基于大数据分析的分布式MOLAP技术研究

在计算机系统运行以及研究环节中,会存在大量的规模效应,此类状况难以避免,要想有效解决此类问题,就需要利用分布式的处理方式,开展对文件系统的分析。文章对分布式多维联机分析过程(MOLAP)的数据模型进行了分析,从维编码的算法、映射归约(MapReduce)算法的实现、分析维的遍历算法等方面作深入探讨。     

Slag eye formation in single and dual bottom purged industrial steelmaking ladles

ABSTRACT

Argon gas is often injected from the bottom of the ladle during steel refining operations. The injected gas interacts with the liquid (metal and slag) bath and enhances the momentum, heat, and mass transfer rate in the melt. However, during these gas–liquid interactions, an opening of the slag layer called slag eye is formed, which exposes the molten metal surface to the atmosphere, which is generally undesirable. In the current work, a transient, three-dimensional mathematical model is used to study the turbulent gas–liquid interactions in single as well as dual bottom blown industrial steelmaking ladles. A Coupled Level Set Volume of Fluid (CLSVOF) model is used for tracking the steel-argon, steel-slag, and argon-slag interfaces, from which the slag-eye area has been predicted. It is found that the inlet gas purging rate, melt height, slag layer thickness, angular and radial positions of the gas inlets affect the slag opening area. Non-dimensional empirical correlations are proposed to predict the slag opening area in both single as well as dual purged ladles, using non-linear regression analysis.     

正偏心正交车铣精加工切削层几何形状研究

针对未考虑正偏心正交车铣切削层几何形状而导致难以全面反映正交车铣切削层几何形状变化规律的问题，基于正交车铣运动规律，在不考虑动力学影响的情况下，对切削层的形成过程进行了静态分析。建立的正偏心正交车铣切削层几何形状的解析模型涉及铣刀侧刃和底刃的切入/切出角度、切削厚度和切削深度。通过试验验证了该解析模型的正确性，并分析了切削参数对铣刀切削层的影响。研究结果为正偏心正交车铣切削层几何形状的变化提供了定量的分析依据，为切削力和颤振的研究提供了理论指导。     

基于模糊综合评判方法的水文地质类型评价

以开元矿井为例,在水文地质资料基础上,选定合适的指标,根据不同指标的重要程度确定各个指标权重,运用模糊综合评判理论建立矿井水文地质类型划分模型,运用该模型进行水文地质类型评价。     

New insight to the oxidation kinetics of silicon-containing steel at high temperature

This study investigated the oxidation kinetics of silicon-containing steel at 1150–1300 °C using a Simultaneous Thermal Analyzer under atmospheric conditions similar to that of an industry reheating furnace. There is a critical time point for the oxidation kinetics at an oxygen concentration of 4·0 vol.-%., following which the oxidation rate constant increases with the increasing oxidation temperature. The model coefficient A in the kinetic oxidation equation was found to be constant. However, before the critical time point, the oxidation rate constant remained unchanged; the model coefficient A decreased with the increasing temperature. Therefore, the kinetic model of silicon-containing steel for isothermal oxidation was observed to be a modified one on the basis of the experimental data. In addition, the critical time point was prolonged with the increasing isothermal oxidation temperature. Moreover, the oxidation activation energy of the tested silicon-containing steel was 366·16 kJ mol^?1.     

A simplified physically-based breach model for a high concrete-faced rockfill dam: A case study

A simplified physically-based model was developed to simulate the breaching process of the Gouhou concrete-faced rockfill dam (CFRD), which is the only breach case of a high CFRD in the world. Considering the dam height, a hydraulic method was chosen to simulate the initial scour position on the downstream slope, with the steepening of the downstream slope taken into account; a headcut erosion formula was adopted to simulate the backward erosion as well. The moment equilibrium method was utilized to calculate the ultimate length of a concrete slab under its self-weight and water loads. The calculated results of the Gouhou CFRD breach case show that the proposed model provides reasonable peak breach flow, final breach width, and failure time, with relative errors less than 15% as compared with the measured data. Sensitivity studies show that the outputs of the proposed model are more or less sensitive to different parameters. Three typical parametric models were compared with the proposed model, and the comparison demonstrates that the proposed physically-based breach model performs better and provides more detailed results than the parametric models.     

利用调度优化模型研究原油调合方案的可行性

针对某沿海炼油企业拟投用原油调合系统以稳定混炼原油的性质,设计方案要求将部分码头罐的操作模式由混储改为单储的情况,采用约束规划与数学规划复合建模,实现了码头至厂区大容积长输线模拟,建立了该企业的原油调度优化模型并研究了设计方案的可行性。针对240h调度周期、10种可加工原油、3艘到港油轮的复杂工况进行了优化计算。结果表明:该设计方案具备可行性,且油轮仍可实现到港即卸油,蒸馏装置混炼油种也可长时间保持稳定;模型的优化计算时间较短(小于15min),且对长输线收付及存油情况模拟准确,复合建模方法满足工业应用要求。     

融合环境因素的有限空间毒气扩散危害程度分析

为探究环境因素对毒气扩散危害程度的影响,通过对比有限空间内外环境差异,了解气体在有限空间内受力情况,并以传统高斯烟羽模型为基础,考虑扩散气体与有限空间边界碰撞产生的反射作用,建立了适用于有限空间气体扩散的改进高斯烟羽模型。深度剖析有限空间气体扩散环境,挖掘气体扩散主要关联因子,构建风速、地表粗糙度对有限空间气体扩散的影响函数;参照有限空间环境特征,分别设置3种不同风速与2种不同地表粗糙度,推求6种不同环境条件下气体扩散面积,阐明风速与地表粗糙度对有限空间气体扩散的影响程度。结果表明:在单一风速条件下,风速越高,地表粗糙度越低,洞室内H2S气体滞留时间越短,洞室内气体的扩散面积越小;风速越低,地表粗糙度越高,洞室内气体的扩散面积越大。     

基于弥散燃料颗粒开裂的金属基体裂纹特征模型

金属基弥散燃料元件在特殊工况下会发生表面起泡失效。燃料颗粒开裂是金属基体开裂的前提条件，只有当金属基体开裂后元件才会发生表面起泡。燃料颗粒开裂后，裂纹宽度和塑性区长度等裂纹特征决定了金属基体开裂行为。基于弹塑性断裂力学和应力平衡条件，建立了基于弥散燃料颗粒开裂的金属基体裂纹特征模型。计算结果表明：裂纹张开位移随退火温度和燃耗深度的升高而增加；裂纹尖端塑性区长度主要与退火温度相关。裂纹张开位移和塑性区长度的计算结果与实验数据均符合较好，验证了金属基体裂纹特征模型的有效性。     

R2D2: A scalable deep learning toolkit for medical imaging segmentation

Deep learning has gained a significant popularity in recent years thanks to its tremendous success across a wide range of relevant fields of applications, including medical image analysis domain in particular. Although convolutional neural networks (CNNs) based medical applications have been providing powerful solutions and revolutionizing medicine, efficiently training of CNNs models is a tedious and challenging task. It is a computationally intensive process taking long time and rare system resources, which represents a significant hindrance to scientific research progress. In order to address this challenge, we propose in this article, R2D2, a scalable intuitive deep learning toolkit for medical imaging semantic segmentation. To the best of our knowledge, the present work is the first that aims to tackle this issue by offering a novel distributed versions of two well-known and widely used CNN segmentation architectures [ie, fully convolutional network (FCN) and U-Net]. We introduce the design and the core building blocks of R2D2. We further present and analyze its experimental evaluation results on two different concrete medical imaging segmentation use cases. R2D2 achieves up to 17.5× and 10.4× speedup than single-node based training of U-Net and FCN, respectively, with a negligible, though still unexpected segmentation accuracy loss. R2D2 offers not only an empirical evidence and investigates in-depth the latest published works but also it facilitates and significantly reduces the effort required by researchers to quickly prototype and easily discover cutting-edge CNN configurations and architectures.