The primary aim of this research study was to model acoustic conditions of the Courtyard of the Gdańsk University of Technology Main Building, and then to design a sound reinforcement system for this interior. First, results of measurements of the parameters of the acoustic field are presented. Then, the comparison between measured and predicted values using the ODEON program is shown. Collected data indicate a long reverberation time which results in poor speech intelligibility. Then, a thorough analysis is perform to improve the acoustic properties of the model of the interior investigated. On the basis of the improved acoustic model two options of a sound reinforcement system for this interior are proposed, and then analyzed. After applying sound absorbing material it was noted that the predicted speech intelligibility increased from bad/poor rating to good category.

The work concerns the dynamic behaviour of a porous, isothermal catalyst pellet in which a simultaneous chemical reaction, diffusion and adsorption take place. The impact of the reactant adsorption onto the pellet dynamics was evaluated. A linear isotherm and a non-linear Freundlich isotherm were considered. Responses of the pellet to sinusoidal variations of the reactant concentration in a bulk gas were examined. It was demonstrated that the dynamics of the pellet is significantly affected both by accounting for the adsorption and by the frequency of the bulk concentration variations. The sorption phenomenon causes damping of the concentration oscillations inside the pellet and damping of its effectiveness factor oscillations. Depending on the frequency of the concentration oscillations in the bulk, the remarkable oscillations can involve an entire volume of the pellet or its portion in the vicinity of the external surface.

In general, currently employed vehicle classification algorithms based on the magnetic signature can distinguish among only a few vehicle classes. The work presents a new approach to this problem. A set of characteristic parameters measurable from the magnetic signature and limits of their uncertainty intervals are determined independently for each predefined class. The source of information on the vehicle parameters is its magnetic signature measured in a system that enables independent measurement of two signals, i.e. changes in the active and reactive component of the inductive loop impedance caused by a passing vehicle. These innovations result in high selective classification system, which utilizes over a dozen vehicle classes. The evaluation of the proposed approach was carried out for good vehicles consisting of 2-axle tractor and a 3-axle semi-trailer.