Simulation is used often in the preliminary design phase when there are fewer control parameters thus making it feasible to use tangible visual analysis. Tangible user interfaces and interactions are realized by deploying real objects representing control parameters. Those objects can be moved and rotated in order to interact with computer and direct the visual analysis. We can take advantage of new technologies, such as Microsoft HoloLens, to provide a mixed reality based system for tangible visual analysis. Instead of using generic tokens, as the current state of the art does, we use semantic representatives that can function without augmentation. We also introduce the iconic view, integrated within a coordinated multiple views tool, which depicts input parameters. The iconic view can be used as an alternative to the tangible interface for input parameter specification. The preliminary results indicate that manipulating simulation parameters in a less abstract way helps the experts.

Design of experiments (DOE) is the study of how to vary control parameters to efficiently design and evaluate experiments. Main effects plot and interaction plot are two data views often used to explore differences between mean values and interactions between the DOE parameters but they are mostly limited to two parameters. We propose a new data view, interactive interaction plot, that supports exploration and analysis of high-dimensional interactions between parameters. The data view is integrated within a coordinated multiple views system. We describe the new data view using an Olympic medals data set. We also describe a case study dealing with initial selection of hybrid vehicle components. Very positive feedback from automotive domain experts demonstrates the usefulness of the newly proposed approach.

The design of modern, hybrid vehicles is an active area of research. As the whole field is new, engineers need intuitive and powerful support tools. In this application paper, we illustrate an application of interactive visual analysis in the concept phase of a hybrid-vehicle design. We exploit coordinated multiple views to explore and analyze a simulation ensemble ‐ a set of simulation runs of the same simulation model. Once we reduce the ensemble to a single run we use a detailed view, including an energy flow graph and a vehicle drive animation. Very positive feedback from domain experts and opportunities for additional improvements encourage further research.

A timing chain drive transfers motion from the engine's crankshaft to the camshaft that operates the valves. The design process of timing chain drives involves computer simulation of many design variants in order to find an optimum. Most of the simulation results can be represented as families of function graphs (data series). Previously, the analysis of those results was based on static 2D diagrams and animated 3D visualizations. They were suitable for the detailed analysis of a few simulation variants, but not for the comparison of many cases. In this paper we propose a new approach to the analysis based on coordinated linked views and advanced brushing features. Our proposed method supports the interactive analysis of many design variants. We introduce a novel view, called segmented curve view, which can display distributions in families of function graphs. The segmented curve view combines individual function graphs where for a fixed value of the independent variable, a bar extends from minimum to maximum values across the family of function graphs. Each bar is divided into segments (bins) with a color that represents the number of function graphs with the value in that segment. In the case study, we demonstrate that the new view combined with "traditional" views provides a strong support for the interactive visual exploration and analysis of a real world timing chain design problem.