Ammonia as an alternative fuel and hydrogen carrier has received increased attention in recent years. To explore the potential of co-firing ammonia with methane for power generation, studies involving robust mathematical analyses are required to progress towards industrial implementation. To explore a best suited mechanism for ammonia/methane combustion in gas turbines, five different detailed mechanisms were compared to identify their accuracy to represent the reaction kinetics under real gas turbine combustor conditions. Ignition delay time was compared with recent literature showing that the mechanisms of Tian and Teresa exhibit the best accuracy over a large range of conditions. A 1D simulation was also conducted using a Chemical Reactor Network (CRN) model, thus providing a relatively quick estimation of the combustion mechanisms under swirling combustion conditions. The simulation of NOx emissions indicates that Tian mechanism has better performance than the others compared. Hence, the Tian mechanism was selected as the most appropriate for further studies of ammonia/methane combustion through a set of experiments carried out at various equivalence ratios and pressure conditions. Finally, sensitivity and pathway analyses were also performed to identify important reactions and species under high pressurized conditions, areas that need more attention for model development and emission control in future studies.
Strip breakage is an undesired production failure in cold rolling. Typically, conventional studies focused on cause analyses, and existing data-driven approaches only rely on a single data source, resulting in a limited amount of information. Hence, we propose an approach for modelling breakage using multiple data sources. Many breakage-relevant features from multiple sources are identified and used, and these features are integrated using a breakage-centric ontology which is then used to create knowledge graphs. Through ontology construction and knowledge embedding, a real-world study using data from a cold-rolled strip manufacturer was conducted using the proposed approach.
The present study investigates the usage of rotating cylinders to generate gas circulation inside high-temperature coil annealing furnaces during the annealing treatment of grain-oriented electrical steel. This technique has been investigated to reduce temperature differentials (hotspots) within the furnace space, a phenomenon that occurs due to extremely high temperatures, the static nature of the gas inside of the furnace and long operation conditions. Finite volume numerical simulation using ANSYS Fluent was performed to test the validity of the proposed technique. The numerical results showed fluctuations in velocity magnitude of the fluid in comparison with a case when the technique was not employed. This is because of the vortex generation under the effect of the cylinder rotation. The generation of turbulence enhances gas-mixing quality, and thus it would save a great amount of energy required for the process, producing a product with desired magnetic properties at lower cost.
No abstract is provided for this article.
Ammonia utilisation in internal combustion engines has attracted wide interest due to the current trend toward decarbonisation, as ammonia is a zero-carbon fuel with different combustion properties to hydrocarbons. The laminar burning velocity (LBV) is a fundamental property of fuels with a significant effect on the combustion processes and accurate calculations and measurements of the LBV over a wide range of fuel blends, pressures and flow conditions is a time-consuming, complicated procedure. The main goal of the current study is to predict the LBV of NH3/H2/air mixtures using a hybrid machine learning (ML) approach based on a training dataset consisting of both the experimental LBV values and additional data obtained from numerical simulations with a detailed kinetic model. Initial ML model training data is collected from existing experimental LBV in the literature for NH3/H2/air mixtures. Then, synthetic data is generated using one-dimensional (1D) simulations to reduce data inhomogeneity and increase accuracy of the ML model. In total, 24 different ML algorithms are tested to find the best model both for the experimental and the hybrid dataset. The results suggest that both Gaussian Process Regression (GPR) and Neural Networks (NNs) can be utilised to predict LBV of NH3/H2/air mixtures with reasonable accuracy. The hybrid ML model achieved a coefficient of determination of R2 = 0.998. Finally, hybrid ML model hyperparameters are optimised to achieve a coefficient of determination of R2 = 0.999. It was also found that ML can speed up LBV computation from 9500 to 27000 times compared to 1D simulations with a reduced mechanism.
No abstract is provided for this article.
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.
Practical implementation of alternative fuels in gas turbine facilities is a challenging step towards cleaner and more responsible energy production. Despite numerous technical, economical and legal obstacles, possibilities for partial or complete substitution of fossil fuels are still subject of profound research. From all possible solutions, one with high acceptance is the symbiosis of existing gas turbine technologies and new ways of waste biomass energy utilization through firing or co – firing of biomass gasification gas. Therefore, the practical implementation of corn cob gasification gas with CO2 recirculation in gas turbines is analyzed in this paper. The followed methodology approaches this solution through two different scenarios each with 5 different cases. In the first scenario fuel mass flows are kept constant regardless of the fuel quality change consequence of the corn cob gas share, while in the second scenario fuel volume flows are assumed constant. Fuel quality refers to fuel composition which affects heat capacity, as well as physical and chemical characteristics of fuel. Impact of fuel composition changes on combustion product characteristics was analyzed using CHEMKIN PRO with GRI–Mech 3.0. Finally, fuel quality impacts on a gas turbine power plant performance are analyzed using a numerical model of a physical cycle that enables the simulation of a 3.9 MW experimentally correlated gas turbine. The results show that utilization of corn cob gasification gas is possible through co-firing with natural gas with acceptable values without modification of the fuel system or gas turbine.
This paper aims to conduct a parametric study for five gas turbine cycles (namely, simple, heat exchanged, free turbine and simple cycle, evaporative, and humidified) using a CO2-argon-steam-oxyfuel (CARSOXY) mixture as a working fluid to identify their optimal working conditions with respect to cycle efficiency and specific work output. The performance of the five cycles using CARSOXY is estimated for wet and dry compression, and a cycle is suggested for each range of working conditions. The results of this paper are based on MATLAB codes, which have been developed to conduct the cycle analysis for CARSOXY gas turbines, assuming a stoichiometric condition with an equivalence ratio of 1.0. Analyses are based on the higher heating value (HHV) of methane as fuel. This paper also identifies domains of operating conditions for each cycle, where the efficiency of CARSOXY cycles can be increased by up to 12% compared to air-driven cycles. The CARSOXY heat exchanged cycle has the highest efficiency among the other CARSOXY cycles in the compressor pressure ratio domain of 2–3 and 6–10, whereas, at 3–6, the humidified cycle has the highest efficiency. The evaporative cycle has intermediate efficiency values, while the simple cycle and the free turbine-simple cycle have the lowest efficiencies amongst the five cycles. Additionally, a 10% increase in the cycle efficiency can be theoretically achieved by using the newly suggested CARSOXY blend that has the molar fractions of 47% argon, 10% carbon dioxide, 10% H2O, and 33% oxyfuel at low compressor inlet temperatures, thus theoretically enabling the use of carbon capture technologies.
Flow past a circular cylinder is a problem for understanding flow around bluff bodies. This flow has been studied both experimentally and numerically of laminar infinite flow of viscous incompressible fluid around a rotating circular cylinder at Reynolds number 80,120,160 and dimensionless rotation rate, α , (ratio of cylinder surface speed to the free stream velocity) varying from 0 to 6 has been carried out. Navier–Stokes and continuity equations were solved numerically by using finite volume technique is conducted with ANSYS CFX 15 package program. High Speed Photography and LDV, present new experimental results for correlation purposes, captured the flow profile. Rotation can be used as a drag reduction technique. Comparison with previous studies showed good agreement.
