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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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This is a presentation about the modeling receiver flux of commercial power tower concentrating solar power plants by using ray tracing. This comparison study is ongoing, and this presentation shares about the journey in this process so far.
A diffusion-based and a discrete ordinates method are used to simulate a neutron noise experiment in the research reactor AKR-2 at the Technical University in Dresden, Germany. The AKR-2 reactor provides an interesting case for the comparison between the two methods because it is characterized by large heterogeneities and regions with low macroscopic neutron cross-sections. For the calculations, the same spatial discretization and the same set of two-energy macroscopic neutron cross-sections with isotropic scattering are used. Significant discrepancies between the diffusion-based and discrete ordinates methods are found in regions of the systems where the diffusion approximation is expected to be inaccurate in reproducing characteristics of the static neutron flux and neutron noise. (authors)
This work will compare the Allen method and Walker method of accounting for subhourly inverter clipping power losses in hourly PV performance models. The Allen method uses a matrix lookup based on DNI clearness and clipping potential to assign a clipping correction loss at each simulation timestep. The Walker method models the PV DC power input to the inverter as a distribution over the hourly timestep and uses integration over the timestep to determine the amount of clipping that occurs within the timestep. Both these models have been recently implemented in the System Advisor Model's (SAM) open-source code, and will be applied to hourly SURFRAD datasets to analyze the subhourly clipping loss predicted by each model for different system designs and inverter loading conditions. Both models will be compared to "true" 1-minute SURFRAD data simulations to see their accuracy against more accurate 1-minute clipping correction loss predictions. This model comparisons will be investigated in more detail at the PVSC conference in Seattle, Washington June 2024.
The investigation of the TRISO coated particles is important in terms of verification the quality of the nuclear fuel samples before placing them in the reactor core. To determine the degree of damage to the coated particles, the samples must be properly polished in order to uncover the inner layers. The poster presents a comparison of two polishing methods. Mechanical polishing method, which is used frequently for sample preparations generates additional mechanical damages in the studied fuel particle, thus directly affecting the experimental results. Due to that, a novel way to polish the samples is presented - an ionic polishing method. Based on the obtained results, it was concluded that the ion polishing method is better because the level of interference with the structures of the individual layers of the tested samples is much lower than with the mechanical method.
Work conducted in FY23 identified that RELAP5-3D was capable of reproducing trends in HTTF data during experiment PG-27 but was incapable of reproducing measured values. The primary cause of this discrepancy between RELAP5-3D results and experimental data was hypothesized to be a distortion in power density that was introduced by the radial nodalization of the model. We further hypothesized that a new model would provide better results when compared to the experiments PG-27 and PG-29. Work this FY developed a new model that is better capable of capturing local heat generation rates and contains a representation of each 1/6 azimuthal sector of the core. We used this model to develop a new set of solutions to Exercises 1 and 2 of Problems 2 and 3 in the benchmark. In this report, we present the first comprehensive comparison of the results between the two models. We see that in Exercise 1A, which is common between problems 2 and 3, the results are similar, though the results from the new model show greater detail than those from the legacy model. In Problem 2 Exercise 1B and Problem 3 Exercise 1B, we see that heat removal is slower in the new model than the legacy model. Problem 3 Exercise 1C shows temperatures that are lower in most places in the new model than the legacy model, but the area with active heat generation has higher block temperatures in the new model than the legacy model. Problem 3 Exercise 1D further shows that long-term heat removal is lower in the new model. Problem 2 Exercise 1C demonstrated that the new model observes higher temperatures in the core regions than the legacy model, justifying the need to preserve the power density in HTTF. The validation of PG-27 and PG-29 also demonstrated the improved temperature agreement in the core regions, particularly with a calibrated model that implements an effective thermal conductivity for the core material. Overall, PG-27 models show reasonable to excellent agreement for steady-state temperatures and minimal to reasonable agreement for transients. PG-29 models showed minimal to insufficient agreement with the data.
This presentation discusses the motivation, preparation, risk mitigation, execution, and results of a full-scale experiment where the rotor of a 1.5 megawatt wind turbine was operated in a downwind configuration. The experiment took place at the National Renewable Energy Laboratory Flatirons Campus in Colorado, USA, and collected conventional loads and power together with acoustic measurements from an array of four microphones. Results from load simulations complement the experiment. Fatigue loads and performance are compared between 410 minutes of downwind operation with 960 minutes of conventional upwind operations. Downwind operations cause an increase in damage equivalent loads in a few load channels. Damage equivalent load of blade root flapwise and edgewise moment and the damage equivalent load of tower base fore aft moment increase between 2% and 20% depending on the wind speed. The comparison in active power is less conclusive, but experimental results show more power in downwind than predicted by simulations. In terms of acoustics, the overall sound pressure levels are similar between upwind and downwind, but downwind worsens the metrics describing amplitude modulation.
Powder metallurgy hot isostatic pressing (PM-HIP) is an advanced manufacturing process that can efficiently produce near net shape parts with high material utilization and uniform microstructures. While the PM-HIP process is used frequently to produce small-scale components, its application to large-scale components is still limited due to inadequate understanding of its complex processes that cause unpredictable post-HIP shape distortions. A computational model can be a cost-effective alternative to exhaustive experimentation required to understand the PM-HIP process fully. Therefore, we present a comparison of plastic and visco-plastic models that are frequently used to model the PM-HIP process. We show that the predictions of powder densification behavior and shape distortions obtained from both the models are similar under most conditions and agree well with experimental observations.
The DUNE near detector LAr-TPC can be moved to different off-axis positions to sample different neutrino fluxes, which in turn will yield different cross section distributions for observables. Several DUNE ND off axis locations were simulated using GENIE and ACHILLES, and generator differences and FSI contributions were examined for various observables. Additionally, the predictions were compared with those of existing experiments, and it is shown that the DUNE ND 20m off axis predictions are similar to that of MicroBooNE for various observables. Finally, the 2p2h interaction mode was simulated for ACHILLES for the first time for ICARUS, and a preliminary comparison is made to MicroBooNE data and simulations from different event generators.
This is my internship project about the comparison of probabilistic risk assessments for light water reactors and advanced reactors.
In assessments of detrimental health risks from exposures to ionising radiation, many forms of risk to dose–response models are available in the literature. The usual practice is to base risk assessment on one specific model and ignore model uncertainty. The analysis illustrated here considers model uncertainty for the outcome all solid cancer incidence, when modelled as a function of colon organ dose, using the most recent publicly available data from the Life Span Study on atomic bomb survivors of Japan. Seven recent publications reporting all solid cancer risk models currently deemed plausible by the scientific community have been included in a model averaging procedure so that the main conclusions do not depend on just one type of model. The models have been estimated with different baselines and presented for males and females at various attained ages and ages at exposure, to obtain specially computed model-averaged Excess Relative Risks (ERR) and Excess Absolute Risks (EAR). Monte Carlo simulated estimation of uncertainty on excess risks was accounted for by applying realisations including correlations in the risk model parameters. Three models were found to weight the model-averaged risks most strongly depending on the baseline and information criteria used for the weighting. Fitting all excess risk models with the same baseline, one model dominates for both information criteria considered in this study. Based on the analysis presented here, it is generally recommended to take model uncertainty into account in future risk analyses.
Long-distance dispersal (LDD) pathogens pose substantial challenges for epidemic control due to their ability to generate new infection foci at great distances. While various modeling approaches have been developed to understand and manage such outbreaks, little work has compared how models of different structures behave under shared conditions. Here, in this study, we compare four structurally distinct epidemiological models — EPIMUL, GEMF, PoPS, and Warwick — each adapted to simulate the spread of wheat stripe rust (WSR), a wind-dispersed LDD pathogen, under identical epidemiological parameters and dispersal kernel. Using data from a controlled field experiment, we evaluate the ability of each model to replicate disease prevalence under nine intervention scenarios that vary in timing and culling area. While the models differ substantially in design — ranging from spatial grid-based to network-based and raster-based frameworks — the shared dispersal kernel allowed for close alignment in their predictions. All models accurately captured general epidemic trends, particularly the strong effect of early intervention on disease suppression. We qualitatively compared their behavioral responses across scenarios and also evaluated an ensemble prediction by averaging across model outputs. Our findings highlight how integrating shared epidemiological components into distinct modeling frameworks can improve consistency and accuracy, while reinforcing the importance of early culling in managing LDD pathogen outbreaks.
We show that electrification of heavy-duty trucks (HDTs) is critical of achieving sustainability and carbon neutrality in road freight. Based on the total cost of ownership and the life-cycle emissions, the study compared the traditional diesel internal combustion engine vehicle technologies with potential electrification options for HDTs in China, including battery electric vehicle, plug-in hybrid electric vehicle, hydrogen fuel cell vehicle, and battery electric catenary vehicle. Scenario and sensitivity analysis were explored the life-cycle effects of these electrification options in China from 2020 to 2040. It is found that green electricity and green hydrogen are the most important factors influencing the life-cycle emissions of CO 2 , NO X , and PM 2.5 for different HDTs’ electrification options. The plug-in hybrid electric vehicle of HDTs has shown good performance in terms of total cost and carbon emissions, mainly due to the reduced battery capacity and the current grid mix in China.
Measurements are presented, alongside corresponding interpretative SOLPS-ITER simulations, of the first MAST-U experiments comparing ohmically heated L-mode fuelling scans in Conventional divertor (CD) and Super-X divertor (SXD) configurations. In experiment, at comparable outer mid-plane separatrix electron density, $n_{e,\textrm{sep,OMP}}$, the maximum lower outer target heat load was found to be a factor 16 $\,\pm\,7$ lower in SXD compared to CD. In simulation, a factor 26.8 reduction was found (slightly higher than the experimental range), suggesting an additional reduction in SXD compared to the factor 9.3 expected from geometric considerations alone. According to the simulations, this additional reduction in the SXD is due to a net radial transport of the energy remaining downstream of the $T_e = 5$ eV location. This energy is carried out of the critical (highest heat load) flux tube by deuterium atoms, demonstrating the importance of a longer legged divertor which provides space for this to occur. Importantly, in both simulation and experiment, the SXD has minimal impact on the upstream n e and T e profiles. Spectral inferences of detachment front movement in SXD compare well between simulation and experiment. In regions of high magnetic field gradient, the parallel movement of the front towards the X-point becomes less sensitive to increasing $n_{e,\textrm{sep,OMP}}$, in qualitative agreement with simplified models and previous predictive simulations. Additional aspects, regarding the target ion flux rollover, upstream separatrix temperature and drift effects, are also presented and discussed.
Reference wind turbines (RWTs) that reflect the state-of-the-art of current wind energy technology are necessary in order to properly evaluate innovative methods in wind turbine design and evaluation. The International Energy Agency (IEA) Wind Technology Collaboration Platform (TCP) Task 37 has recently developed a new RWT geared towards offshore floating-foundation applications: the IEA Wind 15 MW. The model has been implemented in two aeroelastic codes, OpenFAST and HAWC2, based on an underlying common ontology. However, these toolchains result in slightly different structural parameters, and the two codes utilise different structural models. Thus, to increase the utility of the model, it is necessary to compare the aeroelastic responses. This paper compares aeroelastic loads calculated using different fidelities of the blade model in OpenFAST (ElastoDyn and BeamDyn) and HAWC2 (prismatic Timoshenko without torsion and Timoshenko with fully populated stiffness matrix), where both codes use the DTU Basic controller and the same turbulence boxes to reduce discrepancies. The aeroelastic responses to steady wind, step wind and turbulent wind (per IEC 61400-1 wind class IB) are considered. The results indicate a generally good agreement between the loads dominated by aerodynamic thrust and force, especially for the no-torsion blade models. Discrepancies were observed in other load channels, partially due to differences in the asymmetric loading of the rotor and partially due to differing closed-loop dynamics, and they will be the subject of future investigations.
Abstract Advanced microphysics schemes (such as Eulerian bin and Lagrangian superdroplet) are becoming standard tools for cloud physics research and parameterization development. This study compares a double-moment bin scheme and a Lagrangian superdroplet scheme via large-eddy simulations of nonprecipitating and precipitating cumulus congestus clouds. Cloud water mixing ratio in the bin simulations is reduced compared to the Lagrangian simulations in the upper part of the cloud, likely from numerical diffusion, which is absent in the Lagrangian approach. Greater diffusion in the bin simulations is compensated by more secondary droplet activation (activation above cloud base), leading to similar or somewhat higher droplet number concentrations and smaller mean droplet radius than the Lagrangian simulations for the nonprecipitating case. The bin scheme also produces a significantly larger standard deviation of droplet radius than the superdroplet method, likely due to diffusion associated with the vertical advection of bin variables. However, the spectral width in the bin simulations is insensitive to the grid spacing between 50 and 100 m, suggesting other mechanisms may be compensating for diffusion as the grid spacing is modified. For the precipitating case, larger spectral width in the bin simulations initiates rain earlier and enhances rain development in a positive feedback loop. However, with time, rain formation in the superdroplet simulations catches up to the bin simulations. Offline calculations using the same drop size distributions in both schemes show that the different numerical methods for treating collision–coalescence also contribute to differences in rain formation. The stochastic collision–coalescence in the superdroplet method introduces more variability in drop growth for a given rain mixing ratio.
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