Determination of t8/5 cooling times for underwater local dry welding of steel

Knowledge of thermal history is the basic condition for studying the structure - properties of welded joints. The determinant of thermal history is the thermal cycle, whose in-situ measurements are still a big challenge. Water as the welding environment complicates this issue even more. The article presents a method to determine an equation for calculating t_8/5 cooling times for underwater gas metal arc welding of unalloyed steels using the local dry cavity method. The work uses the contact method of temperature measurements with the use of thermocouples to obtain the temperature changes of the points of welded joints covered by the thermal field. On this basis, the values of the t_8/5 cooling times were determined. A regression analysis of the Response Surface Method was used to determine the equation, which resulted in a second-order model with interactions. Statistically significant factors were determined (thickness of welded elements and heat input value) and the model veracity was confirmed as the assumptions of normality and homogeneity of variance (homoscedasticity) of the residuals were met. The t_8/5 cooling time values depend on the thickness of the welded elements and heat input value in a nonlinear way. In terms of the test conditions, the cooling times ranged from 3.0 to 7.7 s. The equation allowed for the calculation of t_8/5 cooling times during underwater welding of unalloyed steels using the local dry cavity method based on the variability of the experimental conditions with satisfactory accuracy.     

基于机器学习的柴油机碳烟颗粒质量排放预测模型

基于SC7H涡轮增压柴油机试验台架,开展了非道路瞬态试验循环下的柴油机排放试验,研究了瞬态循环的工况对碳烟颗粒质量浓度的影响。收集与碳烟颗粒质量浓度相关的各类传感器数据,构建一个大型的柴油机碳烟排放数据集。构建LGB梯度树模型和循环神经网络模型,采用数据集对它们进行训练,然后采用自学习算法对两种模型进行融合,获得一个更高准确度的预测碳烟质量排放融合模型。预测与实测结果的比较表明,构建的融合模型能较为准确地预测柴油机排放的即DPF入口的碳烟质量浓度实时变化,为柴油机后处理过程中碳载量的准确计算以及控制策略的开发提供参考。     

AO工艺处理工业污水的运行研究

为便于制药化工行业废水的调控，针对运行阶段容易出现的出水氨氮不稳定、DO不稳定、出水浊度高等常见问题，筛选符合经济效益的改造手段。本研究主要是通过调控硝化菌种的繁殖周期、以及生存的外环境来控制出水氨氮浓度；通过理论需氧量支撑工程技术改造、保证DO的稳定；通过改变污泥的排放周期和精准控制、降低出水的浊度，为工艺严选和运行把控提供技术支撑。