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Permanent URI for this collectionhttps://vhrz2219.hrz.uni-marburg.de/handle/123456789/28

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    Wissenschaft trifft Wirtschaft: Digitaler Zwilling in Produktion und Logistik [Repository]
    (Universität Kassel) Wenzel, Sigrid; Gliem, Deike; Wittine, Nicolas
    Daten und Auswertung einer Befragung, die im Kontext der Veranstaltung "Wissenschaft trifft Wirtschaft: Digitaler Zwilling in Produktion und Logistik" am 08.10.2024 im Science Park Kassel stattgefunden hat. Im Rahmen der Veranstaltung wurde eine interaktive Publikumsbefragung mit Mentimeter durchgeführt. Die Daten, erfasst über das Webtool und exportiert als Excel-Tabelle, bilden die Grundlage für die Analyse. Ergänzend zur Befragung wurde eine umfassende Literaturrecherche durchgeführt, die aus 244 Treffern 47 relevante Quellen identifizierte. Aus diesen 47 Quellen wurden 8 Quellen zur detaillierten Untersuchung ausgewählt. Diese bilden die Grundlage zur Beantwortung der Forschungsfragen: "Welche Anwendungsfälle des Digitalen Zwillings gibt es?" und "Welche Herausforderungen bestehen bei der Implementierung und Nutzung Digitaler Zwillinge?"
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    Research Data
    Surface layer state after hard turning of 51CrV4
    (Universität Kassel) Wittich, Felix; Wegener, Thomas; Liehr, Alexander; Zinn, Wolfgang; Niendorf, Thomas; Kroll, Andreas

    Description of the dataset:

    Hard-turning experiments were conducted on cylindrical specimens made of a quenched and tempered (Q&T) steel 51CrV4
    in different initial surface hardness levels, i. e. 400 HV30, 500 HV30 and 600 HV30. Prior to heat treatment,
    all specimens were manufactured with the same roughness requirements in order to ensure an almost identical surface
    finish before hard-turning. Three different sections of nine specimen of each hardness level
    (i.e. in total 27 section-specific areas per hardness level) were machined with varied cutting parameters feed rate
    (f), depth of cut (a_p) and cutting speed (v_c).
    Hard-turning of the specimens was carried out on a servo-conventional lathe of type Weiler C30 using
    polycrystalline boron nitride (PCBN) inserts with a corner radius of 0.8 mm.

    After hard-turning, residual stress depth profiles were determined using X-ray diffraction (XRD),
    respectively for each specific area of a specimen. Residual stress measurements were conducted using a
    Pulstec μ-X360 diffractometer equipped with a 0.3 mm collimator and CrKα-radiation with an exposure time
    of 120 sec. Depth profiles were determined by successive removal of the material surface layer using
    electro-chemical polishing. The obtained data have been evaluated applying the cos α-method without consideration
    of any mathematical stress correction.

    Post process surface roughness in axial direction was determined using a Mitutoyo SJ-210 tactile roughness
    measuring device. Post process Vickers hardness testing was carried out using a Struers DuraScan-70 system
    employing a load of 294.2 N (HV30).
    For more detailed information on the material and the experimental setup, i.e., chemical composition, specimen
    geometry, machines and parameters used for hard-turning operations and post process measurements, the reader is
    referred to [1].

    A full factorial experiment design was used with two levels for the initial hardness levels H_Vinit and three
    factors for the cutting parameters, f: {0.05 mm, 0.25 mm, 0.5 mm}, v_c: {100 m/min, 175 m/min, 250 m/min},
    a_p: {0.05 mm, 0.25 mm, 0.5 mm}, resulting in 81 different combinations. For the residual stress depth profile
    modeling, measurements for 12 different depths are available:
    {0, 10, 20, 30, 40, 50, 60, 80, 100, 120, 150, 200} μm, providing for N = 972 samples in total.

    Two data sets are provided:
    1. "hardness_roughness_hard_turning.csv" with the 81 data points for the surface hardness and roughness measurements.
    2. "residual_stress_profile_hard_turning.csv" with the 972 data points for the tangential residual stress depth profiles.

    [1]     Thomas Wegener, Alexander Liehr, Artjom Bolender, Sebastian Degener, Felix Wittich, Andreas Kroll, & Thomas Niendorf,
            "Calibration and validation of micromagnetic data for non-destructive analysis of near-surface properties
            after hard turning" in HTM Journal of Heat Treatment and Materials, 2022, 77(2), 156-172.

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    Research Data
    Navigating the Remanufacturing Trilemma: Balancing Customer, Manufacturer, and Lawmaker Interests [Repository]
    (Universität Kassel) Reintanz, Lisa; Wittine, Nicolas; Lange, Kirsten; Wenzel, Sigrid; Refflinghaus, Robert

    The associated paper explores the trilemma between different circular economy stakeholders (customer, manufacturer and legislator). The overview database (2019-2024) contains 84 relevant papers (out of 880), which were reduced to 27 through analysis. In addition, findings from expert interviews are used to uncover conflicts and synergies.


    The provided Excel file contains the researched literature and documents the process and findings. The main content is found in "References". Each PDF contains an interview protocol, numbered according to the paper’s Table 3. Each protocol contains a description of the expert and a discussion summary.


    The provided presentation was used as a guide to conduct the interviews.

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    Mechanical Properties of Ultra-High Performance Concrete (UHPC)
    (Universität Kassel) Rezazadeh, Farzad; Dürrbaum, Axel; Abrishambaf, Amin; Zimmermann, Gregor; Kroll, Andreas

    Ultra-high-performance concrete (UHPC) possesses mechanical characteristics that significantly outperform traditional concrete. However, replicating these properties consistently across different production batches—even when using the same recipe—remains a challenge.

    This dataset examines how variations in raw materials, environmental conditions, dosage variation, and both mixing and curing practices affect the mechanical properties of UHPC produced from a single reference formulation. Designed according to a three-phase design of experiments methodology, the dataset comprises 150 systematically planned experiments, offering a comprehensive view of the multiple factors influencing UHPC quality. Measurements of compressive and flexural strengths are provided at 24 hours and after 28 days post-mixing. Beside the mechanical properties, the dataset includes five characteristics of the fresh state, measured directly after each mixing process.

    All experiments are conducted in the laboratory of G.tec Engineering GmbH under controlled conditions, using the same mixer, same mixing tool, and the same team of technicians. The environment is maintained at a constant temperature of 20 °C throughout the experimental process.

    From each experiment, three specimens are cured under the designed conditions. First, the flexural strength is measured by carefully halving each of the three specimens. Then, the resulting six halves are used to measure the compressive strength. Finally, after a careful analysis of the results from each specimen, the averages for flexural and compressive strengths are reported.

    The dataset also includes outliers. After analysis by UHPC experts and the data science team, 11 data points (numbered 5, 17, 30, 36, 41, 47, 57, 99, 101, 128, and 148) were identified and removed as outliers to assure data quality.

    By offering a structured collection of high-dimensional data and a relatively small data size, this dataset is particularly suitable for advanced regression analyses, notably those addressing sparse data scenarios.

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    Impact of a single-side 100Cr6 clad layer on the tensile and fatigue properties of S550MC steel [Dataset]
    (Universität Kassel) Krochmal, Marcel; Wegener, Thomas; Niendorf, Thomas
    The production of newly developed hot-rolled layered metal composites (LMC) leads to the availability of sheet materials with specifically adjustable, graded properties being cost-effective and suitable for large-scale production. As many of the envisaged applications of these LMC, e.g., clutch disc carriers, suffer from cyclic loading during service life, a fundamental knowledge of the fatigue behavior is required in order to ensure safe and reliable application of the components. Therefore, the study described in https://doi.org/10.1111/ffe.14383 focuses on the fatigue behavior of a hot-rolled two-layer LMC consisting of a S550MC substrate layer and a 100Cr6 clad layer. In order to investigate the influence of the clad layer, two conditions are directly compared, i.e., the two-layer laminate cladded steel and the single-layer substrate condition.
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    Differentiation between Hydrolytic and Thermo-Oxidative Degradation of Poly(lactic acid) and Poly(lactic acid)/Starch Composites in Warm and Humid Environments [Dataset]
    (Universität Kassel) Goetjes, Victoria; Zarges, Jan-Christoph; Heim, Hans-Peter
    For the application of poly(lactic acid) (PLA) and PLA/starch composites in technical components such as toys, it is essential to know their degradation behavior under relevant application conditions in a hydrothermal environment. For this purpose, composites made from PLA and native potato starch were produced using twin-screw extruders and then processed into test specimens, which were then subjected to various one-week ageing processes with varying temperatures (23, 50, 70, 90 °C) and humidity levels (10, 50, 75, 90%). This was followed by mechanical characterization (tensile test) and identification of degradation using Gel Permeation Chromatography (GPC), Thermogravimetric Analysis (TGA), Fourier Transform Infrared Spectroscopy (FTIR), and Nuclear Magnetic Resonance spectroscopy (NMR). With increasing temperature and humidity, there was a clear degradation of the PLA, which could be reduced or slowed down by adding 50 wt.% starch, due to increased crystallinity. Hydrolysis was identified as the main degradation mechanism for PLA and PLA/starch composites, especially above the glass transition temperature, with thermo-oxidative degradation also playing a subordinate role. Both hydrolytic degradation and thermo-oxidative degradation led to a reduction in mechanical properties such as tensile strength. In case you use the data please cite our corresponding article (https://doi.org/10.3390/ma17153683).
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