Virtual and Augmented Reality

Virtual Airflow Advancements in simulations render it more and more unnecessary to build physical prototypes of new development. Nevertheless, after extensive simulation, a point is reached where the simulation results have to be verified using physical prototypes. Comparing the experimental results with those of a simulation can be tricky, though. Augmented Reality techniques can help here by overlaying the real experimental data like a smoke trail in a wind channel with the visualisation of simulation results like trace lines, creating a “hybrid” prototype. This enables an expert to directly compare the experiment with the simulation. As those experts are normally scattered around the globe within distributed teams and virtual organisations, means have to be found to consult them without introducing a large overhead like travelling costs and time. This setup will be used in IRMOS as a scenario. At one side, a development team with virtual and hybrid prototypes wants to discuss the outcome of a simulation and the experiments on a car within a wind tunnel with a remote expert.

The local team itself is distributed, as the wind tunnel is situated in another hall, a few hundreds of meters from the virtual environment the local team is using. The wind tunnel contains a car body; the experiment will involve the production of stream lines with a smoke probe. Some of the engineers, using a head mounted display device, will do a local analysis of the experiment, overlaying it with the visualisation of the simulated data. The image, together with a set of other images captured by fixed cameras arranged around the physical prototype, will be transferred to a local CAVE and to the remote expert, situated in another location. Also, the simulation results will be distributed to all partners. The expert can select from multiple perspectives, including the perspectives of the local engineers, or automatically receive an image of the position closest to his actual position, thus enabling him to virtually walk around the car and perform his analysis. An audio-/video conference is used in the discussion by all partners. The connection will be routed via the IRMOS network. An initial bandwidth is reserved that allows the smooth transmission of all simulation data, video and audio streams.

The simulation data itself will be generated by a continuously running simulation that is directly connected to the visualisation. The current setup of the wind channel like angle of attack and air speed will be fed into the boundary conditions of the simulation, thus the same parameters for both will be used while the experiment is running. This enables a virtual test bed over a wide area network, making it possible to verify a full series of experiments. As post-processing of the simulation data can be quite complex and resource intensive, resources have to be found that are able to cope with this task. Thus, IRMOS platform will be used to locate the required resources, deploy a COVISE installation there and connect it to the existing COVISE session, running the CPU-intensive modules on the new nodes.

Interactions with the shared prototypes can be manifold. The engineers in the wind tunnel can move around the car, changing their and the remote team’s perspective on the real experimental data. Those new views are transmitted into the connected virtual environments and desktop workspaces, displaying the current view and the current position of the observer. All partners can influence the visualisation of the simulation results. They can collaboratively change the virtual streamlines, add isosurfaces, place markers and annotations to the data set in question, take snapshots for later reviews, etc. Of course, also physical and virtual parameters affecting the running simulation can be manipulated. Adding a real-time distribution of data, streams and feedback would give distributed teams a perfect workspace for carrying out collaborative sessions as if they were sitting together in the same room performing the same task, without the usual lag and noticeable inconsistencies in transmission. This has the potential to render unnecessary many physical meetings, enabling faster and higher quality development cycle using distributed teams.

The scenario will show how data needing a consistent data rate and low latency can be improved using the IRMOS infrastructure, running at top of a real, wide area network link. As mentioned earlier, the quality of every visualisation session is highly dependent on the speed and also reliability as when new data is available. IRMOS flow control and path monitoring tools will be exploited for ensuring a smooth and reliable frame rate.

Technical analysis:

  • Intensive real time processing for performing the simulations – usage of distributed nodes, parallel processing – for guaranteeing the perfect synchronisation of the experiment with the simulation.
  • Integration of real time multimedia applications and collaborative tools – some application to share the results of a simulation/experiment and also for the communication of the different actors.
  • Real time integration of real and virtual images. Allocation of requested nodes for CPU-intensive processing for the integration of real images and simulation results into the virtual environment, which requires a tight synchronisation of the pictures streamed into the virtual environment.