main error sources identified are unobserved winds and measurement bias errors; the latter are exacerbated by the limited number of pressure ports on the EDM.

ExoMars Flush Air Data System: Experimental and Numerical Investigation

The atmospheric reconstruction based on a flush air data system requires knowledge of the surface pressure distribution, which depends on various factors such as the Mach number, angle of attack, and aeroshell geometry of the entry vehicle. The purpose of this work is to provide this information for the postflight analysis of the entry, descent, and landing module of ExoMars 2016, which is called Schiaparelli. Because the flow around the capsule cannot be duplicated exactly in ground testing facilities, and to account for the uncertainties in physical modeling by numerical simulation, a hybrid approach is chosen for the study. First, the atmospheric entry is simulated experimentally, and these experiments are then simulated numerically. The experimental and numerical results are compared and discussed. The almost perfect agreement validates the numerical tool, which is applied afterward to the analysis of the entry flight of Schiaparelli. A focus lies on the understanding of experimental uncertainties and on the impact of necessary numerical simplifications.

Development and Flight Test Results of a Small UAS Distributed Flush Airdata System

AbstractSmall unmanned aircraft systems (sUAS) have proven their effectiveness for measuring both the inertial and aircraft-relative wind. One of the more common aircraft-relative wind instruments is the multihole probe (MHP). While the MHP is accurate and simple to use, two main drawbacks exist: 1) the MHP airdata system can cost several times that of the sUAS and 2) the probe itself is often exposed to damage during routine operations. Flush airdata systems (FADS) are an alternative approach and utilize pressure ports flush with the aircraft surface. This removes any external components, thereby mitigating the risk of damage to the airdata system. The work presented details the implementation of a FADS for sUAS. Computational fluid dynamics simulations were used to determine the port locations of the FADS. Airframe locations were sorted based on the total sensitivity over a range of angles of attack and sideslip. The FADS was calibrated in flight using an onboard MHP. Multilayer feedforward neural networks were employed to produce estimates of the angle of attack and sideslip, while static and stagnation ports on the fuselage measured airspeed. Results from flight testing show errors in angle of attack and sideslip were unbiased. Additionally, 97.9% of the errors in airspeed were within 1 m s−1 of the MHP, while 93.8% and 87.3% of the angle of attack and sideslip errors, respectively, were within 1°. Flight tests show that a FADS can be calibrated in flight and that it is an effective method for measuring the aircraft-relative wind from small UAS.

Wind Tunnel Results for a Distributed Flush Airdata System

AbstractThe multihole probe (MHP) is an effective instrument for relative wind measurements from small unmanned aircraft systems (sUAS). Two common drawbacks for the integration of commercial MHP systems into low-cost sUAS are that 1) the MHP airdata system cost can be several times that of the sUAS airframe; and 2) when extended from the airframe, the pressure-measuring probe is often exposed to damage during normal operations. A flush airdata system (FADS) with static pressure sensing ports mounted flush with the airframe skin provides an alternative to the MHP system. This project implements a FADS with multiple static pressure sensors located at selected locations on the airframe. Computational fluid dynamics simulations are used to determine the airframe locations with the highest pressure change sensitivity to changes in the airframe angle of attack and sideslip angle. Wind tunnel test results are reported with nonlinear least squares and neural networks regression methods applied to the pressure measurements to estimate the instantaneous angle of attack and sideslip. Both methods achieved mean errors of less than . A direct comparison of the regression methods show that the neural network method provides a more accurate relative wind angle estimate than the nonlinear least squares method.

Kriging-algorithm-based Aerodynamic Model for Flush Airdata System

A novel numerical model which calculates the air data for flush airdata system was developed based on the Kriging interpolation. This method constructs the transformation matrix between the inputs i.e. the pressure measured by the sensor and the outputs i.e. angle of attack, angle of slide and Mach number; hence the required air data can be directly computed without iterations. As a result, the air data can be calculated in real-time. The accuracy of the model was compared with the neural network model with different numbers of inputs, and the positions of the sensor were also taken into account in the comparison. The Kriging model showed superior accuracy than the neural network model.

Optimization Design of the Flush Air Data System

A new configuration of multi sensor flush air data system was proposed and the detecting principles of the flush air data system was discussed. A large number of redundant information pick up from multi sensors embedded in aircraft data system put forward the requirements of information optimization. Characteristic value of air data defined in this chapter meet the active control system of aircraft redundancy requirements of total pressure, static pressure, angle of attack and sideslip angle of atmospheric data, was the foundation of the multi sensor information fusion system.

Learning Air-Data Parameters for Flush Air Data Sensing Systems

An adaptive scattered data approximation scheme was developed to calibrate the Flush Air Data System (FADS) of a surface vessel. An array of pressure sensors were mounted flush with the deckhouse periphery and the airdata parameters were extracted from the pressure measurements. The developed Galerkin derived selfadaptive greedy function approximation scheme gave reliable and robust surrogates for predicting wind speed and direction. The resulting surrogates were also used to evaluate the sensitivity to each of the flush mounted pressure sensor. Fault tolerance of the proposed surrogates were also studied with respect to pressure sensor failure.

Effects of Pressure Ports Layout on Angle of Attack and Sideslip Estimation in the Flush Air Data System

Flush air data system (FADS) have been successfully used on the nose tip of large manned/unmanned air vehicles instead of a traditional noseboom air data system. In order to integrate FADS with strapdown inertial navigation, high accuracy of angle of attack and sideslip is required. The estimated accuracy of angle of attack and sideslip in three types of FADS, which have different pressure ports layout, is compared using the nonlinear least squares theory. Evaluation function is provided to evaluate the accuracy of angle of attack and sideslip in different pressure ports layout. The results show that more sensors and radiation-type can provide high accuracy.

Failure management scheme for use in a flush air data system

This paper concerns the development of a failure management software for use in a Flush Air Data System (FADS). FADS is used for the online computation of air data parameters namely, Mach number, angle of attack and angle of side slip. Failure management, an essential requirement for FADS, especially in the context of aircraft flight control applications, has been addressed using a novel concept called failure indicator vector. This new methodology ensures the selection of correct values out of a number of redundant values of a computed air data parameter. This method leads to symbolic processing techniques, which is found to be very effective in terms of programming efficiency and simple procedure for logical reasoning. The method and the software have been successfully tested using the wind tunnel data generated at NAL.

A neural network approach to the calibration of a flush air data system

AbstractA flush air data system uses surface pressure measurements to obtain speed and aerodynamic orientation of a flight vehicle. This paper investigates the use of a neural network to calibrate the air data system on a low-observable aircraft forebody with 22 pressure tappings. Wind tunnel data were obtained for between 0 and 25° angle of attack, 0 to 10° sideslip for speeds of 32, 37 and 45ms-1. Experimental data were used to train multilayer perceptron neural networks. A calibration accuracy of 0·322ms-1, 0·811° and 0·552° for speed, alpha and beta respectively was achieved just using the first five tappings on the nose cone. Increasing the number of tappings used as inputs to the neural network reduces the calibration error. A neural network with 22 inputs gives a best accuracy of 0·095ms-1, 0·15° and 0·085° for speed, α and β respectively. Trained networks show poor robustness to single sensor failures. Robustness is improved by preprocessing input data with an autoassociative network or by introducing sensor redundancy.

Flush Air Data System Calibration Using Numerical Simulation

The use of computational fluid dynamics simulations for calibrating a flush air data system is described, In particular, the flush air data system of the HYFLEX hypersonic vehicle is used as a case study. The HYFLEX air data system consists of nine pressure ports located flush with the vehicle nose surface, connected to onboard pressure transducers, After appropriate processing, surface pressure measurements can he converted into useful air data parameters. The processing algorithm requires an accurate pressure model, which relates air data parameters to the measured pressures. In the past, such pressure models have been calibrated using combinations of flight data, ground-based experimental results, and numerical simulation. We perform a calibration of the HYFLEX flush air data system using computational fluid dynamics simulations exclusively, The simulations are used to build an empirical pressure model that accurately describes the HYFLEX nose pressure distribution ol cr a range of flight conditions. We believe that computational fluid dynamics provides a quick and inexpensive way to calibrate the air data system and is applicable to a broad range of flight conditions, When tested with HYFLEX flight data, the calibrated system is found to work well. It predicts vehicle angle of attack and angle of sideslip to accuracy levels that generally satisfy flight control requirements. Dynamic pressure is predicted to within the resolution of the onboard inertial measurement unit. We find that wind-tunnel experiments and flight data are not necessary to accurately calibrate the HYFLEX flush air data system for hypersonic flight.