Modeling of non-isothermalvapor membrane separation with thermodynamic models and generalized mass transfer equations

A rigorous unit operation model is developed for vapor membrane separation. The new model is able to describe temperature, pressure, and concentration dependent permeation as wellreal fluid effects in vapor and gas separation with hydrocarbon selective rubbery polymeric membranes. The permeation through the membrane is described by a separate treatment of sorption and diffusion within the membrane. The chemical engineering thermodynamics is used to describe the equilibrium sorption of vapors and gases in rubbery membranes with equation of state models for polymeric systems. Also a new modification of the UNIFAC model is proposed for this purpose. Various thermodynamic models are extensively compared in order to verify the models' ability to predict and correlate experimental vapor-liquid equilibrium data. The penetrant transport through the selective layer of the membrane is described with the generalized Maxwell-Stefan equations, which are able to account for thebulk flux contribution as well as the diffusive coupling effect. A method is described to compute and correlate binary penetrant¿membrane diffusion coefficients from the experimental permeability coefficients at different temperatures and pressures. A fluid flow model for spiral-wound modules is derived from the conservation equation of mass, momentum, and energy. The conservation equations are presented in a discretized form by using the control volume approach. A combination of the permeation model and the fluid flow model yields the desired rigorous model for vapor membrane separation. The model is implemented into an inhouse process simulator and so vapor membrane separation may be evaluated as an integralpart of a process flowsheet.

Neurofilament proteins in the postnatal rat hippocampus. Developmental expression and changes in experimental epilepsy

Neurofilament proteins (NFs) are the major components of the intermediate filaments of the neuronal cytoskeleton. The three different NF proteins; the low (NF-L), medium (NF-M),and dendrites.NF proteins play an important role in neuronal development, and plasticity,and seem to contribute to the pathophysiology of several diseases. However, the detailed expression patterns of NF proteins in the course of postnatal aturation, and in response to seizures in the rat have remained unknown. In this work, I have studied the developmental expression and cellular distribution of the three NF proteins in the rat hippocampus during the postnatal development. The reactivity of NF proteins in response to kainic acid (KA)-induced status epilepticus (SE)was studied in the hippocampus of 9-day-old rats, and using in vitro organotypic hippocampal slices cultures prepared from P6-7 rats. The results showed that NF-L and NF-M proteins are expressed already at the postnatal day 1, while the expression of NF-H mainly occurred during the second postnatal week. The immunoreactivity of NF proteins varied depending on the cell type and sub-cellular location in the hippocampus. In adult rats, KA-induced SE typically results in severe and permanent NF degradation. However, in our P9 rats KA-induced SE resulted in a transient increase in the expression of NF proteins during the first few hours but not degradation. No neuronal death or mossy fiber sprouting was observed at any time after SE. The in vitro studies with OHCs, which mimick the in vivo developing models where a local injection of KA is applied(e.g. intrahippocampal), indicated that NF proteins were rapidly degraded in response to KA treatment, this effect being effectively inhibited by the treatment with the AMPA receptor antagonist CNQX, and calpain inhibitor MDL-28170. These compounds also significantly ameliorated the KA-induced region-specific neuronal damage. The NMDA receptor antagonist and the L-type Ca2+ channel blocker did not have any significant effect. In conclusion, the results indicate that the developmental expression of NF in the rat hippocampus is differentially regulated and targeted in the different hippocampal cell types during the postnatal development. Furthermore, despite SE, the mechanisms leading to NF degradation and neuronal death are not activated in P9 rats unlike in adults. The reason for this remains unknown. The results in organotypic hippocampal cultures confirm the validity of this in vitro model to study development processes, and to perform pharmacological studies. The results also suggest that calpain proteases as interesting pharmacological targets to reduce neuronal damage after acute excitotoxic insults.

A generalized 1D particle transport method for convection diffusion reaction model

This work is devoted to the development of numerical method to deal with convection diffusion dominated problem with reaction term, non - stiff chemical reaction and stiff chemical reaction. The technique is based on the unifying Eulerian - Lagrangian schemes (particle transport method) under the framework of operator splitting method. In the computational domain, the particle set is assigned to solve the convection reaction subproblem along the characteristic curves created by convective velocity. At each time step, convection, diffusion and reaction terms are solved separately by assuming that, each phenomenon occurs separately in a sequential fashion. Moreover, adaptivities and projection techniques are used to add particles in the regions of high gradients (steep fronts) and discontinuities and transfer a solution from particle set onto grid point respectively. The numerical results show that, the particle transport method has improved the solutions of CDR problems. Nevertheless, the method is time consumer when compared with other classical technique e.g., method of lines. Apart from this advantage, the particle transport method can be used to simulate problems that involve movingsteep/smooth fronts such as separation of two or more elements in the system.

Generalized Differential Evolution for Global Multi-Objective Optimization with Constraints

The objective of this thesis work is to develop and study the Differential Evolution Algorithm for multi-objective optimization with constraints. Differential Evolution is an evolutionary algorithm that has gained in popularity because of its simplicity and good observed performance. Multi-objective evolutionary algorithms have become popular since they are able to produce a set of compromise solutions during the search process to approximate the Pareto-optimal front. The starting point for this thesis was an idea how Differential Evolution, with simple changes, could be extended for optimization with multiple constraints and objectives. This approach is implemented, experimentally studied, and further developed in the work. Development and study concentrates on the multi-objective optimization aspect. The main outcomes of the work are versions of a method called Generalized Differential Evolution. The versions aim to improve the performance of the method in multi-objective optimization. A diversity preservation technique that is effective and efficient compared to previous diversity preservation techniques is developed. The thesis also studies the influence of control parameters of Differential Evolution in multi-objective optimization. Proposals for initial control parameter value selection are given. Overall, the work contributes to the diversity preservation of solutions in multi-objective optimization.

Detection of Epilepsy with a Commercial EEG Headband

Epilepsy is a chronic brain disorder, characterized by reoccurring seizures. Automatic sei-zure detector, incorporated into a mobile closed-loop system, can improve the quality of life for the people with epilepsy. Commercial EEG headbands, such as Emotiv Epoc, have a potential to be used as the data acquisition devices for such a system. In order to estimate that potential, epileptic EEG signals from the commercial devices were emulated in this work based on the EEG data from a clinical dataset. The emulated characteristics include the referencing scheme, the set of electrodes used, the sampling rate, the sample resolution and the noise level. Performance of the existing algorithm for detection of epileptic seizures, developed in the context of clinical data, has been evaluated on the emulated commercial data. The results show, that after the transformation of the data towards the characteristics of Emotiv Epoc, the detection capabilities of the algorithm are mostly preserved. The ranges of acceptable changes in the signal parameters are also estimated.