The widespread use of computational simulation in physical sciences and
engineering provides many research opportunities
but also presents significant challenges. Multiple independent variables
are considered in a simulation and large and complex
data are computed, especially in the case of multi-run simulation.
Classical visualization techniques usually deal well with 2D or 3D
data and with time-dependent data. The case of additional independent
dimensions, however, amounts to interesting challenges for
visualization. We present an advanced visual analysis approach that
enables a thorough investigation of families of data
surfaces, i.e., datasets, that are seen with respect to pairs of
independent dimensions.
While it is almost trivial to visualize one such data surface, the
visual exploration and analysis of many such data surfaces is a grand
challenge, stressing the users? perception and cognition.
We exemplify our approach in the context of a meteorological multi-run
simulation data case and in the context of a case from the engineering
domain, the simulation of elastohydrodynamic (EHD) lubrication bearing
in the car engine design.