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    Item type:Research Data, Access status: with files ,
    Data for "Millimeter-Scale Lagrangian Sensor Spheres for Local State Monitoring in SMART Reactors: Towards Energy-Autonomous Operation"
    (2026-07-09)
    Geläschus, Anton Ulrich
    ;
    Rennpferdt, Lukas
    ;
    Rathi, Vamika
    ;
    Hussain, Muhammad Daniyal
    ;
    Ruprecht, Daniel
    This dataset contains the underlying measurement data and Python-based analysis scripts supporting the publication “Millimeter-Scale Lagrangian Sensor Spheres for Local State Monitoring in SMART Reactors: Towards Energy-Autonomous Operation”. It includes raw and intermediate data for selected quantitative evaluations, such as power consumption, transmission behavior, energy harvesting, and trajectory-related analysis. The dataset is intended to support traceability and practical reuse of the reported evaluation workflows. Manuscript text and final publication graphics are not the primary subject of this dataset release and should be consulted in the associated journal publication.
    Data Type: Software ; Data Type: Technical Documentation ; Data Type: Experimental Data
      61  56
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    Item type:Research Data, Access status: without files ,
    In-silico Lagrangian sensor tracking in a stirred tank reactor: filtering code
    (2026-06-10)
    Rathi, Vamika
    This repository contains the code used for tracking in-silico Lagrangian sensors governed by the Maxey–Riley–Gatignol equations, as presented in the paper (preprint): Rathi, Sehar, Sommer, Götschel, Stuewe, von Kameke, Ruprecht, "Tracking in-silico Lagrangian sensors in a lab-scale stirred tank reactor", preprint, tba. The repository includes: filtering algorithms and scripts file for interpolation objects for experimental velocity field the Maxey–Riley–Gatignol forward dynamics with analytic Jacobians analytical and experimental velocity-field providers utilities for measurements, noise and plotting a central .json configuration file for all particle, fluid, and filter parameters tracking results and figures Using this code, it is possible to reproduce all results discussed in the paper.
    Data Type: Source Code
      49
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    Item type:Research Data, Access status: without files ,
    Marge3D Solver
    (2026-05-29)
    Rathi, Vamika
    ;
    Lunet, Thibaut
    Solver for the Maxey-Riley-Gatignol Equations (MaRGE) in 3D
    Data Type: Software
      31
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    Item type:Research Data, Access status: without files ,
    Numerical Methods for the Maxey-Riley-Gatignol Equations
    (2026-04-08)
    Sommer, Finn
    First release of a trajectory generation framework for training universal differential equations (UDEs) to approximate the Basset (history) force in the Maxey–Riley–Gatignol equations. This repository provides trajectory generation based on the full Maxey–Riley–Gatignol equations for two types of fluid fields: a synthetic vortex field and an experimental field derived from interpolated measurement data. The interpolation routines are included as part of the codebase. The implementation is available in both Python and Julia. This repository contains the software accompanying the preprint: Sommer, Rathi, Götschel, Ruprecht, “Approximation of the Basset force in the Maxey–Riley–Gatignol equations via universal differential equations”, preprint, tba.
    Data Type: Source Code
      26
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    Research Data for the Publication: Generalization of LSTM and CNN Autoencoders for Anomaly Detection Across Orthogonal and Longitudinal Turning
    (2026-04-07)
    Wu, Ya-Jing
    The dataset consists of several turning tests and is supplementary to the paper 'Generalization of LSTM and CNN Autoencoders for Anomaly Detection Across Orthogonal and Longitudinal Turning'. The experiments cover two datasets by Hamburg University of Technology and TU Dortmund University. The experiments include cutting edges of various indexable inserts, each of which was used with constant process parameters until failure. The three-axis force data is available as in-situ online measurements.
    Data Type: Dataset
      108  40
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    Item type:Research Data, Access status: without files ,
    UDEsAnalysis
    (2026-04-07)
    Sommer, Finn Luca
    First release of analysis tools for the universal differential equation (UDE) framework used to approximate the Basset force. This repository contains the software accompanying the preprint: Sommer, Rathi, Götschel, Ruprecht, "Approximation of the Basset force in the Maxey–Riley–Gatignol equations via universal differential equations".
    Data Type: Research Software
      18
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    JulioUri/Basset-History-Term-Influence
    (2024-11-30)
    Urizarna Carasa, Julio
    This repository contains the Python scripts implemented for the development of the paper Relevance of the Basset history term for Lagrangian particle dynamics. Here one can therefore find the scripts that generate the figures and tables in the following publication: Urizarna-Carasa, L., Ruprecht, D., von Kameke, A., Padberg-Gehle, K., (2024), Relevance of the Basset history term for Lagrangian particle dynamics. To appear in Nonautonomous Dynamical Systems: theory, Methods, and Applications. v2.0 - Changed according to reviews I changed the code to consider nondimensional data and a cylinder as a domain for the Bickley Jet. We use the nondimensionalised version of the MRE and therefore all input from the fields has to be nondimensional. Due to that I had to update the plots too. We also imposed periodic boundary conditions for the horizontal dimension of the Bickley Jet, like if it was an infinite cylinder. Plots had to be updated due to that too.
    Data Type: Research Software
      50
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    JulioUri/CFD_Numerics-for-the-Maxey-Riley-Equation: Small changes
    (2024-11-26)
    Urizarna Carasa, Julio
    This repository contains the Python scripts implemented for the development of the paper "Efficient numerical methods for the Maxey-Riley equations with Basset History Term".
    Data Type: Research Software
      44
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    Parallel-in-Time/pySDC
    (2024-09-23)
    Speck, Robert
    ;
    Lunet, Thibaut
    ;
    Baumann, Thomas
    ;
    Wimmer, Lisa
    ;
    Akramov, Ikrom
    The pySDC project is a Python implementation of the spectral deferred correction (SDC) approach and its flavors, esp. the multilevel extension MLSDC and PFASST. It is intended for rapid prototyping and educational purposes. New ideas like e.g. sweepers or predictors can be tested and first toy problems can be easily implemented.
    Data Type: Research Software
      22
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    Item type:Research Data, Access status: with files ,
    Data artefact: Bathymetry reconstruction from experimental data with PDE-constrained optimisation
    (2024-06-04)
    Ruprecht, Daniel
    This artefact provides data and a detailed description of a wave flume experiment with and without an artifical Gaussian-shaped bathymetry. Provided a wave height measurements at four sensor points over time. Included in this data set are (1) the data itself in TXT format, (2) a video showing the waves in the flume in MP4 format and (3) a description of the experimental setup in PDF format.
    Data Type: Experimental Data
      153  193