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

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Assessment of dislocation reduction on 100 mm diameter bulk GaN grown by the NEAT method

X-ray topography measurements on a 100 mm diameter GaN boule grown by the Near Equilibrium AmmonoThermal method revealed an improvement in dislocation density from >1 × 10 6 cm -2 to between 2 × 10 5 and 5 × 10 5 cm -2, an improvement greater than two to five times from seed to growth. This data builds on previous X-ray diffraction and defect selective etching to quantify the reduction in defect density that is closely associated with increasing growth thickness. This result indicates that there is a pathway to further dislocation reduction by increasing growth thickness for GaN crystals including those of 100 mm or larger diameter. Further reduction of the dislocation density of large-area substrates will lead to GaN power devices with reduced leakage current under reverse bias and better device performance.

36 MATERIALS SCIENCE↗
NASA NTRS1985

Front-End Program for SYSGEN

SYSGEN, Power Generation System Production costing and Reliability Analysis program, simulates production costs and reliability of electric utility with and without time-dependent generating units. FEPS transforms inputs into proper formats, builds data files and adds Job Control Language necessary to running SYSGEN program.

Carlson, C. R.↗
NASA NTRS1993

Operation of the helicopter antenna radiation prediction code

HARP is a front end as well as a back end for the AMC and NEWAIR computer codes. These codes use the Method of Moments (MM) and the Uniform Geometrical Theory of Diffraction (UTD), respectively, to calculate the electromagnetic radiation patterns for antennas on aircraft. The major difficulty in using these codes is in the creation of proper input files for particular aircraft and in verifying that these files are, in fact, what is intended. HARP creates these input files in a consistent manner and allows the user to verify them for correctness using sophisticated 2 and 3D graphics. After antenna field patterns are calculated using either MM or UTD, HARP can display the results on the user's screen or provide hardcopy output. Because the process of collecting data, building the 3D models, and obtaining the calculated field patterns was completely automated by HARP, the researcher's productivity can be many times what it could be if these operations had to be done by hand. A complete, step by step, guide is provided so that the researcher can quickly learn to make use of all the capabilities of HARP.

Braeden, E. W.↗
DOE OSTI2022

What We Learned From Analyzing 18 Million Rows of Commercial Buildings’ HVAC Fault Data

To achieve ambitious decarbonization goals it is critical that buildings operate to their full potential. Commercial HVAC systems, however, experience a wide range of operational faults, adversely affecting energy consumption, occupant comfort, and maintenance costs. Analytical tools such as fault detection & diagnostics (FDD) software identify and help diagnose these types of sensing, mechanical, or control-related faults. While significant energy savings has been documented for FDD, along with limited-scale studies on technical capabilities, there is a lack of empirical data on faults being reported by FDD tools. With FDD deployment accelerating significantly over the past decade there is an opportunity to gather and analyze data on commercial HVAC operational problems at an unprecedented scale. Such data could address many questions such as: [a] What faults are most commonly reported?; and [b] How does fault reporting vary by time of year and other possible drivers? A recent study into FDD fault reporting amassed the largest U.S. dataset of commercial HVAC air-side fault records, drawn from multi-year monitoring across over 60,000 pieces of HVAC equipment. The results of this study provide granular data on fault reporting for over 90 unique fault types. In this paper we provide an overview of the research process and highlight key findings and lessons learned. This study presents an extraordinary level of detail on FDD fault reporting characteristics across many climate zones and building types. Armed with these new insights, commercial building industry stakeholders can make better informed decisions when designing, configuring, and operating commercial HVAC systems.

Crowe, Eliot↗
NASA NTRS2013

NASA Prediction of Worldwide Energy Resource High Resolution Meteorology Data For Sustainable Building Design

A primary objective of NASA's Prediction of Worldwide Energy Resource (POWER) project is to adapt and infuse NASA's solar and meteorological data into the energy, agricultural, and architectural industries. Improvements are continuously incorporated when higher resolution and longer-term data inputs become available. Climatological data previously provided via POWER web applications were three-hourly and 1x1 degree latitude/longitude. The NASA Modern Era Retrospective-analysis for Research and Applications (MERRA) data set provides higher resolution data products (hourly and 1/2x1/2 degree) covering the entire globe. Currently POWER solar and meteorological data are available for more than 30 years on hourly (meteorological only), daily, monthly and annual time scales. These data may be useful to several renewable energy sectors: solar and wind power generation, agricultural crop modeling, and sustainable buildings. A recent focus has been working with ASHRAE to assess complementing weather station data with MERRA data. ASHRAE building design parameters being investigated include heating/cooling degree days and climate zones.

Chandler, William S.↗
DOE OSTI2020

Data-Driven Modeling and Optimization of Building Energy Consumption: a Case Study

Installing sensors and Building Automation Systems (BAS) allows controlling the facility operations while generating data that can be analyzed for model development. This work focuses on data-driven modeling of the building to optimize energy consumption. The City of Orlando aims to reduce its energy consumption so, they provided us access to their BAS for data and studying the operation of its facilities. We selected a mid-size pilot building to conduct data analysis and modeling. We develop an Application Programming Interface (API) to login to the servers and scrape data. The scraped data contains features ranging from environmental conditions to equipment activity. This dataset is a time series so, it's handled in accordance and analyzed to investigate patterns and relations between data points that help choose parameters for predictive models for building and equipment. Finally, the models are optimized to reduce the energy consumption of the facility.

Grover, Divas↗
DOE OSTI2022

Using Open Data to Characterize Building Stock Trends for Energy and Equity Evaluation

This project provides a methodology for retrieving data from both existing public data and municipal open data sets to characterize changes in the building stock, socioeconomic, demographic, and climate indicators at a neighborhood scale. This methodology forms the basis for a geospatial dashboard to analyze and share the data. The developed methodology may be used to collect data for further energy equity analyses. Additional data sets, such as from other municipalities, may be incorporated in the future to expand the extents of the possible analysis.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Utility-scale Building Type Assignment Using Smart Meter Data

United States building energy use accounted for 40% of total energy use, 74% of peak demand, and $412 billion in 2019. Building energy modeling allows researchers to simulate building physics, gain insights into possible energy/demand saving opportunities, and assess cost-effective resilience amidst climate change. Many building features needed to create building energy models are readily available such as 2D footprints and LiDAR (height). A critical feature that is not generally obtainable is the building type. In partnership with a utility, a years worth of real-world, 15-minute electrical use data has been examined. The smart meter data is compared to 97 different prototype building energy models to assign building type. Real-world considerations including data preparation, quality assurance, and handling of missing values for advanced metering infrastructure data are addressed. Euclidean distance for pattern-matching of energy use, dynamic time warping, and time-window statistics with machine learning are compared for determining building type from measured electricity use.

Bass, Brett↗
DOE OSTI2022

Automatic Segmentation of Building Envelope Point Cloud Data Using Machine Learning

About 50% of buildings in the US were constructed before energy codes were introduced. Modular overclad panel retrofits, in which a new envelope is constructed over the existing building, are a promising solution given that it minimizes occupant disruption and shortens construction time at the jobsite. Current state-of-the-art retrofit panel layout and dimensioning consists of three steps: 1) 3D point cloud data generation of the building envelope using commonly available surveying equipment, 2) manual segmentation of 3D point cloud data by a trained professional to identify and dimension window openings, door openings, and other architectural features, and 3) modular panel layout optimization and dimensioning by an architect or engineer. Among these steps, the second one remains the most difficult and costly because it is very labor-intensive. We propose a methodology to automatically label 3D point cloud data to reduce the time and expense spent in manual segmentation. Machine learning methods were employed to classify the point cloud data into distinct groups, each of which corresponds to different features of the building envelope. After classification, a segmentation algorithm was developed to perform boundary detection and separate the components of the façade. Finally, the algorithm returns the relative positions and dimensions of the features in the building envelope. The measurements obtained with the proposed automated method were compared against the actual dimensions to determine the overall algorithm accuracy. The proposed algorithm can then be used to reduce manual efforts for 3D point cloud labeling before modular panel layout optimization is performed.

Maldonado Puente, Bryan↗
NASA NTRS2012

Usage of NASA's Near Real-Time Solar and Meteorological Data for Monitoring Building Energy Systems Using RETScreen International's Performance Analysis Module

This paper describes building energy system production and usage monitoring using examples from the new RETScreen Performance Analysis Module, called RETScreen Plus. The module uses daily meteorological (i.e., temperature, humidity, wind and solar, etc.) over a period of time to derive a building system function that is used to monitor building performance. The new module can also be used to target building systems with enhanced technologies. If daily ambient meteorological and solar information are not available, these are obtained over the internet from NASA's near-term data products that provide global meteorological and solar information within 3-6 days of real-time. The accuracy of the NASA data are shown to be excellent for this purpose enabling RETScreen Plus to easily detect changes in the system function and efficiency. This is shown by several examples, one of which is a new building at the NASA Langley Research Center that uses solar panels to provide electrical energy for building energy and excess energy for other uses. The system shows steady performance within the uncertainties of the input data. The other example involves assessing the reduction in energy usage by an apartment building in Sweden before and after an energy efficiency upgrade. In this case, savings up to 16% are shown.

Paul W Stackhouse, Jr.↗
DOE OSTI2020

Chicago microclimate and building energy use data

These data comprise three elements: - High resolution, 90 m simulated weather data for 1 year at 15 min. intervals (with known gaps toward the end of each month). These files are in .csv format. - A mapping of individual buildings with individual IDs, their latitude/longitude location, and height. (Excel file) - Energy simulation output of these individual buildings, at 15 min. intervals for a whole year. (.json and other files)

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Chicago microclimate and building energy use data

These data comprise three elements: - High resolution, 90 m simulated weather data for 1 year at 15 min. intervals (with known gaps toward the end of each month). These files are in .csv format. - A mapping of individual buildings with individual IDs, their latitude/longitude location, and height. (Excel file) - Energy simulation output of these individual buildings, at 15 min. intervals for a whole year. (.json and other files)

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Building a FAIR data ecosystem for incorporating single-cell transcriptomics data into agricultural genome to phenome research

Introduction The agriculture genomics community has numerous data submission standards available, but the standards for describing and storing single-cell (SC, e.g., scRNA- seq) data are comparatively underdeveloped. Methods To bridge this gap, we leveraged recent advancements in human genomics infrastructure, such as the integration of the Human Cell Atlas Data Portal with Terra, a secure, scalable, open-source platform for biomedical researchers to access data, run analysis tools, and collaborate. In parallel, the Single Cell Expression Atlas at EMBL-EBI offers a comprehensive data ingestion portal for high-throughput sequencing datasets, including plants, protists, and animals (including humans). Developing data tools connecting these resources would offer significant advantages to the agricultural genomics community. The FAANG data portal at EMBL-EBI emphasizes delivering rich metadata and highly accurate and reliable annotation of farmed animals but is not computationally linked to either of these resources. Results Herein, we describe a pilot-scale project that determines whether the current FAANG metadata standards for livestock can be used to ingest scRNA-seq datasets into Terra in a manner consistent with HCA Data Portal standards. Importantly, rich scRNA-seq metadata can now be brokered through the FAANG data portal using a semi-automated process, thereby avoiding the need for substantial expert curation. We have further extended the functionality of this tool so that validated and ingested SC files within the HCA Data Portal are transferred to Terra for further analysis. In addition, we verified data ingestion into Terra, hosted on Azure, and demonstrated the use of a workflow to analyze the first ingested porcine scRNA-seq dataset. Additionally, we have also developed prototype tools to visualize the output of scRNA-seq analyses on genome browsers to compare gene expression patterns across tissues and cell populations. This JBrowse tool now features distinct tracks, showcasing PBMC scRNA-seq alongside two bulk RNA-seq experiments. Discussion We intend to further build upon these existing tools to construct a scientist-friendly data resource and analytical ecosystem based on Findable, Accessible, Interoperable, and Reusable (FAIR) SC principles to facilitate SC-level genomic analysis through data ingestion, storage, retrieval, re-use, visualization, and comparative annotation across agricultural species.

Genetics & Heredity↗
DOE OSTI2020

Processed data from the Building Management System for the System Engineering Building.

The dataset spans November 2018 to May 2020 and includes time-series measurements corresponding to supply and return temperatures of air and water, air, hot water and cold water flow rates, energy and power consumption, set-points etc. as a single CSV file. In addition to the measurements, a metadata .json file, and a .ttl file to visualize the data as per BRICK schema are also included.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1994

Global- to Micro-Scale Evolution of the Pinatubo Aerosol: Using Composite Data Sets to Build the Picture and Assess Consistency of Different Measurements

This paper brings together experimental. evidence required to build realistic models of the global evolution of physical, chemical, and optical properties of the aerosol resulting from the 1991 Pinatubo volcanic eruption. Such models are needed to compute the effects of the aerosol on atmospheric chemistry, dynamics, radiation, and temperature. Whereas there is now a large and growing body of post-Pinatubo measurements by a variety of techniques, some results are in conflict, and a self-consistent, unified picture is needed, along with an assessment of remaining uncertainties. This paper examines data from photometers, radiometers, impactors, optical counters/sizers, and lidars operated on the ground, aircraft, balloons, and spacecraft.

Russell, P. B.↗
NASA NTRS1994

Pinatubo Aerosol Evolution: Using Composite Data Sets to Build the Global- To Micro-Scale Picture and Assess Consistency of Different Measurements

This paper brings together experimental evidence required to build realistic models of the global evolution of physical, chemical, and optical properties of the aerosol resulting from the 1991 Pinatubo volcanic eruption. Such models are needed to compute the effects of the aerosol on atmospheric chemistry, dynamics, radiation, and temperature. Whereas there is now a large and crowing body of post-Pinatubo measurements by a variety of techniques, some results are in conflict, and a self-consistent, unified picture is needed, along with an assessment of remaining uncertainties. This paper examines, data from photometers, radiometers, impactors, optical counter/sizers, and lidars operated on the ground, aircraft, balloons, and spacecraft. Example data sources include: (1) Tracking sunphotometers and lidars at Mauna Loa Observatory (MLO) and on the DC-8. (2) Particle spectrometers and wire impactors on the ER-2 and DC-8. (3) Dustsondes (particle counter/sizers on balloons). and (3) SAGE II, SAM II, AVHRR, CLAES, and ISAMS sensors on a variety of satellites. We assess the mutual consistency of these disparate data sets and recommend 'consensus' properties and uncertainties in the process of developing a composite data set. Recommended properties include the spatial and temporal evolution of particle chemical composition, shape, wavelength-and temperature-dependent refractive index, size distribution, and optical depth spectra. Supporting references are cited and representative data shown.

Russell, Philip B.↗
NASA NTRS1994

Pinatubo Aerosol Evolution: Using Composite Data Sets to Build the Global- to Micro-Scale Picture and Assess Consistency of Different Measurements

This paper brings together experimental evidence required to build realistic models of the global evolution of physical, chemical, and optical properties of the aerosol resulting from the 1991 Pinatubo volcanic eruption. Such models are needed to compute the effects of the aerosol on atmospheric chemistry, dynamics, radiation, and temperature. Whereas there is now a large and growing body of post-Pinatubo measurements by a variety of techniques, some results are in conflict, and a self-consistent, unified picture is needed, along with an assessment of remaining uncertainties. This paper examines data from photometers, radiometers, impactors, optical counters/sizers, and lidars operated on the ground, aircraft, balloons, and spacecraft. Example data sources include: - Tracking sunphotometers and lidars at Mauna Loa Observatory (MLO) and on the DC-8 - Particle spectrometers and wire impactors on the ER-2 and DC-8 - Dustsondes (particle counters/sizers on balloons) - SAGE II, SAM II, AVHRR, CLAES, and ISAMS sensors on a variety of satellites. We assess the mutual consistency of these disparate data sets and recommend 'consensus" properties and uncertainties in the process of developing a composite data set. Recommended properties include the spatial and temporal evolution of particle chemical composition, shape, wavelength and temperature-dependent refractive index, size distribution, and optical depth spectra. Supporting references are cited and representative data shown.

Russell, P. B.↗