Detector Arrangement Research Articles

Detector configuration optimization method considering response time for spatial source parameter estimation in complex urban wind environment

In source parameter estimation, improper arrangement of detectors may lead to ineffective concentration measurement or even failure in leakage detection, which would hold back emergency response efforts. However, current methods for optimizing detector configuration have inherent flaws and thus cannot be ideally applied in real-world scenarios. To address their limitations, this paper develops the method for optimizing detector configuration by considering response time. A novel cost function is proposed to balance response time and estimation accuracy based on specific demands. The optimum configuration is then obtained by genetic algorithm iteration. The wind tunnel test of an urban environment with buildings of varying heights is conducted for the research purpose. The superiority of the proposed method is demonstrated by comparing spatial source parameter estimations using optimum, uniform, and random configurations respectively. The results show that our method avoids placing detectors at locations with low concentrations, i.e., places where readings are invalid. It enables more detectors to obtain readings quickly, generating more accurate estimations in a shorter time. Only with the optimum configuration do detectors show readings for all 15 sources, with each unknown source having the highest number of detectors with readings. In contrast, the uniform configuration results in no readings for 4 sources and the random configuration results in no readings for 11 sources when leaking happens. The proposed method optimizes the detector configuration in three-dimensional space with complex flows, making it more feasible in practical applications.

A fast numerical method for calculating SPND space charge effect at steady state

To address the issue of low efficiency and long computation times in calculating the space charge effect in Self-Powered Neutron Detectors (SPNDs), we developed a fast and efficient numerical method to calculate the steady-state electric fields in SPND insulators. Previous calculations have shown that even when the electric field in the SPND insulator reaches 1 GV/m, its effect on electron transport is negligible. Therefore, we assume that the electric field has a negligible effect on electron transport. Based on this assumption, we developed a one-step numerical method for calculating the steady-state electric field in the insulator. This fast method is based on the charge conservation equation in equilibrium, thus requiring only a single charge deposition result without an electric field to obtain the distribution of the electric field under steady-state conditions. We validated our method by comparing it with precise iterative calculation results and experiments. The computational results indicate that, for three typical experimental scenarios, the fast method only takes up to one percent, or even less, of the time required by the iterative method. At the same time, the Mean Relative Error (MRE) in the electric field distribution between the fast method and iterative calculations are 1.48%, 0.31%, and 5.12%, respectively; whereas the relative errors in sensitivity calculations based on the electric field compared to iterative calculations are all less than 2%. Therefore, the fast method can significantly reduce computation time and ensure sufficient accuracy of steady state electric field distribution when the electric field is less than 1 GV/m. The introduction of this method has made it possible to conduct space charge effect assessments and precise sensitivity calculations for the placement of detectors throughout the entire reactor core.

Microclimatic drivers of winter bat activity in coast redwood forests.

Bats are among the least well-known mammals, particularly in terms of their behavior and activity patterns during the winter. Here, we use passive acoustic monitoring to overcome some of the challenges inherent in surveying cryptic forest bats during the wet season to quantify overwintering behavior for 11 species in California coast redwood forests under varying microclimates. Because different species are active at different forest heights, we also examined the effect of acoustic detector placement (treetop or ground level). Generalized linear mixed models were used to relate acoustic detection probability for 8 species to daytime and nighttime temperature, relative humidity, water vapor pressure, and detector placement. The results indicate that daytime maximum temperature best explained variation in nightly probability of detection, and temperature threshold at which bats were predicted to be detected varied considerably across species. By using more precise species detection methods, we were able to resolve significant differences in activity patterns between Myotis yumanensis and M. californicus, 2 species with similar acoustic signatures that are often lumped together. Myotis californicus was predicted to have a 50% probability of detection at maximum daytime temperature as low as 12.5 °C, whereas M. yumanensis was not predicted to have 50% detection probability until maximum daytime temperature was at least 22 °C, suggesting that M. californicus spends less time in torpor. Also, monitoring at the top of the canopy revealed 4 migratory species to be present in the ecosystem on significantly more monitoring nights than could be observed using conventional ground-based monitoring methods. Improving winter bat survey methods provides evidence that diverse bat species are more active in redwood forests during the winter than previously documented. This finding suggests that coastal forests could provide important winter bat habitat for both resident and migratory species.

Optimizing the Fixed Number Detector Placement for the Nuclear Reactor Core Using Reinforcement Learning

Monitoring three-dimensional flux distribution in a nuclear reactor core is essential for improving safety and economics, which requires strategically placed in-core detectors. However, the deployment of these sensors is often constrained by physical, industrial, and economic limitations. This study treats optimizing the location of in-core detectors as a Markov decision process and develops a reinforcement learning (RL)–based framework to provide a solution for detector placement given a fixed number of detectors and available detector positions. The RL-based framework contains an environment consisting of a Proper Orthogonal Decomposition–based power reconstruction function paired with a novel reward function based on the power reconstruction error and a well-educated agent that updates the detector placement. Four RL algorithms including Proximal Policy Optimization, Deep Q-Network, Advantage Actor-Critic, and Monte Carlo Tree Search are investigated to optimize the detector placement and are analyzed. Genetic Algorithm (GA), a traditional optimization approach, is applied for comparison. The findings reveal that RL outperforms GA in terms of the quality of optimal solutions, demonstrating an inclination toward locating a global solution. Moreover, the flexible nature of RL enables the integration of developed novel reward functions from a specific reactor core into other reactors, considering the particular engineering requirements within the RL-based framework, thereby enhancing the optimization of in-core detector configurations.

A deconvolution method for estimating proton range from measured intensity distribution of prompt gamma rays

This study developed a technique for proton range verification based on measuring the intensity distribution of prompt gamma rays (PGs) along the beam path in a target and applying a deconvolution method for retrieving the corresponding distribution of PG emissions. The end-of-range Rret=dγp + Rres can be estimated according to the peak position dγp of the retrieved PG emission and the residual range Rres determined from the cross section of the relevant nuclear reaction. A 30-MeV, 1.5-nA proton beam irradiated polyethylene (PE) and polymethyl methacrylate (PMMA) targets, and spatial intensity distributions were obtained by measuring 4.4- and 6.13-MeV PGs from a depth of 0 mm to 10 mm; to this end, a collimator–detector arrangement comprising a 2-inch NaI(Tl) detector and a 2-mm-wide slit collimator was used. Simulations were conducted to identify the profile of PG emissions in a target and to determine the detector response; subsequently, the performance of the developed deconvolution algorithm was validated, and the limits of this approach were investigated. The data from the 30-MeV proton beam experiment were used, and the ranges Rret were estimated to be 7.85 mm for the PE target and 7.07 mm for the PMMA target; these were considerably close to the range at 80% dose fall-off level R80 achieved using Monte Carlo simulations. Our results demonstrated that a NaI(Tl)-based system with a millimeter-wide collimator can effectively resolve the spatial variation of PG emissions along a proton beam’s path. The proposed deconvolution method exhibited strong potential for verifying proton ranges with a sub-millimeter-level accuracy in a relatively simple and reliable manner.

XrdPlanner: exploring area detector geometries for powder diffraction and total scattering experiments.

xrdPlanner is a software package designed to aid in the planning and preparation of powder X-ray diffraction and total scattering beam times at synchrotron facilities. Many modern beamlines provide a flexible experimental setup and may have several different detectors available. In combination with a range of available X-ray energies, it often makes it difficult for the user to explore the available parameter space relevant for a given experiment prior to the scheduled beam time. xrdPlanner was developed to provide a fast and straightforward tool that allows users to visualize the accessible part of reciprocal space of their experiment at a given combination of photon energy and detector geometry. To plan and communicate the necessary geometry not only saves time but also helps the beamline staff to prepare and accommodate for an experiment. The program is tailored toward powder X-ray diffraction and total scattering experiments but may also be useful for other experiments that rely on an area detector and for which detector placement and achievable momentum-transfer range are important experimental parameters.

Effect of detector placement on joint estimation in X-ray fluorescence emission tomography.

Imaging the spatial distribution of low concentrations of metal is a growing problem of interest with applications in medical and material sciences. X-ray fluorescence emission tomography (XFET) is an emerging metal mapping imaging modality with potential sensitivity improvements and practical advantages over other methods. However, XFET detector placement must first be optimized to ensure accurate metal density quantification and adequate spatial resolution. In this work, we first use singular value decomposition of the imaging model and eigendecomposition of the object-specific Fisher information matrix to study how detector arrangement affects spatial resolution and feature preservation. We then perform joint image reconstructions of a numerical gold phantom. For this phantom, we show that two parallel detectors provide metal quantification with similar accuracy to four detectors, despite the resulting anisotropic spatial resolution in the attenuation map estimate. Two orthogonal detectors provide improved spatial resolution along one axis, but underestimate the metal concentration in distant regions. Therefore, this work demonstrates the minor effect of using fewer, but strategically placed, detectors in the case where detector placement is restricted. This work is a critical investigation into the limitations and capabilities of XFET prior to its translation to preclinical and benchtop uses.

Power Detector Performance and Placement Effects on Measurement Accuracy in Sampled-Network Reflectometry

Power Detector Performance and Placement Effects on Measurement Accuracy in Sampled-Network Reflectometry

Highly sensitive interferometry with strong anti laser jamming capability based on frequency shift optical feedback

With the proliferation of diverse laser equipment, the optical environment in which highly sensitive optical systems operate has become harsh and intricate. Mitigating laser jamming originating from the operational waveband is a challenging problem encountered by laser interferometric measurement systems. In this paper, we set forth a robust anti-jamming optical interferometry with high sensitivity. This method is based on frequency shift optical feedback, namely anti-jamming laser feedback interferometry (AJLFI). A rear-end pumping Nd:YVO4 microchip laser with bidirectional output channels is employed as the interferometric system source, and the photodetector is posterior to the laser cavity. This particular laser structure and the unique detector placement method from optical feedback interferometry make the laser cavity operate as a high-stop-band filter to filter out laser jamming in the operational waveband. In the AJLFI-based system we established, the jamming laser with a wavelength equaling that of the interferometric system suffers a notable attenuation of 44.8 dB. Concurrently, jamming laser falling within a range of ±10 nm from the wavelength of interferometric system gets an attenuation exceeding 44.43 dB. In addition, we set up the standard laser feedback interferometry(LFI)-based system and the Michelson heterodyne interferometry(MHI)-based system with the same experimental parameters as the AJLFI-based system to perform anti-jamming capability comparative experiments. In the experiments, a pulsed laser beam with a peak power of 1780.9 W is employed as laser jamming in the operating wavebands, which is precisely directed toward the target in conjunction with the probe light of the interferometric systems and scattered into the interferometric systems. The experimental findings demonstrate that the AJLFI-based system exhibits superior anti-jamming capability in both phase and amplitude measurements compared to conventional LFI-based and MHI-based systems.

Methods to maximize detector count rates on small-angle neutron scattering diffractometers at reactor sources: II. Optimizing sample, source and detector sizes

Methods for maximizing the detector count rate for the same scattering angle range and resolution are related to choosing the optimum pinhole collimation parameters which include the source and sample aperture sizes and collimation lengths on small-angle neutron scattering diffractometers located at reactor neutron sources. Calculations and experimental measurements are presented that show enhancements in count rate with the same q-resolution can be achieved by combining both longer flight paths with larger source and sample apertures and beam stop sizes. To be able to both accommodate the larger beam sizes at the detector and to maintain the same range in scattering angle, existing and new detector placement strategies are presented that extend the scattering angle range beyond what is capable with a single 2-D detector.

Efficient Gas Leak Simulation Surrogate Modeling and Super Resolution for Gas Detector Placement Optimization

This study introduces an innovative framework that utilizes a limited number of sensors to detect chemical leaks early, enabling a timely and appropriate initial response. Consequently, it mitigates the risk of major industrial disasters. This framework integrates a surrogate model based on differentiable physics with a sensor placement optimization tool. Particularly noteworthy is that the surrogate model provides faster results compared to traditional CFD tools and seamlessly integrates with a CNN-based deep learning model, yielding higher-resolution outputs. This enhances the feasibility of practical application compared to conventional methods. Sensor placement optimization employs MINLP, considering various constraints to achieve more precise optimization. The proposed framework offers an innovative approach to address industrial safety concerns by enabling early chemical leak detection and facilitating timely responses, ultimately reducing risks like fires, explosions, and toxic incidents.

Passive-seismic sensor placement optimization for geologic carbon storage

The implementation of passive-seismic monitoring is essential for the geological carbon storage projects. For secure and continuous observing of induced passive-seismic events by CO2 injecting, a ground geophone network would be required. By determining the ideal number of seismic stations within a regular network, recent research has enhanced monitoring capabilities while also accommodating budgetary limitations. The primary objective of the optimal placement strategy for the surface geophone network is to create a cost-effective monitoring system. Given the cost limitations, a restricted quantity of sensors can be deployed at each location to maximize monitoring performance. To address this challenge, our approach involves the P-median stochastic programming formulation. The formulation aims to minimize the expected value of a monitoring target metric, which ultimately results in the optimal placement of detectors exhibiting superior expected behaviors. Our methodology is designed to choose the arrangement of detectors with best performance to improve both the early alarm detection time and localization capabilities of the sensor network. We utilize site-specific passive-seismic scenarios that capture the uncertainty in the characteristics of carbon leakage. The sensor grids provided by the optimization method invariably improve the capacity to detect passive-seismic events in comparison to sensors positioned in a regular grid configuration. We test the effectiveness of our approach on synthetic data based on a carbon storage site named Kimberlina. In conclusion, our approach provides a cost-effective solution for the optimal placement of sensors to achieve superior monitoring performance for the detection of passive-seismic events. The incorporation of site-specific scenarios with stochastic uncertainty coverage allows for more accurate and reliable results, leading to better decision-making for long-term geological carbon storage.

Measuring wavelength of laser beam using single slit diffraction: a simple but precise experiment using webcam and ImageJ software

We explore a precise method for determining the wavelength of light using a single-slit diffraction experiment. Normally, within a college level physics lab, an optical bench and a light detector arrangement is used in this experiment and the position of the maxima and minima are manually determined. This method is inaccurate, lengthy, and time consuming. We replace the light-detector by a paper-screen and webcam arrangement to record the image of the diffraction pattern with a computer. Then the recorded images are analysed with a software called ImageJ to determine the span of central maxima which is finally used to determine the wavelength of the incident light.

3-D muographic inversion in the exploration of cavities and low-density fractured zones

SUMMARY Muography is an imaging tool based on the attenuation of cosmic muons for observing density anomalies associated with large objects, such as underground caves or fractured zones. Tomography based on muography measurements, that is, 3-D reconstruction of density distribution from 2-D muon flux maps, brings along special challenges. The detector field of view covering must be as balanced as possible, considering the muon flux drop at high zenith angles and the detector placement possibilities. The inversion from directional muon fluxes to a 3-D density map is usually underdetermined (more voxels than measurements). Therefore, the solution of the inversion can be unstable due to partial coverage. The instability can be solved by geologically relevant Bayesian constraints. However, the Bayesian principle results in parameter bias and artefacts. In this work, linearized (density-length based) inversion is applied by formulating the constraints associated with inversion to ensure the stability of parameter fitting. After testing the procedure on synthetic examples, an actual high-quality muography measurement data set from seven positions is used as input for the inversion. The resulting tomographic imaging provides details on the complicated internal structures of karstic fracture zone. The existence of low density zones in the imaged space was verified by samples from core drills, which consist of altered dolomite powder within the intact high density dolomite.

Compton Camera Arrangement With a Monolithic LaBr3(Ce) Scintillator and Pixelated GAGG Detector for Medical Imaging

The results presented in this manuscript are divided in two main parts. The aim of the presented work is to conduct feasibility tests on a Compton camera setup to be later scaled up and used for PET and triple coincidence γ-PET purposes. The first part is focused on laboratory characterization of a monolithic LaBr3(Ce) scintillator coupled to a 64-channel multi-anode photomultiplier (H8500C PMT from Hamamatsu) in combination with a well-established algorithm allowing to determine the interaction’s position resolution. The second part of the article is dedicated to the evaluation of a Compton camera detector arrangement in which the monolithic scintillator acts as an absorber, while a pixelated GAGG scintillator array, read out by a SiPM multi-pixel photon counter (MPPC), is used as a scatterer component. The accuracy achievable with this system for detecting γ rays from laboratory point sources is investigated. The Compton camera system has been tested with radioactive 137Cs and 60Co point sources. The signal readout and data acquisition system is based on individual spectroscopy electronics modules (NIM and VME), for the absorber and a customized electronics based on Anger logic for the GAGG scatter array. The raw data were analyzed to serve as input for the image reconstruction, performed using the MEGAlib toolkit software. With a spatial resolution of 1 mm for the scatterer and less than 3 mm for the absorber component, respectively, shifts of 2 mm of both radioactive sources (137Cs and 60Co) could be resolved with the whole Compton camera system.

Super high counting rate of positron annihilation lifetime spectrometer achieved via multiple detectors

Positron annihilation lifetime (PAL) spectroscopy has long been considered as a powerful approach to characterize atomic-scale vacancy-type defects and supermicropores, which affect the macroscopic properties of materials. In standard PAL measurements, several million annihilation events are required to achieve accuracy. For a conventional PAL spectrometer which consists of two scintillation detectors and analytical electronics, the two detectors are usually perpendicularly positioned to diminish spectra distortions (caused by backscattering and pileup). The perpendicular placement of detectors leads to a counting rate of 100 – 300 counts/second (cps) while using a 30 μCi 22Na source (3.3 – 10 cps/μCi). Consequently, collecting one PAL spectrum with total counts of one million takes several hours. The long time limits its potential to observe changes in the microstructure. To increase the counting rate of PAL measurements, we propose a novel multi-detector PAL spectrometer, which includes three or four detectors, a digital oscilloscope, and an algorithm for any detector to record both start and stop signals. The spectrometer achieves a high counting rate of around 2144 cps (71.5 cps/μCi) with four detectors, which is about ten times that of a conventional one with two detectors perpendicularly positioned. This work enables us to perform in-situ PAL measurements to disclose the minute-scale evolution of microstructure more precisely during fast physical and chemical processes in the future.

EXPERIMENTAL STUDY OF BATTERY TEMPERATURE UNDER CONSTANT DISCHARGE RATE

This research is about an experimental study of battery temperature under constant discharge rate. This study consider constant discharge rates, constant air velocities, gap between battery cells in the battery module and placement of Resistance Temperature Detector (RTD) sensors to achieve the objective of this experiment studies. The relationship of temperature and discharge rates for different point on battery cell surface is compared. The Lithium-ion battery cells are discharged with a constant discharge current in this experiment. The heat generation on the battery surface as a function of discharge time are linked to the LabVIEW software. An axial fan creates constant air velocities that help in removing heat away from battery module during discharge process. The factors that are considered in this experiment are the discharging rate, air velocities and the thermal behaviour of the Lithium-ion battery cell on various point across the battery surface.

Simultaneous determination of flouride, iodate and iodide by ion chromatography in caustic off-gas scrubber of nuclear recycle facilities by employing dual detectors

ABSTRACT An ion chromatography method was developed for the simultaneous determination of fluoride, iodate and iodide in a caustic scrubber solution used for trapping off-gases released during the dissolution of nuclear fuels. A separation between iodate and fluoride could be realized with 0.6 mM hydroxide, which is too weak to elute other anions including iodide in reasonable time. Studies were carried out at different column temperature, and with the help of Van’t Hoff plots the thermodynamic parameters associated with the column equilibrium were estimated, which helped in understanding the co-elution of iodate and fluoride at higher concentration of eluent. An arrangement of conductivity detector and UV-VIS detector in sequence after the ion exchange column (with 15 mM NaOH as eluent) was used for recording chromatograms for conductivity signal and UV-VIS signal simultaneously. The information from the two chromatograms was utilized to quantify iodate, fluoride and iodide in a single run. The limit of detection for fluoride, iodate and iodide is 7 ppb, 10 ppb and 12 ppb, respectively. The precision of the method is better than 2% (RSD) at 0.5 mg/L. The method was used successfully for the real sample analysis.

SAS GEANT4 application and machine learning algorithms for radioactive particle tracking

Radioactive Particle Tracking (RPT) is a fluid measurement technique used in opaque ducts. To initiate the gauging process, RPT always requires the calibration of detectors. However, calibration poses a challenge for RPT deployment in industries. In most cases, experimental measurements are not a feasible option to calibrate RPT systems. To overcome this issue, Monte-Carlo simulations have been developed to imitate detector behavior and information recording. This study aimed to develop a user-friendly GEANT4 application for non-programmers to implement RPT in pipes with rectangular and cylindrical shapes. Additionally, the study used the application to evaluate which radiation detector arrangement can provide the best information for reconstructing particle position based on an Exploratory Data Analysis and the performance of machine learning algorithms. Two types of trajectories were simulated using the SAS GEANT4 application: straight and helicoidal. The generated results were normalized according to the activity of the radioactive source. The K-Nearest Neighbors algorithm and the Feedforward Neural Network were used to reconstruct the particle position. The detector arrangements were evaluated using Mean Euclidean Distance Error and Mean Absolute Error for each axis.

Information transport and limits of optical imaging in the highly diffusive regime

Noninvasive imaging through the human body or dense fog at optical wavelengths requires the collection of highly scattered photons, which corrupt imaging information and restrict most diffuse imaging techniques to $<$ 10 transport mean free path (TMFP) lengths. An information theoretical analysis of numerical simulations including practical considerations shows imaging information exists at the single-photon detection limit beyond 200 TMFP lengths. Information can be enhanced through increasing the collection of light, optimizing detector placement, and resolving measurements in the space-time domain.