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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Assessment of Spatiotemporal Variability of Evapotranspiration and Its Governing Factors in a Mountainous Watershed at the East River, Colorado, Water: Dataset

This data package contains simulation results of daily evapotranspiration for 17 locations of meteorological stations with different precipitation, air temperature and vegetation within the East River Watershed, Colorado (CLMResult.csv). Daily precipitation data is included for reference. These are the main results of the paper Tran, 2019. Meteorological stations names, latitude and longitude coordinates of meteorological stations, types of lands from the National Land Cover Database, and a comparison with the community land model (CLM) data are also included (Met_LC.csv). The purpose of this data is to analyze the spatio-temporal variations of evapotranspiration at the East River Watershed and understand the factors that control these variations. More information regarding the study, methods, and findings can be found in the Related Reference paper.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A Strengthened Teleconnection of the Quasi‐Biennial Oscillation and Tropical Easterly Jet in the Past Decades in E3SMv1

The Energy Exascale Earth System Model version 1 (E3SMv1) is a new global model that can generate a weakened tropical easterly jet (TEJ) during the easterly quasi-biennial oscillation (EQBO) and a strengthened TEJ during the westerly QBO (WQBO), which is referred to as the QBO-TEJ teleconnection. Although the longitudinal structure of the QBO-TEJ teleconnection is different between reanalysis and simulations, we hypothesize that simulations can still provide insights into the observed long-term changes in the QBO-TEJ teleconnection. The Atmospheric Model Intercomparison Project historical simulations (AMIP-historical) generate a strengthened trend in the correlation between the QBO and TEJ indices in the period of 1950–2014 as in reanalysis. The comparison of the AMIP-historical and the Coupled Model Intercomparison Project coupled historical simulations (coupled-historical) shows that the warming of the Indian Ocean has played a vital role in the strengthened QBO-TEJ teleconnection over the past six decades.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

kynema-fmb [SWR-23-07]

Kynema-FMB (FKA: Kynema) is an open-source performance portable flexible multibody (FMB) dynamics solver designed for time-domain simulations. While originally tailored for wind turbine structural dynamics, the formulation and implementation are those of a general flexible-multidbody dynamics solver that can readily be applied to a wide range of systems. Kynema was designed with a narrow focus, namely to provide a lightweight, fast, accurate FMD solver for coupling to computational-fluid-dynamics (CFD) codes, especially the CFD codes in the Kynema suite, for fluid-structure-interaction (FSI) simulations. Kynema-FMB is equipped to model systems that can be represented as a collection of beams and rigid bodies that are connected through constraints. Degrees of freedom are defined in the inertial/global frame of reference and include displacements and rotations (formally as rotation matrices, but stored as quaternions). The underlying formulation is built on a Lie-group time integrator designed for index-3 differential-algebraic equations, which is second-order accurate in time (Bruls et al., 2012). Beam models are based on geometrically exact beam theory and are discretized as high-order spectral finite elements similar to those in BeamDyn (Wang et al., 2017). The governing equations for a FMD system like a wind turbine constitute a highly nonlinear system of constrained partial-differential equations. Kynema-FMB uses analytical Jacobians in the nonlinear-system solves in each time step. Linear systems use sparse storage and several third-party sparse-linear-system solvers are enabled. Ill conditioning of linear systems is mitigated with preconditioning described in Bottasso et al, 2008. Kynema-FMB is integrated with a simple open-source controller (ROSCO). There is an application programming interface (API) for coupling to geometry-resolved CFD (like that in Sharma et al., 2023) and actuator-force CFD (like that in Kuhn et al., 2025). In the latter, for actuator-line models, Kynema-FMB includes an internal blade-element solver that depends on user-provided lookup tables for coefficients of lift and drag, i.e., aerodynamic polars. Kynema-FMB is written in C++ and leverages Kokkos and Kokkos-Kernels (KokkosEcosystem) as its performance portability layer enabling simulations on both CPU and GPU systems. The repository is equipped with extensive automated testing at the unit and regression/system levels. The following describes the high-level development objectives conceived for Kynema: *Kynema will follow modern software development best practices, including test-driven development (TDD), version control, hierarchical automated testing, and continuous integration (CI) for a robust development environment. *The core data structures are memory efficient and enable vectorization and parallelization at multiple levels. *Data structures are data-oriented to exploit methods for accelerated computing including high utilization of chip resources (e.g., single instruction multiple data (SIMD) instruction sets) and parallelization using GP-GPUs. *The computational algorithms incorporate robust open-source libraries for mathematical operations, resource allocation, and data management. *The API design considers multiple stakeholder needs and ensure integration with existing and future ecosystems for data science, machine learning, and AI. *Kynema-FMB is written in modern C++ and leverages Kokkos as its performance-portability library with inspiration from the kynema stack.

Sprague, MichaelA.↗
DOE OSTI2026

Reductions in wind farm main bearing rating lives resulting from wake impingement

This paper studies the impacts of wake impingement on main bearing rating lives predicted during the wind turbine design stage. A computational tool chain was developed to explore and quantify these effects across a wind farm populated by 10 MW wind turbines. Wind field and turbine load modelling was undertaken using the Dynamiks Python package, including application of a dynamic wake meandering model. The ISO 281 basic bearing rating life formulation was subsequently applied in order to evaluate impacts from wake effects. Analyses included a two-turbine parametric analysis, followed by a full wind farm analysis undertaken for the TotalControl 32-turbine reference wind farm, including full wind rose simulations across all operational wind speeds. Site conditions were accounted for using a Weibull wind speed distribution and a range of parametric wind direction rose models. Results indicate that wind farm main bearing rating lives are negatively impacted by the effects of wake impingement, resulting in rating life reductions for the analysed wind farm of the order of 16 % on average and as much as 20 %–25 %, both for the locating main bearing. Despite these high sensitivities, it is important to note that these resultant rating lives (i.e. the predicted lives) still far exceed the standard wind turbine operational lifetimes of 20–30 years. Wake impacts were also found to be asymmetrically related to the side on which the rotor is impinged, suggesting that, for the main bearing, there may be a “better” side for wake impingement to occur. Rating life sensitivities to wind rose shape were also observed. While these findings must be interpreted with due consideration for the various methodological limitations present, they provide compelling evidence that wake effects at the wind farm level should necessarily be included when undertaking main bearing operational load modelling, rating life assessment, or other load-related analyses.

17 WIND ENERGY↗
DOE OSTI2022

Abundance and Migration Success of Overshoot Steelhead in the Upper Columbia River

Abstract Summer steelhead Oncorhynchus mykiss may enter freshwater almost a year before spawning and potentially make long migrations (>1,000 km) to interior headwater habitats. However, in response to suboptimal freshwater habitat conditions (e.g., warmer water temperatures), adult summer steelhead may exhibit complex behaviors during upstream migration in the Columbia River basin. Steelhead may migrate upstream of their natal tributary (hereafter, referred to as “overshoot”) and spend days to several months before subsequently migrating downstream (hereafter, referred to as “fallback”) to their natal tributary to spawn. An expansion of an existing Bayesian patch occupancy model, derived from observations of adult steelhead that were PIT-tagged to estimate population-specific abundance upstream of the tagging location, incorporated downstream detection locations to estimate the abundance of overshoot fallbacks. Overshoot steelhead abundance at the tagging location was estimated based on the relationship between the number of known overshoot fallbacks (i.e., the number of steelhead that overshot and successfully migrated downstream to their natal tributary) and their model-estimated abundance. During the study period (2010–2017), the annual mean proportion of overshoot steelhead that successfully migrated downstream of the tagging location (Priest Rapids Dam) was 0.59 (SD = 0.14). The number of dams encountered by overshoot steelhead during their downstream migration was negatively correlated with their downstream migration success probability. Improved downstream passage survival for adult steelhead will increase the abundance of affected populations while reducing potential genetic introgression of upstream populations (i.e., strays). This is the first study to estimate the abundance of overshoot and fallback steelhead, providing the data necessary for scientists to estimate potential conservation benefits of improved downstream survival. For example, surface flow passage routes (e.g., sluiceways and temporary spillway weirs) are very effective in guiding and passing adult steelhead downstream of Columbia River hydroelectric projects and data from this assessment show that changes in dam operations throughout the downstream migration period may maximize conservation benefits.

Murdoch, Andrew R. (ORCID:0000000324827689)↗
DOE OSTI2020

Bounded motion design in the Earth zonal problem using differential algebra based normal form methods

Establishing long-term relative bounded motion between orbits in perturbed dynamics is a key challenge in astrodynamics to enable cluster flight with minimum propellant expenditure. Herein, we present an approach that allows for the design of long-term relative bounded motion considering a zonal gravitational model. Entire sets of orbits are obtained via high-order Taylor expansions of Poincarè return maps about reference fixed points. The high-order normal form algorithm is used to determine a change in expansion variables of the map into normal form space, in which the phase space behavior is circular and can be easily parameterized by action–angle coordinates. The action–angle representation of the normal form coordinates is then used to parameterize the original Poincarè return map and average it over a full phase space revolution by a path integral along the angle parameterization. As a result, the averaged nodal period and drift in the ascending node are obtained, for which the bounded motion conditions are straightforwardly imposed. Sets of highly accurate bounded orbits are obtained, extending over several thousand kilometers, and valid for decades.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Subtleties in the trainability of quantum machine learning models

A new paradigm for data science has emerged, with quantum data, quantum models, and quantum computational devices. This field, called quantum machine learning (QML), aims to achieve a speedup over traditional machine learning for data analysis. However, its success usually hinges on efficiently training the parameters in quantum neural networks, and the field of QML is still lacking theoretical scaling results for their trainability. Some trainability results have been proven for a closely related field called variational quantum algorithms (VQAs). While both fields involve training a parametrized quantum circuit, there are crucial differences that make the results for one setting not readily applicable to the other. In this work, we bridge the two frameworks and show that gradient scaling results for VQAs can also be applied to study the gradient scaling of QML models. Our results indicate that features deemed detrimental for VQA trainability can also lead to issues such as barren plateaus in QML. Consequently, our work has implications for several QML proposals in the literature. In addition, we provide theoretical and numerical evidence that QML models exhibit further trainability issues not present in VQAs, arising from the use of a training dataset. We refer to these as dataset-induced barren plateaus. These results are most relevant when dealing with classical data, as here the choice of embedding scheme (i.e., the map between classical data and quantum states) can greatly affect the gradient scaling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Non-dimensional performance and safety parameters for heat pipes

The use of heat pipes in safety-critical systems such as nuclear microreactors dictates the development of generalized, practical, scalable performance and safety parameters. Traditional dimensional metrics, while informative, lack the universality required for comparative analysis across varying designs and operating regimes. Here, this work introduces a comprehensive set of non-dimensional parameters to characterize heat pipe performance and safety, including capillary performance, effective thermal conductivity, response time, exergetic efficiency, allowable temperature gradients, allowable rate of temperature change, priming coefficients, and factor of safety. A reference heat pipe design representative of microreactor applications was analyzed via the developed parameters using both traditional analytical models and Sockeye simulations under transient and steady-state conditions. Sodium, potassium, and water were evaluated as working fluids to demonstrate the applicability of the framework across a broad temperature range. The proposed non-dimensional parameters effectively captured key thermal-hydraulic behaviors and safety concerns, as was demonstrated via Sockeye simulations. This framework supports the development of design optimization strategies, operational protocols, and safety assurance practices for advanced reactor systems and other high-reliability applications.

42 - ENGINEERING↗
DOE OSTI2025

Non-destructive electrochemical diagnosis of failure mechanisms in aqueous zinc batteries

The early detection of secondary reactions that affect the life and performance of zinc manganese oxide batteries requires a shift from conventional time-consuming and often destructive procedures to rapid lifetime-predictive techniques. In this work, an electrochemical approach is employed to elucidate independent signatures for four common types of failure mechanisms in zinc manganese dioxide (Zn||MnO2) batteries—namely, the loss of zinc inventory, the loss of active material at the cathode, electrolyte depletion, and increased cell impedance. Our findings, specific to coin cell configurations, reveal that each induced failure mechanism can be distinctively modeled and identified based on responses from the rest voltage and columbic-efficiency data for prompt detection. For instance, electrolyte depletion response manifests a distinctive abrupt (>80 %) decrease in columbic efficiency (CE) and charge-rest voltage (Vc) while the discharge-rest voltage remained constant at ~1.3 V. Furthermore, electrolyte rejuvenation of the cell increased the CE to >95 % and restored Vc from ~0.3 to >1.7 V. Recovery experiments and reference performance tests demonstrated consistency between electrochemical descriptors and their associated failure mechanisms. Further, the outcomes of this work provide valuable insights and data models for some of the dominant failure mechanisms present in zinc manganese battery chemistries, which are beneficial to accelerated early-lifetime diagnosis and advancement of Zn batteries development.

25 ENERGY STORAGE↗
DOE OSTI2023

In-depth analysis on parallel processing patterns for high-performance Dataframes

The Data Science domain has expanded monumentally in both research and industry communities during the past decade, predominantly owing to the Big Data revolution. Artificial Intelligence (AI) and Machine Learning (ML) are bringing more complexities to data engineering applications, which are now integrated into data processing pipelines to process terabytes of data. Typically, a significant amount of time is spent on data preprocessing in these pipelines, and hence improving its efficiency directly impacts the overall pipeline performance. The community has recently embraced the concept of Dataframes as the de-facto data structure for data representation and manipulation. However, the most widely used serial Dataframes today (R, pandas) experience performance limitations while working on even moderately large data sets. We believe that there is plenty of room for improvement by taking a look at this problem from a high-performance computing point of view. In a prior publication, we presented a set of parallel processing patterns for distributed dataframe operators and the reference runtime implementation, Cylon. In this paper, we are expanding on the initial concept by introducing a cost model for evaluating the said patterns. Furthermore, we evaluate the performance of Cylon on the ORNL Summit supercomputer.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Characterization of a novel HIV-1 circulating recombinant form, CRF91_cpx, comprising CRF02_AG, G, J, and U, mostly among men who have sex with men

Prospective molecular studies of HIV-1 pol region (2253–5250 in HXB2 genome) sequences from sequenced samples of 269 HIV-1-infected patients in Cyprus (2017–2021) revealed a transmission cluster of 14 unknown HIV-1 recombinants that were not classified as previously established CRFs. The earliest recombinant was collected in September 2017, and the transmission cluster continued to grow until November 2020. Near full-length HIV-1 genome sequences of the 11 of the 14 recombinants were successfully obtained (790–8795 in HXB2 genome) and aligned against a reference dataset of HIV-1 subtypes and CRFs. We employed MEGAX for maximum-likelihood tree construction (GTR model, 1000 bootstrap replicates), Cluster-Picker for phylogenetic clustering analysis (genetic distance ≤0.045, bootstrap support value ≥70%), and REGA-3.0 for subtype determination. Bootscan and similarity plot analyses (sliding window of 400 nucleotides overlapped by 40 nucleotides) were conducted using SimPlot-v3.5.1, and subregion confirmatory neighbour-joining tree analyses were conducted using MEGAX (Kimura two-parameter model, 1000 bootstrap replicates, ≥70% bootstrap-support value). Exclusive clustering of the HIV-1 recombinants revealed their uniqueness. The recombination analyses illustrated the same unique mosaic pattern with six putative intersubtype recombination breakpoints, seven fragments of subtypes CRF02_AG, G, J and an unclassified fragment. We conclusively characterized the mosaic structure of the novel HIV-1 CRF, named CRF91_cpx, by the Los Alamos HIV Sequence Database. Additionally, we identified a URF of CRF91_cpx with two additional recombination sites, generated by a recombination event between subtype B and CRF91_cpx. Since the identification of CRF91_cpx, two additional patient samples have been entered into the CRF91_cpx transmission cluster, demonstrating active growth.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Modeling the Metabolic Costs of Heavy Military Backpacking

Existing predictive equations underestimate the metabolic costs of heavy military load carriage. Metabolic costs are specific to each type of military equipment, and backpack loads often impose the most sustained burden on the dismounted warfighter. This study aimed to develop and validate an equation for estimating metabolic rates during heavy backpacking for the US Army Load Carriage Decision Aid (LCDA), an integrated software mission planning tool. Thirty healthy, active military-age adults (3 women, 27 men; age, 25 ± 7 yr; height, 1.74 ± 0.07 m; body mass, 77 ± 15 kg) walked for 6–21 min while carrying backpacks loaded up to 66% body mass at speeds between 0.45 and 1.97 m·s -1 . A new predictive model, the LCDA backpacking equation, was developed on metabolic rate data calculated from indirect calorimetry. Model estimation performance was evaluated internally by k-fold cross-validation and externally against seven historical reference data sets. We tested if the 90% confidence interval of the mean paired difference was within equivalence limits equal to 10% of the measured metabolic rate. Estimation accuracy and level of agreement were also evaluated by the bias and concordance correlation coefficient (CCC), respectively. Estimates from the LCDA backpacking equation were statistically equivalent ( P < 0.01) to metabolic rates measured in the current study (bias, -0.01 ± 0.62 W·kg -1 ; CCC, 0.965) and from the seven independent data sets (bias, -0.08 ± 0.59 W·kg -1 ; CCC, 0.926). The newly derived LCDA backpacking equation provides close estimates of steady-state metabolic energy expenditure during heavy load carriage. These advances enable further optimization of thermal-work strain monitoring, sports nutrition, and hydration strategies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Small Reactors in Microgrids: Technoeconomic Analysis

This report presents the results of technoeconomic analysis that advances understanding of the potential of small modular reactors and microreactors, collectively referred to as small reactors (SRs) in this report, in microgrids. This analysis was conducted using a proxy model for SR in microgrids based on the datapoints that were identified and explored in a predecessor report “Small Reactors in Microgrids: Technical Studies Guidance.” The results and the subsequent comparative analysis in this report show that SRs could be a cost-competitive generation option when capital costs are modeled considering potential economies of scale in sizing. If the CO 2 tax is imposed on carbon fuels, SRs would be even more attractive than gas generators. Then, SRs in microgrids would play a pivotal role in reducing the carbon footprint at the local distribution level. However, it is particularly important to identify the most suitable use cases for early adoption and the right balance of generation mix with other clean technologies as SRs achieve a level of technological and financial maturity.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

DL-TODA: A Deep Learning Tool for Omics Data Analysis

Metagenomics is a technique for genome-wide profiling of microbiomes; this technique generates billions of DNA sequences called reads. Given the multiplication of metagenomic projects, computational tools are necessary to enable the efficient and accurate classification of metagenomic reads without needing to construct a reference database. The program DL-TODA presented here aims to classify metagenomic reads using a deep learning model trained on over 3000 bacterial species. A convolutional neural network architecture originally designed for computer vision was applied for the modeling of species-specific features. Using synthetic testing data simulated with 2454 genomes from 639 species, DL-TODA was shown to classify nearly 75% of the reads with high confidence. The classification accuracy of DL-TODA was over 0.98 at taxonomic ranks above the genus level, making it comparable with Kraken2 and Centrifuge, two state-of-the-art taxonomic classification tools. DL-TODA also achieved an accuracy of 0.97 at the species level, which is higher than 0.93 by Kraken2 and 0.85 by Centrifuge on the same test set. Application of DL-TODA to the human oral and cropland soil metagenomes further demonstrated its use in analyzing microbiomes from diverse environments. Compared to Centrifuge and Kraken2, DL-TODA predicted distinct relative abundance rankings and is less biased toward a single taxon.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Reconnaissance with JWST of the J-region Asymptotic Giant Branch in Distance Ladder Galaxies: From Irregular Luminosity Functions to Approximation of the Hubble Constant

Abstract We study stars in the J-regions of the asymptotic giant branch (JAGB) of near-infrared color–magnitude diagrams in the maser host NGC 4258 and four hosts of six Type Ia supernovae (SNe Ia): NGC 1448, NGC 1559, NGC 5584, and NGC 5643. These clumps of stars are readily apparent near 1.0 < F150W − F277W < 1.5 andm F150W = 22–25 mag with James Webb Space Telescope NIRCam photometry. Various methods have been proposed to assign an apparent reference magnitude to this recently proposed standard candle, including the mode, median, sigma-clipped mean, or a modeled luminosity function parameter. We test the consistency of these by measuring intrahost variations, finding differences of up to ∼0.2 mag that significantly exceed statistical uncertainties. Brightness differences appear intrinsic, and are further amplified by the nonuniform shape of the JAGB luminosity function, also apparent in the LMC and SMC. We follow a “many methods” approach to measure consistently JAGB magnitudes and distance moduli to the SN Ia host sample calibrated by NGC 4258. We find broad agreement with distance moduli measured from Cepheids, tip of the red giant branch, and Miras. However, the SN host mean distance modulus estimated via the JAGB method necessary to estimateH 0 differs by ∼0.19 mag among the above definitions, the result of different levels of luminosity function asymmetry. The methods yield a full range of 71−78 km s −1 Mpc −1 , i.e., a fiducial result ofH 0 = 74.7 ± 2.1(stat) ± 2.3(sys, ±3.1 if combined in quadrature) km s −1 Mpc −1 , with systematic errors limited by the differences in methods. Future work may seek to standardize and refine this promising tool further, making it more competitive with established distance indicators.

Astronomy & Astrophysics↗
DOE OSTI2024

Dynamic Wind Loading on CSP Collectors Caused by Turbulent Wind Fluctuations: Insights from a 2-Year Field Campaign

Concentrating Solar Power (CSP) is a promising solar technology for electricity generation with thermal energy storage and with the additional benefit of industrial heat production. Wind loading on CSP collector structures, such as parabolic troughs or heliostats, is one of the primary drivers of their structural design costs. In particular, dynamic wind loading is a major source of uncertainty in the collector design process, which heavily relies on wind tunnel testing. In the field, the turbulent nature of the incoming wind creates fluctuating loads (support structure loads and resulting mirror deflections) on the collectors, with impacts on fatigue lifetime and optical performance. As is well known, wind tunnel tests cannot entirely reproduce the complex turbulent wind conditions typically observed at full-scale plants. To shed light on this topic, NREL initiated a field campaign at the operational Nevada Solar One (NSO) powerplant that uses parabolic troughs as solar collectors. The aim of the project is a detailed characterization of prevailing wind and turbulence conditions and resulting operational loads on parabolic troughs. We use the published 2-year dataset of high-resolution combined wind and structural loads measurements [1] to characterize the dynamic structural wind response. For quantifying dynamic wind loading, we apply the concept of admittance functions, which are spectral transfer functions that couple the turbulent wind to resulting structural loads (aerodynamic admittance), and to the structural response (mechanical admittance). In practice, aerodynamic admittance describes which turbulent eddy sizes are effective in creating structural loads. The mechanical admittance describes in which frequency ranges these loads are reinforced or dampened by the structure. While these functions are an established concept in civil engineering, their recent application to a single full-scale heliostat [2] proved their broader applicability to CSP collectors. Here, we present a characterization of admittance functions for full-scale parabolic trough collectors and show how wind characteristics (mean wind speed and direction, turbulent kinetic energy, turbulent length scales), the sun-tracking trough angle, and row position alter the admittance functions. Further, we study to which extent the admittance functions are universal for a specific trough geometry and how our findings compare to reported heliostat results. References [1] https://data.openei.org/submissions/5938. [2] Blume, K., Roger, M., and Pitz-Paal, R. 2023b. "Simplified analytical model to describe wind loads and wind-induced tracking deviations of heliostats." Solar Energy, 256, 96-109. https://doi.org/10.1016/j.solener.2023.03.055.

admittance functions↗
DOE OSTI2024

Progress toward the development of a high-fidelity neutronic \model of MARVEL using Griffin

The Microreactor Applications Research Validation and Evaluation (MARVEL) is a 100 kWth microreactor envisioned to start operations at Idaho National Laboratory (INL) in early 2025. This paper is focused on the development of a high-fidelity neutronic model of the MARVEL reactor using Griffin. In particular, the step-by-step verification procedure against Serpent reference calculations is here reported. In this version of the paper, the comparison is only performed in terms of effective multiplication factor, root mean square percentage error (RMSPE) of the pin power, and maximum error for pin-wise power.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗