Técnicas de inteligência artificial para a geração dinâmica de set points para uma coluna de destilação

Artificial Intelligence techniques are applied to improve performance of a simulated oil distillation system. The chosen system was a debutanizer column. At this process, the feed, which comes to the column, is segmented by heating. The lightest components become steams, by forming the LPG (Liquefied Petroleum Gas). The others components, C5+, continue liquid. In the composition of the LPG, ideally, we have only propane and butanes, but, in practice, there are contaminants, for example, pentanes. The objective of this work is to control pentane amount in LPG, by means of intelligent set points (SP s) determination for PID controllers that are present in original instrumentation (regulatory control) of the column. A fuzzy system will be responsible for adjusting the SP's, driven by the comparison between the molar fraction of the pentane present in the output of the plant (LPG) and the desired amount. However, the molar fraction of pentane is difficult to measure on-line, due to constraints such as: long intervals of measurement, high reliability and low cost. Therefore, an inference system was used, based on a multilayer neural network, to infer the pentane molar fraction through secondary variables of the column. Finally, the results shown that the proposed control system were able to control the value of pentane molar fraction under different operational situations

Avaliação da desadaptação das selas de próteses parciais removíveis após 1 a 5 anos de uso

The non-adaptation of the removable partial prosthesis (RPP) base to fibromucosal tissue is caused by resorption of residual ridges (RRR). The onset of bone resorption, which occurs after tooth extraction and continues throughout life, is accelerated by local or systemic factors. Aim: Assess the degree of non-adaptation of removable partial prosthesis saddles and the factors that influence it. Methodology: A sectional study was conducted with 81 patients using RPP who had their prostheses installed between 2003 and 2007 (1 to 5 years of use) at the Faculty of Dentistry of the Universidade Federal do Rio Grande do Norte (UFRN). After anamnese and clinical examination, a cast was made with polyether-based material, using the base of the prosthesis to make the impression. The base of the saddle was loaded with the casting material and positioned in the mouth, applying pressure on the supports. After polymerization, the material was removed from the saddle and measurements were taken at 3 different points using a pachymeter. Results: The non-adaptation of the saddle increased significantly with years of use (p = 0.005). The tooth-tissue supported prostheses obtained higher mean non-adaptation values than those of tooth supported prostheses (p < 0.001). Flaccid mucosa showed the worst non-adaptation results, which were statistically different from resilient mucosa (p < 0.001). The greater the extension of the saddle, the greater the non-adaptation (p < 0.001). The natural tooth antagonistic arch yielded better results than did RPP and total prosthesis (p < 0.001). Saddle non-adaptation at the free end was less near the pillar tooth and greater in the more posterior region (p < 0.001). When adaptation of the supports to the niches was poor, greater saddle non-adaptation occurred than when it was good or fair (p < 0.001). Saddles located in the posterior region of the arch had greater non-adaptation than those in the anterior region (p = 0.023). Conclusion: The mean non-adaptation of the saddle to the residual ridges was 0.27 mm. It can be concluded that, even with the use of RPP, bone height reduction was slight within the 1-5-year period of use. The following are factors that influence adaptation of the RPP saddle base: years of use, age, force transmission path to the alveolar bone, location of the toothless area, antagonistic arch, type of mucosa, adaptation of supports to the niche and extension of the saddle