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

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At least 343 records · Page 19

Part-scale evolution of fine-scale microstructural heterogeneity in solid-state additive manufacturing

Current solid-state additive manufacturing methods, refined through costly and time-consuming trial and error, have spurred interest in computational models that replicate material behavior under typical thermomechanical conditions (e.g., strain-rate ~ 102 s−1). These models, however, struggle to capture time-dependent microstructural evolution. In this work, Additive Friction-Stir Deposition (AFSD) is used as a representative case study for part-scale quantification of microstructure evolution at a fine spatial resolution (200 μm) by examining a liquid-nitrogen-cooled stop-action build via energy-dispersive X-ray diffraction coupled with a multi-channel detector. These results inform modeling efforts by linking process asymmetry to stored plastic strain, residual elastic strain, and texture development, and unlike current state-of-the-art characterization methods (e.g., EBSD or neutron diffraction), this approach provides both the spatial resolution and collection efficiency necessary to quantify fine-scale microstructural heterogeneity over large component volumes. As such, this technique provides essential validation data for computational models, e.g., crystal plasticity, enabling future prediction of heterogeneous behavior in AFSD and other additive manufacturing processes.

Franz, Cole [ORNL] (ORCID:0000000213465881)↗

Population genomics and history of speciation reveal fishery management gaps in two related redfish species ( Sebastes mentella and Sebastes fasciatus )

Abstract Understanding the processes shaping population structure and reproductive isolation of marine organisms can improve their management and conservation. Using genomic markers combined with estimation of individual ancestries, assignment tests, spatial ecology, and demographic modeling, we (i) characterized the contemporary population structure, (ii) assessed the influence of space, fishing depth, and sampling years on contemporary distribution, and (iii) reconstructed the speciation history of two cryptic redfish species, Sebastes mentella and S. fasciatus . We genotyped 860 individuals in the Northwest Atlantic Ocean using 24,603 filtered single nucleotide polymorphisms (SNPs). Our results confirmed the clear genetic distinctiveness of the two species and identified three ecotypes within S. mentella and five populations in S. fasciatus . Multivariate analyses highlighted the influence of spatial distribution and depth on the overall genomic variation, while demographic modeling revealed that secondary contact models best explained inter‐ and intragenomic divergence. These species, ecotypes, and populations can be considered as a rare and wide continuum of genomic divergence in the marine environment. This acquired knowledge pertaining to the evolutionary processes driving population divergence and reproductive isolation will help optimizing the assessment of demographic units and possibly to refine fishery management units.

Benestan, Laura M.↗

gdess: A framework for evaluating simulated atmospheric CO 2 in Earth System Models

Atmospheric carbon dioxide (CO 2 ) plays a key role in the global carbon cycle and global warming. Climate-carbon feedbacks are often studied and estimated using Earth System Models (ESMs), which couple together multiple model components—including the atmosphere, ocean, terrestrial biosphere, and cryosphere—to jointly simulate mass and energy exchanges within and between these components. Despite tremendous advances, model intercomparisons and benchmarking are aspects of ESMs that warrant further improvement (Fer et al., 2021; Smith et al., 2014). Such benchmarking is critical because comparing the value of state variables in these simulations against observed values provides evidence for appropriately refining model components; moreover, researchers can learn much about Earth system dynamics in the process (Randall et al., 2019). We introduce `gdess` (a.k.a., Greenhouse gas Diagnostics for Earth System Simulations), which parses observational datasets and ESM simulation output, combines them to be in a consistent structure, computes statistical metrics, and generates diagnostic visualizations. In its current incarnation, `gdess` facilitates evaluating a model's ability to reproduce observed temporal and spatial variations of atmospheric CO 2 . The diagnostics implemented modularly in `gdess` support more rapid assessment and improvement of model-simulated global CO 2 sources and sinks associated with land and ocean ecosystem processes. We intend for this set of automated diagnostics to form an extensible, open source framework for future comparisons of simulated and observed concentrations of various greenhouse gases across Earth system models.

97 MATHEMATICS AND COMPUTING↗

Development of Scalable Reactive Transport Framework for PFAS

Research on PFAS chemicals is extensive and covers all aspects, including analytical quantification, determination of properties, toxicology, ex situ treatment, and in situ remediation. PFAS chemicals are very stable and thus persistent/recalcitrant in the environment. Although there are many unknowns about PFAS chemicals, degradation pathways, reaction rates, etc., many different sorption, oxidation, reduction, biological, and innovative treatment approaches are being developed. Sorption with activated carbon is currently the only fully available in situ treatment technology for PFAS-impacted groundwater. Given the wide array of PFAS chemicals and transformation products, remediation may need multi-step treatment trains to fully address the PFAS contamination. The work here provides kinetic reaction modules that represent an initial cut at functionality representing PFAS migration and reaction in groundwater aquifer flow and transport models. One reaction kinetics module provides a method to model kinetically limited adsorption using a mass transfer model. The second reaction module represents biological transformation of 8:2 FTOH and daughter species, illustrating how a complex reaction pathway network can be represented. Both reaction modules allow for spatially variable parameter values so that a variety of remediation approaches (e.g., a PRB or volumetric treatment or variations in geochemical conditions) can be simulated. The intent with these PFAS reaction modules is to provide tools for practitioners to aid in the selection, design, and assessment of potential in situ PFAS remediation strategies. It is anticipated that, as PFAS remediation technologies and scientific understanding advances, these modules would be refined or replaced to match new knowledge.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Diagnosing Open Cluster Stock 2: Member Candidates and Mass Distribution with Gaia DR2 and LAMOST

We identify 1325 member candidates of the open cluster (OC) Stock 2 using data from Gaia DR2. We use the algorithms Clusterix 2.0 and HDBSCAN to select cluster candidates and further refine the final cluster membership by defining neighbors in 5D phase space (X {sub cp}, Y {sub cp}, Z{sub cp},κ⋅μ{sub α}{sup ∗}/ϖ, κ · μ {sub δ}/ϖ). Among these candidates, less than half have G, G {sub BP}, and G {sub RP} extinctions from Gaia. When Gaia extinctions are unavailable, we compute extiction using empirical formulas and E(B − V) = 0.350. We analyze the spatial distribution and mass profile of Stock 2. Our results reveal Stock 2 is still a bound OC and we find evidence of mass segregation. By comparing initial mass functions, the present-day mass function indicates that Stock 2 is a massive stellar cluster with a mass of 4000 M {sub ⊙}. The core radius and tidal radius, calculated via the radial density profile and total mass, are 3.97 pc and 22.65 pc, respectively. Common stars between our selected member candidates and the Large Sky Area Multi-Object Fiber Spectroscopic Telescope DR7 medium-resolution catalog give a metalliclity of [Fe/H] = −0.040 ± 0.147.

47 OTHER INSTRUMENTATION↗

Multiscale assessment of North American terrestrial carbon balance

Abstract. Comparisons of carbon uptake estimates from bottom-up terrestrial biosphere models (TBMs) to top-down atmospheric inversions help assess how well we understand carbon dioxide (CO2) exchange between the atmosphere and terrestrial biosphere. Previous comparisons have shown varying levels of agreement between bottom-up and top-down approaches, but they have almost exclusively focused on large, aggregated scales (e.g., global or continental), providing limited insights into reasons for the mismatches. Here we explore how consistency, defined as the spread in net ecosystem exchange (NEE) estimates within an ensemble of TBMs or inversions, varies with at finer spatial scales ranging from 1∘×1∘ to the continent of North America. We also evaluate how well consistency informs accuracy in overall NEE estimates by filtering models based on their agreement with the variability, magnitude, and seasonality in observed atmospheric CO2 drawdowns or enhancements. We find that TBMs produce more consistent estimates of NEE for most regions and at most scales relative to inversions. Filtering models using atmospheric CO2 metrics causes ensemble spread to decrease substantially for TBMs, but not for inversions. This suggests that ensemble spread is likely not a reliable measure of the uncertainty associated with the North American carbon balance at any spatial scale. Promisingly, applying atmospheric CO2 metrics leads to a set of models with converging flux estimates across TBMs and inversions. Overall, we show that multiscale assessment of the agreement between bottom-up and top-down NEE estimates, aided by regional-scale observational constraints is a promising path towards identifying fine-scale sources of uncertainty and improving both ensemble consistency and accuracy. These findings help refine our understanding of biospheric carbon balance, particularly at scales relevant for informing regional carbon-climate feedbacks.

54 ENVIRONMENTAL SCIENCES↗

Application of Remote Sensing to Assess the Impact of Short Term Climate Variability on Coastal Sedimentation

The purpose of this joint University of Wisconsin (UW) and Louisiana State University (LSU) project has been to relate short term climate variation to response in the coastal zone of Louisiana in an attempt to better understand how the coastal zone is shaped by climate variation. Climate variation in this case largely refers to variation in surface wind conditions that affect wave action and water currents in the coastal zone. The primary region of focus was the Atchafalaya Bay and surrounding bays in the central coastal region of Louisiana. Suspended solids in the water column show response to wind systems both in quantity (through resuspension) and in the pattern of dispersement or transport. Wind systems associated with cold fronts are influenced by short term climate variation. Wind energy was used as the primary signature of climate variation in this study because winds are a significant influence on sediment transport in the micro-tidal Gilf of Mexico coastal zone. Using case studies, the project has been able to investigate the influence of short term climate variation on sediment transport. Wind energy data, collected daily for National Weather Service (NWS) stations at Lake Charles and New Orleans, LA, were used as an indicator of short term climate variation influence on seasonal time scales. A goal was to relate wind energy to coastal impact through sediment transport. This goal was partially accomplished by combining remote sensing and wind energy data. Daily high resolution remote sensing observations are needed to monitor the complex coastal zone environment, where winds, tides, and water level all interact to influence sediment transport. The NASA Earth Observing System (EOS) era brings hope for documenting and revealing response of the complex coastal transport mosaic through regular high spatial resolution observations from the Moderate resolution Imaging Spectrometer (MODIS) instrument. MODIS observations were sampled in this project for information content and should continue to be viewed as a resource for coastal zone monitoring. The project initialized the effort to transfer a suspended sediment concentration (SSC) algorithm to the MODIS platform for case 2 waters. MODIS enables monitoring of turbid coastal zones around the globe. The MODIS SSC algorithm requires refinements in the atmospheric aerosol contribution, sun glint influence, and designation of the sediment inherent optical properties (IOPs); the framework for continued development is in place with a plan to release the algorithm to the MODIS direct broadcast community.

Menzel, W. Paul↗

Evaluation of spatial, radiometric and spectral Thematic Mapper performance for coastal studies

A series of experiments were initiated to determine the feasibility of using thematic mapper spectral data to estimate wetlands biomass. The experiments were conducted using hand-held radiometers simulating thematic mapper wavebands 3, 4 and 5. Spectral radiance data were collected from the ground and from a low altitude aircraft in an attempt to gain some insight into the potential utility of actual thematic mapper data for biomass estimation in wetland plant communities. In addition, radiative transfer models describing volume reflectance of eight water column containing submerged aquatic vegetation were refined.

Klemas, V.↗

Non-Gaussian photonic state engineering with the quantum frequency processor

Non-Gaussian quantum states of light are critical resources for optical quantum information processing, but methods to generate them efficiently remain challenging to implement. Here we introduce a generic approach for non-Gaussian state production from input states populating discrete frequency bins. Based on controllable unitary operations with a quantum frequency processor, followed by photon-number-resolved detection of ancilla modes, our method combines recent developments in both frequency-based quantum information and non-Gaussian state preparation. Leveraging and refining the K-function representation of quantum states in the coherent basis, we develop a theoretical model amenable to numerical optimization and, as specific examples, design quantum frequency processor circuits for the production of Schrödinger cat states, exploring the performance tradeoffs for several combinations of ancilla modes and circuit depth. Our scheme provides a valuable framework for producing complex quantum states in frequency bins, paving the way for single-spatial-mode, fiber-optic-compatible non-Gaussian resources.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Geographical Insights into Suicide Mortality Through Spatial Machine Learning

Suicide mortality is a leading cause of death in the United States, with an upward trend that emphasizes its significance as a public health issue. Previous research has employed global models like ordinary least squares (OLS) regression and local models such as geographically weighted regression (GWR). While local models are useful for analyzing spatial variations in suicide mortality, they share limitations with traditional global models, particularly about their inability to handle multi-collinearity and non-linear relationships. Machine learning approaches, like random forests (RF), can address some of these limitations but often fail to account for spatial variability. This gap highlights the need for spatial ML models specifically designed to tackle suicide mortality. This research seeks to fill this void by using a geographically weighted random forest model (GWRF) to examine the associations between county-level suicide mortality in the U.S. from 2010 to 2020 and various social and environmental determinants of health. A key aspect of our methodology is disciplined feature selection, which reduces the pool of explanatory variables by about 90%. This refinement enhances the explanatory power of both global (R2 improved from 0.59 to 0.67) and local (R2 improved from 0.64 to 0.67) RF models while reducing their run times. An analysis of the importance scores for these selected features reveals that the drivers of suicide mortality vary by context. Thus, to effectively address regional disparities and inform targeted public health interventions, a holistic approach that incorporates multiple county-level characteristics is essential.

Lebakula, Viswadeep [ORNL] (ORCID:0000000152935914↗

Large Area Crop Inventory Experiment (LACIE). Review of LACIE methodology, a project evaluation of technical acceptability

The author has identified the following significant results. Results indicated that the LANDSAT data and the classification technology can estimate the small grains area within a sample segment accurately and reliably enough to meet the LACIE goals. Overall, the LACIE estimates in a 9 x 11 kilometer segment agree well with ground and aircraft determined area within these segments. The estimated c.v. of the random classification error was acceptably small. These analyses confirmed that bias introduced by various factors, such as LANDSAT spatial resolution, lack of spectral resolution, classifier bias, and repeatability, was not excessive in terms of the required performance criterion. Results of these tests did indicate a difficulty in differentiating wheat from other closely related small grains. However, satisfactory wheat area estimates were obtained through the reduction of the small grain area estimates in accordance with relative amounts of these crops as determined from historic data; these procedures are being further refined.

Source record↗

Land Boundary Conditions for the Goddard Earth Observing System Model Version 5 (GEOS-5) Climate Modeling System: Recent Updates and Data File Descriptions

The Earths land surface boundary conditions in the Goddard Earth Observing System version 5 (GEOS-5) modeling system were updated using recent high spatial and temporal resolution global data products. The updates include: (i) construction of a global 10-arcsec land-ocean lakes-ice mask; (ii) incorporation of a 10-arcsec Globcover 2009 land cover dataset; (iii) implementation of Level 12 Pfafstetter hydrologic catchments; (iv) use of hybridized SRTM global topography data; (v) construction of the HWSDv1.21-STATSGO2 merged global 30 arc second soil mineral and carbon data in conjunction with a highly-refined soil classification system; (vi) production of diffuse visible and near-infrared 8-day MODIS albedo climatologies at 30-arcsec from the period 2001-2011; and (vii) production of the GEOLAND2 and MODIS merged 8-day LAI climatology at 30-arcsec for GEOS-5. The global data sets were preprocessed and used to construct global raster data files for the software (mkCatchParam) that computes parameters on catchment-tiles for various atmospheric grids. The updates also include a few bug fixes in mkCatchParam, as well as changes (improvements in algorithms, etc.) to mkCatchParam that allow it to produce tile-space parameters efficiently for high resolution AGCM grids. The update process also includes the construction of data files describing the vegetation type fractions, soil background albedo, nitrogen deposition and mean annual 2m air temperature to be used with the future Catchment CN model and the global stream channel network to be used with the future global runoff routing model. This report provides detailed descriptions of the data production process and data file format of each updated data set.

GEOS-5↗

Elucidating a dissolution–deposition reaction mechanism by multimodal synchrotron X-ray characterization in aqueous Zn/MnO 2 batteries

Aqueous Zn/MnO 2 batteries with their environmental sustainability and competitive cost, are becoming a promising, safe alternative for grid-scale electrochemical energy storage. Here, presented as a promising design principle to deliver a higher theoretical capacity, this work offers fundamental understanding of the dissolution–deposition mechanism of Zn/β-MnO 2 . A multimodal synchrotron characterization approach including three operando X-ray techniques (powder diffraction, absorption spectroscopy, and fluorescence microscopy) is coupled with elementally resolved synchrotron X-ray nano-tomography. Together they provide a direct correlation between structural evolution, reaction chemistry, and 3D morphological changes. Operando synchrotron X-ray diffraction and spectroscopy show a crystalline-to-amorphous phase transition. Quantitative modeling of the operando data by Rietveld refinement for X-ray diffraction and multivariate curve resolution (MCR) for X-ray absorption spectroscopy are used in a complementary fashion to track the structural and chemical transitions of both the long-range (crystalline phases) and short-range (including amorphous phases) ordering upon cycling. Scanning X-ray microscopy and full-field nano-tomography visualizes the morphology of electrodes at different electrochemical states with elemental sensitivity to spatially resolve the formation of the Zn- and Mn-containing phases. Overall, this work critically indicates that for Zn/MnO 2 aqueous batteries, the reaction pathways involving Zn–Mn complex formation upon cycling become independent of the polymorphs of the initial electrode and sheds light on the interplay among structural, chemical, and morphological evolution for electrochemically driven phase transitions.

36 MATERIALS SCIENCE↗

A Hybrid Transfer Function Procedure for Broadband Auralization Within Small Flight Vehicle Interiors

Auralization of the sound fields within flight vehicle interiors is of interest to aircraft designers considering crew and passenger ride quality. Computer models can be used to predict the filtering effects that the fuselage structure and interior volume have on the exterior sound field in order to simulate the resulting cabin interior noise. However, this can become expensive when a wide frequency range of analysis suitable for passenger auralization is desired. This is particularly the case when using deterministic modeling methods such as finite element analysis (FEA) wherein prohibitively high levels of detail and finite element discretizations are required to resolve the wavelengths at high frequencies. On the contrary, Statistical Energy Analysis (SEA), while not capturing important modal behaviors at low frequencies, is better suited for higher frequency analyses where structural and interior dynamics exhibit high modal overlap and spatially averaged physical quantities suffice. For this reason, a hybrid procedure is considered here that utilizes FE modal solutions at lower frequencies and SEA results at higher frequencies. A transfer function dataset containing the exterior to interior vibroacoustic filtering effect is calculated accordingly and subsequently stored to be used for a variety of exterior dynamic load cases. At low frequencies, the transfer function dataset detail is related to the level of FE model refinement whereas at high frequencies it functions as an equalizer array with a level of detail corresponding to the SEA subsystem partitioning scheme. The above procedure is described herein and demonstrated on a six passenger flight vehicle with eight propulsors in a hover flight condition.

auralization↗

A Hybrid Transfer Function Procedure for Broadband Auralization Within Small Flight Vehicle Interiors

Auralization of the sound fields within flight vehicle interiors is of interest to aircraft designers considering crew and passenger ride quality. Computer models can be used to predict the filtering effects that the fuselage structure and interior volume have on the exterior sound field in order to simulate the resulting cabin interior noise. However, this can become expensive when a wide frequency range of analysis suitable for passenger auralization is desired. This is particularly the case when using deterministic modeling methods such as finite element analysis (FEA) wherein prohibitively high levels of detail and finite element discretizations are required to resolve the wavelengths at high frequencies. On the contrary, Statistical Energy Analysis (SEA), while not capturing important modal behaviors at low frequencies, is better suited for higher frequency analyses where structural and interior dynamics exhibit high modal overlap and spatially averaged physical quantities suffice. For this reason, a hybrid procedure is considered here that utilizes FE modal solutions at lower frequencies and SEA results at higher frequencies. A transfer function dataset containing the exterior to interior vibroacoustic filtering effect is calculated accordingly and subsequently stored to be used for a variety of exterior dynamic load cases. At low frequencies, the transfer function dataset detail is related to the level of FE model refinement whereas at high frequencies it functions as an equalizer array with a level of detail corresponding to the SEA subsystem partitioning scheme. The above procedure is described herein and demonstrated on a six passenger flight vehicle with eight propulsors in a hover flight condition.

auralization↗

Gamma rays and large scale galactic structure

Many theoretical models were developed in an attempt to explain the spatial structure in the observed emission which results from interactions of energetic cosmic rays with the interstellar gas. The peaks in the observed distribution are remarkably well correlated with longitudes corresponding to tangential directions to known spiral arm features. Based on theoretical and experimental arguments, it is assumed that on the scale of galactic arms the cosmic rays are more intense where the mass of the gas to which they are coupled is greatest. Refining this model with the results of recent surveys of the interstellar gas, a good fit to the observations is obtained whether the cosmic rays are confined to the spiral arms in the disk or are more evenly confined as in a flat halo model.

Kniffen, D. A.↗

Navier-Stokes Simulation of UH-60A Rotor/Wake Interaction Using Adaptive Mesh Refinement

High-resolution simulations of rotor/vortex-wake interaction for a UH60-A rotor under BVI and dynamic stallconditions were carried out with the OVERFLOW Navier-Stokes code.a. The normal force and pitching moment variation with azimuth angle were in good overall agreementwith flight-test data, similar to other CFD results reported in the literature.b. The wake-grid resolution did not have a significant effect on the rotor-blade airloads. This surprisingresult indicates that a wake grid spacing of (Delta)S=10% ctip is sufficient for engineering airloads predictionfor hover and forward flight. This assumes high-resolution body grids, high-order spatial accuracy, anda hybrid RANS/DDES turbulence model.c. Three-dimensional dynamic stall was found to occur due the presence of blade-tip vortices passing overa rotor blade on the retreating side. This changed the local airfoil angle of attack, causing stall, unlikethe 2D perspective of pure pitch oscillation of the local airfoil section.

CFD Validation↗

Tailoring plasticity mechanisms in compositionally graded hierarchical steels fabricated using additive manufacturing

Abstract While there exists in nature abundant examples of materials with site-specific gradients in microstructures and properties, engineers and designers have traditionally used monolithic materials with discrete properties. Now, however, additive manufacturing (AM) offers the possibility of creating structures that mimic some aspects of nature. One example that has attracted attention in the recent years is the hierarchical structure in bamboo. The hierarchical architecture in bamboo is characterized by spatial gradients in properties and microstructures and is well suited to accommodate and survive complex stress states, severe mechanical forces, and large deformations. While AM has been used routinely to fabricate functionally graded materials, this study distinguishes itself by leveraging AM and physical metallurgy concepts to trigger cascading deformation in a single sample. Specifically, we have been successful in using AM to fabricate steel with unique spatial hierarchies in structure and property to emulate the structure and deformation mechanisms in natural materials. This study shows an improvement in the strength and ductility of the nature-inspired “hierarchical steel” compared with conventional cast stainless steels. In situ characterization proves that this improvement is due to the sequential activation of multiple deformation mechanisms namely twinning, transformation-induced plasticity, and dislocation-based plasticity. While significantly higher strengths can be achieved by refining the chemical and processing technique, this study sets the stage to achieve the paradigm of using AM to fabricate structures which emulate the flexibility in mechanical properties of natural materials and are able to adapt to in-service conditions.

36 MATERIALS SCIENCE↗