Distributed parameter estimation and identification for system with fast and slow dynamics: A tubular,fixed-bed catalytic reactor to form styrene

A simple and efficient on-line scheme is developed to estimate temperature and compositions along a packed bed reactor in which styrene is being produced by the dehydrogenation of ethylbenzene. Slowly varying catalyst activity is also identified. The system is distributed in time and axial position and is nonlinear in the states: temperature and nine compositions. The dehydrogenation rate is augmented with a catalyst activity parameter which is assumed to undergo a long-term exponential decay.Since the decline in catalyst activity is slow when compared to state dynamics, a quasi-steady-state approach is used to derive a state filter equation neglecting process state dynamics and assuming spatially uncorrelated measurements and model uncertainty. For this filter, temperature measurements are available from four locations along the reactor and compositions are measured only at the reactor exit. A second dynamic, Kalman filter is used to identify the slowly varying catalyst activity.The two filters, one for distributed, steady-state, state estimation and the other for dynamic catalyst activity identification, are tested by computer simulation using measurements with added white noise. Several cases for numbers of sensors and noise levels are studied. The overall scheme is efficient and useable for on-line implementation. The steady-state filter is readily extended to distributed systems in more than one spatial variable such as reactor models with axial and radial dependencies. For steady-state or static models, multiple measurements yield significant improvements in the quality of the optimal estimates. Internal measurement locations allow for the subdivision of the spatial domain for the problem and improved profile estimates.     

Mapping erosion susceptibility by a multivariate statistical method: A case study from the Ayval?k region, NW Turkey

Erosion is one of the most important natural hazard phenomena in the world, and it poses a significant threat to Turkey in terms of land degredation and desertification. To cope with this problem, we must determine which areas are erosion-prone. Many studies have been carried out and different models and methods have been used to this end. In this study, we used a logistic regression to prepare an erosion susceptibility map for the Ayval?k region in Bal?kesir (NW Turkey). The following were our assessment parameters: weathering grades of rocks, slope gradient, structural lineament density, drainage density, land cover, stream power index (SPI) and profile curvature. These were processed by Idrisi Kilimanjaro GIS software. We used logistic regression analysis to relate predictor variables to the occurrence or non-occurrence of gully erosion sites within geographic cells, and then we used this relationship to produce a probability map for future erosion sites. The results indicate that lineament density, weathering grades of rocks and drainage density are the most important variables governing erosion susceptibility. Other variables, such as land cover and slope gradient, were revealed as secondary important variables. Highly weathered basalt, andesite, basaltic andesite and lacustrine sediments were the units most susceptible to erosion. In order to calculate the prediction accuracy of the erosion susceptibility map generated, we compared it with the map showing the gully erosion areas. On the basis of this comparison, the area under curvature (AUC) value was found to be 0.81. This result suggests that the erosion susceptibility map we generated is accurate.     

An application of a combined wind and solar energy system in Izmir

In this work, a combined system which is produced electrical energy from both solar radiation via solar cells and wind energy by using wind turbine was studied. For wind energy, measurements of wind velocities at 12 m height were taken. Then, these values were calculated for 42 m by using Hellmann equation. After that, wind energy converted to the electrical energy. However, value of solar radiation from solar cells was taken at the optimum slope angle of collector which provided higher energy production for each 1 h during this application. Thus, obtained data from each system were used together for finding total energy. For this study, measurements, which would be used in calculation of wind energy and solar energy were taken for four years between 1995 and 1998 in Izmir. As a result, energy of the combined system could support each other when one of them produces energy insufficiently.     

Fatty acids of neutral and phospholipids of three endangered trout: Salmo trutta caspius Kessler, Salmo trutta labrax Pallas and Salmo trutta macrostigma Dumeril

Total (TL), neutral (NL) and phospholipid (PL) amounts and fatty acid (FA) composition of female Salmo trutta caspius, Salmo trutta labrax and Salmo trutta macrostigma were investigated during one year. Twenty-three FAs were identified in both NLs and PLs. The principal FAs of both fractions were palmitic acid in saturated fatty acid, oleic acid in monounsaturated fatty acid, docosahexaenoic acid (DHA) in n-3 polyunsaturated fatty acids (n-3 PUFAs) and linoleic acid in n-6 PUFAs. The highest values for TLs, NLs and PLs were found in winter. As a general trend, the highest n-3/n-6 ratios and eicosapentaenoic acid (EPA) + DHA amounts were found in the winter and this coincided with the lowest gonado-somatic index.