13 Zentrale Universitätseinrichtungen

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

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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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    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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    Visual analysis of droplet dynamics in large-scale multiphase spray simulations
    (2021) Heinemann, Moritz; Frey, Steffen; Tkachev, Gleb; Straub, Alexander; Sadlo, Filip; Ertl, Thomas
    We present a data-driven visual analysis approach for the in-depth exploration of large numbers of droplets. Understanding droplet dynamics in sprays is of interest across many scientific fields for both simulation scientists and engineers. In this paper, we analyze large-scale direct numerical simulation datasets of the two-phase flow of non-Newtonian jets. Our interactive visual analysis approach comprises various dedicated exploration modalities that are supplemented by directly linking to ParaView. This hybrid setup supports a detailed investigation of droplets, both in the spatial domain and in terms of physical quantities. Considering a large variety of extracted physical quantities for each droplet enables investigating different aspects of interest in our data. To get an overview of different types of characteristic behaviors, we cluster massive numbers of droplets to analyze different types of occurring behaviors via domain-specific pre-aggregation, as well as different methods and parameters. Extraordinary temporal patterns are of high interest, especially to investigate edge cases and detect potential simulation issues. For this, we use a neural network-based approach to predict the development of these physical quantities and identify irregularly advected droplets.
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    Fire rating of post-installed anchors and rebars
    (2020) Mahrenholtz, Philipp; Sharma, Akanshu
    Fire safety is a critical performance aspect of construction products, and post-installed anchors and rebars are no exemption in that regard. During their service life, anchors and rebars are subjected to different kinds of load actions, so they have to be qualified and designed for critical safety performance. While the qualification guidelines for static and seismic loading have matured to conclusive requirements over the past two decades, the requirements for determining the resistance to fire are just about to consolidate. This contribution strives to provide clarity on the fire rating of post-installed anchors and rebars. For this, the current status of the regulations, as well as the underlying background, is reviewed after a brief introduction. Typical examples of fire ratings in the field of post-installed anchors and rebars are given, and recent research undertaken to close the last regulative gaps is briefly presented.
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    A novel runtime algorithm for the real-time analysis and detection of unexpected changes in a real-size SHM network with quasi-distributed FBG sensors
    (2021) Sakiyama, Felipe Isamu H.; Lehmann, Frank; Garrecht, Harald
    The ability to track the structural condition of existing structures is one of the main concerns of bridge owners and operators. In the context of bridge maintenance programs, visual inspection predominates nowadays as the primary source of information. Yet, visual inspections alone are insufficient to satisfy the current needs for safety assessment. From this perspective, extensive research on structural health monitoring has been developed in recent decades. However, the transfer rate from laboratory experiments to real-case applications is still unsatisfactory. This paper addresses the main limitations that slow the deployment and the acceptance of real-size structural health monitoring systems (SHM) and presents a novel real-time analysis algorithm based on random variable correlation for condition monitoring. The proposed algorithm was designed to respond automatically to detect unexpected events, such as local structural failure, within a multitude of random dynamic loads. The results are part of a project on SHM, where a high sensor-count monitoring system based on long-gauge fiber Bragg grating sensors (LGFBG) was installed on a prestressed concrete bridge in Neckarsulm, Germany. The authors also present the data management system developed to handle a large amount of data, and demonstrate the results from one of the implemented post-processing methods, the principal component analysis (PCA). The results showed that the deployed SHM system successfully translates the massive raw data into meaningful information. The proposed real-time analysis algorithm delivers a reliable notification system that allows bridge managers to track unexpected events as a basis for decision-making.
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    Urban digital twins for smart cities and citizens : the case study of Herrenberg, Germany
    (2020) Dembski, Fabian; Wössner, Uwe; Letzgus, Mike; Ruddat, Michael; Yamu, Claudia
    Cities are complex systems connected to economic, ecological, and demographic conditions and change. They are also characterized by diverging perceptions and interests of citizens and stakeholders. Thus, in the arena of urban planning, we are in need of approaches that are able to cope not only with urban complexity but also allow for participatory and collaborative processes to empower citizens. This to create democratic cities. Connected to the field of smart cities and citizens, we present in this paper, the prototype of an urban digital twin for the 30,000-people town of Herrenberg in Germany. Urban digital twins are sophisticated data models allowing for collaborative processes. The herein presented prototype comprises (1) a 3D model of the built environment, (2) a street network model using the theory and method of space syntax, (3) an urban mobility simulation, (4) a wind flow simulation, and (5) a number of empirical quantitative and qualitative data using volunteered geographic information (VGI). In addition, the urban digital twin was implemented in a visualization platform for virtual reality and was presented to the general public during diverse public participatory processes, as well as in the framework of the “Morgenstadt Werkstatt” (Tomorrow’s Cities Workshop). The results of a survey indicated that this method and technology could significantly aid in participatory and collaborative processes. Further understanding of how urban digital twins support urban planners, urban designers, and the general public as a collaboration and communication tool and for decision support allows us to be more intentional when creating smart cities and sustainable cities with the help of digital twins. We conclude the paper with a discussion of the presented results and further research directions.
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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.