Abstract

Abstract
Within the development of motor vehicles, crash safety (e.g. occupant protection, pedestrian protection, low speed damageability), is one of the most important attributes. In order to be able to fulfill the increased requirements in the framework of shorter cycle times and rising pressure to reduce costs, car manufacturers keep intensifying the use of virtual development tools such as those in the domain of Computer Aided Engineering (CAE). For crash simulations, the explicit finite element method (FEM) is applied. The accuracy of the simulation process is highly dependent on the accuracy of the simulation model, including the midplane mesh. One of the roughest approximations typically made is the actual part thickness which, in reality, can vary locally. However, almost always a constant thickness value is defined throughout the entire part due to complexity reasons. On the other hand, for precise fracture analysis within FEM, the correct thickness consideration is one key enabler. hus, availability of per element thickness information, which does not exist explicitly in the FEM model, can significantly contribute to an improved crash simulation quality, especially regarding fracture prediction. Even though the thickness is not explicitly available from the FEM model, it can be inferred from the original CAD geometric model through geometric calculations. This paper proposes and compares two thickness estimation algorithms based on ray tracing and nearest neighbour 3D range searches. A systematic quantitative analysis of the accuracy of both algorithms is presented, as well as a thorough identification of particular geometric arrangements under which their accuracy an be compared. These results enable the identification of each technique's weaknesses and hint towards a new, integrated, approach to the problem that linearly combines the estimates produced by each algorithm.

Abstract

Abstract
Publish/subscribe mechanisms for scalable event dissemination are a core component of many distributed systems ranging from Enterprise Application Integration middleware to news dissemination in the Internet. Hence, a lot of research has been done on overlay networks for efficient decentralized topic-based routing. Specifically, in gossip-based dissemination, bringing nodes with shared interests closer in the overlay makes dissemination more efficient. Unfortunately, this usually requires fully disclosing interests to nearby nodes and impacts reliability due to clustering. In this paper we address this by starting with multiple overlays, one for each topic subscribed, that then separately self-organize to maximize the number of shared physical links, thereby leading to reduced message traffic and maintenance overhead. This is achieved without disclosing a node's topic subscription to any node that isn't subscribed to the same topic and without impacting the robustness of the overlay. Besides presenting the overlay management protocol, we evaluate it using simulation in order to validate our results. © IPTPS 2010.All right reserved.

Abstract

Abstract
Unstructured peer-to-peer overlay networks are very resilient to churn and topology changes, while requiring little maintenance cost. Therefore, they are an infrastructure to build highly scalable large-scale services in dynamic networks. Typically, the overlay topology is defined by a peer sampling service that aims at maintaining, in each process, a random partial view of peers in the system. The resulting random unstructured topology is suboptimal when a specific performance metric is considered. On the other hand, structured approaches (for instance, a spanning tree) may optimize a given target performance metric but are highly fragile. In fact, the cost for maintaining structures with strong constraints may easily become prohibitive in highly dynamic networks. This chapter discusses different techniques that aim at combining the advantages of unstructured and structured networks. Namely we focus on two distinct approaches, one based on optimizing the overlay and another based on optimizing the gossip mechanism itself. © 2010 Springer Science+Business Media, LLC.