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EN
Among 210 congeners only 17 highly toxic, 2,3,7,8-chlorinated dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs) are of toxicological concern. They exhibit high binding affinity to an intracellular aryl hydrocarbon receptor (AhR), causing harmful effects at exposure levels of thousands of times lower than most environmental toxicants. The Chemically Activated LUciferase gene expression bioassay (CALUX) utilizes recombinant cells that were transfected with a luciferase reporter gene, which responds to dioxin-like compounds with the induction of luciferase in a time-, dose-, AhR-dependent and chemical-specific manner. The bioassay evaluation concerning the European Community (EC) requirements for the PCDD/Fs determination for the official control of foodstuffs was performed on salmon tissue. In order to evaluate the bioassay performance characteristics, recovery range, limit of detection (LOD), limit of quantification (LOQ) and precision were determined. The results revealed that combining a dichloromethane: hexane extraction, an acid silica plus activated carbon clean-up provides reliable, reproducible (CV = 9-20%) measurements with acceptable recovery (78%) and sensitivity at the required ppt range. Due to the low cost and high throughput characteristics of the CALUX assay, food monitoring for PCDD/Fs may benefit from use of this bioassay as a prescreening tool to select and prioritize samples for subsequent analysis by high resolution gas chromatography/high-resolution mass spectrometry (HRGC/HRMS). Although the bioassay may not be able to specify identity of the reactive substances, it may serve as a very useful tool for the evaluation of contamination sources.
EN
Accuracy of simulations of materials processing depends on quality of the description of phenomena occurring during deformation. Rheological models usually treat material as continuum and are unable to describe properly several important phenomena, which may be either random or discontinuous or both. Therefore, there is a continuous search for alternative models, which account for non-continuous structure of materials and for the fact, that various phenomena in the materials occur in various scales. Accounting for the stochastic character of phenomena is an additional challenge. Multiscale models, see eg. (Das, 2002), are one of the solutions capable to overcome mentioned difficulties. Authors have developed multiscale models based on combination of the Finite Element (FE) method and Cellular Automata (CA). Such model describing development of the strain localization during material processing (Madej et al., 2007) is one of the CAFE method applications. Numerical tests confirmed qualitatively good predictive capability of the model. Problem of quantitative accuracy still remains open. The qualitative accuracy of this model has already been proved and simulations of several industrial forming processes have been performed. Quantitative accuracy is still a challenge. To reach this accuracy, the values of the coeficients in the transmision rules have to be determined on the basis of the experimental data. It is expected that inverse analysis should be an efficient method to identify the parameters in the model. Since this analysis is usually very costly, it should be preceeded by the sensitivity analysis and selection of the parameters, which are of particular importance. Thus, the objectives of this work are twofold. The first one is to perform a detailed sensitivity analysis to identify key parameters of the model and to determine their influence on the model response. Simple shearing tests will be used as a case study in this part of the work. The second goal is an application of the inverse analysis methodology (Szeliga et al., 2006) to determine parameters of the model. These goals are steps towards qualitatively good predictive capabilities of the CAFE model. Das, S., Palmiere, E.J., Howard, I.C. (2002), CAFE: A tool for modeling thermomechanical processes, Proc. Thermomech. Processing: Mechanics, Microstructure & Control, eds, Palmiere, E.J., Mahfouf, M., Pinna , C., Sheffield, 296-301. Madej, L., Hodgson, P.D., Pietrzyk, M. (2007), Multi scale rheological model for discontinuous phenomena in materials under deformation conditions, Comp. Mat. Sci., 38, 685-691. Szeliga, D., Gawąd, J., Pietrzyk, M. (2006), Inverse Analysis for Identification of Rheological and Friction Models in Metal Forming, Comp. Meth. Appl. Mech. Engrg., 195, 6778-6798
PL
Celem niniejszej pracy jest zastosowanie analizy wrażliwości do określenia wpływu parametrów modelu wieloskalowego CAFE na wyniki symulacji procesu odkształcania związane z lokalizacją odkształcenia. W tym celu przeprowadzono szereg symulacji numerycznych, które posłużyły jako dane wejściowe do analizy wrażliwości metodą Morrisa. W pracy umieszczono opis zastosowanej metody Morisa, omówiono także jej zalety jak i wady. Wyniki przeprowadzonej analizy stanowią podstawę do dyskusji nad kierunkami dalszych badań obejmujących korzystanie metody analizy odwrotnej do identyfikacji parametrów modelu CAFE.
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