Refine
Year of publication
- 2024 (7)
- 2023 (20)
- 2022 (12)
- 2021 (23)
- 2020 (30)
- 2019 (38)
- 2018 (19)
- 2017 (22)
- 2016 (22)
- 2015 (24)
- 2014 (13)
- 2013 (14)
- 2012 (10)
- 2011 (16)
- 2010 (18)
- 2009 (19)
- 2008 (12)
- 2007 (23)
- 2006 (21)
- 2005 (27)
- 2004 (16)
- 2003 (10)
- 2002 (8)
- 2001 (6)
- 2000 (5)
- 1999 (6)
- 1998 (5)
- 1997 (9)
- 1996 (5)
- 1995 (3)
- 1994 (4)
- 1993 (3)
- 1992 (2)
- 1991 (3)
- 1990 (1)
- 1989 (1)
- 1988 (6)
- 1987 (3)
- 1985 (7)
- 1984 (2)
- 1983 (2)
Institute
- Fachbereich Luft- und Raumfahrttechnik (497) (remove)
Language
- English (497) (remove)
Document Type
- Article (254)
- Conference Proceeding (183)
- Part of a Book (26)
- Book (15)
- Conference: Meeting Abstract (6)
- Doctoral Thesis (5)
- Conference Poster (2)
- Other (2)
- Patent (2)
- Preprint (1)
Keywords
- avalanche (6)
- solar sail (5)
- hydrogen (4)
- snow (4)
- Eisschicht (3)
- GOSSAMER-1 (3)
- Hydrogen (3)
- MASCOT (3)
- Obstacle avoidance (3)
- Sonde (3)
Dynamic loads significantly impact the structural design of propeller blades due to fatigue and static strength. Since propellers are elastic structures, deformations and aerodynamic loads are coupled. In the past, propeller manufacturers established procedures to determine unsteady aerodynamic loads and the structural response with analytical steady-state calculations. According to the approach, aeroelastic coupling primarily consists of torsional deformations. They neglect bending deformations, deformation velocities, and inertia terms. This paper validates the assumptions above for a General Aviation propeller and a lift propeller for urban air mobility or large cargo drones. Fully coupled reduced-order simulations determine the dynamic loads in the time domain. A quasi-steady blade element momentum approach transfers loads to one-dimensional finite beam elements. The simulation results are in relatively good agreement with the analytical method for the General Aviation propeller but show increasing errors for the slender lift propeller. The analytical approach is modified to consider the induced velocities. Still, inertia and velocity proportional terms play a significant role for the lift propeller due to increased elasticity. The assumption that only torsional deformations significantly impact the dynamic loads of propellers is not valid. Adequate determination of dynamic loads of such designs requires coupled aeroelastic simulations or advanced analytical procedures.
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.
The aerodynamic performance of propellers strongly depends on their geometry and, consequently, on aeroelastic deformations. Knowledge of the extent of the impact is crucial for overall aircraft performance. An integrated simulation environment for steady aeroelastic propeller simulations is presented. The simulation environment is applied to determine the impact of elastic deformations on the aerodynamic propeller performance. The aerodynamic module includes a blade element momentum approach to calculate aerodynamic loads. The structural module is based on finite beam elements, according to Timoshenko theory, including moderate deflections. Several fixed-pitch propellers with thin-walled cross sections made of both isotropic and non-isotropic materials are investigated. The essential parameters are varied: diameter, disc loading, sweep, material, rotational, and flight velocity. The relative change of thrust between rigid and elastic blades quantifies the impact of propeller elasticity. Swept propellers of large diameters or low disc loadings can decrease the thrust significantly. High flight velocities and low material stiffness amplify this tendency. Performance calculations without consideration of propeller elasticity can lead to decreased efficiency. To avoid cost- and time-intense redesigns, propeller elasticity should be considered for swept planforms and low disc loadings.
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.
We propose a simple parametric OSSD model that describes the variation of the sail film's optical coefficients with time, depending on the sail film's environmental history, i.e., the radiation dose. The primary intention of our model is not to describe the exact behavior of specific film-coating combinations in the real space environment, but to provide a more general parametric framework for describing the general optical degradation behavior of solar sails.
With the increased interest for interstellar exploration after the discovery of exoplanets and the proposal by Breakthrough Starshot, this paper investigates the optimisation of photon-sail trajectories in Alpha Centauri. The prime objective is to find the optimal steering strategy for a photonic sail to get captured around one of the stars after a minimum-time transfer from Earth. By extending the idea of the Breakthrough Starshot project with a deceleration phase upon arrival, the mission’s scientific yield will be increased. As a secondary objective, transfer trajectories between the stars and orbit-raising manoeuvres to explore the habitable zones of the stars are investigated. All trajectories are optimised for minimum time of flight using the trajectory optimisation software InTrance. Depending on the sail technology, interstellar travel times of 77.6-18,790 years can be achieved, which presents an average improvement of 30% with respect to previous work. Still, significant technological development is required to reach and be captured in the Alpha-Centauri system in less than a century. Therefore, a fly-through mission arguably remains the only option for a first exploratory mission to Alpha Centauri, but the enticing results obtained in this work provide perspective for future long-residence missions to our closest neighbouring star system.
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).