Ammonia, a chemical that contains high hydrogen quantities, has been presented as a candidate for the production of clean power generation and aerospace propulsion. Although ammonia can deliver more hydrogen per unit volume than liquid hydrogen itself, the use of ammonia in combustion systems comes with the detrimental production of nitrogen oxides, which are emissions that have up to 300 times the greenhouse potential of carbon dioxide. This factor, combined with the lower energy density of ammonia, makes new studies crucial to enable the use of the molecule through methods that reduce emissions whilst ensuring that enough power is produced to support high-energy intensive applications. Thus, this paper presents a numerical study based on the use of novel reaction models employed to characterize ammonia combustion systems. The models are used to obtain Reynolds Averaged Navier-Stokes (RANS) simulations via Star-CCM+ with complex chemistry of a 70%–30% (mol) ammonia–hydrogen blend that is currently under investigations elsewhere. A fixed equivalence ratio (1.2), medium swirl (0.8), and confined conditions are employed to determine the flame and species propagation at various operating atmospheres and temperature inlet values. The study is then expanded to high inlet temperatures, high pressures, and high flowrates at different confinement boundary conditions. The results denote how the production of NOx emissions remains stable and under 400 ppm, whilst higher concentrations of both hydrogen and unreacted ammonia are found in the flue gases under high power conditions. The reduction of heat losses (thus higher temperature boundary conditions) has a crucial impact on further destruction of ammonia post-flame, with a raise in hydrogen, water, and nitrogen through the system, thus presenting an opportunity of combustion efficiency improvement of this blend by reducing heat losses. Final discussions are presented as a method to raise power whilst employing ammonia for gas turbine systems.

Recent studies have demonstrated that ammonia is an emerging energy vector for the distribution of hydrogen from stranded sources. However, there are still many unknown parameters that need to be understood before ammonia can be a substantial substitute in fuelling current power generation systems. Therefore, current attempts have mainly utilised ammonia as a substitute for natural gas (mainly composed of methane) to mitigate the carbon footprint of the latter. Co-firing of ammonia/methane is likely to occur in the transition of replacing carbonaceous fuels with zero-carbo options. Hence, a better understanding of the combustion performance, flame features, and radical formation of ammonia/methane blends is required to address the challenges that these fuel combinations will bring. This study involves an experimental approach in combination with numerical modelling to elucidate the changes in radical formation across ammonia/methane flames at various concentrations. Radicals such as OH*, CH*, NH*, and NH₂* are characterised via chemiluminescence whilst OH, CH, NH, and NH₂ are described via RANS κ-ω SST complex chemistry modelling. The results show a clear progression of radicals across flames, with higher ammonia fraction blends showing flames with more retreated shape distribution of CH* and NH* radicals in combination with more spread distribution of OH*. Simultaneously, equivalence ratio is a key parameter in defining the flame features, especially for production of NH₂*. Since NH₂* distribution is dependent on the equivalence ratio, CFD modelling was conducted at a constant equivalence ratio to enable the comparison between different blends. The results denote the good qualitative resemblance between models and chemiluminescence experiments, whilst it was recognised that for ammonia/methane blends the combined use of OH, CH, and NH₂ radicals is essential for defining the heat release rate of these flames.

Recirculation in a combustion chamber is required for stabilizing the flame and reducing pollutants. The swirlers can generate recirculation in a combustion chamber, inducing a swirling flow that breaks vorticity and improves the mixing of air and fuel. The swirl number (S_n) is related to the formation of recirculation in conditions of high-intensity flows with S_n > 0.6. Thus, the optimized design of a swirler is necessary to generate enough turbulence that keeps the flame stable. We present the optimized design of a swirler considering the main parameters for a non-premixed combustion chamber. This optimization is made with genetic algorithms to ensure the generation of a recirculation zone in the combustion chamber. This recirculation phenomenon is simulated using computational fluid dynamics (CFD) models and applying the renormalization group (RNG) k-ε turbulence method. The chemistry is parameterized as a function of the mixture fraction and dissipation rate. A CFD comparison of a baseline swirler model and the proposed optimized swirler model shows that a recirculation zone with high intensity and longer length is generated in the primary zone of the combustion chamber when the optimized model is used. Furthermore, the CFD models depict swirling effects in the turbulent non-premixed flame, in which the stabilization is sensitive to the recirculation zone. The temperature results obtained with the CFD models agree well with the experimental results. The proposed design can help designers enhance the performance of combustion chambers and decrease the generation of CO and NO_x.

Constantly growing environmental concerns focused on reducing pollution, in addition to rising fuel costs in recent years, have led the maritime industry to develop and implement fuel-saving solutions. Among them is the optimization of marine propeller efficiency, as marine propellers are a crucial part of ship’s propulsion system. During the initial design stage, selecting the optimal propeller is considered a multi-objective optimization process. This research focused on maximizing propeller open water efficiency, while minimizing engine brake power constrained by thrust and cavitation. Optimization was applied to Wageningen B-series propellers and conducted using the Non-Dominated Sorting Genetic Algorithm II (NSGA-II). The algorithm selected optimum parameters to create the propeller model, which was then evaluated numerically through computational fluid dynamics (CFD) with a multiple reference frame (MRF) and under the SST k-ω turbulence model, to obtain the open water hydrodynamic characteristics. In addition, the cavitation effect was evaluated using the Zwart–Gerber–Belamri cavitation model. The numerical model results were validated through comparison with open water experimental data from the Netherlands Ship Model Basin for the Wageningen B-series propellers. The results showed errors of 3.29% and 2.01% in efficiency under noncavitating and cavitating conditions, respectively. Correct performance of the functions was shown, based on neural networks trained to estimate thrust and torque coefficients instead of polynomials. The proposed optimization process and numerical model are suitable for solving multi-objective optimization problems in the preliminary design of fixed-pitch marine propellers.

The objective of this study is to develop a genetic algorithm that uses the IGP parameterization to increase the lift coefficient (C_L) of three airfoils to be used on wings of unmanned aerial vehicles (UAVs). The geometry of three baseline airfoils was modified by developing a genetic algorithm that operates with the IGP parameterization and performs the aerodynamic analysis using XFOIL in the MATLAB environment. Subsequently, a numerical model was made for each baseline and optimized airfoil using a commercial computational fluid dynamics (CFD) code to analyze the behavior of the lift coefficient. An increase in the average C_L was obtained for the Eppler 68, MH 70, and Wortmann FX 60-126 airfoils for angles of attack ranging from 0 to 10, obtaining increments of 17.243%, 14.967%, and 10.708%, respectively. Additionally, an average 5.027% uncertainty was obtained in lift coefficient calculations between XFOIL and CFD. The utility of the IGP method and genetic algorithms for parameterizing and optimizing airfoils was demonstrated. In addition, airfoils could be tailored for a specific UAV depending on the mission profile. Volume 2 of this study will include experimental data from wind tunnel.