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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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NASA NTRSDate not supplied

Assimilation of Spaceborne Microwave and Radar Observations

Radiative transfer models are extensively used for the assimilation of satellite observations into NWP models as well as retrieving geophysical products from satellite measurements. The Community Radiative Transfer Model (CRTM) is a community model developed by NOAA JCSDA and widely used for different purposes requiring RT calculations. CRTM requires bulk optical properties of hydrometeors in the form of lookup tables in order to perform all-sky RT calculations. However, the current cloud scattering lookup tables in CRTM assume spherical shapes for all frozen hydrometeors, whereas actual clouds contain frozen particles with diverse shapes. The first part of this talk presents the implementation and validation of a comprehensive Discrete Dipole Approximation (DDA) cloud scattering database into CRTM, specifically targeting microwave frequencies. The DDA technique proves effective in simulating the optical properties of non-spherical hydrometeors in the microwave region. The original DDA database assumes total random orientation in calculating single scattering properties. To generate the required mass scattering parameters for CRTM, the single scattering properties and water content dependent particle size distributions are used. The evaluation of results involved a collocated dataset comprising short-term forecasts from the Integrated Forecast System of the European Center for Medium-Range Weather Forecasts and satellite microwave data. The findings demonstrate that the DDA lookup tables significantly reduce discrepancies between simulated and observed values when compared to the Mie tables. Passive instruments lack the ability to provide vertically resolved measurements of clouds and precipitation, which can be obtained by active radar instruments. However, incorporating these active measurements into data assimilation systems presents challenges due to the absence of fast forward radiative transfer models and difficulties in error modeling. The second part of the talk focuses on the development, evaluation, and sensitivity analysis of a forward radar model integrated into CRTM. The forward radar model utilizes scattering properties obtained from hydrometeor lookup tables generated using the discrete dipole approximation. By utilizing CRTM instrument-specific coefficients, the model can calculate both reflectivity and attenuated reflectivity for any given radar instrument and zenith angles. Evaluation using CloudSat measurements demonstrates a strong agreement between simulations and observations when the input profiles of hydrometeors align with the measured reflectivity profiles.

Isaac Moradi↗
DOE OSTI2022

Radiation and Polarization Signatures from Magnetic Reconnection in Relativistic Jets. II. Connection with γ-Rays

Abstract It is commonly believed that blazar jets are relativistic magnetized plasma outflows from supermassive black holes. One key question is how the jets dissipate magnetic energy to accelerate particles and drive powerful multiwavelength flares. Relativistic magnetic reconnection has been proposed as the primary plasma physical process in the blazar emission region. Recent numerical simulations have shown strong acceleration of nonthermal particles that may lead to multiwavelength flares. Nevertheless, previous works have not directly evaluated γ -ray signatures from first-principles simulations. In this paper, we employ combined particle-in-cell and polarized radiation transfer simulations to study multiwavelength radiation and optical polarization signatures under the leptonic scenario from relativistic magnetic reconnection. We find harder-when-brighter trends in optical and Fermi-LAT γ -ray bands as well as closely correlated optical and γ -ray flares. The swings in optical polarization angle are also accompanied by γ -ray flares with trivial time delays. Intriguingly, we find highly variable synchrotron self-Compton signatures due to inhomogeneous particle distributions during plasmoid mergers. This feature may result in fast γ -ray flares or orphan γ -ray flares under the leptonic scenario, complementary to the frequently considered minijet scenario. It may also imply neutrino emission with low secondary synchrotron flux under the hadronic scenario, if plasmoid mergers can accelerate protons to very high energy.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2012

A Fast and Efficient Version of the TwO-Moment Aerosol Sectional (TOMAS) Global Aerosol Microphysics Model

This study develops more computationally efficient versions of the TwO-Moment Aerosol Sectional (TOMAS) microphysics algorithms, collectively called Fast TOMAS. Several methods for speeding up the algorithm were attempted, but only reducing the number of size sections was adopted. Fast TOMAS models, coupled to the GISS GCM II-prime, require a new coagulation algorithm with less restrictive size resolution assumptions but only minor changes in other processes. Fast TOMAS models have been evaluated in a box model against analytical solutions of coagulation and condensation and in a 3-D model against the original TOMAS (TOMAS-30) model. Condensation and coagulation in the Fast TOMAS models agree well with the analytical solution but show slightly more bias than the TOMAS-30 box model. In the 3-D model, errors resulting from decreased size resolution in each process (i.e., emissions, cloud processing wet deposition, microphysics) are quantified in a series of model sensitivity simulations. Errors resulting from lower size resolution in condensation and coagulation, defined as the microphysics error, affect number and mass concentrations by only a few percent. The microphysics error in CN70CN100 (number concentrations of particles larger than 70100 nm diameter), proxies for cloud condensation nuclei, range from 5 to 5 in most regions. The largest errors are associated with decreasing the size resolution in the cloud processing wet deposition calculations, defined as cloud-processing error, and range from 20 to 15 in most regions for CN70CN100 concentrations. Overall, the Fast TOMAS models increase the computational speed by 2 to 3 times with only small numerical errors stemming from condensation and coagulation calculations when compared to TOMAS-30. The faster versions of the TOMAS model allow for the longer, multi-year simulations required to assess aerosol effects on cloud lifetime and precipitation.

Lee, Yunha↗
DOE OSTI2023

Efficient Subset Simulation using Hamiltonian Neural Network enhanced Markov Chain Monte Carlo Methods

The Monte Carlo method delivers an unbiased estimate of the probability of failure. However, the variance of the estimate depends on the number of evaluated samples. This number must be very large for estimations of a low probability of failure. If the evaluation of each sample is computationally expensive, the crude Monte Carlo simulation strategy is impracticable. Therefore, subset simulations are used to reduce the required number of evaluations. Subset simulations require a Markov Chain Monte Carlo sampler, such as the random walk Metropolis-Hastings algorithm. The algorithm, however, struggles with sampling in low-probability regions, especially if they are narrow. As a consequence, advanced Markov Chain Monte Carlo simulations have been developed. In particular, the Hamiltonian Monte Carlo method explores the target distribution rapidly. Driven by the idea of Hamiltonian dynamics, this sampler provides a non-random walk through the target distribution. The incorporation of subset simulation and Hamiltonian Monte Carlo methods has shown promising results for reliability analysis. One downside of the Hamiltonian Monte Carlo method is that gradient evaluations are computationally expensive, especially when dealing with high-dimensional problems and evaluating long trajectories. We show that integrating Hamiltonian neural networks in Hamiltonian Monte Carlo simulations significantly speeds up the sampling task. Furthermore, the enhancement of adaptive trajectory length within the Hamiltonian Monte Carlo results in the efficient proposal of the following states. Based on this recent enhancement, we provide a fast sampling strategy for subset simulations using Hamiltonian neural networks to replace the evaluation of the gradient and significantly speed up the Hamiltonian Monte Carlo simulation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Fast neural Poincaré maps for toroidal magnetic fields

Poincaré maps for toroidal magnetic fields are routinely employed to study gross confinement properties in devices built to contain hot plasmas. In most practical applications, evaluating a Poincaré map requires numerical integration of a magnetic field line, a process that can be slow and that cannot be easily accelerated using parallel computations. We propose a novel neural network architecture, the HénonNet, and show that it is capable of accurately learning realistic Poincaré maps from observations of a conventional field-line-following algorithm. After training, such learned Poincaré maps evaluate much faster than the field-line integration method. Moreover, the HénonNet architecture exactly reproduces the primary physics constraint imposed on field-line Poincaré maps: flux preservation. Furthermore, this structure-preserving property is the consequence of each layer in a HénonNet being a symplectic map. We demonstrate empirically that a HénonNet can learn to mock the confinement properties of a large magnetic island by using coiled hyperbolic invariant manifolds to produce a sticky chaotic region at the desired island location. This suggests a novel approach to designing magnetic fields with good confinement properties that may be more flexible than ensuring confinement using KAM tori.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Experimental evaluation of the vapor box divertor concept with an open vapor box module in Magnum-PSI

A promising approach to handle the intense plasma heat flux in the divertor region of a tokamak is the Vapor Box Divertor (VBD). Here plasma-lithium interaction creates a dense lithium vapor cloud which interacts with the incoming plasma, effectively shielding the tungsten surface beneath, therefore preventing overheating and sputtering of the tungsten and increasing the component’s lifetime. Two key steps must be addressed to validate this concept: investigating plasma-Li interactions and the transport mechanism of the latter in the presence of plasma. To explore this, a Vapor Box Module (VBM) has been designed for use with the linear plasma generator Magnum-PSI. The VBM consists of a series of three cylindrical boxes, with Li being evaporated at a controlled temperature in the central box (CB). Divertor-like plasma enters the VBM from an upstream aperture, interacts with the Li vapor cloud and exits through a downstream aperture ultimately impacting a target equipped with a calorimetry system. Optical diagnostics Thomson scattering, Filtered fast camera Imaging and optical emission spectroscopy provided information on plasma parameters in terms of electron density n e , temperature T e and plasma composition before and after this interaction. A significant reduction in plasma power was observed upon the establishment of lithium vaporization determined via cooling water calorimetry and embedded thermocouples at the downstream target. This resulted in a drop of the target temperature from ∼800 °C to ∼350 °C (57%) at the highest applied power (11.1 MW m −2 ) and CB temperature (∼700 °C). Lithium condensation at the side boxes of the VBM in combination with strong plasma momentum transfer effectively prevented upstream migration of lithium, while enhancing Li transport toward the target. The achievement of the two main goals of reducing plasma power and confining the Li in the VBM, are consistent with earlier published preliminary SOLPS-ITER simulations. This study shows that the presence of lithium in a VBD-like configuration can result in a strong reduction of power to the target surface, while at the same time the lithium vapor is effectively confined by the VBM, aided by the incoming plasma, preventing its escape from the VBM geometry. This represents a valuable step toward validating the feasibility of the VBD configuration in future fusion reactors.

Magnum-PSI↗
NASA NTRS2012

Evaluation of Arctic Sea Ice Thickness Simulated by Arctic Ocean Model Intercomparison Project Models

Six Arctic Ocean Model Intercomparison Project model simulations are compared with estimates of sea ice thickness derived from pan-Arctic satellite freeboard measurements (2004-2008); airborne electromagnetic measurements (2001-2009); ice draft data from moored instruments in Fram Strait, the Greenland Sea, and the Beaufort Sea (1992-2008) and from submarines (1975-2000); and drill hole data from the Arctic basin, Laptev, and East Siberian marginal seas (1982-1986) and coastal stations (1998-2009). Despite an assessment of six models that differ in numerical methods, resolution, domain, forcing, and boundary conditions, the models generally overestimate the thickness of measured ice thinner than approximately 2 mand underestimate the thickness of ice measured thicker than about approximately 2m. In the regions of flat immobile landfast ice (shallow Siberian Seas with depths less than 25-30 m), the models generally overestimate both the total observed sea ice thickness and rates of September and October ice growth from observations by more than 4 times and more than one standard deviation, respectively. The models do not reproduce conditions of fast ice formation and growth. Instead, the modeled fast ice is replaced with pack ice which drifts, generating ridges of increasing ice thickness, in addition to thermodynamic ice growth. Considering all observational data sets, the better correlations and smaller differences from observations are from the Estimating the Circulation and Climate of the Ocean, Phase II and Pan-Arctic Ice Ocean Modeling and Assimilation System models.

sea ice↗
DOE OSTI2022

De novo design and Rosetta-based assessment of high-affinity antibody variable regions (Fv) against the SARS-CoV -2 spike receptor binding domain ( RBD )

The continued emergence of new SARS-CoV-2 variants has accentuated the growing need for fast and reliable methods for the design of potentially neutralizing antibodies (Abs) to counter immune evasion by the virus. Here, we report on the de novo computational design of high-affinity Ab variable regions (Fv) through the recombination of VDJ genes targeting the most solvent-exposed hACE2-binding residues of the SARS-CoV-2 spike receptor binding domain (RBD) protein using the software tool OptMAVEn-2.0. Subsequently, we carried out computational affinity maturation of the designed variable regions through amino acid substitutions for improved binding with the target epitope. Immunogenicity of designs was restricted by preferring designs that match sequences from a 9-mer library of “human Abs” based on a human string content score. We generated 106 different antibody designs and reported in detail on the top five that trade-off the greatest computational binding affinity for the RBD with human string content scores. We further describe computational evaluation of the top five designs produced by OptMAVEn-2.0 using a Rosetta-based approach. We used Rosetta SnugDock for local docking of the designs to evaluate their potential to bind the spike RBD and performed “forward folding” with DeepAb to assess their potential to fold into the designed structures. Ultimately, our results identified one designed Ab variable region, P1.D1, as a particularly promising candidate for experimental testing. This effort puts forth a computational workflow for the de novo design and evaluation of Abs that can quickly be adapted to target spike epitopes of emerging SARS-CoV-2 variants or other antigenic targets.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

Probabilistic Blast Damage Modeling Uncertainties and Sensitivities

Blast overpressure is the predominant source of ground damage posed by potentially hazardous asteroid strikes. Estimates of the extent, severity, and likelihoods of potential blast damage regions will be one of the key metrics needed to mount civil defense or disaster response plans in the face of an impending impact. However, there are many inherent sources of uncertainty in evaluating the damage, both in characterizing the properties of the incoming object and in the approaches used to model the entry/impact and resulting damage, which make it difficult to produce a single ‘accurate’ or ‘best guess’ prediction of ground damage. The current 2021 PDC hypothetical impact scenario poses a particular challenge due to its short warning time. The need for rapid disaster response to prepare for an immanent impact, combined with lack of observational opportunities to refine basic knowledge about the object’s basic size and properties, make understanding the range and relative likelihood of consequences particularly critical. The potential damage caused by these blasts can be evaluated using a range of modeling and simulation approaches and levels of fidelity. Fast-running engineering-level models can be used to run large numbers of probabilistically sampled cases covering wide variations of uncertain properties or parameters. High-fidelity simulations, on the other hand, can capture more detailed/accurate blast physics, but can only be performed for a small selection of specific cases, requiring many assumptions to be made about the initial object and its unpredictable entry/breakup characteristics. In order to provide a more complete picture of the potential threat for effective disaster response, both types of analysis need to be employed together. In this approach, high-fidelity simulations are used to refine and anchor engineering models, and the probabilistic engineering models are used to evaluate broad parameters spaces and guide selection of the most pertinent simulation cases for a given scenario. This presentation expands upon the probabilistic asteroid impact risk assessments being performed as part of the 2021 PDC hypothetical impact exercise, focusing on key aspects of blast damage modeling uncertainties and sensitivities. We review the current modeling and simulation approaches employed in the current assessment, compare the relative levels of uncertainty stemming from each main element of the problem (i.e., knowledge of the asteroid properties, modeling of the atmospheric entry/breakup and airburst, and estimates of the ground damage from the resulting blasts waves), and highlight any notable trends and sensitivities for the current scenario case.

SMD↗
DOE OSTI2020

The application of synchrotron micro-computed tomography to characterize the three-dimensional microstructure in irradiated nuclear fuel

This research demonstrated the first time that synchrotron X-ray micro-computed tomography (μ-CT) was utilized to analyze the three-dimensional (3-D) morphology of the microstructure of irradiated nuclear fuel. Both absorption contrast and propagation-based phase contrast enhanced μ-CT techniques were evaluated. Porosity and phase region volumes were determined in neutron irradiated uranium 10 wt.% zirconium (U-10Zr) using propagation-based phase contrast enhanced μ-CT. Volumes were determined by image processing software and algorithms, with the porosity volume subsequently compared to the ASTM E562 method. The 3-D porosity of a small region (~ 8 x 10 5 µm 3 ) located in the intermediate fuel redistribution zone that was removed via a focused ion beam was determined to be 7.2% via image processing. A detailed 3-D analysis of the porosity with respect to volume and morphology was provided. Five growth stages of pore evolution were observed including: nucleation, growth, coalescence, interconnected porosity, and extended/interconnected porosity. Four distinct phase regions were identified, including the pores, via both absorption contrast and propagation-based phase contrast enhanced μ-CT. A quantitative comparison of fuel swelling between this localized microscopic U-10Zr fuel region, previously irradiated in the Fast Flux Test Facility, and historic U-10Zr fuels irradiated in the Experimental Breeder Reactor-II (EBR-II) was conducted. It was determined that for similar burnups, the localized swelling in this microscopic fuel region was 7.7%, which was approximately one-half of the value of the macroscopic swelling reported in EBR-II irradiated fuel. With the advent of new specimen preparation tools for irradiated materials, as well as advances in characterization techniques, researchers can now obtain previously inaccessible microstructural insight into irradiated fuels. This possibility naturally lends itself to improved fuel performance models for the nuclear community.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Characterization of a minor actinides bearing metallic fuel pin irradiated in EBR-II

The X501 transmutation experiment irradiated in Experimental Breeder Reactor II (EBR-II) was intended to evaluate the safety and performance of the addition of minor actinides (Am, Np) into the metallic nuclear fuel system. The irradiation of this experiment is also of paramount importance for comparisons between true fast spectrum irradiations (e.g. EBR-II) and shrouded irradiation capsules performed at the thermal neutron spectrum Idaho National Laboratory Advanced Test Reactor. The X501 experimental fuel pins were irradiated to a peak measured burnup of 6.2% fission per initial heavy metal atom. This paper reports and discusses Postirradiation Examination results for one of two minor actinide bearing pins from the EBR-II X-501 experiment (X501-G591) with a focus on fuel microstructure evolution. Additionally, fuel swelling, fission product distribution, cladding strain, fission gas release, fuel microstructure and fuel cladding chemical interaction were all evaluated. The fission gas release was 79.9% and the microstructure along the fuel pin presented several characteristics very similar to other EBR-II U-Pu-Zr ternary metallic fuel experience. Minor actinides seem to not dramatically affect the overall performance of this candidate transmutation fuel. Scanning Electron Microscopy was also performed and an in-depth characterization of the different regions and phases is presented. Performance data from these irradiations can be used to inform the feasibility of minor actinide transmutation in future reactor systems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Performance of reanalysis and mesoscale models off the coast of Hawai'i

The eastern Hawai'i coast in the United States is characterized by considerable wind resource fuelled by persistent trade winds, making it an important area for energy research. The need is strong for reanalyses and higher-resolution regional simulations where observations have been historically limited, such as Hawai'i's offshore environments. However, studies using offshore observations in other parts of the world have shown that significant errors can occur in reanalyses and wind datasets, which can lead to inaccurate estimates of wind energy generation, payback periods, and extreme weather risks at project locations. The degree of such errors is influenced by a number of factors, including spatial resolution and the handling of processes within the planetary boundary layer (PBL). In this work, we provide a wind resource characterization from year-long lidar buoy measurements off the eastern coast of O'ahu, Hawai'i, an environment previously unobserved at the rotor level, and use the characterization to evaluate the performance of two simulation datasets. The O'ahu deployment location is meteorologically unique and less complex than land-based wind resource characterizations, being strongly characterized by trade winds with minimal land–atmosphere interaction influences. Despite the unique and fairly consistent meteorological conditions, we hypothesize that distinct simulation datasets will exhibit diverse ranges of errors similar to those that have been seen for other offshore locations. We find the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis version 5 (ERA5) to strongly underestimate observed wind speeds at the O'ahu location (bias = −1.54 m s −1 at a height of 140 m above sea level), while a regional Weather Research and Forecasting Model (WRF) simulation produced by the University of Hawai'i (UH-WRF) provides a significantly smaller wind speed bias (−0.25 m s −1 ), highlighting the value of running regional, higher-resolution simulations. The large bias noted for ERA5 is driven by significant underestimation of fast wind speeds (>9 m s −1 ), which the study site is largely characterized by, along with discontinuities in the ERA5 diurnal cycle. We also speculate that the relative sparsity of observations for data assimilation in this remote part of the world could influence the performance of ERA5 and that challenges with characterizing island effects could impact the performance of both datasets.

17 WIND ENERGY↗
DOE OSTI2020

Layout and performance of HPK prototype LGAD sensors for the High-Granularity Timing Detector

The High-Granularity Timing Detector is a detector proposed for the ATLAS Phase II upgrade. The detector, based on the Low-Gain Avalanche Detector (LGAD) technology, will cover the pseudo-rapidity region of 2.4 < |n| < 4.0 with two end caps on each side and a total area of 6.4 m 2 . The timing performance can be improved by implanting an internal gain layer that can produce signals with a fast rising edge. It significantly improves the signal-to-noise ratio. The required average timing resolution per track for a minimum ionizing particle is 30 ps at the start and 50 ps at the end of the HL-LHC operation. This is achieved with several layers of LGAD. The innermost region of the detector would accumulate a 1MeV neutron-equivalent fluence up to 2.5 10 15 n eq /cm 2 including a safety factor of 1.5 before being replaced during the scheduled shutdowns. The addition of this new detector is expected to play an important role in the mitigation of high pile-ups at the HL-LHC. The layout and performance of the various versions of LGAD prototypes produced by Hamamatsu (HPK) have been studied by the ATLAS Collaboration. The breakdown voltages, depletion voltages, inter-pad gaps, collected charge as well as the time resolution have been measured and the production yield of large size sensors has been evaluated.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

The effect of transient needle lift on the internal flow and near-nozzle spray characteristics for modern GDI systems investigated by high-speed X-ray imaging

The development of the injector nozzle is a dynamic area in regard of several technical aspects. At first, the internal flow influences the near-field spray characteristics via various phenomena such as cavitation and turbulence. However, these phenomena are not fully understood due to their extremely fast, complex and multiscale nature. Furthermore, it governs the spray targeting inside the combustion chamber. High-speed X-ray imaging of GDI injector nozzles is performed in this study. The experimental results presented are related to the internal flow and primary breakup of discharged liquid jets. The injectors used are equipped with nozzles made of aluminum which have been specially developed for these investigations to enhance optical accessibility. The visualization of the needle motion, in-nozzle flow and the primary breakup region provides several exciting observations. First, the needle lift tracking exhibits short overshooting right before the steady-state of the injection phase. Additionally, this event leads to a short-term, however, significant change in the associated performance of the breakup. This phenomenon is found to be a consequence of the transient behavior of the in-nozzle flow. It is shown that under some circumstances hydraulic flip may occur during this overshooting period. The primary jet breakup region is visualized and evaluated by means of image processing. Thus, the transient behavior of liquid jet expansion is quantified in the vicinity of the nozzle. It is observed that the liquid jet direction deviates from the hole axis already at the nozzle outlet, which is caused by internal flow characteristics.

42 ENGINEERING↗
DOE OSTI2021

Evaluation of gamma-ray transmission through rectangular collimator slits for application in nuclear fuel spectrometry

Gamma-ray spectrometry is widely applied in several science fields, and in particular in non-destructive gamma scanning and gamma emission tomography of irradiated nuclear fuel. Usually, a collimator is used in the experimental setup, to selectively interrogate a region of interest in the fuel. For the optimization of instrument design, as well as for planning measurement campaigns, predictive models for the transmitted gamma-ray intensity through the collimator are needed. Commonly, Monte Carlo Radiation Transport tools are used for accurate prediction of gamma-ray transport, however, the long computation time requirements when used in low-efficiency experimental setups present challenges. Here, the full-energy peak intensity transmitted through a rectangular collimator slit was examined. A uniform planar surface source emitting isotropically was considered, and the rate of photons reaching an ideal counter plane on the opposite side of the collimator was evaluated by analytical integration. To find a closed-form primitive function, some idealizations were required, and thereby parametric models were obtained for the optical field of view, dependent on slit dimensions (length, height and width) and source-to-collimator distance. For contributions from outside the optical field of view, where a closed-form expression cannot be found, fast numerical integral methods were instead used. The results were validated using the Monte Carlo code MCNP6 and show an agreement within three percent for the numerical method. For the analytical method, deviations up to tens of percent were obtained, which is deemed to still be sufficient for instrument design and measurement planning, where often the order of magnitude of the count rate is not a priori known. The method is planned for use in iterative optimization routines in the design of Gamma Emission Tomography devices, as well as for the prediction of gamma spectra obtained in the planning of fuel inspections. An application of the proposed method was demonstrated in spectrum prediction for a short cooling-time fuel rod test from the Halden reactor.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1998

Demonstration of a Probabilistic Technique for the Determination of Economic Viability of Very Large Transport Configurations

Over the past few years, modem aircraft design has experienced a paradigm shift from designing for performance to designing for affordability. This report contains a probabilistic approach that will allow traditional deterministic design methods to be extended to account for disciplinary, economic, and technological uncertainty. The probabilistic approach was facilitated by the Fast Probability Integration (FPI) technique; a technique which allows the designer to gather valuable information about the vehicle's behavior in the design space. This technique is efficient for assessing multi-attribute, multi-constraint problems in a more realistic fashion. For implementation purposes, this technique is applied to illustrate how both economic and technological uncertainty associated with a Very Large Transport aircraft concept may be assessed. The assessment is evaluated with the FPI technique to determine the cumulative probability distributions of the design space, as bound by economic objectives and performance constraints. These distributions were compared to established targets for a comparable large capacity aircraft, similar in size to the Boeing 747-400. The conventional baseline configuration design space was determined to be unfeasible and marginally viable, motivating the infusion of advanced technologies, including reductions in drag, specific fuel consumption, wing weight, and Research, Development, Testing, and Evaluation costs. The resulting system design space was qualitatively assessed with technology metric "k" factors. The infusion of technologies shifted the VLT design into regions of feasibility and greater viability. The study also demonstrated a method and relationship by which the impact of new technologies may be assessed in a more system focused approach.

Mavris, Dimitri N.↗
DOE OSTI2022

Deploying Taller Turbines in Complex Terrain: A Hill Flow Study (HilFlowS) Perspective

Terrain-induced flow acceleration is presented for the summertime, peak power season at Lawrence Livermore National Laboratory’s Site 300 for the Hill Flow Study (HilFlowS). HilFlowS, designed as an adjunct field campaign to the Department of Energy’s Second Wind Forecasting Improvement Project (WFIP2), provides wind profile observations at a second location in complex terrain for validating numerical atmospheric model simulations and for better understanding flow behavior over hills for wind power generation. One unique feature of HilFlowS was the inclusion of an undergraduate university student who helped plan and execute the experiment as well as analyze wind data from two remote sensing laser detection and ranging (lidar) instruments deployed along parallel ridgelines. HilFlowS examines the trend of building higher into the atmosphere for the purpose of increasing wind turbine power production and evaluates the wind resource in the Altamont Pass Region of Northern California for a set of wind turbines of differing hub-heights and rotor-disk diameters found in the area. The wind profiles show strongly channeled onshore flow above both hills, enhanced by strong subsidence aloft, which produces a wind maximum (Umax) around z = 10 m and strong negative shear throughout all of the evaluated rotor-disks for much of the summer wind season. Under these conditions, shear becomes more negative with increasing hub-height and increasing rotor-disk size. Rotor-disk equivalent wind speed (Uequiv), a measure of the average wind speed across the entire rotor-disk, is compared to hub-height, rotor length, and rated capacity factor for the set of turbines. Uequiv is most closely related to turbine hub-height and is negatively correlated given the low altitude of Umax. Based on these results, building the largest capacity, large rotor-disk wind turbine at the lowest possible hub-height appears to provide turbines in the Altamont with a fast, near-surface, onshore wind resource during the peak power season.

17 WIND ENERGY↗
NASA NTRS2010

Using Transport Diagnostics to Understand Chemistry Climate Model Ozone Simulations

We demonstrate how observations of N2O and mean age in the tropical and midlatitude lower stratosphere (LS) can be used to identify realistic transport in models. The results are applied to 15 Chemistry Climate Models (CCMs) participating in the 2010 WMO assessment. Comparison of the observed and simulated N2O/mean age relationship identifies models with fast or slow circulations and reveals details of model ascent and tropical isolation. The use of this process-oriented N2O/mean age diagnostic identifies models with compensating transport deficiencies that produce fortuitous agreement with mean age. We compare the diagnosed model transport behavior with a model's ability to produce realistic LS O3 profiles in the tropics and midlatitudes. Models with the greatest tropical transport problems show the poorest agreement with observations. Models with the most realistic LS transport agree more closely with LS observations and each other. We incorporate the results of the chemistry evaluations in the SPARC CCMVal Report (2010) to explain the range of CCM predictions for the return-to-1980 dates for global (60 S-60 N) and Antarctic column ozone. Later (earlier) Antarctic return dates are generally correlated to higher (lower) vortex Cl(sub y) levels in the LS, and vortex Cl(sub y) is generally correlated with the model's circulation although model Cl(sub y) chemistry or Cl(sub y) conservation can have a significant effect. In both regions, models that have good LS transport produce a smaller range of predictions for the return-to-1980 ozone values. This study suggests that the current range of predicted return dates is unnecessarily large due to identifiable model transport deficiencies.

Strahan, S. E.↗