The Computer Graphics and HCI Group is member of
Current projectsCompleted projects
Project partner: Volkswagen AG
Project Partner: Fraunhofer IESE
The project MMV is composed of three research topics: fiber dynamics and fiber laydown, droplet population dynamics, and simulated room acoustics.
This project addresses the problems of sequential CFD work-flows by introducing online monitoring and computational steering concepts into existing CFD systems. The focus is on application-dependent visualization methods needed to provide sufficient information about ongoing simulations and their quality.
Intuitive Multi-Touch-Interaction provides an effective and efficient support of users so that even complex representations may be individualized and explored in an intuitive and context-specific manner. The central goal is the development of an framework, which allows the application to choose from a variety of multi-touch gestures, while abstracting from the underlying hardware-specific multi-touch framework. MULTI is funded by "Stiftung Rheinland-Pfalz für Innovation".
GeoDict generates and operates on 3D geometric material models and requires the visualization of these models as well as that of computed scalar, vectorial and tensorial fields, such as temperature distributions, flow fields, displacement fields, etc. The objective of this project is to develop a highly time- and memory-efficient pde-solver that is compatible with GeoDicts voxelized structure and solution representation. This project is realized in cooperation with Fraunhofer ITWM and AG Computergrafik and HCI.
The project deals with the augmentation of safety and reliability of technical systems. The methods and technologies being developed are both application-specific and cross-application. The objective of this integration is to transfer methodic knowledge into the application area and to generalize these methods.
Heart vessel diseases, as atherosclerosis are one of the leading cause of death in modern society. Lots of research focusses on the early and fast detection of these diseases. CT scans are a wide used diagnosis method to review the entire heart system. Unfortunately an early detection of heart vessel anomalies on CT scans is often not possible as its resolution is low and contains several image errors. In this project we aim to enhance CT scans in a way that medical researchers are able to detect diseases earlier, more accurate and trustworthy by extracting features from CT scans, simulating blood flow and visually provide our medical coworkers with tools to examine CT scans in a more efficient way. This project is proceeded as a collaboration with the Wright State University, Dayton (OH).
This Project is proceeded as a collaboration with UC Davis (CA) and is part of the IRTG 2057 - "Physical Modeling for Virtual Manufacturing Systems and Processes". In this research project, we propose to develop and evaluate human-centered visualization and interaction techniques that scale both with the level of the transaction to be considered and with the used devices with the expected result of a Human-centered virtual production environment achieved by the development of a highly scalable visualization/interaction framework, focusing on the cross product of visualization, interaction and collaboration.
In recent times, visual analysis has become increasingly important, especially in the area of software measurement, as most of the data from software measurement is multivariate. In this regard, standard software analysis tools are limited by their lack of ability to process huge collections of multidimensional data sets; current tools are designed to either support only well-known metrics, are too complicated to use for generating custom software metrics, or have limited software visualization capabilities. Furthermore, the analyst requires extensive knowledge of the underlying data schemas and the relevant querying language. To address these shortcomings, we propose an interactive visual workflow modeling approach that focuses on visual elements, their configurations, and inter-connectivity rather than a data ontology and querying language. Importantly, in terms of software comprehension we provide a tighter integration between 'software analysis' and 'software visualization' in order to provide an integrated means to specify and visualize software measurements.
In the field of technical textiles (nonwovens, glass wool, ...), fibers and filaments of different materials are produced and processed. Simulations allow trying out modifications to these processes and running experiments at reduced cost, before implementing them in the real world. During the production, the fibers are subject to forces determining their dynamics. In order to simulate such processes, the dynamics of the fibers need to be modeled. One of the challenges for the simulation is to model the interaction of fibers with machine parts. When a collision of a fiber with the machine geometry is detected, its dynamics equation has to be expanded by geometric constraints to prevent penetration. The time step is then recomputed including appropriate contact forces resulting from the constraints. The picture shows the simulation of a filament in air flow for a spunbond line of Oerlikon Neumag, computations performed by Fraunhofer ITWM.
In car manufacturing and prototyping, quality control plays an important role. While this was done mostly by tactile measurements, using robots, there is a supposed paradigm change towards optical measurements via stereoscopic cameras or similar devices. The aim of our project is to efficiently store, evaluate and visualize this new type of measurement data and integrate it into Kronion’s widely used eMMA software suite. Funding by: Zentrales Innovationsprogramm Mittelstand (ZIM). Kooperationsprojekt zwischen Steinbichler Optotechnik GmbH, Hochschule Rhein-Main, Kronion GmbH, Universität Kaiserslautern.
Collaborators: Los Alamos National Laboratories, UC Davis In today's large scale simulations we encounter limitations due to storage capacity or bandwidth. Additionally, data triage becomes more and more difficult, as the data sets grow in size. As a consequence we need to filter out relevant parts of the data. Basing on a recently published quad tree based method, we present a novel approach, where we use a Voronoi tree to store approximately the same amount of relevant data in each cell. As a result, large cells cover less interesting data and small cells contain the most important data, which will allow us efficient data reduction or highlighting.
In the dawn of the fourth industrial revolution, we investigate how advanced measurement and simulation techniques can be used to optimize design decisions in manufacturing and construction. These techniques provide data in the form of unstructured samples of multivariate functions or fields, which have to be processed and represented visually in order to provide analysis of the design's performance. In this project, we contribute novel means to steer simulations, explore high-dimensional parameter spaces, and to find optimal design decisions for manufacturing and construction. Our scalar- and vector field processing techniques contribute to scattered field processing in general and introduce novel ways of analyzing and processing temporal, spatial, and semantical relationships within high-dimensional parameter spaces, thus providing insights into field topology and simulation boundary conditions. Other collaborator's include: - Molecular Biophysics, Department of Biology, TU Kaiserslautern - Police Department, Kaiserslautern
The goal of this project on a software engineering and development level is the development of an adaptable and scalable modeling platform, which includes changeable target functions and basic conditions like demographic development, water usage and energy consumption. Therefore, many user studies for understanding the user`s needs are necessary and have to be performed. In addition, an overall system has to be designed which includes the communication between different modules from different research institutes. Furthermore, scalable visualizations and intuitive interaction techniques have to be developed for serving different user groups, operation systems and devices.
Numerical simulation of the magnetic field generation of the Earth (the geodynamo), other planets, and the sun, presents an enormous computational and visualization challenges. Simulations of the physical system that generates the magnetic field, the geodynamo, is being developed and carried out on some of the world’s fastest computers, requiring massively parallel computing to carry out long-duration simulations at sufficiently high resolution. The geodynamo represents a major visualization challenge, as the output consists of time-varying vector and scalar fields representing turbulent convection in the Earth’s core and the coupled magnetic field generated by that flow. The number of fields to be studied, the resolution required, and the long-time series makes extraction of features very challenging; moreover, the observation used to compare against simulations is the magnetic field at and above the Earth’s surface far from the computational domain of the simulations. Effective and specialized analysis and visualization systems capable of allowing a geophysicist to truly comprehend a simulated data set in its entirety and derive the relevant, hidden scientific insight are still missing. Our research effort is motivated by this fact, and the members of interdisciplinary constituting this effort jointly specified the design objectives of the magnetic field system presented here. Specifically, the Earth’s magnetic field exhibits highly turbulent behavior in the Earth’s interior, leading to simulated magnetic fields to highly intricate and hard-to-comprehend flow behavior and patterns. Contact: Patrick Rüdiger
Virtual Environments are proposing new challenges when it comes to collaboration and communication. While manufacturing and factory planning was organized in clearly separated departments over the last decade, the upcoming virtualization disrupted the concept of this organizational structure and demands for more communication over all levels. A lot of efforts have been made through the recent development of VR and AR technologies. So far the majority of these techniques is investigated technically in terms of efficiency etc. If human factors are investigated the majority of the results still is qualitatively. The application of scientific results from the visualization therefor is mainly happening on the data, but not on the communication of humans in the process. The increasing amount of data processed and the heterogeneous group of people with different background knowledge dealing with and cooperating in this new environment is the challenge we want to further investigate. In order to tackle the challenge of incorporating the diverse group of users, we need to understand how the background knowledge and the human factors itself affects the information perceived through visualizations and virtual environments. This can be achieved with the help from the cognitive science, where measurements such as cognitive load, bias and entropy are well studied and allow conclusions about how humans react on various stimuli (such as visual or auditory). Based on these insights visualization and interaction techniques can be evaluated and optimized for the special needs of a general composed user group. In order to perform these experiments a solid framework is needed, which also serves the purpose of a virtual manufacturing dashboard. The goal is a general scientifically evident experimental framework allowing the quantification of visualizations based on their human factors and thus making a big step forward in understanding the preservation of entropy through the communication via virtual environments. Furthermore, we expect a deeper understanding on how humans perceive, interact and transform information in a virtual cooperative environment and thus enabling more potential from the virtualization.