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At least 415 records · Page 23

The Clementine instrument complement

The recent successes of the Galileo solid-state imaging (SSI) experiment at the Moon and Gaspra show the utility of multispectral imaging of planetary objects. 'Clementine' is the planetary community's 'code name' for the SDIO (Space Defense Initiative Organization), mission to the Moon and the asteroid Geographos. This mission is designed as a long term stressing test on sensors and space systems developed for SDIO. In the course of this test Clementine will obtain science data using a varied and powerful array of remote sensing instruments which were developed by or for Lawrence Livermore National Laboratory in Livermore, California. Clementine carries five cameras, one for navigation and four for science experiments. In addition, a laser ranger is included which will serve as a laser altimeter. The Clementine cameras cover a wider range of spatial resolutions and wavelength range than did Galileo and are almost ideally suited to mapping of mafic rock types as are present on the Moon and expected at Geographos. Calibration of the cameras will occur at the sensor calibration laboratory at LLNL. In flight calibrations, using standard stars and other standards should improve the stated accuracies. Signal-to-noise ratios (SNRs) include the following noise sources: shot noise, calibration error, digitization noise, readout noise, and frame transfer noise (where applicable). The achieved SNRs are a balance between detector saturation and acceptable image smear. The 'worst' case uses the longest possible integration times.

Lucey, Paul G.↗

Extension of mutation testing for the requirements and design faults - 322

Mutation Testing is a fault-based software testing technique that is considered to be the most efficient in detecting faults. It focuses on the software code level and follows a set of rules which are called mutation operators to systematically seed faults into the source code. Each seeded fault results is a new version of the software, which is called a mutant. Mutation testing promises to be effective in identifying adequate test data which can be used to find faults in the source code. However, traditional mutation testing is not geared towards the detection of requirements and design faults. To cover the full spectrum of possible faults, the mutation framework has been extended from the code level to the requirements and design level. Twenty-nine defects that appear in requirements and design documents were identified to define appropriate mutants. Then corresponding mutation operators that model the defects were developed. For each mutation operator, the strategy to generate a mutant and the evaluation of the number of possible mutants were defined. Existing code level cost reduction techniques were tailored for requirements and design mutation operators that result in a large number of mutants. With the extended mutation testing framework, the full spectrum of possible faults will be tested and identified to ensure the safety and functionality of the software. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

An optimization method of relativistic backward wave oscillator using particle simulation and genetic algorithms

Optimal design method of high-power microwave source using particle simulation and parallel genetic algorithms is presented in this paper. The output power, simulated by the fully electromagnetic particle simulation code UNIPIC, of the high-power microwave device is given as the fitness function, and the float-encoding genetic algorithms are used to optimize the high-power microwave devices. Using this method, we encode the heights of non-uniform slow wave structure in the relativistic backward wave oscillators (RBWO), and optimize the parameters on massively parallel processors. Simulation results demonstrate that we can obtain the optimal parameters of non-uniform slow wave structure in the RBWO, and the output microwave power enhances 52.6% after the device is optimized.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Real-time machine-learning-driven control system of a deformable mirror for achieving aberration-free X-ray wavefronts

A neural-network machine learning model is developed to control a bimorph adaptive mirror to achieve and preserve aberration-free coherent X-ray wavefronts at synchrotron radiation and free electron laser beamlines. The controller is trained on a mirror actuator response directly measured at a beamline with a real-time single-shot wavefront sensor, which uses a coded mask and wavelet-transform analysis. The system has been successfully tested on a bimorph deformable mirror at the 28-ID IDEA beamline of the Advanced Photon Source at Argonne National Laboratory. It achieved a response time of a few seconds and maintained desired wavefront shapes (e.g., a spherical wavefront) with sub-wavelength accuracy at 20 keV of X-ray energy. This result is significantly better than what can be obtained using a linear model of the mirror’s response. The developed system has not been tailored to a specific mirror and can be applied, in principle, to different kinds of bending mechanisms and actuators.

47 OTHER INSTRUMENTATION↗

TropiRoot 1.0: Database of tropical root characteristics across environments

Tropical ecosystems contain the world's largest biodiversity of vascular plants. Yet, our understanding of tropical functional diversity and its contribution to global diversity patterns is constrained by data availability. This discrepancy underscores an urgent need to bridge data gaps by incorporating comprehensive tropical root data into global datasets. Here, we provide a database of tropical root characteristics. This new database, TropiRoot 1.0, will be instrumental in evaluating an array of hypotheses pertaining to root functional ecology and plant biogeography, both within the tropics and relative to other global biomes. The data compilation was conducted by the TropiRoot Initiative, in partnership with the Fine-Root Ecology Database (FRED) and the Global Root Trait (GRooT) database, Colorado State University (CSU) and the Smithsonian Tropical Research Institute (STRI). Literature search and data extraction were conducted between 2020 and 2024. Literature was identified using Web of Science, Scopus, and complemented using the expert knowledge of members of TropiRoot. To provide broad environmental and geographical distributions, literature searches included root characteristics (traits) across global change drivers, natural gradients, and from different continents. We adopted FRED standardized data columns and streamlined the format to enhance accessibility for data extraction across various user groups. This optimized framework resulted in a smaller, yet comprehensive datasheet. To make the database compatible with other global root trait initiatives, column identification was standardized following the codes provided by FRED. These efforts culminated in data extracted from 104 new sources, resulting in more than 8000 rows of data (either species or community data). Most of the data in TropiRoot 1.0 include root characteristics such as root biomass, morphology, root dynamics, mass fraction, architecture, anatomy, physiology, and root chemistry. This initiative represents a 30% increase in the currently available data for tropical roots in FRED. TropiRoot 1.0 contains root characteristics from 25 different countries, where seven are located in Asia, six in South America, five in Central America and the Caribbean, four in Africa, two in North America, and 1 in Oceania. Due to the volume of data, when ancillary data were available, including soil data, these data were either extracted and included in the database or its availability was recorded in an additional column. Multiple contributors checked the entries for outliers during the collation process to ensure data quality. For text-based observations, we examined all cells to ensure that their content relates to their specific categories. For numerical observations, we ordered each numerical value from least to greatest and plotted the values, checking apparent outliers against the data in their respective sources and correcting or removing incorrect or impossible values. Some data (soil and aboveground) have different columns for the same variable presented in different units, including originally published units, but root characteristics data had units converted to match those reported in FRED. By filling a gap from global databases, TropiRoot 1.0 expands our knowledge of otherwise so far underrepresented regions and our ability to assess global trends. This advancement can be used to improve tropical forest representation in vegetation models. The data are freely available and should be cited when used.

FRED↗

Tomographic Image Reconstruction for the Parallel-Slit Ring Collimator Fast Neutron Emission Tomography System

For the past three years, Oak Ridge National Laboratory (ORNL) has been developing a passive fast-neutron emission tomography capability. The goal of this development is the ability to quantify the neutron source strength of individual fuel pins (rods) in spent nuclear fuel assemblies. Such a system could be used to measure the burnup of each fuel pin in a spent fuel assembly in order to take burnup credit when loading dry storage casks or to count individual fuel pins in spent fuel assemblies for safeguards purposes. At present, a laboratory prototype imager is under construction. The purpose of this prototype is to demonstrate imaging capability sufficient to resolve individual fuel pins in spent fuel assemblies. This report documents the development of the iterative reconstruction code used to perform tomographic image reconstruction, the imager response calculation used by the reconstruction code, and the results of reconstructions of simulated tomographic imaging measurements for the prototype imager design.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DESIGN AND VALIDATION OF A GAMMA-RAY SCANNING SYSTEM FOR MEASURING IRRADIATED NUCLEAR FUEL (ABSTRACT)

A prototype gamma-ray scanning system was designed to perform post-irradiation measurements of nuclear fuel at Idaho National Laboratory (INL). The system is composed of a coaxial high-purity germanium (HPGe) detector, a collimator, and mechanical positioning stages that translate the fuel sample across the front of the collimator. This paper documents the design process, modeling and the laboratory characterization performed to validate the system. The modeling of the system was done using the Monte Carlo N-Particle code with vendor-supplied design specifications, dimensional measurements, and x-ray radiographs of the HPGe detector. The characterization included measurements of calibrated radiation sources in different geometries, and calculations for absolute efficiency and dead time. Benchmark measurements were performed by scanning an irradiated fuel rodlet containing ten pellets of 4.9% enriched UO2 in zirconium alloy. These results were compared to simulated spectra to further help characterize the detector model. One goal of the system is to determine the number of fissions per gram of UO2 in the fuel; comparison of the results from this prototype system's assay of the irradiated fuel rodlet are in agreement with previously estimated results.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Failure Assessment

Three questions to which software developers want accurate, precise answers are "How can the software system fail?", "mat bad things will happen if the software fails?t', and "How many failures will the software experience?". Numerous techniques have been devised to answer these questions; three of the best known are: 1) Software Fault Tree Analysis (SFTA) 2) Software Failure Modes, Effects, and Criticality Analysis (SFMECA 3) Software Fault/Failure Modeling. SFTA and SFMECA have been successfully used to analyze the flight software for a number of robotic planetary exploration missions, including Galileo, Cassini, and Deep Space 1. Given the increasing interest in reusing software components from mission to mission, one of us has developed techniques for reusing the corresponding portions of the SFTA and SFMECA, reducing the effort required to conduct these analyses. SFTA has also been shown to be effective in analyzing the security aspects of software systems; intrusion mechanisms and effects can easily be modeled using these techniques. The Bi- Directional Safety Analysis (BDSA) method combines a forward search (similar to SFMECA) from potential failure modes to their effects, with a backward search (similar to SFTA) from feasible hazards to the contributing causes of each hazard. BDSA offers an efficient way to identify latent failures. Recent work has extended BDSA to product-line applications such as flight-instrumentation displays and developed tool support for the reuse of the failure-analysis artifacts within a product line. BDSA has also been streamlined to support those projects having tight cost and/or schedule constraints for their failure analysis efforts. We discuss lessons learned from practice, describe available tools, and identi@ some future directions for the topic. A substantial amount of research has been devoted to estimating the number of failures that a software system will experience during test and operations, as well as the number of faults that have been inserted into that system during its development. One of us has found that the amount of structural change to a system during its development is strongly related to the number of faults inserted into it. Using techniques requiring no additional effort on the part of the development organization, the required measurements of structural evolution can be easily obtained from a development effort's configuration management system and readily transformed into an estimate of fault content. So far, structure-fault relationships have been identified for source code; current work seeks to examine artifacts available earlier in the lifecycle to determine if similar relationships between structure and fault content can be found. In particular, relationships between requirements change requests and the number of faults inserted into the implemented system would provide a significant improvement in our ability to control software quality during the early development phases.

fault tree↗

Analysis of the Honeywell Uncertified Research Engine (HURE) with Ice Crystal Cloud Ingestion at Simulated Altitudes: Public Version

The Honeywell Uncertified Research Engine (HURE), a research version of a turbofan engine that never entered production, was tested in the NASA Propulsion System Laboratory (PSL), an altitude test facility at the NASA Glenn Research Center. The PSL is a facility that is equipped with water spray bars capable of producing an ice cloud consisting of ice particles, having a controlled particle diameter and concentration in the air flow. In preparation for testing of the HURE, numerical analysis of flow and ice particle thermodynamics was performed on the compression system of the turbofan engine to predict operating conditions that could potentially result in a risk of ice accretion due to ice crystal ingestion. The results of those analyses formed the basis of the test matrix. The goal of the test matrix was to have ice accrete in two regions of the compression system: region one, which consists of the fan-stator through the inlet guide vane (IGV), and region two which is the first stator within the high pressure compressor. The predictive analyses were performed with the mean line compressor flow modeling code (COMDES-MELT) which includes an ice particle model. Together these comprise a one-dimensional icing tool. The HURE engine was tested in PSL with the ice cloud over the range of operating conditions of altitude, ambient temperature, simulated flight Mach number, and fan speed with guidance from the analytical predictions. The engine was fitted with video cameras at strategic locations within the engine compression system flow path where ice was predicted to accrete, in order to visually confirm ice accretion when it occurred. In addition, traditional compressor instrumentation such as total pressure and temperature probes, static pressure taps, and metal temperature thermocouples were installed in targeted areas where the risk of ice accretion was expected. The current research focuses on the analysis of the data that was obtained after testing the HURE engine in PSL with ice crystal ingestion. The computational method was enhanced by computing key parameters through the fan-stator at multiple spanwise locations, in order to increase the fidelity with the current mean-line method. In addition, other sources of heat (non-adiabatic walls) were suspected to be the cause of accretion near the splitter-lip and shroud. Since there were no thermocouples near the splitter, a simple order of magnitude heat transfer model was implemented to estimate the wall temperature. Future analyses will require a higher fidelity thermal analysis of the compression system metal walls to accurately calculate the total heat flux to the ice particle. For many data points analyzed, there were differences between the thermodynamic system model and the measured test data that may partially be responsible for uncertainties with the results of the current analyses.

Turbomachinery↗

SNM neutron detection using a time-gated synthetic aperture hybrid approach

This work focuses on using forward and adjoint transport in a hybrid application of 3-D deterministic (PENTRAN) and Monte Carlo (MCNP5) codes to model a series of neutron detector blocks. These blocks, or 'channels, ' contain a unique set of moderators with 4 atm He-3 detectors tuned to detect and profile a gross energy spectrum of a passing neutron (SNM) source. Ganging the units together as a large area system enables one to apply time gating the source-detector response to maximize signal to noise responses from a passing source with minimal background; multiple units may be positioned as a collective synthetic aperture detector array to be used as a way of performing real time neutron spectroscopy for detecting special nuclear materials in moving vehicles. The initial design, detector response coupling, confirmation of initial design functionality using adjoint transport calculations, and realistic simulation using PENTRAN and MCNP5 are presented. Future work will include optimization and application to realistic scenarios and additional sources. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Combined Mesonet and Tracker

Title: Combined Mesonet and Trackers (UNL Mobile Mesonets) Authors University of Nebraska PI: Adam Houston, UNL Professor (ahouston2@unl.edu) Mailing Address: 126 Bessey Hall P.O. Box 880340 Lincoln, NE 68588-0340 CoMeT Overview The University of Nebraska-Lincoln operates three Combined Mesonet and Tracker (CoMeTs). CoMeTs are Ford Explorers (model years 2015, 2017, and 2019) with forward-mounted suites of meteorological sensors and dual moonroofs, combining the capability of a mobile mesonet to collect near-surface observations with the capability of an unmanned aircraft systems (UAS) tracker vehicle, which enables an observer in the second row of seats to see the aircraft and maintain compliance with Federal Aviation Administration policies on UAS operation. The CoMeTs collect observations of slow temperature and humidity at ~2 m above ground level (AGL) using a Vaisala HMP155A, fast temperature at ~2 m AGL using a Campbell Scientific 109SS-L thermistor, pressure at ~2.5 m AGL using a Vaisala PTB210, wind speed and direction at ~3.25 m AGL using an R.M. Young 05103 propeller anemometer, and vehicle heading using a KVH Industries C-100 fluxgate compass (Barbieri et al. 2019). The HMP155A and 109SS-L thermistor are shielded and aspirated within a U-tube (Waugh and Frederickson 2010; Houston et al. 2016). This list of sensors is also included in the CoMeT data file metadata. Manufacturer specifications for these instruments are given in Table 1 of Hanft and Houston (2018). The reported measured quantities are summarized below.CoMeT-3 was funded through an equipment allocation included in the NSF TORUS award (AGS-1824649). Instrument Description The specific sensors included on each CoMeT are summarized in the table at the end of this section. In general each CoMeT collects observations of slow temperature and humidity at ~2 m above ground level (AGL) using a Vaisala HMP155, fast temperature at ~2 m AGL using a Campbell Scientific 109SS-L thermistor, pressure at ~2.5 m AGL using a Vaisala PTB210 barometer with a Gill pressure port, wind speed and direction at ~3.25 m AGL using an R.M. Young 05103 propeller anemometer, position using a Garmin 19x HVS receiver, and vehicle heading using a KVH Industries C-100 fluxgate compass. The HMP155 and 109SS are shielded and aspirated within a U-tube (Waugh and Frederickson 2010; Houston et al. 2016). Fast temperature and corrected RH measurements (using sensors housed within the U-tube) have a time constant of 10-12 s based on data collected across a temperature and RH shock during the CLOUD-MAP 2017 calibration/validation tests on June 26, 2017. Vehicle speed was < 10 kts for this test. CoMeT-1 CoMeT-2 CoMeT-3 Slow Temperature Slow RH Vaisala HMP155A-L20-PT Part #: 22280-7 Vaisala HMP155E Part #: E1AA11A0B1A1A0A Vaisala HMP155E Part #: E1AA11A0B1A1A0A Fast temperature Campbell Scientific 109SS-L20-PT Part #: 21448-3 Campbell Scientific 109SS-L12-PW Part #: 21448-109 Campbell Scientific 109SS-L12-PW Part #: 21448-150 Pressure Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Wind RM Young 05103-L20-PT Part #: 18435-310 RM Young 05103-L20-PW Part #: 18435-244 RM Young 05103-L20-PW Part #: 18435-244 GPS Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Compass KVH C-100 Part #: 01-0177-15 KVH C-100 Part #: 01-0177-15 KVH C-100 Part #: 01-0177-15 Logger Campbell Scientific CR6-NA-XT-SW Part #: 28385-9 Campbell Scientific CR6-WIFI-XT-SW Part #: 28385-6 Campbell Scientific CR6-WIFI-XT-SW Part #: 28385-6 Data Collection and Real-Time Processing The reported measured quantities are summarized in the table below. Quantity Units Source Epoch time Seconds GPS Latitude and longitude Degrees GPS Altitude m GPS Pressure hPa PTB210 Temperature (fast) deg C 109SS-L Temperature (slow) deg C HMP155 RH (slow) % HMP155 Vehicle speed m/s GPS Vehicle heading deg C-100 and GPS In addition to the measured variables, several derived variables are calculated. Corrected/fast relative humidity (%) Relative humidity is adjusted to the fast temperature following Richardson et al. (1998) and Houston et al. (2016). Water vapor mixing ratio (g/kg) Dew point temperature (&deg;C) Potential temperature (Kelvin) Virtual potential temperature (Kelvin) Equivalent potential temperature (Kelvin) Regular intercomparisons between all three CoMeTs were performed during TORUS 2019. Comparisons were also conducted between CoMeT-1 and CoMeT-2 during LAPSE-RATE (2018) on 14 July. In these intercomparisons, the vehicles were parked adjacent to each other aligned perpendicular to (and facing into) the wind. To minimize engine heating effects, intercomparisons were only conducted when the wind speed was >10 kts. Data Format Original data files for each deployment are saved as text files and then converted to NetCDF. NetCDF versions have units that are CF compliant and may not match the original units in the txt files. The naming convention for the NetCDF files is as follows: UNL.CoMeT3.{deployment date YYYYMMDD}.{start time of observation collection in UTC HHMM}.L2.{post-processing codes}.cdf example: UNL.CoMeT3.20190627.1931.L2.g1.f1.cdf Post-processing codes are included to track modifications to the raw data. These codes are closely connected to error flags associated with each record. Each letter corresponds to a particular instrument: g: GPS p: Barometer tf: Fast temperature ts: Slow temperature rh: Relative humidity f: Compass w: Wind monitor a: All instruments Each number corresponds to a particular post-processing action described more below. Measured and derived variables are included in the following table. Variable Heading Standard Name Units time Time seconds since 00:00:00, 01-01-1970 Alt Altitude meters lat Latitude degrees north lon Longitude degrees east fast_temp Air Temperature kelvin slow_temp Air Temperature kelvin pressure Air Pressure pascals logger_RH Relative Humidity percent calc_corr_RH Relative Humidity percent wind_speed Wind Speed meters per second wind_dir Wind From Direction degrees vehicle_dir Vehicle Direction degrees dewpoint Dew Point Temperature kelvin mixing_ratio Humidity Mixing Ratio g/g theta Air Potential Temperature kelvin theta_v Virtual Potential Temperature kelvin theta_e Equivalent Potential Temperature Kelvin error_flag The error_flag variable is a string that matches the post-processing codes listed above. All instruments will have an associated code, but will have a &ldquo;0&rdquo; if the datum is unchanged from the initial processed value. Error Codes The following table summarizes the error codes for data collected before 2020: Error Code Relevant CoMeT Description g1 1,2,3 Exact correction. GPS position and time reprocessed from raw data g2 1 As far as we can tell this is an exact correction to an error in the GPS time. During the correct time periods the time suddenly went backwards ~250s and stayed at this offset for 750s when it corrected itself. The offset was applied to the &ldquo;time warp&rdquo; period. p1 2 Approximate correction. Hole in the pressure tube connecting the pressure port to the barometer. Resulted in erroneously low air pressure measurements when the vehicle was in motion. Derived variables recalculated (dew point temperature [e depends on qv and p], water vapor mixing ratio, potential temperature, virtual potential temperature, equivalent potential temperature) a1 3 Exact correction. Missing data reprocessed from raw data a2 1 Bug fix to bias correction for ts1, ts2, and rh1: water vapor mixing ratio was off by a factor of 10 and virtual potential temperature was wrong because of this. f1 3 No correction, missing data. Fluxgate compass inoperable. Wind speed and direction calculated using GPS-derived vehicle heading instead. rh1 1 Approximate correction. Constant bias of +1.7% removed from relative humidity. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) ts1 1 Approximate correction. Constant bias of +0.6 K removed from slow temperature. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) ts2 1 Approximate correction. Constant bias of +1.0 K removed. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) References Bolton, D., 1980: The Computation of Equivalent Potential Temperature. Mon. Wea. Rev., 108, 1046&ndash;1053, https://doi.org/10.1175/1520-0493(1980)108<1046:TCOEPT>2.0.CO;2. Hanft, W., and A. L. Houston, 2018: An Observational and Modeling Study of Mesoscale Air Masses with High Theta-E. Mon. Wea. Rev., 146, 2503&ndash;2524, https://doi.org/10.1175/MWR-D-17-0389.1.Wexler Houston, A. L., R. J. Laurence III, T. W. Nichols, S. Waugh, B. Argrow, and C. L. Ziegler, 2016: Intercomparison of unmanned aircraft-borne and mobile mesonet atmospheric sensors. Journal of Atmospheric and Oceanic Technology. 33, 1569-1582, doi: 10.1175/JTECH-D-15-0178.1. Lowe, P. R., 1977: An Approximating Polynomial for the Computation of Saturation Vapor Pressure. J. Applied Meteorology, 16, 100&ndash;103. Richardson, S. J., S. E. Frederickson, F. V. Brock, and J. A. Brotzge, 1998: Combination temperature and relative humidity probes: Avoiding large air temperature errors and associated relative humidity errors. Preprints, 10th Symp. On Meteorological Observations and Instrumentation, Phoenix, AZ, Amer. Meteor. Soc., 278&ndash;283. Waugh, S., and S. E. Frederickson, 2010: An improved aspirated temperature system for mobile meteorological observations, especially in severe weather. 25th Conf. on Severe Local Storms, Denver, CO, Amer. Meteor. Soc., P5.2. [Available online at https://ams.confex.com/ams/25SLS/techprogram/paper_176205.htm.]

54 ENVIRONMENTAL SCIENCES↗

Time-resolved soft x-ray spectra from laser-produced Cu plasma

The volumetric heating of a thin copper target has been studied with time resolved x-ray spectroscopy. The copper target was heated by a plasma produced using the Lawrence Livermore National Laboratory's Compact Multipulse Terawatt (COMET) laser. A variable spaced grating spectrometer coupled to an x-ray streak camera measured soft x-ray emission (800-1550 eV) from the back of the copper target to characterize the bulk heating of the target. Radiation hydrodynamic simulations were modeled in two-dimensions using the HYDRA code. The target conditions calculated by HYDRA were post-processed with the atomic kinetics code CRETIN to generate synthetic emission spectra. A comparison between the experimental and simulated spectra indicates the presence of specific ionization states of copper and the corresponding electron temperatures and ion densities throughout the laser-heated copper target.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Measurements and simulations of the cosmic-ray-induced neutron background

The cosmic-ray-induced neutron background at ground level has been measured and simulated in conjunction with EJ-309 organic liquid scintillators with an approximate deposited energy range of 0.5–6 MeV. Specifically, the pulse height distributions, net neutron count rates, and angular dependences were obtained. The simulations were carried out using the Monte Carlo transport code MCNPX-PoliMi combined with the (Cosmic-Ray Shower Generator) CRY source subroutine that returns secondary particles produced by cosmic rays. A scaling formula from literature was also implemented in the simulation. The angular dependence of the neutron count rate was measured by collimating the liquid scintillator with polyethylene to attain 18° angular resolution from 0° downwards to 72° horizontally. The neutron count rate was measured to be 23.10±1.69 h -1 sr -1 at 0°, and 7.20±0.78 h -1 sr -1 at 72°. The simulations and measurements compare well and show similar cosine anisotropy for the angular distribution. Finally, the study thus shows that the neutron background response in detector systems can be efficiently and accurately simulated using the procedures described.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Analysis of a Prototype Multi-Detector Fast-Neutron Radiography Panel

A multi-detector fast neutron radiography panel was built using the previous work on scalable neutron radiography using the IDEAS ROSSPAD readout module. A new aluminum housing was built to accommodate a large number of detectors tiled together. Additional changes to startup and processing code were made to operate the detector as one cohesive unit. Spatial resolution of the full panel using Cs-137 gammas was reported to be 0.42 line pairs per centimeter at 90% MTF and 2.09 line pairs per centimeter at 10% MTF. Here, three neutron radiographs generated using a Cf-252 fission neutron source were used to determine the spatial resolution of the panel for neutrons. The experiments had 90% MTF values of 0.24, 0.3, and 0.27 line pairs per centimeter and 10% MTF values of 1.30, 1.46, and 1.40 line pairs per centimeter. An example neutron radiograph was also used to prove that the radiography panel can perform true neutron radiography.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

The specific ( α ,n) production rate for 234 U in UF 6

Natural, depleted, and low enriched uranium hexafluoride is manufactured and transported on an industrial scale to support commercial nuclear power plant operation. One-way material production and flow is verified by nuclear safeguards inspectorates is by neutron counting. The dominant neutron source term is ( α ,n) production due to 234 U which gets enriched/depleted along with 235 U. We describe recent efforts to accurately determine the ( α ,n)/s/g of 234 U in UF 6 . This piece of nuclear data is of direct value to the nuclear safeguards community in the science-based verification and assay of bulk uranium hexafluoride. It also provides a benchmark on codes that calculate yield curves for various compounds from cross section data, and hence, provides a scale or normalization constraint on evaluated basic cross section data. Finally, in turn, evaluated basic data allows the yield from other materials to be calculated; for instance, moist uranyl fluoride, which is of interest in holdup measurements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Gamma-ray Spectroscopy in Low-Power Nuclear Research Reactors

Gamma-ray spectroscopy is an effective technique for radioactive material characterization, routine inventory verification, nuclear safeguards, health physics, and source search scenarios. Gamma-ray spectrometers typically cannot be operated in the immediate vicinity of nuclear reactors due to their high flux fields and their resulting inability to resolve individual pulses. Low-power reactor facilities offer the possibility to study reactor gamma-ray fields, a domain of experiments hitherto poorly explored. In this work, we present gamma-ray spectroscopy experiments performed with various detectors in two reactors: The EPFL zero-power research reactor CROCUS, and the neutron beam facility at the Ohio State University Research Reactor (OSURR). We employed inorganic scintillators (CeBr3), organic scintillators (trans-stilbene and organic glass), and high-purity germanium semiconductors (HPGe) to cover a range of typical—and new—instruments used in gamma-ray spectroscopy. The aim of this study is to provide a guideline for reactor users regarding detector performance, observed responses, and therefore available information in the reactor photon fields up to 2 MeV. The results indicate several future prospects, such as the online (at criticality) monitoring of fission products (like Xe, I, and La), dual-particle sensitive experiments, and code validation opportunities.

Pakari, Oskari V. (ORCID:0000000337048190)↗

Characterization of a mixed high-energy spallation neutron–proton field using monoisotopic activation detectors

In this paper, we used monoisotopic Co, Au, and Bi threshold activation detectors to characterize the high-energy ( > 5 MeV) portion of a mixed spallation neutron–proton (n/p) field. The field was produced by irradiating the natural uranium target–blanket subcritical assembly Quinta with 660-MeV protons from Phasotron accelerator at the Joint Institute for Nuclear Research (JINR) in Dubna. Experimental yields of the (n,x) and (p,x) reactions were compared to the calculated reaction rates, which represent the convolution of particle flux and reaction cross section. The flux was simulated using the radiation transport code MCNPX 2.7.0, and the cross sections were extracted from the following three sources: the intranuclear cascade model INCL4.2, the phenomenological spherical optical model from TALYS-1.8, and the evaluated nuclear data file TENDL-2015. We show that, in most cases, the evaluated data provide a closer agreement with the experimental data in comparison with INCL4.2 model, which is an integral part of MCNPX. Finally, our results bring a contribution to those fields of physics research that utilize computer prediction of neutron generation in the energy range of tens to hundreds MeV, such as the medical radioisotope production, radiation shielding of spallation neutron sources, and nuclear transmutation in accelerator-driven systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Genetic algorithms applied to reconstructing coded imaging of neutrons and analysis of residual watermark

Monte-Carlo simulation of neutron coded imaging based on encoding aperture for Z-pinch of large field-of-view with 5 mm radius has been investigated, and then the coded image has been obtained. Reconstruction method of source image based on genetic algorithms (GA) has been established. 'Residual watermark,' which emerges unavoidably in reconstructed image, while the peak normalization is employed in GA fitness calculation because of its statistical fluctuation amplification, has been discovered and studied. Residual watermark is primarily related to the shape and other parameters of the encoding aperture cross section. The properties and essential causes of the residual watermark were analyzed, while the identification on equivalent radius of aperture was provided. By using the equivalent radius, the reconstruction can also be accomplished without knowing the point spread function (PSF) of actual aperture. The reconstruction result is close to that by using PSF of the actual aperture.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗