Automatic real-time interpolation of radiation hazards: prototype and system architecture considerations

Detecting and monitoring the development of radioactive releases in the atmosphere is important. In many European countries monitoring networks have been established to perform this task. In the Netherlands the National Radioactivity Monitoring network (NRM) was installed. Currently, point maps are used to interpret the data from the NRM. Automatically generating maps in realtime would improve the interpretation of the data by giving the user a clear overview of the present radiological situation and provide an estimate of the radioactivity level at unmeasured locations. In this paper we present a prototype system that automatically generates real-time maps of radioactivity levels and presents results in an interoperable way through a Web Map Service. The system defines a first step towards a emergency management system and is suited primarily for data without large outliers. The automatic interpolation is done using universal kriging in combination with an automatic variogram fitting procedure. The focus is on mathematical and operational issues and on architectural considerations on how to improve the interoperability and portability of the prototype system

Using rainfall radar data to improve interpolated maps of dose rate in the Netherlands

The radiation monitoring network in the Netherlands is designed to detect and track increased radiation levels, dose rate more specifically, in 10-minute intervals. The network consists of 153 monitoring stations. Washout of radon progeny by rainfall is the most important cause of natural variations in dose rate. The increase in dose rate at a given time is a function of the amount of progeny decaying, which in turn is a balance between deposition of progeny by rainfall and radioactive decay. The increase in progeny is closely related to average rainfall intensity over the last 2.5 h. We included decay of progeny by using weighted averaged rainfall intensity, where the weight decreases back in time. The decrease in weight is related to the half-life of radon progeny. In this paper we show for a rainstorm on the 20th of July 2007 that weighted averaged rainfall intensity estimated from rainfall radar images, collected every 5 min, performs much better as a predictor of increases in dose rate than using the non-averaged rainfall intensity. In addition, we show through cross-validation that including weighted averaged rainfall intensity in an interpolated map using universal kriging (UK) does not necessarily lead to a more accurate map. This might be attributed to the high density of monitoring stations in comparison to the spatial extent of a typical rain event. Reducing the network density improved the accuracy of the map when universal kriging was used instead of ordinary kriging (no trend). Consequently, in a less dense network the positive influence of including a trend is likely to increase. Furthermore, we suspect that UK better reproduces the sharp boundaries present in rainfall maps, but that the lack of short-distance monitoring station pairs prevents cross-validation from revealing this effect

Optimization of mobile radioactivity monitoring networks

In case of a nuclear accident, decision makers rely on high-resolution and accurate information about the spatial distribution of radioactive contamination surrounding the accident site. However, the static nuclear monitoring networks of many European countries are generally too coarse to provide the desired level of spatial accuracy. In the Netherlands, authorities are considering a strategy in which measurement density is increased during an emergency using complementary mobile measuring devices. This raises the question, where should these mobile devices be placed? This article proposes a geostatistical methodology to optimize the allocation of mobile measurement devices, such that the expected weighted sum of false-positive and false-negative areas (i.e. false classification into safe and unsafe zones) is minimized. Radioactivity concentration is modelled as the sum of a deterministic trend and a zero-mean spatially correlated stochastic residual. The trend is defined as the outcome of a physical atmospheric dispersion model, NPK-PUFF. The residual is characterized by a semivariogram of differences between the outputs of various NPK-PUFF model runs, designed to reflect the effect of uncertainty in NPK-PUFF meteorological inputs (e.g. wind speed, wind direction). Spatial simulated annealing is used to obtain the optimal monitoring design, in which accessibility of sampling sites (e.g. distance to roads) is also considered. Although the methodology is computationally demanding, results are promising and the computational load may be considerably reduced to compute optimal mobile monitoring designs in nearly real time

Real-time automatic interpolation of ambient gamma dose rates from the Dutch radioactivity monitoring network

Detection of radiological accidents and monitoring the spread of the contamination is of great importance. Following the Chernobyl accident many European countries have installed monitoring networks to perform this task. Real-time availability of automatically interpolated maps showing the spread of radioactivity during and after an accident would improve the capability of decision makers to accurately respond to a radiological accident. The objective of this paper is to present a real-time automatic interpolation system suited for natural background radioactivity. Interpolating natural background radiation allows us to better understand the natural variability, thus improving our ability to detect accidents. A real-time automatic interpolation system suited for natural background radioactivity presents a first step towards a system that can deal with radiological accidents. The interpolated maps are produced using a combination of universal kriging and an automatic variogram fitting procedure. The system provides a map of (1) the kriging prediction, (2) the kriging standard error and (3) the position of approximate prediction intervals relative to a threshold. The maps are presented through a Web Map Service (WMS) to ensure interoperability with existing Geographic Information Systems (GIS

Optimization of mobile radioactivity monitoring networks

In case of a nuclear accident, decision makers rely on high-resolution and accurate information about the spatial distribution of radioactive contamination surrounding the accident site. However, the static nuclear monitoring networks of many European countries are generally too coarse to provide the desired level of spatial accuracy. In the Netherlands, authorities are considering a strategy in which measurement density is increased during an emergency using complementary mobile measuring devices. This raises the question, where should these mobile devices be placed? This article proposes a geostatistical methodology to optimize the allocation of mobile measurement devices, such that the expected weighted sum of false-positive and false-negative areas (i.e. false classification into safe and unsafe zones) is minimized. Radioactivity concentration is modelled as the sum of a deterministic trend and a zero-mean spatially correlated stochastic residual. The trend is defined as the outcome of a physical atmospheric dispersion model, NPK-PUFF. The residual is characterized by a semivariogram of differences between the outputs of various NPK-PUFF model runs, designed to reflect the effect of uncertainty in NPK-PUFF meteorological inputs (e.g. wind speed, wind direction). Spatial simulated annealing is used to obtain the optimal monitoring design, in which accessibility of sampling sites (e.g. distance to roads) is also considered. Although the methodology is computationally demanding, results are promising and the computational load may be considerably reduced to compute optimal mobile monitoring designs in nearly real time

A time projection chamber with microstrip read-out

International audienceThe design and testing of a novel detector for heavy-ion physics in the intermediate-energy regime is described. This detector consists of a large drift chamber with microstrip read-out in combination with thick plastic scintillators . With this system particle identification and energy determination with high spatial resolution and multiple hit capacity is achieved