Search NASA⌕ Search

SEARCH · Search NASA

Results for “AWS performance”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Elastic Resource Management for Deep Learning Applications in a Container Cluster

The increasing demand for learning from massive datasets is restructuring our economy. Effective learning, however, involves nontrivial computing resources. Most businesses utilize commercial infrastructure providers (e.g., AWS) to host their computing clusters in the cloud, where various jobs compete for available resources. While cloud resource management is a fruitful research field that has made many advances in production, such as Kubernetes and YARN, few efforts have been invested to further optimize the system performance, especially for deep learning (DL) training jobs in a container cluster. This work introduces FlowCon, a system that is able to monitor the individual evaluation functions of DL jobs at runtime, and thus to make placement decisions on resource allocations elastically. Here, we present a detailed design and implementation of FlowCon and conduct intensive experiments over various DL models. The results demonstrate that FlowCon significantly improves DL job completion time and resource utilization efficiency, compared to default systems. According to the results, FlowCon is able to improve the completion time by up to 68.8% and meanwhile, reduce the makespan by 18.0%, in the presence of various DL job workloads.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Open Source Synergy: Developing and Validating PMU Data Analysis Techniques Using Open Source Tools and Datasets

This paper presents an exploration into the development and validation of data analysis approaches for Phasor Measurement Units (PMUs) using open-source datasets and tools. Various methods for event detection, event classification, frequency response, and oscillation analysis were tested. We leverage the capabilities of Archive Walker (AW), the Frequency Response Analysis Tool (FRAT), and the Oscillation Baselining and Analysis Tool (OBAT), all open-source tools, for efficient processing and analysis of synchrophasor data. The open-source Transmission Signature Library (TSL) dataset was employed as a dataset for a comprehensive evaluation to assess the performance and reliability of the proposed methods.

PMU, event analysis, oscillation, Frequency Respon↗
DOE OSTI2021

Verification of Maximal Oxygen Uptake in Active Military Personnel During Treadmill Running

Figueiredo, PS, Looney, DP, Pryor, JL, Doughty, EM, McClung, HL, Vangala, SV, Santee, WR, Beidleman, BA, and Potter, AW. Verification of maximal oxygen uptake in active military personnel during treadmill running. J Strength Cond Res 36(4): 1053–1058, 2022—It is unclear whether verification tests are required to confirm “true” maximal oxygen uptake ($\dot{V}_{o2}$max) in modern warfighter populations. Our study investigated the prevalence of $\dot{V}_{o2}$max attainment in U.S. Army soldiers performing a traditional incremental running test. In addition, we examined the utility of supramaximal verification testing as well as repeated trials for familiarization for accurate $\dot{V}_{o2}$max assessment. Sixteen U.S. Army soldiers (1 woman, 15men; age, 21±2 years; height, 1.73±0.06m; body mass, 71.6±10.1 kg) completed 2 laboratory visits, each with an incremental running test (modified Astrand protocol) and a verification test (110% maximal incremental test speed) on a motorized treadmill. We evaluated $\dot{V}_{o2}$max attainment during incremental testing by testing for the definitive $\dot{V}_{o2}$ plateau using a linear least-squares regression approach. Peak oxygen uptake ($\dot{V}_{o2}$peak) was considered statistically equivalent between tests if the 90% confidence interval around the mean difference was within 62.1 ml·kg -1 ·min -1 . Oxygen uptake plateaus were identified in 14 of 16 volunteers for visit 1 (87.5%) and all 16 volunteers for visit 2 (100%). Peak oxygen uptake was not statistically equivalent, apparent from the mean difference in $\dot{V}_{o2}$peak measures between the incremental test and verification test on visit 1 (2.3 ml·kg -1 ·min -1 , [1.3–3.2]) or visit 2 (1.1 ml·kg -1 ·min -1 [0.2–2.1]). Interestingly, $\dot{V}_{o2}$peak was equivalent, apparent from the mean difference in $\dot{V}_{o2}$peak measures between visits for the incremental tests (0.0ml·kg -1 ·min -1 [-0.8to 0.9]) but not the verification tests (-1.2 ml·kg -1 ·min -1 [-2.2 to -0.2]). Modern U.S. Army soldiers can attain $\dot{V}_{o2}$max by performing a modified Astrand treadmill running test. Additional familiarization and verification tests for confirming $\dot{V}_{o2}$max in healthy active military personnel may be unnecessary.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

eagles-project/haero

A toolbox for constructing performance portable aerosol packages

Johnson, Jeffrey N. [Cohere Consulting LLC]↗
NASA NTRS2008

Cross Calibration and Validation Using CLARREO

The presentation focuses on study questions, effort, and result. Study questions include a focus on MW/LW, error sources and what can be expected, how validation will be performed and what resolution is required, and spatial resolution required for cross-calibration. Study effort includes empirical approach by examining AIRS ,IASI and MODIS cross-calibration methods already in place and estimate the number of clear and Dome C observations possible versus spatial resolution. Study results include 5000 sampler per cross-calibration recommended, insufficient cloud free and Dome C AWS observations for cross calibration and validation at 100km, and less than 20 km IFOV at 100 km swath needed to achieve sufficient samples for cross-calibration of CLARREO.

calibration↗
NASA NTRSDate not supplied

SatCORPS Global Cloud Composite (GCC): the Design and Delivery of A High Quality, High Resolution, Global Cloud Product Available in Near-Real Time

The NASA Satellite ClOud and Radiation Property retrieval System (SatCORPS) supports the development of an analysis ready and cloud-optimized data transformation pipeline and geospatial service enablement of a global cloud composite (GCC) product derived from global geostationary satellite imagery. This geospatial service will be available at high temporal and spatial resolution via the SatCORPS web mapping application for visualization and analysis as well as direct ingestion to common geospatial software and custom programming. The resulting global cloud composite products from the processing pipeline can then be geospatially-service enabled as ArcGIS Image Services and Open Geospatial Consortium (OGC) Web Mapping/Coverage Services for visualization and analysis via a web mapping application and common geospatial software. Near real time global observations are created through the composition of five geostationary satellites that provides modelling and forecasting communities with the capability to provide high quality and timely information to start the projection process. The Global Cloud Composite product combines information from geostationary satellites, GOES-16, GOES-17, Himawari-8, Meteosat-11 and Meteosat-9 to create a single global composite netcdf file and images using the different products within the netcdf file. The SatCORPS team, though our Global Cloud Composite (GCC) product and web-based visualization tools including Geographical Information System (GIS) services provide near real time global cloud product information to both automated processes and traditional web users that is timely and high quality derived from geostationary satellites. The Global Cloud Composite product takes advantage of the scalable processing resources provided by the AWS batch service to provide new composites every thirty minutes. Because information from each of the low earth orbiting satellites is available on schedules tuned to the specific satellite, the processing algorithm temporally composites the final dataset as each satellite’s information becomes available. The SatCORPS team has leveraged our experience using Amazon Web Services (AWS) to build a low latency high availability tool that allows end users both human and automated to acquire high quality and high-resolution Geostationary Earth Orbiting (GEO) information at zero cost to the end user. This presentation will describe how we architected and implemented the service as well as lessons learned based on our experiences both developing and operating the system. The lessons learned include how we integrated multiple services including Amazon Batch, Amazon S3 and Amazon Lambda service to create a low cost but high-performance processing system that is capable of identifying and processing the most appropriate satellite overpass information into global cloud composites. We will also describe our web-based tools including our Geographic Information System that can be used for visualization and analysis. The products from the processing can be geospatially-service enabled as ArcGIS Image Services and Open Geospatial Consortium (OGC) Web Mapping/Coverage Services for visualization and analysis via a web mapping application and common geospatial software. The SatCORPS Global Composite Cloud product provides sophisticated global composited cloud research products with very low latency that we see that as filling a rapidly growing need in the research and modelling community with no up-front nor ongoing costs associated with downloading or using the information.

AWS AMCE SMCE GCC SATCORPS GLOBAL CLOUD COMPOSITE ↗
NASA NTRS2009

Evaluation of Margins of Safety in Brazed Joints

One of the essential steps in assuring reliable performance of high cost critical brazed structures is the assessment of the Margin of Safety (MS) of the brazed joints. In many cases the experimental determination of the failure loads by destructive testing of the brazed assembly is not practical and cost prohibitive. In such cases the evaluation of the MS is performed analytically by comparing the maximum design loads with the allowable ones and incorporating various safety or knock down factors imposed by the customer. Unfortunately, an industry standard methodology for the design and analysis of brazed joints has not been developed. This paper provides an example of an approach that was used to analyze an AlBeMet 162 (38%Be-62%Al) structure brazed with the AWS BAlSi-4 (Al-12%Si) filler metal. A practical and conservative interaction equation combining shear and tensile allowables was developed and validated to evaluate an acceptable (safe) combination of tensile and shear stresses acting in the brazed joint. These allowables are obtained from testing of standard tensile and lap shear brazed specimens. The proposed equation enables the assessment of the load carrying capability of complex brazed joints subjected to multi-axial loading.

Flom, Yury↗
NASA NTRS2017

Use of Schema on Read in Earth Science Data Archives

Traditionally, NASA Earth Science data archives have file-based storage using proprietary data file formats, such as HDF and HDF-EOS, which are optimized to support fast and efficient storage of spaceborne and model data as they are generated. The use of file-based storage essentially imposes an indexing strategy based on data dimensions. In most cases, NASA Earth Science data uses time as the primary index, leading to poor performance in accessing data in spatial dimensions. For example, producing a time series for a single spatial grid cell involves accessing a large number of data files. With exponential growth in data volume due to the ever-increasing spatial and temporal resolution of the data, using file-based archives poses significant performance and cost barriers to data discovery and access. Storing and disseminating data in proprietary data formats imposes an additional access barrier for users outside the mainstream research community. At the NASA Goddard Earth Sciences Data Information Services Center (GES DISC), we have evaluated applying the schema-on-read principle to data access and distribution. We used Apache Parquet to store geospatial data, and have exposed data through Amazon Web Services (AWS) Athena, AWS Simple Storage Service (S3), and Apache Spark. Using the schema-on-read approach allows customization of indexing spatially or temporally to suit the data access pattern. The storage of data in open formats such as Apache Parquet has widespread support in popular programming languages. A wide range of solutions for handling big data lowers the access barrier for all users. This presentation will discuss formats used for data storage, frameworks with This presentation will discuss formats used for data storage, frameworks with support for schema-on-read used for data access, and common use cases covering data usage patterns seen in a geospatial data archive.

cloud applications↗
DOE OSTI2022

Frontal Polymerization of Dihydrofuran Comonomer Facilitates Thermoset Deconstruction

Frontal ring-opening metathesis polymerization (FROMP) is a rapid, low-energy manufacturing reaction that is useful for curing thermosetting materials. FROMP of dicyclopentadiene (DCPD) results in poly(dicyclopentadiene) (p(DCPD)), a tough thermoset with excellent mechanical performance and chemical stability. Like most thermosets, p(DCPD) cannot be reprocessed and is therefore difficult to recycle. Previous work demonstrated that the incorporation of a small quantity of cleavable units in the strand segments of p(DCPD) networks enables their deconstruction. Here, we report that a commercially available multifunctional comonomer, 2,3-dihydrofuran (DHF), both acts as a potent Grubbs catalyst inhibitor during FROMP and introduces acid cleavable units. The resulting materials retain high performance characteristics, including glass-transition temperatures ranging from 115 to 165 °C and ultimate strength ranging from 35 to 40 MPa. The addition of DHF above critical loading levels enables deconstructable thermosets. Here, we further demonstrate freeform three-dimensional (3D) printing of deconstructable thermosets via frontal polymerization.

36 MATERIALS SCIENCE↗
NASA NTRS2019

Cloud Giovanni: Reining in Costs and Improving Performance with Analytical Data Stores Using Scalable Serverless Architecture

Giovanni is the Geospatial Interactive Online Visualization ANd aNalysis Infrastructure developed at NASA GES DISC which provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science data. It receives large number of user requests each day for a variety of analysis and visualization services, which leads to the big data challenge of serving gradually increasing large data volumes with diverse statistical algorithms. We hereby propose a multi-dimensional accumulation method which provides fast and cost-efficient cloud analysis for diverse services including both area averaging and time averaging. This method involves the weighted volume integration over multiple variable dimensions (time and space), and is implemented in AWS using Athena providing serverless and highly scalable data analysis. Compared to the standard method, this approach dramatically reduced the computational time by order of magnitude with a minimal AWS cost incurred. For example, for a benchmark of 10-year area averaging over the 1x1 degree daily variable, the computational time was reduced from minutes to seconds, and the Athena cost is only $5 for 100,000 requests.

Zhang, Hailiang↗
DOE OSTI2025

Ion Exchange Processing of AW-105 Hanford Tank Waste through Crystalline Silicotitanate in a Staged 2- then 3-Column System

The Hanford Site stores an estimated 56 million gallons of mixed radioactive and chemically hazardous waste in large underground tanks. In support of the Direct Feed Low-Activity Waste (DFLAW) Program for expediting Hanford tank waste supernate treatment, laboratory-scale ion exchange processing using prototypic unit operations was conducted on AW-105 tank waste at the Pacific Northwest National Laboratory Radiochemical Processing Laboratory. This report describes the small-scale ion exchange testing with 9.2 L of diluted and filtered supernate from Tank 241-AW-105 (hereafter referred to as AW-105) at 16 °C (62 °F). One of the waste acceptance criteria (WAC) for the Waste Treatment Plant (WTP) Low-Activity Waste Facility is that the waste must contain less than 3.18×10 -5 Ci 137 Cs per mole of Na. For the AW-105 tank waste to meet this criterion, only 0.225% of the influent 137 Cs concentration may be delivered to the WTP; this requires a Cs decontamination factor of 445. Testing with AW-105 matched current Tank Side Cesium Removal (TSCR) facility prototypic operations where a lead-lag configuration was used until the lag column reached the WAC limit, then a polish column was brought online for continued processing in a lead-lag-polish column configuration. Feed was processed at 1.9 bed volumes (BVs) per hour; the flowrate, in terms of contact time with the crystalline silicotitanate (CST) bed, matched the expected flowrate at TSCR. The Cs-decontaminated product was retained for vitrification testing (to be reported separately). The lead column reached 83% Cs breakthrough after processing ~1500 BVs of feed; the 50% Cs breakthrough was interpolated from the breakthrough data and occurred at 1041 BVs. Despite the AW-105 having a significantly higher K concentration (0.55 M compared to 0.10 M), testing compared to previous AP-107 ion exchange column testing at 16 °C showed no difference in BVs processed to reach the WAC on the lead column and only an approximate ~20 BV decrease in volume processed to reach the WAC limit on the lag column. The negligible differences in capacity despite the 5x concentration differences in K was determined to be due to the significantly lower NO3 concentration in the AW-105 supernate compared to the AP-107 tank waste matrix. A comparison in breakthrough curves for the two tests also indicated slightly faster kinetic behavior in the AW-105, with the variations in feed matrices (lower NO3 concentration) likely responsible for the deviation. The Cs effluent from the lag column reached the WAC limit after processing 772 BVs. Anticipating this breakthrough point, the polish column was preemptively installed around 675 BVs. Cs breakthrough from the lag column began at 300 BVs, reaching 1.10×10 1 µCi/mL, or 14.13 % Cs breakthrough, after processing all 1500 BVs of feed. The polish column processed nominally 830 BVs and reached 2.10×10 -1 µCi/mL, or 0.27 % Cs breakthrough at the conclusion of the test. Table S.1 and Figure S.1 summarize the observed column performance and relevant Cs loading characteristics.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRSDate not supplied

Improving Access to the GEOS Composition Forecast Model with API Development and Ingestion into Google Earth Engine

The GEOS Composition Forecast (GEOS-CF) model produces forecast and historical estimates of atmospheric composition and meteorology fields, which provide useful insight into air quality issues and events. In a year for which Canadian wildfires created adverse air quality conditions in the eastern United States, access to model fields such as PM2.5 are in high demand. The GEOS-CF team at the NASA Global Modeling and Assimilation Office (GMAO) first developed in-house solutions to improve data access via the CF API, and recently partnered with Google to ingest a collated set of model diagnostics into the Google Earth Engine (GEE) data repository. GEOS-CF model output is also being ingested into AWS storage. Creating these various open access points to GEOS-CF model diagnostics provides the public with an opportunity to easily interact with air quality information. Users are able to use a temporally consistent global grid of air quality fields in machine learning applications, mapping tools, and data informatics. Hosting GEOS-CF forecasts and the historical timeseries of these chemistry and meteorology fields in GEE allows users to create dynamic JavaScript-based air quality applications in the GEE code editor. GEOS-CF users can also access the model output via the GEE Python application programming interface (API), making it easy to perform various analyses with Python. This presentation will show two examples of accessing the GEOS-CF model through GEE. The first is an example application made in the GEE code editor which allows users to view time series plots and downscaled maps of surface level NO2. The second example exhibits using the GEE Python API to create a machine learning model to temporally gap-fill between air quality observations. These examples are an introduction to the many possible benefits of having open access to the GEOS-CF model through multiple platforms.

Callum Wayman↗
NASA NTRSDate not supplied

Improving Access to the GEOS Composition Forecast Model with API Development and Ingestion into Google Earth Engine

The GEOS Composition Forecast (GEOS-CF) model produces forecast and historical estimates of atmospheric composition and meteorology fields, which provide useful insight into air quality issues and events. In a year for which Canadian wildfires created adverse air quality conditions in the eastern United States, access to model fields such as PM2.5 are in high demand. The GEOS-CF team at the NASA Global Modeling and Assimilation Office (GMAO) first developed in-house solutions to improve data access via the CF API, and recently partnered with Google to ingest a collated set of model diagnostics into the Google Earth Engine (GEE) data repository. GEOS-CF model output is also being ingested into AWS storage. Creating these various open access points to GEOS-CF model diagnostics provides the public with an opportunity to easily interact with air quality information. Users are able to use a temporally consistent global grid of air quality fields in machine learning applications, mapping tools, and data informatics. Hosting GEOS-CF forecasts and the historical timeseries of these chemistry and meteorology fields in GEE allows users to create dynamic JavaScript-based air quality applications in the GEE code editor. GEOS-CF users can also access the model output via the GEE Python application programming interface (API), making it easy to perform various analyses with Python. This presentation will show two examples of accessing the GEOS-CF model through GEE. The first is an example application made in the GEE code editor which allows users to view time series plots and downscaled maps of surface level NO 2 . The second example exhibits using the GEE Python API to create a machine learning model to temporally gap-fill between air quality observations. These examples are an introduction to the many possible benefits of having open access to the GEOS-CF model through multiple platforms.

Callum Wayman↗
DOE OSTI2024

Hydrogen and its Vital Role in a Clean Energy Future

Large-scale, low -cost hydrogen production can enable an economically competitive, secure, and environmentally beneficial future energy system across multiple sectors. Furthermore, clean hydrogen can address specific sectors that are hard to decarbonize (e.g., heavy-duty trucking, load-following electricity, iron, steel, and cement) and can help the U.S. meet the net zero carbon goal by 2050. To achieve this goal, tens of millions of metric tons of clean, reliable, and affordable hydrogen will be needed annually1. In 2021, the Hydrogen Energy Earthshot was launched, and its goal is to reduce the cost of clean hydrogen to $1 per $1 kilogram in 1 decade (1 1 1) 2. One very promising pathway for large-scale hydrogen production is water splitting. Water splitting technologies range from commercial technologies such as electrolyzers to approaches that are at a much earlier stage of development, such as photoelectrochemical (PEC) and thermochemical (TCH) processes. All these water splitting pathways offer diverse benefits in energy storage, grid services, and cross-sector emissions reductions while taking advantage of the diverse domestic resources. However, critical materials-, component- and system-level challenges must be addressed to improve efficiency and durability and reduce cost. To address these barriers and move these promising and high impact technologies forward, the HydroGEN Advanced Water Splitting Materials (AWSM) and the H2 from the Next-generation of Electrolyzers of Water (H2NEW) consortia were formed and supported by the Department of Energy (DOE) EERE Hydrogen and Fuel Cell Technologies Office (HFTO). HydroGEN (https://www.energy.gov/eere/h2awsm/) consortium, established in 2016, is an Energy Materials Network (EMN) that aims to accelerate the materials R&D of low technology readiness level (TRL) advanced water splitting (AWS) technologies. The consortium comprises five core national laboratories and focuses on four early-stage AWS pathways: alkaline exchange membrane (AEM) electrolysis, proton conducting solid oxide electrolysis (p-SOEC), photoelectrochemical, and thermochemical water splitting. Liquid alkaline and PEM electrolyzers are already commercial and significant advancements in oxygen conducting solid oxide electrolysis cells (o-SOECs) have been realized. Yet, these systems are still too expensive and not sufficiently durable for wide-scale commercialization. To enable high-volume manufacturing of affordable, durable, efficient electrolyzers, H2NEW (https://h2new.energy.gov/), another multi-lab consortium, was established in 2020. This comprehensive, concerted effort is focused on overcoming barriers related to components and materials integration and scale-up to achieve performance, durability, with an initial focus to achieve $2/kg H2 by 2026.

AEM↗
NASA NTRS2003

Flaw Tolerance in Lap Shear Brazed Joints

Furnace brazing is a joining process used in the aerospace and other industries to produce strong permanent and hermetic structural joints. As in any joining process, brazed joints have various imperfections and defects. At the present time, our understanding of the influence of the internal defects on the strength of the brazed joints is not adequate. The goal of this 3-part investigation is to better understand the properties and failure mechanisms of the brazed joints containing defects. This study focuses on the behavior of the brazed lap shear joints because of their importance in manufacturing aerospace structures. In Part 1, an average shear strength capability and failure modes of the single lap joints are explored. Stainless steel specimens brazed with pure silver are tested in accordance with the AWS C3.2 standard. Comparison of the failure loads and the ultimate shear strength with the Finite Element Analysis (FEA) of the same specimens as a function of the overlap widths shows excellent correlation between the experimental and calculated values for the defect-free lap joints. A damage zone criterion is shown to work quite well in understanding the failure of the braze joints. In Part 2, the findings of the Part 1 will be verified on the larger test specimens. Also, various flaws will be introduced in the test specimens to simulate lack of braze coverage in the lap joints. Mechanical testing and FEA will be performed on these joints to verify that behavior of the flawed ductile lap joints is similar to joints with a reduced braze area. Finally, in Part 3, the results obtained in Parts 1 and 2 will be applied to the actual brazed structure to evaluate the load-carrying capability of a structural lap joint containing discontinuities. In addition, a simplified engineering procedure will be offered for the laboratory testing of the lap shear specimens.

Flom, Yury↗
DOE OSTI2026

High finesse buckled microcavities

Optical cavities are widely used in modern science and technology to enable a wide range of both quantum and classical applications. Recently, the growing demand for miniaturization and high performance has fueled the exploration of new fabrication methods beyond traditional polishing techniques and macroscopic mirrors. Visible and near-infrared (NIR) wavelengths are particularly important for quantum applications, where achieving low-loss resonators is also more challenging than in the telecom range, presenting unique challenges and opportunities for microscopic cavity systems. Here, we present a fabrication method for making NIR microcavities using buckled dielectric membrane mirrors, achieving a record finesse of 0.9 million at 780 nm for microcavities. We demonstrated flexible device geometries—including singular mirrors and mirror arrays, featuring radii of curvature ranging from 1 to 10 mm. The fabrication process offers high uniformity, high yield, and robust performance across a wide range of cavity lengths. Additionally, we can produce easy-to-assemble microcavity packages, with a total volume of ~2(4) mm 3 , featuring optical modes with a linewidth of 5.16 MHz (570 kHz) and a free spectral range (FSR) of 3.18 THz (150 GHz). Our results extend the frontier of microcavity fabrication for classical and quantum photonic technologies.

Ding, Sophie Weiyi [Harvard Univ., Cambridge, MA (↗
DOE OSTI2026

Cloud-Based Demonstration of the Eastern Interconnection Situational Awareness Monitoring System (ESAMS)

This report describes a cloud-based implementation and field demonstration of the Eastern Interconnection Situational Awareness and Monitoring System (ESAMS). ESAMS was developed to support the detection and source localization of forced oscillations using synchrophasor measurements from tie-lines connecting areas served by different reliability coordinators (RCs), so that RCs could better coordinate their response to wide-area events. A previous effort had identified deployment barriers associated with hosting shared situational awareness tools at a single RC. To address these barriers, ESAMS was migrated to Amazon Web Services and evaluated in a six-month field demonstration. ISO New England (ISO-NE) and PJM streamed data to the platform using AWS Direct Connect and a site-to-site VPN, respectively. The resulting multi-utility measurement footprint enabled regional source localization across major portions of the U.S. Eastern Interconnection and supported routine identification of oscillation events. During the final three months of the trial, 24 events above 2 MW/MVAR were detected. The largest detected oscillation approached a 25 MW peak-to-peak amplitude, and the longest persisted intermittently for more than 11 hours. The demonstration also assessed operational considerations—including data transfer volumes, end-to-end latency, and cloud computing costs—and found that network and compute requirements were modest relative to typical cloud capabilities while providing performance comparable to prior on-premises deployments. Overall, the results indicate that cloud hosting can provide a practical path to shared interconnection-wide oscillation monitoring. The cloud ESAMS demonstration establishes a foundation for broader utility participation and for building future wide-area analytics that leverage measurements across organizational boundaries.

Follum, James D.↗
DOE OSTI2020

Evaporated Se x Te 1-x Thin Films with Tunable Bandgaps for Short-Wave Infrared Photodetectors

Semiconducting absorbers in high-performance short-wave infrared (SWIR) photodetectors and imaging sensor arrays are dominated by single-crystalline germanium and III-V semiconductors. However, these materials require complex growth and device fabrication procedures. In this work, thermally evaporated Se x Te 1- x alloy thin films with tunable bandgaps for the fabrication of high-performance SWIR photodetectors are reported. From absorption measurements, it is shown that the bandgaps of Se x Te 1- x films can be tuned continuously from 0.31 eV (Te) to 1.87 eV (Se). Owing to their tunable bandgaps, the peak responsivity position and photoresponse edge of Se x Te 1- x film-based photoconductors can be tuned in the SWIR regime. By using an optical cavity substrate consisting of Au/Al 2 O 3 to enhance its absorption near the bandgap edge, the Se 0.32 Te 0.68 film (an optical bandgap of ≈0.8 eV)-based photoconductor exhibits a cut-off wavelength at ≈1.7 μm and gives a responsivity of 1.5 AW -1 and implied detectivity of 6.5 × 10 10 cm Hz 1/2 W -1 at 1.55 μm at room temperature. Importantly, the nature of the thermal evaporation process enables the fabrication of Se 0.32 Te 0.68 -based 42 × 42 focal plane arrays with good pixel uniformity, demonstrating the potential of this unique material system used for infrared imaging sensor systems.

36 MATERIALS SCIENCE↗