Flow boiling data and prediction method for enhanced boiling tubes and tube bundles with R-134a and R-236fa including a comparison with falling film evaporation

New enhanced boiling tubes from Wolverine Tube Inc. (Turbo-B5) and Wieland-Werke AG (Gewa-B5) were investigated using R-134a and R-236fa as test fluids. The tests were done at saturation temperatures of 5 and 15 °C, mass flow rates from 4 to 35 kg m⁻² s⁻¹ and heat fluxes from 15 to 70 kW m⁻². A new prediction method based on a theoretical analysis of thin film evaporation was used to propose a new correlating parameter. A large new database of local heat transfer coefficients was obtained and utilized to generate an improved prediction method for bundle boiling and the onset of dryout. Onset of dryout and the simultaneous reduction in heat transfer performance occurred at very high vapour quality on these enhanced tubes in convective bundle boiling. Furthermore, a direct comparison was made between the tubes operating in falling film and convective bundle boiling modes.     

Effects of oxygen concentration on the macroscopic characteristic indexes of high-temperature oxidation of coal

To explore the macroscopic characteristic indexes for oxidation of coal under high-temperature conditions, an XKGW-1-type high-temperature-programmed heating experimental system was constructed. Tests on high-temperature oxidation of coal under high-temperature conditions at five oxygen concentrations of 21, 17, 13, 8, and 3 vol% were independently conducted. Laws of variation in high-temperature oxidation of coal indices, such as the coal temperature, gas ratios, rate of oxygen consumption, and exothermic strength from indoor temperature to 500 °C, were investigated at those oxygen concentrations. The results showed that the variation tendencies of characteristic indices for high-temperature oxidation of coal at different oxygen concentrations were extremely intricate. At the five oxygen concentrations, the rate of oxygen consumption increased rapidly with an increase in coal temperature and eventually remained at a higher range. The rate of oxygen consumption increased with temperature with an approximate exponential trend at the five oxygen concentrations tested. For the same coal temperature, the rate of oxygen consumption decreased with the oxygen concentration. The variation tendencies of the CO and CO₂ production rates were similar, both increased rapidly with an increase in coal temperature in the early stages and reached a maximum at a coal temperature of 380 °C. They decreased slightly with an increase in coal temperature at first and increased promptly thereafter. The concentrations of CH₄, C₂H₄, and C₂H₆ first increased with an increase in the coal temperature and markedly decreased after the maximal value. The temperatures for the extreme points were 480, 410, and 420 °C for CH₄, C₂H₄, and C₂H₆, respectively. The trends of the macroscopic characteristic indexes throughout the process of high-temperature oxidation of coal in a certain temperature range at various oxygen concentrations can be used for temperature prediction and fire prevention during coal mining.     

基于PU学习的链接预测方法

基于分类的链接预测方法中,由于链接未知节点对的大规模性与不确定性,选择可靠负例成为构造链接预测分类器的难点问题.为此,文中提出基于正例和无标识样本(PU)学习的链接预测方法.首先,提取节点对的拓扑信息以构造样本集.再利用社区结构确定候选负例的分布,基于分布进行多次欠采样,获得多个候选负例子集,集成多个负例集与正例集中构建的分类器选择可靠负例.最后基于正例与可靠负例构造链接预测分类器.在4个网络数据集上的实验表明文中方法预测结果较优.     

Studies on air core size in a simplex pressure-swirl atomizer

The air core formed in the pressure-swirl atomizer has been experimentally and theoretically investigated. The experiments were implemented from the pressure of 0.1 MPa–1.4 MPa at the room temperature. Five types of atomizers with different swirl chamber length and five types of mixture of the glycerol and water with different liquid viscosity were employed for discussing effects of the swirl chamber length and the liquid viscosity on the air core size. In addition, a semi-theoretical prediction correlation of the air core size was derived by establishing a control-volume model based on the angular momentum theorem in the particles system, and then was verified with the experimental results. It is found that the air core size increases with the decrease of the swirl chamber length and the decrease of the liquid viscosity. The air core will disappear when the swirl chamber length is greater than a critical length or the ejected liquid viscosity exceeds a threshold if other parameters are unchanged. The critical swirl chamber length decreases with an increase of the liquid viscosity and the viscosity threshold decreases with an increase of the swirl chamber length. Compared with some available correlations proposed in the literatures, predictions by the new correlation derived in the present paper roughly show better agreement with the experimental results at a wide range of liquid viscosity.     

Discussion

The use of Stein estimation in multiple linear regression is considered. Tables and graphs are presented that compare the prediction mean squared errors of positive-part James-Stein, preliminary-test, reduced, and full-model least squares estimates. The appropriateness of using Stein contraction on possibly extraneous variables is emphasized, and a procedure is presented for evaluating the likely savings in using Stein estimation on the problem at hand. An example is given.     

Measurement of Bulk Mechanical Properties and Modeling the Load-Response of Rootzone Sands. Part 1: Round and Angular Monosize and Binary Mixtures

The bulk mechanical properties of two different types of rootzone sands (round and angular) were measured using a cubical triaxial tester. Two monosize sands (d 50 = 0.375 mm and 0.675 mm) and their 50:50 binary mixtures (d 50 = 0.500 mm) were studied. The compression, shear, and failure responses of the above-mentioned six compositions were analyzed, compared, and modeled. Two elastic parameters (bulk and shear moduli) and two elastoplastic parameters (swelling and consolidation indices) of the six sand compositions were also calculated and compared. The angular sand was more compressible than round sand during isotropic compression. In addition, the angular sands tended to have lower initial bulk density and high porosity values. Among the three different size fractions, the 0.375 mm mixture was least compressible for both sand shapes. The failure strength and shear modulus of the angular sand were higher than the round sands. In addition, due to their simplicity, phenomenological models were developed to predict the compression and shear behavior of the sands. The prediction models were validated using subangular and subround sands. Average relative difference values were calculated to determine the effectiveness of the prediction models. The mean average relative difference values for compression profiles, i.e., volumetric stress vs. volumetric strain, were from 16 % to 39 %, except for the initial load-response portion (< 1 % volumetric strain). The predictive models were effective in reproducing the failure responses: at 17.2 kPa confining pressure, the mean of average relative difference was 23 %; at 34.5 kPa , the mean difference was 24 %.     

An Approximation to the Negative Moments of the Positive Binomial Useful in Life Testing

The purpose of this paper is to obtain the mean and variance of the maximum likelihood estimator of the scale parameter of a Weibull distribution where the sample is censored at a fixed time. It will be shown that these moments are functions of the negative moments of the positive binomial distribution. A simple approximation is obtained for the negative moments of the positive binomial, thus giving an approximate expression for the mean and variance of the estimator.     

机械设备故障规律及运行趋势预测方法综述

对于机械设备的故障运行问题,技术人员应当深入研究机械设备的故障规律,并研究出运行趋势的预测方法,从传感器的检测时间间隔与使用数量等方面加以深入的研究。本文介绍了机械设备运行状态的故障预测方法,并将机械设备运行状态的故障预测方法总结为三个步骤,分别是数据获取、处理与设备寿命预测,结合这些内容,提出了关于机械设备故障运行的一些方法,旨在为相关技术人员提供参考依据。     

Prediction of ground motion parameters using randomized ANFIS (RANFIS)

In this paper, a novel neuro-fuzzy learning machine called randomized adaptive neuro-fuzzy inference system (RANFIS) is proposed for predicting the parameters of ground motion associated with seismic signals. This advanced learning machine integrates the explicit knowledge of the fuzzy systems with the learning capabilities of neural networks, as in the case of conventional adaptive neuro-fuzzy inference system (ANFIS). In RANFIS, to accelerate the learning speed without compromising the generalization capability, the fuzzy layer parameters are not tuned. The three time domain ground motion parameters which are predicted by the model are peak ground acceleration (PGA), peak ground velocity (PGV) and peak ground displacement (PGD). The model is developed using the database released by PEER (Pacific Earthquake Engineering Research Center). Each ground motion parameter is related to mainly to four seismic parameters, namely earthquake magnitude, faulting mechanism, source to site distance and average soil shear wave velocity. The experimental results validate the improved performance of the machine, with lesser computation time compared to prior studies.     

Hazard prediction discriminates between novice and experienced drivers

Typical hazard perception tests often confound multiple processes in their responses. The current study tested hazard prediction in isolation to assess whether this component can discriminate between novice and experienced drivers. A variant of the hazard perception test, based on the Situation Awareness Global Assessment Technique, found experienced drivers to outperform novices across three experiments suggesting that the act of predicting an imminent hazard is a crucial part of the hazard-perception process. Furthermore three additional hypotheses were tested in these experiments. First, performance was compared across clips of different length. There was marginal evidence that novice drivers’ performance suffered with the longest clips, but experienced drivers’ performance did not, suggesting that experienced drivers find hazard prediction less effortful. Secondly, predictive accuracy was found to be dependent on the temporal proximity of visual precursors to the hazard. Thirdly the relationship between the hazard and its precursor was found to be important, with less obvious precursors improving the discrimination between novice and experience drivers. These findings demonstrate that a measure of hazard prediction, which is less confounded by the influence of risk appraisal than simple response time measures, can still discriminate between novice and experienced drivers. Application of this methodology under different conditions can produce insights into the underlying processes that may be at work, whilst also providing an alternative test of driver skill in relation to the detection of hazards.