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NASA NTRS2021

Understanding Uncertainty of Snow Radiative Transfer Modeling Within a Mixed Deciduous and Evergreen Forest

Satellite-based passive microwave observations provide the best available continuous observational estimates of global snow water storage due to their broad geographic footprint and low sensitivity to clouds and precipitation. However, these observations are subject to substantial uncertainty due to the complex radiative properties of snow and from interference in forested areas. Physical radiative transfer models can be leveraged to improve the fidelity of these observations and as a data-assimilation tool. In this article, the Dense Media Radiative Transfer model with Multiple Layers (DMRT-ML) is used to simulate snow brightness temperatures from data collected from snow pits excavated during a two-day-long field study performed a temperate forest in the Northeast United States. The simulations are evaluated against surface-based radiometer observations collected at the snow pits. The DMRT-ML is configured with varying complexity to determine the snowpack characteristics most essential toward simulating brightness temperature within a temperate forest with complicated snow stratigraphy. In general, the single-layer configurations were not sufficiently complex to accurately simulate snow brightness temperature without significant tuning. The most accurate simulation was a two-layer configuration with a prescribed ice layer separating the snow layers. This simulation had a root-mean-square error <;15 K for the 37-GHz frequency. More complicated snowpack stratigraphy configurations did not substantively improve the results over the two-layer model configuration. The DMRT-ML was also used to examine differences between redundant datasets of density and grain size. It was determined that similar snow data collection and radiative transfer model configuration techniques are critical to ensure cross-study comparability.

Theodore Letcher↗

NASA NTRSDate not supplied

Insights into Long-Term Global Precipitation from IMERG and GPCP

Multiple satellite-based datasets provide estimates of the long-term record of global precipitation. Each necessarily includes both the real atmospheric behavior and a collection of artifacts driven by the input data sources and design choices in the retrievals and dataset construction. For this presentation, the Integrated Multi-satellitE Retrievals for GPM (IMERG) products from the Global Precipitation Measurement (GPM) mission’s U.S. Science Team are designed as a modern High-Resolution Precipitation Product (HRPP), while the Global Precipitation Climatology Project’s (GPCP) products are designed as a modern Climate Data Record (CDR). Although they share some common input data sources, the computational process for each is rather different. Comparing the precipitation estimates from each algorithm gives us insights into likely artifacts and the natural variations that are common to both. The goal of an HRPP is to give the best estimate of precipitation at each time step in the dataset, generally meaning that “all possible available” data are used. In contrast, the CDR is intended to provide a precipitation record that has relatively homogeneous statistics, necessary for climate analysis. Each analysis strives for both goals, of course, but this means that the HRPP uses the disparate collection of satellites whose statistics don’t quite match the ideal record, while the CDR is computed from fewer satellites that provide a relatively homogeneous set of precipitation statistics. This presentation employs the current versions of the IMERG and GPCP products, V07B and V3.2, respectively. A variety of analyses have demonstrated that IMERG has more artifacts, as expected, which tend to result from changes in the source of intercalibration for the various input satellites, namely the Combined Radar-Radiometer Algorithm using TMI and PR during the TRMM era and using GMI and DPR-Ku during the GPM era. As well, a shift occurs when the altitudes of the TRMM and GPM satellites change as a result of orbit boosts. For the most part the mean precipitation shows good continuity across these boundaries, but there are noticeable changes in the respective histograms. The latter has taken on more importance in recent years due to increased scrutiny on extremes which implicitly focus on the upper end of the precipitation histograms. The GPCP product is more homogeneous, with only one major change in calibrator, transitioning from the SSMI series of satellites to the SSMIS series of satellites in 2009. The GPCP analysis does a good job of minimizing artifacts in the means at this boundary, while the histograms show a smaller, but still noticeable shift in the histograms, a result that is similar to data boundaries in IMERG. The GPCP Daily, which is a month-by-month rescaling of the daily accumulated IMERG Final product, shows more consistency than the equivalent daily IMERG, but inherits the histogram shifts from IMERG. Given this overlay of artifacts, there is enough consistency between the products to illustrate some important long-term variations, including interannual variations, not all of which are easily attributable to ENSO events, and trends that are large regionally, but comparatively small when averaged across the globe.

precipitation↗

NASA NTRS1996

Analysis and Modeling of a Two-Phase Jet Pump of a Flow Boiling Test Facility for Aerospace Applications

Jet pumps are devices capable of pumping fluids to a higher pressure employing a nozzle/diffuser/mixing chamber combination. A primary fluid is usually allowed to pass through a converging-diverging nozzle where it can accelerate to supersonic speeds at the nozzle exit. The relatively high kinetic energy that the primary fluid possesses at the nozzle exit is accompanied by a low pressure region in order to satisfy Bernoulli's equation. The low pressure region downstream of the nozzle exit permits a secondary fluid to be entrained into and mixed with the primary fluid in a mixing chamber located downstream of the nozzle. Several combinations may exist in terms of the nature of the primary and secondary fluids in so far as whether they are single or two-phase fluids. Depending on this, the jet pump may be classified as gas/gas, gas/liquid, liquid/liquid, two-phase/liquid, or similar combinations. The mixing chamber serves to create a homogeneous single-phase or two-phase mixture which enters a diffuser where the high kinetic energy of the fluid is converted into pressure energy. If the fluid mixture entering the diffuser is in the supersonic flow regime, a normal shock wave usually develops inside the diffuser. If the fluid mixture is one that can easily change phase, a condensation shock would normally develop. Because of the overall rise in pressure in the diffuser as well as the additional rise in pressure across the shock layer, condensation becomes more likely. Associated with the pressure rise across the shock is a velocity reduction from the supersonic to the subsonic range. If the two-phase flow entering the diffuser is predominantly gaseous with liquid droplets suspended in it, it will transform into a predominantly liquid flow containing gaseous bubbles (bubbly flow) somewhere in the diffuser. While past researchers have been able to model the two-phase flow jet pump using the one-dimensional assumption with no shock waves and no phase change, there is no research known to the authors apart from that of Anand (1992) which accounted for condensation shocks. One of the objectives of this research effort is to develop a comprehensive model in which the effects of phase slip and inter-phase heat transfer as well as the wall friction and shock waves are accounted for. While this modeling effort is predominantly analytical in nature and is primarily intended to provide a parametric understanding of the jet pump performance under different operating scenarios, another parallel effort employing a commercial CFD code is also implemented. The latter effort is primarily intended to model an axisymmetric counterpart of the problem in question. The viability of using the CFD code to model a two-phase flow jet pump will be assessed by attempting to recreate some of the existing performance data of similar jet pumps. The code will eventually be used to generate the jet pump performance characteristics of several scenarios involving jet pump geometries as well as flow regimes in order to be able to determine an optimum design which would be suitable for a two-phase flow boiling test facility at NASA-Marshall. Because of the extensive nature of the analytical model developed, the following section will only provide very brief highlights of it, while leaving the details to a more complete report submitted to the NASA colleague. This report will also contain some of the simulation results obtained using the CFD code.

Sherif, S. A.↗

NASA NTRS2016

Pluto is the new Mars!

Data from NASA's New Horizons encounter with Pluto in July 2015 revealed an astoundingly complex world. The surface seen on the encounter hemisphere ranged in age from ancient to recent. A vast craterless plain of slowly convecting solid nitrogen resides in a deep primordial impact basin, reminiscent of young enigmatic deposits in Mars' Hellas basin. Like Mars, regions of Pluto are dominated by valleys, though the Pluto valleys are thought to be carved by nitrogen glaciers. Pluto has fretted terrain and halo craters. Pluto is cut by tectonics of several different ages. Like Mars, vast tracts on Pluto are mantled by dust and volatiles. Just as on Mars, Pluto has landscapes that systematically vary with latitude due to past and present seasonal (and mega-seasonal) effects on two major volatiles. On Mars, those volatiles are H2O and CO2; on Pluto they are CH4 and N2. Like Mars, some landscapes on Pluto defy easy explanation. In the Plutonian arctic there is a region of large (approx. 40 km across) deep (approx. 3-4 km) pits that probably could not be formed by sublimation, or any other single process, alone. Equally bizarre is the Bladed terrain, which is composed of fields of often roughly aligned blade-like ridges covering the flanks and crests of broad regional swells. Topping the unexpected are two large mounds approximately150 km across, approx. 5-6 km high, with great central depressions at their summits. The central depressions are almost as deep as the mounds are tall. These mounds have many of the characteristics of volcanic mountains seen on Mars and elsewhere in the inner solar system. Hypotheses for the formation of these Plutonian mounds so far all have challenges, principally revolving around the need for H2O ice to support their relief and the difficulty imagining mechanisms that would mobilize H2O. From the perspective of one year after the encounter, our appreciation of the extent of Pluto's diversity and complexity is quite reminiscent of the perspective the science community had of Mars, with similar quality data sets, soon after the early reconnaissance of that planet in the late 1960s and early 70s. So certainly in this sense, Pluto is the new Mars.

Pluto↗

NASA NTRS1995

Visualization tools for the processing of airglow data from RAIDS

In anticipation of large data sets associated with a number of atmospheric imaging instruments being prepared for long term global coverage, NRL is developing graphical interfaces for all aspects of the program. For the first of these projects, RAIDS (the Remote Atmospheric and Ionospheric Detection System), a graphical approach to data handling, visualization, and analysis is envisioned and will set the stage for the satellites that follow. An overall system of hardware and a set of software 'tools,' that will allow for both the routine handling of all data and the analysis of large data sets assembled by scientists and instrument engineers, are currently being developed. The software for standard processing and visualization of instrument data is independent of computer platform and will allow for easy adaptation from one experiment to another. The processing will produce data sets that have similar characteristics, allowing for easy comparison of data obtained under similar circumstances. The visualization of both the engineering and scientific data is an important part of the system. By creating graphical environments for engineering evaluations and for scientific analysis data sets can be viewed and analyzed rapidly. This rapid analysis of data will contribute towards a greater portion of the RAIDS data being utilized.

Miller, Gordon J.↗

DOE OSTI2023

Spatiotemporal Changes in Trace Metal Bioavailability in the Sediment Pore water of a Constructed Wetland Using Passive Pore water Samplers

Sediments in aquatic systems often act as a major sink for contaminants. Diffusive gradient in thin films (DGTs) and in situ equilibrium dialysis samplers (peepers) are two major in situ pore water sampling devices that overcome the problems associated with conventional pore water sampling methods. In the present study, DGTs and peepers were used to study the spatial and seasonal effects (cool months, October–February; warm months, May–September) on metal bioavailability in the H‐02 constructed wetland and the sink versus source role of the sediments by calculating the metal resupply capacity. Data showed similar seasonal trends in metal concentrations using passive samplers, peepers, and DGTs. Pooled Cu and Zn concentrations measured using DGTs were lower in warm months (1.67 ± 1.50 and 2.62 ± 0.68 μg L –1 , respectively, p < 0.001) versus in cool months (2.12 ± 0.65 and 5.58 ± 1.33 μg L –1 , respectively, p < 0.001; mean ± 95% confidence interval). Sulfate (SO 4 2− ) concentrations were significantly (p = 0.0139) lower in warm months (averaged at 0.22 ± 0.05 mg L –1 ) compared to in cool months (0.16 ± 0.05 mg L –1 ). The increase in SO 4 2− concentration is an indicator of the lower activity of sulfate‐reducing bacteria, which need SO 4 2− during anaerobic respiration, in which SO 4 2− is reduced to sulfide (S 2– ) that forms insoluble salts with Cu and Zn, which could partially explain the higher bioavailability of these metals in the cool season. Metal resupply capacity of the sediments was mostly <0.2 for Cu and Zn. Taken together, the H0‐2 wetland sediments mostly acted as a sink to both Cu and Zn over the course of the present study. Environ Toxicol Chem 2023;42:2726–2736. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Spatial and temporal overlap between hatchery- and natural-origin steelhead and Chinook Salmon during spawning in the Klickitat River, Washington, USA

Abstract Objective A goal of many segregated salmonid hatchery programs is to minimize potential interbreeding between hatchery- and natural-origin fish. Our objective was to assess this on the Klickitat River, Washington, USA. Methods We used radiotelemetry to evaluate spatiotemporal spawning overlap between hatchery- and natural-origin steelhead Oncorhynchus mykiss and spring Chinook Salmon O. tshawytscha. We estimated percentages of tagged fish that spawned naturally in the Klickitat River subbasin, emigrated from the Klickitat River, or died before spawning. A kernel density analysis was used to estimate probability of spatiotemporal overlap between hatchery- and natural-origin spawners. Result For steelhead, 12% of hatchery-origin and 50% of natural-origin fish spawned naturally. For spring Chinook Salmon, 18% of hatchery-origin and 44% of natural-origin fish spawned naturally. Tag loss may result in underestimates in these percentages. Most hatchery-origin steelhead (90%) spawned downstream of river kilometer (rkm) 32, and 75% spawned from November to mid-March. The majority of natural-origin steelhead (64%) spawned upstream of rkm 32, and 75% spawned from mid-March to late May. Spawn timing of hatchery-origin Chinook Salmon (early August to mid-September) overlapped with that of natural-origin Chinook Salmon (late July to late September), and fish of both origins spawned in the same 30-km reach of the river. We estimated the percentage of hatchery-origin spawners (pHOS) on the natural spawning grounds to be 12% for steelhead and 40% for spring Chinook Salmon across all study years. For steelhead, we estimated the overlap probability to be 25% (95% CI = 22.5–28%). For spring Chinook Salmon, tight spatial clustering of hatchery-origin fish resulted in a lower overlap estimate of 21% (13–31%). Conclusion We suggest adjusting pHOS estimates using these overlap estimates or similar spatiotemporal data on actual spawner proximity and possible interactions, and that these types of analyses be used in conjunction with gene flow analysis to accurately evaluate effects of individual hatchery programs.

Zendt, Joseph S.↗

DOE OSTI2022

Probing eddy size and its effective mixing length in stably stratified roughness sublayer flows

Stably stratified roughness sublayer flows are ubiquitous yet remain difficult to represent in models and to interpret using field experiments. Here, continuous high-frequency potential temperature profiles from the forest floor up to 6.5 times the canopy height observed with distributed temperature sensing (DTS) are used to link eddy topology to roughness sublayer stability correction functions and coupling between air layers within and above the canopy. The experiments are conducted at two forest stands classified as hydrodynamically sparse and dense. Near-continuous profiles of eddy sizes (length scales) and effective mixing lengths for heat are derived from the observed profiles using a novel conditional sampling approach. The approach utilizes potential temperature isoline fluctuations from a statically stable background state. The transport of potential temperature by an observed eddy is assumed to be conserved (adiabatic movement) and we assume that irreversible heat exchange between the eddy and the surrounding background occurs along the (vertical) periphery of the eddy. This assumption is analogous to Prandtl's mixing-length concept, where momentum is transported rapidly vertically and then equilibrated with the local mean velocity gradient. A distinct dependence of the derived length scales on background stratification, height above ground, and canopy characteristics emerges from the observed profiles. Implications of these findings for (1) the failure of Monin–Obukhov similarity in the roughness sublayer and (2) above-canopy flow coupling to the forest floor are examined. The findings have practical applications in terms of analysing similar DTS data sets with the proposed approach, modelling roughness sublayer flows, and interpreting nocturnal eddy covariance measurements above tall forested canopies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Using a Genetic Algorithm to Optimize Configurations in a Data-Driven Application

Users of highly-configurable software systems often want to optimize a particular objective such as improving a functional outcome or increasing system performance. One approach is to use an evolutionary algorithm. However, many applications today are data-driven, meaning they depend on inputs or data which can be complex and varied. Hence, a search needs to be run (and re-run) for all inputs, making optimization a heavy-weight and potentially impractical process. In this paper, we explore this issue on a data-driven highly-configurable scientific application. We build an exhaustive database containing 3,000 configurations and 10,000 inputs, leading to almost 100 million records as our oracle, and then run a genetic algorithm individually on each of the 10,000 inputs. We ask if (1) a genetic algorithm can find configurations to improve functional objectives; (2) whether patterns of best configurations over all input data emerge; and (3) if we can we use sampling to approximate the results. We find that the original (default) configuration is best only 34% of the time, while clear patterns emerge of other best configurations. Out of 3,000 possible configurations, only 112 distinct configurations achieve the optimal result at least once across all 10,000 inputs, suggesting the potential for lighter weight optimization approaches. We show that sampling of the input data finds similar patterns at a lower cost.

Sinha, Urjoshi↗

DOE OSTI2021

Two-zone stratified wetwell model development and implementation for RELAP-7

The Reactor Core Isolation Cooling (RCIC) system consists of a turbine, pump and wetwell and is used in many US Boiling Water Reactors (BWRs) as an important heat removal system. The wetwell is a major heat sink within containment. Experimental investigations have shown that thermal stratification may occur in the wetwell during RCIC operation. Current systems-level analysis codes lack stratified wetwell models. Here, this paper describes the development of a stratified wetwell model for the RELAP-7 code. This paper uses a simple two-zone model for the wetwell water that can capture thermal stratification. This model assumes that a buoyant plume transports heat and mass from the steam injection site to the upper water zone. The buoyant plume assumption requires that steam is injected at a low enough rate so it adds negligible momentum. Model validation against experimental data shows similar trends of temperature field development in the suppression pool.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Applying a Compact Porous Media Model to Numerically Derive Resistance Coefficients for Lattice Structures

Additive Manufacturing allows for exploring various geometries to achieve specific engineering criteria. Lattices are one geometry with unique properties, including being periodically repeating structures which allow flow through them to be represented as a porous media according to Darcy-Forchheimer equations. These equation’s coefficients are generally experimentally derived, but this work demonstrates the ability to numerically derive them with CFD. Simulations were performed using three-dimensional stead state Reynolds-averaged Navier-Stokes with a k-ω Shear Stress Transport turbulence model using Ansys Fluent. Three lattice geometries were investigated and drag coefficients were derived. The method was validated against externally published data for similar geometries demonstrating strong agreement, and grid convergence for all simulations was calculated with a Grid Convergence Index method. Wall roughness is demonstrated to have a non-negligible impact on results and roughness values are considered for the primary focus Octahedral geometry where both smooth wall and rough wall coefficients were derived. The porosity coefficients for the Octahedral geometry at 1.0 [m/s] were found to be 2.89×10 6 and 2.90×10 6 [1/(Pa*m*s)] for the permeability coefficients, 6.37×10 1 and 5.44×10 1 [m 2 /kg] for the inertial resistance coefficients, and with a max pressure drop of 5116.7 [Pa] and 4429.5 [Pa] for the smooth walls and rough walls, respectively. The derived numerical method enables rapid exploration and optimization of new lattice designs for diverse engineering applications.

42 ENGINEERING↗

DOE OSTI2024

A mesoscale 3D model of irradiated concrete informed via a 2.5 U-Net semantic segmentation

The concrete biological shield in light-water reactors is exposed to neutron and gamma irradiation, which deteriorates the concrete’s mechanical properties in the long term. To assess the irradiation-induced damage, predictive mechanical models are developed and used in parallel with the characterization of irradiated concrete samples. Realistic 3D simulation domains can drastically improve a model’s prediction. In this work, we utilized x-ray computed tomography (XCT) data of a concrete specimen to reconstruct its 3D microstructure. The XCT data shows low contrast between the concrete’s aggregates and cement paste, resulting in poor image segmentation when using traditional unsupervised techniques. To address this issue, we developed and trained a 2.5D U-Net model on only 24 pre-labeled XCT layers to segment 651 layers of the XCT data. The overall F1-score of the model is approximately 96%. Then, we created a 3D finite element (FE) mesh based on the stack of segmented images. The FE model contains radiation-induced expansion, damage, and creep. The constitutive equations are adapted to each phase (aggregates and cement paste). Here, we simulated the effects of neutron irradiation in the concrete specimen as well as the specimen’s mechanical response to uniaxial compression. Finally, model validation was performed using experimental data on similar concrete specimens in the literature.

2.5D U-Net↗

DOE OSTI2025

Common Column Identification for Table Similarity Detection in Electrified Transportation Data Lakes

Electrified transportation often requires researchers and operators to interact with datasets from a wide range of sources and disciplines, such as transportation, power systems, public health, policies, and regulations. These datasets vary in quality and format, making it difficult to understand, preprocess, and identify key columns representing real-world entities or values for indexing and joining, which can negatively impact downstream analysis and operation. Existing solutions are limited, requiring extensive manual customization or data expertise to utilize. In this article, we propose a multi-layered approach to automatically identify key columns to expedite preprocessing and aid in analysis of electrified transportation data. Our method leverages a dynamic ontology to identify common fields and an information theory-based strategy for edge cases that are difficult to generalize. Evaluations on a number of datasets from data.gov and kaggle.com show improved performance of our methods over several baseline techniques, and our ablation analyses illustrate the efficacy of individual components of our method. Our case studies also demonstrate that our methods have the potential to improve analysis of electrified transportation data and aid in automatic integration of such datasets.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

Strong Ferromagnetic Exchange Coupling and Single-Molecule Magnetism in MoS 4 3– -Bridged Dilanthanide Complexes

We report the synthesis and characterization of the trinuclear 4d-4f compounds [Co(C 5 Me 5 ) 2 ][(C 5 Me 5 ) 2 Ln(μ-S) 2 Mo(μ-S) 2 Ln(C 5 Me 5 ) 2 ], 1-Ln (Ln = Y, Gd, Tb, Dy), containing the highly polarizable MoS 4 3 - bridging unit. UV-Vis-NIR diffuse reflectance spectra and DFT calculations of 1-Ln reveal a low-energy metal-to-metal charge transfer transition assigned to charge transfer from the singly occupied 4d z 2 orbital of Mo V to the empty 5d orbitals of the lanthanides (4d in the case of 1-Y ), mediated by sulfur-based 3p orbitals. Electron paramagnetic resonance spectra collected for 1-Y in a tetrahydrofuran solution show large 89 Y hyperfine coupling constants of A ⊥ = 23 MHz and A || = 26 MHz, indicating the presence of significant yttrium-localized unpaired electron density. Magnetic susceptibility data support similar electron delocalization and ferromagnetic Ln-Mo exchange for 1-Gd , 1-Tb , and 1-Dy . This ferromagnetic exchange gives rise to an S = 15/2 ground state for 1-Gd and one of the largest magnetic exchange constants involving Gd III observed to date, with J Gd-Mo = +16.1(2) cm -1 . Additional characterization of 1-Tb and 1-Dy by ac magnetic susceptibility measurements reveals that both compounds exhibit slow magnetic relaxation. Although a Raman magnetic relaxation process is dominant for both 1-Tb and 1-Dy , an extracted thermal relaxation barrier of U eff = 68 cm -1 for 1-Dy is the largest yet reported for a complex containing a paramagnetic 4d metal center. Furthermore, these results provide a potentially generalizable route to enhanced n d-4f magnetic exchange, revealing opportunities for the design of new n d-4f single-molecule magnets and bulk magnetic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Molecular basis of force-pCa relation in MYL2 cardiomyopathy mice: Role of the super-relaxed state of myosin

Here, in this study, we investigated the role of the super-relaxed (SRX) state of myosin in the structure–function relationship of sarcomeres in the hearts of mouse models of cardiomyopathy-bearing mutations in the human ventricular regulatory light chain (RLC, MYL2 gene). Skinned papillary muscles from hypertrophic (HCM–D166V) and dilated (DCM–D94A) cardiomyopathy models were subjected to small-angle X-ray diffraction simultaneously with isometric force measurements to obtain the interfilament lattice spacing and equatorial intensity ratios (I 11 /I 10 ) together with the force-pCa relationship over a full range of [Ca 2+ ] and at a sarcomere length of 2.1 μm. In parallel, we studied the effect of mutations on the ATP-dependent myosin energetic states. Compared with wild-type (WT) and DCM–D94A mice, HCM–D166V significantly increased the Ca 2+ sensitivity of force and left shifted the I 11 /I 10 -pCa relationship, indicating an apparent movement of HCM–D166V cross-bridges closer to actin-containing thin filaments, thereby allowing for their premature Ca 2+ activation. The HCM–D166V model also disrupted the SRX state and promoted an SRX-to-DRX (super-relaxed to disordered relaxed) transition that correlated with an HCM-linked phenotype of hypercontractility. While this dysregulation of SRX ↔ DRX equilibrium was consistent with repositioning of myosin motors closer to the thin filaments and with increased force-pCa dependence for HCM–D166V, the DCM–D94A model favored the energy-conserving SRX state, but the structure/function–pCa data were similar to WT. Our results suggest that the mutation-induced redistribution of myosin energetic states is one of the key mechanisms contributing to the development of complex clinical phenotypes associated with human HCM–D166V and DCM–D94A mutations.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Coupled Monte Carlo Transport and Conjugate Heat Transfer for Wire-Wrapped Bundles Within the MOOSE Framework

Cardinal is an open-source application that couples OpenMC Monte Carlo transport and NekRS computational fluid dynamics (CFD) to the Multiphysics Object-Oriented Simulation Environment (MOOSE), closing neutronics and thermal-fluid gaps in conducting high-resolution multiscale and multiphysics analyses of nuclear systems. We first provide a brief introduction to Cardinal's software design, data mapping, and coupling strategy to highlight our approach to overcoming common challenges in high-fidelity multiphysics simulations. Here we then present two Cardinal simulations for hexagonal pin bundles. The first is a validation of Cardinal's conjugate heat transfer coupling of NekRS's Reynolds-Averaged Navier Stokes model with MOOSE's heat conduction physics for a bare seven-pin Freon-12 bundle flow experiment. Predictions for pin surface temperatures under three different heating modes agree reasonably well with experimental data and similar CFD modeling from the literature. The second simulation is a multiphysics coupling of OpenMC, NekRS, and BISON for a reduced-scale, seven-pin wire-wrapped version of an Advanced Burner Reactor bundle. Wire wraps are approximated using a momentum source model, and coupled predictions are provided for velocity, temperature, and power distribution.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Characterization of turbulence under different stability conditions using lidar scanning data

The spatiotemporal scales of turbulence in the boundary layer flow vary with the static stability of the atmosphere. For example, turbulence structures in unstable conditions are often found to be large and coherent, whereas the turbulent structures in stable conditions are relatively small and sporadic. To better understand the behavior of such turbulent structures under different atmospheric stability conditions in the lower atmosphere, herein, we use scanning lidar data collected over several months during the US Department of Energy's second Wind Forecast Improvement Project (WFIP 2) in 2016. The radial velocity data from scanning lidar were gathered along the horizontal plane (PPI mode) and were analyzed using proper orthogonal decomposition (POD) and spectral energy methods. The results from these analyses show that the turbulent structures in daytime unstable conditions are different from those present during nighttime stable conditions in terms of amount of energy and coherent structures. The POD energy is distributed more evenly in all the higher spatial modes in the daytime unstable case compared to the nighttime stable case. Besides characterizing the turbulence in the flow, the lidar data were also used to compare the simulated flow field generated from the WRF-LES framework (Weather Research and Forecasting - large-eddy simulation) with the scanning lidar data. The results from both simulated and lidar scanned data show similar structures orienting the streak-like structure along the mean wind. This indicates that the streak-like structures can exist in the real atmosphere during unstable atmospheric condition cases.

Rai, Raj K.↗

DOE OSTI2022

Structure of Offshore Low-Level Jet Turbulence and Implications to Mesoscale-to-Microscale Coupling

This paper explores realistic nonstationary atmospheric boundary layer (ABL) turbulence arising from nonstationarity at the mesoscale, particularly within offshore low-level jets with implications to offshore wind farms, using high-fidelity multiscale large-eddy simulations (LES). To this end, we analyzed the single-point turbulence statistical structure of a North-Atlantic offshore LLJ event simulated using high-resolution LES (AMR-Wind). The nonstationary LLJ is simulated using a mesoscale-to-microscale coupled (MMC) simulation procedure involving data assimilation of mesoscale velocity and temperature data from the Weather Research and Forecasting (WRF) model. Unlike the assimilation of mesoscale velocity data into the LES, the direct assimilation of temperature profiles had a strong impact on turbulence stratification, thereby causing erroneous predictions of turbulence both above and within the jet layer. Various approaches to mitigate this effect have resulted in multiple (four) variants of this MMC strategy. Outcomes from this work clearly show that the turbulence within the low-level jet is a strong function of the MMC approach as the turbulence structure within the low-level jet is dependent on the flux of residual turbulence from outside the jet, which in turn depends on the temperature forcing history. Additionally, the turbulence predicted by all these different methods (as well as the observation data) show similar deviations from equilibrium as evidenced by comparisons with idealized atmospheric turbulence structure obtained using the same numerical method. In general, we observe that the predicted LLJ turbulence tends to differ from canonical ABL turbulence with comparable shear. Particularly, the combination of shear and turbulence observed in such nonstationary low-level turbulence cannot be matched using equilibrium settings and therefore, represents a critical use-case for both testing and leveraging meso–micro coupling strategies.

17 WIND ENERGY↗