The flashback analysis in Gas Turbines for Power Generation has been of great concern for manufacturers and researchers in the last decade. This is due to the increased interest in using biofuels and enriched hydrogen combustibles for emission reduction and economical alternatives to fossils. This paper analyses experimentally and numerically the phenomenon in a Tangential Swirl Burner under different conditions in order to increase the understanding of the phenomenon to reduce its impacts in real gas turbines.
Ammonia is believed to eventually play an important role in substituting conventional fossil fuels for future energy systems. In this study, to gain a deep insight into the combustion properties of co-firing ammonia/methane fuel blends for the power and steel industry, a detailed chemical-kinetics mechanism model was developed for comprehensively modelling ammonia/methane fuels combustion. Characteristics of ignition delay time, unstretched laminar flame speed and NO, CO2 and CO emissions in the exhaust gas were obtained over a wide range of equivalence ratios and ammonia fractions. High NO emissions will be a main problem as CO and CO2 emissions tend to drop when adding ammonia into methane. To gain a further understanding of the effect of ammonia substituting methane for combustion use, analyses of laminar premixed flame structures were performed. The impact of ammonia substitution was illustrated by analysing relevant specific radicals. Furthermore, to study the combustion characteristics of ammonia/methane under more practical conditions, effects of engine relevant conditions (elevated pressure and initial temperature) were also studied. Results indicate that pressure has a more prominent effect than initial temperature and there is a good potential that unwanted emissions can be reduced significantly under industrial conditions.
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To date, a number of mechanical, electrical, thermal, and chemical approaches have been developed for storing electrical energy for utility-scale services. The only sufficiently flexible mechanism allowing large quantities of energy to be stored over long time periods is chemical energy storage in the form of carbon or hydrogen. One chemical considered for hydrogen carriage that can potentially be employed for storage is ammonia. Ammonia can substitute pure hydrogen for storage and be employed for power generation at large industrial scale if the molecule is efficiently burned through mature equipment such as gas turbines, thus providing not only a carbon free fuel, but also a chemical capable of being stored at low energy requirements. Thus, progress on the use of ammonia in gas turbines is a main priority for groups working on the area. Studies need to be conducted in experimental rigs with strong CFD analyses for further industrial implementation. In this paper, modelling of ammonia combustion in a generic gas turbine combustor is explored in order to provide an effective tool for future application. Large Eddy Simulation approach was used to develop a model for ammonia/hydrogen combustion in gas turbine combustors. To capture more details of the turbulent reacting flow, a detailed chemical mechanism was selected for a deep insight. A Partially Stirred Reactor framework was utilized to deal with the turbulence/chemistry interaction. The developed model was then applied to the simulation of lean premixed ammonia/hydrogen flames in a generic swirl burner. A preliminary validation for the model is performed by correlation of NOx emission with experimental data. Results show the model can provide detailed information of flow field, flame structure, emissions, etc. It can be used to optimize the procedure of utilizing ammonia as a fuel in future equipment design.
In the present study, combustion characteristics of ammonia/methane were evaluated computationally utilizing counterflow premixed ammonia/methane/air flames at normal temperature and pressure conditions. Investigations were carried out over a wide range of flame strain rates, fuel blend compositions and equivalence ratios. Extinction characteristic results show that methane addition and equivalence ratio have significant impact on the extinction limits of the stretched flames. With more methane in the ammonia/methane fuel blends, the flame sustainability to high stretch rate substantially increases. Flame structures of the stretched flames were then investigated to have a deep insight into the combustion process of the ammonia/methane premixed combustion. Results show that temperature, heat release rate and important intermediate radicals of the flames are enhanced. However, the considerably increased carbon oxides and nitrogen oxides emissions suggest emission reduction is a key issue in the ammonia/methane combustion process. Pathway and sensitivity analyses reveal the chemistry of NOx emission characteristics of different ammonia/methane flames.
Energy storage is one of the highest priority challenges in transitioning to a low-carbon economy. Fluctuating, intermittent primary renewable sources such as wind and solar require low-carbon storage options to enable effective load matching, ensuring security of supply. Chemical storage is one such option, with low or zero carbon fuels such as hydrogen, alcohols and ammonia having been proposed. Ammonia provides zero-carbon hydrogen storage whilst offering liquefaction at relatively low pressures and atmospheric temperatures, enabling ease of transportation in a pre-existing infrastructure. Ammonia can also be used directly as a fuel in power plants such as gas turbines to avoid complete conversion back to hydrogen. It is a relatively unreactive fuel, and so it is of interest to explore the potential utilisation of ammonia/hydrogen mixtures. Hence, the goal of this paper is to provide a first assessment of the suitability of a chosen 70%NH3 30%H2 (%vol) blend for utilisation within a gas turbine environment, based on primary combustion diagnostics including combustion stability – via OH chemiluminescence - and emissions (NOx and NH3). An established optical generic swirl-burner enabled studies of the influence of equivalence ratio (φ > 1), ambient temperature (<484 ± 10 K) and bypass air, with a focus on NOx reduction, one of the main challenges for ammonia combustion. A numerical GT cycle model is developed alongside the experimental investigation. The results demonstrate that the blend has considerable potential as a fuel substitute with reasonable combustion stability and significant reduction of emissions for the cases without bypass air, due to increased chemical reactivity of unburned ammonia. However, emissions are still above those recommended for gas turbine cycles, with a theoretical cycle that still produces low efficiencies compared to DLN methane, highlighting the requirement for new injection techniques to reduce NOx/unburned NH3 in the flue gases whilst ensuring increased power outputs.
Among the undesirable quality incidents in the cold rolling process of strip products, strip snap could result in yield loss and reduced work speed. Therefore, it is necessary to reveal the factors influencing the occurrence of this failure for quality improvement. In this study, a data analytics approach was applied with the aim of determining relevant variables affecting snap occurrence. To validate this approach, a case study was conducted based on real-world data collected from an electrical steel reversing mill. The results suggested a selection of variables to characterize the quality issue of strip snap in the cold rolling process. This quality characterization study was performed as the preliminary stage of a quality improvement task.
As an undesired and instantaneous failure in the production of cold-rolled strip products, strip breakage results in yield loss, reduced work speed and further equipment damage. Typically, studies have investigated this failure in a retrospective way focused on root cause analyses, and these causes are proven to be multi-faceted. In order to model the onset of this failure in a predictive manner, an integrated multi-source feature-level approach is proposed in this work. Firstly, by harnessing heterogeneous data across the breakage-relevant processes, blocks of data from different sources are collected to improve the breadth of breakage-centric information and are pre-processed according to its granularity. Afterwards, feature extraction or selection is applied to each block of data separately according to the domain knowledge. Matrices of selected features are concatenated in either flattened or expanded manner for comparison. Finally, fused features are used as inputs for strip breakage prediction using recurrent neural networks (RNNs). An experimental study using real-world data instantaneous effectiveness of the proposed approach.
Zero-carbon fuels such as hydrogen and ammonia play a pivotal role in the energy transition by offering cleaner alternatives to natural gas (methane), especially in industrial combustion systems. Binary and ternary blends of these fuels offer a transitionary, low-carbon solution in the near future. Laminar burning velocity (LBV), as a fundamental combustion property, is significantly different for ammonia, hydrogen, and methane. Although the LBV of binary blends of these fuels is well-studied, ternary blends have not been extensively studied. In this study, the primary objective is to employ a simple ensemble learning method to predict the LBV of ternary ammonia/hydrogen/methane/air mixtures. The training dataset consists of experimental data sourced from a large number of publications (3,846 data points), as well as synthetic data generated by 1D freely propagating premixed flame simulations in Cantera using a detailed chemical kinetic model. Three machine learning algorithms, namely artificial neural networks, gaussian process regression, and extreme gradient boosting trees are trained and optimised. Then, a simple ensemble averaging method is used to reduce overfitting and improve robustness. The ensemble model achieves coefficient of determination (R2) of 0.991 on the test set with an inference time that is approximately 8,000 times faster than the 1D simulation run time. The ensemble model is capable of predicting LBVs of ammonia/hydrogen/methane/air mixtures for T=[295–756K], P=[1–10bar], ϕ=[0.5–1.8] across all possible blending ratios.
This study numerically investigates the potential use of ammonia as a chemical inhibitor in hydrogen/air premixed combustion systems, aiming to reduce the risks associated with hydrogen use. Various flame configurations are explored using zero-dimensional and one-dimensional reacting models, including the homogeneous reactor, perfectly stirred reactor, unstrained premixed flame (freely propagating and quenching), and strained premixed flame in counterflow. The impact of ammonia addition on key flame behaviors, such as the ignition delay time, laminar burning velocity, flame thickness, and extinction strain rate, is evaluated. Results show that adding 20% ammonia achieves up to 50% inhibition efficiency across these metrics. Furthermore, heat release rate analysis is conducted for unstrained premixed flames during both free propagation and head-on quenching. It is found that the controlling elementary reactions contributing to the heat release rate differ significantly between these two phases. The study also examines the environmental implications of ammonia addition, particularly regarding NOx and N2O emissions. While pure stoichiometric hydrogen/air combustion produces minimal NOx and N2O, the addition of ammonia results in emissions on the order of O(103) ppm or higher, indicating significant environmental challenges. This dual focus on inhibition and emission informs future strategies to balance the efficiency and environmental impact of hydrogen combustion systems. This study emphasizes the importance of experimental validation and encourages future experiments to collect data for further research.
