Quantitative Assessment of Flame Stability Through Image Processing and Spectral Analysis

This paper experimentally investigates two generalized methods, i.e., a simple universal index and oscillation frequency, for the quantitative assessment of flame stability at fossil-fuel-fired furnaces. The index is proposed to assess the stability of flame in terms of its color, geometry, and luminance. It is designed by combining up to seven characteristic parameters extracted from flame images. The oscillation frequency is derived from the spectral analysis of flame radiation signals. The measurements involved in these two methods do not require prior knowledge about fuel property, burner type, and other operation conditions. They can therefore be easily applied to flame stability assessment without costly and complex adaption. Experiments were carried out on a 9-MW heavy-oil-fired combustion test rig over a wide range of combustion conditions including variations in swirl vane position of the tertiary air, swirl vane position of the secondary air, and the ratio of the primary air to the total air. The impact of these burner parameters on the stability of heavy oil flames is investigated by using the index and oscillation frequency proposed. The experimental results obtained demonstrate the effectiveness of the methods and the importance of maintaining a stable flame for reduced NOx emissions. It is envisaged that such methods can be easily transferred to existing flame closed-circuit television systems and flame failure detectors in power stations for flame stability monitoring

A Locally Adaptive Shrinkage Approach to False Selection Rate Control in High-Dimensional Classification

The uncertainty quantification and error control of classifiers are crucial in many high-consequence decision-making scenarios. We propose a selective classification framework that provides an indecision option for any observations that cannot be classified with confidence. The false selection rate (FSR), defined as the expected fraction of erroneous classifications among all definitive classifications, provides a useful error rate notion that trades off a fraction of indecisions for fewer classification errors. We develop a new class of locally adaptive shrinkage and selection (LASS) rules for FSR control in the context of high-dimensional linear discriminant analysis (LDA). LASS is easy-to-analyze and has robust performance across sparse and dense regimes. Theoretical guarantees on FSR control are established without strong assumptions on sparsity as required by existing theories in high-dimensional LDA. The empirical performances of LASS are investigated using both simulated and real data

Electrochemical interfacial influences on deoxygenation and hydrogenation reactions in CO reduction on a Cu(100) surface.

Electroreduction of CO2 to hydrocarbons on a copper surface has attracted much attention in the last few decades for providing a sustainable way for energy storage. During the CO2 and further CO electroreduction processes, deoxygenation that is C-O bond dissociation, and hydrogenation that is C-H bond formation, are two main types of surface reactions catalyzed by the copper electrode. In this work, by performing the state-of-the-art constrained ab initio molecular dynamics simulations, we have systematically investigated deoxygenation and hydrogenation reactions involving two important intermediates, COHads and CHOads, under various conditions of (i) on a Cu(100) surface without water molecules, (ii) at the water/Cu(100) interface and (iii) at the charged water/Cu(100) interface, in order to elucidate the electrochemical interfacial influences. It has been found that the electrochemical interface can facilitate considerably the C-O bond dissociation via changing the reaction mechanisms. However, C-H bond formation has not been affected by the presence of water or electrical charge. Furthermore, the promotional roles of an aqueous environment and negative electrode potential in deoxygenation have been clarified, respectively. This fundamental study provides an atomic level insight into the significance of the electrochemical interface towards electrocatalysis, which is of general importance for understanding electrochemistry