Dawid Taler

Due to their advantageous heat transfer characteristics and compact design, helically coiled heat exchangers have found extensive application in HVAC systems and are also gaining importance in advanced nuclear technologies, particularly in Small Modular Reactor (SMR) concepts. Accurate correlations for heat transfer are essential for their effective design; however, reliable predictive relationships remain limited, particularly for flow in annular channels. This study presents a new combined experimental and numerical approach for the simultaneous identification ofheat transfer correlations for the hot and cold fluids in a helically coiled concentric-tube heat exchanger. A nonlinear least-squares approach was employed to identify the unknown correlation coefficients by minimising the sum of squared residuals between the experimental and predicted outlet temperatures of both fluids. Experimental investigations were conducted over a broad range of inlet temperatures and water flow rates using a computerised data acquisition system. The experimental results provided the basis for establishing new Nusselt number relationships for the hot and cold water. Application of these relationships yielded outlet-temperature predictions that closely matched the values obtained from the measurements. In addition, 95% confidence intervals were established for each identified coefficient. The inner-tube correlation was examined in relation to correlations available in the literature, showing close agreement with previously published results.

Plate heat exchangers are used in heat substations for domestic hot water preparation and building heating in municipal central heating systems. Water from the municipal water supply is heated by hot water from a district heating network. This paper presents a numerical method for simultaneously determining heat transfer correlations on the cold and hot water sides based on flow-thermal measurements of the plate heat exchanger. The unknown parameters in the functions approximating the Nusselt numbers, which depend on the Reynolds and Prandtl numbers, are determined using the least-squares method, so the sum of the squares of the differences in the calculated and measured temperatures at the heat exchanger outlet reaches a minimum. One or two correlations were sought for a plate heat exchanger, and the total number of parameters sought is between three and six. The limits of the 95% confidence intervals for all estimated parameters were also determined. Correlations for Nusselt numbers determined experimentally for a clean plate heat exchanger can be used in the online monitoring of the degree of fouling of plate heat exchangers installed in the substations of a large urban district heating network.

This study investigates the combustion behavior of polycarbonate (PC) and polycarbonate–carbon nanotube (PC-CNT) composites in fluidized bed reactors. The primary objective was to evaluate the influence of carbon nanotubes (CNTs) on the thermal stability and combustion efficiency of PC. Simultaneous thermogravimetric and differential scanning calorimetry (TG-DSC) analyses were conducted under both air and oxygen-deficient conditions to assess decomposition temperature ranges and energetic effects. Additionally, a simultaneous TG-DSC analysis of the samples’ decomposition in a 2 vol.% O₂ atmosphere was carried out to simulate adverse combustion conditions that may occur in some combustion technologies, such as the accumulation of degraded material on the grate. Combustion experiments were performed in inert and catalytic fluidized beds, the latter incorporating Fe₂O₃-coated cenospheres to enhance catalytic activity. The results demonstrated that the presence of CNTs alters the combustion mechanism, reducing energy release in the initial degradation stage while significantly intensifying exothermic effects in subsequent stages. Under oxygen-deficient conditions, both PC and PC-CNT required higher temperatures and extended times for complete decomposition. The catalytic fluidized bed markedly improved combustion efficiency at lower temperatures, achieving up to 90% conversion at 550 °C, compared to inert beds that required 750 °C for similar efficiency.

The electrocatalyst layers (ECLs) in polymer electrolyte membrane (PEM) electrolyzers are fundamentally comprised of IrOx catalysts, support material, and an ionomer. Their stability is critically dependent on structure and composition, necessitating a thorough understanding of ionization potential and work function. We employ Density Functional Theory (DFT) to determine the ionization states of ECLs and to optimize their electronic properties. Furthermore, advanced deep learning simulations (DLSs) significantly enhance the kinetic and transport behaviors of these layers. This work integrates DFT and DLS to elucidate the characteristics of ECLs within PEM electrolyzer cells. We strategically utilize DFT to refine catalyst molecules and assess their electronic properties, while DLS is employed to predict the potential energy of support molecules in the catalyst layers. We establish a clear relationship between the energy and geometry of IrOx molecules. The DFT-DLS framework robustly calculates potential energy and reaction coordinates, effectively bridging theoretical computations with the dynamic behavior of molecules in catalyst layers. We validate our model by comparing it with the experimental polarization curve of the IrOx-based anode catalyst layer in a functioning electrolyzer. The observed Tafel slope and exchange current density unequivocally confirm that the oxygen evolution reaction (OER) occurs through a well-defined electrochemical pathway, with oxygen generation proceeding according to the charge transfer mechanism predicted by the DFT-DLS framework.

A numerical simulation of the circular cylinder as an obstacle in a double forward-facing (DFFS) step was performed. The size and position of the upstream cylinder (c₁) and downstream cylinder (c₂) were varied to explore their role in heat transfer in both laminar and turbulent conditions. Comparative results of the upper and lower half of the downstream cylinder were plotted as results to understand the heat transfer and flow characteristics around the downstream cylinder due to the effect of the upstream cylinder’s dimension and position. For Re = 800, when the c₁ is placed near the bottom of the wall, it results in a pair of rear-side symmetrical vortices, and the c₂ cylinder vortices become larger when the c₁ is shifted towards the top wall. Additional flow separation happens adjacent to the steps when c₁ is greater than c₂. These vortices strongly influence the convection heat transfer from the step. However, when Reynolds number (Re) is increased from 800 to 80,000, these vortices’ size is decreased. When c₁ moves from 0.375H to 0.75H, the average Nusselt number is increased significantly. Moreover, a hike in Re results in a higher average Nusselt number irrespective of the position of obstacles. The upstream cylinder significantly enhances the Nusselt number when it is placed near the top wall rather than the bottom wall.

This paper deals with the topic of reducing drag force acting on aircraft wings by incorporating novel winglet designs, such as multi-tip, bird-type, and twisted. The high-speed NASA common research model (CRM) was selected as the baseline model, and winglet designs were retrofitted while keeping the projected wingspan constant. Computational analysis was performed using RANS coupled with the Spalart–Allmaras turbulence model to determine aerodynamic coefficients, such as C_L and C_D. It was observed that the multi-tip and bird-type designs performed exceptionally well at a low angle of attack (0°). A parametric study was conducted on multi-tip winglets by tweaking the parameters such as sweep angle (Λ), tip twist (Є), taper ratio (λ), and cant angle (Φ). The best combination of parameters for optimal aerodynamic performance while maintaining the wing root bending moment was determined using both the Taguchi method and Taguchi-based grey relational analysis (T-GRA) coupled with principal component analysis (PCA). Also, the percentage contribution of each parameter was determined by using the analysis of variance (ANOVA) method. At the design point, the optimized winglet design outperformed the baseline design by 18.29% in the Taguchi method and by 20.77% in the T-GRA coupled with the PCA method based on aerodynamic efficiency and wing root bending moment.