Ammonia combustion is gaining interest as a feasible alternative to traditional fossil fuels because of to the low environmental impact and as hydrogen and energy carrier. This study used Computational Fluid Dynamics (CFD) simulations to compare various turbulence models for premixed ammonia/hydrogen combustion in a swirl-stabilized burner. The primary aim was to identify the best turbulence model for accurately predicting the flow dynamics, combustion behaviour, and emissions profiles of ammonia/hydrogen fuel blends. The turbulence models evaluated were Large Eddy Simulation (LES), Realizable k- $$\epsilon$$ ϵ , Renormalization Group (RNG) k- $$\epsilon$$ ϵ , k- $$\omega$$ ω SST, and Reynolds Stress Model (RSM). On the LES side, a further comparison of two subgrid models (Smagorinsky-Lilly and WALE) was investigated. The Flamelet Generated Manifold (FGM) method was utilized with a detailed chemistry scheme taking into consideration all $$\hbox {NO}_x$$ NO x reactions. To improve the prediction of $$\hbox {NO}_x$$ NO x emissions, additional scalar transport equations for NO and $$\hbox {NO}_2$$ NO 2 were included. This methodology aimed to be a balance between computational efficiency and the accuracy expected of detailed chemistry models. Validation was done with a swirl burner from Cardiff University’s Gas Turbine Research Centre. Results showed that all turbulence models accurately captured flame characteristics in terms of exhaust temperature and axial velocity with minor differences in the recirculation zones, where only the RSM model can predict the velocity trend as the LES simulation while other RANS models differ by at least 7 m/s. The temperature reached by the LES resulted 100 K higher than the other models in the flame zone. LES simulation can predict the emission value with an error of less than 10 $$\%$$ % . Moreover, the error related to emissions derived from the RANS simulations was not negligible, underestimating $$\hbox {NO}_x$$ NO x emissions by about 35 $$\%$$ % . However, RSM model produced results that were closer to those derived from the high-fidelity LES when compared to the others RANS models, particularly in terms of flame thickness and emissions. It was concluded that it is mandatory to perform an unsteady analysis to reach reasonable results.

The potential of applying a floating PV (FPV) system in an Italian context (namely, Cecita dam and Mucone hydroelectric power plants) is studied. The additional PV energy production, as well as the effect of non-evaporated water on the productivity of the hydropower plant, is analyzed by varying the basin surface coverage. The simulations highlight that the amount of additional hydroelectricity is quite small if compared to the non-FPV system, reaching about 3.56% for 25% basin surface coverage. However, the annual PV energy production is noticeable even at low coverage values. The expected gain in electricity production in the case of 25% basin surface coverage with the FPV plant rises to 391% of that of the actual hydropower plant. This gain becomes even larger if a vertical axis tracking system is installed and the increase is about 436%. The economic analysis confirms that the production costs (USD/kWh) of FPV systems are comparable to those of land-based PV (LBPV) plants, becoming smaller in the case that a tracking system is installed. In particular, the best solution is the one with 15% coverage of the lake. In this case, the levelized cost of electricity for the LBPVs is 0.030 USD/kWh and for the FVPs, with and without tracking, it is equal to 0.032 and 0.029 USD/kWh, respectively.

The relevance of selecting an appropriate bed material in fluidized bed gasification is a crucial aspect that is often underestimated. The ideal material should be economical, resistant to high temperatures and have small chemical interaction with biomass. However, often only the first of such three aspects is considered, neglecting the biomass–bed interaction effects that develop at high temperatures. In this work, olivine and K-feldspar were upscale-tested in a prototype fluidized bed gasifier (FBG) using arboreal biomass (almond shells). The produced syngas in the two different tests was characterized and compared in terms of composition (H₂, CH₄, CO, CO₂, O₂) and fate of contaminants such as volatile organic compounds (VOCs), tar and metals.. Moreover, the composition of olivine and K-feldspar before and after the biomass gasification process has been characterized. The aim of this work is to show which advantages and disadvantages there are in choosing the most suitable material and to optimize the biomass gasification process by reducing the undesirable effects, such as heavy metal production, bed agglomeration and tar production, which are harmful when syngas is used in internal combustion engines (ICE). It has been observed that metals, such as Ni, Cu, Zn, Cd, Sn, Ba and Pb, have higher concentrations in the syngas produced by using olivine as bed material rather than K-feldspar. In particular, heavy metals, such as Pb, Cu, Cd, Ni and Zn, show concentrations of 61.06 mg/Nm³, 15.29 mg/Nm³, 17.97 mg/Nm³, 37.29 mg/Nm³ and 116.39 mg/Nm³, respectively, compared to 23.26 mg/Nm³, 11.82 mg/Nm³, 2.76 mg/Nm³, 24.46 mg/Nm³ and 53.07 mg/Nm³ detected with K-feldspar. Moreover, a more hydrogen-rich syngas when using K-feldspar was produced (46% compared to 39% with olivine).

The study utilizes open-access data to generate power demand curves for a hybrid automotive system, testing twelve configurations with three different energy management strategies and four values for the degree of hybridization (DOH), the latter representing the share of the total power of the vehicle powertrain supplied by the battery. The first control logic (Battery Main—BTM) uses mainly batteries to satisfy the power demand and fuel cells as backup, while in the other two controllers, fuel cells operate continuously (Fuel Cell Main—FCM) or within a fixed range (Fuel Cell Fixed—FCF) using batteries as backup. The results are assessed in terms of H₂ consumption, overall system efficiency, and fuel cell predicted lifespan. The battery is heavily stressed in the BTM and FCF logics, while the FCM logic uses the battery only occasionally to cover load peaks. This is reflected in the battery’s State of Charge (SOC), indicating different battery stress levels between the BTM and FCF modes. The FCF logic has higher stress levels due to load demand, reducing battery lifetime. In the BTM and FCM modes, the fuel cell operates with variable power, while in the FCF mode, the fuel cell operates in a range between 90 and 105% of its rated power to ensure its lifetime. In the BTM and FCM modes, hydrogen consumption decreases at almost the same rate as the DOH increases, due to a decrease in battery capacity and a smaller amount of hydrogen being used to recharge it. In contrast, the FCF control logic results in a larger fuel consumption when the DOH decreases. In terms of FC durability, the FCF control logic performs better, with a predicted lifetime ranging from 1815 h for DOH = 0.5 to 2428 h for DOH = 0.1. The FCM logic has the worst performance, with a predicted lifetime of 800 to 808 h, being almost insensitive to the DOH variation. Simulations were performed on two different driving cycles, and similar trends were observed. Simulations taking into account fuel cell (FC) performance degradation showed an increase in hydrogen consumption of approximately 38% after 12 years. Overall, this study highlights the importance of optimizing control systems to improve the performance of fuel cell hybrid vehicles, also taking into account the component of performance degradation.