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Chemistry evaluation is a bottleneck to computational fluid dynamics (CFD) simulations of many real-life problems such as propulsion system design, engine diagnostics, and atmospheric modeling. In this work, we study approach for accelerating chemical kinetics calculations using artificial neural networks (ANNs) on the example of combustion of a hydrogen–air mixture. This work carries out a detailed exploratory study of the optimal design of a fully connected neural network, including the number of network parameters, number of layers as well as used activation function. Part of the work is also dedicated to investigation and optimization of network training process itself. Comparison with the results of other works, bringing some unification to the widely disparate reported results, is also performed. Links to the used datasets and the resulting neural network are provided.

As a fuel commonly used by air heaters for ground tests of high-speed aircraft, the combustion mechanism of ethanol in air heaters is still unclear, especially the atomic-level chemical mechanism of important intermediate products represented by hydrogen in maintaining stable flame combustion needs to be further studied. In this paper, the combustion process of ethanol/oxygen mixtures under different hydrogen additions was simulated using the reactive force field (ReaxFF) molecular dynamics (MD) method. The results show that increasing the proportion of hydrogen in the mixed gas can not only reduce the ignition delay time of ethanol combustion but also promote the consumption of ethanol and accelerate the progress of the combustion reaction. It was also found that hydrogen and ethanol produced a competitive relationship for oxygen, which changed the ideal stoichiometric ratio (1:3) of complete combustion of ethanol and oxygen and significantly affected the intermediate products and reaction paths of ethanol and oxygen. In addition, increasing the combustion reaction temperature will affect the reaction path of ethanol/oxygen, and the number of intermediate products produced will reach the peak faster and then decompose. Theoretical support for a deeper understanding of the intermediate product hydrogen in the combustion of the three-component air heater of ethanol/liquid oxygen/air and also for improving the combustion efficiency of liquid rocket engine fuel are provided in this study.

The aim of the present study is to calculate the process of detonation combustion of gas mixtures in engines. Development and verification of 3D transient mathematical model of chemically reacting gas mixture flows incorporating hydrogen was performed. Development of a computational model based on the mathematical one for parallel computing on supercomputers incorporating CPU and GPU units was carried out. Investigation of the influence of computational grid size on simulation precision and computational speed was performed. Investigation of calculation runtime acceleration was carried out subject to variable number of parallel threads on different architectures and implying different strategies of parallel computation.

In this study, we consider problems of thermal ignition and flame front propagation. Ordinary and partial differential equations with proper initial and boundary conditions are solved for generic cases. Numerical schemes are tested and results are discussed. Comparisons with the literature for benchmark cases are favorable.

Y₂O₃:Eu nanopowders were synthesized by urea combustion method containing different concentration of Eu. The synthesized Y₂O₃:Eu nanopowders were characterized by X-ray diffractometry, scanning electron microscopy (SEM), transmission electron microscopy (TEM), high resolution transmission electron microscopy (HRTEM), selected area electron diffraction (SAED), energy dispersive X-ray analysis (EDX) and photoluminescence spectroscopy (PL). The particle size was calculated to be in the range of 15–30 nm using Scherrer's formula. The Ia-3 structure of synthesized Y₂O₃:Eu nanopowders were confirmed with X-ray diffractometry. The crystallinity of Y₂O₃:Eu nanopowders were confirmed by SAED and TEM images. The ⁵D₀–∑⁷F_J (J = 0, 1, 2, 3) and ⁵D₁–⁷F₁ transitions bands were observed at 575–650 and 530–550 ranges in the photoluminescence spectrum. The concentration quenching was estimated to be about 5 mol% of Eu. The best chromaticity to the standard red color was observed with the sample containing 3 mol% of Eu.