Numerical and Experimental Measures of the Unmanned Aerial System UAS-S4 of Hydra Technologies
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Bibliographic record
Abstract
This article presents a structural analysis of the Unmanned Aerial System UAS-S4 ETHECATL. Mass, center of gravity position and mass moment of inertia are numerically determined and experimentally attested using the pendulum method. To determine the mass moment of inertia, a bifilar torsion-type pendulum is used for the Z-axis and a type of this pendulum for the X and Y axes [14]. A nonlinear dynamic model for the UAS-S4 is developed for the rotational motion about the center of gravity (Gs) of the tested system, including the effects of large-angle oscillations, aerodynamic drag, viscous damping and additional mass effects. MATLAB genetic algorithms are then used to obtain the values of mass moment of inertia that would validate the experimental data with the numerical results. The experiment used data gathered by three sensors: an accelerometer, a gyroscope and a magnetometer. Therefore, a method is used to calibrate these three sensors. In this paper, the experimental results for an object of uniform density for which the moment of inertia is computed directly from geometrical data are presented. The experimental results obtained for the UAS-S4 ETHECATL are also presented. The experimental method gives, with respect to the numerical results, an error of 4.4% for the moment of inertia around the Z-axis and of 9.5% for the moment of inertia around the X and Y axes; therefore the experimental results validate the numerical method results with a relative error of 6.52% on average. Introduction Measurements of inertial properties are needed during the design of aircraft. In fact, the knowledge of these measurements is one of the most crucial problems to be solved when studying aircraft rotational motion or designing aircraft flight control systems This paper presents a structural analysis of the Unmanned Aerial System UAS-S4 ETHECATL. Mass, center of gravity position and mass moment of inertia are numerically determined through Raymer [1], Williams and Vukelich ( [2], [3], [4]) statistical-empirical methods, coupled with mechanical calculations. Williams and Vukelich ( [2], [3], [4]) contributed therefore to the conception of the DATCOM software for the determination of the main geometrical properties of aircraft but also for the stability analysis of aircraft based on geometrical data. Anton et al. ( [5], [6], [7], [8]) improved the DATCOM software with new aerodynamic formulations, and therefore designed the FDerivative new code for stability analysis determination from geometrical data. Experimental tests are performed using the pendulum method to validate the numerical predictions Generally in such studies, the common technique is to ignore the damping and to linearize the equations of motion to model the bifilar or simple pendulum as a harmonic un-damped oscillator [12]. This work extends previous studies by incorporating a higher fidelity of dynamic models of bifilar and simple pendulums. The aim of the UAS (Unmanned Aerial System) project, in which this work takes place, is to apply the morphing wing concept on a fixed-wing UAS by replacing the original wings with morphing wings in order to reduce the drag and the fuel consumption. Before testing and validating the morphing UAS-S4 design model in our subsonic wind tunnel, the conceptual design of the wings requires precise knowledge of its inertial properties. Different aerodynamics methodologies were performed for the morphing wing design of the UAS-S4 from Hydra Technologies by Gabor Sugar et al. ( [9], [10], [11]). Because the UAS S4-18 ETHECALT has been obtained without any inertial data, it has been essential to perform bench tests in the absence of aerodynamics, therefore prior to wind tunnel tests, to obtain its aerodynamics characteristics. Thus, a first numerical structural analysis of the UAS-S4 has been made by the internship student Fabien Dubois [13] and that was followed by bench tests to validate the first set of numerical predictions with experimental bench tests results. The main objective of this work was to perform a second set of experimental tests using a second more accurate method. Thus, the paper gives a complete discussion of the determination of both the center of gravity position and the proper mass moment of inertia of the UAS-S4 and other general classes of such UAS by combining, comparing and validating numerical with experimental bench test methods results. I. Determination of the center of gravity The figure below sets out the classical orientations of the UAS-S4 body axes. Figure 1. UAS body axes Assuming that the UAS is rigorously symmetric, the Y-coordinate of the center of gravity, Ycg, is theoretically equal to zero. I.1 Z-coordinate of the center of gravity Zcg Figure 2 shows the swinging gear proposed to tilt the UAS Figure 2. Swinging gear This bench test was carried out according to the following procedure: 1 st step: Hang the table horizontally on a beam as shown in Figure 2. 2 nd step: Place the UAS on the table, keeping the system (UAS and table) horizontal; this means the UAS’ and the table’s centers of gravity are vertically aligned. 3 rd step: Hang an extra weight m (as shown in Figure 3) to unbalance the system (UAS + table) by titling the assemblage around the X or Y axis. Figure 3. UAS-S4 and table tilting about the X or Y axis From Figure 3, the moment equilibrium around an axis (Δ) leads to: (1) ( ) [ ( ) ( )] (2)
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it