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Terragon: A Unified Framework for Earth Observation Data Cube Generation
No full textTerragon (Earth(Poly)gon) is a Python package facilitating access to remote sensing and Earth observation data from multiple sources. Its goal is to unify the process of downloading data in a simple and efficient manner. While existing tools focus on specific satellites or data providers,
Terragon offers a more flexible solution. The package offers a consistent way to search, filter, and download data from various data sources. It utilizes a polygon format to define the region of interest and creates a spatio-temporal data cube (Mahecha et al., 2020) of rasterized data
in the Xarray Dataset format, as illustrated in Figure 1. Additionally, it ensures the alignment of projections and resolutions, organizing the data according to the selected resolution and coordinate reference syste
Investigating extreme crosswind-stability of vehicles on bridges: applying a moving-model and side wind-tunnel methodology with full-scale validation
No full textA multi-disciplinary approach – combining wind engineering and vehicle aerodynamics – is being developed for investigations into the stability of vehicles operating in extreme crosswind conditions. In this case, heavy vehicles travelling over a 56m high bridge across a Norwegian fjord that could encounter wind gusts of up to 40m/s. Potential changes to the climate and weather conditions could result in increased occurrence of extreme wind events, in addition to ever increasing road usage and infrastructure development. Crosswind exposure and vehicle-infrastructure interaction are inherently transient, non-statistically stationary aerodynamic events that require novel scaled experimental methodologies and full-scale measurements for realistic, representative aerodynamic investigations
Aerodynamic optimization of freight-train operation: utilizing real-world and wind-tunnel experiments
No full textThe DLR FR8-LAB, a self-contained measurement-system equipped container has been used to take aerodynamic measurements on operational freight-trains. Transient pressure was measured with 330 sensors, and the global transient-forces and moments have been derived: aerodynamic drag – important for operational efficiency, and side-force and rolling moment – important for safety (the risk of overturning and derailment). LiDAR sensors, satellite navigation and thermal cameras are used to couple the aerodynamic measurements with the operating scenarios. Results have indicated significant differences in aerodynamic characteristics based on the operating conditions of freight trains: loading configuration, tunnels, crosswind – that have a significant impact on operating efficiency, and potentially the safety of operation. Together with wind-tunnel experiments performed in parallel – validated by this real-world data – recommendations for aerodynamic optimization can be made for freight-train and infrastructure operators and manufacturers
Ice Shelf Area and Ice Shelf Area Change from Sentinel-1 SAR
No full textFloating ice shelves fringe 74% of Antarctica's coastline, directly linking the ice sheet and the surrounding oceans. The landward extent of the ice shelf is the grounding line, which marks the transition of grounded ice to the ice shelf, and its seaward limit is the ice shelf front, which is the boundary between the shelf and the ocean. The change in ice shelf area is an important indicator of ice shelf stability in a warming climate, being affected by grounding line retreat as a possible consequence of ice thinning and calving events at the front, culminating with ice shelf disintegration or collapse.
Two independent processing chains developed at DLR's Earth Observation Center are used to quantify the ice shelf perimeter around Antarctica. For the ice shelf fronts, we use IceLines, a deep learning-based framework providing calving front locations (CFL) on different temporal scales (daily, monthly, quarterly, annual) for Antarctic ice shelves automatically extracted from Sentinel-1 radar imagery. The procedure is operational, and monthly releases of the datasets are available on the DLR's GeoService data portal (https://download.geoservice.dlr.de/icelines/files/). The time series of gapless grounding lines is more challenging to obtain due to limited timely and coherent SAR acquisitions. We use the time-annotated Grounding Line Location (GLL) product of ESA's Antarctic Ice Sheet Climate Change Initiative to derive an average grounding line for a certain period, e.g., one year. Our custom procedure fills the gaps with grounding lines from manual and machine-learning delineations of temporally close Sentinel-1 DInSAR interferograms and external datasets.
This study presents ice shelf area changes derived with a novel method that was developed to combine the grounding lines derived from Sentinel-1 A/B with contemporaneous Sentinel-1 A/B-based ice shelf fronts. By analyzing area change based on changes in the ice shelf front and the grounding line we can attribute area change to either grounding line retreat or ice shelf calving, providing information about the causes of an area change. Examples of annual ice shelf perimeters of major ice shelves from the start of the Sentinel-1 era to the present will be presented and discussed
Urban air mobility: level of service framework for the performance-based evaluation of vertidrome airside operations
No full textAs the urban air mobility (UAM) industry matures, the need for a comprehensive evaluation framework to assess its performance from a transport service perspective becomes increasingly important. This dissertation contributes to the dynamically changing landscape of UAM by focusing on vertidromes, UAM-tailored ground infrastructure for passenger transport services provided by (electric) vertical take-off and landing capable aircraft. A systematic literature review of more than 190 sources has identified fundamental knowledge and key principles for the design and integration of vertidromes into the airspace.
However, significant research gaps remain, particularly in the areas of cost estimation, safety assessment, regulatory guidance, weather dependency, noise impact, and security assessment. The key innovation of this dissertation is the development and validation of the Vertidrome Airside Level of Service (VALoS) framework. The VALoS is a UAM service-oriented, performance-based approach to evaluate the airside traffic flow of a given vertidrome design, taking into account the service requirements and operational performance targets of the vertidrome stakeholders. Based on the current state of the art, an exemplary vertidrome layout and airside operational concept were developed and used as a reference to analyze the applicability of the VALoS framework.
Through fast-time simulation validation, the VALoS framework - evaluated at 15-minute intervals and tailored to the key stakeholders passenger, air taxi operator, and vertidrome operator - provides valuable insights to support strategic decision making and operational planning under nominal, disturbed and disrupted conditions. In addition, the impact of changing wind conditions on vertidrome operations was investigated. By analyzing historical METAR wind data for two potential vertidrome locations, Munich Airport and Hamburg Airport, the VALoS framework shows the weather impact on UAM operations, enabling informed decision to be made about vertidrome operating hours and restrictions, the impact on vertidrome airside traffic flows, and profitable UAM routes. The VALoS metric is therefore able to indicate both the performance degradation and the suitability of a particular vertidrome location. The results of this dissertation underline the ability of the VALoS framework to effectively contribute to the strategic airside design phase of future UAM vertidromes. With the Vertidrome Airside Level of Service framework, it is possible to quantitatively measure the airside performance of future UAM ground infrastructure and to ensure that vertidrome operations meet stakeholder expectations, address the right business cases, enable demand-driven scalability, and target long-term sustainability from an infrastructure construction perspective. The VALoS framework supports vertidrome planners and operators to ensure the "use case right" design and operation of vertidromes. It lays the foundation for a sustainable and efficient vertidrome ecosystem design, contributing to the successful development and implementation of UAM
Methods to develop PEM fuel cell-based powertrains for regional aircraft – a multiple scales approach
No full textIn this paper, four different test environments operated by the DLR Institute of Engineering Thermodynamics are presented. These test environments are designed for the development and optimization of fuel cell systems and fuel cell-based powertrains for aircraft applications and the development of application-specific operating strategies. To this end, the research is conducted on different scales, ranging from the investigation of short-stack fuel cell systems with a few kW power under high-altitude conditions to the analysis of the coupling behavior of the different subsystems of a fuel cell-based electrical powertrain in the MW range. Selected results of experimental investigations are discussed. On the one hand, these results highlight the large optimization potential through altitude-adaptive fuel cell system control. On the other hand, the successful proof of performance of a multi-stack fuel cell system and an e-drive system in the MW range conducted on a novel large-scale research facility is shown
A Field Experiment at the Hohenheim Land-Atmosphere Feedback Observatory (LAFO) During the Vegetation Period in 2025: Instrument Synergy and First Results
No full textQuantifying isomeric effects on metric for fuel impact
No full textThe aeronautical sector, responsible for about 2 to 3 % of global CO2 emissions, has set
an ambitious goal: achieving carbon neutrality by 2050 in order to limit its impact on
climate change. In this perspective, sustainable aviation fuels appear as a key solution, offering a renewable alternative capable of significantly reducing emissions while integrating
with existing infrastructure. To maximize the efficiency and minimize the environmental
impact of SAF, it is essential to understand in detail how the molecular composition, and
more particularly isomeric variations, influence their combustion properties and emissions.
With this in mind, the DLR is currently building a tool called simfuel to analyze, design
and optimize fuels for aeronautics. One of the main features of simfuel is to be a database
consisting of complex fuel but also pure molecule data. We will therefore only use the
database composed of pure molecules as part of this report. This database is based on
experimental data collected in the University of Washington database but also with inter-
nal data from the DLR. Our study is based on the following physico-chemical properties:
density, kinematic viscosity, surface tension and cetane number. Since all these properties
are not available in the initial databases, using a model to predict these properties allows
us to solve this problem. Thus the method ’Mean Quantitative Structure-Property Relationship method’ which will be called MQSPR allows to overcome this problem. This
method allows starting from the numbering of 49 atomic particulate structures which we
will call MQSPR representation to predict a possible value of the different missing proper-
ties. We also need to know the evaporation rate of the different molecules studied; for this
we used an internal calculation code at DLR: Spraysim. Spraysim allows calculating an
evaporation time of our molecules when we insert them into the combustion chamber, this
allows calculating an evaporation rate if we know the atomization diameter of our fuel at
the injection of the combustion chamber. Now that all our fundamental properties have
been estimated, we can detail the models used to address our problem of quantifying the
effects of isomers. Our different models are: the sauter mean diameter which allows estimating the atomization diameter, the fuel consumption limit at lean burn, the maximum
distance that our aircraft can travel, water emissions, carbon dioxide emissions and soot
emissions, the effects of condensation streaks and finally the total radiative effects due
to combustion. We have therefore developed a python code allowing to calculate these
different models from fundamental properties of each molecule in the simfuel database.
The preliminary results of these models allow us to realize that aromatic families should
be avoided to reduce pollutant emissions. To deepen this result, we calculated a Pearson correlation between the data of these models and the MQSPR representation. This
highlights the atomic structures that contribute the most to each of our models. Thus
the presence of a ring and aromatic carbon (carbon in a ring that has a single bond and
a double with other carbon atoms) are the two main structures that contribute most to
pollutant emissions. Finally, we looked at the influence of isomer structures on our models
within a hydrocarbon family and a fixed carbon number. We compared this gap to the
average value with the gap between the families of hydrocarbons as well as between the
numbers of carbons. It follows that the type of hydrocarbon influences the models more
than the structures of isomers. However, the types of isomers influence nearly twice as
much as the number of carbon. Thus, when possible, knowledge of the structure of the
isomer provides real additional information. However, knowing the isomer structure of
each molecule in a multi-molecule fuel remains very complex to obtain experimentally.
The objective of the simfuel project is ultimately to combine this structural knowledge
with machine learning approaches to accelerate the rational design of sustainable and
efficient fuels
Simulation of Thermoplastic Composite Storage Vessels for Cryogenic Fluids
No full textThis thesis investigates the structural performance of composite materials with thermoplastic matrices for use in cylindrical tanks designed for liquid hydrogen storage under cryogenic conditions. A material property database at cryogenic temperatures is developed and implemented in ANSYS Workbench. The study systematically examines the influence of several design parameters, including composite wall thickness, matrix and fiber type, liner presence, and liner material. Among the materials evaluated, carbon fiber-reinforced PPS and PEEK exhibit the best performance, while glass fiber composites are less effective. While the incorporation of an HDPE liner reduces the IRF, greater reductions for a lower mass penalty are realised when using higher performance thermoplastics, particularly PEEK and PPS, as a liner material as well as composite matrix. The optimal configuration—a 9.6 mm linerless CFPPS tank—achieves the highest performance between the selected configurations. Although the modeling approach is intentionally simplified, the findings offer valuable insights for material selection and structural optimization. The study also identifies key areas for future work, including improved modeling fidelity and the exploration of additional materials and geometries