Oxy-fuel combustion of solid fuels

Soot processes in compression ignition engines

Oxy-fuel coal combustion—A review of the current state-of-the-art

Emission control of nitrogen oxides in the oxy-fuel process

Biodiesel is receiving increasing attention each passing day because of its fuel properties and compatibility with the petroleum-based diesel fuel (PBDF). Therefore, in this study, the prediction of the engine performance and exhaust emissions is carried out for five different neural networks to define how the inputs affect the outputs using the biodiesel blends produced from waste frying palm oil. PBDF, B100, and biodiesel blends with PBDF, which are 50% (B50), 20% (B20) and 5% (B5), were used to measure the engine performance and exhaust emissions for different engine speeds at full load conditions. Using the artificial neural network (ANN) model, the performance and exhaust emissions of a diesel engine have been predicted for biodiesel blends. According to the results, the fifth network is sufficient for all the outputs. In the fifth network, fuel properties, engine speed, and environmental conditions are taken as the input parameters, while the values of flow rates, maximum injection pressure, emissions, engine load, maximum cylinder gas pressure, and thermal efficiency are used as the output parameters. For all the networks, the learning algorithm called back-propagation was applied for a single hidden layer. Scaled conjugate gradient (SCG) and Levenberg-Marquardt (LM) have been used for the variants of the algorithm, and the formulations for outputs obtained from the weights are given in this study. The fifth network has produced R^2 values of 0.99, and the mean % errors are smaller than five except for some emissions. Higher mean errors are obtained for the emissions such as CO, NO"x and UHC. The complexity of the burning process and the measurement errors in the experimental study can cause higher mean errors.

Prediction of performance and exhaust emissions of a diesel engine fueled with biodiesel produced from waste frying palm oil

A noncontact, color-band pyrometer, based on widely available, inexpensive digital imaging devices, such as commercial color cameras, and capable of pixel-by-pixel resolution of particle-surface temperature and emissivity is demonstrated and described. This diagnostic instrument is ideally suited to many combustion environments. The devices used in this method include color charge-coupled device (CCD), or complementary metal oxide semiconductor (CMOS) digital camera, or any other color-rendering camera. The color camera provides spectrally resolved light intensity data of the image, most commonly for three color bands (Red, Green, and Blue,), but in some cases for four or more bands or for a different set of colors. The CCD or CMOS sensor-mask combination has a specific spectral response curve for each of these color bands that spans the visible and often near infrared spectral range. A theory is developed, based on radiative heat transfer and camera responsivity that allows quantitative surface temperature distribution calculation, based on a photograph of an object in emitted light. Particle surface temperature calculation is corrected by heat transfer analysis with reflection between the particle and reactor wall for particles located in furnace environments, but such corrections lead to useful results only when the particle temperature is near or below the wall temperatures. Wood particle-surface temperatures were measured with this color-band pyrometry during pyrolysis and combustion processes, which agree well with thermocouple measured data. Particle-surface temperature data simultaneously measured from three orthogonal directions were also mapped onto the surface of a computer generated 3-D (three-dimensional) particle model. © 2008 American Institute of Chemical Engineers AIChE J, 2009

Particle surface temperature measurements with multicolor band pyrometry

Calibration of an RGB, CCD Camera and Interpretation of its Two-Color Images for KL and Temperature

Measurement of nitrogen evolution in a staged oxy-combustion coal flame

Numerous investigations have been conducted to determine the effect of fuel composition and molecular structure on particulate emissions using exhaust gas analysis, but relatively few measurements have been obtained in-cylinder or under conditions where fuel effects can be isolated from other variables. Recent work has shown that the amount of air entrained upstream of the lift-off length is critical to soot formation and therefore must be controlled when making relative comparisons of soot formed from various fuels. In this work, dimethoxymethane was used as the base fuel to produce a non-sooting flame with relatively constant lift-off length in a constant volume combustion vessel at 1000 K, and a density of 16.6 kg/m 3 . A second fuel was then mixed into the dimethoxymethane (DMM) to determine a point at which soot formation begins. Line-of-sight extinction measurements of soot produced in binary fuel mixture flames was used as the primary diagnostic tool to determine if a correlation existed between soot and fuel properties such as the number of C-C bonds, C/H ratio or C/O ratio. Tests to date show that fuels with different molecular structures have the same incipient soot limit at a C/H ratio near 0.4, while further increases in C/H ratio produce a linear increase in soot concentration, but with a different slope for each fuel. Soot was first formed with the addition of 10 vol% toluene to DMM, while it took 40 vol% undecane and 50 vol% n-heptane. The incipient soot oxygen-to-carbon ratio at the assumed 12 mm lift-off length was 0.6 for toluene, 0.37 for undecane, and 0.3 for n-heptane. These data indicate that the aromatic toluene has a greater tendency to produce soot than the alkanes.

Fuel Composition and Molecular Structure Effects on Soot Formation in Direct-Injection Flames Under Diesel Engine Conditions

A new approach to modeling NOX under oxy-fuel combustion conditions in a simple staged-oxidizer flow field is presented. The approach is centered on the combination of devolatilization and char oxidation models with a detailed kinetic mechanism for light hydrocarbon combustion. NOX chemistry is included by the user's selection of the detailed mechanism, while the devolatilization model consists of the chemical percolation devolatilization (CPD) model modified to be independent of oxidizer composition. Literature-based correlations provide elemental composition of the volatiles. Model predictions were compared to experimental measurements with good agreement in several respects. The model provides insights for the interpretation of experimental oxy-fuel combustion NOX results, and recommendations are given for computational fluid dynamics (CFD) modeling of NOX in oxy-fuel combustion.

Andrew J. Mackrory

Papers

Particle surface temperature measurements with multicolor band pyrometry

Calibration of an RGB, CCD Camera and Interpretation of its Two-Color Images for KL and Temperature

Measurement of nitrogen evolution in a staged oxy-combustion coal flame

Fuel Composition and Molecular Structure Effects on Soot Formation in Direct-Injection Flames Under Diesel Engine Conditions

Predictions of NOX in a Laboratory Pulverized Coal Combustor Operating under Air and Oxy-Fuel Conditions