John Hunter Mack

A far ultraviolet photometer for space research

Abstract A photometer for use in the wavelength region from 100 to 1300 A has been developed. Specific bands within this region can be isolated by combining the spectral response of individual solar blind photocathodes with the transmission qualities of various thin metallic films. A continuous channel electron multiplier is used as a low background, high gain charge amplifier in the device. Each of these components is discussed in turn with emphasis placed on those characteristics which have special relevance to space borne instrumentation. Two examples of instruments employing these components are given, one a device to measure the resonantly scattered hydrogen and helium radiation in the upper atmosphere, and the other a device to measure the far u.v. photon flux generated in an aurora.

Effect of hydrogen peroxide addition to methane fueled homogeneous charge compression ignition engines through numerical simulations

The effect of the direct injection of hydrogen peroxide into a port-injected methane fueled homogeneous charge compression ignition engine was investigated numerically. The injection of aqueous hydrogen peroxide was implemented as a means of combustion phasing control. A single-cylinder homogeneous charge compression ignition engine (2.43 L Caterpillar) was modeled using the Cantera 2.0 flame code toolkit, the GRI-Mech 3.0 chemical reaction mechanism, and a single-zone slider-crank engine model. Start of injection timing and the amount of injected hydrogen peroxide were manipulated to achieve desired combustion phasing under a wide range of intake temperatures. As the concentration of hydrogen peroxide is increased, the combustion phasing is advanced up to 22° for the conditions investigated in this study. This advancing effect is most pronounced at small concentrations (<10 g H2O2/kg CH4) and early injection timings (start of injection < 25° before top dead center). The model suggests hydrogen peroxide can be introduced as a means of combustion phasing control while maintaining the low emissions and peak in-cylinder pressures inherent in homogeneous charge compression ignition engines.

The spectra of ten galactic X-ray sources in the southern sky.

Data on ten galactic X-ray sources were obtained during a rocket flight from Brazil in June 1969. Detailed spectra of these sources have been compared with bremsstrahlung, black body, and power law models, each including interstellar absorption. Six of the sources were fitted well by one or more of these models. In only one case were the data sufficient to distinguish the best model. Three of the sources were not fitted by any of the models, which suggests that more complex emission mechanisms are applicable. A comparison of our results with those of previous investigations provides evidence that five of the sources vary in intensity by a factor of 2 or more, and that three have variable spectra. New or substantially improved positions have been derived for four of the sources observed.

Artificial Neural Network for Predicting Cetane Number of Biofuel Candidates Based on Molecular Structure

The production of next-generation biofuels is being explored through a variety of chemical and biological approaches, all aiming at lowering costs and increasing yields while producing viable alternatives to gasoline or diesel fuel. Chemical synthesis can lead to a huge variety of different fuels and the guidelines from which molecules yield desirable properties as a fuel are largely based on intuition. One such property of interest is the cetane number (CN), a measure of the ignition quality of diesel fuel. The present work improves on existing models and extends them to more oxygenates (primarily ethers) to increase the model’s generalizability to the large variety of new potential biofuels currently of interest to researchers. This predictive model uses artificial neural networks (ANN’s) as a tool for quantitative structure property relationship (QSPR) analysis. Predicting the cetane number of a fuel is especially important because testing a fuel requires large volumes of pure sample (100mL for derived cetane number, >1L for cetane number), the production of which can be difficult, costly and time-consuming at the lab scale. To this end, a predictive model will allow chemists to eliminate unlikely targets and focus their attention on promising candidates.Copyright