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Predicting the persistence of explosives materials

机译:预测爆炸物的持久性

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Trace quantities of explosives left behind by those handling explosives materials present an opportunity to identify boththe handlers and the objects they have contaminated. Understanding the evolution of these particles is critical for tailoringdetection strategies of optical techniques as well as non-optical contact harvesting methods. We are working towards acomplete particle persistence model that captures the contribution of environmental factors such as temperature, airflow,and humidity as well as physical factors such as vapor pressure, particle size and inter-particle spacing to predict particlelifetimes for explosives and other chemicals. Our approach involves depositing particles onto glass substrates using particlesizes and loadings known to be deposited by fingerprint deposition, and then studying their behavior in a custom flow cellwith controlled airflow, humidity and temperature. Optical microscope images of the sample taken at fixed time intervalsare analyzed to monitor particle sublimation, and those images used to determine the mass loss as a function of time. Thedata are then fit to a model and from the fitting constants the sublimation rate is calculated. We find that the measuredsublimation rate exhibits the expected dependence on vapor pressure for a given material, and that the dependence onvapor pressure is largely material independent. We focus on the behavior of a model material, 2,4-dinitrotoluene and selectexplosive materials under controlled conditions.We are able to use the data from 2,4-dinitrotoluene to predict the behaviorof 2,4,6-trinitrotoluene using the physical properties (e.g., vapor pressure) of the respective materials and compare it toexperimental results.
机译:那些处理爆炸物的人留下的痕量炸药为人们提供了机会来识别这两种 处理程序及其污染的物体。了解这些粒子的演变对于定制至关重要 光学技术以及非光学接触收集方法的检测策略。我们正在努力 完整的粒子持久性模型,可捕获环境因素(例如温度,气流, 和湿度以及物理因素(例如蒸气压,粒度和粒子间间距)来预测粒子 炸药和其他化学品的使用寿命。我们的方法涉及使用粒子将粒子沉积到玻璃基板上 已知通过指纹沉积来沉积的大小和负载,然后在自定义流通池中研究其行为 具有受控的气流,湿度和温度。以固定的时间间隔拍摄的样品的光学显微镜图像 进行分析以监测粒子的升华,并使用这些图像确定质量损失随时间的变化。这 然后将数据拟合到模型中,并根据拟合常数计算升华率。我们发现 升华率显示出对给定材料的蒸气压的预期依赖性,并且对 蒸气压在很大程度上与材料无关。我们关注模型材料2,4-二硝基甲苯的行为,然后选择 可控条件下的爆炸性材料。我们能够使用2,4-二硝基甲苯中的数据来预测行为 2,4,6-三硝基甲苯使用相应材料的物理性质(例如蒸气压)进行比较,并与 实验结果。

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