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- Fachbereich Luft- und Raumfahrttechnik (247) (remove)
The Dry Low NOx (DLN) Micromix combustion principle with increased energy density is adapted for the industrial gas turbine APU GTCP 36-300 using hydrogen and hydrogen-rich syngas with a composition of 90%-Vol. hydrogen (H₂) and 10%-Vol. carbon-monoxide (CO). Experimental and numerical studies of several combustor geometries for hydrogen and syngas show the successful advance of the DLN Micromix combustion from pure hydrogen to hydrogen-rich syngas. The impact of the different fuel properties on the combustion principle and aerodynamic flame stabilization design laws, flow field, flame structure and emission characteristics is investigated by numerical analysis using a hybrid Eddy Break Up combustion model and validated against experimental results.
Picosecond dynamics in haemoglobin from different species: A quasielastic neutron scattering study
(2014)
There is significant interest in sampling subglacial environments for geobiological studies, but they are difficult to access. Existing ice-drilling technologies make it cumbersome to maintain microbiologically clean access for sample acquisition and environmental stewardship of potentially fragile subglacial aquatic ecosystems. The IceMole is a maneuverable subsurface ice probe for clean in situ analysis and sampling of glacial ice and subglacial materials. The design is based on the novel concept of combining melting and mechanical propulsion. It can change melting direction by differential heating of the melting head and optional side-wall heaters. The first two prototypes were successfully tested between 2010 and 2012 on glaciers in Switzerland and Iceland. They demonstrated downward, horizontal and upward melting, as well as curve driving and dirt layer penetration. A more advanced probe is currently under development as part of the Enceladus Explorer (EnEx) project. It offers systems for obstacle avoidance, target detection, and navigation in ice. For the EnEx-IceMole, we will pay particular attention to clean protocols for the sampling of subglacial materials for biogeochemical analysis. We plan to use this probe for clean access into a unique subglacial aquatic environment at Blood Falls, Antarctica, with return of a subglacial brine sample.
In this paper we consider low Péclet number flow in bead packs. A series of relaxation exchange experiments has been conducted and evaluated by ILT analysis. In the resulting correlation maps, we observed a collapse of the signal and a translation towards smaller relaxation times with increasing flow rates, as well as a signal tilt with respect to the diagonal. In the discussion of the phenomena we present a mathematical theory for relaxation exchange experiments that considers both diffusive and advective transport. We perform simulations based on this theory and discuss them with respect to the conducted experiments.
This paper describes the implementation of topographic curvature effects within the RApid Mass MovementS (RAMMS) snow avalanche simulation toolbox. RAMMS is based on a model similar to shallow water equations with a Coulomb friction relation and the velocity dependent Voellmy drag. It is used for snow avalanche risk assessment in Switzerland. The snow avalanche simulation relies on back calculation of observed avalanches. The calibration of the friction parameters depends on characteristics of the avalanche track. The topographic curvature terms are not yet included in the above mentioned classical model. Here, we fundamentally improve this model by mathematically and physically including the topographic curvature effects. By decomposing the velocity dependent friction into a topography dependent term that accounts for a curvature enhancement in the Coulomb friction, and a topography independent contribution similar to the classical Voellmy drag, we construct a general curvature dependent frictional resistance, and thus propose new extended model equations. With three site-specific examples, we compare the apparent frictional resistance of the new approach, which includes topographic curvature effects, to the classical one. Our simulation results demonstrate substantial effects of the curvature on the flow dynamics e.g., the dynamic pressure distribution along the slope. The comparison of resistance coefficients between the two models demonstrates that the physically based extension presents an improvement to the classical approach. Furthermore a practical example highlights its influence on the pressure outline in the run out zone of the avalanche. Snow avalanche dynamics modeling natural terrain curvature centrifugal force friction coefficients.
There is common agreement within the scientific community that in order to understand our local galactic environment it will be necessary to send a spacecraft into the region beyond the solar wind termination shock. Considering distances of 200 AU for a new mission, one needs a spacecraft traveling at a speed of close to 10 AU/yr in order to keep the mission duration in the range of less than 25 yrs, a transfer time postulated by European Space Agency (ESA). Two propulsion options for the mission have been proposed and discussed so far: the solar sail propulsion and the ballistic/radioisotope-electric propulsion (REP). As a further alternative, we here investigate a combination of solar-electric propulsion (SEP) and REP. The SEP stage consists of six 22-cms diameter RIT-22 ion thrusters working with a high specific impulse of 7377 s corresponding to a positive grid voltage of 5 kV. Solar power of 53 kW at begin of mission (BOM) is provided by a lightweight solar array.
Digital elevation models (DEMs), represent the three-dimensional terrain and are the basic input for numerical snow avalanche dynamics simulations. DEMs can be acquired using topographic maps or remote-sensing technologies, such as photogrammetry or lidar. Depending on the acquisition technique, different spatial resolutions and qualities are achieved. However, there is a lack of studies that investigate the sensitivity of snow avalanche simulation algorithms to the quality and resolution of DEMs. Here, we perform calculations using the numerical avalance dynamics model RAMMS, varying the quality and spatial resolution of the underlying DEMs, while holding the simulation parameters constant. We study both channelized and open-terrain avalanche tracks with variable roughness. To quantify the variance of these simulations, we use well-documented large-scale avalanche events from Davos, Switzerland (winter 2007/08), and from our large-scale avalanche test site, Valĺee de la Sionne (winter 2005/06). We find that the DEM resolution and quality is critical for modeled flow paths, run-out distances, deposits, velocities and impact pressures. Although a spatial resolution of ~25 m is sufficient for large-scale avalanche modeling, the DEM datasets must be checked carefully for anomalies and artifacts before using them for dynamics calculations.
Low emission zones and truck bans, the rising price of diesel and increases in road tolls: all of these factors are putting serious pressure on the transport industry. Commercial vehicle manufacturers and their suppliers are in the process of identifying new solutions to these challenges as part of their efforts to meet the EEV (enhanced environmentally friendly vehicle) limits, which are currently the most robust European exhaust and emissions standards for trucks and buses.
Numerical avalanche dynamics models have become an essential part of snow engineering. Coupled with field observations and historical records, they are especially helpful in understanding avalanche flow in complex terrain. However, their application poses several new challenges to avalanche engineers. A detailed understanding of the avalanche phenomena is required to construct hazard scenarios which involve the careful specification of initial conditions (release zone location and dimensions) and definition of appropriate friction parameters. The interpretation of simulation results requires an understanding of the numerical solution schemes and easy to use visualization tools. We discuss these problems by presenting the computer model RAMMS, which was specially designed by the SLF as a practical tool for avalanche engineers. RAMMS solves the depth-averaged equations governing avalanche flow with accurate second-order numerical solution schemes. The model allows the specification of multiple release zones in three-dimensional terrain. Snow cover entrainment is considered. Furthermore, two different flow rheologies can be applied: the standard Voellmy–Salm (VS) approach or a random kinetic energy (RKE) model, which accounts for the random motion and inelastic interaction between snow granules. We present the governing differential equations, highlight some of the input and output features of RAMMS and then apply the models with entrainment to simulate two well-documented avalanche events recorded at the Vallée de la Sionne test site.
Two- and three-dimensional avalanche dynamics models are being increasingly used in hazard-mitigation studies. These models can provide improved and more accurate results for hazard mapping than the simple one-dimensional models presently used in practice. However, two- and three-dimensional models generate an extensive amount of output data, making the interpretation of simulation results more difficult. To perform a simulation in three-dimensional terrain, numerical models require a digital elevation model, specification of avalanche release areas (spatial extent and volume), selection of solution methods, finding an adequate calculation resolution and, finally, the choice of friction parameters. In this paper, the importance and difficulty of correctly setting up and analysing the results of a numerical avalanche dynamics simulation is discussed. We apply the two-dimensional simulation program RAMMS to the 1968 extreme avalanche event In den Arelen. We show the effect of model input variations on simulation results and the dangers and complexities in their interpretation.
The powerful avalanche simulation toolbox RAMMS (Rapid Mass Movements) is based on a depth-averaged
hydrodynamic system of equations with a Voellmy-Salm friction relation. The two empirical friction parameters
μ and correspond to a dry Coulomb friction and a viscous resistance, respectively. Although μ and lack a
proper physical explanation, 60 years of acquired avalanche data in the Swiss Alps made a systematic calibration
possible. RAMMS can therefore successfully model avalanche flow depth, velocities, impact pressure and run
out distances. Pudasaini and Hutter (2003) have proposed extended, rigorously derived model equations that
account for local curvature and twist. A coordinate transformation into a reference system, applied to the actual
mountain topography of the natural avalanche path, is performed. The local curvature and the twist of the
avalanche path induce an additional term in the overburden pressure. This leads to a modification of the Coulomb
friction, the free-surface pressure gradient, the pressure induced by the channel, and the gravity components
along and normal to the curved and twisted reference surface. This eventually guides the flow dynamics and
deposits of avalanches. In the present study, we investigate the influence of curvature on avalanche flow in
real mountain terrain. Simulations of real avalanche paths are performed and compared for the different models
approaches. An algorithm to calculate curvature in real terrain is introduced in RAMMS. This leads to a curvature
dependent friction relation in an extended version of the Voellmy-Salm model equations. Our analysis provides
yet another step in interpreting the physical meaning and significance of the friction parameters used in the
RAMMS computational environment.
Solar Sail Kinetic Energy Impactor Trajectory Optimization for an Asteroid-Deflection Mission
(2007)
Testing of a 10 kW diffusive micro-mix combustor for hydrogen-fuelled micro-scale gas turbines
(2007)
Using results from an 8 m2 instrumented force plate we describe field measurements of normal and shear stresses, and fluid pore pressure for a debris flow. The flow depth increased from 0.1 to 1 m within the first 12 s of flow front arrival, remained relatively constant until 100 s, and then gradually decreased to 0.5 m by 600 s. Normal and shear stresses and pore fluid pressure varied in-phase with the flow depth. Calculated bulk densities are ρb = 2000–2250 kg m−3 for the bulk flow and ρf = 1600–1750 kg m−3 for the fluid phase. The ratio of effective normal stress to shear stress yields a Coulomb basal friction angle of ϕ = 26° at the flow front. We did not find a strong correlation between the degree of agitation in the flow, estimated using the signal from a geophone on the force plate, and an assumed dynamic pore fluid pressure. Our data support the idea that excess pore-fluid pressures are long lived in debris flows and therefore contribute to their unusual mobility.
Multiple Near-Earth Asteroid Rendezvous and Sample Return Using First Generation Solar Sailcraft
(2005)
Solar Sail Trajectory Optimization for Intercepting, Impacting, and Deflecting Near-Earth Asteroids
(2005)
Solar Sails for Near- and Medium-Term Scientific Deep Space Missions / W. Sebolt ; B. Dachwald
(2005)
Das Drallrohr
(2005)
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).
The entangled Universe
(2004)
This paper examines the positive and negative aspects of a range of interpretations of nearest-neighbours models. Measures-oriented and distributionoriented verification methods are applied to categorial, probabilistic and descriptive interpretations of nearest neighbours used operationally in avalanche forecasting in Scotland and Switzerland. The dependence of skill and accuracy measures on base rate is illustrated. The purpose of the forecast and the definition of events are important variables in determining the quality of the forecast. A discussion of the application of different interpretations in operational avalanche forecasting is presented.