电子产品野外环境下温循加速载荷谱编制方法

目的 将电子产品在野外环境下日变化波动与季节差异明显的温度载荷编制成温循载荷谱和转换为加速载荷谱。方法 通过四点雨流计数法提取原谱中的载荷循环信息,对提取的循环信息进行分布拟合、相关性检验等统计分析,进而构建循环均值与范围值的联合概率密度函数,再运用概率密度法,编制出8×8二维环境载荷谱。在二维载荷谱基础上,编制出温循载荷谱,使用针对电子部件参数修正的加速方程转化为加速载荷谱。结果 利用野外作业现场1个作业周期内的气温纪录,提供了一套编制温循载荷谱和转换加速载荷谱的合理化流程和解决方案。结论 该制谱方法可以利用原始环境谱中绝大部分有效信息,较好地还原电子部件野外作业阶段经历的温度变化过程,为电子产品的加速寿命试验和使用寿命预测奠定基础。     

电化学探头法测定水中溶解氧分析方法的介绍

根据电化学探头法的原理,对便携式溶解氧测定仪测定水中溶解氧的分析方法进行了介绍,并与碘量法进行分析对比。     

实行年度目标考核是促进监测工作发展的有效方法

实行年度目标责任制考核 ,为监测站的改革和发展找到了一条有效途径。文章通过对年度目标考核责任制的方式、方法及实施后所取得成效的介绍 ,为监测站的改革与发展提供了借鉴     

基于Bishop条分法的多点多向地震动作用下边坡稳定性分析

以人工合成的多点、多向地震加速度时程作为地震动输入,基于Bishop条分法推导了地震边坡稳定安全系数的表达公式。在此基础上,针对某一具体算例,分析了不同地震峰值加速度下的不同坡高边坡稳定安全系数的变化规律,并与单点、单向地震动输入的结果进行了对比。结果表明,对于本文给出的算例,在坡高与地震峰值加速度都相同的条件下,多点、多向地震作用下的边坡安全系数要大于单点、单向作用下的安全系数;当坡高小于30 m、地震峰值加速度小于0.1 g时,多点、多向地震动作用下的边坡安全系数与单点、单向相差不大;当坡高大于30 m、地震峰值加速度大于0.1 g时,多点、多向地震动作用下的边坡安全系数相对单点、单向要小36%以上,此时边坡稳定性评价必须考虑地震动的多点、多向特性。     

原状黄土的反压饱和法试验研究

含水量是黄土液化特性研究中的一个至关重要的参数,对原状黄土进行充分饱和是饱和黄土动三轴试验中一个不可回避的课题。以WF公司生产的WF12440型空心圆柱扭剪仪为实验平台,运用反压饱和法,对室内原状黄土进行了饱和试验研究。该仪器提供3种不同加压方式增加围压和反压(孔压),即手动加压、自动加压和线性持续加压,通过检测孔隙压力系数B值是否达到0.95以上来判断黄土是否完全饱和。试验表明,即便是初始饱和度较低的原状黄土,也可以采用反压饱和法,在较短的时间内使孔压系数B值达到0.95以上,实现完全饱和,具体可以采用线性连续加压方式;初始压力差,即围压和反压之差一般可设为10 kPa,起始围压也设为10 kPa,太大或太小都会对试样造成破坏;如果孔压在1分钟内的变化值小于围压和反压之间压力差的5%,则认为孔压稳定,即可进行B值检测。     

林聪悟-直线法在基于美国混凝土规范设计中的程序实现

首先,阐述了美国ACI318-08规范中钢筋混凝土受弯、受压构件的设计原理和基本假定。与我国混凝土结构设计规范不同,ACI318-08规范是根据构件的受力破坏形态来确定名义抗压和抗弯承载力的折减系数的,相对于延性破坏,脆性破坏构件的承载力折减较多。然后,由平衡条件、平截面假定及Newton迭代格式,推导出林聪悟-直线法的计算公式。编制程序实现该算法时,须根据最大、最小配筋率的规定对迭代区域进行限定;在确定P-M相关曲线上的拐点位置的基础上,实现中性轴高度在曲线上的分段迭代。通过在曲线拐点处设置微小增量及自动调整中性轴高度等方法,解决了程序计算时可能出现的迭代发散问题。算例表明,所编制程序的计算结果具有很高的精度。     

智能手机应用程序使用与操作的驾驶分心风险影响研究

为研究智能手机应用程序操作方式与使用行为对驾驶分心影响的问题,探讨智能手机程序操作方式对驾驶分心影响的优劣关系,基于结构方程模型提出4个因果关系假设,构建涵盖程序使用、驾驶分心、驾驶绩效等潜变量的智能手机使用行为影响的结构方程模型。通过收集线下问卷的方式进行调查,搭建模拟场景,设计6项实验方案,通过驾驶模拟实验方式收集相关数据,建立相对偏差矩阵。研究结果表明：手机通话功能的使用(路径系数0.472)对驾驶分心影响显著,手机导航功能使用(路径系数0.256)、手机音乐功能使用(路径系数0.249)对驾驶分心影响不显著。语音交互方式均优于手动操作方式,其中语音交互启动导航方式(F₃=0.019)的影响最小。研究结果可对道路驾驶情况下智能手机应用使用与操作方式的研究起推动作用。     

Structural equation model of the influence of noise annoyance on miners’ unsafe behavior in coal mines

Miners' unsafe behavior (UB) is the main cause of coal mine accidents. Previous research has suggested that excessive noise in tunnels impacts miners' temperaments and safe production behavior. To explore the influence of noise on UB, four different dimensions of noise annoyance were identified: cognitive, emotional, communication, and physical mechanism annoyance. The coal mine noise annoyance scale, miners' unsafe behavior intention (UBI) scale, and miners’ UB scale were developed according to different dimensions. In the first survey, a total of 200 questionnaires were distributed in the two coal mines, and 193 valid questionnaires were recovered. Exploratory factor analysis was conducted, and invalid items were removed according to the analysis results to form the final scale. Then, 500 final scales were distributed in two Chinese coal mines, and 482 valid questionnaires were collected. Confirmatory factor analysis was conducted by collating the data of the second questionnaire. Based upon the structural equation model (SEM), the SEM of the influence of noise annoyance degree on UB and the path analysis with latent variable path analysis with the latent variables (PA-LVs) mediating model of the effect of UBI on UB were established, and the path coefficients with fitting data of the model were analyzed. The results indicated that the four dimensions of coal mine noise annoyance had a strong positive impact on UB, which was reduced by less noise annoyance. In addition, the Bootstrap method was used to verify the mediating method among the four dimensions of noise annoyance, cognitive annoyance, emotional annoyance, with communication annoyance indirectly affecting UB through UBI. The research results provide theoretical support for reducing the UB of miners and improving coal mine safety levels.     

The TNO multi-energy method combined to mathematical programming and computational fluid dynamics for optimisation of gas detectors

Gas leakage is a matter of concern for several industries such as oil and gas, mining, food, and healthcare. When the industry considers gas detectors, the main questions are: How many gas detectors are required? Where is the best location to install them? To answer these questions Computational Fluid Dynamics (CFD) simulations and optimisation procedures are employed to calculate the plume location and plume volume to better position the gas detectors. We investigated how the optimisation cell size for the set covering problem can be calculated based on a given explosion overpressure threshold. Resorted by the multi-energy explosion model, we calculate the flammable cloud volume associated with a pre-defined overpressure value. The cloud volume is applied in the solution of the set covering problem and an optimal set for the gas detectors is obtained. The final gas detector network (number and location of the devices) is validated against CFD simulations for small releases. The results provide evidence that the optimal gas detector networks is able to detect gas leaks within a feasible time.     

Effect of particle size on CO adsorption and thermodynamic analysis

The liquid nitrogen adsorption method was used to characterize the pore structure of non-cohesive coal in the 061,404 working face of the Lingxin coal mine. The amount of specific surface area of micropores in the sample continuously rose as particle sizes reduced. The volumetric method was used to measure the CO isothermal adsorption curves of three samples (sample I, 0.425–0.25 mm, sample II, 0.18–0.25 mm, and sample III, 0.15–0.18 mm). The experimental results were fitted by the Langmuir model. According to the experimental results, it was conducive to CO adsorption with the conditions of high pressure and low-temperature. The decrease in grain diameter increased the number and volume of micropores in the sample, which improved the adsorption capacity of the sample. In addition, according to the adsorption data, the CO adsorption thermodynamics of three samples were analyzed, including surface potential (Ω), Gibbs free energy change (ΔG) and entropy change (ΔS). The results demonstrated that CO adsorption by coal was a spontaneous process. Sample III has the most substantial adsorption capacity, whereas the sample I has the weakest adsorption capacity.