Contribution to the Energy Efficiency and Environmental Compatibility of Cranes for Inland Waterway/ Feeder Ship Handling

Basis for the economic efficiency of international supply chains rests on the efficiency of multimodal transport chains. Materials and products are transported along the edges of transport networks with the forwarder endeavouring to maximize the transport efficiency by using the effects of scale along the edges. The network nodes provide the means to have the goods transferred between the means of transport. Whilst purely economic criteria were initially the driving force for a change in the means of transport, ecological requirements are now becoming ever more relevant. The transportation chains should not only be economically presentable but also it makes sense for them to have a “green footprint”. In this context the following considerations will deal with the transfer processes within the network nodes, especially those within inland and feeder terminals. Replies are to be given to the questions as to how far the choice of the crane primary drive has an impact on energy consumption and environmental compatibility of handling the goods and which additional benefit does the recuperation of engrained energies bring during the handling process.

Collision Detection: Broad Phase Adaptation from Multi-Core to Multi-GPU Architecture

We present in this paper several contributions on the collision detection optimization centered on hardware performance. We focus on the broad phase which is the first step of the collision detection process and propose three new ways of parallelization of the well-known Sweep and Prune algorithm. We first developed a multi-core model takes into account the number of available cores. Multi-core architecture enables us to distribute geometric computations with use of multi-threading. Critical writing section and threads idling have been minimized by introducing new data structures for each thread. Programming with directives, like OpenMP, appears to be a good compromise for code portability. We then proposed a new GPU-based algorithm also based on the "Sweep and Prune" that has been adapted to multi-GPU architectures. Our technique is based on a spatial subdivision method used to distribute computations among GPUs. Results show that significant speed-up can be obtained by passing from 1 to 4 GPUs in a large-scale environment.