Vladimir Kondrasovs

Moving Sources Detection Algorithm for Radiation Portal Monitors Used in a Linear Network

To monitor radioactivity passing through a vehicle such as a pedestrian, a car, a train or a truck, Radiation Portal Monitors (RMP) are commonly employed. These detection systems consist of a large volume detector set close to the potential source path. An alarm is then triggered when the signal rises over a threshold initially estimated in view of the natural background signal. The approach developed in this work makes use of several detectors in a network along the source path. The correlation detection approach is elaborated to take into account the temporal periodicity of the signals taken by all distributed sensors as a whole. This new detection method is then not based only on counting statistics but also on the temporal series analysis. Therefore, a specific algorithm has been developed in our laboratory for this security application and shows a significant improvement, especially in terms of detection probability increase and false alarm reduction. This paper presents the theoretical approach and promising results obtained by simulation.

MA-NRBC: First successful attempt for neutron gamma discrimination in plastic scintillators

In this paper, a new electronic hardware and algorithms enabling discrimination between neutron and gamma in plastic scintillators together with the first associated experimental results, are presented. This electronic platform is mainly based onto a quad 200 MHz ADCs. Using phase rotating, it is possible to sample the signal up to 800 MHz equivalent, with 8 bits precision. This sampling frequency allows a real time signal processing. Despite all previous work, we have shown during this study that it is possible to discriminate neutron from gamma in plastic scintillators even for low energy neutrons (less than 10 MeV). Two patents have been accepted and registered; the first deals with the intrinsic signal processing and the second with thermal stabilization methods of photomultiplier tubes. The system could be used up to 100 000 events per second (both gamma and neutron). This system is currently dedicated to homeland security devices; this is due to its response time (in the order of 1 up to 3 seconds). The next step is to implement the thermal stabilization algorithm in the FPGA and microcontroller to obtain a global system free from any trouble caused by the environment thermal variations. This aspect of the research is crucial for measurements in the field. The time response should also be improved to make it a reliable alternative to Helium-3 shortage for neutron detection at borders checkpoint.

Data Acquisition and Analysis of the UNCOSS Underwater Explosive Neutron Sensor

The purpose of the FP7 UNCOSS project (Underwater Coastal Sea Surveyor, http://www.uncoss-project.org) is to develop a neutron-based underwater explosive sensor to detect unexploded ordnance lying on the sea bottom. The Associated Particle Technique is used to focus the inspection on a suspicious object located by optical and electromagnetic sensors and to determine if there is an explosive charge inside. This paper presents the data acquisition electronics and data analysis software which have been developed for this project. A field programmable gate array that digitizes and processes the signal allows to perform precise time-of-flight and gamma-ray energy measurements. The gamma-ray spectra are unfolded into pure elemental count proportions, mainly C, N, O, Fe, Al, Si, and Ca. The C, N, and O count fractions are converted into chemical proportions, taking into account the gamma-ray production cross sections, as well as neutron and photon attenuation in the different shields between the ROV (Remotely Operated Vehicle) and the explosive, such as the explosive iron shell, seawater, and ROV envelop. A two-dimensional (2D) barycentic representation of the C, N, and O proportions is built from their chemical ratios, and a 2D likelihood map is built from the associated statistical and systematic uncertainties. The threat level is evaluated from the best matching materials of a database including explosives.

Estimation of Nuclear Counting by a Nonlinear Filter Based on a Hypothesis Test and a Double Exponential Smoothing

Online nuclear counting represents a challenge due to the stochastic nature of radioactivity. The counting data have to be filtered in order to provide a precise and accurate estimation of the count rate, while ensuring a response time compatible with the application in view. An innovative filter is presented in this paper to address this issue. The filter is nonlinear and based on a Centered Significance Test (CST) providing a local maximum likelihood estimation of the signal. This nonlinear approach allows enables to smooth the counting signal while maintaining a fast response when brutal change in activity occurs. The filter is then improved by the implementation of a Browns double Exponential Smoothing (BES). The filter has been validated and compared to other state-of-the-art smoothing filters. The CST* filter shows a significant improvement compared to all tested smoothing filters.

An adaptive smoother for counting measurements

Counting measurements associated with nuclear instruments are tricky to carry out due to the stochastic process of the radioactivity. Indeed events counting have to be processed and filtered in order to display a stable count rate value and to allow variations monitoring in the measured activity. Smoothers (as the moving average) are adjusted by a time constant defined as a compromise between stability and response time.

New monitoring system to detect a radioactive material in motion

Illegal radioactive material transportation detection, by terrorist for example, is problematic in urban public transportation. Academics and industrials systems include Radiation Portal Monitor (RPM) to detect radioactive matters transported in vehicles or carried by pedestrians. However, todays RPMs are not able to efficiently detect a radioactive material in movement. Due to count statistic and gamma background, false alarms may be triggered or at the contrary a radioactive material not detected. The statistical false alarm rate has to be as low as possible in order to limit useless intervention especially in urban mass transportation. The real-time approach depicted in this paper consists in using a time correlated detection technique in association with a sensor network. It is based on several low-cost and large area plastic scintillators and a digital signal processing designed for signal reconstruction from the sensor network. The number of sensors used in the network can be adapted to fit with applications requirements or cost. The reconstructed signal is improved by comparing other approaches. This allows us to increase the device speed that has to be scanned while decreasing the risk of false alarm. In the framework of a project called SECUR-ED Secured Urban Transportation - European Demonstration, this prototype system will be used during an experiment in the Milan urban mass transportation.

Nuclear counting filter based on a Centered Skellam Test and a double Exponential Smoothing

Online nuclear counting represents a challenge due to the stochastic nature of radioactivity. The count data have to be filtered in order to provide a precise and accurate estimation of the count rate, this with a response time compatible with the application in view. An innovative filter is presented in this paper addressing this issue. It is a nonlinear filter based on a Centered Skellam Test (CST) giving a local maximum likelihood estimation of the signal based on a Poisson distribution assumption. This nonlinear approach allows to smooth the counting signal while maintaining a fast response when brutal change activity occur. The filter has been improved by the implementation of a Browns double Exponential Smoothing (BES). The filter has been validated and compared to other state of the art smoothing filters. The CST-BES filter shows a significant improvement compared to all tested smoothing filters.

Moving sources detection system

To monitor radioactivity passing through a pipe or in a given container such as a train or a truck, radiation detection systems are commonly employed. These detectors could be used in a network set along the source track to increase the overall detection efficiency. However detection methods are based on counting statistics analysis. The method usually implemented consists in trigging an alarm when an individual signal rises over a threshold initially estimated in regards to the natural background signal. The detection efficiency is then proportional to the number of detectors in use, due to the fact that each sensor is taken as a standalone sensor. A new approach is presented in this paper taking into account the temporal periodicity of the signals taken by all distributed sensors as a whole. This detection method is not based only on counting statistics but also on the temporal series analysis aspect. Therefore, a specific algorithm is then developed in our lab for this kind of applications and shows a significant improvement, especially in terms of detection efficiency and false alarms reduction. We also plan on extracting information from the source vector. This paper presents the theoretical approach and some preliminary results obtain in our laboratory.

A generic isotope identification approach for nuclear instrumentation

Isotope identification is generally done from spectra from high intrinsic resolution such as germanium. A lot of approaches are proposed in the literature. Most of them are not efficient with poor energy resolution detectors such as non-loaded scintillators. The proposed approach is a new isotope identification principle to deal with the overall range of nuclear detectors. The proposed method allows the identification of isotopes using detectors with poor intrinsic resolution and lower counting than the existing techniques.

Sodium fast reactor power monitoring and clad failure detection using ADONIS system

This work deals with the use of gamma spectrometry for fourth generation Sodium Fast Reactor (SFR) power monitoring and clad failure detection. Usually, gamma spectrometers could not manage on-line applications in high count rate and fast activity variations but recent improvements in this research field may improve it. The ADONIS analyser for gamma spectrometry could met two needs of fourth generation SFR [1]. The ex-core neutron power measurement gives instant neutron power estimation but has some shift problems, mainly due to the burn-up phenomenon. High security margins are then set and so, the reactor can not work at its best thermodynamic efficiency. Previous works on Pressurized Water Reactors (PWR) show that gamma emitters concentration in primary coolant is also directly linked with reactor power (16N power measurement) [7]. On SFR, the use of short decay period gamma emitters as the 20F radionuclide will allow a fast power measurement with a direct correlation with the instant fission rate and without burn-up dependency. The second need is the clad failure detection improvement. The SFR clad failure detection is done by radiochemical and gamma measurements on argon cover gas and primary sodium samples. Gaseous fission products and delayed neutron fission products (only the 137I and the 87Br) are measured but lots of fission products (gamma emitters) are not measured nowadays on-line due to high sodium activity and its fast changes. This paper presents the experiment done at the French Phénix SFR of the CEA Marcoule and its analysis. Measuring activation and fission products contained in primary sodium coolant, the adaptive ADONIS gamma spectrometry system set on primary sodium coolant sample could be a new innovating power monitoring and clad failure detection system for future SFR.