13 Zentrale Universitätseinrichtungen

Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/14

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Institute: search.filters.UBSInstitut.Fakultätsübergreifend / Sonstige EinrichtungStart date: 2022

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Now showing 1 - 10 of 28
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    Touching data with PropellerHand
    (2022) Achberger, Alexander; Heyen, Frank; Vidackovic, Kresimir; Sedlmair, Michael
    Immersive analytics often takes place in virtual environments which promise the users immersion. To fulfill this promise, sensory feedback, such as haptics, is an important component, which is however not well supported yet. Existing haptic devices are often expensive, stationary, or occupy the user’s hand, preventing them from grasping objects or using a controller. We propose PropellerHand, an ungrounded hand-mounted haptic device with two rotatable propellers, that allows exerting forces on the hand without obstructing hand use. PropellerHand is able to simulate feedback such as weight and torque by generating thrust up to 11 N in 2-DOF and a torque of 1.87 Nm in 2-DOF. Its design builds on our experience from quantitative and qualitative experiments with different form factors and parts. We evaluated our prototype through a qualitative user study in various VR scenarios that required participants to manipulate virtual objects in different ways, while changing between torques and directional forces. Results show that PropellerHand improves users’ immersion in virtual reality. Additionally, we conducted a second user study in the field of immersive visualization to investigate the potential benefits of PropellerHand there.
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    Datamator : an authoring tool for creating datamations via data query decomposition
    (2023) Guo, Yi; Cao, Nan; Cai, Ligan; Wu, Yanqiu; Weiskopf, Daniel; Shi, Danqing; Chen, Qing
    Datamation is designed to animate an analysis pipeline step by step, serving as an intuitive and efficient method for interpreting data analysis outcomes and facilitating easy sharing with others. However, the creation of a datamation is a difficult task that demands expertise in diverse skills. To simplify this task, we introduce Datamator, a language-oriented authoring tool developed to support datamation generation. In this system, we develop a data query analyzer that enables users to generate an initial datamation effortlessly by inputting a data question in natural language. Then, the datamation is displayed in an interactive editor that affords users the ability to both edit the analysis progression and delve into the specifics of each step undertaken. Notably, the Datamator incorporates a novel calibration network that is able to optimize the outputs of the query decomposition network using a small amount of user feedback. To demonstrate the effectiveness of Datamator, we conduct a series of evaluations including performance validation, a controlled user study, and expert interviews.
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    Schaustücke : Einblicke in wissenschaftliche Sammlungen der Universität Stuttgart
    (Stuttgart : Universität Stuttgart, 2022) Wiatrowski, Frank (Gestaltung, Fotograf); Engstler, Katja Stefanie (Gestaltung); Ceranski, Beate (Vorwort); Rambach, Christiane (Vorwort)
    Die wissenschaftlichen Sammlungen der Universität zeugen von einer langen Lehr- und Forschungstradition. In Fakultäten und Instituten, in der Universitätsbibliothek und im Universitätsarchiv sind vielfältige Sammlungen beheimatet, zum Teil mit ungewöhnlichen oder gar einzigartigen Objekten. Die Broschüre gibt erste Einblicke in diese vielfach versteckte Welt der universitären Sammlungen in Stuttgart.
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    Performance comparison of CFD microbenchmarks on diverse HPC architectures
    (2024) Galeazzo, Flavio C. C.; Garcia-Gasulla, Marta; Boella, Elisabetta; Pocurull, Josep; Lesnik, Sergey; Rusche, Henrik; Bnà, Simone; Cerminara, Matteo; Brogi, Federico; Marchetti, Filippo; Gregori, Daniele; Weiß, R. Gregor; Ruopp, Andreas
    OpenFOAM is a CFD software widely used in both industry and academia. The exaFOAM project aims at enhancing the HPC scalability of OpenFOAM, while identifying its current bottlenecks and proposing ways to overcome them. For the assessment of the software components and the code profiling during the code development, lightweight but significant benchmarks should be used. The answer was to develop microbenchmarks, with a small memory footprint and short runtime. The name microbenchmark does not mean that they have been prepared to be the smallest possible test cases, as they have been developed to fit in a compute node, which usually has dozens of compute cores. The microbenchmarks cover a broad band of applications: incompressible and compressible flow, combustion, viscoelastic flow and adjoint optimization. All benchmarks are part of the OpenFOAM HPC Technical Committee repository and are fully accessible. The performance using HPC systems with Intel and AMD processors (x86_64 architecture) and Arm processors (aarch64 architecture) have been benchmarked. For the workloads in this study, the mean performance with the AMD CPU is 62% higher than with Arm and 42% higher than with Intel. The AMD processor seems particularly suited resulting in an overall shorter time-to-solution.
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    Local bilinear computation of Jacobi sets
    (2022) Klötzl, Daniel; Krake, Tim; Zhou, Youjia; Hotz, Ingrid; Wang, Bei; Weiskopf, Daniel
    We propose a novel method for the computation of Jacobi sets in 2D domains. The Jacobi set is a topological descriptor based on Morse theory that captures gradient alignments among multiple scalar fields, which is useful for multi-field visualization. Previous Jacobi set computations use piecewise linear approximations on triangulations that result in discretization artifacts like zig-zag patterns. In this paper, we utilize a local bilinear method to obtain a more precise approximation of Jacobi sets by preserving the topology and improving the geometry. Consequently, zig-zag patterns on edges are avoided, resulting in a smoother Jacobi set representation. Our experiments show a better convergence with increasing resolution compared to the piecewise linear method. We utilize this advantage with an efficient local subdivision scheme. Finally, our approach is evaluated qualitatively and quantitatively in comparison with previous methods for different mesh resolutions and across a number of synthetic and real-world examples.
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    Investigations of metallurgical differences in AISI 347 and their influence on deformation and transformation behaviour and resulting fatigue life
    (2024) Veile, Georg; Regitz, Elen; Smaga, Marek; Weihe, Stefan; Beck, Tillmann
    Due to variations in chemical composition and production processes, homonymous austenitic stainless steels can differ significantly regarding their initial microstructure, metastability, and thus, their fatigue behavior. Microstructural investigations and fatigue tests have been performed in order to evaluate this aspect. Three different batches and production forms of nominally one type of steel AISI 347 were investigated under monotonic tensile tests and cyclic loading under total strain and stress control in low and high cycle fatigue regimes, respectively. The deformation induced α’-martensite formation was investigated globally by means of in situ magnetic measurements and locally using optical light microscopy of color etching of micrographs. The investigation showed that the chemical composition and the different production processes influence the material behavior. In fatigue tests, a higher metastability and thus a higher level of deformation induced α’-martensite pronounced cyclic hardening, resulting in significantly greater endurable stresses in total strain-controlled tests and an increase in fatigue life in stress-controlled tests. For applications of non-destructive-testing, detailed knowledge of a component’s metastability is required. In less metastable batches and for lower stress levels, α’-martensite primarily formed at the plasticization zone of a crack. Furthermore, the formation and nucleation points of α’-martensite were highly dependent on grain size and the presence of δ-ferrite. This study provides valuable insights into the different material behavior of three different batches with the same designation, i.e., AISI 347, due to different manufacturing processes and differences in the chemical composition, metastability, and microstructure.
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    Hagrid : using Hilbert and Gosper curves to gridify scatterplots
    (2022) Cutura, Rene; Morariu, Cristina; Cheng, Zhanglin; Wang, Yunhai; Weiskopf, Daniel; Sedlmair, Michael
    A common enhancement of scatterplots represents points as small multiples, glyphs, or thumbnail images. As this encoding often results in overlaps, a general strategy is to alter the position of the data points, for instance, to a grid-like structure. Previous approaches rely on solving expensive optimization problems or on dividing the space that alter the global structure of the scatterplot. To find a good balance between efficiency and neighborhood and layout preservation, we propose Hagrid , a technique that uses space-filling curves (SFCs) to “gridify” a scatterplot without employing expensive collision detection and handling mechanisms. Using SFCs ensures that the points are plotted close to their original position, retaining approximately the same global structure. The resulting scatterplot is mapped onto a rectangular or hexagonal grid, using Hilbert and Gosper curves. We discuss and evaluate the theoretic runtime of our approach and quantitatively compare our approach to three state-of-the-art gridifying approaches, DGrid , Small multiples with gaps SMWG , and CorrelatedMultiples CMDS , in an evaluation comprising 339 scatterplots. Here, we compute several quality measures for neighborhood preservation together with an analysis of the actual runtimes. The main results show that, compared to the best other technique, Hagrid is faster by a factor of four, while achieving similar or even better quality of the gridified layout. Due to its computational efficiency, our approach also allows novel applications of gridifying approaches in interactive settings, such as removing local overlap upon hovering over a scatterplot.
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    Soya yield prediction on a within-field scale using machine learning models trained on Sentinel-2 and soil data
    (2022) Pejak, Branislav; Lugonja, Predrag; Antić, Aleksandar; Panić, Marko; Pandžić, Miloš; Alexakis, Emmanouil; Mavrepis, Philip; Zhou, Naweiluo; Marko, Oskar; Crnojević, Vladimir
    Agriculture is the backbone and the main sector of the industry for many countries in the world. Assessing crop yields is key to optimising on-field decisions and defining sustainable agricultural strategies. Remote sensing applications have greatly enhanced our ability to monitor and manage farming operation. The main objective of this research was to evaluate machine learning system for within-field soya yield prediction trained on Sentinel-2 multispectral images and soil parameters. Multispectral images used in the study came from ESA’s Sentinel-2 satellites. A total of 3 cloud-free Sentinel-2 multispectral images per year from specific periods of vegetation were used to obtain the time-series necessary for crop yield prediction. Yield monitor data were collected in three crop seasons (2018, 2019 and 2020) from a number of farms located in Upper Austria. The ground-truth database consisted of information about the location of the fields and crop yield monitor data on 411 ha of farmland. A novel method, namely the Polygon-Pixel Interpolation, for optimal fitting yield monitor data with satellite images is introduced. Several machine learning algorithms, such as Multiple Linear Regression, Support Vector Machine, eXtreme Gradient Boosting, Stochastic Gradient Descent and Random Forest, were compared for their performance in soya yield prediction. Among the tested machine learning algorithms, Stochastic Gradient Descent regression model performed better than the others, with a mean absolute error of 4.36 kg/pixel (0.436 t/ha) and a correlation coefficient of 0.83%.
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    Can a hand-held 3D scanner capture temperature-induced strain of mortar samples : comparison between experimental measurements and numerical simulations
    (2023) Haynack, Alexander; Zadran, Sekandar; Timothy, Jithender J.; Gambarelli, Serena; Kränkel, Thomas; Thiel, Charlotte; Ožbolt, Joško; Gehlen, Christoph
    The expected lifespan of cement-based materials, particularly concrete, is at least 50 years. Changes in the pore structure of the material need to be considered due to external influences and associated transport processes. The expansion behaviour of concrete and mortar during freeze-thaw attacks, combined with de-icing salt agents, is crucial for both internal and external damage. It is essential to determine and simulate the expansion behaviour of these materials in the laboratory, as well as detect the slow, long-term expansion in real structures. This study measures the expansion of mortar samples during freeze-thaw loading using a high-resolution hand-held 3D laser scanner. The specimens are prepared with fully or partially saturated pore structures through water storage or drying. During freeze-thaw experiments, the specimens are exposed to pure water or a 3% sodium chloride solution (NaCl). Results show contraction during freezing and subsequent expansion during thawing. Both test solutions exhibit similar expansion behaviour, with differences primarily due to saturation levels. Further investigations are required to explore the changing expansion behaviour caused by increasing microcracking resulting from continuous freeze-thaw cycles. A numerical analysis using a 3D coupled hygro-thermo-mechanical (HTM) model is conducted to examine the freeze–thaw behaviour of the mortar. The model accurately represents the freezing deformation during the freeze–thaw cycle.
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    Visual analytics for nonlinear programming in robot motion planning
    (2022) Hägele, David; Abdelaal, Moataz; Oguz, Ozgur S.; Toussaint, Marc; Weiskopf, Daniel
    Nonlinear programming is a complex methodology where a problem is mathematically expressed in terms of optimality while imposing constraints on feasibility. Such problems are formulated by humans and solved by optimization algorithms. We support domain experts in their challenging tasks of understanding and troubleshooting optimization runs of intricate and high-dimensional nonlinear programs through a visual analytics system. The system was designed for our collaborators’ robot motion planning problems, but is domain agnostic in most parts of the visualizations. It allows for an exploration of the iterative solving process of a nonlinear program through several linked views of the computational process. We give insights into this design study, demonstrate our system for selected real-world cases, and discuss the extension of visualization and visual analytics methods for nonlinear programming.