Fraunhofer Institute for Wind Energy Systems
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CherrySet - A comprehensive dataset of three cherry trees throughout the 2023 season
No full textCherrySet encompasses a collection of 2D images covering three sweet cherry trees at more than 10 distinct time points, spanning from dormancy in March through blooming and growth until harvest in July 2023. In addition to the image data, CherrySet offers manually recorded ground truth information obtained from reference branches throughout the growing season, which includes comprehensive bud, blossoms and fruit counts during all vegetation phases, as well as the total number of cherries gathered at harvest.The For5G project is funded by the 5G innovation program of the German federal ministry for digital and transport under the funding code 165GU103B
MVIP: A Dataset for Industrial Part Recognition
Get PDFWe present MVIP, a novel dataset for multi-modal and multi-view application oriented industrial part recognition. Here we combine a calibrated RGBD multi-view dataset with additional object context such as physical properties, natural language, and super-classes. Our main goal with MVIP is to study and push transferability of various state-of-the-art methods within related downstream tasks towards an efficient deployment of industrial classifiers. Additionally, we intent to push with MVIP research regarding several modality fusion topics, (automated) synthetic data generation, and complex data sampling methods -- combined in a single application oriented benchmark
B3AMpy: Beamforming Toolbox for three-component ambient seismic noise
Get PDFThis is an archived version of version 0.1 with small updates from 26.10.2023. The latest version can be found at: https://github.com/cl-finger/B3Ampy
A Matlab Version of this code can be found at https://github.com/katrinloer/B3AMThis project has been subsidized through the Cofund GEOTHERMICA, which is supported by the European Union's HORIZON 2020 programme for research, technological development and demonstration under grant no. 731117 (DEEP). The german subprojet DEEP-SIGHT has been funded by the 'Bundesministerium für Wirtschaft und Klimaschutz' under project number 03EE4016
Scanning acoustic microscope images for the localization of defects inside dummy pouch cells
No full textThe identification and location of critical defects inside battery cells before the performance decreases or safety issues arise remains a challenge. Here we show images acquired from Scanning Acoustic Microscopy (SAM) as a non-destructive testing methods for the 3D visualization of defects at different depths inside a pouch battery cell. A manufactured dummy pouch cell with 8 cathode sheets is used for this investigation. SAM using a 15 MHz transducer in reflection mode can detect defects with a lateral resolution of 150 µm in 2 min. The time intervals of each micrograph have a length of 30 ns. The images are acquired with a resolution of with a pixel dimension of 50 x 50 μm²/ pixel
Supplementary material for publication in Datenbank-Spektrum
No full textThe data serve as a supplement to the publication Data Catalogs in the Enterprise: Applications and Integration. It includes a table listing the data catalog offerings surveyed, their application class and commercial characteristics, and a table detailing the questions, approach, and results of the data catalog integration survey
Effects of the GDPR in South East Asia vs. Europe - A Large-scale Analysis of IoT Devices
No full textTabular Data for a Conference Paper
Analyzing the regulatory framework gaps for gas distribution networks with decreasing natural gas demand in Germany
No full textThe two datasets are supplement to the publication Oberle, Stella; Gnann, Till; Wayas, Louis; Wietschel, Martin "Analyzing the regulatory framework gaps for gas distribution networks with decreasing natural gas demand in Germany" (to be published): German energy system studies, investigating the energy transition pathways to the set climate targets, depict a significant decrease in gas demand. This leads to a discussion about the long-term need of gas distribution networks. The discussion intensified with the war in Ukraine and the subsequent energy price crisis. The German regulatory agency responded to these developments with adjusting the regulatory framework to the current challenges. Up to now, the depreciation period of network components varies between 45 to 65 years, and consequently the monetary capital is tied up for a long time, lowering the flexibility of network operators to react to current challenges. Therefore, the German regulatory agency allows the shortening of depreciation periods of new gas network assets. Nonetheless, it is still unclear how to deal with existing assets at risk of becoming stranded assets and how to regulate the decommissioning of gas networks. Therefore, this paper addresses the research question: “What effect do different regulations for decommissioning of gas distribution networks have on operators and users?”. To answer the question the model MERLIN is applied, which integrates the current and future regulation options into long-term investment decision analysis. The results show a need of shortening the depreciation period of existing assets to avoid stranded assets. Further, partial decommissioning with including the decommission costs in the regulatory framework and hence finance it through the network users, is the most economical attractive option for network operator and users
Daten zum Projekt (BGA-PtG)2: Ganzheitliche Bewertung der Integration von Power-to-Gas-Konzepten in Biogas- und Biomethananlagen einschließlich der Entwicklung von Geschäftsmodellen für regenerative Gase
No full textDaten, die in eine technische und wirtschaftliche Simulation eingeflossen sind. Kontext ist das Forschungsprojekt (BGA-PtG)2: Ganzheitliche Bewertung der Integration von Power-to-Gas-Konzepten in Biogas- und Biomethananlagen einschließlich der Entwicklung von Geschäftsmodellen für regenerative Gase.
Der Abschlussbericht wird bei der TIB veröffentlicht
K35/K85 structure, and Diclofenac and PFBS force field parameters
No full textEnvironmental pollution by man-made toxic and persistent organic compounds, found throughout the world in surface and groundwater, has various negative effects on aquatic life systems and even humans. Therefore, it is important to develop and improve water treatment technologies capable of removing such substances from wastewater or purifying drinking water. The two substances investigated are the widely used painkiller diclofenac and a member of the class of "forever chemicals", perfluorobutane sulfonate, both of which are known to have serious negative effects on living organisms, especially under long-term exposure. In this study, a human hair keratin dimer is investigated for its ability to absorb diclofenac and perfluorobutane sulfonate. Initial predictions for binding sites are obtained via molecular docking and subjected to molecular dynamics simulations for more than 1µs. The binding affinities obtained by the linear interaction energy method are high enough to motivate further research on human hair keratins as a sustainable, low-cost, and easily allocatable filtration material.Fraunhofer funding under Grant MEF 835617K35/K85 relaxed molecular structure and CGENFF force field parameters of adsobents (diclofenac and PFBS
Data set for AI a ssisted detection of the belt tension on a conveyer belt for condition monitoring
No full textA measurement setup based on an accelerometer, MEMS gyroscope and magnetometer was used to gather data on a conveyor belt to determine the tension of the belt. 100,000 data points are split into 10 measurement series with 10,000 data points each. Each data point consists of 9 time series of the 3 sensors with 3 axis each.A conveyor belt (Vetter Kleinförderbänder GmbH, BK-20-40-1-300-20) is equipped with an inertial measurement unit (IMU) and magnetometer. The IMU is a STMicroelectronics LSM6DSOX, which is mounted via a 3D-printed adapter next to the pulley of the belt. The magnetometer is a STMicroelectronics LIS3MDL, which is mounted near the motor of the belt. The data is sampled by a development board (STMicroelectronics NUCLEO-F446RE) and send via the integrated virtual serial port to a PC to store the data. The amplifier board serves as adapter between the microcontroller on the development board and the sensors via an I2C interface. This board also contains analog amplifiers for other sensors, which are not included in this setup. The data is saved in a HDF5 format using Python