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Jun 30, 2025 - Data Analytics in Engineering
Keshav, Sanath; Herb, Julius; Fritzen, Felix, 2025, "Supplemental data for "Spectral Normalization and Voigt–Reuss net: A universal approach to microstructure‐property forecasting with physical guarantees"", https://doi.org/10.18419/DARUS-5120, DaRUS, V1
This repository contains supplemental data for the article "Spectral Normalization and Voigt-Reuss net: A universal approach to microstructure‐property forecasting with physical guarantees", accepted for publication in GAMM-Mitteilungen by Sanath Keshav, Julius Herb, and Felix Fritzen [1]. The data contained in this DaRUS repository acts as an exte...
Jun 26, 2025 - Institute of Engineering and Computational Mechanics
Leprich, David; Rosenfelder, Mario; Hermle, Mario; Chen, Jingshan; Eberhard, Peter, 2025, "Experiment Video for Model Predictive Path-Following Control of a Quadrotor", https://doi.org/10.18419/DARUS-5099, DaRUS, V1
The provided video shows an experimental result of a Model Predictive Path-Following Controller (MPPFC) applied to a Crazyflie Quadrotor. The objective is to fly along the lemniscate path. The lemniscate is defined as a time-independent geometric curve, parameterized by a so-called timing law. Based on this, the MPPFC generates a dynamically feasib...
MPEG-4 Video - 4.1 MB - MD5: 9110fa67576c6b32780b1a0f022b3024
Jun 24, 2025 - HEFDiG
Loehle, Stefan; Leiser, David; Toth, Juraj; Matlovič, Pavol; Pisarčíková, Adriana; Vaubaillon, Jeremie; Grigat, Felix; Eberhart, Martin; Hufgard, Fabian; Ravichandran, Ranjith; Poloni, Erik; Hörner, Igor; Dürnhofer, Christian; Delahaie, Sara; Ferrière, Ludovic; Sylvian Rommeluere; Rambaux, Nicolas, 2025, "Data from the MetSpec Experiments", https://doi.org/10.18419/DARUS-5100, DaRUS, V1, UNF:6:uEwTKTW4z6RxtYl8SAGfaQ== [fileUNF]
Data from ground testing of meteorites. It comprises video, still frames and spectroscopic data from 31 experiments examining 28 meteorite samples of various origins. The three experimental campaigns took place between 2020 and 2022.
Adobe PDF - 553.3 KB - MD5: dfea32224c5291e144f827645dc9591b
MS Powerpoint - 6.0 MB - MD5: 653db6632372ee1aa385a18598b64cfa
MS Powerpoint - 1015.8 KB - MD5: 4d1ea4fd6387fc053ba8fbd9e5032cb1
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