The hydrodynamics of liquid flow in packed columns affects the column performance from the point of view of heat and mass transfer. The interfacial and the specific wetted areas are decisive in this case. The complex three-dimensional liquid flow on a single structured and flat packing element of Rombopak 4M was investigated. It consists of four connected wavy inclined plates in an X-shape configuration. The geometric characteristics of the packing were related to the fluid mechanics of the liquid distribution. CFD simulation results for different cell sizes and flow rates, obtained using the VOF (volume of fluid) model, are presented as being capable of describing this complex geometry. With the help of the CFD simulation and the experimental results from Rombopak 4M, correlations from the literature describing the interfacial and wetted area and liquid holdup in packed columns were adjusted to describe the hydrodynamic performance of Rombopak 4M.

The laminar liquid rivulet flow on an inclined flat metal plate and wavy metal plate is taken as a test case to validate the CFD-simulation results using the VOF (Volume of Fluid) multiphase flow model. The local rivulet thickness was measured using an optically assisted mechanical sensor and compared with the simulation results. The circular shape of the rivulet profile has been proven for an inclined plate. Glycerin water mixtures with different concentrations were used in the experiments. Two theoretical models to describe this laminar rivulet flow in comparison to the experimental and CFD results are discussed.

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Bimetals are widely used as a thermal tripping mechanism inside the miniature circuit breakers (MCBs) products when an overload current passes through the circuit for a certain period. Experimental, numerical, and, recently artificial intelligence methods are widely used in designing electric components. However, developing the bimetal for MCB products somewhat differs from developing other conductor items since they are strongly related to the electrical, mechanical, and thermal performance of the MCB. The conventional experimental and numerical approaches are time-consuming processes that cannot be easily utilized in optimizing the product's performance within the development lead time. In this study, a simple, fast, robust, and accurate novel methodology has been introduced to predict the temperature rise of the bimetal and other related performance characteristics. The numerical model has been built on the time-based finite difference method to frame the theoretical thermal model of the bimetal. Then, the numerical model has been consolidated by the machine learning (ML) model to take advantage of the experiments to provide an accurate, fast and reliable model finally. The novel model agrees well with the experimental tests, where the maximum error does not exceed 8%. The model has been used to redesign the bimetal of a 32 A MCB product and significantly reduce the maximum temperature by 24 °C. The novel model is promising since it considerably reduces the required design time, provides accurate predictions, and helps to optimize the performance of the circuit breaker products.