Visuelle Analyse großer Partikeldaten

Partikelsimulationen sind eine bewährte und weit verbreitete numerische Methode in der Forschung und Technik. Beispielsweise werden Partikelsimulationen zur Erforschung der Kraftstoffzerstäubung in Flugzeugturbinen eingesetzt. Auch die Entstehung des Universums wird durch die Simulation von dunkler Materiepartikeln untersucht. Die hierbei produzierten Datenmengen sind immens. So enthalten aktuelle Simulationen Billionen von Partikeln, die sich über die Zeit bewegen und miteinander interagieren. Die Visualisierung bietet ein großes Potenzial zur Exploration, Validation und Analyse wissenschaftlicher Datensätze sowie der zugrundeliegenden Modelle. Allerdings liegt der Fokus meist auf strukturierten Daten mit einer regulären Topologie. Im Gegensatz hierzu bewegen sich Partikel frei durch Raum und Zeit. Diese Betrachtungsweise ist aus der Physik als das lagrange Bezugssystem bekannt. Zwar können Partikel aus dem lagrangen in ein reguläres eulersches Bezugssystem, wie beispielsweise in ein uniformes Gitter, konvertiert werden. Dies ist bei einer großen Menge an Partikeln jedoch mit einem erheblichen Aufwand verbunden. Darüber hinaus führt diese Konversion meist zu einem Verlust der Präzision bei gleichzeitig erhöhtem Speicherverbrauch. Im Rahmen dieser Dissertation werde ich neue Visualisierungstechniken erforschen, welche speziell auf der lagrangen Sichtweise basieren. Diese ermöglichen eine effiziente und effektive visuelle Analyse großer Partikeldaten

Void-and-Cluster Sampling of Large Scattered Data and Trajectories

We propose a data reduction technique for scattered data based on statistical sampling. Our void-and-cluster sampling technique finds a representative subset that is optimally distributed in the spatial domain with respect to the blue noise property. In addition, it can adapt to a given density function, which we use to sample regions of high complexity in the multivariate value domain more densely. Moreover, our sampling technique implicitly defines an ordering on the samples that enables progressive data loading and a continuous level-of-detail representation. We extend our technique to sample time-dependent trajectories, for example pathlines in a time interval, using an efficient and iterative approach. Furthermore, we introduce a local and continuous error measure to quantify how well a set of samples represents the original dataset. We apply this error measure during sampling to guide the number of samples that are taken. Finally, we use this error measure and other quantities to evaluate the quality, performance, and scalability of our algorithm.Comment: To appear in IEEE Transactions on Visualization and Computer Graphics as a special issue from the proceedings of VIS 201

Stochastic Volume Rendering of Multi-Phase SPH Data

In this paper, we present a novel method for the direct volume rendering of large smoothed‐particle hydrodynamics (SPH) simulation data without transforming the unstructured data to an intermediate representation. By directly visualizing the unstructured particle data, we avoid long preprocessing times and large storage requirements. This enables the visualization of large, time‐dependent, and multivariate data both as a post‐process and in situ. To address the computational complexity, we introduce stochastic volume rendering that considers only a subset of particles at each step during ray marching. The sample probabilities for selecting this subset at each step are thereby determined both in a view‐dependent manner and based on the spatial complexity of the data. Our stochastic volume rendering enables us to scale continuously from a fast, interactive preview to a more accurate volume rendering at higher cost. Lastly, we discuss the visualization of free‐surface and multi‐phase flows by including a multi‐material model with volumetric and surface shading into the stochastic volume rendering

Social Innovations in the extended Lake Constance area – an overview of the current activities

In recent years the importance of social innovation for societies is rising. Therefore, the European Union realized, that political goals can be successfully achieved through social innovations.1 The concept is offering solutions for social challenges broadly based and in a variety of different fields Thus, the focus of this paper will be to identify social innovation activities in the Lake Constance area and the problems which are being solved through those activities. It will therefore provide a quantitative analysis of the identified projects including the main idea of the activity as well as information about the innovators. The key outcomes of this paper are, that social innovators are mainly focusing on current political challenges such as the refugee crisis. Problems which the society is already facing for a longer period of time, are less focused. It could further be identified, that the majority of social innovators are students or graduates. Also, most of the activities have their origin in bigger cities such as Stuttgart, Karlsruhe or Heidelberg

Analysis of the Relationship between Frugal Innovation and Sustainable Development

The relation between Frugal Innovation and Sustainability is a widely discussed topic in current academic literature. To assess the correlation between these two concepts, a sample of the most frequently mentioned Frugal Innovations was selected. The criteria to evaluate the sustainability potential for each of these cases was built upon the UN Sustainable Development Goals, a global reference indicator. Frugal Innovations among the banking, transport, energy, ICT, water, appliances and healthcare sectors were evaluated. The results suggested a positive contribution and impact of Frugal Innovations towards economic, social and environmental development

Analysis of the variation of the element types of properties and functions of technical systems in product development practice

In product development practice, it appears that engineering activities very often focus on the variation of the physical embodiment, as this is where the greatest and most obvious implications for the product seem to be perceived. Nevertheless, an empirical study revealed that variation in physical embodiment affects many other dimensions of a product, such as properties and functions. Within the scope of product specification, this requires a stronger differentiation of various dimensions of system elements. For this purpose, initial challenges and solution approaches in automotive product development practice are analyzed to gain a deeper understanding of the interrelationships of the variation of different types of system elements. The gathered findings and insights are then synthesized in a comprehensive systematic consisting of the structuring of elements of a new product generation or the reference system and an understanding of the set of elements in the Model of PGE – Product Generation Engineering. In summary, the differentiation of the variation types of the element types “property” and “function” is confirmed via the conducted case study. Further research should focus on supporting the product developer in identifying the alterations of the system elements by deriving the generic variation operator specifically onto the system elements of properties and functions of technical systems

The value of multimodality imaging for detection, characterisation and management of a wall adhering structure in the right atrium

The case presents a wall adherent structure in the right atrium in a young patient with peripheral tcell lymphoma followed by successful prolonged lysis therapy resulting in the resolution of the thrombus is presented. This case highlights the utility of multimodality imaging in an accurate assessment of the right atrium thrombus and the effectiveness of prolonged lysis therapy.peer-reviewe

Understanding the variation of physical elements and their impact on properties and functions: a case study on roll stabilization systems

This paper explores the variation in physical elements, functions, and properties of roll stabilization systems in automobiles over successive generations. Two key methodologies, Characteristics-Properties Modelling (CPM) / Property-Driven Development/Design (PDD) and the C&C²-Approach (Contact and Channel Approach), are utilized to analyze the attributes of the system elements and their functional correlations. Through detailed comparison of traditional roll stabilization subsystems and the active roll stabilization system, the research uncovers several correlations between variation types and system properties. The findings show the importance of attribute variation for understanding complex mechatronic systems. The research results may guide future planning of new product generations and foster innovative solutions in the early phases of product development