Numerical simulation of far-field blast loads arising from large TNT equivalent explosives

Large TNT equivalent explosions usually arise from accidents occurring during the transportation, storage, and manufacturing of chemicals relevant to process industries. The blast wave generated by the explosion will spread and interact with the surrounding factories and storehouses, damaging the building structures within several kilometers and causing significant casualties and property losses. This study aims to develop an efficient numerical simulation method to predict blast loads to estimate the consequences of accidents involving far-field free air bursts or surface burst explosions. Before its interaction with the interested target, a blast wave is generated in the numerical model by specifying the initial and boundary conditions of the disturbed air. Based on empirical data of incident overpressure, an explicit formula to calculate the air particle velocity is derived from the governing equations of a perfect inviscid gas. A simplified path line method is proposed to calculate the air density. The proposed method is applied to the LS-DYNA CESE solver to simulate the blast loads on building structures in the far field. Validations against empirical data and experiments indicate that the proposed method is sufficiently accurate for engineering applications and, through a case study, presents a more efficient performance than the LOAD_BLAST_ENHANCED (LBE) and mapping methods.     

Flooding and schools: experiences in Hull in 2007

Hull, a city in the East Riding of Yorkshire, United Kingdom, suffered severe flooding in June 2007, affecting some 8,600 households and most schools. Despite the potential for damage in such disasters, no studies of the effects of floods on teachers and schools in the UK appear to have been published previously. This study analysed the impacts of the floods on teachers in Hull in two stages: first through correspondence with Hull City Council and a mailed questionnaire to 91 head teachers of primary, secondary, and special schools; and second, through in‐depth interviews with head teachers from six flooded schools, representing different degrees of flood experience, and a questionnaire completed by eight teachers from the same schools. The findings reveal the importance and the complexity of the role of the school in the wider community in a time of crisis. The study highlights issues concerning preparedness for floods, support for schools, and flood protection for schools.     

引水放流方式对太湖贡湖示范区水质的影响

基于国家水专项太湖贡湖湾示范区水质水量调控的需求,构建了示范区的等比例缩放实体模型。通过研究模型中4种不同调水方案的效果,为示范区调水技术的比较与选择提供决策依据。研究中,通过测定模型中5个断面的流场数据,判断引水方式对模型流场的影响,以此评价不同调水方案效果。同时以墨汁作为示踪剂,通过不同引水放流方式下示踪剂的扩散场变化,验证不同断面流速测定对整个区域流场判断的准确性,从而分析引水放流方式对水质的影响。     

水稻土对Cu~(2+)吸附反应动力学及离子强度和磷酸根的影响

研究了水稻土对Cu2+的吸附反应动力学,并考察了p H和磷酸根2个因素对Cu2+吸附的影响。结果表明:水稻土对Cu2+的吸附反应速率可明显分为快、慢2个阶段,快速阶段主要是Cu2+结合在高亲和力位点,而慢速阶段则是结合在低亲和力位点。提高溶液p H可促进水稻土对Cu2+的吸附,降低溶液p H则将抑制Cu2+的吸附,这主要是因为p H可通过改变水稻土表面电荷的性质以及溶液Cu2+的形态来影响吸附反应。提高离子强度,将降低低p H条件下Cu2+的吸附量,而对高p H条件下Cu2+的吸附量影响较小,这表明水稻土对Cu2+存在很大比例的专性吸附。溶液中磷酸根的存在,可促进水稻土对Cu2+的吸附。本文所得到的研究结果对认识Cu2+在水稻土中的土壤环境行为及其污染控制有一定的理论意义。     

化学环境下的应力-渗流耦合对尾 矿库稳定性影响试验

通过扫描电镜（FE-SEM）、能谱分析（EDX）、X射线衍射（XRD）、LMS-30激光粒度分析等室内试验探究了尾矿库内存在的酸、碱离子对尾矿颗粒的沉降、微观形貌、物质组成以及粒径级配的影响；建立酸、碱影响下的孔隙比与渗透系数的数学关系模型，并将建立的模型用来表征尾矿库内的应力渗-流场两场耦合机制，实现代入有限元计算软件的目的。结果表明:化学因素的存在影响着尾矿颗粒的多项性状，酸性环境下尾矿颗粒发生溶蚀，部分金属元素流失；碱性环境下尾矿颗粒间生成胶结物质，孔隙出现以含氢氧化铁为主的絮状、团簇状堵塞物，改变了渗流速度；尾矿库内浸润线高度在碱性、中性、酸性环境下依次降低，而渗流速度依次升高。     

Numerical study on premixing characteristics and explosion process of starch in a vertical pipe under turbulent flow

Fire and explosion accidents are frequently caused by combustible dust, which has led to increased interest in this area of research. Although scholars have performed some research in this field, they often ignored interesting phenomena in their experiments. In this paper, we established a 2D numerical method to thoroughly investigate the particle motion and distribution before ignition. The optimal time for the corn starch dust cloud to ignite was determined in a semi-closed tube, and the characteristics of the flame propagation and temperature field were investigated after ignition inside and outside the tube. From the simulation, certain unexpected phenomena that occurred in the experiment were explained, and some suggestions were proposed for future experiments. The results from the simulation showed that 60–70 ms was the best time for the dust cloud to ignite. The local high-temperature flame clusters were caused by the agglomeration of high-temperature particles, and there were no flames near the wall of the tube due to particles gathering and attaching to the wall. Vortices formed around the nozzle, where the particle concentration was low and the flame spread slowly. During the explosion venting, particles flew out of the tube before the flame. The venting flame exhibited a “mushroom cloud” shape due to interactions with the vortex, and the flame maintained this shape as it was driven upward by the vortex.     

Strength and tightness evaluation method for pipe flange connections considering thermal effects

The pipe flange connection is widely applied in chemical, power plants, petrochemical, offshore oil and gas industries, and its strength and tightness are significant for the safe operation. However, there are still no practical and applicable strength and tightness evaluation methods for pipe flange connections working in dramatically varying temperatures. This paper proposed an approach to evaluate the pipeline's strength and sealing performance considering thermal effects in actual operating conditions by combining the experimental measurement and thermostructural analysis. The critical thermodynamic parameters are identified through measured temperature data in operating conditions, and then these parameters are used in the thermostructural analysis to obtain the actual temperature and stress fields. Then, the strength and tightness in complex temperature cases can be evaluated accurately. The pipe flange connection of a liquefied natural gas (LNG) fueling station is analyzed to verify the presented method's effectiveness. This method applies to evaluating the pipeline's strength and tightness and can predict the pipeline's performances under extreme temperatures using the tested data within the measurement range and the corresponding thermostructural analysis. Furthermore, the work in this paper also provides a reference for the design and analysis of pipe flange connections working in complex temperature conditions.     

基于BERT-BILSTM-CRF模型的电力行业事故文本智能分析*

为解决电力行业事故报告文本较长、语义复杂,难以进行有效文本识别问题,提出1种以BERT作为底层的预训练模型,并设计1种双重注意力机制编码器,结合BILSTM-CRF深度挖掘事故文本语义特征,从而实现文本智能分析。首先构建电力词典,通过对BERT预训练,进行BIO标注,然后引入BILSTM-CRF模型实现对文本标签智能分类,最后将该模型与现行其他4种深度学习模型进行对比。研究结果表明:该模型智能识别精确率、召回率及F1值(查准率)均达到约97%,较其他4种模型中效果最好的模型分别提高0.02,0.03,0.02。研究结果可为电力行业事故报告文本分析提供1种新思路。     

水稻光合同化碳在土壤中的矿化和转化动态

作物光合碳是"大气-植物-土壤"碳循环的重要组成部分,是农田土壤有机碳的重要来源,然而其在土壤碳库中的矿化和转化动态尚不清楚.应用室内模拟培养实验,研究水稻收获后输入土壤的光合同化碳在土壤碳库中的矿化及其转化特征.结果表明,100 d的培养期内,原有有机碳的平均矿化速率在4.44~17.8μg·(g·d)-1之间,而光合碳(新碳)的矿化速率则在0.15~1.51μg·(g·d)-1之间.光合同化碳的输入对土壤活性碳库(DOC、MBC)的转化产生显著影响,在培养期内,14C-DOC的转化量为1.89~5.32 mg·kg-1,转化速率的变化幅度为0.18~0.34 mg·(kg·d)-1,原有DOC则在61.13~90.65 mg·kg-1,减少幅度为4.10~5.48 mg·(kg·d)-1;14C-MBC和原有MBC的转化量分别为10.92~44.11 mg·kg-1和463.31~1 153.46mg·kg-1,转化速率变化幅度分别为0.80~2.87 mg·(kg·d)-1和41.60~74.46 mg·(kg·d)-1,说明水稻光合碳的输入对MBC的周转要大于DOC的周转.而且,与原有有机碳相比,输入的"新碳"易被微生物矿化分解,100 d的培养期内,有13.5%~20.2%的新碳被矿化分解,而仅2.2%~3.7%的原有有机碳被矿化分解,光合同化碳的输入对维持稻田土壤的碳汇功能具有重要作用.     

2000年1月15日姚安6.5级地震余震序列震源机制解与震源区应力场分析

本文利用垂直向的Pg和Sg波的最大振幅比方法,计算2000年1月15日云南姚安6.5级地震后余震序列震源机制解,通过统计和系统聚类分析,再结合震中分布图,综合分析了云南姚安6.5级地震的震源机制解和震源区应力场破裂特征,研究结果表明震源断层的走向为SEE-NWW占主导,其平均解为120°,震区主压应力轴平均解为145°,即SSE向,与震源区现今构造应力场主压应力方向一致,表明余震的应力场主要受区域应力场的控制.