Refine
Year of publication
- 2024 (49)
- 2023 (114)
- 2022 (143)
- 2021 (154)
- 2020 (171)
- 2019 (194)
- 2018 (171)
- 2017 (154)
- 2016 (158)
- 2015 (176)
- 2014 (167)
- 2013 (173)
- 2012 (163)
- 2011 (189)
- 2010 (185)
- 2009 (189)
- 2008 (156)
- 2007 (149)
- 2006 (160)
- 2005 (130)
- 2004 (161)
- 2003 (106)
- 2002 (130)
- 2001 (106)
- 2000 (108)
- 1999 (109)
- 1998 (99)
- 1997 (99)
- 1996 (81)
- 1995 (78)
- 1994 (86)
- 1993 (59)
- 1992 (54)
- 1991 (29)
- 1990 (39)
- 1989 (45)
- 1988 (57)
- 1987 (32)
- 1986 (19)
- 1985 (34)
- 1984 (22)
- 1983 (20)
- 1982 (29)
- 1981 (20)
- 1980 (36)
- 1979 (24)
- 1978 (34)
- 1977 (14)
- 1976 (13)
- 1975 (12)
- 1974 (3)
- 1973 (2)
- 1972 (2)
- 1971 (1)
- 1968 (1)
Institute
- Fachbereich Medizintechnik und Technomathematik (1689)
- Fachbereich Elektrotechnik und Informationstechnik (718)
- IfB - Institut für Bioengineering (624)
- Fachbereich Energietechnik (588)
- INB - Institut für Nano- und Biotechnologien (557)
- Fachbereich Chemie und Biotechnologie (551)
- Fachbereich Luft- und Raumfahrttechnik (497)
- Fachbereich Maschinenbau und Mechatronik (279)
- Fachbereich Wirtschaftswissenschaften (217)
- Solar-Institut Jülich (165)
Language
- English (4909) (remove)
Document Type
- Article (3277)
- Conference Proceeding (1162)
- Part of a Book (191)
- Book (144)
- Doctoral Thesis (30)
- Conference: Meeting Abstract (28)
- Patent (25)
- Other (10)
- Report (9)
- Conference Poster (6)
Keywords
- Biosensor (25)
- Finite-Elemente-Methode (12)
- Einspielen <Werkstoff> (10)
- CAD (8)
- civil engineering (8)
- Bauingenieurwesen (7)
- Blitzschutz (6)
- FEM (6)
- Gamification (6)
- Limit analysis (6)
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.
Sleep spindles are neurophysiological phenomena that appear to be linked to memory formation and other functions of the central nervous system, and that can be observed in electroencephalographic recordings (EEG) during sleep. Manually identified spindle annotations in EEG recordings suffer from substantial intra- and inter-rater variability, even if raters have been highly trained, which reduces the reliability of spindle measures as a research and diagnostic tool. The Massive Online Data Annotation (MODA) project has recently addressed this problem by forming a consensus from multiple such rating experts, thus providing a corpus of spindle annotations of enhanced quality. Based on this dataset, we present a U-Net-type deep neural network model to automatically detect sleep spindles. Our model’s performance exceeds that of the state-of-the-art detector and of most experts in the MODA dataset. We observed improved detection accuracy in subjects of all ages, including older individuals whose spindles are particularly challenging to detect reliably. Our results underline the potential of automated methods to do repetitive cumbersome tasks with super-human performance.
The existence of several mobile operating systems, such as Android and iOS, is a challenge for developers because the individual platforms are not compatible with each other and require separate app developments. For this reason, cross-platform approaches have become popular but lack in cloning the native behavior of the different operating systems. Out of the plenty cross-platform approaches, the progressive web app (PWA) approach is perceived as promising but needs further investigation. Therefore, the paper at hand aims at investigating whether PWAs are a suitable alternative for native apps by developing a PWA clone of an existing app. Two surveys are conducted in which potential users test and evaluate the PWA prototype with regard to its usability. The survey results indicate that PWAs have great potential, but cannot be treated as a general alternative to native apps. For guiding developers when and how to use PWAs, four design guidelines for the development of PWA-based apps are derived based on the results.
The concept of a laser-enhanced solar sail is introduced and the radiation pressure force model for an ideal laser-enhanced solar sail is derived. A laser-enhanced solar sail is a “traditional” solar sail that is, however, not solely propelled by solar radiation, but additionally by a laser beam that illuminates the sail. The additional laser radiation pressure increases the sail's propulsive force and can give, depending on the location of the laser source, more control authority over the direction of the solar sail’s propulsive force vector. This way, laser-enhanced solar sails may augment already existing solar sail mission concepts and make novel mission concepts feasible.
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.
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).
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.
By DLR-contact, sample return missions to the large main-belt asteroid “19, Fortuna” have been studied. The mission scenario has been based on three ion thrusters of the RIT-22 model, which is presently under space qualification, and on solar arrays equipped with triple-junction GaAs solar cells. After having designed the spacecraft, the orbit-to-orbit trajectories for both, a one-way SEP mission with a chemical sample return and an all-SEP return mission, have been optimized using a combination of artificial neural networks with evolutionary algorithms. Additionally, body-to-body trajectories have been
investigated within a launch period between 2012 and 2015. For orbit-to-orbit calculation, the launch masses of the hybrid mission and of the all-SEP mission resulted in 2.05 tons and 1.56 tons, respectively, including a scientific payload of 246 kg. For the related transfer
durations 4.14 yrs and 4.62 yrs were obtained. Finally, a comparison between the mission scenarios based on SEP and on NEP have been carried out favouring clearly SEP.
The recently proposed NASA and ESA missions to Saturn and Jupiter pose difficult tasks to mission designers because chemical propulsion scenarios are not capable of transferring heavy spacecraft into the outer solar system without the use of gravity assists. Thus our developed mission scenario based on the joint NASA/ESA Titan Saturn System Mission baselines solar electric propulsion to improve mission flexibility and transfer time. For the calculation of near-globally optimal low-thrust trajectories, we have used a method called Evolutionary Neurocontrol, which is implemented in the low-thrust trajectory optimization software InTrance. The studied solar electric propulsion scenario covers trajectory optimization of the interplanetary transfer including variations of the spacecraft's thrust level, the thrust unit's specific impulse and the solar power generator power level. Additionally developed software extensions enabled trajectory optimization with launcher-provided hyperbolic excess energy, a complex solar power generator model and a variable specific impulse ion engine model. For the investigated mission scenario, Evolutionary Neurocontrol yields good optimization results, which also hold valid for the more elaborate spacecraft models. Compared to Cassini/Huygens, the best found solutions have faster transfer times and a higher mission flexibility in general.