Real-time prediction of lean blowout using chemical reactor network

Abstract

The lean blow-out (LBO) of gas turbine combustors is a concern that can limit the rate of descent for an aircraft, the maneuverability of military jets, and cause a costly and time-intensive reignition of land-based gas turbines. This work explores the feasibility of a model-based combustor monitoring for the real-time prediction of combustion system proximity to LBO. The approach makes use of (1) iv

Low-Order Reactor-Network-Based Prediction of Pollutant Emissions Applied to FLOX® Combustion

“…Bhargava et al [16] x Single-nozzle experiments and numerical modeling, study of pressure effects Falcitelli et al [17] x NOx prediction in industrial energy combustion systems Falcitelli et al [18] x NOx prediction in industrial furnaces, NOx reduction techniques Falcitelli et al [19] x Methodical assessment of ERN pollutant prediction from CFD Mohamed et al [20] x NOx, UHC, and CO for gas turbine combustion (model only) Novosselov et al [21] x NOx and CO in a swirl-stabilized burner Russo et al [22] x NOx and CO in a recuperated micro gas turbine Benedetto et al [23] x Industrial furnace facilities Fichet et al [24] x NOx emissions in a staged gas turbine combustor Lee et al [25] x NOx emissions in a simplified combustor, GE7FA gas turbine Lyra and Cant [26] x NOx emissions in a high-pressure nozzle test case De Toni et al [27] x NOx emissions in a BERL 300 kW furnace combustor Colorado et al [28] x NOx emissions in a C60 gas turbine combustor Nguyen [29] x NOx emissions for a generic gas turbine burner using Chemkin Nguyen et al [30] x NOx prediction with Chemkin for a gas turbine combustor Innocenti et al [31] x NOx and CO in a swirl-stabilized aero-engine combustor Kaluri et al [32] x Real-time reactor network for LBO predictions Nguyen [2] x Emissions in a swirl-stabilized combustor using Chemkin Gupta et al [33] x Real-time reactor network for LBO predictions Perpignan et al [34] x NOx and CO emissions at flameless oxidation combustion Zhang et al [35] x NOx and CO emissions in a swirl-stabilized aero-engine combustor sector Surprisingly, the degree of model fidelity does not necessarily increase with time. Many early studies use automated algorithms for network extraction from CFD data [17][18][19]21], whereas few rely on using CFD results as guidance for manual network creation only [22,23,27].…”

Flame Extinction and Re-Ignition in a Swirl Stabilized Prevaporized Liquid Fuel Flame Close to Lean Blow-Out

“…Since this process is highly dynamic and occurs on timescales on the order of milliseconds, optical diagnostics with high spatio-temporal resolution are necessary in order to fully resolve this phenomenon. In recent years, different approaches for online prediction of the LBO were discussed, for example based on chemiluminescence sensors [13,14] or sensors in combination with a chemical reactor network [15]. However, prediction of the lean blow-out limit during the design process or for different fuels remains challenging.…”

Temperature control of real‐time identified fixed bed reactor by adaptive sliding mode control equipped with Arduino in Matlab

“…A performance comparison with Proportional Integral (PI) controller was shown by them. Kaluri et al predicted the proximity of lean blowout in combustion systems using real‐time temperature measurements in chemical reactor network. Sinha et al suggested a control scheme, which ensures the stability of Continuous Stirred Tank Reactor (CSTR) under closed‐loop condition.…”