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At least 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Gaussian Process Optimization of Sensitivity-Based Similarity Metrics between New Nuclear Applications and New/Existing Benchmarks

Confidently designing safe, new nuclear criticality experiments requires expert judgement, which could take years of experience. Sensitivity/uncertainty (S/U) analysis can be utilized by less experienced individuals to conservatively estimate uncertainties in important parameters, such as k eff , in newly proposed nuclear applications. This type of analysis relies on matching new nuclear applications with existing benchmark experiments. The Whisper-1.1 software package included in MCNP6.2 ®1 contains more than 1,100 International Criticality Safety Benchmark Evaluation Project (ICSBEP) benchmarks. These benchmarks however rarely match new nuclear applications. The number of benchmarks available to match a given set of materials or geometric configurations varies significantly. Furthermore, recently performed benchmark experiments may not have had enough time to be properly documented and published. Benchmarks are vital for determining the accuracy of nuclear data and can assist nuclear physics and evaluators in improving nuclear data libraries. Exhaustively exploring the parameter space using simulations with software such as MCNP is too computationally expensive. In this work, Gaussian process optimization was implemented to reduce the number of simulations needed for optimization over multiple parameters. This optimization scheme was designed to selectively generate new benchmarks with high sensitivity-based similarity metrics to user-defined nuclear applications. Two benchmark models of spherically nested shells containing plutonium, uranium, tantalum, and water were used in the optimization to match an application containing plutonium plates, stacked in a tantalum reflector, surrounded by water.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Constraining the impact of chlorine as a neutron absorber in next-gen fast reactor designs

The role of chlorine as a neutron poison and as a seed for producing radioactive waste in nuclear systems has driven a renewed interest to improve its nuclear data uncertainties. Additionally, basic and applied science programs that use CLYC (Cs 2 LiYCl 6 :Ce) detectors for neutron spectroscopy and monitoring are also very sensitive to any change in chlorine nuclear data for simulations of the detector response. In this work, sensitivities relevant for these different applications are addressed through simulations of the efficiency of CLYC detectors in a fast fission spectrum when applying new chlorine nuclear data as input. These simulations are validated by an experimental measurement using CLYC detectors coupled to an ionization chamber loaded with a 252 Cf spontaneous fission source. The results are then used to obtain the first reliable direct measurement of the 35 Cl(n,p 0 ) and summed Cl(n,p+n,α) fission spectrum average cross sections, found to be 54.7(32) and 105.0(98) mb, respectively. The results are within uncertainty of calculated fission spectrum averaged cross sections based on recently re-evaluated chlorine nuclear data, which confirm recent impact studies performed for the Molten Chloride Reactor Experiment. Meanwhile, there currently exists only one published criticality benchmark experiment that is sufficiently sensitive to chlorine nuclear data. Discrepancies are found with this set of criticality safety benchmarks, which are more sensitive to thermal and epithermal neutron energies than the energies, above 100 keV, tested in this current work. Hence, there is still a need to re-evaluate the chlorine nuclear data at lower energies to assess these discrepancies. Interpretation of the data from future “faster” criticality benchmarks, which are needed for next-gen fast reactor designs, benefit from the improved constraints on the chlorine nuclear data validated in this work.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Data Assimilation using Non-invasive Monte Carlo Sensitivity Analysis of Reactor Kinetics Parameters

Accurately predicting the criticality of an experiment before interacting with the experimental components is very important for criticality safety. Radiation transport software can be utilized to calculate the effective neutron multiplication factor of a nuclear system. Because of the integral nature of the effective neutron multiplication factor, the value calculated contains various sources of nuclear-data induced uncertainty. The sensitivity analysis and data assimilation technique presented in this paper exhibit one possible method of identifying and reducing the effective neutron multiplication factor nuclear-data induced uncertainty. The results presented in this work show that it is possible to use relative sensitivity coefficients of the prompt neutron decay constant and the effective delayed neutron fraction to 239 Pu nuclear data to reduce nuclear-data induced uncertainties in the effective neutron multiplication factor. This work has been utilized by members of the Los Alamos National Laboratory project EUCLID (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) for optimally designing a new experiment, which will be used to reduce compensating errors in 239 Pu nuclear data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Producing ENDF/B-quality Evaluations of 239 Pu(n,f) and 235 U(n,f) Average Prompt Neutron Multiplicities using the CGMF Model

This report documents evaluations of the neutron-induced 239 Pu and 235 U average prompt neutron multiplicities, $\overline{v}_p$, using the CGMF model developed at LANL. These evaluations are not updates of existing ENDF/B-VIII.0 nuclear data, but were both re-done from "scratch". That is, all experimental data were extracted from EXFOR, re-normalized to the newest nuclear data representing monitor observables, and detailed uncertainties were estimated from information in EXFOR as well as from templates of expected measurement uncertainties. We also included experimental data that were not yet available for ENDF/B-VIII.0, for instance, the data of Marini et al. for 239 Pu(n,f) $\overline{v}_p$ or the data of Khoklov et al. for 235 U(n,f) $\overline{v}_p$. Finally, we include the CGMF model; it computes $\overline{v}_p$ based on model parameters that at the same time calculate fission fragments as a function of mass, Y (A), the average total kinetic energy as a function of incident-neutron energy, $\langle TKE \rangle$(E inc ), etc. Such a detailed fission model that ties together many fission quantities has not been used to date for any $\overline{v}_p$ evaluation in ENDF/B. Here, we show that we can get evaluated 235 U(n,f) and 239 Pu $\overline{v}_p$ that not only correspond well to experimental $\overline{v}_p$, but that the associated evaluated model parameters also yield parameterizations of Y (A), $\langle TKE \rangle$(E inc ), etc., that correspond well to their respective experimental data. The new evaluated 239 Pu(n,f) $\overline{v}_p$ was also combined into a 239 Pu test file with the newest nuclear data for the 239 Pu prompt-fission neutron spectrum and fission cross sections. This new 239 Pu file performed reasonably well in predicting PU-MET-FAST assemblies, reaction rates in Jezebel and Flattop and three LLNL pulsed spheres. Due to that, the new 239 Pu(n,f) $\overline{v}_p$ evaluation presented here is being considered for ENDF/B-VIII.1. Hence, we can show here that CGMF is able to produce ENDF/B quality $\overline{v}_p$ nuclear data.

239Pu, 235U, Average Prompt-fission Neutron Multip↗
DOE OSTI2015

Inventory Uncertainty Quantification using TENDL Covariance Data in Fispact-II

The new inventory code Fispact-II provides predictions of inventory, radiological quantities and their uncertainties using nuclear data covariance information. Central to the method is a novel fast pathways search algorithm using directed graphs. The pathways output provides (1) an aid to identifying important reactions, (2) fast estimates of uncertainties, (3) reduced models that retain important nuclides and reactions for use in the code's Monte Carlo sensitivity analysis module. Described are the methods that are being implemented for improving uncertainty predictions, quantification and propagation using the covariance data that the recent nuclear data libraries contain. In the TENDL library, above the upper energy of the resolved resonance range, a Monte Carlo method in which the covariance data come from uncertainties of the nuclear model calculations is used. The nuclear data files are read directly by FISPACT-II without any further intermediate processing. Variance and covariance data are processed and used by FISPACT-II to compute uncertainties in collapsed cross sections, and these are in turn used to predict uncertainties in inventories and all derived radiological data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Sensitivity studies to Support TEX critical experiments design

In the frame of the ongoing Thermal/Epithermal experiments program, supported by the DOE-NCSP, we are characterizing expected data with analysis of sensitivity coefficients to nuclear data. The computations were performed for detailed and simplified models of the experimental configurations in order to demonstrate their invariance with respect to small geometry variations. The sensitivity coefficients were computed with recently developed precise methodologies using Monte Carlo tools (MCNP-6.1, SCALE 6.1 and MORET 5.C.1) with the following nuclear data libraries: ENDF/B-VII.0, ENDF/B-VII.1, and JEFF3.1. Since the considered experiments are devoted to tantalum data validation, their neutronic characteristics are compared with the relevant integral experiment data collected in the OECD/NEA ICSBEP Handbook. Although analysis of sensitivity coefficients taken alone is insufficient for an entire assessment, we can conclude that TEX experimental results can fill gaps in the available benchmarks to facilitate quantification of uncertainty for plutonium containing systems with epithermal neutron spectra (e.g. wet plutonium-based powders). However, analysis of sensitivity profiles demonstrates that an advanced statistical methodology will be needed to fit tantalum nuclear data or to evaluate the associated uncertainties. (authors)

42 ENGINEERING↗
DOE OSTI2022

Reactivity Coefficient Measurements and Sensitivity Studies [Abstract]

Nuclear data validation is often performed today using criticality measurements. The gold standard for criticality measurements is the International Criticality Safety Benchmark Experiment Project (ICSBEP). The validation specifically focuses on the effective multiplication factor (k eff ). K eff is a relatively easy parameter to infer and has reduced uncertainty due to being at or above critical. However, while k eff is a well-documented parameter with detailed sensitivity and uncertainty analysis, it cannot be used as a standalone metric to determine inaccuracies in nuclear data (e.g., cross section data, PFNS, nu), which is based on theory, physics, and differential measurements. The Experiments Underpinned by Computational Learning for Improvements in nuclear Data (EUCLID) project aims to identify compensating errors in specific nuclear data by optimally designing experiments that are sensitive to a suite of measurement parameters beyond k eff . By identifying how each parameter's nuclear data sensitivity differs from others, experiments can be designed to constrain questionable nuclear data. One sensitivity that is of particular interest to this project includes reactivity coefficient sensitivities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Validation of Jezebel Reactivity Coefficients and Sensitivity Analysis

Nuclear data validation is often performed today using criticality measurements. The gold standard for criticality measurements is the International Criticality Safety Benchmark Experiment Project (ICSBEP). The validation specifically focuses on the effective multiplication factor ($k_{eff}$). $K_{eff}$ is a relatively easy parameter to infer and has reduced uncertainty due to being at or above critical. However, while $k_{eff}$ is the most documented parameter and its uncertainties and sensitivities have been evaluated in great detail, it cannot be used as a standalone metric to determine inaccuracies in nuclear data (e.g., cross section data, PFNS, nu), which is based on theory, physics, and differential measurements. The Experiments Underpinned by Computational Learning for Improvements in nuclear Data (EUCLID) project aims to identify compensating errors in specific isotope nuclear data by optimally designing experiments that are, or are not sensitive to a suite of measurement parameters beyond $k_{eff}$. By identifying parameters that are sensitive to each other, oppositely sensitive, or have substantial magnitude differences in sensitivity, experiments can be designed to constrain questionable nuclear data. One sensitivity that is of particular interest to this project includes the sensitivity of reactivity coefficients. Reactivity coefficients compare reactivity, which is related to $k_{eff}$ at two different states therefore being sensitive to small changes in the system. The most common type of reactivity coefficient measurements is comparison to void for a small sample within the assembly. It is key that the sample sizes are small enough to not affect the flux of the full system. Reactivity coefficients were evaluated for many early experiments to better understand transport corrected cross sections. In fact, ICSBEP includes reactivity coefficient results as “Supplemental Measurements” in appendices for a handful of older benchmarks. One of those benchmarks is Jezebel, the bare Pu critical assembly. This paper compares new simulations of reactivity coefficients for Jezebel, and explores the sensitivity of reactivity coefficients to small changes in nuclear data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Python Library For Reading Endf Files

Evaluated Nuclear Data Files (ENDFs) are the most common way to store nuclear data. However, they are a hard-to-read format that few people or programs can read. OpenMC, an open source project, developed a way to read Evaluated Nuclear Data Files (ENDF) into a useful form for python. This library will remove all unnecessary code from OpenMC to focus solely on reading nuclear data. In addition, it will handle parsing Grouped cross-section data from an ENDF file, which OpenMC does not currently handle.

Gale, MicahD.↗
DOE OSTI2012

Preliminary neutronics design of china lead-alloy cooled demonstration reactor (CLEAR-III) for nuclear waste transmutation

China Lead-Alloy cooled Demonstration Reactor (CLEAR-III), which is the concept of lead-bismuth cooled accelerator driven sub-critical reactor for nuclear waste transmutation, was proposed and designed by FDS team in China. In this study, preliminary neutronics design studies have primarily focused on three important performance parameters including Transmutation Support Ratio (TSR), effective multiplication factor and blanket thermal power. The constraint parameters, such as power peaking factor and initial TRU loading, were also considered. In the specific design, uranium-free metallic dispersion fuel of (TRU-Zr)-Zr was used as one of the CLEAR-III fuel types and the ratio between MA and Pu was adjusted to maximize transmutation ratio. In addition, three different fuel zones differing in the TRU fraction of the fuel were respectively employed for this subcritical reactor, and the zone sizes and TRU fractions were determined such that the linear powers of these zones were close to each other. The neutronics calculations and analyses were performed by using Multi-Functional 4D Neutronics Simulation System named VisualBUS and nuclear data library HENDL (Hybrid Evaluated Nuclear Data Library). In the preliminary design, the maximum TSRLLMA was {approx}11 and the blanket thermal power was {approx}1000 MW when the effective multiplication factor was 0.98. The results showed that good performance of transmutation could be achieved based on the subcritical reactor loaded with uranium-free fuel. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

4th Big Data for Nuclear Power Plants Workshop 2023

The Ohio State University and Idaho National Laboratory organized the 4 th Big Data for Nuclear Power Plants Workshop in November, 2023 in Columbus, Ohio. Workshop topics were chosen to understand the challenges and gaps that need to be addressed to maximize the impact of data on the nuclear industry, as well as the associated applications and risks. Discussions were focused around six specific application areas: Operation and Maintenance; Machine Learning in Nuclear Materials and Advanced Manufacturing; Cybersecurity; High-Performance Computing and Massive Computation; Big Data and Digital Twins; and Nuclear Non-Proliferation. The opportunities, challenges, and risks identified in the six focus areas explored in this workshop are diverse, but some common themes emerge, such as the importance of data integrity, quality, coverage, privacy, and traceability. Big data and AI/ML tools can be leveraged to reduce costs, optimize human tasking, and reduce human error across various application areas. In order for the nuclear industry to benefit from big data and advanced analytic capabilities, it is essential to address challenges and risks, such as data privacy, model reliability, and computational resource availability. Learning from other industries that have successfully implemented big data and AI/ML technologies, like the aerospace industry, can help the nuclear industry successfully integrate these technologies.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Modeling of the Molten Salt Reactor Experiment with SCALE

A SCALE model was developed for the Molten Salt Reactor Experiment (MSRE) benchmark that was recently added to the International Handbook of Evaluated Reactor Physics Benchmark Experiments. This SCALE model served as a basis for criticality calculations and nuclear data sensitivity and uncertainty analyses with the Monte Carlo code Shift and the TSUNAMI computational capabilities in the SCALE code system. The focus of this work is the assessment of the impact of nuclear data on the calculated eigenvalue results in support of the discussion of differences between the calculated and the experimental eigenvalue result. The differences in the eigenvalues obtained using the ENDF/B-VII.0, ENDF/B-VII.1, and ENDF/B-VIII.0 nuclear data libraries cover a relatively small range of ~230 pcm. Since eigenvalue sensitivity of the MSRE is dominated by the neutron multiplicity and neutron capture of 235 U and elastic scattering in graphite, relevant changes in the ENDF/B libraries for nuclear reactions (such as carbon capture) that caused large differences in other graphite-moderated systems did not have a significant impact. Propagation of nuclear data uncertainty results in an eigenvalue uncertainty of ~700 pcm with the major contributors being 235 U neutron multiplicity, graphite elastic scattering, and 7Li neutron capture. All calculations resulted in large differences of ~2000 pcm in eigenvalue compared to the benchmark experimental value. Several potential contributors to this difference—including uncertainties and gaps in the knowledge of the material, geometry, and nuclear data—were identified. Simplified models of the full MSRE core were developed, and similarity assessments were conduced with the full MSRE core model. It was found that simplified models can serve as adequate surrogates of the full-core model such that they can be used for performing selected nuclear data performance assessments with a lower computational burden.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Nuclear Weapons Data Strategy

This document describes the data strategy for the Nuclear Weapons Program Management Unit (NW PMU), with emphasis on functions related to the product realization lifecycle. It describes a vision to more effectively value and utilize data as an asset: data often is our product, and when it isn't, our products are made possible only through the data produced and consumed throughout each product's lifecycle. True confidence in the nuclear deterrent requires a clear understanding of how our products perform against requirements; both in the near term as well as over long periods of time. Data is the foundation for this understanding, and as such is a key enabler of the success of the NW mission. This document defines principles that enable a "culture of care" around NW data and drive the specific approaches to create a data-centric environment that is sustainable, agile, and responsive to the needs of the NW mission. The strategy outlined within this document must guide the definition of a high-level roadmap to achieve this vision, which in turn will be supported by separate detailed implementation plans.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2011

Isotopic yield measurement in the heavy mass region for {sup 239}Pu thermal neutron induced fission

Despite the huge number of fission yield data available in the different evaluated nuclear data libraries, such as JEFF-3.1.1, ENDF/B-VII.0, and JENDL-4.0, more accurate data are still needed both for nuclear energy applications and for our understanding of the fission process itself. It is within the framework of this that measurements on the recoil mass spectrometer Lohengrin (at the Institut Laue-Langevin, Grenoble, France) was undertaken, to determine isotopic yields for the heavy fission products from the {sup 239}Pu(n{sub th},f) reaction. In order to do this, a new experimental method based on {gamma}-ray spectrometry was developed and validated by comparing our results with those performed in the light mass region with completely different setups. Hence, about 65 fission product yields were measured with an uncertainty that has been reduced on average by a factor of 2 compared to that previously available in the nuclear data libraries. In addition, for some fission products, a strongly deformed ionic charge distribution compared to a normal Gaussian shape was found, which was interpreted as being caused by the presence of a nanosecond isomeric state. Finally, a nuclear charge polarization has been observed in agreement, with the one described on other close fissioning systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Inverse Sensitivity/Uncertainty Methods Development for Nuclear Fuel Cycle Applications

The Standardized Computer Analyses for Licensing Evaluation (SCALE) software package developed at the Oak Ridge National Laboratory includes codes that propagate uncertainties available in the nuclear data libraries to compute uncertainties in nuclear application performance parameters (responses). We report on our recently commenced eorts to extend this capability to develop an inverse sen- sitivity/uncertainty (IS/U) methodology that identies the improvements in nuclear data that are needed to compute application responses within prescribed tolerances, while minimizing the cost of such data improvements. We report on our progress to date and present a simple test case for our method. Our methodology is directly applicable to thermal and intermediate neutron energy systems because it addresses the implicit neutron resonance self-shielding eects that are essential to accurate modeling of thermal and intermediate systems. This methodology is likely to increase the eciency of nuclear data eorts.

Arbanas, Goran↗
DOE OSTI2025

Evaluation of PBR Spent Fuel Criticality and Dose Rate Compliance for Storage and Transportation

Spent tri-structural isotropic (TRISO)–based fuels have a strong track record in storage and transportation without documented incidents. This work seeks to reduce uncertainty to aid in more informed spent fuel management of TRISO-based fuels by modeling both fresh and spent pebble bed reactor (PBR) fuel and comparing the results to the regulatory standards from 10 CFR 71. SCALE was used for all modeling due to it having fast and accurate methods for handling PBR fuel modeling, as well as having an efficient method for shielding calculations in monaco with automated variance reduction using importance calculations (MAVRIC), which utilizes the consistent adjoint-driven importance sampling (CADIS) and the forward-weighted consistent adjoint-driven importance sampling (FW-CADIS) methods. KENO-VI was used for all criticality calculations, TSUNAMI was used for uncertainty quantification on k-effective, TRITON and the Oak Ridge isotope generation code (ORIGEN) were both used for depletion of the fuel, and MAVRIC was used for shielding calculations. For criticality assessments, this study focused on the requirement that the value of the neutron multiplication factor, k-effective (k-eff), would not exceed a peak value of 0.95, including uncertainty, with 95% confidence. Criticality was initially examined by modeling fresh fuel from three different designs—HTR-10 fuel, PBMR-400 fuel, and demonstration fuel representative of a TRISO-fueled modern high-temperature gas reactor (HTGR) design, henceforth referred to as Demo HTGR—and placing them into various sized containers with conditions described in 10 CFR 71 to quantify the peak k-eff state. When the peak value of 0.95 k-eff was exceeded, mitigation methods were examined in those scenarios. Burnup credit, pebble displacement in areas of strong neutron multiplication, and random pebble replacement using pebbles of various compositions and replacement fractions were examined. In summary, the criticality of PBR fuels can be well accounted for by restricting container size, taking credit for burnup, or by displacing/replacing pebbles. Uncertainty of the k-eff due to nuclear data uncertainties was recorded at ~0.6644%Δk/k, or roughly 664% mil (pcm). The nuclear data–induced uncertainty was relatively small and should not require significant modification in the design to be accounted for. Revisions to the evaluated nuclear data file values have been shown to have a larger impact than nuclear data–induced uncertainty. For dose rate aspects, U.S. Nuclear Regulatory Commission regulations require a maximum dose rate of 10 millirem per hour (mrem/h) at 2 meters. In examining the dose rate behavior of spent PBR fuel, the representative Demo HTGR fuel was modeled exclusively due to it possessing the highest target burnup of the examined fuels. Equilibrium cycle modeling methods were used to produce a higher-fidelity discharge isotopic composition than simple assumptions, such as reflected pebbles. The discharge composition was used as a source term in the fixed-source transport shielding calculations, and dose rates were calculated at 2 m for the shortest possible cooling time. The low concentration of fuel material led to dose rates that were in line with regulatory limits, despite the high burnup when compared to traditional light water reactor fuels. In conclusion, the methods employed in this study would require more work to further verify and validate and are limited to the criticality and dose rate analyses performed.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Subcritical Copper-Reflected-α-phase Plutonium (SCRαP) Integral Experiment Design

A Subcritical Copper-Reflected α-phase Plutonium (SCRαP) integral benchmark experiment is proposed where multiplication will be approximated using correlated neutron data from a detector system consisting of {sup 3}He tubes inside polyethylene. Measurements will be performed on various subcritical experimental configurations consisting of a weapons-grade plutonium sphere surrounded by different Cu thicknesses. In addition to the proposed base experimental configurations with Cu, additional configurations are planned with the plutonium ball nested in various thicknesses of interleaved polyethylene spherical shells mixed in with the Cu shells. The polyethylene is intended to provide fast neutron moderation and reflection, resulting in additional measurements with differing multiplication, spectra, and nuclear data sensitivity. The proposed experiments will performed at the National Criticality Experiments Research Center (NCERC). NCERC is home to a 4.5-kg α-phase stainless steel clad plutonium sphere that is referred to as the BeRP (Beryllium-Reflected Plutonium) ball due to its historical use in a beryllium-reflected critical experiment. In 2014, similar subcritical measurements were performed with the BeRP ball surrounded by nickel and tungsten. The nickel-reflected measurements were documented as a benchmark evaluation which was accepted by the International Criticality Safety Benchmark Evaluation Project (ICSBEP). Similar to past measurements, the proposed work will help both identify deficiencies and quantify uncertainties in nuclear data and validate computational methods related to neutron multiplication inference for subcritical benchmark evaluations. Monte Carlo simulations were performed for the preliminary design of a subcritical Copper-Reflected - phase Plutonium (SCRP) integral benchmark experiment. Specifically, MCNP{sup R} version 6 was used to determine the k{sub eff} and associated nuclear data sensitivities for different preliminary configurations (reflector thickness, material type). The final experimental design process will include continuous-energy nuclear data sensitivity analysis. This will help assess the potential impact of this integral measurement as it relates to international efforts to continuously improve current libraries (ENDF, JEFF, JENDL etc) that still tend to over/under-estimate the measured results of integral experiments, sometimes significantly. Deficiencies in underlying nuclear data quantities such as Nubar have been shown to have an effect on inferred values from subcritical measurements as well. The proposed experiments and subsequent computational validation will help identify such deficiencies. It will also help validate new nuclear data evaluations, including one for Cu that was recently performed in the resolved region up to 100 MeV for {sup 65}Cu and {sup 63}Cu which is expected to improve Cu-related benchmark simulation performance. The final experimental design phase will also include simulation results that will incorporate the detectors that will be used for the subcritical measurements. For the benchmark portion of the measurements, the main detectors that are being considered are portable neutron multiplicity counters made up of {sup 3}He tubes embedded in polyethylene and lined with cadmium. These detectors employ a data acquisition system that produces list-mode data (correlated information where each event is listed sequentially) that can be analyzed using the Feynman variance-to-mean method. Other detector systems including SNAP (single {sup 3}He tube embedded in polyethylene), and a high-purity germanium (HPGe) detector are being considered for supplementary measurements only and are not intended to be used for the final benchmark measurements. Decoupling the supplementary detectors from the system eliminates any contribution to the total system multiplication, and greatly simplifies the final computational benchmark model. Therefore, an optimization of the portable neutron multiplicity counter placement in the benchmark measurements will be performed to ensure that there is minimal contribution to the total system multiplication. In addition, new temperature measurement techniques and hardware will be explored. (authors)

42 ENGINEERING↗