Materials in situ visualization
Breakthroughs in material science and engineering allow on a daily basis the creation of new innovative products with well targeted functionalities : energy savings, mechanical resistance, water repellency, optical selectivity … While those features are always initially considered at the lab scale, the most promising candidates are the ones which will be able to demonstrate their capacities in real-life conditions.
Considering new materials aesthetics aspect, a significant need to go beyond the samples appearance quickly appears while trying to convince relevant stakeholders. In this context, being able to put forward an in situ visualization of the said product will strongly support any kind of argument. However, physical full-scale transposition of lab scale samples might be highly costly with an associated tremendous lead time. Alternatively, a fast, cost-effective and reliable method enabling such an in situ visualization is the measured based approach proposed by the virtual prototyping.
In order to highlight the benefit of the virtual prototyping technique, a typical case study involving painted glass is presented here below.
Case study : Painted glass render
Painted glass consists in glass with a lacquer layer deposited on one of its face and mainly used for decorative purposes. In the present case study, various painted glass were considered with two different lighting conditions (Fig. 1).
Figure 1 : Physical painted glass samples photography under two lighting conditions.
As a first step in the rendering process, received samples need to be optically characterized. This procedure is not as straightforward as it might look like due to the intrinsic optical complexity of the product. Indeed, painted glass exhibits two main optical contributions as described here below (Fig. 2):
- External optical contribution : The glass reflection
- Internal optical contribution : The refracted diffusion of the paint
Figure 2 : Main optical contribution of the painted glass
The combined effects are displayed on Fig. 2.3 as well as a ray-tracing view. It should be stressed that due to the glass intrinsic absorption properties, the perceived color of the paint through the glass might be slightly altered in comparison with the naked paint.
In order to properly catch those optical features, spectrophotometer, goniospectrophotometer measurement and integrating sphere are required. Relevant data such as reflectance and BRDF are used as input data in OceanTM (Eclat Digital software).
In a second step, in order to assess the predictiveness of the renders generated by OceanTM , preliminary renders are generated using a 3D geometry similar to the one used for the photography on Fig. 1 as well as same lighting conditions. The results are presented on Fig. 3 , exhibiting a high degree of matching between the renders and the physical samples.
Figure 3 : Photography and renders comparison using two lighting conditions.
Acknowledging such rendering reliability, in situ renders can be faithfully generated in a given situation. The results is presented on Fig. 4 .
Figure 4 : In situ renders of painted glass.