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NASA NTRS2005

TERRA/MOPITT Measurements of Tropospheric Carbon Monoxide Distributions in Support of INTEX

Interaction with the ongoing satellite measurements programs was an important goal of INTEX- A. The Terra/MOPITT instrument had been making global measurements of the tropospheric carbon monoxide (CO) distribution for 4 years, and was in a unique position to provide valuable support during the field campaign. Remote sensing of CO directly addressed the scientific questions motivating the IXTEX-A strategy and deployment, and measurement of this gas was rated as being mission critical. CO is an important trace gas in tropospheric chemistry due to its role in determining the atmospheric oxidizing capacity, as an ozone precursor, and as an indicator and tracer of both natural and anthropogenic pollution arising from incomplete combustion. The satellite perspective provided the more general temporal and spatial context to the aircraft and ground-based measurements during the subsequent scientific analysis. We proposed to build on the experience of supplying MOPITT data to previous field campaigns, such as TRACE-P. We provided expedited MOPITT data processing in near real-time, along with basic analysis of the measurements to indicate, where possible, the origin of the CO plumes that impacted the regions of flight operations and other in situ measurement activities. To ensure maximum exploitation of the satellite information, we will also had a scientist in the field to present and interpret the MOPITT data for the INTEX team, and to help ensure its utility in flight planning.

Edwards, D. P.↗
DOE OSTI2022

BISON Validation to In-Situ Cladding Burst Test and High Burnup LOCA Experiments

The process to develop and qualify nuclear fuels for commercial nuclear application requires fundamental material development, characterization, and design; out-of-pile testing on unirradiated materials; integral fuel rod irradiations, testing, and post irradiation examinations (PIEs); and transient analyses. The historical approach depends on the generation of large empirical datasets and series of integral fuel rod irradiations, and this approach ultimately takes approximately 20 years—or sometimes longer—to acquire data through extensive sequential testing. Thus, the qualification and eventual deployment of new fuel systems constitute a long and drawn-out process. However, recent technological advancements have provided researchers the opportunity to perform out-of-cell, in-situ measurements to assess material performance for the duration of the experiment. One such example of this capability is the use of digital image coordination and thermal imaging to assess Zircaloy cladding performance under a simulated loss-of-coolant accident (LOCA) transient condition. In general, the in-situ measurements provide high-fidelity strain, strain rates, and temperature surface maps. This is critical for the United States nuclear industry, which is actively developing a technical basis to support extending the peak rod average burnup from 62 to ~75 GWd/tU and the deployment of accident-tolerant fuel. However, the Nuclear Regulatory Commission, through their research information letter, outlined a number of technical issues for the industry to address before extending burnup. One topic of specific interest is understanding the cladding balloon and rupture geometry during the LOCA heatup phase. Leveraging these advanced in-situ capabilities, this work intends to use insitu data generated from a simulated LOCA in the Severe Accident Test Station at Oak Ridge National Laboratory to better understand high-temperature creep and its impact on Zircaloy balloon and rupture performance. This work used the BISON fuel performance code to compare BISON’s high-temperature creep model predictions to in-situ data and identify limitations and gaps within the model. Additionally, BISON will subsequently be used to simulate relevant high-burnup LOCA tests. The results will be analyzed and compared to the available post-test data in a manner consistent with the approach outlined in the Nuclear Regulatory Commission research information letter.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2018

The Development of the New GEOS-MITgcm Atmosphere-Ocean Model for Coupled Data Assimilation System

During the last two plus decades, The Goddard Earth Observing System (GEOS) and Massachusetts Institute of Technology (MIT) modeling groups have developed, respectively, atmosphere-only and ocean-only global general circulation models. These two models (GEOS and MITgcm) have demonstrated their data assimilation capabilities with the recent releases of the Modern Era Reanalysis for Research Applications, Version 2 (MERRA-2) atmospheric reanalysis and the Estimating the Circulation and Climate of the Ocean, Version 4 (ECCO-v4) ocean (and sea ice) state estimate. Independently, the two modeling groups have also produced global atmosphere-only and ocean-only simulations with km-scale grid spacing which proved invaluable for process studies and for the development of satellite and in-situ sampling strategies.Recently, a new effort has been made to couple these two models and to leverage their data-assimilation and high resolution capabilities (i.e., eddy-permitting ocean, cloud-permitting atmosphere). The focus in the model development is put on sub-seasonal to decadal time scales. In this talk, I discuss the new coupled model and present some first coupled simulation results. This will include a high-resolution coupled GEOS-MIT simulation, whereby we have coupled a cubed-sphere-720 (~ 1/8 deg) configuration of the GEOS atmosphere to a lat-lon-cap-1080 (~ 1/12 deg) configuration of the MIT ocean. We compare near-surface diagnostics of this fully coupled ocean-atmosphere set-up to equivalent atmosphere-only and ocean-only simulations. In the comparisons we focus in particular on the differences in air-sea interactions between sea surface temperature (SST) and wind for the coupled and uncoupled simulations.

Strobach, Ehud↗
NASA NTRS2018

A New Atmosphere-Ocean Model for Studying Air-Sea Interactions and Coupled Data Assimilation

During the last two plus decades, The Goddard Earth Observing System (GEOS) and Massachusetts Institute of Technology (MIT) modeling groups have developed, respectively, atmosphere-only and ocean-only global general circulation models. These two models (GEOS and MITgcm) have demonstrated their data assimilation capabilities with the recent releases of the Modern Era Reanalysis for Research Applications, Version 2 (MERRA-2) atmospheric reanalysis and the Estimating the Circulation and Climate of the Ocean, Version 4 (ECCO-v4) ocean (and sea ice) state estimate. Independently, the two modeling groups have also produced global atmosphere-only and ocean-only simulations with km-scale grid spacing which proved invaluable for process studies and for the development of satellite and in-situ sampling strategies.Recently, a new effort has been made to couple these two models and to leverage their data-assimilation and high resolution capabilities (i.e., eddy-permitting ocean, cloud-permitting atmosphere). The focus in the model development is put on sub-seasonal to decadal time scales. In this talk, I discuss the new coupled model and present some first coupled simulation results. This will include a high-resolution coupled GEOS-MIT simulation, whereby we have coupled a cubed-sphere-720 (~ 1/8°) configuration of the GEOS atmosphere to a lat-lon-cap-1080 (~ 1/12°) configuration of the MIT ocean. We compare near-surface diagnostics of this fully coupled ocean-atmosphere set-up to equivalent atmosphere-only and ocean-only simulations. In the comparisons we focus in particular on the differences in air-sea interactions between sea surface temperature (SST) and wind for the coupled and uncoupled simulations.

Strobach, Ehud↗
NASA NTRS2018

The Development of the New GEOS-MITgcm Atmosphere-Ocean Model for Coupled Data Assimilation System

During the last two plus decades, The Goddard Earth Observing System (GEOS) and Massachusetts Institute of Technology (MIT) modeling groups have developed, respectively, atmosphere-only and ocean-only global general circulation models. These two models (GEOS and MITgcm) have demonstrated their data assimilation capabilities with the recent releases of the Modern Era Reanalysis for Research Applications, Version 2 (MERRA-2) atmospheric reanalysis and the Estimating the Circulation and Climate of the Ocean, Version 4 (ECCO-v4) ocean (and sea ice) state estimate. Independently, the two modeling groups have also produced global atmosphere-only and ocean-only simulations with km-scale grid spacing which proved invaluable for process studies and for the development of satellite and in-situ sampling strategies.Recently, a new effort has been made to couple these two models and to leverage their data-assimilation and high resolution capabilities (i.e., eddy-permitting ocean, cloud-permitting atmosphere). The focus in the model development is put on sub-seasonal to decadal time scales. In this talk, I discuss the new coupled model and present some first coupled simulation results. This will include a high-resolution coupled GEOS-MIT simulation, whereby we have coupled a cubed-sphere-720 (~ 1/8°) configuration of the GEOS atmosphere to a lat-lon-cap-1080 (~ 1/12°) configuration of the MIT ocean. We compare near-surface diagnostics of this fully coupled ocean-atmosphere set-up to equivalent atmosphere-only and ocean-only simulations. In the comparisons we focus in particular on the differences in air-sea interactions between sea surface temperature (SST) and wind for the coupled and uncoupled simulations.

Strobach, Ehud↗
DOE OSTI2025

Self‐Assembly Methods Induce Different Individual‐Polymer‐Block Solvation Responses

An understanding of block-specific responses to stimuli in self-assembled copolymers is essential for the effective design of responsive materials. Here, materials formed from different post-reaction processing methods of the same ROMP block copolymer exhibit different block-specific solvent responses, as characterized in situ by fluorescence lifetime imaging microscopy (FLIM). FLIM data were acquired by tagging the polar or nonpolar block separately with a covalently incorporated viscosity-sensitive fluorescent molecular rotor to measure the changing tightness or looseness of assembly upon changes in solvent composition. Rapid precipitation from an insoluble solvent to form a film results in tighter assembly and less difference in tightness/looseness between the two blocks. Further, it interrupts individual block-solvent response behavior. Both results indicate an apparent disruption of the core–shell assembly. This model from FLIM is further supported by differential scanning calorimetry (DSC) and small-angle X-ray scattering (SAXS) data from isolated solids, which show tighter long-range interactions and more long-range order in these kinetically trapped states. Here, the experiments develop FLIM as a method for pinpointing stimuli-responsive behaviors from different processing methods to individual blocks. Together these outcomes provide a future handle for tailoring solvent-triggered assembly/disassembly behavior.

López, Pía A. [University of California, Irvine, C↗
DOE OSTI2026

Soil Water Retention and Hydraulic Conductivity Data and Model at Snodgrass Mountain in East River Watershed, Colorado 2020-2025

This data package includes soil water retention and hydraulic conductivity data and model fitting results from measurements of ex-situ soil samples and in-situ soil sensors at Snodgrass Mountain. Soil water retention curves (SWRC) characterize soil water content as a function of soil water potential. SWRC depends on soil texture and pore structure and can be used to describe the constraints on biogeochemical processes in terms of soil water availability. In this data package, the sample identification follows the format SG-X-Y, where SG refers to Snodgrass Mountain, X is the location identifier, and Y is the depth identifier at the same X (shallow Y=1). Specifically, SG-EHS is associated with ecohydrology sites under the East-Taylor Watershed Community Observatory Sites directory, and SG-ERTn (upslope n=1) are points along the Snodgrass electrical resistivity tomography transect not associated with the existing site names in the directory. The sample and location information can be found in metadata.csv. Sampling and Measurements Each sample falls into one of the three sampling methods – (1) intact cores, (2) repacked samples, or (3) soil sensors – and one of the two measurement methods – (a) laboratory or (b) in-situ. Both intact cores and repacked samples were measured using the laboratory methods, which include measurements of soil water potential (HYPROP & WP4C, METER), saturated (KSAT, METER) and unsaturated hydraulic conductivity (HYPROP). The in-situ method uses a pair of co-located soil sensors to measure volumetric water content (TEROS12, METER) and soil water potential (TEROS21, METER), and the hydraulic conductivity was not measured. In comparison, the laboratory methods progress from full saturation to dry conditions, and the in-situ method includes both dry-to-wet and wet-to-dry cycles. The sampling and measurement methods for each sample can be found in metadata.csv, and more information about the measurements is detailed in the Methods section below. Models Retention and hydraulic conductivity data were fitted with four van-Genuchten-type models (specified by “model_name” column in the files): (1) traditional constrained van Genuchten model (“vG_constrained”), (2) traditional unconstrained van Genuchten model (“vG_unconstrained”), (3) PDI-variant of the constrained van Genuchten model (“vG_constrained_PDI”), and (4) PDI-variant of the unconstrained van Genuchten model (“vG_unconstrained_PDI”). The difference between the constrained (1: n) and the unconstrained (2: n, m) van Genuchten models is the number of pore-size distribution parameters in the model equations, giving the unconstrained model more degrees of freedom when fitting the data. Between the traditional and the PDI-variant models, model fitting differs the most at the dry end of the measurements. The traditional models allow infinite suction at the residual water content (water content does not drop below residual water content), and the PDI-variant models enforce a soil water potential value of pF=6.8 (~ -630 MPa) at oven-dryness (water content reaches 0). The inclusion of the van-Genuchten-type models is due to their common application. If other retention models are required, users can access the data in data.csv for further data fitting. More information about the models can be found in the Methods section below. Fitting Tasks The model fitting can be categorized into three levels of tasks (specified by “fitting_task” column in the files). Level 1 (“fit_retention”) only includes retention data fitting (the only level available for the in-situ method). Level 2 (“fit_retention_conductivity”) includes both retention and hydraulic conductivity data fitting, and the saturated hydraulic conductivity (Ks, a parameter of the hydraulic conductivity functions) is fixed by the measurements from KSAT. Level 3 (“fit_retention_conductivity_Ks”) also includes both retention and hydraulic conductivity data fitting, but Ks is a fitted parameter without the constraints from KSAT measurements. Among the same retention models (e.g. vG_constrained models of the same sample), level 1 should produce the best retention data fitting. Level 2 should have the highest misfit of the retention and hydraulic conductivity data, because the retention and hydraulic conductivity functions share common model parameters, and the unsaturated hydraulic conductivity (HYPROP) data fitting is subject to Ks measured independently by KSAT. Level 3 should have mid-level misfits of the retention and hydraulic conductivity data. While level 3 fits the hydraulic conductivity data better than level 2, the fitted Ks value might be unreasonable due to the lack of constraints at the wet end of the measurements. General recommendation when using this data package: (1) Choice of sampling methods: Intact cores and in-situ soil sensors could be prioritized because these sampling methods are less destructive. While the repacked samples were packed to the target bulk density (estimated post-sampling, when sample volume was known), these samples had altered pore structures. Nevertheless, intact cores might suffer from sample gaps that would lead to overestimation of Ks (sample gaps can be inferred from the “soil_sample_volume” column in metadata.csv when the value is < 249). In-situ method also has higher uncertainty in characterizing the wet end of the SWRC because of sensor limitations and the difficulty in reaching full saturation under natural conditions. (2) Choice of fitting tasks: When only retention data is needed, level 1 (“fit_retention”) should be prioritized. When both retention and hydraulic conductivity data are needed, level 2 (“fit_retention_conductivity”) could be prioritized. (3) Choice of models: This could depend on what the downstream models call for. If no specific model is required, model misfit could be used as a ranking criterion. Model misfit values in terms of RMSE can be found in model_parameters.csv. The following files are included in this data package: (1) metadata.csv – This file includes the general information of each sample, including location (description, geocoordinates, elevation), sampling and measurements details (method, depth, time or period, volume, instruments), and soil physical properties (bulk density, saturated hydraulic conductivity, only applicable to physical soil samples). (2) data.csv – This file includes soil water potential, volumetric water content, and unsaturated hydraulic conductivity data of each sample. Column “instrument” specifies the instrument (HYPROP, WP4C, or TEROS) used to perform the measurements. (3) model_fit.csv – This file includes soil water potential, volumetric water content, and unsaturated hydraulic conductivity fitted from the four models and three fitting tasks. Column “model_name” specifies the retention model used, and “fitting_task” specifies the level of data fitting. Missing values indicate that the variable does not apply to that fitting task. (4) model_parameters.csv – This file includes the fitted model parameters, model misfits, and conventional water content thresholds (field capacity and wilting point) from the four models and three fitting tasks. Column “model_name” specifies the retention model used, and “fitting_task” specifies the level of data fitting. Missing values indicate that the parameter does not apply to that model and/or that fitting task. (5) data_Ks.csv – This file includes the saturated hydraulic conductivity measurements from KSAT. (6) /figure/*.png – This folder includes three quick visualizations of the data, retention model fitting results and misfits, and hydraulic conductivity model fitting results, misfits, and parameters. The model fitting results are separated by samples and fitting tasks and colored by models. Zoom-in required. (7) /hyprop/*.bdhx – This folder includes proprietary hyprop files that require the free Labros SoilView-Analysis (METER) to open. Users can explore data fitting using other retention models (i.e. Brooks-Corey, Fredlund-Xing, Kosugi, bimodal models). Be aware that Ks value is pre-entered under “Fitting tab, Conductivity functions parameters” for level 2 fitting. If the value is lost, please refer to metadata.csv under “Ks” column. (8) Six file-level metadata that summarize file, header, column, and variable information of all files. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

EARTH SCIENCE > LAND SURFACE > SOILS↗
NASA NTRS2004

EOS Aqua AMSR-E Arctic Sea Ice Validation Program: Intercomparison Between Modeled and Measured Sea Ice Brightness Temperatures

During March 2003, an extensive field campaign was conducted near Barrow, Alaska to validate AQUA Advanced Microwave Scanning Radiometer (AMSR) sea ice products. Field, airborne and satellite data were collected over three different types of sea ice: 1) first year ice with little deformation, 2) first year ice with various amounts of deformation and 3) mixed first year ice and multi-year ice with various degrees of deformation. The validation plan relies primarily on comparisons between satellite, aircraft flights and ground-based measurements. Although these efforts are important, key aspects such as the effects of atmospheric conditions, snow properties, surface roughness, melt processes, etc on the sea ice algorithms are not sufficiently well understood or documented. To improve our understanding of these effects, we combined the detailed, in-situ data collection from the 2003 field campaign with radiance modeling using a radiative transfer model to simulate the top of the atmosphere AMSR brightness temperatures. This study reports on the results of the simulations for a variety of snow and ice types and compares the results with the National Oceanographic and Atmospheric Administration Environmental Technology Laboratory Polarimetric Scanning Radiometer (NOAA) (ETL) (PSR) microwave radiometer that was flown on the NASA P-3.

Stroeve, J.↗
DOE OSTI2021

Mechanistic insight into copper cation exchange in cadmium selenide semiconductor nanocrystals using X-ray absorption spectroscopy

In terms of producing new advances in sustainable nanomaterials, cation exchange (CE) of post-processed colloidal nanocrystals (NCs) has opened new avenues towards producing non-toxic energy materials via simple chemical techniques. The main processes governing CE can be explained by considering hard/soft acid/base theory, but the detailed mechanism of CE, however, has been debated and has been attributed to both diffusion and vacancy processes. In this work, we have performed in situ x-ray absorption spectroscopy to further understand the mechanism of the CE of copper in solution phase CdSe NCs. The x-ray data indicates clear isosbestic points, suggestive of cooperative behavior as previously observed via optical spectroscopy. Examination of the extended x-ray absorption fine structure data points to the observation of interstitial impurities during the initial stages of CE, suggesting the diffusion process is the fundamental mechanism of CE in this system.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS2016

Analysis of Summer-Time Ozone and Precursor Species in the Southeast United States

Ozone (O3) is a greenhouse gas and toxic pollutant which plays a major role in air quality and atmospheric chemistry. The understanding and ability to model the horizontal and vertical structure of O3 mixing ratios is difficult due to the complex formation/destruction processes and transport pathways that cause large variability of O3. The Environmental Protection Agency has National Ambient Air Quality Standards for O3 set at 75 ppb with future standards proposed to be as low as 65 ppb. These lower values emphasize the need to better understand/simulate the transport processes, emission sources, and chemical processes controlling precursor species (e.g., NOx, VOCs, and CO) which influence O3 mixing ratios. The uncertainty of these controlling variables is particularly large in the southeast United States (US) which is a region impacted by multiple different emission sources of precursor species (anthropogenic and biogenic) and transport processes resulting in complex spatio-temporal O3 patterns. During this work we will evaluate O3 and precursor species in the southeast US applying models, ground-based and airborne in situ data, and lidar observations. In the summer of 2013, the UAH O3 Differential Absorption Lidar (DIAL) (part of the Tropospheric Ozone Lidar Network (TOLNet)) measured vertical O3 profiles from the surface up to approximately 12 km. During this period, the lidar observed numerous periods of dynamic temporal and vertical O3 structures. In order to determine the sources/processes impacting these O3 mixing ratios we will apply the CTM GEOS-Chem (v9-02) at a 0.25 deg x 0.3125 deg resolution. Using in situ ground-based (e.g., SEARCH Network, CASTNET), airborne (e.g., NOAA WP-3D - SENEX 2013, DC-8 - SEAC4RS), and TOLNet lidar data we will first evaluate the model to determine the capability of GEOS-Chem to simulate the spatio-temporal variability of O3 in the southeast US. Secondly, we will perform model sensitivity studies in order to quantify which emission sources (e.g., anthropogenic, biogenic, lighting, wildfire) and transport processes (e.g., stratospheric, long-range, local scale) are contributing to these TOLNet-observed dynamic O3 patterns. Results from the evaluation of the model and the study of sources/processes impacting observed O3 mixing ratios will be presented.

Optical Radar↗
NASA NTRS2022

Research Campaign: Advanced Manufacturing in Space: Properties, Structure and Simulations to Pioneer New Applications

This topic underpins synthesis of, and in many cases manufacturing of, value-added materials via liquid phase processing. Materials and processes range from cast metals and optical glasses through exploration-relevant technologies such as additive manufacturing, casting and in-situ resource utilization to support human space exploration. A recurring theme is the need for accurate thermophysical property and atomic structure data for relevant materials and the exploitation of reduced convection/sedimentation in microgravity to enhance the quality of data and to develop new and transformative technologies for materials processing.

Michael SanSoucie↗
NASA NTRS2000

Phase Shift Interferometer and Growth Set Up to Step Pattern Formation During Growth From Solutions. Influence of the Oscillatory solution Flow on Stability

We have assembled an experimental setup based on Michelson interferometry with the growing crystal surface as one of the reflective surfaces. The crystallization part of the device allows optical monitoring of a face of a crystal growing at temperature stable within 0.05 C in a flow of solution of controlled direction and speed. The reference arm of the interferometer contains a liquid crystal element that allows controlled shifts of the phase of the interferograms. We employ an image-processing algorithm, which combines five images with a pi/2 phase difference between each pair of images. The images are transferred to a computer by a camera capable of capturing 60 frames per second. The device allows data collection on surface morphology and kinetics during the face layers growth over a relatively large area (approximately 4 sq. mm) in situ and in real time during growth. The estimated depth resolution of the phase shifting interferometry is approximately 50 Angstroms. The data will be analyzed in order to reveal and monitor step bunching during the growth process. The crystal chosen as a model for study in this work is KH2PO4 (KDP). This optically non-linear material is widely used in frequency doubling applications. There have been a number of studies of the kinetics of KDP crystallization that can serve as a benchmark for our investigations. However, so far, systematic quantitative characteristics of step interaction and bunching are missing. We intend to present our first quantitative results on the onset, initial stages and development of instabilities in moving step trains on vicinal crystal surfaces at varying supersaturation, flow rate, and flow direction. Behavior of a vicinal face growing from solution flowing normal to the steps and periodically changing its direction in time was considered theoretically. It was found that this oscillating flow reduces both stabilization and destabilization effects resulted from the unidirectional solution flow directed up the step stream and down the step stream. This reduction of stabilization and destabilization comes from effective mixing which entangles the phase shifts between the spatially periodic interface perturbation and the concentration wave induced by this perturbation. Numerical results and simplified mixing criterion will be discussed.

Chernov, Alex A.↗
NASA NTRS2018

Development of the GEOS-MIT gcm Atmosphere-Ocean Model for Coupled Data Assimilation

During the last two plus decades, The Goddard Earth Observing System (GEOS) and Massachusetts Institute of Technology (MIT) modeling groups have developed, respectively, atmosphere-only and ocean-only global general circulation models. These two models (GEOS and MIT-GCM (General Circulation Model)) have demonstrated their data assimilation capabilities with the recent releases of the Modern Era Reanalysis for Research Applications, Version 2 (MERRA-2) atmospheric reanalysis and the Estimating the Circulation and Climate of the Ocean, Version 4 (ECCO-v4) ocean (and sea ice) state estimate. Independently, the two modeling groups have also produced global atmosphere-only and ocean-only simulations with km-scale grid spacing which proved invaluable for process studies and for the development of satellite and in-situ sampling strategies. Recently, a new effort has been made to couple these two models and to leverage their data-assimilation and high resolution capabilities (i.e., eddy-permitting ocean, cloud-permitting atmosphere). The focus in the model development is put on sub-seasonal to decadal time scales. In this talk, I discuss the new coupled model and present some first coupled simulation results. This will include a high-resolution coupled GEOS-MIT simulation, whereby we have coupled a cubed-sphere-720 (approximately 1/8 degrees) configuration of the GEOS atmosphere to a latitude-longitude-cap-1080 (approximately 1/12 degrees) configuration of the MIT ocean. We compare near-surface diagnostics of this fully coupled ocean-atmosphere set-up to equivalent atmosphere-only and ocean-only simulations. In the comparisons we focus in particular on the differences in air-sea interactions between sea surface temperature (SST) and wind for the coupled and uncoupled simulations.

Strobach, Ehud↗
NASA NTRS2014

Investigation into the Use of the Concept Laser QM System as an In-Situ Research and Evaluation Tool

The NASA Marshall Space Flight Center (MSFC) is using a Concept Laser Fusing (Cusing) M2 powder bed additive manufacturing system for the build of space flight prototypes and hardware. NASA MSFC is collecting and analyzing data from the M2 QM Meltpool and QM Coating systems for builds. This data is intended to aide in understanding of the powder-bed additive manufacturing process, and in the development of a thermal model for the process. The QM systems are marketed by Concept Laser GmbH as in-situ quality management modules. The QM Meltpool system uses both a high-speed near-IR camera and a photodiode to monitor the melt pool generated by the laser. The software determines from the camera images the size of the melt pool. The camera also measures the integrated intensity of the IR radiation, and the photodiode gives an intensity value based on the brightness of the melt pool. The QM coating system uses a high resolution optical camera to image the surface after each layer has been formed. The objective of this investigation was to determine the adequacy of the QM Meltpool system as a research instrument for in-situ measurement of melt pool size and temperature and its applicability to NASA's objectives in (1) Developing a process thermal model and (2) Quantifying feedback measurements with the intent of meeting quality requirements or specifications. Note that Concept Laser markets the system only as capable of giving an indication of changes between builds, not as an in-situ research and evaluation tool. A secondary objective of the investigation is to determine the adequacy of the QM Coating system as an in-situ layer-wise geometry and layer quality evaluation tool.

Bagg, Stacey↗
DOE OSTI2025

Monitoring the long-term performance of organic redox flow battery by a distribution of relaxation time analysis

Organic redox flow batteries hold great promise as an energy storage technology, but their intricate chemistry makes them vulnerable to various degradation mechanisms. Monitoring this degradation is essential for identifying the limiting processes within the cells. Electrochemical impedance spectroscopy (EIS) offers a straightforward, in-situ method for measuring the total resistance of an operating cell. However, to pinpoint the limiting processes during long-term cycling, EIS data must be complemented by other techniques. Distribution of relaxation time (DRT) analysis is particularly effective for differentiating resistance components. Here, in this study, we perform a comprehensive analysis of resistance evolution and the separation of anode and cathode contributions during long-term cycling of a full cell employing 7,8-dihydroxyphenazine-2-sulfonic acid (DHPS) as the anolyte. Separate analyses of the DHPS anolyte and ferri-/ferrocyanide catholyte were conducted using a symmetric cell setup. The relaxation times derived from symmetric cells facilitate the identification of peaks in the DRT profiles from the full cell. Importantly, the DRT profiles indicate a correlation between the evolution of charge transfer resistance and the chemical degradation of DHPS. The methodologies and results outlined in this study offer significant insights for developing diagnostic tools applicable to other types of redox flow batteries.

Distribution of relaxation time↗
NASA NTRS1989

An interim reference model for the variability of the middle atmosphere H2O vapor distribution

Water vapor is an important minor constituent in the studies of the middle atmosphere for a variety of reasons, including its role as a source for active HO(y) chemicals and its use in analysis of transport processes. A number of in situ and remote techniques were employed in the determination of water vapor distributions. Two of the more complete data sets were used to develop an interim reference profile. First, there are the seven months of Nimbus 7 limb infrared monitor of the stratosphere (LIMS) data obtained during Nov. 1978 to May 1979 over the range 64S to 84N latitude and from about 100 to 1 mb in the mid-mesosphere at several fixed Northern Hemisphere mid-latitude sites. These two data sets were combined to give a mid-lattitude, interim reference water vapor profile for the entire vertical range of the middle atmosphere and with accuracies of better than 25 percent. The daily variability of stratospheric water vapor profiles about the monthly mean was also established from these data sets for selected months. Information is also provided on the longitudinal variability of LIMS water vapor profiles about the daily, weekly, and monthly zonal means. Generally, the interim reference water vapor profile and its variability are consistent with prevailing ideas about chemistry and transport.

Remsberg, E. E.↗
NASA NTRS1992

A Backscatter Moessbauer Spectrometer (BaMS) for use on Mars

The use of Moessbauer spectroscopy for in situ analysis on the surface of Mars was proposed and the design and implementation of a backscatter Moessbauer spectrometer (BaMS) instrument suitable for planetary missions to the surfaces of Mars (MESUR), the Moon (Artemis and lunar outpost), asteroids, or other solid solar system objects is discussed. The BaMS instrument is designed to be capable of analysis of a sample for the mineralogy of its iron-bearing phases without any sample preparation. A requirement of lander missions to Mars is instrumentation for in situ mineralogical analyses. Such analyses provide data needed for primary characterization as to the type of surface materials present and by inference the processes that formed and subsequently modified them. For purposes of providing diagnostic information about naturally occurring materials, the element iron is particularly important because it is abundant and multivalent (primarily 0, +2, and +3 oxidation states). Knowledge of the oxidation state of iron and its distribution among iron-bearing mineralogies tightly constrains the types of materials present. The pivotal role of iron was already recognized in 1978 by COMPLEX, who recommended development of flight instruments that would identify mineralogy and the oxidation state of iron in planetary surface materials. The near-term U.S. strategy for the exploration of Mars is the MESUR (Mars Environmental SURvey) program, which entails emplacement of a network of small, long-lived surface landers. For the Moon, BaMS was recommended as part of a three-instrument landed payload for the Artemis missions, targeted for 1997. BaMS would prospect for ilmenite, an oxygen resource material, and provide data to assess the maturity of lunar soil. Because instrumental characteristics are low mass, low volume, and low power consumption, BaMS is suitable for implementation on even small landers and rovers, as are being envisioned in MESUR and Artemis concepts. In addition to providing highly diagnostic data, a BaMS analyzer is inherently simple and, as is highly desirable for remote operation, no sample preparation is required.

Agresti, D. G.↗
NASA NTRS2004

Preliminary Sample Analysis Plan for the Cometary and Interstellar Samples Being Returned by the Stardust Spacecraft

The NASA Stardust comet sample return mission is proceeding very well, and the science team breathed a collective sigh of relief following the successful comet sample collection phase which occurred during a 6.1 km/s, 340km-close flyby of comet Wild-2 on Jan 2 of this year. Multiple images of the comet nucleus were obtained and a variety of onboard instruments returned in situ data on the spatial distribution, particle size frequency and composition of the dust in the comet s coma. These data are currently being processed and analyzed. It is expected that 500-1000 comet particles >15 m were collected by impact into low density silica aerogel, as well as many more smaller grains. Previous tests with hypervelocity guns firing small particles into aerogel indicate that material should have successfully been collected by the Stardust aerogel [1&2]. In addition, many (~100) grains of interstellar material newly entering the Solar System should have been collected by the spacecraft during its cruise phase to the comet.

Zolensky, M.↗