Evaluating approximations generated by the GNG3D method for mesh simplification

In this paper we present different error measurements with the aim to evaluate the quality of the approximations generated by the GNG3D method for mesh simplification. The first phase of this method consists on the execution of the GNG3D algorithm, described in the paper. The primary goal of this phase is to obtain a simplified set of vertices representing the best approximation of the original 3D object. In the reconstruction phase we use the information provided by the optimization algorithm to reconstruct the faces thus obtaining the optimized mesh. The implementation of three error functions, named Eavg, Emax, Esur, permitts us to control the error of the simplified model, as it is shown in the examples studied.

Effect of the Concentration of Siliceous Materials Added to Tobacco Cigarettes on the Composition of the Smoke Generated during Smoking

Two as-synthesized meso- and macro-porous siliceous materials (MPSMs), i.e., Al-MCM-41 and SBA-15, were mixed with tobacco to study their effect on tobacco smoke chemistry. A reference cigarette, 3R4F, and a commercial cigarette, Fortuna, containing different percentages of MPSM were smoked in a smoking machine, and the mainstream smoke was analyzed. SBA-15 showed the highest reductions of nicotine; close to 90% when it was added at 8 mass %. The superb behavior of these materials may be related to their high particulate matter filtering efficiency in combination with their catalytic activity. The selectivity of these materials with respect to nicotine was also analyzed. Al-MCM-41 presents higher selectivity for condensed compounds than for gases, whereas SBA-15 presents similar ratios for both fractions. The highest selectivity was obtained for the liquid fraction when smoking 3R4F cigarettes mixed with Al-MCM-41.