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DOE OSTI2025

Short-Term Electric Load Forecasting for a Residential Household in Alaska

Accurate short-term load forecasting at a fine scale is essential for demand response programs, peak shaving, and load-shedding strategies [1]. While traditionally, only aggregate short-term consumption data was available, advanced metering infrastructure (AMI) now provides data at the individual consumer level [1]. There is increasing interest in utilizing this data for short-term load forecasting (from an hour to a few days) to optimize grid operations. Electricity consumption in individual households is highly influenced by residents’ personal behaviors [2]. As a result, unlike aggregate loads, electrical power usage in single households often shows significant volatility, making meter-level load forecasting for individual users particularly challenging [3], [4]. Deep learning methods, with their strong ability to model nonlinear data, have become popular for improving the accuracy of household electricity consumption forecasting [4]. Notably, the Long ShortTerm Memory (LSTM) has attracted significant attention [5], [6].

42 ENGINEERING↗

DOE OSTI2025

Predicting High‐Resolution Spatial and Spectral Features in Mass Spectrometry Imaging with Machine Learning and Multimodal Data Fusion

Recent advancements in molecular Mass Spectrometry Imaging have sparked interest in integrating high spatial resolution methods with molecular mass-spectrometry-based chemical imaging. Fusion-based algorithms have proven effective in generating high spatial-resolution molecular mass spectra. However, a significant challenge stems from the differing physical mechanisms underlying image generation and data upsampling techniques, potentially leading to discrepancies in integrated information channels. Integrating physical constraints into data processing workflows is essential to tackle this issue. In this study, we propose an innovative approach that merges data from Fourier transform ion cyclotron resonance (FTICR), time-of-flight matrix-assisted laser desorption/ionization, and time-of-flight secondary ion mass spectrometry imaging techniques. By leveraging FT-ICR's unparalleled spectral resolution and ToF-SIMS's exceptional spatial resolution, we achieve submicron spatial resolution, enabling the observation of intact molecular species with remarkable spectral precision. Canonical correlation analysis is employed to incorporate physical constraints. Through sophisticated image processing and machine learning techniques, the results of this fusion hold significant promise for advancing our comprehension of complex systems and unveiling concealed molecular intricacies.

canonical correlation analysis↗

NASA NTRS2012

Performance and Loads Correlation of a UH-60A Slowed Rotor at High Advance Ratios

Measured data from the slowed rotor part of the 2010 UH-60A Airloads Rotor test in the NASA Ames 40- by 80- Foot Wind Tunnel are compared with CAMRAD II calculations. The emphasis in this initial study is to correlate overall trends. This analytical effort considers advance ratios from 0.3 to 1.0, with the rotor rotational speed at 40%NR. The rotor performance parameters considered are the thrust coefficient, power coefficient, L/DE, torque, and H-force. The blade loads considered are the half peak-to-peak, mid-span and outboard torsion, flatwise, and chordwise moments, and the pitch link load. For advance ratios . 0.7, the overall trends for the performance and loads (excluding the pitch link load) could be captured, but with substantial overprediction or underprediction. The correlation gradually deteriorates as the advance ratio is increased and for advance ratios . 0.8 there is no correlation. The pitch link load correlation is not good. There is considerable scope for improvement in the prediction of the blade loads. Considering the modeling complexity associated with the unconventional operating condition under consideration, the current predictive ability to capture overall trends is encouraging.

Kottapalli, Sesi B.↗

DOE OSTI2020

Open Energy Data Initiative (OpenEDI) - Open Data Access Tools (OEDI-ODAT) [SWR 20-57]

Open Energy Data Initiative (OpenEDI): Advancing Analytics and Research Innovation through Improved Data Access. The Open Energy Data Initiative (OEDI) aims to improve and automate access of high-value energy data sets across the U.S. Department of Energy’s (DOE’s) programs, offices, and national laboratories. Sponsored by the DOE, this platform is being implemented by the National Renewable Energy Laboratory (NREL) to make data actionable and discoverable by researchers and industry to accelerate analysis and advance innovation. Partners at other national laboratories will help utilize the platform for analysis, can be directly involved in determining requirements, and will be resources for providing new datasets that can be shared with the public to expand innovation.

Rager, David↗

NASA NTRS1980

Orbit Transfer Vehicle (OTV) advanced expander cycle engine point design study. Task 7: Engine data summary

A performance optimized engine system design for a man-rated advanced LOX/hydrogen expander cycle engine was investigated. The data are presented in tables, figures, and drawings. The following categories of data for the advanced expander cycle engine are presented: engine operating specification and pressure schedule; engine system layout drawing; major component layout drawings, including thrust chamber and nozzle, extendible nozzle actuating mechanism and seal, LOX turbopump, LOX boost pump, hydrogen turbopump, hydrogen boost pump, and propellant control valves; engine performance and service life prediction; engine weight; and engine envelope. The data represent updates based upon current results from the design and analyses tasks performed under contract. Futher iterations in the designs and data can be expected as the advanced expander cycle engine design matures.

Christensen, K. L.↗

NASA NTRS2019

Medical Data Architecture (MDA) Project Status

The Medical Data Architecture (MDA) project supports the Exploration Medical Capability (ExMC) risk to minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the ExMC MDA project addresses the technical limitations identified in ExMC Gap Med 07: We do not have the capability to comprehensively process medically-relevant information to support medical operations during exploration missions. This gap identifies that the current in-flight medical data management includes a combination of data collection and distribution methods that are minimally integrated with on-board medical devices and systems. Furthermore, there are a variety of data sources and methods of data collection. For an exploration mission, the seamless management of such data will enable a more medically autonomous crew than the current paradigm. The medical system requirements are being developed in parallel with the exploration mission architecture and vehicle design. ExMC has recognized that in order to make informed decisions about a medical data architecture framework, current methods for medical data management must not only be understood, but an architecture must also be identified that provides the crew with actionable insight to medical conditions. This medical data architecture will provide the necessary functionality to address the challenges of executing a self-contained medical system that approaches crew health care delivery without assistance from ground support. Hence, the products supported by current prototype development will directly inform exploration medical system requirements.In fiscal year 2018, the MDA project developed Test Bed 2, the second iteration in a series of prototypes with functionality focused on data security through role-based access control and encryption, integration with One Portal exercise software and ingestion of an ultrasound Digital Imaging and Communications in Medicine (DICOM) file and image display. Test Bed 2 advances the medical data system architecture framework by providing these functionalities in a scalable system that maintained a layered, modular design. The architecture framework uses a data services approach with role-based access to data in a customized medical record system suitable for space exploration. These functionalities were demonstrated as part of the Next Space Technologies for Exploration Partnerships (NextSTEP) ground test demonstrated at the NASA Johnson Space Center Integrated Power, Avionics and Software (iPAS) facility. Interfacing to a Core Flight Software (CFS) system, the MDA system, using Consultative Committee for Space Data Systems (CCSDS) protocol, transferred an exercise file from the simulated flight MDA system to a mirrored MDA system on the ground through the CFS system. The selection of data sources and demonstrations enabled the team to address stakeholder concerns throughout the development process. In the next iteration, the MDA team will work with stakeholders to identify additional relevant functionalities to further advance system data models, standards and principles that will inform the medical system requirements development.

medical data architecture↗

DOE OSTI2022

Visualization Tool for Comparing Low-Carbon Energy Options

This project developed a web based visualization tool for comparing current and future nuclear fuel cycle options to low-carbon and conventional energy technologies in the United States. While nuclear power is well established as the gold-standard for baseload power production and also as the technology with the lowest overall carbon intensity of any commercial form of electricity generation. This project develop a web-based tool for electricity producers and consumers to compare renewable and conventional energy technologies to the conventional and advanced nuclear fuel cycle options. The work leveraged data on land use, carbon intensity, unit cost and pricing data for renewables from the open literature. Input data from the Advanced Fuel Cycle Cost Basis report will be used for current and advanced nuclear power systems. We coupled these data to energy flow and lifecycle models for user-selected energy generation and storage types. We will display economic comparisons from the perspectives of generators and consumers, as well as carbon production, land use, and reliability comparisons.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2026

Modeling Framework for Data Center

This chapter highlights the critical need for advanced modeling of data centers due to their rapidly increasing energy consumption and impact on grid reliability. Driven by the demand for AI applications, data centers are projected to consume a significant portion of US energy by 2028, putting stress on an already challenged power grid. The chapter emphasizes the importance of "fast" time-scale models to understand the dynamic interactions between data centers and the grid, especially given the rapid power fluctuations of AI workloads. It outlines a modeling framework that includes both offline and real-time EMT domain simulations, detailing the necessary representations for various components like utility interfaces, transformers, IT loads, UPS, cooling loads, Battery Energy Storage Systems (BESS), generators, protection systems, and higher-level control systems. While standard simulation tools like PSCAD offer basic models, custom development is often required to accurately capture the unique and fast-changing behaviors of modern data centers. The chapter also discusses key metrics and test cases for validating these models, focusing on transient load responses, protection relay coordination, and demand flexibility. Finally, it addresses the challenges of modeling large-scale data centers, such as computational complexity and the trade-off between model fidelity and practicality, suggesting hybrid modeling approaches as a solution. The overarching goal is to create a robust framework that helps assess data center impacts on grid stability, identify vulnerabilities, and inform the development of standards for reliable integration of these large loads into the bulk power system.

25 ENERGY STORAGE↗

DOE OSTI2023

Tutorial: Lessons Learned for Behavior Analysts from Data Scientists

Big data is a computing term used to refer to large and complex data sets, typically consisting of terabytes or more of diverse data that is produced rapidly. The analysis of such complex data sets requires advanced analysis techniques with the capacity to identify patterns and abstract meanings from the vast data. The field of data science combines computer science with mathematics/statistics and leverages artificial intelligence, in particular machine learning, to analyze big data. This field holds great promise for behavior analysis, where both clinical and research studies produce large volumes of diverse data at a rapid pace (i.e., big data). This article presents basic lessons for the behavior analytic researchers and clinicians regarding integration of data science into the field of behavior analysis. We provide guidance on how to collect, protect, and process the data, while highlighting the importance of collaborating with data scientists to select a proper machine learning model that aligns with the project goals and develop models with input from human experts. Here, we hope this serves as a guide to support the behavior analysts interested in the field of data science to advance their practice or research, and helps them avoid some common pitfalls.

42 ENGINEERING↗

NASA NTRS2003

Atic Experiment: Flight Data Processing

The Advanced Thin Ionization Calorimeter (ATIC) is a balloon borne experiment to measure the composition and energy spectra of Z = 1 to 28 cosmic rays over the energy range approx. 30 GeV - 100 TeV. The instrument consists of a fully active 320-crystal Bismuth Germanate (BGO) calorimeter, 202 scintillator strips in 3 hodoscopes interleaved with a graphite target, and a 4480-pixel silicon matrix charge detector. ATIC has had two successful Long Duration Balloon flights from McMurdo, Antarctica: from 12/28/00 to 01/13/01 and from 12/29/02 to 01/18/03. We have developed the ATIC Data Processing System (ADPs), which is an Object Oriented data processing program based on ROOT. In this paper, we describe the processing scheme used in handling the flight data, especially the calibration method and the event reconstruction algorithm.

Ahn, H. S.↗

NASA NTRS1992

Comparison of preliminary results from Airborne Aster Simulator (AAS) with TIMS data

The Japanese Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER), being developed for a NASA EOS-A satellite, will have 3 VNIR, 6 SWIR, and 5 TIR (8-12 micron) bands. An Airborne ASTER Simulator (AAS) was developed for Japan Resources Observation System Organization (JAROS) by the Geophysical Environmental Research Group (GER) Corp. to research surface temperature and emission features in the MWIR/TIR, to simulate ASTER's TIR bands, and to study further possibility of MWIR/TIR bands. ASTER Simulator has 1 VNIR, 3 MWIR (3-5 microns), and 20 (currently 24) TIR bands. Data was collected over 3 sites - Cuprite, Nevada; Long Valley/Mono Lake, California; and Death Valley, California - with simultaneous ground truth measurements. Preliminary data collected by AAS for Cuprite, Nevada is presented and AAS data is compared with Thermal Infrared Multispectral Scanner (TIMS) data.

Kannari, Yoshiaki↗

NASA NTRS2012

An Assessment of Comprehensive Code Prediction State-of-the-Art Using the HART II International Workshop Data

Despite significant advancements in computational fluid dynamics and their coupling with computational structural dynamics (= CSD, or comprehensive codes) for rotorcraft applications, CSD codes with their engineering level of modeling the rotor blade dynamics, the unsteady sectional aerodynamics and the vortical wake are still the workhorse for the majority of applications. This is especially true when a large number of parameter variations is to be performed and their impact on performance, structural loads, vibration and noise is to be judged in an approximate yet reliable and as accurate as possible manner. In this paper, the capabilities of such codes are evaluated using the HART II Inter- national Workshop data base, focusing on a typical descent operating condition which includes strong blade-vortex interactions. Three cases are of interest: the baseline case and two cases with 3/rev higher harmonic blade root pitch control (HHC) with different control phases employed. One setting is for minimum blade-vortex interaction noise radiation and the other one for minimum vibration generation. The challenge is to correctly predict the wake physics - especially for the cases with HHC - and all the dynamics, aerodynamics, modifications of the wake structure and the aero-acoustics coming with it. It is observed that the comprehensive codes used today have a surprisingly good predictive capability when they appropriately account for all of the physics involved. The minimum requirements to obtain these results are outlined.

vanderWall, Berend G.↗

NASA NTRS2009

American Meteorological Society (AMS) - The Modern Era Retrospective-Analysis for Research and Applications (MERRA) Data and Accessibility

The AM Short Course on The Modern Era Retrospective-analysis for Research and Applications (MERRA) data and accessibility will be held on January 11, 2009 preceding the 89th Annual Meeting in Phoenix, Arizona. Preliminary programs, registration, hotel, and general information will be posted on the AMS Web site in mid-September 2008. Retrospective-analyses (or reanalyses) have been established as an important tool in weather and climate research over the last decade. As computer power increases, the data assimilation and modeling systems improve and become more advanced, the input data quality increases and so reanalyses become more reliable. In 2008, NASA Global Modeling and Assimilation Office began producing a new reanalysis called the Modem Era Retrospective-analysis for Research and Applications (MERRA). The initial data from the reanalysis has been made available to the community and should be complete through 30 years (1979-present) by Fall of 2009. MERRA has taken advantage of the advancement of computing resources to provide users more data than previously available. The native spatial resolution is nominally 1/2 degrees and the surface two dimensional data are one hourly frequency. In addition to the meteorological analysis data, complete mass, energy and momentum budget data and also stratospheric data are provided. The eventual data holdings will exceed 150Tb. In order to facilitate user accessibility to the data, it will be stored in online hard drives (not tape storage) and available through several portals. Subsetting tools will also be available to allow users to tailor their data requests. The goals of this short course are to provide hands on users of reanalyses instruction on MERRA systems and also interactive experience with the online data and access tools. The course is intended for students and research scientists who will be actively interested in accessing and applying MERRA data in their weather, climate or applications work. The course has three parts. There will be an overview of the MERRA system, the validation of the system and the native data format. Second, Instructors will provide examples of weather and climate data analysis using various software packages (primarily GrADS) as well as the online access tools for subsetting and download, as well as visualization (e.g. Giovanni and Google Earth). This will also include examples on changing the data format to fit user's preferences and also to regrid the data for comparisons to other reanalyses and observational data. Lastly, there will he time set aside for participants to have hands on access to the data and software while interacting with the instructors and other developers. The course convener is Dr. Michael Bosilovich, NASA GSFC Global Modeling and Assimilation Office (GMAO). He will be joined by several GMAO, Goddard Earth Science Data and information Services Center (GES DISC) and Software Integration and Visualization Office (SIVO) staff.

daSilva, Arlindo↗

DOE OSTI2021

Nuclear Science for the Manhattan Project and Comparison to Today’s ENDF Data

Nuclear physics advances in the United States and Britain from 1939 to 1945 are described. The Manhattan Project’s work led to an explosion in our knowledge of nuclear science. A conference in April 1943 at Los Alamos provided a simple formula used to compute critical masses and laid out the research program needed to determine the key nuclear constants. In short order, four university accelerators were disassembled and reassembled at Los Alamos, and methods were established to make measurements on extremely small samples owing to the initial lack of availability of enriched 235U and plutonium. I trace the program that measured fission cross sections, fission-emitted neutron multiplicities and their energy spectra, and transport cross sections, comparing the measurements with our best understanding today as embodied in the Evaluated Nuclear Data File ENDF/B-VIII.0. The large nuclear data uncertainties at the beginning of the project, which often exceeded 25% to 50%, were reduced by 1945 often to less than 5% to 10%. Uranium-235 and plutonium-239 fission cross-section assessments in the fast mega-electron-volt range were reduced following more accurate measurements, and the neutron multiplicity $\overline{v}$ increased. By a lucky coincidence of canceling errors, the initial critical mass estimates were close to the final estimated masses. Some images from historical documents from our Los Alamos archives are shown. Many of the original measurements from these early years have not previously been widely available. Through this work, these data have now been archived in the international experimental nuclear reaction data library (EXFOR) in a collaboration with the International Atomic Energy Agency and Brookhaven National Laboratory.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1983

Techniques for diagnosing mesoscale phenomena affecting aviation using VAS satellite data

A major advance in geostationary satellite observations occurred recently with the inclusion of an experimental instrument aboard the latest Geostationary Operational Environmental Satellites (GOES). This instrument, called the Visible Infrared Spin-Scan Radiometer (VISSR) Atmospheric Sounder (VAS), permits simultaneous observations of the atmosphere in up to 12 infrared channels, in addition to the visible image. In the present investigation, particular emphasis is placed on the ability of VAS imagery and derived soundings to delineate isolated, meso-scale regions of convective instability. The results of the investigation point to the ability of the VAS instrument to delineate meteorologically meaningful patterns of low-level moisture and mid-level dryness and to the utility of the image overlay procedure for isolating, in real time, regions of convective potential, at time and space scales unresolvable using radiosonde data alone.

Petersen, R. A.↗

NASA NTRS1986

Proceedings of the Second Airborne Imaging Spectrometer Data Analysis Workshop

The Second Airborne Imaging Spectrometer (AIS) Data Analysis Workshop was held at the Jet Propulsion Laboratory on May 6, 7, and 8, 1986. It was attended by 100 people from seven countries. Papers were presented by 24 attendees; summaries of 19 of the papers are published in these Workshop Proceedings. The Second Workshop was divided into three sessions: Calibration, the Atmosphere, and Data Techniques; Geological Research; and Botanical and Geobotanical Research. Because many of the AIS researchers have had an additional year to work with their data, a general advance was seen in the utilization of the data for solving earth science problems. The major conclusions that can be drawn from the Workshop are: (1) Almost everyone now working with AIS data is attempting to take into account in data analysis the effects of the atmosphere and sensor calibration and performance. As a result, information extraction techniques are becoming more sophisticated and effective. (2) The emphasis on work in the geological disciplines is beginning to shift to the application of AIS data for solving geological problems now that the efficacy of the data for mineral identification has been demonstrated. (3) In the botanical sciences, interpretation of AIS data is becoming more quantitative. Several statistical techniques are under development for extracting the subtle differences in plant spectra in the region of the near infrared and short wavelength infrared. In summary, an overall advance was seen in the ability to effectively utilize the fundamentally new class of data acquired with imaging spectrometers. There was also a general feeling at the Workshop however, that much work remains to be done in remote sensing research before the maximum potential of these data for solving earth science problems is realized.

Gregg Vane↗

NASA NTRS2004

Development of a Low Data Event Timer for Monitoring an Advancing Crack in Fracture

Monitoring the crack position and velocity in a fracture specimen can be difficult and laborious. In addition, the data storage requirements can be considerable depending upon the testing conditions. A low data event timer was developed to alleviate these problems. The test apparatus was applied to cantilever beams bonded with a structural epoxy and tested under different conditions such as stable to unstable transitions and different temperature extremes. The results indicate that the approach eliminates problems associated with other types of crack measurement and greatly simplifies the measuring process.

Macon, D. J.↗

DOE OSTI2023

Rapidly Changing Range Limits in a Warming World: Critical Data Limitations and Knowledge Gaps for Advancing Understanding of Mangrove Range Dynamics in the Southeastern USA

Climate change is altering species’ range limits and transforming ecosystems. For example, warming temperatures are leading to the range expansion of tropical, cold-sensitive species at the expense of their cold-tolerant counterparts. In some temperate and subtropical coastal wetlands, warming winters are enabling mangrove forest encroachment into salt marsh, which is a major regime shift that has significant ecological and societal ramifications. Here, we synthesized existing data and expert knowledge to assess the distribution of mangroves near rapidly changing range limits in the southeastern USA. We used expert elicitation to identify data limitations and highlight knowledge gaps for advancing understanding of past, current, and future range dynamics. Mangroves near poleward range limits are often shorter, wider, and more shrublike compared to their tropical counterparts that grow as tall forests in freeze-free, resource-rich environments. The northern range limits of mangroves in the southeastern USA are particularly dynamic and climate sensitive due to abundance of suitable coastal wetland habitat and the exposure of mangroves to winter temperature extremes that are much colder than comparable range limits on other continents. Thus, there is need for methodological refinements and improved spatiotemporal data regarding changes in mangrove structure and abundance near northern range limits in the southeastern USA. Advancing understanding of rapidly changing range limits is critical for foundation plant species such as mangroves, as it provides a basis for anticipating and preparing for the cascading effects of climate-induced species redistribution on ecosystems and the human communities that depend on their ecosystem services.

54 ENVIRONMENTAL SCIENCES↗