Movement and distribution of Sitophilus zeamais adults and relationship between their density and trapping frequency in wheat bulks under different grain temperatures and moisture contents

Movement and distribution of Sitophilus zeamais adults and relationship between their trapping frequency and insect density were determined in one tonne wheat with 11.5 ± 0.2, 12.5 ± 0.1 and 13.5 ± 0.2% moisture contents (wet basis) inside cylindrical bins at 20, 25 and 30 °C. The introduced adult densities were 0.5, 1.0, and 2.0 adults/kg wheat (A/kg). Inside each bin, 15 probe traps were vertically installed in three layers. In each layer, five traps were installed at the center and half radii of the bin individually. The trapped adults were counted daily up to 7 d, and then 15 kg wheat was sampled at each trap location. The insect number in each sample was counted.The recovered adults in the top layer were less than that in the middle layer, while no significant difference between at middle and bottom layers. In each layer, adults preferred the center location at 0.5 A/kg, while this trend was unidentified at other densities. There was an autocorrelation of insect densities at adjacent locations at ≥ 1.0 A/kg, while no autocorrelation in the vertical direction. The adults had an aggregation distribution at any temperature, moisture content and adult density. The normal and Poisson model could not be used to describe the distribution of the count frequency of the adults in the samples, while the negative binomial model could describe this distribution in 18 out of 27 sampling sets at ≤ 1.0 A/kg. The trapping frequency was strongly influenced by the trapping period and increased with the increase of insect densities. The relationship between adult densities and trapping frequencies at the sampling locations had a significant difference at different grain temperatures, while no difference at different moisture contents, grain depths, and locations.     

Evolving an Accurate Decision Tree-Based Model for Predicting Carbon Dioxide Solubility in Polymers

Solubility is one of the most indispensable physicochemical properties determining the compatibility of components of a blending system. Research has been focused on the solubility of carbon dioxide in polymers as a significant application of green chemistry. To replace costly and time-consuming experiments, a novel solubility prediction model based on a decision tree, called the stochastic gradient boosting algorithm, was proposed to predict CO₂ solubility in 13 different polymers, based on 515 published experimental data lines. The results indicate that the proposed ensemble model is an effective method for predicting the CO₂ solubility in various polymers, with highly satisfactory performance and high efficiency. It produces more accurate outputs than other methods such as machine learning schemes and an equation of state approach.     

豫西吉家洼金矿床主矿脉找矿前景分析

吉家洼金矿床位于豫西熊耳山上宫金矿集区的西部。通过对矿床地质、主要矿脉地质特征研究,对F1、F2和WF1矿脉进行了矿体趋势预测和找矿前景分析。分析结果表明,WF1矿脉北中部125～119线间、中部123～107线间及南部100～114线间,深部具有较大的找矿潜力;F1、F2矿脉11～8线为找矿有利地段,具有进一步找矿空间。     

水平管内R245fa/R141b沸腾换热特性的实验研究

针对新型混合工质R245fa/R141b，开展水平光滑管(外径10 mm)内工质沸腾换热特性的实验研究，对比纯工质与混合工质的换热性能及4种常用关联式的预测精度。结果表明：纯工质与混合工质的沸腾传热系数均随质量流速和热通量的增加而增大，随饱和压力的增加而减小；随干度的增加，沸腾传热系数均先增大后减小，即存在“过渡干度”，且混合工质的过渡干度大于纯工质；干度小于0.55时，混合工质传热系数小于纯工质；干度大于0.55后，混合工质的传热系数更高；随R245fa质量分数的增加，混合工质的沸腾传热系数增大。在所选关联式中，Gungor-Winterton关联式能准确地预测工质在光滑管内的沸腾换热特性，平均相对误差为16.67%。     

国内建筑涂料市场影响因素与预测分析

中国是全球最大的建筑涂料市场，各涂料厂商在中国建筑涂料市场上进行激烈竞争，能够精准预测行业趋势对各涂料厂商精准决策和投资，提升企业经营质量具有重要意义。文章收集了近 12年建筑业总产值、房地产投资、城镇常住居民人口、 M2和 GDP等影响建筑涂料市场的数据，通过回归分析的方法得出：各影响因素与建筑涂料产量存在紧密且正相关的定量关系，并由此预测了国内建筑涂料市场在未来 3年将稳步发展。     

Al2O3 loss prediction model of selective laser melting Al2O3–Al composite

The element/phase loss is undesirable but existing during selective laser melting (SLM) of materials with volatile element/phase, which not only changes the material composition but also affects the molten pool flow. In the previous researches, the effect of remelting on the element/phase loss was neglected during the SLM process, instead, laser energy density was thought to be uppermost. In fact, the SLM process fabricates the parts in a manner of line by line and layer by layer, i.e., additive character, and the remelting in the overlap zone occurs during the SLM process. In this paper, three different Al₂O₃ loss prediction models of SLM Al₂O₃–Al composite by considering the additive character of SLM and the distribution of the Al₂O₃ associated with the different molten pool driving forces were developed. By comparing with the experimental results and predicted results, it is found that the Al₂O₃ is distributed on both sides of the molten pool under the combined action of the Marangoni flow and the evaporation recoil pressure. This kind of Al₂O₃ distribution enhances the effect of the remelting on the Al₂O₃ loss, i.e., the remelting brings a logarithmic increase in the Al₂O₃ loss rate. This determines the final Al₂O₃ loss rate of the SLMed 3D samples. During this study, although the Al₂O₃ loss rate of the single-track is only 33%, the loss rate of SLMed 3D samples increases significantly to 97% when the hatching space of 60 μm and scanning speed of 200 mm/s are utilized, i.e., almost no Al₂O₃ in the 3D sample. Thus, it is more important to reduce the remelting, i.e., overlap rate for reducing the element/phase loss. This study is a benefit for understanding and reducing the element/phase loss in SLM.     

Prediction of process parameters of water-assisted injection molding based on inverse radial basis function neural network

Because of the introduction of new processing parameters in water-assisted injection molding (WAIM), processes control has become more difficult. First, design of experiment (DOE) was carried out by using optimized Latin hypercubes (Opt LHS). On the basis of this, computational fluid dynamics (CFD) method was used to simulate and calculate hollowed core ratios and wall thickness differences of cooling water pipe at different positions. Then inverse radial basis function (RBF) neural network model reflecting the fitting relationship between processing parameters and molding quality was established, and accuracy of the model was detected by cross validation. Finally, expected molding quality was applied to predict processing parameters, and the obtained molding quality under the predicted processing parameters was verified by computer aided engineering (CAE) simulation and experimental methods. The results showed that mean relative precisions of processing parameters such as melt temperature, delay time, short shot size, water pressure, and mold temperature for inverse RBF model were 98.6%, 93.6%, 98.5%, 93.9%, and 97.9%, respectively, which met the accuracy requirements. Furthermore, compared with expected values of hollowed core ratios and wall thickness differences, the average errors of CAE and experiment were 2.3% and 4.9%, respectively.     

浅谈煤矿数据的分析与应用

当今社会科技发展快、信息流通量大,人们之间的交流越来越密切,大数据这个高科技时代的产物也应运而生。煤炭作为工业发展的重要组成部分,其发展关系着整个工业的发展。如今,许多现代大型煤矿已能将井下设备信息上传到地面,在地面就可直观的看到设备当前运行的情况,从而更可靠的进行安全生产。通过结合实例将上传的设备信息数据进行整理和分析,从而预测设备的运行状况,提出建设性建议。同时对加强煤矿安全生产、促进煤炭行业现代化建设、提高煤矿的经济效益和社会效益具有重要的意义。     

综放高瓦斯矿井煤层瓦斯涌出量综合预测

为了成功预测竹林山煤矿综放高瓦斯矿井大采高工作面煤层瓦斯涌出量,以主采3号煤层为主要研究对象,针对3号煤层以往开采情况,通过布设测点测量其煤层瓦斯含量和了解相邻矿井瓦斯含量,采用分源预测法、回归法及统计法等预测方法得到了3号煤层瓦斯含量的分布规律,并绘制了3号煤层的瓦斯含量等值线图。对矿井不同生产时期的瓦斯含量进行预测,得到了生产前期、中期及后期采区的最大绝对瓦斯涌出量和最大相对瓦斯涌出量,说明了竹林山煤矿各个时期均属于高瓦斯矿井。     

Fatigue strength dependence on the ultimate tensile strength and hardness in magnesium alloys

The relationships between fatigue strength and ultimate tensile strength as well as hardness have been studied in high-strength NZK alloys (Mg–yNd–zZn–xZr) and other magnesium alloys. In the absence of casting defects, clear linear relationships have been found between the fatigue strength and the ultimate tensile strength and the hardness values in these magnesium alloys in both T4 (solutionized) and T6 (solutionized and aged) conditions. The fatigue strength models developed in this work alloys can be directly applied to other defect-free magnesium alloys.