Article
Refine
Year of publication
Institute
- Fachbereich Luft- und Raumfahrttechnik (368) (remove)
Has Fulltext
- no (368) (remove)
Document Type
- Article (368) (remove)
Keywords
- avalanche (5)
- snow (3)
- Drinfeld modules (2)
- Transcendence (2)
- t-modules (2)
- 1P hub loads (1)
- Active humidity control (1)
- Aeroelasticity (1)
- Antarctic Glaciology (1)
- Avalanche (1)
Multiple Near-Earth Asteroid Rendezvous and Sample Return Using First Generation Solar Sailcraft
(2005)
Möglichkeiten der ottomotorischen Prozeßführung bei Verwendung des elektromechanischen Ventiltriebs
(1998)
The Saturnian moon Enceladus with its extensive water bodies underneath a thick ice sheet cover is a potential candidate for extraterrestrial life. Direct exploration of such extraterrestrial aquatic ecosystems requires advanced access and sampling technologies with a high level of autonomy. A new technological approach has been developed as part of the collaborative research project Enceladus Explorer (EnEx). The concept is based upon a minimally invasive melting probe called the IceMole. The force-regulated, heater-controlled IceMole is able to travel along a curved trajectory as well as upwards. Hence, it allows maneuvers which may be necessary for obstacle avoidance or target selection. Maneuverability, however, necessitates a sophisticated on-board navigation system capable of autonomous operations. The development of such a navigational system has been the focal part of the EnEx project. The original IceMole has been further developed to include relative positioning based on in-ice attitude determination, acoustic positioning, ultrasonic obstacle and target detection integrated through a high-level sensor fusion. This paper describes the EnEx technology and discusses implications for an actual extraterrestrial mission concept.
Wie sieht das unbemannte Flugzeug von Übermorgen aus? Dieser Frage stellen sich Forscher an der Fachhochschule Aachen. Die weltweit rasant fortschreitende Entwicklung des Marktes für unbemannte Fluggeräte (UAVs - „Unmanned Aerial Vehicles“) bietet großes Potenzial für Wachstum und Wertschöpfung. Unbemannte fliegende Systeme können – für bestimmte Anwendungsgebiete – wesentlich günstiger, kleiner und effizienter ausgelegt werden als bemannte Lösungen. Dabei sind sich viele Unternehmen über das mögliche Potential dieser Technologie noch gar nicht bewusst.
Nonlocal Cosmology
(1996)
On the flight performance impact of landing gear drag reduction methods for unmanned air vehicles
(2018)
The flight performance impact of three different landing gear configurations on a small, fixed-wing UAV is analyzed with a combination of RANS CFD calculations and an incremental flight performance algorithm. A standard fixed landing gear configuration is taken as a baseline, while the influence of retracting the landing gear or applying streamlined fairings is investigated. A retraction leads to a significant parasite drag reduction, while also fairings promise large savings. The increase in lift-to-drag ratio is reduced at high lift coefficients due to the influence of induced drag. All configurations are tested on three different design missions with an incremental flight performance algorithm. A trade-off study is performed using the retracted or faired landing gear's weight increase as a variable. The analysis reveals only small mission performance gains as the aerodynamic improvements are negated by weight penalties. A new workflow for decision-making is presented that allows to estimate if a change in landing gear configuration is beneficial for a small UAV.
High aerodynamic efficiency requires propellers with high aspect ratios, while propeller sweep potentially reduces noise. Propeller sweep and high aspect ratios increase elasticity and coupling of structural mechanics and aerodynamics, affecting the propeller performance and noise. Therefore, this paper analyzes the influence of elasticity on forward-swept, backward-swept, and unswept propellers in hover conditions. A reduced-order blade element momentum approach is coupled with a one-dimensional Timoshenko beam theory and Farassat's formulation 1A. The results of the aeroelastic simulation are used as input for the aeroacoustic calculation. The analysis shows that elasticity influences noise radiation because thickness and loading noise respond differently to deformations. In the case of the backward-swept propeller, the location of the maximum sound pressure level shifts forward by 0.5 °, while in the case of the forward-swept propeller, it shifts backward by 0.5 °. Therefore, aeroacoustic optimization requires the consideration of propeller deformation.
Operational Modal Analysis (OMA) is a promising candidate for flutter testing and Structural Health Monitoring (SHM) of aircraft wings that are passively excited by wind loads. However, no studies have been published where OMA is tested in transonic flows, which is the dominant condition for large civil aircraft and is characterized by complex and unique aerodynamic phenomena. We use data from the HIRENASD large-scale wind tunnel experiment to automatically extract modal parameters from an ambiently excited wing operated in the transonic regime using two OMA methods: Stochastic Subspace Identification (SSI) and Frequency Domain Decomposition (FDD). The system response is evaluated based on accelerometer measurements. The excitation is investigated from surface pressure measurements. The forcing function is shown to be non-white, non-stationary and contaminated by narrow-banded transonic disturbances. All these properties violate fundamental OMA assumptions about the forcing function. Despite this, all physical modes in the investigated frequency range were successfully identified, and in addition transonic pressure waves were identified as physical modes as well. The SSI method showed superior identification capabilities for the investigated case. The investigation shows that complex transonic flows can interfere with OMA. This can make existing approaches for modal tracking unsuitable for their application to aircraft wings operated in the transonic flight regime. Approaches to separate the true physical modes from the transonic disturbances are discussed.
Optimization of Interplanetary Rendezvous Trajectories for Solar Sailcraft Using a Neurocontroller
(2002)
Searching optimal interplanetary trajectories for low-thrust spacecraft is usually a difficult and time-consuming task that involves much experience and expert knowledge in astrodynamics and optimal control theory. This is because the convergence behavior of traditional local optimizers, which are based on numerical optimal control methods, depends on an adequate initial guess, which is often hard to find, especially for very-low-thrust trajectories that necessitate many revolutions around the sun. The obtained solutions are typically close to the initial guess that is rarely close to the (unknown) global optimum. Within this paper, trajectory optimization problems are attacked from the perspective of artificial intelligence and machine learning. Inspired by natural archetypes, a smart global method for low-thrust trajectory optimization is proposed that fuses artificial neural networks and evolutionary algorithms into so-called evolutionary neurocontrollers. This novel method runs without an initial guess and does not require the attendance of an expert in astrodynamics and optimal control theory. This paper details how evolutionary neurocontrol works and how it could be implemented. The performance of the method is assessed for three different interplanetary missions with a thrust to mass ratio <0.15mN/kg (solar sail and nuclear electric).