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At least 721 records · Page 40

Quantifying Spatiotemporal Variability of Glacier Algal Blooms and the Impact on Surface Albedo in Southwestern Greenland

Albedo reduction due to light-absorbing impurities can substantially enhance ice sheet surface melt by increasing surface absorption of solar energy. Glacier algae have been suggested to play a critical role in darkening the ablation zone in southwestern Greenland. It was very recently found that the Sentinel-3 Ocean and Land Colour Instrument (OLCI) band ratio R709 nm∕R673 nm can characterize the spatial patterns of glacier algal blooms. However, Sentinel-3 was launched in 2016, and current data are only available over three melting seasons (2016–2019). Here, we demonstrate the capability of the MEdium Resolution Imaging Spectrometer (MERIS) for mapping glacier algae from space and extend the quantification of glacier algal blooms over southwestern Greenland back to the period 2004–2011. Several band ratio indices (MERIS chlorophyll a indices and the impurity index) were computed and compared with each other. The results indicate that the MERIS two-band ratio index (2BDA) R709 nm∕R665 nm is very effective in capturing the spatial distribution and temporal dynamics of glacier algal growth on bare ice in July and August. We analyzed the interannual (2004–2011) and summer (July–August) trends of algal distribution and found significant seasonal and interannual increases in glacier algae close to the Jakobshavn Isbrae Glacier and along the middle dark zone between the altitudes of 1200 and 1400 m. Using broadband albedo data from the Moderate Resolution Imaging Spectroradiometer (MODIS), we quantified the impact of glacier algal growth on bare ice albedo, finding a significant correlation between algal development and albedo reduction over algae-abundant areas. Our analysis indicates the strong potential for the satellite algal index to be used to reduce bare ice albedo biases in regional climate model simulations.

surface albedo↗

Overview of Predictive Simulation Capability Development for Crater Evolution and Ejecta in Continuum/Rarefied Flows

As part of the Game Changing Development (GCD) Program, funded by NASA’s Space Technology Mission Directorate (STMD), the development of simulation capability for the prediction of extra-terrestrial Plume Surface Interaction (PSI) environments has been undertaken by the Fluid Dynamics Branch at NASA/MSFC. The Predictive Simulation Capability (PSC) Element is focused on creating simulation capability for the reliable and accurate prediction of PSI in Martian (~650 Pa) and Lunar (vacuum) ambient environments. In addition to the predictive simulation capability, the GCD Program also contains a companion Ground Testing Element for development of focused datasets for validation of predictive capability as well as a Flight-focused Instrumentation Element. The focus of this paper is to provide an overview and a brief status on one area of capability development through this GCD PSI project - capturing the effects of mixed continuum/rarefied flow on crater development and ejecta sheets. This includes both capability enhancements and maturation of the predictive tool, Loci/GGFS, into a production capable tool as well as validation of the tool against PSI data in Martian and Lunar environments. There are six newly developed capabilities that will be production ready by the end of the fiscal year. Newly developed capabilities must first be verified prior to being production ready, and this process includes capability demonstration, solution verification, and performance evaluation. An overview of the newly developed capabilities with respect to several test cases, including cratering simulations of the Apollo Lunar Module, will be presented. Several validation analyses have been performed to validate in Martian and more Lunar-like environments, including simulations of cratering from a subsonic flow test at Planetary Aeolian Lab (PAL) conducted in a Martian-like environment and pre-test cratering predictions of Physics Focused Ground Test (PFGT) tests planned to be performed in Martian-like and more Lunar-like environments. An overview of these validation analyses as it pertains to the capability development will be presented.

Andrew Weaver↗

Experimental Results and Interfacial Lift-off Model Predictions of Critical Heat Flux for Flow Boiling with Subcooled Inlet Conditions – In Preparation for Experiments Onboard the International Space Station

This study investigates critical heat flux (CHF) for subcooled flow boiling of n-Perfluorohexane based on results of pre-launch Earth-gravity Mission Sequence Tests (MSTs) of the Flow Boiling and Condensation Experiment (FBCE), which was launched to the International Space Station (ISS) in August 2021. CHF measurements were made in a rectangular channel having a 2.5 mm by 5 mm cross-section and a 114.6-mm long heated segment. Both single-sided and double-sided heating were tested in vertical upflow in Earth gravity for a variety of inlet conditions. The inlet subcooling was varied in the range of 0.4 – 32.0°C and encompassed both near-saturated and highly subcooled conditions. Experimental trends and high-speed video records were investigated to better understand the mechanism of CHF. Overall trends show CHF increases as flow rate and/or inlet subcooling are increased. Flow features from the events around CHF justify the applicability of the Interfacial Lift-off Model and the determination of limiting criteria for its application. The present experimental data are combined with prior databases for various flow orientations with respect to Earth gravity and microgravity data collected on parabolic flights. Predictions are made using the Interfacial Lift-off Model for this consolidated subcooled-inlet FBCE-CHF database. A heat utility ratio was included in the model to capture the effects of subcooling and corresponding thermodynamic non-equilibrium. An overall mean absolute error of 19.04% indicates good predictive capability of the model for both heating configurations, different gravity environments, and a wide range of inlet subcooling.

flow boiling↗

Overview of Predictive Simulation Capability Development for Crater Evolution and Ejecta in Continuum/Rarefied Flows

As part of the Game Changing Development (GCD) Program funded by NASA’s Space Technology Mission Directorate (STMD), the development of simulation capability for the prediction of extra-terrestrial plume surface interaction (PSI) environments has been undertaken by the Fluid Dynamics Branch at NASA/MSFC. The Predictive Simulation Capability (PSC) Element is focused on creating simulation capability for the reliable and accurate prediction of PSI in Martian (~650 Pa) and Lunar (vacuum) ambient environments. In this paper, an overview and brief status on one area of capability development through this GCD PSI project, capturing the effects of mixed continuum/rarefied flow on crater development and ejecta sheets, is presented with respect to capability enhancements, predictive tool maturation, and validation of the Loci/GGFS tool against PSI data in Martian and Lunar environments. Axisymmetric modeling, overset mesh/moving mesh, and multiple-species mixture modeling capabilities are verified against Loci/CHEM, and a demonstration of the capabilities is presented for the Apollo Lunar Module.

Andrew Weaver↗

A Quantum Algorithm to Simulate Open Quantum Systems

Given the advent of quantum algorithms for a wide array of problems in linear algebra and machine learning, it is important to develop general methods for the simulation of arbitrary (ie non-unitary) operators on quantum hardware. In this talk, we present a novel quantum algorithm based on the quantum singular value transformation (QSVT) to apply an arbitrary operator K to some input state and subsequently estimate the expectation value of some observable. Our construction then immediately yields a route to estimating observables of states undergoing open quantum dynamics, whose effect is captured by a set of non-unitary Kraus operators. Our algorithm succeeds deterministically given the Sz-Nagy dilation, and we provide details on the algorithm's query and gate complexity, numerical verification, and comparisons with prior methods.

Quantum computing↗

Sensitivity Study of Impact Risk Model Results to Thermal Radiation Damage Model for Large Objects

NASA’s Probabilistic Asteroid Impact Risk (PAIR) assessment model assesses the likelihood of potential damage for asteroid impact scenarios. Fast-running models are used to capture the effects of different hazards. This paper looks specifically at local ground damage hazards, including blast overpressure and thermal radiation damage, for large object impact scenarios. A sensitivity study is conducted to determine which parameters, and over what ranges, cause impact risks to become sensitive to thermal damage. Two additional thermal models with different approaches are used for comparison. The study determined the current thermal model is most sensitive to the luminous efficiency parameter that reflects the model’s uncertainty in the amount of energy contributing to the thermal radiation damage. This sensitivity was most apparent for the highest severity damage levels. Comparisons of the three models showed that in addition to sensitivities within the models, the impact risks are also sensitive to the choice of thermal model. The study results were applied to the 2023 PDC hypothetical asteroid impact scenario and parameter ranges of interest determined. At the serious damage level, luminous efficiencies above 0.006 showed a small chance of thermal playing an important role, while luminous efficiencies above 0.0008 led to thermal playing a significant role at the unsurvivable damage severity level. Study results are used to identify key areas where additional model refinement and better knowledge of asteroid properties may be important for improving damage estimates.

SMD↗

Sensitivity Study of Impact Risk Model Results to Thermal Radiation Damage Model for Large Objects

NASA’s Probabilistic Asteroid Impact Risk (PAIR) assessment model assesses the likelihood of potential damage for asteroid impact scenarios. Fast-running models are used to capture the effects of different hazards. This paper looks specifically at local ground damage hazards, including blast overpressure and thermal radiation damage, for large object impact scenarios. A sensitivity study is conducted to determine which parameters, and over what ranges, cause impact risks to become sensitive to thermal damage. Two additional thermal models with different approaches are used for comparison. The study determined the current thermal model is most sensitive to the luminous efficiency parameter that reflects the model’s uncertainty in the amount of energy contributing to the thermal radiation damage. This sensitivity was most apparent for the highest severity damage levels. Comparisons of the three models showed that in addition to sensitivities within the models, the impact risks are also sensitive to the choice of thermal model. The study results were applied to the 2023 Planetary Defense Conference hypothetical asteroid impact scenario and parameter ranges of interest determined. At the serious damage level, luminous efficiencies above 0.006 showed a small chance of thermal playing an important role, while luminous efficiencies above 0.0008 led to thermal playing a significant role at the unsurvivable damage severity level. Study results are used to identify key areas where additional model refinement and better knowledge of asteroid properties may be important for improving damage estimates.

SMD↗

Learjet 25D Jet Noise Flyover Measurements: Comparisons with Scale-Model Data

Continued interest in commercial supersonic flight has highlighted the need for accurate jet-noise predictions as jet noise is expected to be a dominant noise source for aircraft takeoff conditions. The current study compares the acoustic spectra obtained from a scale-model investigation to that from a Learjet 25D flyover test. Reasonable agreement was achieved between the scale-model and flight data in both peak level and frequency when the physical scale factor for the scale-model was increased by roughly 6%. The peak perceived noise levels (PNL) for the flight data were between 1.29 dB and 1.65 dB higher than those for the scale model. The roll-off of PNL with time for large emission angles was greater for the flight data than for the scale-model data. Using a distributed source model for shear-layer-refraction corrections to the scale-model data slightly improved comparisons to flight data at low frequencies for emission angles near 70° and between 110° and 130°. Distributed source models had no impact on the scale-model spectra near the peak jet-noise angle. Applying a stretching factor to the distributed source models to capture the effects of a flight stream had a very limited impact on the computed spectra.

Acoustics↗

ResORR: A Globally Scalable and Satellite Data-Driven Algorithm for River Flow Regulation Due to Reservoir Operations

We propose a globally scalable algorithm, ResORR (Reservoir Operations driven River Regulation), to predict regulated river flow and tested it over the heavily regulated basin of the Cumberland River in the US. ResORR was found able to model regulated river flow due to upstream reservoir operations of the Cumberland River. Over a mountainous basin dominated by high rainfall, ResORR was effective in capturing extreme flooding modified by upstream hydropower dam operations. On average, ResORR improved regulated river flow simulation by more than 50% across all performance metrics when compared to a hydrologic model without a regulation module. ResORR is a timely software algorithm for understanding human regulation of surface water as satellite-estimated reservoir state is expected to improve globally with the recently launched Surface Water and Ocean Topography (SWOT) mission.

River Regulation↗

Strain Measurement of Geological Samples Subjected to Triaxial Stresses Experienced During Hydraulic Loading

Understanding stress and strain relationships and having the ability to predict these quantities for known load conditions is crucial to all geomechanical and, in some instances, reservoir flow applications. The constitutive equations governing the deformation of geological materials are typically adequate for bulk or large scale deformation and stress analyses. However, these rules are generally less precise in their ability to make accurate predictions in physical processes where highly localized material heterogeneity exists or where the presence of geometric irregularities such as micro-cracks may be present. This is especially relevant to EGS where hydraulic fracture propagation models are needed to develop optimal reservoir creation strategies and where fracture permeability is significantly influenced by regional stress states and may affect reservoir operation strategies. The deficiencies of the models used to describe these physical processes are a practical reality necessitated by the manner in which rock properties must be obtained. Conventional rock mechanics tests subject samples to controlled load conditions and measure bulk deformations of the sample or more localized deformations only on exposed surfaces of the sample. They are currently unable to comprehensively map the deformation state within the sample. For processes such as fracture, however, the state of a particular region within the rock drives the overall failure behavior of the sample. The authors believe that possessing a means to measure strains within samples subjected to hydraulic fracture loading conditions will provide a useful tool for understanding the localized effects not captured by conventional techniques and may serve as a method for improving hydraulic fracture models. An ongoing effort at Oak Ridge National Laboratory endeavors to develop a neutron diffraction based strain measurement capability to interrogate the strain state of a geological sample, at arbitrary internal locations, subjected to a triaxial stress state. The basis of the method and initial results for simple load conditions were reported at last year s Stanford Geothermal Workshop. This work will report results from recent neutron diffraction strain measurement experiments in which marble samples were subjected to load conditions more representative of hydraulic fracturing operations within a pressure cell specially designed for the reported strain measurement technique.

An, Ke↗

Pellet Cladding Mechanical Interaction Modeling Using the Extended Finite Element Method

As a brittle material, the ceramic UO2 used as light water reactor fuel experiences significant fracturing throughout its life, beginning with the first rise to power of fresh fuel. This has multiple effects on the thermal and mechanical response of the fuel/cladding system. One such effect that is particularly important is that when there is mechanical contact between the fuel and cladding, cracks that extending from the outer surface of the fuel into the volume of the fuel cause elevated stresses in the adjacent cladding, which can potentially lead to cladding failure. Modeling the thermal and mechanical response of the cladding in the vicinity of these surface-breaking cracks in the fuel can provide important insights into this behavior to help avoid operating conditions that could lead to cladding failure. Such modeling has traditionally been done in the context of finite-element-based fuel performance analysis by modifying the fuel mesh to introduce discrete cracks. While this approach is effective in capturing the important behavior at the fuel/cladding interface, there are multiple drawbacks to explicitly incorporating the cracks in the finite element mesh. Because the cracks are incorporated in the original mesh, the mesh must be modified for cracks of specified location and depth, so it is difficult to account for crack propagation and the formation of new cracks at other locations. The extended finite element method (XFEM) has emerged in recent years as a powerful method to represent arbitrary, evolving, discrete discontinuities within the context of the finite element method. Development work is underway by the authors to implement XFEM in the BISON fuel performance code, and this capability has previously been demonstrated in simulations of fracture propagation in ceramic nuclear fuel. These preliminary demonstrations have included only the fuel, and excluded the cladding for simplicity. This paper presents initial results of efforts to apply XFEM to model stress concentrations induced by fuel fractures at the fuel/cladding interface during pellet cladding mechanical interaction (PCMI). This is accomplished by enhancing the thermal and mechanical contact enforcement algorithms employed by BISON to permit their use in conjunction with XFEM. The results from this methodology are demonstrated to be equivalent to those from using meshed discrete cracks. While the results of the two methods are equivalent for the case of a stationary crack, it is demonstrated that XFEM provides the additional flexibility of allowing arbitrary crack initiation and propagation during the analysis, and minimizes model setup effort for cases with stationary cracks.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Radioisotope Power System Dose Estimation Tool

The Radioisotope Power System Dose Estimation Tool (RPS-DET) is used to create, perform and analyze particle-transport simulations of radioisotope power systems (RPS). RPS-DET consists of a Matlab graphical user interface (GUI) to generate and analyze Monte Carlo N-Particle (MCNP) 6 input and output files. Simulation geometries are created using a library-based method of combining multiple RPS units and environmental scenarios while source terms are produced from databases of time-dependent photon and neutron spectra generated by the software packages IsoChain and ORIGEN. Simulation results are saved in a three-dimensional format for neutron and photon flux and dose in tissue or silicon and may be interactively inspected via the GUI. RPS-DET allows flexibility in the simulation-space by providing the ability to mix-and-match RPS units with relevant environments along with capturing the effects of fuel-aging for the particle-energy-spectra and intensity. This work has been benchmarked against measurements of existing RPS units and found to comparably predict neutron and gamma flux, absorbed dose, and dose equivalent in humans and electronics (silicon).

Smith, Michael↗

Short-Term Forecasting Across a Network for the Autonomous Wind Farm: Preprint

In an autonomous wind farm, turbines will use information from nearby turbines to achieve wind farm-level objectives such as optimizing the overall performance of a wind farm, ensuring resiliency when other sensors fail, and adapting to changing local conditions. In this paper, the wind farm can be modeled as a network within which turbines (nodes) share information across designated communication channels, with a focus on turbines at the outside of the wind farm capturing local effects and sharing that information with downstream turbines. Understanding of varied inflow conditions can be especially important in complex terrain. This information can be used to monitor turbines, self-organize turbines into groups, and predict the power performance of a wind farm. In particular, this paper describes an autonomous wind farm that incorporates information from local sensors in real time to predict wind speed and wind direction at each turbine over a short-term horizon. Results indicate that the estimate of wind direction can be used to improve the knowledge of the wind speed and direction over the persistence method on a 10- 15-minute time horizon. These short-term forecasts can also be used to facilitate advanced control methods such as feedforward control within a wind farm.

17 WIND ENERGY↗

Development of Molten Salt Reactor Modeling and Simulation Capabilities in VERA

In recent years, the nuclear community has seen a resurgence of interest in molten salt reactors (MSRs). Because of their molten, flowing fuel, MSRs present several new challenges not present in many other reactors, necessitating tightly coupled multiphysics modeling and simulation for accurate analysis. The Virtual Environment for Reactor Applications (VERA) has been developed to provide a high-fidelity multiphysics framework for reactor analysis. Though it was originally developed for light water reactor applications, VERA’s multiphysics capabilities make for a natural extension to MSR analysis. Recent efforts have focused on capturing the effects of moving fuel. A lumped depletion capability has been added that accounts for the moving and mixing of the fuel, as well as time spent outside the active core. A general multi-phase species transport module has also been added to track the movement and evolution of salt constituents as the salt flows through the core and around the primary loop. This paper presents a discussion of the new MSR capabilities in VERA, along with results for the lumped depletion and species transport capabilities for the Molten Salt Reactor Experiment, demonstrating VERA’s effectiveness in multiphysics simulations of MSRs.

Graham, Aaron↗

Short-Term Forecasting Across a Network for the Autonomous Wind Farm

In an autonomous wind farm, turbines will use information from nearby turbines to achieve wind farm-level objectives such as optimizing the overall performance of a wind farm, ensuring resiliency when other sensors fail, and adapting to changing local conditions. In this paper, the wind farm can be modeled as a network within which turbines (nodes) share information across designated communication channels, with a focus on turbines at the outside of the wind farm capturing local effects and sharing that information with downstream turbines. Understanding of varied inflow conditions can be especially important in complex terrain. This information can be used to monitor turbines, self-organize turbines into groups, and predict the power performance of a wind farm. In particular, this paper describes an autonomous wind farm that incorporates information from local sensors in real time to predict wind speed and wind direction at each turbine over a short-term horizon. Results indicate that the estimate of wind direction can be used to improve the knowledge of the wind speed and direction over the persistence method on a 10-15-minute time horizon. These short-term forecasts can also be used to facilitate advanced control methods such as feedforward control within a wind farm.

17 WIND ENERGY↗

Testing Gravity Using Type Ia Supernovae Discovered by Next-Generation Wide-Field Imaging Surveys

In the upcoming decade cadenced wide-field imaging surveys will increase the number of identified $z<0.3$ Type~Ia supernovae (SNe~Ia) from the hundreds to the hundreds of thousands. The increase in the number density and solid-angle coverage of SNe~Ia, in parallel with improvements in the standardization of their absolute magnitudes, now make them competitive probes of the growth of structure and hence of gravity. The peculiar velocity power spectrum is sensitive to the growth index $\gamma$, which captures the effect of gravity on the linear growth of structure through the relation $f=\Omega_M^\gamma$. We present the first projections for the precision in $\gamma$ for a range of realistic SN peculiar-velocity survey scenarios. In the next decade the peculiar velocities of SNe Ia in the local $z<0.3$ Universe will provide a measure of $\gamma$ to $\pm 0.01$ precision that can definitively distinguish between General Relativity and leading models of alternative gravity.

79 ASTRONOMY AND ASTROPHYSICS↗