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Poster presented at the ASSW in Tromsø (March 2022)

Involving air traffic controllers and pilots into the bird strike prevention process is considered an essential step to increase aviation and avian safety. Prior to implementing operational measures such as real-time warning systems, it is vital to evaluate their feasibility. This paper studies the efficacy of a bird strike advisory system for air traffic control. In addition to the potential safety benefit, the possible impact on airport operations is analyzed. To this end, a previously developed collision avoidance algorithm underlying the system was tested in fast-time Monte Carlo simulations involving various air traffic and bird densities to obtain representative conclusions for different operational conditions. The results demonstrate the strong safety potential of operational bird strike prevention in case of precise bird movement prediction. Unless airports operate close to their capacity limits while bird abundance is high, the induced delays remain tolerable. Prioritization of hazardous strikes involving large individuals as well as flocks of birds are expected to support operational feasibility in all conditions.

This poster was presented at the ESA Living Planet Symposium 2019 (LPS19) in Milano (Italy).We give a status of the coordinated contributions from EUMETSAT OSI SAF and ESA CCI to the Sea Ice Concentration ECV.Existing data records are presented, as well as some visualization of recent sea-ice trends. Plans for the period 2019-2022 are outlined (further developments of algorithms, and future data records).For more info contact the authors, and/or visit osisaf.met.no and cci.esa.int.

In einem zukünftigen Luftraummanagementsystem für unbemannte und bemannte Luftraumteilnehmer – insbesondere Flüge in urbanen Gebieten – müssen eine Vielzahl von Randbedingungen beachtet werden, um eine sichere und zugleich effiziente Integration von neuen Luftraumteilnehmern zu gewährleisten. Diese Luftraumteilnehmer können sehr vielfältig sein und umfassen neben VFR-Flugverkehr ebenfalls andere Teilnehmer wie Personal Air Vehicle (PAV), Cargo-UAS, Fallschirmspringer, Wetterballons oder auch zu priorisierenden Luftverkehr wie z.B. Rettungshubschrauber. Neben Aspekten unterschiedlicher UAS/PAV-Bauart, Leistung und Fähigkeiten sind bei einem City-ATM-Konzept auch zusätzliche Anforderungen hinsichtlich geschützter Flugbereiche (sogenanntes Geofencing) oder favorisierte, risikominimierte Flugstrecken (gemäß Minimum Risk Configuration -MRC) zu beachten. Im DLR Projekt City-ATM wird ein Konzept für ein zukünftiges Luftraummanagement (Air Traffic Management – ATM) im urbanen Luftraum entwickelt, welches eine sichere und effiziente Integration von neuen Luftverkehrsteilnehmern (wie unbemannte Luftfahrzeugsysteme und PAV) ermöglichen soll. Dies beinhaltet die Definition und Validierung von operationellen und technischen Konzepten für ein Luftraummanagement, die Informationsbereitstellung, die Verkehrsflusssteuerung und -überwachung sowie grundlegende Konzepte für eine Kommunikations-, Navigations- und Überwachungsinfrastruktur. Basierend auf diesen erarbeiteten Konzepten wird in City-ATM eine Simulations- und Demonstrationsplattform für urbanes ATM ausgearbeitet werden. Dies beinhaltet die Entwicklung eines operationellen Betriebskonzeptes, die Definition von Anforderungen und Rahmenbedingungen an das zukünftiges ATM-System, aber auch Betrachtungen zur technischen Realisierbarkeit eines Luftfahrzeuges, welches in diesen Umgebungsbedingungen sicher operieren kann.

A key topic of the European CL‐Windcon project, and specifically WP1 of the project, is the accurate modelling of wind turbine and wind farm dynamics at a varying range of fidelities. Hence, this document describes the different numerical models employed throughout the project and presents their arrangement and fidelity classification based on the different capabilities, limitations and complexity of their underlying physics. The description of the four categories selected: steady‐state models, control‐oriented dynamical models, medium‐fidelity simulation models, and high‐fidelity simulation models is included and discussed in the document.

This deliverable deals with the classification and the analysis of the wake models set in the CL-Windcon project. The wake models of task 1.2 are classified with respect to their capabilities with various aspects. First, the deliverable gives a general overview on each model as well as a written classification description. The document shows different aspects of validation and tuning of the models. Calibration and parameter tuning are described in detail with the FLORIS and the WFSim model. A sensitivity study is performed using the FAST.Farm model analyzing the impact and uncertainty of different parameters. Then the validation with simulation and wind tunnel data is shown and furthermore, the validation of the reduced-order POD models are performed. In the last chapter several models are compared in a blind test with field-testing data to emphasize the predictability of the wake shape under realistic conditions of the wake models. Altogether various aspects of the models are stated and their capabilities are evaluated and compared.

Nature, 537 (7618), ISSN:0028-0836, ISSN:1476-4687

Im Forschungsbereich PBAM (Performance Based Airport Management) wurde das DLR interne Forschungsprojekt P-AIR-FORM durchgeführt. Hier wurden anhand eines Beispielflughafens die betrieblichen Auswirkungen einer KPI basierten, prätaktischen Betriebsplanung auf die Flughafen-Stakeholder untersucht. Dabei wurde festgestellt, ob ein nach KPIs gesteuerter Flughafenbetrieb grundsätzlich umsetzbar ist und welche Vorteile sich daraus ergeben.

At airports Stakeholders, like ANSP, airport authority, ground service provider and airlines are driven by different goals. Therefore they very often just focus on their own processes and do not coordinate with other Stakeholders. That results in missing information, installation of buffer times and a lack of alignment. The new concept of a Performance Based Airport Management (PBAM) introduces Key Performance Indicators (KPI) to manage the processes and requires the involvement of all Stakeholders. As one enabler for PBAM pre-tactical planning of airport processes is identified. Particularly disruptive for the daily airport business are weather events like thunderstorms or snow fall and freezing rain. Today impacts on the operations are awaited but mostly not considered in pre-tactical planning (timeframe up to day of ops) of operational processes. Often, the present meteorological services do not meet the needs of operators at an airport or the delivered products are not specific enough. The disruptive impact of adverse weather on an airport could however be mitigated by using dedicated and tailored observations and forecasts of weather and integrating them into the information sharing and decision making processes. Through a reliable and robust weather forecast air traffic can be operationally influenced much earlier and necessary decisions can be initiated.

The overall transportation speed is a significant factor influencing the attractiveness as well as the profitability of the transit system. If a vehicle needs less time to complete a tour, it can serve more tours and thus more passengers within the same time. Likewise, the passengers benefit from a decreased in-vehicle travel time. In this paper, the factors affecting the passenger transfer time are discussed for the case of Berlin, Germany. Furthermore, the paper presents the results of a survey that focuses (i) on the average time needed for passengers to board and alight a vehicle, (ii) its deviation, and (iii) the impact of the vehicle’s occupancy and number of boarding/alighting passengers. Such data can also be used to model the boarding and alighting process at stops in transport simulations in a more realistic way. For buses and subways, more passengers standing in the door area of a vehicle are found to slow down the boarding and alighting process. The Berlin specific policy to allow the boarding of a bus only at the first door induces a significantly higher boarding time per passenger.

International audience; We combine second order local regression meta-models with the Covariance Matrix Adaptation Evolution Strategy in order to enhance its efficiency in the optimization of computationally expensive problems. Computationally intensive direct numerical simulations of an anguilliform swimmer provide the testbed for the optimization. We propose two concepts to reduce the computational cost of the meta-model building. The novel versions of the local meta-model assisted Evolution Strategy are tested on benchmark problems and compared to results from literature. The results demonstrate that the use of local meta-models increases significantly the efficiency of already competitive evolution strategies and that the model building cost can be successfully reduced. The meta-model assisted Evolution Strategy is applied to the optimization of the swimming motion of a three-dimensional, self-propelled eel-like body. The motion of the self-propelled body is determined by a set of parameters but the motion is not prescribed apriori. Instead here we introduce the concept of identifying the swimming motion parameters from an evolutionary optimization procedure. The optimization successfully identifies a motion pattern that is 30% more efficient than an existing reference motion pattern. During the efficient swimming motion, the deformation of the body is extended along its length in a controlled fashion.

[no abstract]

Sea ice is a very important component of the climate system. While the Arctic sea ice extent has retreated during the past 20 years, it has remained constant in the Antarctic. In order to better understand the role of sea ice in the climate system in the context of global warming currently used coupled Atmosphere-Ocean Global Circulation Models have to be improved. This requires to know the sea ice concentration C for a long period for both hemispheres and at the best possible spatial resolution. Currently used methods to obtain C like the NASA Team (NT) algorithm are based on data acquired by the Special Sensor Microwave/Imager (SSM/I) at 19 and 37GHz. The SEA LION (SL) algorithm presented here allows to infer C from the polarization P at 85GHz taking advantage of the higher spatial resolution at this frequency. However, the decrease of P caused by the weather influence leads to an overestimation of C. Therefore, P is corrected using a radiative transfer model and atmospheric data taken from Numerical Weather Prediction models and/or derived from SSM/I measurements. The various sea ice and snow properties are considered calculating monthly sea ice tie points. The average standard deviation of C derived with the SL algorithm is 12% for C < 50% and below 5% for C > 90%. The SL ice edge agrees within 10km with the one evident in VIS/IR images. The SL ice concentration gradient across the marginal ice zone (MIZ) agrees much better with the one evident in SAR images compared to results of the NT algorithm. Using the higher spatial resolution at 85GHz the SL algorithm allows to detect smaller open water areas than known algorithms. A major limitation of the SL algorithm arises from the quality of atmospheric data needed for the weather correction. A spatial resolution of these data lower than the 85GHz SSM/I channels and/or a time lag larger than half an hour between both data sets can cause relative errors above 100%, particulary in the cloud-covered parts of the MIZ.

Sea ice is a very important component of the climate system. While the Arctic sea ice extent has retreated during the past 20 years, it has remained constant in the Antarctic. In order to better understand the role of sea ice in the climate system in the context of global warming currently used coupled Atmosphere-Ocean Global Circulation Models have to be improved. This requires to know the sea ice concentration C for a long period for both hemispheres and at the best possible spatial resolution. Currently used methods to obtain C like the NASA Team (NT) algorithm are based on data acquired by the Special Sensor Microwave/Imager (SSM/I) at 19 and 37GHz. The SEA LION (SL) algorithm presented here allows to infer C from the polarization P at 85GHz taking advantage of the higher spatial resolution at this frequency. However, the decrease of P caused by the weather influence leads to an overestimation of C. Therefore, P is corrected using a radiative transfer model and atmospheric data taken from Numerical Weather Prediction models and/or derived from SSM/I measurements. The various sea ice and snow properties are considered calculating monthly sea ice tie points. The average standard deviation of C derived with the SL algorithm is 12% for C < 50% and below 5% for C > 90%. The SL ice edge agrees within 10km with the one evident in VIS/IR images. The SL ice concentration gradient across the marginal ice zone (MIZ) agrees much better with the one evident in SAR images compared to results of the NT algorithm. Using the higher spatial resolution at 85GHz the SL algorithm allows to detect smaller open water areas than known algorithms. A major limitation of the SL algorithm arises from the quality of atmospheric data needed for the weather correction. A spatial resolution of these data lower than the 85GHz SSM/I channels and/or a time lag larger than half an hour between both data sets can cause relative errors above 100%, particulary in the cloud-covered parts of the MIZ., thesis

A key topic of the European CL‐Windcon project, and specifically WP1 of the project, is the accurate modelling of wind turbine and wind farm dynamics at a varying range of fidelities. Hence, this document describes the different numerical models employed throughout the project and presents their arrangement and fidelity classification based on the different capabilities, limitations and complexity of their underlying physics. The description of the four categories selected: steady‐state models, control‐oriented dynamical models, medium‐fidelity simulation models, and high‐fidelity simulation models is included and discussed in the document.

This deliverable deals with the classification and the analysis of the wake models set in the CL-Windcon project. The wake models of task 1.2 are classified with respect to their capabilities with various aspects. First, the deliverable gives a general overview on each model as well as a written classification description. The document shows different aspects of validation and tuning of the models. Calibration and parameter tuning are described in detail with the FLORIS and the WFSim model. A sensitivity study is performed using the FAST.Farm model analyzing the impact and uncertainty of different parameters. Then the validation with simulation and wind tunnel data is shown and furthermore, the validation of the reduced-order POD models are performed. In the last chapter several models are compared in a blind test with field-testing data to emphasize the predictability of the wake shape under realistic conditions of the wake models. Altogether various aspects of the models are stated and their capabilities are evaluated and compared.

The German PMW project and the European EGYC consortium are driving gyrotron developments for the two major plasma fusion experiments in Europe using ECRH, Wendelstein W7-X at Greifswald and the international ITER at Cadarache. 1 MW CW, 140 GHz conventional cavity gyrotrons have been developed and are being delivered to W7-X whereas advanced 2 MW CW, 170 GHz coaxial-cavity gyrotron technology has been tested for ITER. Additionally, an 1 MW, 170 GHz conventional cavity design is under development for ITER. Furthermore, research work on gyrotron concepts for future fusion experiments, focusing on frequency-step tunable gyrotrons and multi-MW coaxial-type gyrotrons is ongoing at Europe, in particular at KIT. This paper is reporting some of the important results and the ongoing research work.

This deliverable deals with the classification and the analysis of the wake models set in the CL-Windcon project. The wake models of task 1.2 are classified with respect to their capabilities with various aspects. First, the deliverable gives a general overview on each model as well as a written classification description. The document shows different aspects of validation and tuning of the models. Calibration and parameter tuning are described in detail with the FLORIS and the WFSim model. A sensitivity study is performed using the FAST.Farm model analyzing the impact and uncertainty of different parameters. Then the validation with simulation and wind tunnel data is shown and furthermore, the validation of the reduced-order POD models are performed. In the last chapter several models are compared in a blind test with field-testing data to emphasize the predictability of the wake shape under realistic conditions of the wake models. Altogether various aspects of the models are stated and their capabilities are evaluated and compared.

Wind energy is one of the fastest growing energy sources, leading to important research efforts targeting costs reduction, improved reliability and grid integration of the wind farms. The development of wind farm simulation tools is thus particularly important, as numerical approaches offer a convenient framework for elaborating control strategies aimed at responding to a grid demand or at mitigating the negative effects related to the rotor wakes. Indeed, in a wind farm configuration, the wake phenomena are responsible for a decrease in power production and a shortening of the lifetime of the turbines, and have a direct impact on the Levelized Cost of Energy. Numerical tools thus have to accurately capture the physics of the rotors and wakes and the unsteady nature of a wind farm production, at a reasonable computational cost. This work aims at achieving this by using Large Eddy Simulation on coarse meshes, combined with an Actuator Disk (AD) method for the wind turbine model. This last approach implies an averaged effect of the blade forces on the surface swept by the rotor. A major effort is made in order to have the most accurate response of the AD, in spite of the underlying approximation and of its coarse resolution: we here consider a rotating disk, for which the loads are estimated from local disk velocities, and a new methodology is implemented to enable the use of a tip-loss correction in wind farm flows. This correction aims at improving the AD behavior by accounting for the differences between a disk method and a discrete blade type approach. This implemented AD is first verified in terms of aerodynamics, loads and wake statistics for a single wind turbine, and results are compared to a higher fidelity approach at a finer resolution, here a Vortex Particle-Mesh method coupled to immersed lifting lines. In a second part, the AD is equipped with realistic control schemes and used in wind farm simulations. These aim at several purposes: (i) to evaluate the performances of the tool in large wind farms in terms of computational costs, (ii) to verify the power production against measurements for an actual wind farm, and (iii) to investigate the wake statistics and the rotor responses in several scenarios. (FSA - Sciences de l'ingénieur) -- UCL, 2018