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This paper analyzes the drag characteristics of several landing gear and turret configurations that are representative of unmanned aircraft tricycle landing gears and sensor turrets. A variety of these components were constructed via 3D-printing and analyzed in a wind-tunnel measurement campaign. Both turrets and landing gears were attached to a modular fuselage that supported both isolated components and multiple components at a time. Selected cases were numerically investigated with a Reynolds-averaged Navier-Stokes approach that showed good accuracy when compared to wind-tunnel data. The drag of main gear struts could be significantly reduced via streamlining their cross-sectional shape and keeping load carrying capabilities similar. The attachment of wheels introduced interference effects that increased strut drag moderately but significantly increased wheel drag compared to isolated cases. Very similar behavior was identified for front landing gears. The drag of an electro-optical and infrared sensor turret was found to be much higher than compared to available data of a clean hemisphere-cylinder combination. This turret drag was merely influenced by geometrical features like sensor surfaces and the rotational mechanism. The new data of this study is used to develop simple drag estimation recommendations for main and front landing gear struts and wheels as well as sensor turrets. These recommendations take geometrical considerations and interference effects into account.
Wind is closely associated with the discussion of fairness in ski jumping. To counter-act its influence on the jump length, the International Ski Federation (FIS) has introduced a wind compensation approach. We applied three differently accurate computer models of the flight phase with wind (M1, M2, and M3) to study the jump length effects of various wind scenarios. The previously used model M1 is accurate for wind blowing in direction of the flight path, but inaccuracies are to be expected for wind directions deviating from the tangent to the flight path. M2 considers the change of airflow direction, but it does not consider the associated change in the angle of attack of the skis which additionally modifies drag and lift area time functions. M3 predicts the length effect for all wind directions within the plane of the flight trajectory without any mathematical simplification. Prediction errors of M3 are determined only by the quality of the input data: wind velocity, drag and lift area functions, take-off velocity, and weight. For comparing the three models, drag and lift area functions of an optimized reference jump were used. Results obtained with M2, which is much easier to handle than M3, did not deviate noticeably when compared to predictions of the reference model M3. Therefore, we suggest to use M2 in future applications. A comparison of M2 predictions with the FIS wind compensation system showed substantial discrepancies, for instance: in the first flight phase, tailwind can increase jump length, and headwind can decrease it; this is opposite of what had been anticipated before and is not considered in the current wind compensation system in ski jumping.
In this paper, the multicarrier physical layers of WiMAX are evaluated in the context of airport data links. The orthogonal frequency-division multiplexing (OFDM) and orthogonal frequency-division multiple-access (OFDMA) cases are applied to the forward link (FL) and reverse link (RL), respectively. The performance of the so called parking and taxi scenarios is presented for airport communications in C-band. Numerical results show that the proposed scheme brings good performance for both the FL and the RL. For the OFDMA case a structure changing called double-tile is also proposed to improve the system performance.
Wilhelm Schürmann
(1976)
Geboren 1946, lebt und arbeitet in Aachen. Studium der Chemie an der Technischen Hochschule Aachen. Danach als freiberuflicher Photograph tätig für verschiedene Tageszeitungen. Seit 1972 Lehrer für Photographie am Reiff Museum der TH-Aachen, Institut für Architektur. Seit 1973 Dozent für Photographie an der Volkshochschule Aachen. Ende 1973 Gründung der Galerie Lichttropfen in Aachen. Organisator zahlreicher Ausstellungen historischer und zeitgenössischer Photographie im In- und Ausland.
Wiegand-Modul
(2022)
Ein Wiegand-Modul (110;210;310) umfassend- eine Sensorspule (112;212;312),- einen ersten Wiegand-Draht (116a;216a;316a), der zumindest teilweise innerhalb der Sensorspule (112;212;312) angeordnet ist, und- einen zweiten Wiegand-Draht (116b;216b;316b), der zumindest teilweise innerhalb der Sensorspule (112;212;312) angeordnet ist und sich im Wesentlichen parallel zu dem ersten Wiegand-Draht (116a;216a;316a) erstreckt, ist bekannt.Um eine effiziente Ausnutzung der durch die Ummagnetisierung der Wiegand-Drähte (116a,116b;216a,216b;316a,316b) in die Sensorspule (112;212;312) induzierten elektrischen Energie zu ermöglichen, sind der erste Wiegand-Draht (116a;216a;316a) und der zweite Wiegand-Draht (116b;216b;316b) bezogen auf eine axiale Richtung der Sensorspule (112;212;312) versetzt zueinander angeordnet.
With the growing interest in small distributed sensors for the “Internet of Things”, more attention is being paid to energy harvesting techologies. Reducing or eliminating the need for external power sources or batteries make devices more self-sufficient, more reliable, and reduces maintenance requirements. The Wiegand effect is a proven technology for harvesting small amounts of electrical power from mechanical motion.
In this article we describe an Internet-of-Things sensing device with a wireless interface which is powered by the oftenoverlooked harvesting method of the Wiegand effect. The sensor can determine position, temperature or other resistively measurable quantities and can transmit the data via an ultra-low power ultra-wideband (UWB) data transmitter. With this approach we can energy-self-sufficiently acquire, process, and wirelessly transmit data in a pulsed operation. A proof-of-concept system was built up to prove the feasibility of the approach. The energy consumption of the system is analyzed and traced back in detail to the individual components, compared to the generated energy and processed to identify further optimization options. Based on the proof-of-concept, an application demonstrator was developed. Finally, we point out possible use cases.