Modelling of dust lifting process behind propagating shock wave

Dust dispersion from a layer is a complicated problem, which has not been completely solved yet, especially if an Eulerian–Eulerian approach has to be used to model the two-phase dusty flow. In previous investigation, a phenomenological model of the dust dispersion process from a layer was developed, but the evaluation of the model revealed some weaknesses. In the current paper, the model of the dust dispersion process was presented and three improvements of the model were studied: Saffman force, Magnus force and particles collisions. The implementation of Magnus and Saffman forces into the code did not improve the numerical results and it was shown that it had very little influence on the dust lifting process, in case the phenomenological model of the layer is used. Some explanations were proposed in the paper. Besides, an empirical model of particles collisions was also added to the code and its influence on the results was studied. It was shown that the particles collisions model improved the obtained results, but further modifications are to be studied in the future.     

基于地电场数值模拟的边坡软弱层稳定性评价

为解决露天采场边坡失稳带来的巨大安全隐患问题,以鞍本地区铁矿露天采场为例,在分析高密度电阻率法基本原理、探测系统和正反演原理的基础上,测定了研究区内主要岩矿体电阻率,据此建立了基于地电场数值模拟的层间软弱层稳定性评价模型。温纳和偶极装置工作下,设定的地电模型正演模拟和反演计算结果表明,电阻率异常特征准确地反映了软弱层的稳定性状态,地电场分布特征与模型设定结果基本吻合。评价实例和钻探验证结果表明,模型可准确评价层间软弱层的稳定状态,取得了良好的实际效果。     

Numerical and experimental investigations on laser melting of stainless steel 316L metal powders

This paper presents numerical and experimental investigations on laser melting of SS grade 316L powder on top of AISI 316L substrate using a pulsed Nd:YAG laser. The objectives of the present study are to understand the effect of process parameters such as laser power, scanning speed and beam size on geometry characteristics of the melt zone and ball formation. We formulated a moving heat source problem and obtained transient temperature solutions using commercial finite element solver. The geometry characteristics of the melt zone are evaluated from the temperature solutions and compared with experimental results. The effect of laser parameters on the geometry, morphology and homogeneity of single track realization was methodically analyzed by utilizing characterization tools such as laser particle size analyzer, macro and microscopic inspection, Scanning Electron Microscope (SEM), X-Ray Diffraction (XRD) and Fourier Transform Infrared Spectroscopy (FTIR). The results presented in this paper are beneficial to realize homogenous layer formation in additive manufacturing processes involving powder melting by laser beam.     

环境实验室温度均匀性的数值分析研究

目的研究送风参数及围护结构对飞机结构及机构环境条件下功能性和耐久性实验室温度均匀性的影响。方法采用CFD方法对实验室的气流组织进行数值模拟,根据气流组织评价标准对工作区的温度均匀性进行分析。结果送风温差越大、送风速度越小温度场均匀性越差,保温层较厚时,温差过大将导致工作区温度分布达不到设计要求。结论相同温差下,减少送风口数量并提高单个送风口的送风速度有助于提高温度均匀性。     

电收尘极板上沉积尘的附着力与振打加速度

振打清灰是保证静电除尘器正常运行的一个重要环节.为确定振打加速度,基于Penney和Klingler理论,认为带电粉尘层对收尘极板的附着力主要是外电场力和附加电场力共同作用的结果.附加电场是由于电晕电流通过沉积在收尘极板上的粉尘层产生电荷积累而形成的.应用静电学理论导出粉尘层内电场分布与带电粉尘层厚度的平方成正比.通过建立荷电粉尘层对收尘极板附着力的微分方程,由牛顿第二定律得出振打加速度的理论计算式.研究结果表明,振打加速度是电晕电流面密度和粉尘比电阻乘积ρ×J的函数,且与粉尘粒径成反比.参考已发表的实验数据和理论结果发现,在外加电压保持不变的情况下,电晕电流面密度和粉尘比电阻的乘积ρ×J=常数,此时,振打加速度与ρ×J无关.从这一新观点出发,根据Oglesby提供的粉尘层击穿前的电晕电流和粉尘比电阻的相关曲线,得出临界振打加速度计算式.由此计算式给出了一种确定临界振打加速度的简易图解法.     

村镇小型生活垃圾热处理炉底渣的理化特性

小型垃圾热处理设备可实现就地处置,节约运输成本,目前在中国山区、丘陵地带的村镇得到广泛应用.为了解村镇小型生活垃圾热处理炉底渣的理化特性及其影响因素,对中国云南、贵州、安徽村镇实际运行的小型生活垃圾热处理设备产生的底渣进行取样,分析其热灼减率、物理组成、化学组成、晶相组成、重金属含量和浸出特性,探讨处理工艺、地域及季节...     

成都冬季典型辐射逆温过程分析

本文利用测温声雷达的探测结果，借助同期探空和地面观测资料，分析了成都平原典型辐射逆温的生消演变规律，指出了其主要特征。这些结果对气候资源利用、污染气象条件的研究等具有重要意义。     

煤气设备水封的有效高度

通过分析煤气设备水封的有效高度的有关规定,及水封有效高度的计算方法,阐述生产单位水封跑气事故情况,提出了煤气设备水封的有效高度的新计算方法。     

日本海底地震观测现状与进展

详细介绍了日本在本世纪70 年代～90 年代初的三个海底地震仪观测系统,和日本政府在1995 年阪神大震后投巨资兴建海底地震监测网络的情况。并就上述内容的国际研究现状,提出了存在问题和未来海洋地震观测研究的设想     

Air Quality Management in Izmir Region of Turkey as Required by Clean Air Plans

Future (24 h later) daily ground level SO₂ concentration in Istanbul was modeled and predicted using a new and powerful technique, Artificial Neural Networks (ANN) in the case of meteorological parameters as input variables. Results show that the trend of SO₂ from higher values in winter to lower values in spring and summer, and again to higher values towards winter can be correctly represented by the neural networks. The model better predicted the lower SO₂ values in spring and summer seasons when compared to higher values in winter season because of the pattern distribution in training data sets. Beside the amount of the database, the more the variation of the values of the parameters in their own ranges, the more the network learns the database. As a result of this study, considerably successful results were obtained when considering the complex and nonlineer structure of the atmosphere, which is the source of the database.