In this study, a Decision Support System methodology for a transformation of existing centralized Urban Water Systems to decentralized water management is proposed. A study area in Germany is composed of Otterbach, Winnweiler, Weilerbach, Rockenhausen, Meisenheim, Wolfstein, Altenglan, Alsenz, and Lauterecken. This area is served by a single groundwater well located at Kaiserslautern. Current performance of the study area is analyzed by using EPANET software.
The main goal of the our research topic is to provide a virtual reality platform helping in analyzing the safety aspects of the embedded systems. The research should provide a technique to integrate between the multi views of the embedded system parts. The hardware and the software parts. The provided prototype should be easily integrated into different 3d platform such as the PowerWall, the CAVE system and the Desktop 3d display. The research is a part of a big joint project called Vier4Es2.
Surface prototyping generates a so-called masterpiece of a new product. Usually, these masterpieces are very similar to the final product, so only small modifications are supposed to be made. We present a linear deformation technique for this kind of modifications, preserving the total curvature of the masterpiece.
We introduce a novel multi-dimensional domain decomposition method. A new type of tree combines the advantages of the octree and the KD-tree without having their disadvantages. The tree's data structure is dened by a topological algebra based on the symbols A = fL; I;Rg that encode the decomposition steps. The set of successors is restricted such that each cell has the partition of unity property to decompose domains with- out overlap. The data structure allows local renement, parallelization and proper restriction of transition ratios between cells. The concept of virtual trees enables us to describe data-consistent algorithms. The Lane- Riesenfeld algorithm applied to the virtual tree provides a C2k
Scientific visualization of large-scale vector fields with integration-based methods that rely on the analysis of particle trajectories is not feasible with current methods, since existing algorithms cannot make efficient use of parallel architectures such as clusters and supercomputers. This project aims at developing a novel methodological framework for integration-based visualization that will provide visualization of largest-scale vector fields in current scientific application. The proposed methodology will allow researchers in science and industry to visualize, analyze and understand the processes described by large vector field data from simulation or measurement. The project is funded in the form of a EU FP7 Marie Curie People Career Integration Grant.
Contemporary simulation and experimental data acquisition enable scientists to gather progressively larger and inherently more complex (multivariate) data. Working closely with application scientists and engineers, this thesis thrives to identify core features that can be utilized to abstract, classify, and visualize multivariate data. This research aims to amalgamate domain expertise from key disciplines such as statistics, machine learning, data mining, and visualization; to develop fundamental mathematical foundations that are required to support interactive visual data exploration, the first and foremost step in data analysis to date.
This work aims to investigate the suitability of applying Virtual Reality techniques in the exploration of Mars terrain features in order to support the creation of topographic maps of the planet. Traditionally, these tasks are performed using Geo-Information-Systems (GIS) on Desktop Workstations, using a two-dimensional projection of the collected data as the basis on which an operator performs manual feature extraction. After identifying features and characterizing them quantitatively using measurement operators, they are ultimately represented visually by so called geo-objects. Within the scope of this project, a system will be developed which enables this workflow to happen entirely within a VR-environment, using appropriate navigation and interaction metaphors. The main goal of the project is to investigate whether the more natural immersion in the VR-environment can help to improve the identification and spatial analysis of surface features.
Modern science utilizes advanced measurement and simulation techniques to analyze phenomena from fields such as medicine, physics, or mechanics. The data produced by application of these techniques takes the form of multi-dimensional functions or fields, which have to be processed and represented visually in order to provide meaningful parts of the data to domain experts. In this thesis, we contribute novel feature extraction and visualization techniques that are able to convey data from multiple fields created by scientific simulations or measurements. Our scalar-, vector-, and tensor field processing techniques contribute to scattered field processing in general and introduce novel ways of analyzing and processing tensorial quantities such as strain and displacement in flow fields, providing insights into field topology and general continuum mechanics.
The thesis "visualization methods for sustainable planning" provides both new approaches for measuring and monitoring two indicators of sustainability - urban sprawl and carbon footprints - as well as three-dimensional representations of those indicator results. Second it presents an alternative approach in measuring and visualizing both indicators by utilizing a Neighborhood Relation Diagram (NRD), based on weighted Voronoi diagrams.
Safety is a very important property of embedded systems, to avoid human injury or negative impact on the environment during the system usage. In this work a visualization system is developed to address the most important concepts of Minimal Cut Set Analysis. Additionally, the visualization and interaction gaps, needs, and the tasks performed in MCS analysis are studied and analysed in order to enhance the work of the safety analysts and ease the communication between the safety analysts and the system’s developers and be able to exchange their knowledge.
Matrix visualizations of graphs are attracting widespread interest in fields such as social networks, security visualization, bio-chemistry, or software engineering. In software engineering, matrix visualization plays an important role in showing the static structure of the software system. This static structure is used for a large variety of tasks, e.g., system design, detailed design, or reverse engineering. Especially, supporting reverse engineering of legacy systems is an important task, as many systems need to be extended even after the main developers are no longer available. As the matrix visualization provides a scalable and space efficient visualization of software architectures, it is particularly well suited to support these tasks.
Applying binder to glass wool or for refinement of filaments fibers are sprinkled with a liquid in an air flow. The liquid is injected into the air flow as droplets. In this process, collisions of droplets and fibers occur. This project aims at providing an adequate mathematical description of the process. Due to the complexity of the problem we use stochastic methods for our simulations.
In the field of technical textiles like nonwovens and glass wool, fibers and filaments of different materials are produced and processed. During the production, these fibers are subject to forces determining their dynamics. In order to simulate such processes, the dynamics of the fibers needs to be modeled. Important challenges for the simulation of technical processes include the interaction of fibers with air flow (exerting stochastic forces), machine parts (constraining forces) and other fibers (coupled constraining forces).
Electrical Impedance Tomography (EIT) is an imaging technique used for mechanical ventilation with a low spatial resolution that shows conductivity changes relative to a reference baseline. Its accuracy and quality crucially depend on the body model that is used for image reconstruction. This thesis aims at improving the interpretability of EIT images by providing an individualized body model and anatomical context for image regions. Our contributions include an interactive segmentation workflow for thoracic CT data (to generate the body models), image reconstruction using the improved model (to improve image quality), landmark detection and registration in both EIT and CT data (to create anatomical context), and studying the interpretability of these images.
The purpose of this doctoral thesis is on the one hand to describe and examine the development of inner city retail locations against the background of the booming online shopping. On the other hand, strategies for the cities that help to qualify inner city retail locations for the new demands should be formulated. In order to achieve these goals the great mutual importance of inner cities and stationary retail, online shopping as a new trend, the effects of the increased use of internet and online shopping on consumer behavior as well as the spatial consequences for the inner city retail and its locations will be described.
In this dissertation, a high-resolution parameterization of complex urban geometries is created and used for microscale numerical modeling of aerosol and moisture distribution within and above the Urban Canopy Layer (UCL). In order to trace the dispersion of these precipitation-relevant elements, a multilayer canopy model is implemented inside a digital representation of a city with a non-homogenous canopy- and surface configuration, simulating microscale heat and moisture fluxes as well as flow regimes. In a third step, an adequate abstraction of the complex urban geometries is derived that is still able to represent the processes in an adequate way, but more efficient regarding computational resources. This representation shall be applicable in mesoscale meteorological models in order to obtain a higher accuracy in terms of the prediction of precipitation patterns.
As Large Displays, such as Tiled Walls or Projector Displays, become more and more common in collaborative environments, a need for new interaction techniques suited for these environments arises. Mobile Devices, especially Smart Phones and tablets, are very powerful devices with capabilities that make them interesting as a universal input device. These capabilities include WiFi, accelerometers, (Multi-) touchscreens, cameras and more. This project investigates new ways of using those devices to interact with Large Displays.
The focus of this research project is to utilize revolutionary ideas in the area of interactive exploratory visualization and to apply these modern techniques in the context of software architecture maintenance and evolution.
Service-oriented came from the business world. As such they don't have a strong theoretic basis. This work tries to define that basis.
This dissertation project consists of two parts: the first part deals with moment invariants and their applications, the second part deals with collaborations with industry and with other fields of academia. In the first part, it is studied how moments are defined how you can compute invariants of them, how you compute the in an optimized manner using tensor hypergraphs, and how to apply them. In the second part different visualization projects were implemented: the first project is an architectural project that deals with the three-dimensional visualization and printing of land-use plans together with example buildings and the visualization of the violations of the regulations given in a land-use-plan. The second project is a system that helps to collect ideas quickly, rate them collectively using an organization's special needs and visualize the ratings. The third project deals with the re-design of a renderer for coordinate measurement data of construction parts together with errors.
Distributed production and global activities make it difficult for companies to collaborate with co-workers, employees, and shareholders all over the world. But, vbisualization is one of the most important mediums for human communi- cation and interaction. The research focuses on a concept for factory planning within the Virtual Reality for spatially distributed users. The aim is a collaboration tool for factory planning that supports different visualization methods.
Our research is situated in the field of photorealistic 3D reconstruction. We are developing a new scanning device together with algorithms for capturing shape, color and reflectance properties of objects. A major goal of this project is a high quality of the reconstructions. Key for a faithful reconstruction is the precise capturing of shape and appearance.
Our research is situated in the field of photorealistic 3D reconstruction. We are developing a new scanning device together with algorithms for capturing shape, color and reflectance properties of objects. A major goal of this project is, besides a high quality of the reconstructions, automation. We thus investigate methods for automatic calibration of projectors, cameras and light sources and outlier removal.
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.
Computational Fluid Dynamics (CFD) became a powerful analysis tool and is important in many application domains. With increasing capabilities of high-performance computing resources very detailed numerical analysis can be supported. However, one of the problems of existing CFD solutions is their sequential work-flow requiring for many executions until a simulation was successful. This thesis addresses the problems of sequential CFD work-flows by introducing online monitoring and computational steering concepts in order to judge the state of an ongoing simulation and change simulation at runtime. To analyze the ever increasing simulation results, interactive exploration will be a key concept in this thesis.
Due to remarkable technological advances in the last three decades the capacity of computer systems has improved tremendously. Considering Moore's law, the number of transistors on integrated circuits has doubled approximately every two years and the trend is continuing. Likewise, developments in storage density, network bandwidth, and compute capacity show similar patterns. As a consequence, the amount of data that can be processed by today's systems has increased by orders of magnitude. At the same time, however, the resolution of screens has hardly increased by a factor of ten.
In reverse engineering and computer aided design (CAD) applications point cloud data is usually manually scanned, reconstructed, and post-processed in separated steps. Thus, if the scanned data is insufficient for the reconstruction, the complete scanning process has to be repeated or the reconstruction fails. On-line reconstruction of 3d geometry allows one to generate and update a CAD reconstruction on-line during the scanning process with an hand-held laser scanner. Thus, regions where the scanned data is insufficient for the reconstruction are detected on the fly to allow an immediate correction and improvement of the scanned data. This enables the human operator to focus on critical regions in the scanned data to improve the reconstruction quality.
Modern scanning devices that allow a high quality and large scale acquisition of complex real world models often deliver a large set of points as resulting data structure of the scanned surface. A direct triangulation of those point clouds does not always result in good models. So it is suitable to stay a little longer in the point based world to analyze the point cloud data with respect to such features and apply a surface reconstruction method afterwards that is known to construct continuous and smooth surfaces and extend it to reconstruct sharp features. The thesis presents such a method and additional algorithms for analysis, surface reconstruction and also combination of designed and scanned data.
The research is aimed at developing a suitable visual collaboration method for Information Visualization and Visual Analytics tasks with or without using large display technology. Initially, the state-of-the-art is established in the field of Collaborative Visualization and relevant topics in Information Visualization, Human-Computer Interaction and Computer-Supported Collaborative Work. After a thorough analysis of the gathered information, a novel visualization method is devised, one that fosters the advantages of collaborative work and at the same time offers support for gaining insight as a result of team effort. Further, a visualization tool is implemented to highlight the proposed research and its feasibility.
This research work focuses on the generation of a high resolution digital surface model featuring complex urban surface characteristics in an attempt to improve the overall hydraulic capacity of the urban drainage systems. High resolution surface data describing hydrologic and hydraulic properties of complex urban areas is the prerequisite to more accurately describing and simulating the flood water movement and thereby taking adequate measures against urban flooding. Airborne LiDAR (Light detection and ranging) is an efficient way of generating a high resolution digital surface model (DSM) of any study area. The processing of high-density and large volume of unstructured LiDAR data is a difficult and time-consuming task towards generating fine resolution spatial datasets when considering only human intervention. The application of robust algorithms in terms of processing this massive volume of data can significantly reduce the data processing time and thereby increase the degree of automation as well as accuracy.
The concepts of risk, uncertainty and resiliency have been in recent scientific discussions due to the increasing rates of unstructured growth in third world urban areas. Majority of areas at risk are high density urban networks with unplanned informal growth. Both visual computational steering of simulations using remote sensing as well as informal growth have been researched in the proposer's previous work. The idea of application of Remote Sensing to risk analysis and resiliency building is relatively new and would be explored by the researcher by means of taking case studies of various disasters for visualization and model development. The validity/accuracy of developed model(s) would then be tested against data from other disasters to analyze if the impacts determined by computational simulations match the real experienced impacts.
Point clouds generated by LiDaR (Light Detection and Ranging) scan devices and/or by reconstruction from two-dimensional (2D) image series represent discrete samples of real world objects. Depending on the type of scenery the resulting point cloud may exhibit a variety of different structures. Especially, in the case of environmental LiDaR scans the complexity of the corresponding point clouds is relatively high. Hence, finding new techniques allowing the efficient extraction and representation of the underlying structural entities becomes an important research issue. The thesis introduces new methods concerning the extraction and visualization of structural features like surfaces and curves (e.g. ridge-lines, creases) from 3D (environmental) point clouds.
Component fault tree (CFT) analysis is a safety analysis technique of embedded systems. To support the minimal cut set (MCS) analysis based on the CFTs, we propose a visualization approach that allows detailed data of the MCSs of interest to be viewed, while maintaining a satisfactory overview of a large-scale MCS dataset for pattern exploration. Engineers may intuitively analyze the influence of MCSs along the CFT structures. We also propose a visualization approach that supports to identify the vulnerable CFT com¬ponents regarding the hierarchies of system architecture and investigate the failure propagation of the important basic failures. Based on the identified important basic failures, a visual process is proposed that is aimed at identifying the optimal improvement solutions for the safety of a system.
Noise from machining processes influences employees’ healthy and it even causes serious diseases. It became one of the most frequent occupational hazards in manufacturing. This application investigates the noise issue in industry using a simulation as well as VR supported method. The visualization of simulation results in VR provides a new point of view to understand this issue and to fulfill the requirements of noise control/reduction during factory planning.