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All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

The Collection 6 'dark-target' MODIS Aerosol Products

Aerosol retrieval algorithms are applied to Moderate resolution Imaging Spectroradiometer (MODIS) sensors on both Terra and Aqua, creating two streams of decade-plus aerosol information. Products of aerosol optical depth (AOD) and aerosol size are used for many applications, but the primary concern is that these global products are comprehensive and consistent enough for use in climate studies. One of our major customers is the international modeling comparison study known as AEROCOM, which relies on the MODIS data as a benchmark. In order to keep up with the needs of AEROCOM and other MODIS data users, while utilizing new science and tools, we have improved the algorithms and products. The code, and the associated products, will be known as Collection 6 (C6). While not a major overhaul from the previous Collection 5 (C5) version, there are enough changes that there are significant impacts to the products and their interpretation. In its entirety, the C6 algorithm is comprised of three sub-algorithms for retrieving aerosol properties over different surfaces: These include the dark-target DT algorithms to retrieve over (1) ocean and (2) vegetated-dark-soiled land, plus the (3) Deep Blue (DB) algorithm, originally developed to retrieve over desert-arid land. Focusing on the two DT algorithms, we have updated assumptions for central wavelengths, Rayleigh optical depths and gas (H2O, O3, CO2, etc.) absorption corrections, while relaxing the solar zenith angle limit (up to 84) to increase pole-ward coverage. For DT-land, we have updated the cloud mask to allow heavy smoke retrievals, fine-tuned the assignments for aerosol type as function of season location, corrected bugs in the Quality Assurance (QA) logic, and added diagnostic parameters such as topographic altitude. For DT-ocean, improvements include a revised cloud mask for thin-cirrus detection, inclusion of wind speed dependence in the retrieval, updates to logic of QA Confidence flag (QAC) assignment, and additions of important diagnostic information. At the same time as we have introduced algorithm changes, we have also accounted for upstream changes including: new instrument calibration, revised land-sea masking, and changed cloud masking. Upstream changes also impact the coverage and global statistics of the retrieved AOD. Although our responsibility is to the DT code and products, we have also added a product that merges DT and DB product over semi-arid land surfaces to provide a more gap-free dataset, primarily for visualization purposes. Preliminary validation shows that compared to surface-based sunphotometer data, the C6, Level 2 (along swath) DT-products compare at least as well as those from C5. C6 will include new diagnostic information about clouds in the aerosol field, including an aerosol cloud mask at 500 m resolution, and calculations of the distance to the nearest cloud from clear pixels. Finally, we have revised the strategy for aggregating and averaging the Level 2 (swath) data to become Level 3 (gridded) data. All together, the changes to the DT algorithms will result in reduced global AOD (by 0.02) over ocean and increased AOD (by 0.02) over land, along with changes in spatial coverage. Changes in calibration will have more impact to Terras time series, especially over land. This will result in a significant reduction in artificial differences in the Terra and Aqua datasets, and will stabilize the MODIS data as a target for AEROCOM studie

Aerosol retrieval algorithms↗
DOE OSTI2015

Direct comparisons of X-ray scattering and atomistic molecular dynamics simulations for precise acid copolymers and ionomers

Designing acid- and ion-containing polymers for optimal proton, ion, or water transport would benefit profoundly from predictive models or theories that relate polymer structures with ionomer morphologies. Recently, atomistic molecular dynamics (MD) simulations were performed to study the morphologies of precise poly(ethylene-co-acrylic acid) copolymer and ionomer melts. Here, we present the first direct comparisons between scattering profiles, I(q), calculated from these atomistic MD simulations and experimental X-ray data for 11 materials. This set of precise polymers has spacers of exactly 9, 15, or 21 carbons between acid groups and has been partially neutralized with Li, Na, Cs, or Zn. In these polymers, the simulations at 120 °C reveal ionic aggregates with a range of morphologies, from compact, isolated aggregates (type 1) to branched, stringy aggregates (type 2) to branched, stringy aggregates that percolate through the simulation box (type 3). Excellent agreement is found between the simulated and experimental scattering peak positions across all polymer types and aggregate morphologies. The shape of the amorphous halo in the simulated I(q) profile is in excellent agreement with experimental I(q). We found that the modified hard-sphere scattering model fits both the simulation and experimental I(q) data for type 1 aggregate morphologies, and the aggregate sizes and separations are in agreement. Given the stringy structure in types 2 and 3, we develop a scattering model based on cylindrical aggregates. Both the spherical and cylindrical scattering models fit I(q) data from the polymers with type 2 and 3 aggregates equally well, and the extracted aggregate radii and inter- and intra-aggregate spacings are in agreement between simulation and experiment. Furthermore, these dimensions are consistent with real-space analyses of the atomistic MD simulations. By combining simulations and experiments, the ionomer scattering peak can be associated with the average distance between branches of type 2 or 3 aggregates. Furthermore, this direct comparison of X-ray scattering data to the atomistic MD simulations is a substantive step toward providing a comprehensive, predictive model for ionomer morphology, gives substantial support for this atomistic MD model, and provides new credibility to the presence of stringy, branched, and percolated ionic aggregates in precise ionomer melts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

PV Fleet Performance Data Initiative Program and Methodology

The US Department of Energy’s PV Fleet Performance Data Initiative has been launched in order to collect and evaluate production data across multiple PV fleet partners. Performance statistics are anonymized, aggregated and shared to represent a snapshot of the US commercial and utility-scale fleet. Production data have been collected from over 1500 systems representing more than 1.3 GWdc capacity. Preliminary analysis indicates median performance loss rates are in line with previous publications of system degradation, on the order of –0.6%/yr to –0.9%/yr (preliminary numbers subject to change). These values are higher than module-only degradation rates which are often used in pro-forma estimates of project performance and economics, potentially exposing owner/operators to increased risk if systems under-perform over time.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2016

Completing the Link between Exposure Science and Toxicology for Improved Environmental Health Decision Making: The Aggregate Exposure Pathway Framework

Driven by major scientific advances in analytical methods, biomonitoring, and computational exposure assessment, and a newly articulated vision for a greater impact in public health, the field of exposure science is undergoing a rapid transition from a field of observation to a field of prediction. Deployment of an organizational and predictive framework for exposure science analogous to the computationally enabled “systems approaches” used in the biological sciences is a necessary step in this evolution. Here we propose the aggregate exposure pathway (AEP) concept as the natural and complementary companion in the exposure sciences to the adverse outcome pathway (AOP) concept in the toxicological sciences. The AEP framework offers an intuitive approach to successful organization of exposure science data within individual units of prediction common to the field, setting the stage for exposure forecasting. Looking farther ahead, we envision direct linkages between aggregate exposure pathway and adverse outcome pathways, completing the source to outcome continuum and setting the stage for more efficient integration of exposure science and toxicity testing information. Together these frameworks form and inform a decision making framework with the flexibility for risk-based, hazard-based or exposure-based decisions.

Teeguarden, Justin G.↗
NASA NTRS2007

Exploring and Visualizing A-Train Instrument Data

The succession of US and international satellites that follow each other in close succession, known as the A-Train, affords an opportunity to atmospheric researchers that no single platform could provide: Increasing the number of observations at any given geographic location.. . a more complete "virtual science platform". However, vertically and horizontally, co-registering and regridding datasets from independently developed missions, Aqua, Calipso, Cloudsat, Parasol, and Aura, so that they can be inter-compared can be daunting to some, and may be repeated by many. Scientists will individually spend much of their time and resources acquiring A-Train datasets of interest residing at various locations, developing algorithms to match up and graph datasets along the A-Train track, and search through large amounts of data for areas and/or phenomena of interest. The aggregate amount of effort that can be expended on repeating pre-science tasks could climb into the tens of millions of dollars. The goal of the A-Train Data Depot (ATDD) is to enable free movement of remotely located A-Train data so that they are combined to create a consolidated vertical view of the Earth's Atmosphere along the A-Train tracks. The innovative approach of analyzing and visualizing atmospheric profiles along the platforms track (i.e., time) is accomplished by through the ATDDs Giovanni data analysis and visualization tool. Giovanni brings together data from Aqua (MODIS, AIRS, AMSR-E), Cloudsat (cloud profiling radar) and Calipso (CALIOP, IIR), as well as the Aura (OMI, MLS, HIRDLS, TES) to create a consolidated vertical view of the Earth's Atmosphere along the A-Train tracks. This easy to learn and use exploration tool will allow users to create vertical profiles of any desired A-Train dataset, for any given time of choice. This presentation shows the power of Giovanni by describing and illustrating how this tool facilitates and aids A-Train science and research. A web based display system Giovanni provides users with the capability of creating co-located profile images of temperature and humidity data from the MODIS, MLS and AIRS instruments for a user specified time and spatial area. In addition, Cloud and Aerosol profiles may also be displayed for the Cloudsat and Caliop instruments. The ability to modify horizontal and vertical axis range, data range and dynamic color range is also provided. Two dimensional strip plots of MODIS, AIRS, OM1 and POLDER parameters, co-located along the Cloudsat reference track, can also be plotted along with the Cloudsat cloud profiling data. Center swath pixels for the same parameters can also be shown as line plots overlaying the Cloudsat or Calipso profile images. Images and subsetted data produced in each analysis run may be downloaded. Users truly can explore and discover data specific to their needs prior to ever transferring data to their analysis tools.

Kempler, S.↗
NASA NTRS1996

Soot and Radiation Measurements in Microgravity Jet Diffusion Flames

The subject of soot formation and radiation heat transfer in microgravity jet diffusion flames is important not only for the understanding of fundamental transport processes involved but also for providing findings relevant to spacecraft fire safety and soot emissions and radiant heat loads of combustors used in air-breathing propulsion systems. Our objectives are to measure and model soot volume fraction, temperature, and radiative heat fluxes in microgravity jet diffusion flames. For this four-year project, we have successfully completed three tasks, which have resulted in new research methodologies and original results. First is the implementation of a thermophoretic soot sampling technique for measuring particle size and aggregate morphology in drop-tower and other reduced gravity experiments. In those laminar flames studied, we found that microgravity soot aggregates typically consist of more primary particles and primary particles are larger in size than those under normal gravity. Comparisons based on data obtained from limited samples show that the soot aggregate's fractal dimension varies within +/- 20% of its typical value of 1.75, with no clear trends between normal and reduced gravity conditions. Second is the development and implementation of a new imaging absorption technique. By properly expanding and spatially-filtering the laser beam to image the flame absorption on a CCD camera and applying numerical smoothing procedures, this technique is capable of measuring instantaneous full-field soot volume fractions. Results from this technique have shown the significant differences in local soot volume fraction, smoking point, and flame shape between normal and reduced gravity flames. We observed that some laminar flames become open-tipped and smoking under microgravity. The third task we completed is the development of a computer program which integrates and couples flame structure, soot formation, and flame radiation analyses together. We found good agreements between model predictions and experimental data for laminar and turbulent flames under both normal and reduced gravity. We have also tested in the laboratory the techniques of rapid-insertion fine-wire thermocouples and emission pyrometry for temperature measurements. These techniques as well as laser Doppler velocimetry and spectral radiative intensity measurement have been proposed to provide valuable data and improve the modeling analyses.

Ku, Jerry C.↗
DOE OSTI2018

Introducing a risk aggregation rationale for mapping risks to aquifers from point- and diffuse-sources–proof-of-concept using contamination data from industrial lagoons

Highlights: • Aquifer risk mapping is introduced for contaminants acting as point/diffuse-sources. • Innovations are framed by risk cells based on Source-Pathway-Receptor-Source (SPRC). • Point-source (Risk Cell 1) and diffuse-source (Risk Cell 2) use sets of algorithms. • Algorithms include MODPATH, DRASTIC, GWPI and are integrated on a modular basis. • Risk Cells 1/2 are aggregated giving fit-for-purpose results as proof-of-concept. - Abstract: Proof-of-concept for a methodology is presented on mapping risks to aquifers impacted from point- and diffuse-sources, where mapping or indexing refers to relative but not absolute values. The methodology is generic but tested by investigating impacts of a risk exposure from industrial wastewater lagoons. The methodology is innovative for using the qualitative Source-Pathways-Receptors-Consequences (SPRC) framework to aggregate risks from both point-sources and diffuse-sources through breaking down a study area into SPRC risk cells. In this paper, two risk cells are required as: (i) Cell 1 is directly impacted from a point-source; and (ii) Cell 2 is impacted by diffuse-sources to slowly contaminate the aquifer by infiltration over a large area. Indexing both types of risk cells generically comprise three tiered processes: (i) binary indexing establishes if a grid cell is at a potential risk or not; (ii) graded indexing measures the strength of the risk pathways from source to receptors; and (iii) local indexing measures intrinsic potentials at the grid cell to propagate the risk. These three processes apply to both point- and diffuse-sources but with different mathematical formulations. The proof-of-concept for the methodology of risk aggregation using the SPRC framework is supported by results of a study area, in which a set of performance metrics are used by comparing with the measurements. The results are found to be fit-for-purpose for serving as proactive management tools and to provide a deeper insight into potential impacts of adverse effects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

SU-E-T-471: Small Field Jaw/MLC Reference Data

Purpose: In recent years the need for small field data of MLCs has increased due to the use of intensity-modulated radiation (IMRT), but moreover the use of stereotactic body radiation (SBRT) has increased, which uses not simply small field sizes, but small jaw and field sizes together. Having reference data for these small fields that is reliable would be invaluable to the physics community. Our study has gathered these values and the data distributions from the Radiological Physics Center's (RPC) site visits between 1990 and the present. Methods: For all measurements, the RPC used a 25 × 25 × 25cm water phantom placed at 100cm SSD. All measurements were made with an Exradin A16 cylindrical ion chamber at an effective depth of 10 cm. A total of 42 Varian machine measurements were used to compose the data for a 6 MV beam and 5 TrueBeam 6 MV flattening filter free (FFF) beams were used for FFF data. Results: Jaw/MLC fields were measured for both 6 MV and 6 MF FFF beams with the jaws and MLCs both at the following field sizes: 6×6, 4×4, 3×3, and 2×2cm. Measurements were normalized to the 10×10 field readings (defined by the jaws and MLC). Spread in the data was minimal and demonstrates a high level of accuracy of acquired data. Conclusion: Small field Jaw/MLC reference data for Varian 6MV and 6 MV FFF beams has been analyzed and presented here, composed of the aggregation of numerous RPC site visits. Obtaining reliable small field data remains difficult, however the RPC has collected high fidelity small field Jaw/MLC data. The data are presented as a reference along with their distributions, in such a way that the physicist can act based upon their own desired agreement with the reference data.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

A review of privacy in energy applications

As the distribution system continues to experience an increase in distributed energy resource (DER) and electric vehicle (EV) penetration, so does the need for new solutions that can help grid operators manage and leverage their capabilities. This will undoubtedly lead to new operational schemes and business opportunities that will transform the traditional consumer into a prosumer who will be more actively engaged in grid operations. Although the field is still under active development, many of the potential use cases presented in literature or industry are built upon edge computing, two-way communications, and other innovative computational constructs to attain their goals. However, at their core, many use cases assume a great level of data access to aid with the decision-making process, an assumption that may need to be revised to ensure fair and equitable operational processes are maintained. This may be particularly true as edge resources are predicted to participate in retail-side, many-to-many, or peer-to-peer markets and thus may lead to financial impacts if data access considerations are ignored. The need to revise data access mechanisms can be further justified by the introduction of new participants into the operational process, who do not have the same level of trust, nor the incentives to focus on energy delivery as their primary objective. At the same time, more consumers are becoming aware of their own data, and the potential impacts of its abuse. To help solution developers better understand these risks, this report has been developed to offer an initial introduction to the topic of privacy. This is achieved by 1) Highlighting the need for privacy-aware solutions; 2) Encouraging system designers to be inquisitive about the status quo; 3) Documenting the existing threat space; 4) Presenting and evaluating tools that may be helpful towards enabling better privacy postures; and 5) Making recommendations to encourage the adoption of better practices. From a technical perspective, the report focuses on evaluating two potential techniques by applying them to the Transactive Energy Space. Based on the obtained results, it can be established that differential privacy (DP) methods may have limited applicability when highly correlated, time-series data records need to be protected. However, DP may be a powerful tool when it is used to aggregate and analyze mid-size and large-size data sets in a more traditional statistical environment. The second tool under evaluation is threshold cryptography, which can guarantee complete secrecy (and thus privacy) but requires the establishment of key management procedures and dedicated communication channels for key coordination. Therefore, due to its increased computational overhead, the use of threshold cryptography must be weighted using a cost/benefit analysis on a per-application basis.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2005

The Virtual Solar Observatory: Still a Small Box

Two and a half years after a design study began, and a year and a half after development commenced, version 1.0 of the Virtual Solar Observatory (VSO) was released at the 2004 Fall AGU meeting. Although internal elements of the VSO have changed, the basic design has remained the same, reflecting the team's belief in the importance of a simple, robust mechanism for registering data provider holdings, initiating queries at the appropriate provider sites, aggregating the responses, allowing the user to iterate before making a final selection, and enabling the delivery of data directly from the providers. In order to make the VSO transparent, lightweight, and portable, the developers employed XML for the registry, SOAP for communication between a VSO instance and data services, and HTML for the graphic user interface (GUI's). We discuss the internal data model, the API, and user responses to various trial GUI's as typical design issues for any virtual observatory. We also discuss the role of the "small box" of data search, identification, and delivery services provided by the VSO in the larger, Sun-Solar System Connection virtual observatory (VxO) scheme.

Gurman, J. B.↗
DOE OSTI2018

Uncertainty Quantification in Vibro-Acoustics Diagnosis of Alkali-Silica Reaction Degradation in Medium-Sized Concrete Samples

The objectives of this ongoing research project focus on health monitoring and data analytics of concrete slabs containing reactive aggregates and thus subjected to degradation due to alkali-silica reaction (ASR). A controlled concrete slab with four pockets of reactive aggregates (pure silica, wells, placitas, and spratt) was cast at Vanderbilt University and cured in representative conditions to accelerate degradation due to ASR. A set of four concrete samples were also cast and cured at the University of Alabama for ASR testing. Of these four samples, two slabs contained reactive aggregates while the other two had the non-reactive aggregate counterparts mixed throughout the samples. Vibro-acoustic testing was used on these slabs to locate ASR damage within the reactive samples. Vibro-acoustic modulation (VAM) is a vibration-based NDE method that utilizes signatures of nonlinear dynamic interactions on contact surfaces of crack or delamination damage to detect and localize the damage. VAM analysis was conducted on both the Vanderbilt and Alabama samples using multiple variables for damage detection and localization. The results from the data analysis of the vibro-acoustic testing on concrete slabs cured at Vanderbilt University and the University of Alabama are discussed in detail in this report. Results for damage localization are dependent on multiple variables used in the vibro-acoustic modulation experiments. A major focus of this report is to quantify the uncertainty in the diagnosis due to multiple factors and uncertainty sources. The uncertainty quantification methodology presented in this report was applied to VAM-based diagnosis and prognosis. However, the methodology is general, and is capable of being applied to multiple technique that collect spatially distributed data. Future work needs to investigate the incorporation of uncertainty quantification in developing a robust Prognostics and Health Management framework. Digital image correlation is a three-dimensional, full-field, optical NDE technique to measure contour, deformation, vibration, and strain. The application of the digital image correlation technique to study ASR-related degradation on a large concrete specimen at the University of Tennessee is discussed and observations are presented in this report.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Distinguishing the importance of fullerene phase separation from polymer ordering in the performance of low band gap polymer: Bis-fullerene heterojunctions

It is known, one way to improve power conversion efficiency (PCE) of polymer based bulk-heterojunction (BHJ) photovoltaic cells is to increase the open circuit voltage (V oc ). Replacing PCBM with bis-adduct fullerenes significantly improves V oc and the PCE in devices based on the conjugated polymer poly(3-hexyl thiophene) (P3HT). However, for the most promising low band-gap polymer (LBP) system, replacing PCBM with ICBA results in poor short-circuit current (J sc ) and PCE although V oc is significantly improved. The optimization of the morphology of as-cast LBP/bis-fullerene BHJ photovoltaics is attempted by adding a co-solvent to the polymer/fullerene solution prior to film deposition. Varying the solubility of polymer and fullerene in the co-solvent, bulk heterojunctions are fabricated with no change of polymer ordering, but with changes in fullerene phase separation. The morphologies of the as-cast samples are characterized by small angle neutron scattering and neutron reflectometry. A homogenous dispersion of ICBA in LBP is found in the samples where the co-solvent is selective to the polymer, giving poor device performance. Aggregates of ICBA are formed in samples where the co-solvent is selective to ICBA. Furthermore, the resultant morphology improves PCE by up to 246%. Finally, a quantitative analysis of the neutron data shows that the interfacial area between ICBA aggregates and its surrounding matrix is improved, facilitating charge transport and improving the PCE.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2025

Data for: Miscanthus × giganteus changes soil structure and increases maximum water holding capacity

The data provided include results from a comparative study evaluating the impact of Miscanthus × giganteus (miscanthus) versus maize on soil structural properties and maximum water holding capacity (MWHC) across two Iowa sites. The dataset includes MWHC values determined using the Funnel Filter Paper Drainage (FFPD) method, as well as additional measurements of MWHC following structural disruption of the soil to isolate the effect of aggregation. It also contains three-dimensional micro-computed tomography (microCT) data used to quantify total porosity and pore size distribution (PSD) of soil aggregates at a 5 µm resolution. All data are provided as raw replicate-level measurements, organized by site, crop, and depth, along with processed summary files in table form in CSV (.csv) format to support reproducibility and downstream analysis.

Misanthus x giganteus↗
NASA NTRS1980

AgRISTARS: Foreign commodity production forecasting. Minutes of the annual formal project manager's review, including preliminary technical review reports of FY80 experiments

The U.S./Canada wheat/barley exploratory experiment is discussed with emphasis on labeling, machine processing using P1A, and the crop calendar. Classification and the simulated aggregation test used in the U.S. corn/soybean exploratory experiment are also considered. Topics covered regarding the foreign commodity production forecasting project include: (1) the acquisition, handling, and processing of both U.S. and foreign agricultural data, as well as meteorological data. The accuracy assessment methodology, multicrop sampling and aggregation technology development, frame development, the yield project interface, and classification for area estimation are also examined.

Source record↗
DOE OSTI2024

Responses of Drying-rewetting (Transient Soil Moisture) and Steady State Soil Moisture Incubation on Soil Organic Carbon Dynamics in Three US Soils, 2017

This data set contains measurements of soil characteristics (aggregate size distribution and mean size, total aggregate associated carbon, extractable organic C, and microbial biomass C), microbial respiration, and soil metabolite concentrations from a transient and steady soil moisture incubation experiment using soils of different textures (sandy, loamy, and clayey). The study investigated mechanisms driving the Birch effect (increased carbon mineralization pulses with wetting following a drying period) in differing soil textures. Three different soils of distinctly different textures were collected from 0-15cm depth in Georgia (sandy, 2017-05-01), Missouri (loamy, 2017-06-14), and Texas (clayey, December 2017). Soils were incubated for 140 days with destructive harvests done on days 1, 29, 33, 56, 112, 116, and 140 in transient soil moisture incubation and on days 1, 33, 116, and 140 in steady state soil moisture incubation. This dataset contains six data files in comma separate (.csv) format. Additional metadata are provided: six data dictionaries and a file-level metadata file in comma separate (*.csv) format and a user guide in PDF (*.pdf) format.

1-Methyladenosine concentration↗
DOE OSTI2018

Enhancement of Structural Health Monitoring Framework by Optimizing Vibro-Acoustic Modulation Technique to Localize Alkali-Silica Reaction Degradation in Medium-Sized Concrete Samples

Assessment and management of aging concrete structures in nuclear power plants require a more systematic approach than simple reliance on existing code margins of safety. Health monitoring of concrete structures is performed to understand the current condition of a structure based on heterogeneous measurements and then produce high confidence actionable information regarding structural integrity. This information can then be used to support operational and maintenance decisions. The objectives of this ongoing research project focus on health monitoring and data analytics of concrete slabs containing reactive aggregates and thus subjected to degradation due to alkali-silica reaction (ASR). A controlled concrete slab with four pockets of reactive aggregates (pure silica, wells, placitas, and spratt) was cast at Vanderbilt University and cured in representative conditions to accelerate degradation due to ASR. A set of four concrete samples were also cast and cured at the University of Alabama for ASR testing. Of these four samples, two slabs contained reactive aggregates while the other two had the non-reactive aggregate counterparts mixed throughout the samples. Vibro-acoustic methods were used on these slabs to locate large pockets of ASR within the reactive samples and determine the effects of rebar using the non-reactive slabs. Vibro-acoustic modulation (VAM) is a vibration-based NDE method that utilizes signatures of nonlinear dynamic interactions on contact surfaces of crack or delamination damage to detect and localize the damage. VAM analysis was conducted on both Vanderbilt and Alabama’s samples using multiple variables for damage detection and localization. The results from the data analysis of the NDE vibro-acoustic techniques on concrete slabs cured at Vanderbilt University and the University of Alabama are discussed in detail in this report. The major outcome of the analysis suggests that the VAM method can be used to detect damage within the concrete samples by comparing the results found in different sections of the samples. Results for damage localization are dependent on multiple variables used in the vibro-acoustic modulation experiments. Digital image correlation (DIC) is a three-dimensional, full-field, optical NDE technique to measure contour, deformation, vibration, and strain. The application of the digital image correlation technique to study ASR-related degradation on a large concrete sample at the University of Tennessee Knoxville is discussed and observations are presented in this report.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

A round-robin approach provides a detailed assessment of biomolecular small-angle scattering data reproducibility and yields consensus curves for benchmarking

Through an expansive international effort that involved data collection on 12 small-angle X-ray scattering (SAXS) and four small-angle neutron scattering (SANS) instruments, 171 SAXS and 76 SANS measurements for five proteins (ribonuclease A, lysozyme, xylanase, urate oxidase and xylose isomerase) were acquired. From these data, the solvent-subtracted protein scattering profiles were shown to be reproducible, with the caveat that an additive constant adjustment was required to account for small errors in solvent subtraction. Further, the major features of the obtained consensus SAXS data over the q measurement range 0–1 Å −1 are consistent with theoretical prediction. The inherently lower statistical precision for SANS limited the reliably measured q -range to <0.5 Å −1 , but within the limits of experimental uncertainties the major features of the consensus SANS data were also consistent with prediction for all five proteins measured in H 2 O and in D 2 O. Thus, a foundation set of consensus SAS profiles has been obtained for benchmarking scattering-profile prediction from atomic coordinates. Additionally, two sets of SAXS data measured at different facilities to q > 2.2 Å −1 showed good mutual agreement, affirming that this region has interpretable features for structural modelling. SAS measurements with inline size-exclusion chromatography (SEC) proved to be generally superior for eliminating sample heterogeneity, but with unavoidable sample dilution during column elution, while batch SAS data collected at higher concentrations and for longer times provided superior statistical precision. Careful merging of data measured using inline SEC and batch modes, or low- and high-concentration data from batch measurements, was successful in eliminating small amounts of aggregate or interparticle interference from the scattering while providing improved statistical precision overall for the benchmarking data set.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Distributed Cross-Channel Hierarchical Aggregation for Foundation Models

Vision-based scientific foundation models hold significant promise for advancing scientific discovery and innovation. This potential stems from their ability to aggregate images from diverse sources—such as varying physical groundings or data acquisition systems—and to learn spatio-temporal correlations using transformer architectures. However, tokenizing and aggregating images can be compute-intensive, a challenge not fully addressed by current distributed methods. In this work, we introduce the Distributed Cross-Channel Hierarchical Aggregation (D-CHAG) approach designed for datasets with a large number of channels across image modalities. Our method is compatible with any model-parallel strategy and any type of vision transformer architecture, significantly improving computational efficiency. We evaluated D-CHAG on hyperspectral imaging and weather forecasting tasks. When integrated with tensor parallelism and model sharding, our approach achieved up to a 75% reduction in memory usage and more than doubled sustained throughput on up to 1,024 AMD GPUs on the Frontier Supercomputer.

Tsaris, Aristeidis (aris) [ORNL] (ORCID:0000000277↗