In-core Neutron Detectors Research Articles

A computational- experimental model of reactor kinetic for investigating the linearity response of in-core neutron detectors of a low power research reactor

In this study, the linear response of fission chamber (FC) neutron detectors in Isfahan miniature neutron source reactor (MNSR) is investigated through experiments and calculations at different powers of the reactor. The linearity of the response of the main neutron detector in the MNSR is important due to its safety functions in reactor power control. Additionally, determining the linear response region of this detector presents a linear neutron dosimetry field even outside of the reactor core, i.e. at the outlet of external beam tubes. Moreover, it is very difficult to remove and calibrate this neutron detector that has been installed in the reactor core for a long time. For this purpose, an alternative method for measuring the linearity of the response of a neutron detector is extended by investigating the kinetic behavior of reactor. The aim of this method is to calculate the delayed neutrons population in the reactor core and compare with the FC detector response. In this method, the numerical solution method is used to solve the point kinetic equation with 15 delayed neutron groups (6 delayed neutron groups and 9 photo-neutron groups) after inserting a large negative reactivity into the MNSR core by considering temperature and xenon reactivity feedbacks during a coupling procedure. To obtain the xenon reactivity feedback, xenon concentration is calculated by coupling the 135Xe and 135I production equations and the εpPFnlPTnl parameter is obtained by an experimental method. Furthermore, the value of fission cross section (Σf) is calculated using a validated model in the Dragon code. The large reactivities are inserted at two initial power of 150 W and 30 kW to investigate the response of the main FC neutron detector in a cold xenon-free condition and by considering temperature and xenon reactivity feedbacks, respectively. The results demonstrate that the response of the MNSR FC detector is linear in the neutron flux range between 5 × 107 to 1 × 1012 n.cm−2.s−1, which is equivalent to reactor power of 1.5 W to 30 kW. This innovative method can be applied to calibrate the neutron detectors in other research and power reactors.

A general method for delay compensation of self-powered neutron detectors in reactors

Self-Powered Neutron Detectors (SPNDs) have long been widely used as reactor in-core neutron detectors. However, delayed type SPNDs, a typical type SPND with delayed current component, can not be directly used for real-time neutron flux monitoring. To solve this problem, several researchers have established compensation methods to reconstruct neutron flux. For the various SPNDs with delayed currents, the existing compensation methods are usually case-dependent. Therefore, a general compensation method for delayed type SPNDs with high portability is proposed in this paper. Based on linear equations in the s domain, this method is applicable for all the delayed SPNDs, giving the general compensation solution with definite iterations. Moreover, this compensation method is tested by two typical delayed SPNDs, indicating its high portability and applicability.

Performance evaluation of AHWR flux mapping system during normal operational scenarios

In large nuclear reactors, a number of appropriately distributed in-core neutron detectors are used for monitoring and control of neutron flux distribution in the core. In Advanced Heavy Water Reactor (AHWR) too, a set of 168 self-powered neutron detectors installed vertically at 6 locations in 28 in-core detector housing units has been proposed to be used. This configuration arrived at using the K-means clustering approach, has been found to reconstruct the core neutron flux distribution for a number of steady-state flux shapes. For practical application, in addition to steady-state, the optimized set of in-core detectors should provide reasonably accurate core monitoring for regular reactor operations as well. This paper investigates the accuracy characteristics of flux mapping using the proposed set of 168 in-core self-powered neutron detectors in the reconstruction of time-varying flux shapes encountered during normal reactor operations. Time-dependent flux shapes arising due to perturbations such as the movement of reactivity devices, refuelling and xenon spatial oscillations are considered for this study. Flux reconstruction is performed using the well-known flux synthesis method. From the analysis, it can be observed that the proposed set of in-core detectors reliably reconstructs the flux distribution in the reactor even during the normal operational scenarios. The maximum RMS error in mesh flux using 168 SPNDs and 35 eigenmodes is found to be 4.45% across all the operational scenarios considered.

Artificial neural network reconstructs core power distribution

To effectively monitor the variety of distributions of neutron flux, fuel power or temperatures in the reactor core, usually the ex-core and in-core neutron detectors are employed. The thermocouples for temperature measurement are installed in the coolant inlet or outlet of the respective fuel assemblies. It is necessary to reconstruct the measurement information of the whole reactor position. However, the reading of different types of detector in the core reflects different aspects of the 3D power distribution. The feasibility of reconstruction the core three-dimension power distribution by using different combinations of in-core, ex-core and thermocouples detectors is analyzed in this paper to synthesize the useful information of various detectors. A comparison of multilayer perceptron (MLP) network and radial basis function (RBF) network is performed. RBF results are more extreme precision but also more sensitivity to detector failure and uncertainty, compare to MLP networks. This is because that localized neural network could offer conservative regression in RBF. Adding random disturbance in training dataset is helpful to reduce the influence of detector failure and uncertainty. Some convolution neural networks seem to be helpful to get more accurate results by use more spatial layout information, though relative researches are still under way.

Applicability of the Krško nuclear power plant core Monte Carlo model for the determination of the neutron source term

A detailed geometrical model of a Krško reactor core was developed using a Monte Carlo neutron transport code MCNP. The main goal of developing an MCNP core model is for it to be used in future research focused on ex-core calculations. A script called McCord was developed to generate MCNP input for an arbitrary fuel cycle configuration from the diffusion based core design package CORD-2, taking advantage of already available material and temperature data obtained in the nuclear core design process. The core model was used to calculate 3D power density profile inside the core. The applicability of the calculated power density distributions was tested by comparison to the CORD-2 calculations, which is regularly used for the nuclear core design calculation verification of the Krško core. For the hot zero power and hot full power states differences between MCNP and CORD-2 in the radial power density profile were <3%. When studying axial power density profiles the differences in axial offset were less than 2.3% for hot full power condition. To further confirm the applicability of the developed model, the measurements with in-core neutron detectors were compared to the calculations, where differences of 5% were observed.

Delayed gamma fraction determination in the zero power reactor CROCUS

Gamma rays are an inextricable part of a nuclear reactor’s radiation field, and as such require characterization for dose rate estimations required for the radiation protection of personnel, material choices, and the design of nuclear facilities. Most commonplace radiation transport codes used for shielding calculations only included the prompt neutron induced component of the emitted gamma rays. The relative amount of gamma rays that are emitted from delayed processes – the delayed gamma fraction – amount to a significant contribution, e.g. in a typical zero power reactor at steady state is estimated to be roughly a third. Accurate predictions of gamma fields thus require an estimation of the delayed content in order to meaningfully contribute. As a consequence, recent code developments also include delayed gamma sources and require validation data. The CROCUS zero power research reactor at EPFL is part of the NEA IRPhE and has therefore been characterized for benchmark quality experiments. In order to provide the means for delayed gamma validation, a dedicated experimental campaign was conducted in the CROCUS reactor using its newly developed gamma detection capabilities based on scintillators. In this paper we present the experimental determination of the delayed gamma fraction in CROCUS using in-core neutron and gamma detectors in a benchmark reactor configuration. A consistent and flexibly applicable methodology on how to estimate the delayed gamma fraction in zero power reactors has hitherto not existed – we herein present a general experimental setup and analysis technique that can be applied to other facilities. We found that the build-up time of relevant short lived delayed gamma emitters is likely attributed to the activation of the aluminium cladding of the fuel. Using a CeBr3scintillator in the control rod position of the CROCUS core, we determined a delayed gamma fraction of (30.6±0.6)%.

NEUTRON NOISE-BASED ANOMALY CLASSIFICATION AND LOCALIZATION USING MACHINE LEARNING

A methodology is proposed in this paper allowing the classification of anomalies and subsequently their possible localization in nuclear reactor cores during operation. The method relies on the monitoring of the neutron noise recorded by in-core neutron detectors located at very few discrete locations throughout the core. In order to unfold from the detectors readings the necessary information, a 3-dimensional Convolutional Neural Network is used, with the training and validation of the network based on simulated data. In the reported work, the approach was also tested on simulated data. The simulations were carried out in the frequency domain using the CORE SIM+ diffusion-based two-group core simulator. The different scenarios correspond to the following cases: a generic “absorber of variable strength”, axially travelling perturbations at the velocity of the coolant flow (due to e.g. fluctuations of the coolant temperature at the inlet of the core), fuel assembly vibrations, control rod vibrations, and core barrel vibrations. In all those cases, various frequencies were considered and, when relevant, different locations of the perturbations and different vibration modes were taken into account. The machine learning approach was able to correctly identify the different scenarios with a maximum error of 0.11%. Moreover, the error in localizing anomalies had a mean squared error of 0.3072 in mesh size, corresponding to less than 4 cm. The proposed methodology was also demonstrated to be insensitive to parasitic noise and will be tested on actual plant data in the near future.

Reconstruction of neutron flux distribution by nodal synthesis method using online in-core neutron detector readings

The safety and optimal performance of nuclear reactors require online monitoring in the core. The present paper describes a method that avoids the solution of the time-dependent neutron diffusion equation, and it uses online readings of the fixed in-core neutron detectors to reconstruct the three-dimensional (3D) neutron flux distribution. The essential idea of the nodal synthesis method is the separation of time and space-dependence of the neutron flux distribution. The time-dependent section of the flux distribution is determined by in-core neutron detector readings, and the space-dependent section is obtained from pre-computed harmonics of the neutron diffusion equation. In online computation, time-dependent coefficients are only computed, and flux distribution is reconstructed by pre-computed harmonics. To calculate the diffusion equation harmonics, the nodal expansion method and the Gram-Schmidt process are used. Online reconstruction of neutron flux distribution in the Bushehr Nuclear Power Plant with VVER-1000/446 reactor type is simulated, and the results are benchmarked by valid results. The maximum relative percent error between reconstructed results and the valid results is about 5%, and the computing time is about 0.5 s.

Reactor core power mapping based on Bayesian inference

Bayesian inference provides a coherent probabilistic approach for combining information from measurements of in-core neutron detectors and numerical neutronics simulation results, and thus is an appropriate framework for reactor core power mapping which has been implemented in this paper. Measurements from DayaBay Unit 1 PWR are used to verify the accuracy of the Bayesian inference method, and comparisons are made among the Bayesian inference method, the Kalman filter method and the very-often-used coupling coefficients method. The root mean square errors (RMSE), the maximum relative errors (MRE), and the power peak reconstruction error (PPRE) of the Bayesian inference method are less than 0.31%, 1.64% and 0.07% for the entire operating cycle separately. The reconstructed assembly power distribution results and the calculation speed show that the Bayesian inference method is a promising candidate for on-line core power distribution monitoring system.

Application of data reconciliation for fault detection and isolation of in-core self-powered neutron detectors using iterative principal component test

In-core neutron detectors are used in large nuclear reactors for the purpose of acquiring knowledge about the spatial flux distribution, which helps in control, monitoring and protection of the reactors. Random errors and faults, which cause degradations of the signals from the true values, invalidate the in-core detector measurement data. A scheme utilizing the analytical redundancy among physically redundant in-core detectors greatly facilitates removing the ill-effects of these errors. Particularly, data-based or process-history-based schemes are suitable when there are a large number of variables as in the case of in-core detectors. In this paper, application of a Data Reconciliation (DR) scheme (with the aim of minimizing the effect of random errors) coupled with a Fault Detection and Isolation (FDI) technique (which makes the data free from faults) to the in-core detector measurement data of the Advanced Heavy Water Reactor (AHWR) is presented. This reactor uses Vanadium Self-Powered Neutron Detectors (VSPNDs) as in-core neutron detectors. Since the constraint model developed for all the in-core neutron detectors as a whole cannot yield satisfactory performance from the DR and FDI, they are developed for the individual clusters of VSPNDs using the Iterative Principal Component Analysis (IPCA), a multi-variate statistical technique. The FDI technique used is the Iterative Principal Component Test (IPCT) discussed in Sagar et al. (2015c). The effectiveness of this scheme is tested as follows: (i) the mathematical model of the AHWR is used to simulate measurement data from VSPNDs; (ii) the data from VSPNDs are grouped as clusters based on correlations among the variables; and (iii) the effectiveness of the DR-based FDI of VSPNDs in some clusters is established based on some performance indices, when the spatial control of the reactor is active.

Control rod position reconstruction based on K-Nearest Neighbor Method

Regression method based on Radial Basis Function Neural Network (RBFNN) has been applied to reconstruct the control rod position from the fixed in-core neutron detector signals, and the raw reconstructed rod position which has a decimal part should be rounded into integer. In this paper, K-Nearest Neighbor (K-NN) classification method is utilized to obtain the reconstructed rod position in the form of integer directly. Neutronics code SMART is used to simulate in-core neutron detector signals for different rod position, and noises are added to the simulated signals to generate training data set and test data set. The simulation results show that the K-NN method can reconstruct the control rod position accurately, and modification strategy based on calibration factor is used to improve the rod position monitoring accuracy when there are mismatches between actual physical factors and modeled physical factors.

Модель формирования сигнала внутризонного детектора нейтронов

Модель формирования сигнала внутризонного детектора нейтронов

Development of the Prediction Technology of Cable Disconnection of In-Core Neutron Detector for the Future High-Temperature Gas-Cooled Reactors

Maintenance technologies for the reactor system have been developed by using the High Temperature engineering Test Reactor (HTTR). One of the important purposes of development is to accumulate the experiences and data to satisfy the availability of operation up to 90% by shortening the duration of the periodical maintenance for future high-temperature gas-cooled reactors (HTGRs) by shifting from time-based maintenance to condition-based maintenance. The technical issue of the maintenance of the in-core neutron detector, wide range monitor (WRM), is to predict the malfunction caused by cable disconnection to plan the replacement schedule. This is because it is difficult to observe directly inside the WRM in detail. The electrical inspection method was proposed to detect and predict the cable disconnection of the WRM by remote monitoring from outside the reactor using the time-domain reflectometry (TDR). The disconnection position, which was specified by the electrical method, was identified by nondestructive and destructive inspection. The accumulated data are expected to be contributed for advanced maintenance of future HTGRs.

A newly designed multichannel scaling system: Validated by Feynman-α experiment in EHWZPR

In this work, an embedded multi-input multi-million-channel MCS in a newly design is constructed for multi-detector experimental research applications. Important characteristics of the system are possible to be tuned based on experimental case studies utilizing the reprogrammable nature of the silicon. By means of differentiation of the integrated counts registered in memory, this system is featured as a zero channel advance time measuring tool ideal for experiments on time correlated random processes. Using this equipment, Feynman-α experiment is performed in Esfahan Heavy Water Zero Power Reactor (EHWZPR) utilizing three different in-core neutron detectors. One million channel data is collected by the system in 5ms gate time from each neutron detector simultaneously. As heavy water moderated reactors are significantly slow systems, a huge number of data channels is required to be collected. Then, by making in use of bunching method, the data is analyzed and prompt neutron decay constant of the system is estimated for each neutron detector positioned in the core. The results are compared with the information provided by endogenous pulsed neutron source experiment and a good agreement is seen within the statistical uncertainties of the results. This equipment makes further research in depth possible in a range of stochastic experiments in nuclear physics such as cross correlation analysis of multi-detector experiments.

Demonstration of the importance of a dedicated neutron beam monitoring system for BNCT facility

The neutron beam monitoring system is indispensable to BNCT facility in order to achieve an accurate patient dose delivery. The neutron beam monitoring of a reactor-based BNCT (RB-BNCT) facility can be implemented through the instrumentation and control system of a reactor provided that the reactor power level remains constant during reactor operation. However, since the neutron flux in reactor core is highly correlative to complicated reactor kinetics resulting from such as fuel depletion, poison production, and control blade movement, some extent of variation may occur in the spatial distribution of neutron flux in reactor core. Therefore, a dedicated neutron beam monitoring system is needed to be installed in the vicinity of the beam path close to the beam exit of the RB-BNCT facility, where it can measure the BNCT beam intensity as closely as possible and be free from the influence of the objects present around the beam exit. In this study, in order to demonstrate the importance of a dedicated BNCT neutron beam monitoring system, the signals originating from the two in-core neutron detectors installed at THOR were extracted and compared with the three dedicated neutron beam monitors of the THOR BNCT facility. The correlation of the readings between the in-core neutron detectors and the BNCT neutron beam monitors was established to evaluate the improvable quality of the beam intensity measurement inferred by the in-core neutron detectors. In 29 sampled intervals within 16 days of measurement, the fluctuations in the mean value of the normalized ratios between readings of the three BNCT neutron beam monitors lay within 0.2%. However, the normalized ratios of readings of the two in-core neutron detectors to one of the BNCT neutron beam monitors show great fluctuations of 5.9% and 17.5%, respectively.

Development of three methods for control rod position monitoring based on fixed in-core neutron detectors

Nuclear reactor core power distribution on-line monitoring system is very important in core surveillance, and this system should have the ability to indicate some abnormal conditions, such as the unacceptable control rod misalignment. In this study, the methodologies of radial basis function neural network (RBFNN), group method of data handling (GMDH) and Levenberg–Marquardt (LM) algorithm are utilized separately to unfold the control rod position from the fixed in-core neutron detector measurements. For using these methods, a large number of in-core detector signals corresponding to various known rod positions are needed. These data can be generated by an advanced core calculation code. In this study, the neutronics code SMART was used. The simulation results show that all these methods can unfold the control rod position accurately, and the performance comparison shows that the regularized RBFNN performs best. Two correction strategies are proposed to correct the simulated fixed in-core detector signals and improve the rod position monitoring accuracy when there are mismatches between actual physical factors and modeled physical factors.

A new power mapping method based on ordinary kriging and determination of optimal detector location strategy

The Ordinary Kriging (OK) method is presented that is designed for a core power mapping calculation of pressurized water reactors (PWRs). Measurements from DayaBay Unit 1 PWR are used to verify the accuracy of the OK method. The root mean square (RMS) reconstruction errors are kept at less than 0.35%, and the maximum reconstruction relative errors (RE) are kept at less than 1.02% for the entire operating cycle. The reconstructed assembly power distribution results show that the OK method is fit for core power distribution monitoring. The quality of power distribution obtained by the OK method is partly determined by the neutron detector locations, and the OK method is also applied to solve the optimal neutron detector location problem. The spatially averaged ordinary kriging variance (AOKV) is minimized using simulated annealing, and then, the optimal in-core neutron detector locations are obtained. The result shows that the current neutron detector location of DayaBay Unit 1 reactor is near-optimal.

Valuation of Power Oscillations in a BWR After Control Rod Banks Withdrawal Events

The out-of-phase mode of oscillation is a very challenging type of instability occurring in BWR (Boiling Water Reactor) and its study is relevant because of the safety implications related to the capability to promptly detect any such inadvertent occurrence by in-core neutron detectors, thus triggering the necessary countermeasures in terms of selected rod insertion or even reactor shutdown. In this work, control rod banks withdrawal transient was considered to study the power instability occurring in a BWR. To simulate this transient, the control rod banks were continuously removed from the BWR core in different cases. The simulation resulted in a very large increase in the power. To perform the instability simulations, the RELAP5/MOD3.3 thermal hydraulic system code was coupled with the PARCS/2.4 3-D neutron kinetic code. Data from a real BWR, the Peach Bottom, have been used as reference conditions and reactor parameters. The trend of the mass flow rate, pressure, coolant temperature and the void fraction to four thermal hydraulic channels symmetrically located in the core with respect to the core centre, were taken. The behavior of the thermal hydraulic parameters investigated presented out-of-phase evolution comparing the channels that represents each half of the core.

Simulation of an hypothetical out-of-phase instability case in boiling water reactor by RELAP5/PARCS coupled codes

A very complex type of power instability occurring in boiling water reactor (BWR) consists of out-of-phase regional oscillations, in which normally subcritical neutronic modes are excited by thermal-hydraulic feedback mechanisms. The out-of-phase mode of oscillation is a very challenging type of instability and its study is relevant because of the safety implications related to the capability to promptly detect any such inadvertent occurrence by in-core neutron detectors, thus triggering the necessary countermeasures in terms of selected rod insertion or even reactor shutdown. In this work, simulations of out-of-phase instabilities in a BWR obtained by assuming an hypothetical continuous control rod bank withdrawal are being presented. The RELAP5/Mod3.3 thermal-hydraulic system code coupled with the PARCS/2.4 3D neutron kinetic code has been used to simulate the instability phenomenon. Data from a real BWR nuclear power plant (NPP) have been used as reference conditions and reactor parameters. Simulated neutronic power signals from local power range monitors (LPRM) have been used to detect and study the local power oscillations. The decay ratio (DR) and the natural frequency (NF) of the power oscillations (typical parameters used to evaluate the instabilities) have been used in the analysis. The results are discussed also making use of two-dimensional plots depicting relative core power distribution during the transient, in order to clearly illustrate the out-of-phase behavior.

Response functions for calculating axial power-density profiles in fuel rods using in-core neutron detectors

Micro-pocket fission detectors (MPFDs) have recently been fabricated and successfully tested as in-core flux monitoring devices in the nuclear reactor in Kansas State University. These detectors are sufficiently small to be inserted between fuel elements. Data from an MPFD array can be converted into a 3D power-density map of the reactor core for real-time flux monitoring. In the present study, the necessary mathematical models are developed that relate the power-density profiles in fuel rods to the MPFDs' response. The applicability of an inversion algorithm proposed for obtaining power-density profiles is also verified in this study.