Combustion characteristics of a hydroxylammonium nitrate based liquid propellant. Combustion mechanism and application to thrusters

A new composition of hydroxylammonium nitrate based solution containing ammonium nitrate, methanol, and water was developed for monopropellant in a reaction control system (RCS) as an alternative to conventional hydrazine. In comparison with hydrazine, this solution has a 20% higher specific impulse, 1.4 times higher density, and lower freezing point and toxicity. The linear burning rate of the solution is moderate at the operating pressures of RCS thrusters. It was found that the linear burning rate had some characteristics whose mechanisms had not been understood. The combustion mechanism of this solution was investigated. The burning behavior was observed using a medium speed camera, and a temperature profile for the combustion wave was measured with a 2.5 μm diameter thermocouple. From these results, the instability of the liquid-gas interface may trigger a sudden increase in the burning rate, and methanol was found to be effective in reducing the bubble growth rate in the solution. The reactivity of several catalysts was evaluated in an open-cup test, and the S405 catalyst for hydrazine showed the best performance among them. Thruster tests were conducted using the S405 catalyst with variation in the propellant mass flow rate, catalyst bed configuration, and length-to-diameter ratio of the combustor. As a result, parameters were determined that ensured long operating time. The model thruster operated stably for up to 100 sec with a specific impulse I _sp = 240 sec, which corresponds to a 90% efficiency. __________ Translated from Fizika Goreniya i Vzryva, Vol. 45, No. 4, pp. 109–120, July–August, 2009. An erratum to this article can be found at     

Application of nonlinear fitting and selection of the most fitted equation by AIC in stability test of pharmaceutical ingredients

We proposed a method for objectively selecting the most fitted rate equation among candidate rate equations based on chemical kinetics by both nonlinear regression analysis and Akaike's information criterion (AIC), to express the decrease of pharmaceutical ingredient as an appropriate equation. Pseudo-zero, first, and second-order rate equations were prepared as candidates beforehand, and AIC was introduced for selecting the most fitted rate equation among the candidates. We compared the proposed method to the Weibull method that expressed any decrease patterns as a single equation.

We quantified the contents of thiamine nitrate (VB1) and taurine after storage for one, three, and six months under 40°C-75% relative humidity by high-pressure liquid chromatography. Decrease patterns of each sample were most fitted to one of the candidate rate equations, that is, pseudo-zero, first, and second-order rate equations, respectively, and the degree of fit in the most fitted equation was superior to that of the Weibull method, except for the pseudo-first-order rate equation.

Moreover, we confirmed that the proposed method was considerably precise for estimating the stability of pharmaceuticals by comparing estimated residual rates and confidence intervals to experimental data.     

Effect of mixing ratio on bactericidal action of MgO–CaO powders

MgO–CaO powders were prepared with different molar ratios (MgO/CaO) at 1400 °C for 2 h in air. By using the powder samples obtained, the change in bactericidal effect as a function of MgO–CaO composition was studied by colony count method. From the XRD measurements, it was found that CaO solid solution was formed by the replacement of Mg²⁺ ion with larger Ca²⁺ ion. However, no formation of MgO solid solution was observed. The average particle size and the specific surface area of the samples used in this study were about 0.2 m and 10.5m²g^–1, respectively. The pH values of physiological saline containing powder samples increased with the increase of CaO content, and the value reached 12.1 in sample with the molar ratio (MgO/CaO) of 0.25. From the results of bactericidal tests for Staphylococcus aureus, it was found that the bactericidal effect increased with the increase of CaO content in the samples.     

Beating in Membrane Potential Mediated by Cortical γ-Oscillations for Reading Out Synchronous Neuronal Activities Over Distant Cortical Areas

I investigate whether cortical -oscillations are relevant to reading out synchronous neuronal firings that are distributed over the brain. A cortical neural network model is proposed and simulated. The model consists of two sensory networks (SI and SII) and one coincidence-sensitive network (CS). -oscillatory inputs and external stimuli are applied to interneurons and projection neurons of the sensory networks, respectively. The SI and SII networks project to the CS network in a divergent/convergent manner. Here I show that beating in membrane potential of CS neurons mediates the detection of synchronous neuronal firings between the SI and SII networks. A slight increase (a few Hz) in difference between frequencies of the -oscillations in the SI and SII networks generates the beating in the CS network. The synchronous neuronal firings are detected at each peak of the beating, regardless of difference in signal transmission time between SI-to-CS and SII-to-CS pathways.     

Surface modification of an organosilane self-assembled monolayer on silicon substrates using atomic force microscopy: scanning probe electrochemistry toward nanolithography

Organosilane self-assembled monolayers (SAMs) have been applied to resist materials for nanolithography based on scanning probe microscopy. An organosilane SAM was prepared on Si substrates from a precursor, that is octadecyltrimethoxysilane. Using an atomic force microscope with a conductive probe, current was injected from the probe into the SAM-covered Si substrate so that the SAM was locally degraded at the probe-contacting point. Nanoscale patterns drawn on the SAM was clearly imaged by lateral force microscopy. The patterning could be conducted in air while, in vacuum at the order of 10(-6) Torr, no detectable patterns were fabricated. The presence of adsorbed water at the probe/sample junction was confirmed to be crucial for the patterning of the SAM/Si. Its mechanism was, thus, ascribed to electrochemical reactions of both the SAM and Si with adsorbed water.     

On Robust Stability And Sensitivity Of Circadian Rhythms

We develop an approach to robustness analysis of circadian rhythms from the viewpoints of (local) robust stability of periodic trajectories and their period‐sensitivity, based on mathematical models. Our attention is directed to the core molecular model generating circadian rhythms in Drosophila, proposed by Goldbeter [1], for our approach to be illustrated. We consider two cases when the circadian rhythms are subjected to periodic forcing by light/dark (LD) cycles and when the circadian rhythms are under continuous darkness (DD). First, we propose conditions/algorithms for (local) robust stability, and show that the circadian rhythms generated by the core molecular model are (locally) robustly stable, in both LD and DD cases. Second, in DD case, we derive a formula of period sensitivity, and assess effects of (infinitesimal) parameter‐variations on the period of the circadian rhythms.     

Modulated Hebb-Oja learning Rule-a method for principal subspace analysis

This paper presents analysis of the recently proposed modulated Hebb-Oja (MHO) method that performs linear mapping to a lower-dimensional subspace. Principal component subspace is the method that will be analyzed. Comparing to some other well-known methods for yielding principal component subspace (e.g., Oja's Subspace Learning Algorithm), the proposed method has one feature that could be seen as desirable from the biological point of view-synaptic efficacy learning rule does not need the explicit information about the value of the other efficacies to make individual efficacy modification. Also, the simplicity of the "neural circuits" that perform global computations and a fact that their number does not depend on the number of input and output neurons, could be seen as good features of the proposed method.     

Adaptive Sampling Methods for Scaling Up Knowledge Discovery Algorithms

Scalability is a key requirement for any KDD and data mining algorithm, and one of the biggest research challenges is to develop methods that allow to use large amounts of data. One possible approach for dealing with huge amounts of data is to take a random sample and do data mining on it, since for many data mining applications approximate answers are acceptable. However, as argued by several researchers, random sampling is difficult to use due to the difficulty of determining an appropriate sample size. In this paper, we take a sequential sampling approach for solving this difficulty, and propose an adaptive sampling method that solves a general problem covering many actual problems arising in applications of discovery science. An algorithm following this method obtains examples sequentially in an on-line fashion, and it determines from the obtained examples whether it has already seen a large enough number of examples. Thus, sample size is not fixed a priori; instead, it adaptively depends on the situation. Due to this adaptiveness, if we are not in a worst case situation as fortunately happens in many practical applications, then we can solve the problem with a number of examples much smaller than required in the worst case. We prove the correctness of our method and estimates its efficiency theoretically. For illustrating its usefulness, we consider one concrete task requiring sampling, provide an algorithm based on our method, and show its efficiency experimentally.     

Shape optimization of curves and surfaces considering fairness metrics and elastic stiffness

A method is presented for generating round curves and surfaces allowing discontinuities in tangent vectors and curvatures. The distance of the centre of curvature from the specified point is used for formulating the objective function which is a continuous function of the design variables through convex and concave shapes. It is shown that a shell with and without ribs can be generated within the same problem formulation if the minimization problem is converted into a maximization problem and the parameter region where integration is to be carried out is restricted in view of the curvature. Optimal shapes are also found under constraints on the compliance against static loads. A multiobjective optimization problem is solved by the constraint method to generate a trade-off design between roundness and mechanical performance.An erratum to this article can be found at