Hotspot auto-ignition induced detonation development: emphasis on energy density and chemical reactivity

Author(s):  
Jiaying Pan ◽  
Lei Wang ◽  
Yu He ◽  
Haiqiao Wei ◽  
Gequn Shu ◽  
...  
2018 ◽  
Vol 8 (12) ◽  
pp. 2667
Author(s):  
Antonio Mariani ◽  
Andrea Unich ◽  
Mario Minale

The paper describes a numerical study of the combustion of hydrogen enriched methane and biogases containing hydrogen in a Controlled Auto Ignition engine (CAI). A single cylinder CAI engine is modelled with Chemkin to predict engine performance, comparing the fuels in terms of indicated mean effective pressure, engine efficiency, and pollutant emissions. The effects of hydrogen and carbon dioxide on the combustion process are evaluated using the GRI-Mech 3.0 detailed radical chain reactions mechanism. A parametric study, performed by varying the temperature at the start of compression and the equivalence ratio, allows evaluating the temperature requirements for all fuels; moreover, the effect of hydrogen enrichment on the auto-ignition process is investigated. The results show that, at constant initial temperature, hydrogen promotes the ignition, which then occurs earlier, as a consequence of higher chemical reactivity. At a fixed indicated mean effective pressure, hydrogen presence shifts the operating range towards lower initial gas temperature and lower equivalence ratio and reduces NOx emissions. Such reduction, somewhat counter-intuitive if compared with similar studies on spark-ignition engines, is the result of operating the engine at lower initial gas temperatures.


Author(s):  
Dexiang Gao ◽  
Xingyu Tang ◽  
Xuan Wang ◽  
Xin Yang ◽  
Peijie Zhang ◽  
...  

Pressure-induced phase transition and polymerization of nitrogen-rich molecules are widely focused due to its extreme importance for the development of green high energy density materials. Here, we present a study...


2000 ◽  
Vol 122 (19) ◽  
pp. 4756-4762 ◽  
Author(s):  
P. Pérez ◽  
Y. Simón-Manso ◽  
A. Aizman ◽  
P. Fuentealba ◽  
R. Contreras

Author(s):  
A. M. Bradshaw

X-ray photoelectron spectroscopy (XPS or ESCA) was not developed by Siegbahn and co-workers as a surface analytical technique, but rather as a general probe of electronic structure and chemical reactivity. The method is based on the phenomenon of photoionisation: The absorption of monochromatic radiation in the target material (free atoms, molecules, solids or liquids) causes electrons to be injected into the vacuum continuum. Pseudo-monochromatic laboratory light sources (e.g. AlKα) have mostly been used hitherto for this excitation; in recent years synchrotron radiation has become increasingly important. A kinetic energy analysis of the so-called photoelectrons gives rise to a spectrum which consists of a series of lines corresponding to each discrete core and valence level of the system. The measured binding energy, EB, given by EB = hv−EK, where EK is the kineticenergy relative to the vacuum level, may be equated with the orbital energy derived from a Hartree-Fock SCF calculation of the system under consideration (Koopmans theorem).


Author(s):  
Thomas W. Shattuck ◽  
James R. Anderson ◽  
Neil W. Tindale ◽  
Peter R. Buseck

Individual particle analysis involves the study of tens of thousands of particles using automated scanning electron microscopy and elemental analysis by energy-dispersive, x-ray emission spectroscopy (EDS). EDS produces large data sets that must be analyzed using multi-variate statistical techniques. A complete study uses cluster analysis, discriminant analysis, and factor or principal components analysis (PCA). The three techniques are used in the study of particles sampled during the FeLine cruise to the mid-Pacific ocean in the summer of 1990. The mid-Pacific aerosol provides information on long range particle transport, iron deposition, sea salt ageing, and halogen chemistry.Aerosol particle data sets suffer from a number of difficulties for pattern recognition using cluster analysis. There is a great disparity in the number of observations per cluster and the range of the variables in each cluster. The variables are not normally distributed, they are subject to considerable experimental error, and many values are zero, because of finite detection limits. Many of the clusters show considerable overlap, because of natural variability, agglomeration, and chemical reactivity.


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