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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 631 records · Page 35

All sources NASA NTRS DOE OSTI

NASA NTRS1994

Spacecraft command and control using expert systems

This paper describes a product called the Intelligent Mission Toolkit (IMT), which was created to meet the changing demands of the spacecraft command and control market. IMT is a command and control system built upon an expert system. Its primary functions are to send commands to the spacecraft and process telemetry data received from the spacecraft. It also controls the ground equipment used to support the system, such as encryption gear, and telemetry front-end equipment. Add-on modules allow IMT to control antennas and antenna interface equipment. The design philosophy for IMT is to utilize available commercial products wherever possible. IMT utilizes Gensym's G2 Real-time Expert System as the core of the system. G2 is responsible for overall system control, spacecraft commanding control, and spacecraft telemetry analysis and display. Other commercial products incorporated into IMT include the SYBASE relational database management system and Loral Test and Integration Systems' System 500 for telemetry front-end processing.

Norcross, Scott↗

NASA NTRS1996

High Spatial Resolution Investigations of Microchannel Plate Imaging Properties for UV Detectors

Microchannel plate (MCP) photon counting detectors are currently being used with great success on many of the recent NASA/ESA ultraviolet (UV) astrophysics missions that make observations in the 1OO A - 1600 A range. These include HUT, the Wide Field Camera on ROSAT, EUVE, ALEXIS, ORFEUS, and SOHO. These devices have also been chosen to fly on future UV astrophysics missions such as FUSE, FUVITA, IMAGE, and both the HST STIS and Advanced Camera instruments. During the period of this award we have fabricated a dual-chamber vacuum test facility to carry out laboratory testing of detector resolution, image stability and linearity, and flat field performance to enable us to characterize the performance of MCPs and their associated read-out architectures. We have also fabricated and tested a laboratory 'test-bed' delay line detector, which can accommodate MCP's with a wide range of formats and run at high data rates, to continue our studies of MCP image fixed pattern noise, and particularly for new small pore MCP's which have recently come onto the market. These tests were mainly focussed on the assessment of cross delay-line (XDL) and double delay line (DDL) anode read-out schemes, with particular attention being focussed on flat-field and spatial resolution performance.

Siegmund, Oswald↗

NASA NTRS2000

The Eclipse Project

The Eclipse Project by Tom Tucker provides a readable narrative and a number of documents that record an important flight research effort at NASA's Dryden Flight Research Center. Carried out by Kelly Space and Technology, Inc., in partnership with the Air Force and Dryden at Edwards Air Force Base in the Mojave Desert of California, this project tested and gathered data about a potential newer and less expensive way to launch satellites into space. Whether the new technology comes into actual use will depend on funding, market forces, and other factors at least partly beyond the control of the participants in the project. This is a familiar situation in the history of flight research.

Tucker, Tom↗

NASA NTRS2019

Reliability Requirements and Research Strategies for Urban Air Mobility Propulsion

An emerging new mission for aeronautics is Urban Air Mobility (UAM), a concept for air transportation around metropolitan areas with passenger-carrying operations. UAM vehicles must be capable of vertical take-off and landing, and this requirement presents unique technical challenges for electric and hybrid-based vertical take-off and landing (eVTOL). A critical challenge for UAM market growth is to gain public acceptance for being as safe as - or safer than - commercial air travel and automotive transportation. There is a lack of data for propulsion systems, components, and the associated thermal management systems for UAM eVTOL propulsion systems. The new mission, new propulsion system concepts, safety criticality of propulsion component performance during vertical take-off and lift operations, and lack of data presents many research challenges and opportunities. NASA has developed and published UAM vehicle concept studies. For a subset of the said concept vehicles, NASA has contracted for a study to identify failure modes and hazards associated with the propulsion systems of the concept vehicles and to perform functional hazard analyses (FHA) and failure modes and effects criticality analyses (FMECA) for each. From the completed study results, it was recommended for NASA to support research toward developing electric/hybrid-electric propulsion components with improved reliability and to explore powertrain architectures that can take advantage of higher reliability components to achieve inherent air-vehicle safety. NASA has started a research effort for UAM propulsion with a focus toward improving safety and reliability. Recent results and research strategy will be discussed toward the goals by means of: 1) improving individual component reliability through advanced materials and design methods, 2) improving the thermal management system, and 3) designing propulsion system architectures to provide inherent UAM vehicle safety.

Krantz, Timothy↗

DOE OSTI2022

Best Practices for Energy Management Information Systems Metadata Schemas

The Federal Energy Management Program (FEMP) promotes best practices for impactful utilization of Energy Management Information Systems (EMIS) at federal facilities. This best practice document is part of a series of fact sheets created to help accelerate the market adoption and use of EMIS in the federal sector. The use of standard naming conventions and a metadata schema, which may be referred to as 'data tags,' improves the ability of the EMIS to consistently analyze, visualize, and derive value from operational data. To help address these issues, this fact sheet highlights best practices for use of metadata in an EMIS stack, which can significantly reduce the initial time required to deploy an EMIS.

EMIS↗

DOE OSTI2024

Shallow Geothermal Resources for Cooling Applications at the University of Hawai‘i

Scientists at Berkeley Lab have teamed up with The University of Hawai‘i at Manoa (UH Manoa) through the U.S. Department of Energy’s (DOE’s) Energy Transitions Initiative Partnership Project (ETIPP) to evaluate the technological and market feasibility of shallow geothermal heat exchanger (GHE) technology for building cooling, energy efficiency, and emissions reduction applications in Hawai’i. The team is assessing the data necessary to model the feasibility of deploying this technology, the actual models that will be used, and what hurdles need to be overcome to install a demonstration case. UH has an abundance of geologic and geothermal data and is looking to the national labs’ expertise to execute this analysis. UH is also interested in investigating policy, regulatory, and business conditions advantageous for implementation of a pilot project, and more broad deployment of this technology in Hawai‘i. In many locations around the world, the demands for heating and cooling are roughly balanced over the course of the year, so GHEs do not cause significant long-term changes in subsurface temperature. This is not the case in Hawai’i, where the demand for heating is very small, meaning that over time, GHEs will add heat to the subsurface. If temperatures increase significantly, GHE systems will not work as designed. Regional groundwater flow has the potential to sweep heated water away from boreholes, thereby maintaining the functionality of the GHE system. Significant regional groundwater flow requires two things: a sufficiently large driving hydraulic head gradient (usually closely related to surface topography), and sufficient porosity and permeability to enable groundwater to flow in large enough quantities to enable near-borehole temperatures to be maintained at ambient values. Hawai‘i’s volcanic terrain offers ample surface topographic variation. The lava itself shows an extremely large range of porosity and permeability, making it crucial to select sites with large enough values of these properties. Numerical modeling of coupled groundwater and heat flow can be used to determine how large is large enough. Both closed-loop and open-loop systems are being investigated. Another option being considered is using cool seawater as the source of chill. Currently work is progressing on two fronts. A hydrogeologic model for a closed-loop system is being developed for the Stan Sheriff Center at the UH Manoa campus, where a subsurface karst system immediately downgradient of the borefield may provide efficient removal of heated groundwater. The team will also develop a technoeconomic model for this site to compare the cost of cooling using a GHE system with the costs of operating the current air conditioning system. At the state scale, geographic information system (GIS) layers of various attributes relevant for GHE are being combined to develop an overall favorability map for employing GHE in Hawai‘i.

Doughty, C↗

DOE OSTI2026

ComStock Measure Documentation: High-Efficiency Rooftop Unit

Building on the 3-year End-Use Load Profiles project to calibrate and validate the U.S. Department of Energy's ResStock and ComStock models, this work produces national data sets that enable cities, states, utilities, and other stakeholders to answer a broad range of questions regarding their commercial building stock. ComStock is a highly granular, bottom-up model that uses various data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual subhourly energy consumption of the commercial building stock across the United States. The "baseline" model intends to represent the U.S. commercial building stock as it existed in 2018. The methodology of the baseline model is discussed in the ComStock Reference Documentation. The goal of this work is to develop energy efficiency and demand flexibility measures that cover market-ready technologies and study their mass adoption impact on the baseline building stock. "Measures" refers to various "what-if" scenarios that can be applied to buildings. The results for the baseline and measure scenario simulations are published in public data sets that provide insights into building stock characteristics, operational behaviors, utility bill impacts, and annual and sub-hourly energy usage by fuel type and end use. This report describes the modeling methodology for a single ComStock measure scenario - high-efficiency rooftop unit (RTU) - and briefly introduces key results. The full public data set can be accessed on the Comstock data lake or via the Data Viewer at comstock.nlr.gov. The public data set enables users to create custom aggregations of results for their use case (e.g., filter to a specific county or building type).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

ComStock Measure Documentation: Variable-Speed Pumps

Building on the 3-year End-Use Load Profiles project to calibrate and validate the U.S. Department of Energy's ResStock and ComStock models, this work produces national data sets that enable cities, states, utilities, and other stakeholders to answer a broad range of questions regarding their commercial building stock. ComStock is a highly granular, bottom-up model that uses various data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual subhourly energy consumption of the commercial building stock across the United States. The "baseline" model intends to represent the U.S. commercial building stock as it existed in 2018. The methodology of the baseline model is discussed in the ComStock Reference Documentation. The goal of this work is to develop energy efficiency and demand flexibility measures that cover market-ready technologies and study their mass adoption impact on the baseline building stock. "Measures" refers to various "what-if" scenarios that can be applied to buildings. The results for the baseline and measure scenario simulations are published in public data sets that provide insights into building stock characteristics, operational behaviors, utility bill impacts, and annual and sub-hourly energy usage by fuel type and end use. This report describes the modeling methodology for a single ComStock measure scenario - variable speed pumps - and briefly introduces key results. The full public data set can be accessed on the ComStock data lake or via the Data Viewer at comstock.nlr.gov. The public data set enables users to create custom aggregations of results for their use case (e.g., filter to a specific county or building type).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Revenue prediction for integrated renewable energy and energy storage system using machine learning techniques

Revenue estimation for integrated renewable energy and energy storage systems is important to support plant owners or operators’ decisions in battery sizing selection that leads to maximized financial performances. A common approach to optimizing revenues of a hybrid hydro and energy storage system is using mixed-integer linear programming (MILP). Although MILP models can provide accurate production cost estimations, they are typically very computationally expensive. To provide a fast yet accurate first-step information to hydropower plant owners or operators who consider integrating energy storage systems, we propose an innovative approach to predicting optimal revenues of an integrated energy generation and storage system. In this study, we examined the performance of two prediction techniques: Generalized Additive Models (GAMs) and machine learning (ML) models developed based on artificial neural networks (ANN). Predictive equations and models are generated based on optimized solutions from a market participation optimization model, the Conventional Hydropower Energy and Environmental Resource System (CHEERS) model. The two predicting techniques reduce the computational time to evaluate annual revenue for one set of battery configurations from 3 h to 1 to 4 min per run while also being implementable with significantly less data. The model validation prediction errors of developed GAMs and ML models are generally below 5%; for model testing predictions, the ML models consistently outperform the regression equations in terms of root mean square errors. This new approach allows plant owners, operators, or potential investors to quickly access multiple battery configurations under different energy generation and market scenarios. This new revenue prediction method will therefore help reduce the barriers, and thereby promoting the deployment of battery hybridization with existing renewable energy sources.

13 HYDRO ENERGY↗

DOE OSTI2020

Analysis of Fault Data Collected from Automated Fault Detection and Diagnostic Products for Packaged Rooftop Units

Rooftop units (RTUs) and other packaged systems are very common in commercial buildings in the U.S., and they often have minimal controls and poor performance. Automated fault detection and diagnostics (AFDD) is a powerful tool that can continuously monitor operating equipment, detect abnormal performance, diagnose problems, and report findings to building operators. AFDD technologies for RTUs have been under development for many years and have recently begun to enter the market in a significant way. There are several AFDD systems available for RTUs that feature a wide range of designs, capabilities, and reporting. Unfortunately, there is little consistency among the AFDD applications and little understanding of the performance and value of these systems. This study presents analysis of AFDD data provided by four companies from over 28,000 RTUs, five building types, and multiple climate zones. The objectives of this investigation were to gain a better understanding of how RTU AFDD systems operate, the types and frequencies of faults identified, and how building operators interact with these systems. The monitoring of a variety of RTUs provides insights into the AFDD monitoring inputs, faults, and diagnostics from which these tools are capable of informing building owners about the status of their HVAC systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Analysis of Fault Data Collected from Automated Fault Detection and Diagnostic Products for Packaged Rooftop Units

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2007

Using Satellite Remote Sensing Data in a Spatially Explicit Price Model

Famine early warning organizations use data from multiple disciplines to assess food insecurity of communities and regions in less-developed parts of the World. In this paper we integrate several indicators that are available to enhance the information for preparation for and responses to food security emergencies. The assessment uses a price model based on the relationship between the suitability of the growing season and market prices for coarse grain. The model is then used to create spatially continuous maps of millet prices. The model is applied to the dry central and northern areas of West Africa, using satellite-derived vegetation indices for the entire region. By coupling the model with vegetation data estimated for one to four months into the future, maps are created of a leading indicator of potential price movements. It is anticipated that these maps can be used to enable early warning of famine and for planning appropriate responses.

Brown, Molly E.↗

DOE OSTI2022

Charging needs for electric semi-trailer trucks

Battery-electric vehicles provide a pathway to decarbonize heavy-duty trucking, but the market for heavy-duty battery-electric semi-trailer trucks is nascent, and specific charging requirements remain uncertain. We leverage large-scale vehicle telematics data (>205 million miles of driving) to estimate the charging behaviors and infrastructure requirements for U.S. battery-electric semi-trailer trucks within three operating segments: local, regional, and long-haul. We model two types of charging - mid-shift (fast) and off-shift (slow) - and show that off-shift charging at speeds compatible with current light-duty charging infrastructure (i.e., =350 kW) can supply 35% to 77% of total energy demand for local and regional trucks with =300-mile range. Megawatt-level speeds are required for mid-shift charging, which make up 44% to 57% of energy demand for long-haul trucks with =500-mile range. However, demand shifts from mid-shift to off-shift charging as the range for battery-electric trucks increases and when off-shift charging is widely available. Finally, we observe geographic trends in charging demand, finding that local trucks have greater demand within urban areas, whereas long-haul trucks have more demand along rural interstate corridors. As the range for battery-electric trucks increases, we show that charging demand shifts from rural to urban locations due to observed vehicle dwell tendencies.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

A deep generative model enables automated structure elucidation of novel psychoactive substances

Over the past decade, the illicit drug market has been reshaped by the proliferation of clandestinely produced designer drugs. These agents, referred to as new psychoactive substances (NPSs), are designed to mimic the physiological actions of better-known drugs of abuse while skirting drug control laws. The public health burden of NPS abuse obliges toxicological, police and customs laboratories to screen for them in law enforcement seizures and biological samples. However, the identification of emerging NPSs is challenging due to the chemical diversity of these substances and the fleeting nature of their appearance on the illicit market. Here, in this study, we present DarkNPS, a deep learning-enabled approach to automatically elucidate the structures of unidentified designer drugs using only mass spectrometric data. Our method employs a deep generative model to learn a statistical probability distribution over unobserved structures, which we term the structural prior. We show that the structural prior allows DarkNPS to elucidate the exact chemical structure of an unidentified NPS with an accuracy of 51% and a top-10 accuracy of 86%. Our generative approach has the potential to enable de novo structure elucidation for other types of small molecules that are routinely analysed by mass spectrometry.

Cheminformatics↗

DOE OSTI2025

Overview of leakage scenarios in supervised machine learning

Machine learning (ML) provides powerful tools for predictive modeling. ML’s popularity stems from the promise of sample-level prediction with applications across a variety of fields from physics and marketing to healthcare. However, if not properly implemented and evaluated, ML pipelines may contain leakage typically resulting in overoptimistic performance estimates and failure to generalize to new data. This can have severe negative financial and societal implications. Our aim is to expand understanding associated with causes leading to leakage when designing, implementing, and evaluating ML pipelines. Illustrated by concrete examples, we provide a comprehensive overview and discussion of various types of leakage that may arise in ML pipelines.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1965

Dry film lubricants

The Space Age has necessitated accelerated development of many technologies which have direct application to commercial, earthbound hardware. One striking example is dry film lubrication. The stimulus for the development of dry film lubricants was provided by the unsatisfactory condition created when commercial liquid lubricants were exposed to the multiple environs of space. In the search for a satisfactory solution to lubrication in space, dry films were investigated. The dry film lubrication concept has proven most desirable for space, and a natural fallout is the potential shown by such films for consumer item application. On the acceptance that the coefficient of friction of dry films is not equivalent to that of a liquid lubricant under ideal conditions, this paper discusses how the ideal condition for liquid lubrication is rarely achieved in practical applications. Comparisons are made between the performance of dry film and liquid lubricants as a function of temperature, environmental pressure, and life. Furthermore, consideration is given to the comparative costs of liquid versus dry film lubricants to show the practicality and desirability of dry film lubrication to consumer items. Although no data on the performance of consumer items lubricated with dry films are presented, the comparisons clearly establish the potential of dry film lubricants in a competitive consumer market.

SOLID LUBRICANT↗

NASA NTRS1993

Small Business Innovations

Under an Army Small Business Innovation Research (SBIR) grant, Symbiotics, Inc. developed a software system that permits users to upgrade products from standalone applications so they can communicate in a distributed computing environment. Under a subsequent NASA SBIR grant, Symbiotics added additional tools to the SOCIAL product to enable NASA to coordinate conventional systems for planning Shuttle launch support operations. Using SOCIAL, data may be shared among applications in a computer network even when the applications are written in different programming languages. The product was introduced to the commercial market in 1993 and is used to monitor and control equipment for operation support and to integrate financial networks. The SBIR program was established to increase small business participation in federal R&D activities and to transfer government research to industry. InQuisiX is a reuse library providing high performance classification, cataloging, searching, browsing, retrieval and synthesis capabilities. These form the foundation for software reuse, producing higher quality software at lower cost and in less time. Software Productivity Solutions, Inc. developed the technology under Small Business Innovation Research (SBIR) projects funded by NASA and the Army and is marketing InQuisiX in conjunction with Science Applications International Corporation (SAIC). The SBIR program was established to increase small business participation in federal R&D activities and to transfer government research to industry.

Source record↗

NASA NTRS2012

Low-Cost Telemetry System for Small/Micro Satellites

A Software Defined Radio (SDR) concept uses a minimum amount of analog/radio frequency components to up/downconvert the RF signal to/from a digital format. Once in the digital domain, all other processing (filtering, modulation, demodulation, etc.) is done in software. The project will leverage existing designs and enhance capabilities in the commercial sector to provide a path to a radiation-hardened SDR transponder. The SDR transponder would incorporate baseline technologies dealing with improved Forward Error Correcting (FEC) codes to be deployed to all Near Earth Network (NEN) ground stations. By incorporating this FEC, at least a tenfold increase in data throughput can be achieved. A family of transponder products can be implemented using common platform architecture, allowing new products to be more quickly introduced into the market. Software can be reused across products, reducing software/hardware costs dramatically. New features and capabilities, such as encoding and decoding algorithms, filters, and bit synchronizers, can be added to the existing infrastructure without requiring major new capital expenditures, allowing implementation of advanced features in the communication systems. As new telecommunication technologies emerge, incorporating them into the SDR fabric will be easily accomplished with little or no requirements for new hardware. There are no preferred flight platforms for the SDR technology, so it can be used on any type of orbital or sub-orbital platform, all within a fully radiation hardened design.

Sims, William↗