An Inverse Method for Determining Source Characteristics for Emergency Response Applications
An Inverse Method for Determining Source Characteristics for Emergency Response Applications
复制标题
确定应急响应应用源特性的逆向方法
DOI：
10.1007/s10546-012-9712-y
复制
发表时间：
2012
影响因子：
4.3
通讯作者：
Rudd A
中科院分区：
文献类型：
--
作者：
Rudd A
在室外环境中发生恶意或意外大气泄漏后，急救人员必须通过识别可能危及人类生命的区域来确保安全。为了迅速实现这一目标，需要有关源强度和位置以及释放的化学制剂类型的可靠信息。我们在这里提出了一种逆向建模技术，该技术使用来自化学传感器网络的有限数量的浓度测量值（考虑到单个稳定的地面源）来估计此类释放的源强度和位置，以及这些估计中的不确定性。该技术使用在气象风洞中进行的一组分散实验的数据进行评估，其中从无源示踪剂的地面点源发射的羽流中获得了浓度时间序列的同步测量。特别是，我们分析了对部署的传感器数量及其布置以及采样和模型误差的响应。我们发现，只要传感器放置得当并且采样误差得到控制，逆算法就可以用少至四个传感器生成可接受的源特性估计。发现在整个羽流的轮廓中具有至少三个传感器的配置优于所检查的其他配置。对由于使用短平均时间而造成的抽样误差影响的分析表明，源估计的不确定性随着抽样时间的减少而增加。这表明，大于约 5 分钟（满量程时间）的平均时间可以获得可接受的精度。
Following a malicious or accidental atmospheric release in an outdoor environment it is essential for first responders to ensure safety by identifying areas where human life may be in danger. For this to happen quickly, reliable information is needed on the source strength and location, and the type of chemical agent released. We present here an inverse modelling technique that estimates the source strength and location of such a release, together with the uncertainty in those estimates, using a limited number of measurements of concentration from a network of chemical sensors considering a single, steady, ground-level source. The technique is evaluated using data from a set of dispersion experiments conducted in a meteorological wind tunnel, where simultaneous measurements of concentration time series were obtained in the plume from a ground-level point-source emission of a passive tracer. In particular, we analyze the response to the number of sensors deployed and their arrangement, and to sampling and model errors. We find that the inverse algorithm can generate acceptable estimates of the source characteristics with as few as four sensors, providing these are well-placed and that the sampling error is controlled. Configurations with at least three sensors in a profile across the plume were found to be superior to other arrangements examined. Analysis of the influence of sampling error due to the use of short averaging times showed that the uncertainty in the source estimates grew as the sampling time decreased. This demonstrated that averaging times greater than about 5min (full scale time) lead to acceptable accuracy.
CBRN 传输和扩散的数据融合和预测以确保安全
DOI：
10.1109/aero.2008.4526584
发表时间：
2008
期刊：
2008 IEEE Aerospace Conference
影响因子：
--
作者：
S. E. Haupt;G. Young;K. Long;A. Beyer;A. Annunzio
通讯作者：
A. Annunzio
用于反演轨道问题的最小二乘法
影响因子：
0.9
作者：
R. Bannister
通讯作者：
R. Bannister
使用布里格斯参数化计算大气色散系数时的错误
影响因子：
5
作者：
R. Griffiths
通讯作者：
R. Griffiths