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Data-Informed Evaluation Framework for Integrated Energy Systems: Insights from Power, Process Heat, and Hydrogen Production Applications

The multi-criteria decision analysis (MCDA) framework provides a systematic evaluation of the diverse preferences and performance metrics associated with alternative solutions. This approach is advantageous over a single-criterion methodology, which are only valid under conditions that assume ceteris paribus or an "apples-to-apples" comparison. However, selecting suitable technologies for integrated energy systems (IES) can be likened to an "apples-to-oranges" comparison, given the heterogeneous factors at stake. These factors include economics and performance parameters, geological compatibility, and environmental impacts. Consequently, past research has often employed a mixture of qualitative and quantitative criteria tailored to the specific interests of each study. While the method proves effective in handling the intricate interplay of criteria, the resulting rankings and scores can vary from study to study. This inconsistency is introduced from the use of subjectively defined thresholds and weights. As a result, decision-makers frequently find it challenging to establish clear connections between specific criteria and the resulting scores, as the transformation of criteria into ordinal scores results in a substantial loss of information. To address this challenge, we introduce a data-informed IES evaluation framework that offers comprehensive, interpretable, and traceable evaluations backed by quantifiable rationale. First, we identified key IES evaluation criteria from a decade of literature, focusing on relevant IES applications in power, process heat, and hydrogen production. We leveraged state-of-the-art cost estimates from the Idaho National Laboratory (INL) and technical data from 78 reactor designs from the International Atomic Energy Agency (IAEA) and the Organization for Economic Co-operation and Development - Nuclear Energy Agency (OECD-NEA). Lastly, we established thresholds by analyzing the mean, variance, root mean square, and slope of values across alternatives, categorizing the preferences of decision-makers into distinct utility functions, such as linear, saturating, exponential, and stepwise. Our approach yielded two main outcomes: (1) it provided consistent assessments across different stakeholder groups and (2) it visualized uncertainties in the decision-making context via comprehensive sensitivity analysis. To demonstrate the impact of our framework, we conducted case studies on 6 reactor designs (AP1000, NuScale, BWRX-300, Xe-100, eVinci, iMSR) for the three applications. Our data-driven framework proved to be highly effective in addressing heterogenous uncertainties faced by varied decision-makers? preferences and IES applications, as well as cost and technical estimates of advanced reactors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Chapter 8 - Testing and Evaluation Methods for Protection Systems

In this chapter, we aim to present different approaches used formally and informally for the evaluation of protection devices and schemes. This chapter starts with presenting background on generalization of protection device components, followed by the resources necessary to evaluate the protection system. Further, this chapter presents the different approaches used in protection evaluation with their advantages and disadvantages. Finally, this chapter closes by presenting background on technology readiness level metrics. Technology readiness level metric is borrowed from the space industry for the purpose of comparing the maturity of the different protection technologies and using the appropriate evaluation methods from the list presented here.

power systems↗

Development of a Benchmark Eddy Flux Evapotranspiration Dataset for Evaluation of Satellite-Driven Evapotranspiration Models Over the CONUS

A large sample of ground-based evapotranspiration (ET) measurements made in the United States, primarily from eddy covariance systems, were post-processed to produce a benchmark ET dataset. The dataset was produced primarily to support the intercomparison and evaluation of the OpenET satellite-based remote sensing ET (RSET) models and could also be used to evaluate ET data from other models and approaches. OpenET is a web-based service that makes field-delineated and pixel-level ET estimates from well-established RSET models readily available to water managers, agricultural producers, and the public. The benchmark dataset is composed of flux and meteorological data from a variety of providers covering native vegetation and agricultural settings. Flux footprint predictions were developed for each station and included static flux footprints developed based on average wind direction and speed, as well as dynamic hourly footprints that were generated with a physically based model of upwind source area. The two footprint prediction methods were rigorously compared to evaluate their relative spatial coverage. Data from all sources were post-processed in a consistent and reproducible manner including data handling, gap-filling, temporal aggregation, and energy balance closure correction. The resulting dataset included 243,048 daily and 5,284 monthly ET values from 194 stations, with all data falling between 1995 and 2021. We assessed average daily energy imbalance using 172 flux sites with a total of 193,021 days of data, finding that overall turbulent fluxes were understated by about 12% on average relative to available energy. Multiple linear regression analyses indicated that daily average latent energy flux may be typically understated slightly more than sensible heat flux. This dataset was developed to provide a consistent reference to support evaluation of RSET data being developed for a wide range of applications related to water accounting and water resources management at field to watershed scales.

54 ENVIRONMENTAL SCIENCES↗

Potential of deep learning methods to enhance satellite-based monitoring of nuclear power plants focusing on remote operation evaluations

The anticipated expansion of the nuclear industry and the deployment of new nuclear reactors (200 + GW of new nuclear capacity by 2050) require the development of monitoring systems that align with safety and security concerns, providing enhanced evaluation capabilities. A remote monitoring system using satellites and deep learning techniques was evaluated for its ability to detect anomalies and capture various features of nuclear reactors independently of the conditions on the ground. Satellite images of current operational and under-construction nuclear power plants were collected from Google Earth Pro as a surrogate database. Subsequently, five datasets were created from the collected images. Transfer learning technique was used for several classification tasks utilizing VGG16, ResNet50V2, Xception, DenseNet121, and MobileNetV2 pre-trained models. In the first task, the capability of the monitoring system to detect abnormal conditions or processes in a nuclear power plant was investigated. In the second task, the ability to capture operational features remotely was examined. As an example, for the purposes of this study, these features included classifying reactors based on type, power range, or onsite condition. Several evaluation metrics were used to compare the performance of the pre-trained models and the overall monitoring system. Here, the evaluation results demonstrated that deep learning techniques and pre-trained models applied to satellite images have the potential to facilitate further and expand capabilities in monitoring systems to assess plant operation details.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Energy-saving potential evaluation for primary schools with occupant-centric controls

Recent studies demonstrated that there is significant energy-saving potential for primary schools, which heating, ventilation, and air-conditioning (HVAC) systems with occupant-centric control (OCC) is an excellent candidate to save energy. However, such an energy impact has yet to be evaluated for different climate zones as well as different energy code versions, but is critical for technology transfer and deployment. Therefore, this paper conducts comprehensive evaluation on the energy-saving potentials for the primary schools with two advanced OCC strategies: presence-based and counting-based. In this work, ninety-six building energy models with stochastic behavior of occupants are developed and simulated, which consist of two building energy code versions, 16 climate zones, and baseline case (without OCC) and two advanced cases (with OCC). To evaluate the energy saving potentials for OCC, primary schools in the U.S. are used as an example. The results show that there is significant energy-saving potential for primary schools by considering OCC strategies, especially the counting-based case. The energy-saving potential is up to 10.2% for presence-based OCC and 12.41% for counting-based OCC. Furthermore, both climate and code version have a significant impact on energy savings from OCC strategies. The energy-saving potentials vary from 1.79% to 12.41% for different climates and code versions. This evaluation can also contribute to quantify the nationwide energy saving potential for other countries.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Performance evaluation of finned tube heat exchanger using curved wavy delta winglet vortex generators with circular perforations

Vortex generation is recognized as an effective passive approach to improve the heat transfer rate in fin and tube heat exchangers (FTHEs). The current study proposed innovative designs of curved wavy delta winglet vortex generators (CWDWVGs), both without and with circular perforations, to improve the heat transfer efficiency of FTHEs. There is potential to increase heat transfer performance further through various CWDWVG designs. Here, this study explores seven unique CWDWVG configurations, from 1-wave to 7-wave. A 3-D computational numerical model is utilized to evaluate the Thermo-hydraulic performance of FTHEs fitted with these different CWDWVG configurations across Reynolds numbers from 400 to 2000. This comparative analysis of the Thermo-hydraulic performance of FTHEs featuring four parallel circular tube layouts assesses configurations both with and without vortex generators (VGs) and various hole configurations. The evaluation of Thermo-hydraulic performance involves different parameters, including the London area goodness factor (LAGF), Colburn factor (j), friction factor (f), pressure drop (?P), and Nusselt number (Nu). Results demonstrate that the various CWDWVG configurations and the number of holes in them substantially affect the efficiency, as evaluated by the dimensionless Performance Evaluation Criteria (PEC). Notably, the 7-wave CWDWVGs surpassed other configurations, and integrating circular punched perforations further improved the thermal-hydraulic performance of FTHE. Specifically, the 7-wave CWDWVGs without holes demonstrated superior performance over other configurations, showing a significant increase in Nusselt number by 75.18% and 85.16% at Reynolds numbers of 2000 and 400, respectively, alongside an increase in pressure drop by 216.38% to 224.96%. Meanwhile, the 7-wave CWDWVGs with eight holes, in comparison to those without holes, exhibited a Nusselt number increase of 0.85%, a pressure drop decrease of 7.31%, and a reduction in the friction factor by 5.82%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Failure evaluation of neutron-irradiated SiC/SiC composites by underwater acoustic emission

Here, understanding the statistical properties of mechanical properties of non-irradiated and neutron-irradiated SiC/SiC composites is essential for component design. This study aims to evaluate the detailed damage accumulation behavior of composites focusing on two fracture parameters: proportional limit stress (PLS) and acoustic emission (AE) onset stress. The developmental underwater AE technique, which is benefit in non-contact in-situ failure monitoring method during mechanical testing and in handle of the irradiated material, was first applied to evaluate damage accumulation behavior. Two types of chemical vapor infiltration SiC/SiC composites were used: one reinforced with Hi-Nicalon Type-S SiC fiber and one reinforced with Tyranno-SA3 SiC fiber in the form of satin-woven 2D fabrics with pyrolytic carbon interface. Neutron irradiation in the High Flux Isotope Reactor at Oak Ridge National Laboratory reached a fluence of 30 dpa at a temperature of 620–670°C. Four-point flexural tests were conducted to evaluate post-irradiation strength. Weibull statistics did not suggest marked degradation of composite strength. Detailed failure behavior evaluated by AE demonstrated no irradiation-induced change of the AE onset stress (i.e., crack initiation equivalent stress). Failure probability analysis suggests that increasing the reliability of composites (i.e., the Weibull modulus rather than strength itself) is essential to expanding the design margin and benefiting from a probabilistic design approach.

36 MATERIALS SCIENCE↗

Deep-Learning-Derived Evaluation Metrics Enable Effective Benchmarking of Computational Tools for Phosphopeptide Identification

Tandem mass spectrometry (MS/MS)-based phosphoproteomics is a powerful technology for global phosphorylation analysis. However, applying four computational pipelines to a typical mass spectrometry (MS)-based phosphoproteomic dataset from a human cancer study, we observed a large discrepancy among the reported phosphopeptide identification and phosphosite localization results, underscoring a critical need for benchmarking. While efforts have been made to compare performance of computational pipelines using data from synthetic phosphopeptides, evaluations involving real application data have been largely limited to comparing the numbers of phosphopeptide identifications due to the lack of appropriate evaluation metrics. We investigated three deep learning-derived features as potential evaluation metrics: phosphosite probability, Delta RT and spectral similarity. Predicted phosphosite probability is computed by MusiteDeep, which provides high accuracy as previously reported; Delta RT is defined as the absolute retention time (RT) difference between RTs observed and predicted by AutoRT; and spectral similarity is defined as the Pearson’s correlation coefficient between spectra observed and predicted by pDeep2. Using a synthetic peptide dataset, we found that both Delta RT and spectral similarity provided excellent discrimination between correct and incorrect peptide-spectrum matches (PSMs) both when incorrect PSMs involved wrong peptide sequences and even when incorrect PSMs were caused by only incorrect phosphosite localization. Based on these results, we used all the three deep learning-derived features as evaluation metrics to compare different computational pipelines on diverse set of phosphoproteomic datasets and showed their utility in benchmarking performance of the pipelines. The benchmark metrics demonstrated in this study will enable users to select computational pipelines and parameters for routine analysis of phosphoproteomics data and will offer guidance for developers to improve computational methods.

59 BASIC BIOLOGICAL SCIENCES↗

Evaluation of sequence tracking methods for Compton cameras based on CdZnTe arrays

In this study, the performance of sequence tracking methods for multiple interaction events in specific CdZnTe Compton imagers was evaluated using Monte Carlo simulations. The Compton imager consisted of a 6 × 6 array of virtual Frisch-grid CZT crystals, where the dimensions of each crystal were 5 × 5 × 12 mm 3 . The sequence tracking methods for another Compton imager that consists of two identical CZT crystals arrays were also evaluated. When 662 keV radiation was incident on the detectors, the percentages of the correct sequences determined by the simple comparison and deterministic methods for two sequential interactions were identical (~80 %), while those evaluated using the minimum squared difference method (55-59 %) and Three Compton method (45-55 %) for three sequential interactions, differed from each other. The reconstructed images of a 662 keV point source detected using single and double arrays were evaluated based on their angular resolution and signal-to-noise ratio, and the results showed that the double arrays outperformed single arrays.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Development and demonstration of a methodology to evaluate high burnup fuel susceptibility to pulverization under a loss of coolant transient

For economic reasons, the US nuclear industry is renewing efforts to build a technical basis to extend rod average burnup limits above the current regulatory burnup limit of 62 GWd/MTU. The primary driver is to increase pressurized water reactor cycle lengths to 24 months, reducing the number of fresh fuel assemblies and core design constraints, thereby making core energy utilization more efficient. However, fuel pellet fragmentation and pulverization, termed high burnup fuel fragmentation (HBFF), has been observed in the high burnup (>90 GWd/MTU) Halden loss-of-coolant-accident (LOCA) integral test series. The issue gained attention when fuel fragmentation and pulverization were also observed closer to the current US regulatory limit during the US Nuclear Regulatory Commission (NRC) sponsored out-of-core integral test at Studsvik Nuclear in early 2011. This led to NRC concerns with potential changes to fuel and core designs relative to fuel pellet pulverization. In a letter to the NRC Commissioners, the staff specifically identified a need to “…define the boundary of safe operation for key fuel design and operating parameters,” stating that “the staff is challenged to evaluate the acceptability of future fuel design advancements and fuel utilization changes.” As such, it can be concluded that HBFF and potential dispersal into the reactor coolant system introduces additional complications in light-water reactor (LWR) fuel safety evaluations. However, it is not clear how much fuel will be susceptible to HBFF; nor has there been a methodology developed to evaluate fuel susceptibility to HBFF. To that end, this paper proposes an analysis methodology to assess fuel susceptibility to HBFF during LOCA scenarios. The work presented here uses the BISON fuel performance code to evaluate a representative pressurized water reactor fuel rod exposed to a rod average burnup of 75 GWd/MTU. Sensitivity studies investigated the impact of the peak cladding temperature, transient fission gas released, and pre-transient fission gas release on cladding ballooning and burst timing. Subsequently, a methodology to assess fuel susceptibility to HBFF will be developed based on experimental data published in the open literature. The methodology will then be demonstrated by calculating the mass of fuel susceptibility to HBFF. The BISON results conclude that increasing peak cladding temperature drastically decreased time to failure, and decreased balloon size both of which have been confirmed experimentally. Additionally, the effect of pre-transient and transient fission gas release affected cladding balloon size and burst timing. Finally, fuel susceptibility to HBFF significantly decreased as a function of peak cladding temperature.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Evaluation of RANS vs. LES simulation of fluid flow through 3 × 3 rod bundle with a simple spacer grid as a precursor to coupled fluid–structure interaction simulations

The research literature on Computational Fluid Dynamics (CFD) of coolant flow through rod bundles with spacer-grids and mixing vanes is replete, ranging from high fidelity Large Eddy Simulation (LES)/Direct Numerical Simulation (DNS) simulations to Reynolds-Averaged Navier–Stokes (RANS) modeled studies. The mixing of flow between subchannels and the pressure drop through the bundle are fundamental quantities useful for comparing and evaluating CFD methods. Less commonly observed and compared are the forces exerted onto the structure by the fluid. The present study seeks to evaluate the use of RANS simulations for predicting the structural response to fluid flow. Wall resolved RANS simulations are benchmarked against LES simulations of fluid flow at a Reynolds number of 15,000 through a 3 × 3 fuel rod bundle with a simple spacer grid. Velocity line-plots are compared showing good agreement between RANS and LES results, ascertaining that the former is capable of capturing the essential time-averaged velocity profile. Additionally, the distribution of forces on the spacer grid and fuel rods are collected as a function of time and space. The RANS methods are evaluated using the frequency and magnitude of the fluctuating forces on various portions of the structure as compared to LES. In conclusion, the power spectral density evaluation of the models reveal underprediction of force amplitude on the rod walls by RANS and also discrepancy in the prediction of high frequency spectra, especially in the immediate vicinity of spacer-grid structure, which may be attributed to the lack of random turbulence fluctuation or insufficient modeling of small-scale eddies in RANS simulation.

FIV↗

A Modified Vegetation Photosynthesis and Respiration Model (VPRM) for the Eastern USA and Canada, Evaluated With Comparison to Atmospheric Observations and Other Biospheric Models

Atmospheric CO 2 measurements from a dense surface network can help to evaluate terrestrial biosphere model (TBM) simulations of Net Ecosystem Exchange (NEE) with two key benefits. First, gridded CO 2 flux estimates can be evaluated over regional scales, not possible using flux tower observations at discrete locations for model evaluation. Second, TBM ability to explain atmospheric CO 2 fluctuations due to the biosphere can be directly tested, an important objective for anthropogenic emissions monitoring using atmospheric observations. Here, we customize the Vegetation Photosynthesis and Respiration Model (VPRM) for an eastern North American domain with strong biological activity upwind of urban areas. Parameters are optimized using flux tower observations from a historical database with sites in (and near) the domain. In addition, the respiration model (originally a linear function of temperature) is modified to account for impacts of changing foliage, non-linear temperature, and water stress. Flux estimates from VPRM, the Carnegie-Ames-Stanford Approach (CASA) model and the Simple Biosphere Model v4 (SiB4), are convolved with footprints from atmospheric transport models for evaluation with CO 2 observations at 21 towers in the domain, with roughly half of the towers used here for the first time. Results show that the new respiration model in VPRM helps to correct a growing season sink bias in the atmosphere associated with underestimated summertime respiration using the original model with annual parameters. The new VPRM also better explains fine-scale atmospheric CO 2 variability compared to other TBMs, due to higher resolution diagnostic phenology, the new respiration model, domain-specific parameters, and high-quality input data sets.

54 ENVIRONMENTAL SCIENCES↗

Implementation and Evaluation of Emission‐Driven Land‐Atmosphere Coupled Simulation in E3SMv2.1

Emissions-driven (prognostic CO 2 ) simulations are essential for representing two-way carbon-climate feedback in Earth System Models. We present an emissions-driven land–atmosphere coupled biogeochemistry (BGC) configuration (BGCLNDATM_progCO2) in version 2.1 of the Energy Exascale Earth System Model (E3SMv2.1). This is the first E3SM configuration that performs land-atmosphere emission-hindcasts. Here, we document its implementation, evaluate the model's performance against observations and other models, and propose a structured evaluation protocol for such emissions-driven simulations. We conducted transient historical simulations (1850–2014) with BGCLNDATM_progCO2 and compare them to reference simulations—a land-atmosphere coupled simulation without BGC and a standalone land simulation with BGC, both using prescribed CO 2 concentrations—and to observations. BGCLNDATM_progCO2 overestimates atmospheric CO 2 concentrations by 11–23 ppm yet stays within the 40-ppm spread CMIP6 emission-driven models and retains physical climate properties comparable to the reference runs. The CO 2 biases are partly attributed to underrepresented oceanic CO 2 uptake and inadequate representations of some terrestrial processes. In general, introducing prognostic CO 2 did not change physical climate metrics at the global scale but had larger regional effects, particularly over land where spatially heterogeneous CO 2 and prognostic leaf area index influenced surface energy balance. Finally, we propose a general evaluation protocol including spin-up assessment, atmospheric CO 2 benchmarking, physical climate evaluation, and land biogeochemical analysis to support scientific rigor and facilitate inter-model comparisons. The new configuration lays the groundwork for future enhancements, including improved terrestrial biogeochemical processes, integrated marine biogeochemistry, and additional human–Earth system interactions. These developments advance E3SM toward fully coupled emissions-driven simulations, enabling more accurate carbon–climate feedback projections and informing mitigation policy by providing physically consistent carbon-budget metrics for mitigation scenarios.

54 ENVIRONMENTAL SCIENCES↗

International network of nuclear structure and decay data evaluators

Compilation, evaluation and dissemination of nuclear data are arduous tasks that rely on contributions from experts in both the basic and applied sciences communities whose efforts are coordinated by the International Atomic Energy Agency (IAEA). The Evaluated Nuclear Structure Data File (ENSDF) includes the most extensive and comprehensive set of nuclear structure and decay data evaluations performed by the international network of Nuclear Structure and Decay Data evaluators (NSDD) under the auspices of the IAEA. In this report we describe the recent NSDD activities supported by the IAEA and provide some future perspectives.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Experimental spectrum averaged cross sections (SACS) in 252 Cf(sf) neutron field and its impact on the evaluation of neutron standards

A new evaluation of spectrum averaged cross sections (SACS) of 235 U, 238 U, and 239 Pu measured in the 252 Cf(sf) reference neutron field is presented and found to be consistent with the original Mannhart SACS evaluation in IRDF-2002. The comprehensive vetted experimental database that includes SACS ratio and absolute SACS measurements of major actinides is being used to update the SACS database employed as input of the new GMApy code to derive the Neutron Standards. An update of the current neutron standards based on Time Projection Chamber (TPC) shape data, a new comprehensive uncertainty quantification, and revised SACS experimental database is proposed which result in a 0.7% increase of the evaluated 239 Pu(n,f)/ 235 U(n,f) crosssection ratio in the 1–5 MeV energy region. The increase is due to a 0.3% reduction of the standard 235 U(n,f) cross section and a 0.4% increase of the 239 Pu(n,f) reference cross section in the 1–5 MeV energy region. Those changes are well within estimated USU fission cross-section uncertainties of 1.2%, but are relevant for the evaluated mean values.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Experimental Validation of Thermal Scattering Evaluations

In order to test the performance of new neutron thermal scattering law (TSL) evaluations it is desirable to have experimental data that is highly sensitive to the TSL and provides high fidelity information on the energy dependent performance of TSL evaluations. Three relevant experiments are discussed including: accurate thermal total cross section measurements, thermal neutron die-away experiments, and neutron leakage experiments. The experimental setups and results are reviewed, and examples provided for some moderators including polyethylene, Plexiglas, and YHx. For the experiments preformed thus far, there is generally good agreement between the measured total cross section and simulations using current TSL evaluations, however in certain energy ranges differences were observed. Similarly, neutron die-away and leakage measurements for samples at room temperature are in good agreement with data computed from TSLs, however leakage measurements for polyethylene at 29K show discrepancies with TSL evaluations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Evaluation of the Abel inversion integral in O-mode plasma reflectometry using Chebyshev–Gauss quadrature

The Abel transform is often used to reconstruct plasma density profiles from O-Mode polarized reflectometry diagnostics. However, standard numerical trapezoidal evaluation of the Abel inversion integral can be computationally expensive for a large number of evaluation points, and an endpoint singularity exists on the upper-bound of the integral, which can result in an increased error. In this work, Chebyshev–Gauss quadrature is introduced as a new method to evaluate the Abel inversion integral for the problem of O-Mode plasma reflectometry. Here, the method does not require numerical evaluation of an integral singularity and is shown to have similar accuracy compared to existing methods while being computationally efficient.

47 OTHER INSTRUMENTATION↗

New Measurements to Resolve Discrepancies in Evaluated Model Parameters of 181 Ta

To resolve discrepancies in evaluated cross sections among major nuclear data libraries, energy-differential neutron transmission and radiative capture yield of 181 Ta were measured from 0.15 to 100 keV using multiple sample thicknesses. The new measurements provide resolution such that the resolved resonance region (RRR) can be evaluated up to at least 2.5 keV and the unresolved resonance region can be evaluated up to at least 100 keV. The transmission and capture yield measurements were modeled using resonance parameters from three major libraries to assess the predictive capability of each. It was found that JENDL-5.0 performed best in the RRR. Because of the poor performance of the U.S. ENDF/B evaluation, it is recommended that ENDF/B be reevaluated for 181 Ta.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗