C. Dopazo

Modelling the Temporal Evolution of a Reduced Combustion Chemical System With an Artificial Neural Network

The present work introduces a way of embedding a combustion chemical system in a neural network, in such a way that it can be used, with considerable CPU time and RAM memory savings, in fluid-flow-simulation codes. The system is composed of four neural networks, with three of them simulating the evolution of the reactive species and one providing density and temperature as a function of composition. The performance in terms of accuracy of the networks is assessed by comparison with the results of the direct integration of the thermochemical system for a large number of random samples. Error measurements are reported, and sample evolutions of the chemical system with both methods are compared. It can be summarized that the results of this exercise are satisfactory, and the CPU-time and memory savings encouraging.

An economical strategy for storage of chemical kinetics: Fitting in situ adaptive tabulation with artificial neural networks

Reducing the computational time of chemical kinetics is essential for implementation of realistic chemistry into large-scale numerical simulations. Among the storage-based techniques, the in situ adaptive tabulation (ISAT) method features storing and retrieving data during the simulation: therefore, only the needed data are stored. As ISAT is based on linear approximation, the required storage can grow rapidly when a wide range of chemical states is involved, such as occurs in turbulent flames. An economical strategy for storing chemical kinetics data is proposed here by fitting results obtained from ISAT with artificial neural networks (ANN). This concept is explored in this study using a partially stirred reactor (PaSR) with two reduced chemical mechanisms of 9 and 17 reactive scalars. The performance of the ANN fitting is assessed on the basis of accuracy, memory, and CPU time. Test results based on PaSR demonstrate that a significant saving in memory can be realized with the ANN. Both the accuracy and CPU time with the ANN are found comparable with those of ISAT, suggesting great promise for use of ANN in large-scale computations.

Computational Evaluation of Low NOx Operating Conditions in Arch-Fired Boilers

In the present paper, a computational model is used to simulate the aero-dynamic, thermal, and chemical conditions inside an arch-fired coal boiler. The model is based on the Eulerian-Eulerian concept, in which Eulerian conservation equations are solved both for the gas and the particulate phases. A NO{sub x} formation and destruction submodel is used to calculate the local concentration of NO. The model is used to simulate a range of operating conditions in an actual, 350 MW, arch-fired boiler, with the aim of reducing, using primary measures, the emissions of NO{sub x}. The model results shed some light on the relevant NO{sub 2}-formation mechanisms under the several operating conditions. Furthermore, they correlate well quantitatively with the available field measurements at the plant, and reproduce satisfactorily the tendencies observed under the different operating modes.

The instability growth leading to a liquid sheet breakup

The instability growth leading to a liquid sheet breakup has been studied with the objective of improving the understanding of the fundamental mechanisms of atomization. A three-dimensional Lagrangian code based on vortex dynamics methods has been implemented to track the air/liquid interfaces treated as inviscid vortex sheets. The results of these numerical simulations indicate a possible explanation for the presence of transverse and longitudinal filaments observed in liquid sheet air-assisted atomization experiments.

Investigation of low-NOx strategies for natural gas combustion

Abstract Different NOx control techniques have been investigated and implemented in a natural gas burner at two different scales. Both fuel- and air-staging strategies can be implemented in a single burner, by properly adjusting some of the available settings. Experiments were performed on a semi-industrial scale (thermal input 0.3–0.33 MW) in a laboratory furnace. The study included a thorough parametric analysis to identify the optimum operating conditions for minimum NOx emission. In addition, some detailed in-flame measurements provided valuable information for the understanding of the relevant phenomena. In a second stage, a prototype of the burner was tested in a boiler (6.5–17 MW(t)) to check the validity of the conclusions obtained on the smaller scale. The tests demonstrated that the new burner can reduce NOx emissions by > 70% with respect to the values obtained with the burner originally installed in the same boiler. Comparison between the measurements performed on both scales also provided valuable information regarding the effects of scaling on the performance of low-NOx burners. A scaling law intermediate between the constant-velocity and residence-time criteria was selected in one of the test series, leading to a remarkable similarity of the results obtained on the two scales, in terms of both NOx emissions and qualitative burner performance.