Philippe Cerfontaine

Towards a Flexible and Distributed Simulation Platform

This work is focused on bringing forth integrated simulation as a means to understand complex processes more thoroughly. Production processes that arise in the field of engineering sciences usually require expertise and knowledge from various fields and areas to be fully understood. These processes typically range across different domains, like material science and manufacturing for instance, while they also share various technical and economic aspects. Simulation already plays an important part in conceiving such processes and its role is likely to increase in the future. As simulation technology progresses and calculations provide more accurate predictions of real phenomena, the need for more and more intuitive ways to analyze and represent the resulting information also increases. In the context of continuous process chains it is important to focus on the links between the distinct processing stages, and to demonstrate the influence and interdependencies between them. Virtual Reality (VR) provides the necessary means and technology to visualize and understand the complete process.

Automatic Multi-Camera Setup Optimization for Optical Tracking

We propose a method to determine the optimal camera alignment for a tracking system with multiple cameras by specifying the volume to be tracked and an initial camera setup. We use optimization strategies based on methods usually employed for solving nonlinear systems of equations. All approaches are fully automatic and take advantage of modern graphics hardware since we also implement a GPU-based, accelerated visibility test. The algorithm automatically optimizes the whole setup by adjusting the given set of camera parameters. We can steer the optimization towards different goals depending on the desired application, e.g. the widest possible volume coverage or maximum camera visibility to overcome heavy occlusion problems during the tracking process. We also consider parameter constraints that the user may specify according to restrictions in the local environment where the cameras have to be mounted. This allows for a convenient definition of higher level constraints for the camera setup.

Enterprise Application Integration for Virtual Production

The focus of this work is to promote the adoption of Enterprise Application Integration (EAI) as a framework for virtual production. The product planning phase in real and virtual production usually requires a huge range of various applications that are used by different departments of a company. To increase productivity on the one hand and reduce complexity of application integration on the other hand, it is essential to be able to interconnect the differing syntax, structure and semantics of the distributed applications. The presented EAI framework will be used in the production planning process of a Line-Pipe as a use case. The successful application interconnection in this use case is used to validate the framework.

Enterprise Application Integration für die virtuelle Produktion

Moglichst prazise und detailliert virtuell abzubilden, wie aus unterschiedlichsten Rohstoffen ein fertiges Produkt hergestellt wird, ist das Ziel des Produktplanungsprozesses. Um ihn ganzheitlich anzulegen, mussen viele verschiedene Faktoren beachtet werden. So muss das Wissen von Experten unterschiedlicher Disziplinen zusammengebracht werden und der Prozess selbst muss dynamisch und flexibel angelegt sein, um an wechselnde Anforderungen adaptiert werden zu konnen. Da im Produktplanungsprozess viele heterogene und als Insellosungen entwickelte Softwarewerkzeuge eingesetzt werden, die jedoch lediglich Teile der Produktion vorab virtualisieren, ist es fur eine durchgangige Darstellung des Prozesses notwendig, diese zu verbinden, um langfristig wettbewerbsfahige Produkte zu planen und herzustellen. Am Beispiel des Herstellungsprozesses eines Stahlrohrs fur eine Pipeline wird deutlich, wo die Probleme bei einer durchgangigen Abbildung liegen. So mussen z. B. Veranderungen der Form eines Bauteils mit Veranderungen in der Werkstoffstruktur in Verbindung gebracht werden. Dies kann mit Hilfe der Enterprise Application Integration (EAI) erfolgen. In diesem Beitrag wird ein auf EAI basierendes Datenintegrationswerkzeug vorgestellt, das die Verknupfung heterogener Simulationen ermoglicht.

Interactive Simulation Data Exploration in Virtual Environments

In the last few years, simulation of technical and physical processes has become an important pillar in engineering. Computational Engineering Science (CES) is nowadays an indispensable and essential tool for the development of, e.g., airplanes, cars, combustion engines, turbines etc. In this work, we present a framework that tackles the growing complexity of these simulations. For simulations of highly complex processes, we enable interactive exploration in 3D space by application of Virtual Reality (VR) technology. For simulation data that is only a part of a complete process simulation, we propose methods that facilitate data analysis within the global context of an interdisciplinary project. By considering a single simulation as well as its part in a larger context, this framework enables engineers to explore their data on multiple scales of complexity.

Immersive Visualization for Integrated Process Simulation

In this work we present a system that enables flexible coupling of distributed simulations as well as an immersive visualization solution for connected simulation results. Using this technology allows us to simulate entire production process chains, considering the various aspects at once rather than examining them separately one by one. The simulation experts that are involved get the opportunity to discuss and analyze their results inside a greater context with all the other experts. This is meant to further a scientific examination of the complete simulated process chain as an integral result. The post processing and visualization both rely on a concept that allows for the seamless integration of the expertly crafted individual visualizations, while still guaranteeing stable and interactive frame rates required in virtual environments. Using level of detail management,as well as selective refinement, the user(s) will be able to identify and mark important phenomena occurring within a certain space and time area of the simulation data with the so called widgets. Those can then be linked to other widgets and phenomena that provide an explanation. Using annotation techniques causal, relation based visualization combines the simulation data, its representation, and the explanations required to understand them.

3D-representation of phase and property diagrams in multi-component systems

Abstract This paper shows the potential of three-dimensional diagrams, using up-to-date computer graphics techniques. In contrast to the past perspective diagrams can now be generated from quantitative calculations of phase equilibria for systems with any number of components. These diagrams can even be made quantitatively readable. Furthermore new visualisation techniques from the field of virtual reality are used to make the complex data easier to understand.

Camera setup optimization for optical tracking in virtual environments

In this paper we present a method for finding the optimal camera alignment for a tracking system with multiple cameras, by specifying the volume that should be tracked and an initial camera setup. The approach we use is twofold: on the one hand, we use a rather simple gradient based steepest descent method and on the other hand, we also implement a simulated annealing algorithm that features guaranteed optimality assertions. Both approaches are fully automatic and take advantage of modern graphics hardware since we implemented a GPU-based accelerated visibility test. The proposed algorithms can automatically optimize the whole camera setup by adjusting the given set of parameters. The optimization may have different goals depending on the desired application, e.g. one may wish to optimize towards the widest possible coverage of the specified volume, while others would prefer to maximize the number of cameras seeing a certain area to overcome heavy occlusion problems during the tracking process. Our approach also considers parameter constraints that the user may specify according to the local environment where the cameras have to be set up. This makes it possible to simply formulate higher level constraints e.g. all cameras have a vertical up vector. It individually adapts the optimization to the given situation and also asserts the feasibility of the algorithms output.