火箭弹电点火系统抗电磁危害加固技术研究

火箭弹、导弹等武器的电发火系统在恶劣的电磁环境中可能会受到意外的电磁辐照使其安全性受到威胁。通过对火箭弹电发火系统电磁危害机理进行分析,得出了一些火箭弹电发火系统电磁危害防护的基本方法和提高火箭弹电发火系统抗电磁危害性能的设计原则。     

铁阳极电凝聚法处理活性红241染料废水能耗分析

对铁阳极电凝聚处理活性红241染料废水过程影响电能消耗的影响因素进行了考察.结果表明:电流密度、染料废水初始pH、染料废水温度、电解质浓度以及染料浓度的变化均能对能耗和脱色效率产生较大影响;电流效率受电流密度、染料废水初始pH、电解质浓度的影响较大,受染料废水温度和初始浓度影响不大;对于浓度为50 mg/L的活性红241染料废水,在电流强度为12.5 A/m2、电解温度为25 ℃、硫酸钠浓度为0.01 mol/L、pH为7.53、电解时间为60 min的实验条件下,染料废水脱色率达92.7%,电能消耗为1.53kWh/kg dye,电流效率为94.2%.     

富氧助燃技术减少NOx排放

富氧助燃技术是最新节能环保技术,可以用于各种燃料和多种窑炉.不但显著节能、增产,而且能延长炉龄,环保达标,通常几个月就能收回全部投资.富氧燃烧能有效地降低NOx的排放量,在环境问题得到日益重视的今天富氧助燃技术具有显著的经济意义和社会意义.先介绍其节能和环保的机理,然后再介绍有关典型工艺流程、技改要点和典型应用实例.并对热力型NOx的生成进行了探讨.     

核能利用与环境保护

通过分析核能的起源与发展,世界核电发展现状,论述核能对环境影响和核能利用的环侏对策,预测核能是今后解决能源危机最主要也是最本质的途径,并对核能大发展的情况下可能对环境产生的影响进行了评述。     

酒精蒸气/烟草粉尘两相混合体系最小点火能试验研究

在烟草加工的加香工序,挥发的酒精和搅拌混料产生的烟草粉尘形成气粉混合体系,其燃爆特性相较于单相烟草粉尘有较大变化。对20 L爆炸球进行了部分改造,可完成20℃～80℃环境温度、100%LEL以下酒精蒸气浓度、最大2 J电火花能量组合的气粉混合物的最小点火能测试。选用烘丝和加香烟草粉尘做对比,探究了环境温度和酒精蒸气浓度对酒精蒸气/烟草粉尘两相混合体系点火能的影响规律。结果表明：相同环境温度下,加香烟草粉尘的最小点火能比烘丝烟草粉尘低;加香粉尘、烘丝粉尘及混合体系的最小点火能随环境温度变化的趋势一致,均随温度的升高而降低;加入10%LEL的酒精蒸气后,相同温度下气粉混合体系的最小点火能低于单相烟草粉尘。随着环境温度的升高,二者的差值逐渐减小,酒精蒸气诱导烟草粉尘最小点火能降低的能力逐步减小甚至消失;在电点火条件下,当酒精蒸气浓度低于50%LEL时,气粉混合体系较难被点燃,当酒精蒸气浓度高于75%LEL时,混合体系较易被点燃。     

Prediction of BLEVE mechanical energy by implementation of artificial neural network

In the event of a BLEVE, the overpressure wave can cause important effects over a certain area. Several thermodynamic assumptions have been proposed as the basis for developing methodologies to predict both the mechanical energy associated to such a wave and the peak overpressure. According to a recent comparative analysis, methods based on real gas behavior and adiabatic irreversible expansion assumptions can give a good estimation of this energy. In this communication, the Artificial Neural Network (ANN) approach has been implemented to predict the BLEVE mechanical energy for the case of propane and butane. Temperature and vessel filling degree at failure have been considered as input parameters (plus vessel volume), and the BLEVE blast energy has been estimated as output data by the ANN model. A Bayesian Regularization algorithm was chosen as the three-layer backpropagation training algorithm. Based on the neurons optimization process, the number of neurons at the hidden layer was five in the case of propane and four in the case of butane. The transfer function applied in this layer was a sigmoid, because it had an easy and straightforward differentiation for using in the backpropagation algorithm. For the output layer, the number of neurons had to be one in both cases, and the transfer function was purelin (linear). The model performance has been compared with experimental values, proving that the mechanical energy of a BLEVE explosion can be adequately predicted with the Artificial Neural Network approach.     

基于压电传感板的建筑疏散照明技术

在当今世界,电力、能源和安全是人们日常生活的基本要求。为了应对日益增长的能源需求,最终的解决办法是实施可再生能源,然后将其用于人类的安全。可再生能源需要以它们各自正确的方式实施。研究基于压电传感器片的迈步发电装置,并演示了如何利用这些能量实现建筑物疏散照明。我们在传感器的下方和顶部分别固定了木板和可移动网螺栓,利用压电传感器系统,行人可以通过迈步向发电装置施加电能,另外,将硅凝胶粘贴在位于下部木板空洞中的所有传感器顶部。当有人踩到板上时,就会自动施加压力。在木板的顶部和底部设置了一个孔,以便随时调整在底部和顶板之间安装的可移动网螺栓。烟雾传感器用于启动灯光。使用这种设备,我们实现了建筑物疏散路径上的LED灯正常运行。结果表明,这种安全发电的设计和方法具有一定的实用价值,同时也满足了全球对能源的需求。     

初始氧化温度对浸水长焰煤二次氧化特性的影响机制

为揭示不同初始氧化温度下浸水长焰煤的氧化自燃特性,利用红外光谱和热分析实验手段以及MS数值模拟方法研究其氧化自燃规律,并采用线性拟合的方法阐述自由基变化特性。结合分子键能的变化,分析浸水条件下二次氧化的煤氧链式反应过程。研究结果表明:经过120 ℃预氧化后,浸水风干长焰煤的还原性官能团甲基、亚甲基、羟基均高于原煤,而羰基、羧基低于原煤;与原煤相比,浸水风干后的煤预氧化温度在120 ℃时最大升温速率最高（0.036 9 ℃/s）,表现出更强的自燃倾向性;MS模拟优化得出煤中各官能团在预氧化120 ℃时键能变化较大,结合热分析实验,确立预氧化后浸水风干煤体氧化自燃特性机制。     

Applications of dust explosion hazard and disaster prevention technology

Powdered materials are widely used in industrial processes, chemical processing, and nanoscience. Because most flammable powders and chemicals are not pure substances, their flammability and self-heating characteristics cannot be accurately identified using safety data sheets. Therefore, site staff can easily underestimate the risks they pose. Flammable dust accidents are frequent and force industrial process managers to pay attention to the characteristics of flammable powders and create inherently safer designs.This study verified that although the flammable powders used by petrochemical plants have been tested, some powders have different minimum ignition energies (MIEs) before and after drying, whereas some of the powders are released of flammable gases. These hazard characteristics are usually neglected, leading to the neglect of preventive parameters for fires and explosions, such as dust particle size specified by NFPA-654, MIE, the minimum ignition temperature of the dust cloud, the minimum ignition temperature of the dust layer, and limiting oxygen concentration. Unless these parameters are fully integrated into process hazard analysis and process safety management, the risks cannot be fully identified, and the reliability of process hazard analysis cannot be improved to facilitate the development of appropriate countermeasures. Preventing the underestimation of process risk severity due to the fire and explosion parameters of unknown flammable dusts and overestimation of existing safety measures is crucial for effective accident prevention.     

Trends in Raindrop Kinetic Energy with Modeled Climate Warming in the Lake Tahoe Basin

Two means by which climate change may increase surface soil erosion in mountainous terrain are: (1) increasing the frequency of extreme rainfall events and (2) decreasing the duration of snow cover on bare soil. We used output from four general circulation models (GCMs) and two greenhouse gas trajectories to produce a suite of hydrologic variables at a daily time‐step for historic and projected 21st Century conditions. We statistically disaggregated the daily rainfall to hourly, using hourly rainfall from a network of nine weather stations in the Tahoe Basin, and filtered out rain falling on a snowpack. We applied published equations to convert hourly intensity to raindrop kinetic energy (KE) for each day and grid cell in the Basin, averaged across grid cells, and created time series of total annual and maximum annual hourly kinetic energy (TKE and MKE) on snow‐free ground. Using the Generalized Extreme Value distribution, we calculated the significance of long‐term trends in KE on snow‐free ground, and estimated energy levels for return periods of 2, 20, and 100 years. We then detrended the snowpack data and compared the resulting trends in KE with the trends resulting from changes in both rainfall energy and snowpack under two GCMs. Principal findings include (1) upward trends in MKE, (2) stronger upward trends in TKE; and (3) an effect of increasing rainfall intensities on KE in some cases, and a strong effect of reduced snowpack in all cases examined.