Dynamic torsional vibration dampers are for a long time inherent integral components of internal combustion engines. One of the most common types of the dynamic dampers is a silicone damper. It has been, for many years, perceived as an exclusively viscous damper, thus it has been constructed and designed according to this perception. When compared to other types of dynamic dampers of the similar size with flexible components used for their construction, the standard viscous damper has a lower damping effect. Moreover, this damper type has been a significantly cheaper and simpler solution. Current silicone oils with high nominal viscosity, having not only the expected damping properties, but also significant elastic characteristics under alternate shear stress, enable construction of dynamic dampers with a higher damping effect than a viscous damper. Frequency and temperature dependent complicated rheological properties of high viscosity silicone fluids can only be identified experimentally using a suitable dynamic viscometer. However, the measured frequency dependencies of both components of the complex shear modulus are only defined for harmonic loading while internal combustion engine load is periodic and contains several tens harmonics. The key to the solution is therefore to find suitable multiparameter rheological models comprised of linear elastic and damping elements that would approximate in the specified frequency range both components of the complex shear modulus. Such a complicated task can be solved using efficient optimization algorithms. This article focuses on the mathematical description of convolute rheological properties of high viscosity silicone liquids and also contains an example of the application of created rheological models in the complex dynamic model of a V10 diesel engine. A computational tool for the determination of stiffness and damping coefficients of the multi-parameter rheological model was created and solved in the optimization software GAMS by means of the CONOPT solver. The possibility of these modern technologies is shown by the comparison of computation models and experimentally set torsional vibration spectres with standard viscous damper and damper utilizing a high viscosity silicone oil.

The paper presents the comparison of optimization-regulation algorithms applied to the secondary cooling zone in continuous steel casting where the semi-product withdraws most of its thermal energy. In steel production, requirements towards obtaining defect-free semi-products are increasing day-by-day and the products, which would satisfy requirements of the consumers a few decades ago, are now far below the minimum required quality. To fulfill the quality demands towards minimum occurrence of defects in secondary cooling as possible, some regulation in the casting process is needed. The main concept of this paper is to analyze and compare the most known metaheuristic optimization approaches applied to the continuous steel casting process. Heat transfer and solidification phenomena are solved by using a fast 2.5D slice numerical model. The objective function is set to minimize the surface temperature differences in secondary cooling zones between calculated and targeted surface temperatures by suitable water flow rates through cooling nozzles. Obtained optimization results are discussed and the most suitable algorithm for this type of optimization problem is identified. Temperature deviations and cooling water flow rates in the secondary cooling zone, together with convergence rate and operation times needed to reach the stop criterium for each optimization approach, are analyzed and compared to target casting conditions based on a required temperature distribution of the strand. The paper also contains a brief description of applied heuristic algorithms. Some of the algorithms exhibited faster convergence rate than others, but the optimal solution was reached in every optimization run by only one algorithm.

The main concept of this paper is to utilize advanced numerical modelling techniques with self-regulation algorithm in order to reach optimal casting conditions for real-time casting control. Fully 3-D macro-solidification model for the continuous casting (CC) process and an original fuzzy logic regulator are combined. The fuzzy logic (FL) regulator reacts on signals from two data inputs, the temperature field and the historical steel quality database. FL adjust the cooling intensity as a function of casting speed and pouring temperature. This approach was originally designed for the special high-quality high-additive steel grades such as higher strength grades, steel for acidic environments, steel for the offshore technology and so forth. However, mentioned approach can be also used for any arbitrary low-carbon steel grades. The usability and results of this approach are demonstrated for steel grade S355, were the real historical data from quality database contains approximately 2000 heats. The presented original solution together with the large steel quality databases can be used as an independent CC prediction control system.