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An extension of the baseline XFOIL from Mark Drela to include the effects of Vortex Generators. Further references available here: https://doi.org/10.1177/0309524X18780390

This tool allows cloud customers to manage both their Access Lists and Firewall entries. Supports custom rules and Intranet-Rules which are automatically updated using the Intranet list provided by CC-Daten

Token Manager for (Flex-based) Abaqus Tokens. Configurable through policy file.

Folder containing public accessible tutorials for wind turbine rotor blades aerodynamic applications in OpenFOAM

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The demonstration illustrates the generation of a quantum feature map for a simple regression problem. Reinforcement learning techniques are used, visualizing the decision process of the AI agent through a simple visualization of the quantum circuit creation. We show how to load, train and test the model. The results show a feature map design tailored to the problem.

Finds smallest distance between any point in R3 to a point on a specific curve

JavaScript library to wrap in the browser with the factory pattern a client for the STOMP protocol over web sockets.

Link zur Doku: http://fre10753.pages.fraunhofer.de/mkdocs-example

Public mirror of internal repository

We propose a quantum version of the deterministic annealing algorithm to verify the input-output relations of a neural network. We apply the algorithm to traffic sign recognition, an important task for self-driving vehicles.

Interference signals cause position errors and outages to global navigation satellite system (GNSS) receivers. However, to solve these problems, the interference needs to be detected, classified, its purpose determined, and localized, such that it can be eliminated. Several interference monitoring solutions exist, but these are expensive, resulting in fewer nodes that may miss spatially sparse interference signals. This paper introduces a low-cost commercial-off-the-shelf (COTS) GNSS interference monitoring, detection, and classification receiver. It employs machine learning (ML) on tailored signal pre-possessing of the raw signal samples and GNSS measurements to facilitate a generalized, high-performance architecture that does not require human in the loop (HIL) calibration. Therefore, the low-cost receivers with high performance can justify significantly more receivers to be deployed, resulting in a significantly higher probability of intercept (POI). The initial results of controlled interference scenarios demonstrate detection and classification capabilities exceeding conventional approaches.