Stability and Free Radical Production for CO2 and H2 in Air Nanobubbles in Ethanol Aqueous Solution

In this study, 8% hydrogen (H2) in argon (Ar) and carbon dioxide (CO2) gas nanobubbles was produced at 10, 30, and 50 vol.% of ethanol aqueous solution by the high-speed agitation method with gas. They became stable for a long period (for instance, 20 days), having a high negative zeta potential (−40 to −50 mV) at alkaline near pH 9, especially for 10 vol.% of ethanol aqueous solution. The extended Derjaguin, Landau, Verwey, and Overbeek (DLVO) theory was used to evaluate the nanobubble stability. When the nanobubble in ethanol alkaline aqueous solution changed to an acidic pH of around 5, the zeta potential of nanobubbles was almost zero and the decrease in the number of nanobubbles was identified by the particle trajectory method (Nano site). The collapsed nanobubbles at zero charge were detected thanks to the presence of few free radicals using G-CYPMPO spin trap reagent in electron spin resonance (ESR) spectroscopy. The free radicals produced were superoxide anions at collapsed 8%H2 in Ar nanobubbles and hydroxyl radicals at collapsed CO2 nanobubbles. On the other hand, the collapse of mixed CO2 and H2 in Ar nanobubble showed no free radicals. The possible presence of long-term stable nanobubbles and the absence of free radicals for mixed H2 and CO2 nanobubble would be useful to understand the beverage quality.

Functioning of a technical system with an instantly replenished time reserve, taking into account preventive maintenance

В работе рассматривается функционирование технической системы с мгновенно пополняемым резервом времени с учетом профилактики. Приводится описание функционирования такой системы. При использовании аппарата полумарковских исследований производится построение аналитической модели системы с мгновенно пополняемым резервом времени при учете влияния профилактики на ее производительность. При построении полумарковской модели принимается ограничение на количество профилактик за время восстановления рабочего элемента. Описываются полумарковские состояния исследуемой системы, и приводится граф состояний. Определяются времена пребывания в состояниях системы, вероятности переходов и стационарное распределение вложенной цепи Маркова. Для определения функции распределения времени пребывания системы в подмножестве работоспособных состояний с использованием метода траекторий находятся все траектории переходов системы из этого подмножества в подмножество неработоспособных состояний и вероятности их реализации. Определяются времена пребывания системы в найденных траекториях. На основании теоремы полной вероятности определяются функции распределения времен пребывания системы в подмножествах работоспособных и неработоспособных состояний и коэффициент готовности системы. Приводится пример моделирования исследуемой системы. Проводится сравнение полученных результатов с результатами использования теоремы о среднестационарном времени пребывания системы в подмножестве состояний. The work examines the functioning of a technical system with an instantly replenished reserve of time, taking into account prevention. The description of the functioning of such a system is given. When using the apparatus of semi-Markov studies, an analytical model of the system is constructed with an instantly replenished reserve of time, taking into account the effect of prevention on its performance. When constructing a semi-Markov model, a limitation on the number of preventive measures during the restoration of a working element is adopted. The semi-Markov states of the system under study are described, and the state graph is given. The sojourn times in the states of the system, the transition probabilities, and the stationary distribution of the embedded Markov chain are determined. To determine the distribution function of the time spent by the system in a subset of operable states using the trajectory method, all trajectories of the system's transitions from this subset to the subset of inoperable states and the probability of their realization are found. The residence times of the system in the found trajectories are determined. On the basis of the total probability theorem, the distribution functions of the sojourn times of the system in subsets of the healthy and inoperable states and the system availability factor are determined. The modeling example of th system under study is given. The results obtained are compared with the results of using the theorem on the average stationary sojourn time of the system in a subset of states.

An Improved Similarity Trajectory Method Based on Monitoring Data under Multiple Operating Conditions

With the complexity of the task requirement, multiple operating conditions have gradually become the common scenario for equipment. However, the degradation trend of monitoring data cannot be accurately extracted in life prediction under multiple operating conditions, which is because some monitoring data is affected by the operating conditions. Aiming at this problem, this paper proposes an improved similarity trajectory method that can directly use the monitoring data under multiple operating conditions for life prediction. The morphological pattern and symbolic aggregate approximation-based similarity measurement method (MP-SAX) is first used to measure the similarity between the monitoring data under multiple operating conditions. Then, the similar life candidate set, and corresponding weight are obtained according to the MP-SAX. Finally, the life prediction results of equipment under multiple operating conditions can be calculated by aggregating the similar life candidate set. The proposed method is validated by the public datasets from NASA Ames Prognostics Data Repository. The results show that the proposed method can directly and effectively use the original monitoring data for life prediction without extracting the degradation trend of the monitoring data.

ГАУССОВ ПУЧОК КАК МОДЕЛЬ ИСТОЧНИКА ИОНОВ

Для расчета статистического аксептанса КФМ использовался траекторный метод. Функция плотности вероятности захваченных фазовых точек предназначена для определения матриц вторых моментов. Элементы этих матриц описывают эллипсы захвата на X и Y фазовых плоскостях. Мерой согласования Гауссова пучка и аксептанса квадруполя служат площади эллипсов. При постоянных параметрах Гауссова пучка ионов эффективность согласования слабо уменьшается с увеличением разрешающей способности. Полученные данные будут полезны при проектировании современных источников ионов. To calculate the statistical QMF acceptance, an ion trajectory method has been used. The probability density functions of accepted points allow fitting the matrix of the second moments. The elements of these matrices describe the acceptance ellipses on phase X and Y planes. The measure of the coupling Gaussian beam and quadrupole acceptance is ellipse area. Colored distributions of the input and output coordinates and velocities are presented, in which the initial phases are marked with different colors. It was found that with increasing resolution, the statistical acceptance ellipses are nested into each other. At constant parameters of the input Gaussian beam, the matching efficiency weakly decreases with resolution. The obtained data will be useful for creation a new modern ion sources.

A simulation study of excitation contour of a linear trap with spatial harmonics

The process of nonlinear resonant excitation of ion oscillations in a linear trap is studied. There is still no detailed simulation of the resonance peak in the literature. We propose to use the excitation contour to describe the collective ion resonance. The excitation contour is a resonant mass peak obtained by the trajectory method with the Gaussian distribution of the initial coordinates and velocities. The following factors are considered: excitation time, low order hexapole and octopole harmonics with amplitudes A3 and A4, the depth of the initial ion cloud position. These multipoles are used for selective ion ejection from linear ion trap. All these factors affect the ion yield and the shape of the contours. Obtained data can be useful for control of such processes as ion fragmentation, ion isolation, ion activation, and ion ejection. Simulated resonance peaks are important for the theoretical description of the ion collective nonlinear resonances.