ATD: Stochastic algorithms for countering chemical and biological threats

ATD：应对化学和生物威胁的随机算法

• 批准号: 1016441
• 负责人: Jan Hannig
• 金额: $ 89.62万
• 依托单位: University of North Carolina at Chapel Hill
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-10-01 至 2015-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1016441&HistoricalAwards=false
• 关键词: ATD; Stochastic; algorithms; countering; chemical

The vision for the proposed work is to capitalize on experience in specific areas involving biological / chemical attacks and to develop as wide-ranging algorithms as possible for countermeasures to such threats. These will be based on stochastic modeling to describe (deterministic and random) features of contamination location and spread from which algorithms to detect threats may be developed. Standard parametric models will be examined for applicability, along with development of appropriate space-time random fields tailored to the specific situation. This is similar in approach to current use of Gaussian fields to model trends and fluctuations in pollution regulation studies, requiring few specific assumptions, but allowing application of general methods such as Central Limit and Extreme Value Theory. The starting point will be the PI's prior experience in assisting EPA scientists and engineers with the development of statistical designs for assuring confidence in complete decontamination of anthrax from buildings in the face of budgetary limitations which was based on very simple assumptions such as statistical independence of positions of anthrax deposits. Better and more cost effective statistical conclusions are likely to result from the proposed models - relaxing the independence assumptions. Clearance of contaminated buildings is typically achieved by Chlorine Dioxide fumigation - a highly effective process since the gas under appropriate pressure and duration of application can be expected to reach all areas where contaminant may be lodged. The cost of and time required for such clearance can be quite staggering (e.g. estimates of $130 million for just the Brentwood postal facility over a 26 month period, and $1 billion in all for the total of the early post 9/11 incidents). Additionally, in spite of a high expectation that fumigation achieves total clearance, systematic sampling of surfaces for residual anthrax is done for confirmation. This cannot be exhaustive in view of the high cost of sampling and laboratory analysis and the sheer number of samples required for reasonably complete coverage. Hence, determinations are made (using simple statistical assumptions) of the extent of sampling required to ensure that if all samples turn out to be negative, there is specified very high confidence that the entire area of concern is entirely contaminant free. This seems a reasonable approach to give adequate added assurance of successful clearance since if even one sample tested positive for anthrax, entire fumigation would have to be repeated. Current routines for determining necessary sampling to achieve a given clearance confidence have been developed under simple assumptions. The future work on this topic will use the more realistic statistical assumptions of stochastic modeling which are expected to lead to algorithms, which are both more accurate and cost efficient. The above case of building decontamination is described as a starting point for much more complex investigations such as detection of the presence of contaminants being actively introduced in an HVAC system for circulation throughout a building - a topic which has received some previous attention in the literature. A related area of initial activity concerns the discrimination between toxic substances such as anthrax and harmless powders for which novel statistical (for example, wavelet) methods are already being developed in collaboration with EPA researchers. Further, the issues involved in such "Homeland examples" arise in various forms in the detection of battlefield threats (such as hidden IED's) with attendant problems of signal detection - subjects for consideration under this grant. Finally, the methods are expected to have useful "non-terrorism" applications such as to the spread of pandemics and risks of importation of anthrax bearing animal products such as meat and hides.

拟议工作的愿景是利用涉及生物/化学攻击的特定领域的经验，并开发尽可能广泛的算法来应对此类威胁。这些将基于随机建模来描述污染位置和传播的（确定性和随机）特征，并可从中开发检测威胁的算法。将检查标准参数模型的适用性，并根据具体情况开发适当的时空随机场。这与当前使用高斯场来模拟污染监管研究中的趋势和波动的方法类似，需要很少的具体假设，但允许应用中心极限和极值理论等通用方法。起点将是 PI 之前协助 EPA 科学家和工程师开发统计设计的经验，以确保在面临预算限制的情况下对建筑物中的炭疽进行完全净化的信心，这是基于非常简单的假设，例如炭疽沉积位置的统计独立性。 所提出的模型可能会产生更好、更具成本效益的统计结论——放宽独立性假设。 清除受污染的建筑物通常是通过二氧化氯熏蒸来实现的，这是一种非常有效的过程，因为在适当的压力和持续时间下，气体预计会到达所有可能存在污染物的区域。此类清理所需的成本和时间可能相当惊人（例如，仅布伦特伍德邮政设施在 26 个月内的成本估计就高达 1.3 亿美元，而 9/11 事件初期的总成本则高达 10 亿美元）。此外，尽管人们对熏蒸实现完全清除抱有很高的期望，但还是对表面进行了残留炭疽的系统采样以进行确认。鉴于采样和实验室分析的高昂成本以及合理完整覆盖所需的样本数量巨大，这不可能是详尽无遗的。因此，确定（使用简单的统计假设）所需的采样范围，以确保如果所有样本结果均为阴性，则表明整个关注区域完全没有污染物的置信度非常高。这似乎是一种合理的方法，可以为成功清除提供充分的额外保证，因为即使有一个样本炭疽测试呈阳性，也必须重复整个熏蒸。当前用于确定必要采样以实现给定间隙置信度的例程是在简单的假设下开发的。该主题的未来工作将使用随机建模的更现实的统计假设，预计将产生更准确且更具成本效益的算法。 上述建筑物净化案例被描述为更复杂的调查的起点，例如检测主动引入 HVAC 系统中以在整个建筑物内循环的污染物的存在 - 这一主题先前在文献中受到了一些关注。初始活动的一个相关领域涉及区分炭疽等有毒物质和无害粉末，目前已经与 EPA 研究人员合作开发了新的统计（例如小波）方法。此外，此类“国土例子”中涉及的问题在检测战场威胁（例如隐藏的简易爆炸装置）时以各种形式出现，并伴随着信号检测问题——这是本次赠款下需要考虑的主题。最后，这些方法预计将具有有用的“非恐怖主义”应用，例如流行病的传播和进口带有炭疽的动物产品（例如肉类和兽皮）的风险。