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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Hourly Electricity Demand Projections for Eight Combined Climate and Socioeconomic Scenarios

This dataset contains 40 years (1980-2019) of simulated historical hourly electricity demand (i.e., loads) and 80 years (2020-2099) of projected hourly loads for 54 Balancing Authorities (BAs) and 48 states plus the District of Columbia. Details about the scenarios and variables included in this dataset are in the readme.pdf file. The two primary models that created the dataset are a version of the Global Change Analysis Model with detailed sectoral resolution over the United States (GCAM-USA) and the Total ELectricity Loads (TELL) model. Links to the model source code and workflow for deriving the dataset are provided in an accompanying meta-repository: https://github.com/IMMM-SFA/burleyson-etal_2024_applied_energy. Projections are for four future climate scenarios that represent combinations of Representative Concentration Pathways (RCPs) 4.5 and 8.5 combined with two levels of climate model sensitivities: rcp45cooler, rcp45hotter, rcp85cooler, and rcp85hotter. The four climate scenarios are crossed with Shared Socioeconomic Pathways (SSPs) 3 and 5 to yield eight different future load projections: rcp45cooler_ssp3, rcp45cooler_ssp5, rcp45hotter_ssp3, rcp45hotter_ssp5, rcp85cooler_ssp3, rcp85cooler_ssp5, rcp85hotter_ssp3, and rcp85hotter_ssp5. The climate scenarios are from the IM3 Thermodynamic Global Warming (TGW) dataset which is linked below in the related metadata. The related metadata also contains links to a repository containing the raw GCAM-USA output files.

Climate Change↗
NASA NTRS1997

Spacecraft Demand Access: Autonomy for Low-Cost Planetary Operations

In this paper we describe a new concept and prototype for dramtically reducing the cost of contact with planetary spacecraft. Known as spacecraft Demand Access, a suite of spacecraft and ground automation technologies, it enables future intelligent spacecraft to act as initiators of cost effective contact with the ground - doing it only when necessary.

Low cost planetary operations Spacecraft Demand Ac↗
NASA NTRS2018

Required Time of Arrival as a Control Mechanism to Mitigate Uncertainty in Arrival Traffic Demand Management

The objective of this study is to explore the use of Required Time of Arrival (RTA) capability on the flight deck as a control mechanism on arrival traffic management to improve traffic delivery accuracy by mitigating the effect of traffic demand uncertainty. The uncertainties are caused by various factors, such as departure error due to the difference between scheduled departure and the actual take-off time. A simulation study was conducted using the Multi Aircraft Control System (MACS) software, a comprehensive research platform developed in the Airspace Operations Laboratory (AOL) at NASA Ames Research Center. The Crossing Time (CT) performance (i.e. the difference between target crossing time and actual crossing time) of the RTA for uncertainty mitigation during cruise phase was evaluated under the influence of varying two main factors: wind severity (heavy wind vs. mild wind), and wind error (1 hour, 2 hours, and 5 hours wind forecast errors). To examine the CT performance improvement made by the RTA, the comparison to the CT of the aircraft that were not assigned with RTA (Non-RTA) under the influence of the selected factors was also made. The Newark Liberty International Airport (EWR) was chosen for this study. A total 66 inbound traffic to the EWR (34 of them were airborne when the simulation was initiated, 32 were pre-departures at that time) was simulated, where the pre-scripted departure error was assigned to each pre-departure (61 conform to their Expected Departure Clearance Time, which is +-300 seconds of their scheduled departure time). The results of the study show that the delivery accuracy improvement can be achieved by assigning RTA, regardless of the influence of the selected two factors (the wind severity and the wind information inaccuracy). Across all wind variances, 66.9 (265 out of 396) of the CT performance of the RTA assigned aircraft was within +- 60 seconds (i.e. target tolerance range) and 88.9 (352 out of 396) aircraft met +-300 seconds marginal tolerance range, while only 33.6 (133 out of 396) of the Non-RTA assigned aircrafts CT performance achieved the target tolerance range and 75.5 (299 out of 396) stayed within the marginal. Examination of the impact of different error sources i.e. departure error, wind severity, and wind error suggest that although large departure errors can significantly impact the CT performance, the impacts of wind severity and errors were modest relative the targeted +- 60 second conformance range.

required time of arrival (RTA)↗
NASA NTRS2019

Integrated Demand Management (IDM) Project Overview

Overview of NASA Integrated Demand Management (IDM) research into synchronized use of strategic and tactical air traffic management systems describes the initial motivation for the research, summary description of key experiments conducted between 2016 and the present, collaboration with outside partners and stakeholders, and the current status of the research.

Integrated Demand Management↗
NASA NTRSDate not supplied

Bionutrients: Microbial Production of on-Demand Nutrients on the International Space Station

Providing adequate nutrition to crew members is essential as deep-space missions cannot rely on consistent Earth-based resupply. The current NASA pre-packaged food system is designed for low-earth-orbit missions with a stated shelf-life of two years and notable vitamin degradation over time. One strategy to mitigate nutrient loss is to implement bioregenerative food sources to supplement the pre-packaged food system. The BioNutrients project is designed to provide targeted production of short shelf-life nutrients in a single-use production pack. BioNutrients-1 includes two strains of edible yeast that have been genetically engineered to produce carotenoids, β-carotene, and zeaxanthin. This five-year mission on the International Space Station (ISS), launched in 2019, tests the long-term storage and nutrient production of the microorganisms of interest. Additional microorganisms are also stored in stasis packs to determine the effects of long-duration storage on the ISS. These organisms may be useful for production of fermented foods, pharmaceuticals, or biomanufacturing processes. Improving on the BioNutrients-1 project, BioNutrients-2 has optimized the production pack hardware by reducing the overall mass and volume of the system. Furthermore, BioNutrients-2 has expanded the projects scope by investigating novel products and microbial food sources. BioNutrients-2 is a six-month mission, launched in 2022, which tests production of fresh foods such as yogurt and kefir. The BioNutrients missions seek to provide advances for in-space biomanufacturing by addressing safe and reliable production of high-value nutrients and on-demand foods for future exploration efforts.

BioNutrients↗
NASA NTRS2023

Aconcagua Basin Agriculture: Analyzing Hydrological Norms, Evapotranspiration, and Soil Moisture to Assess Crop Water Demand and Water Usage in Chile’s Aconcagua River Basin

The Aconcagua basin has experienced a prolonged drought since 2010, posing a significant concern to the agricultural sector, which contributes to 12% of the national agriculture output. Reduced precipitation and warmer conditions have led to water constraints for agricultural activities. As the agriculture sector relies more on irrigation, there has been a decline in surface water availability and a shrinking groundwater supply, both primarily sourced from snow and glacial melt. This study focuses on evaluating crop water demand and water usage in the Aconcagua Basin, leveraging in-situ and available satellite data from Aqua and Terra Moderate Resolution Imaging Spectroradiometer (MODIS), 1-km downscaled Soil Moisture Active Passive (SMAP), Global Precipitation Measurement Mission IMERG (GPM), and Landsat 8 Operational Land Imager (OLI). Remote sensing hydrologic norms from pre- and intra-drought conditions provided a baseline for our water use analysis. We have identified areas of the basin where water usage is exaggerated compared to other regions by analyzing soil moisture, evapotranspiration, and vegetation index trends across agricultural lands. The study highlights the presence of irrigation and exaggerated water usage categorized by crop type while normalizing the data by the quantity of water allocation (m3/s) to each subregion. The findings have the potential to assist our partners, the Centro de Información de Recursos Naturales (CIREN) and the Ministry of Agriculture, in refining water allocation approaches; showcasing the feasibility of leveraging remote sensing and earth observation datasets to monitor agricultural practices within the context of water scarcity.

Remote sensing↗
NASA NTRSDate not supplied

Bionutrients: Microbial Production of on-Demand Nutrients on the International Space Station

Providing adequate nutrition to crew members is essential as deep-space missions cannot rely on consistent Earth-based resupply. The current NASA pre-packaged food system is designed for low-earth-orbit missions with a stated shelf-life of two years and notable vitamin degradation over time. One strategy to mitigate nutrient loss is to implement bioregenerative food sources to supplement the pre-packaged food system. The BioNutrients project is designed to provide targeted production of short shelf-life nutrients in a single-use production pack. BioNutrients-1 includes two strains of edible yeast that have been genetically engineered to produce carotenoids, β-carotene, and zeaxanthin. This five-year mission on the International Space Station (ISS), launched in 2019, tests the long-term storage and nutrient production of the microorganisms of interest. Additional microorganisms are also stored in stasis packs to determine the effects of long-duration storage on the ISS. These organisms may be useful for production of fermented foods, pharmaceuticals, or biomanufacturing processes. Improving on the BioNutrients-1 project, BioNutrients-2 has optimized the production pack hardware by reducing the overall mass and volume of the system. Furthermore, BioNutrients-2 has expanded the projects scope by investigating novel products and microbial food sources. BioNutrients-2 is a six-month mission, launched in 2022, which tests production of fresh foods such as yogurt and kefir. The BioNutrients missions seek to provide advances for in-space biomanufacturing by addressing safe and reliable production of high-value nutrients and on-demand foods for future exploration efforts.

BioNutrients↗
DOE OSTI2015

Heat Pump Water Heaters: Controlled Field Research of Impact on Space Conditioning and Demand Response Characteristics

A new generation of heat pump water heaters (HPWH) has been introduced into the U.S. market that promises to provide significant energy savings for water heating. Many electric utilities are promoting their widespread adoption as a key technology for meeting energy conservation goals and reducing greenhouse gas emissions. There is, however, considerable uncertainty regarding the space conditioning impact of an HPWH installed in a conditioned space. There is also uncertainty regarding the potential for deployment of HPWHs in demand response (DR) programs to help manage and balance peak utility loads in a similar manner as conventional electric resistance water heaters (ERWH). To help answer these uncertainties, controlled experiments have been undertaken over 30 months in a matched pair of unoccupied Lab Homes located on the campus of the Pacific Northwest National Laboratory (PNNL) in Richland, Washington.

demand response↗
DOE OSTI2017

Asheville, North Carolina: Reducing Electricity Demand through Building Programs & Policies (City Energy: From Data to Decisions)

This fact sheet "Asheville, North Carolina: Reducing Electricity Demand through Building Programs & Policies" explains how the City of Asheville used data from the U.S. Department of Energy's Cities Leading through Energy Analysis and Planning (Cities-LEAP) and the State and Local Energy Data (SLED) programs to inform its city energy planning. It is one of ten fact sheets in the "City Energy: From Data to Decisions" series.

buildings↗
DOE OSTI2018

Stochastic Model Predictive Control for Demand Response in a Home Energy Management System: Preprint

This paper presents a chance constrained, model predictive control (MPC) algorithm for demand response (DR) in a home energy management system (HEMS). The HEMS optimally schedules controllable appliances given user preferences such as thermal comfort and energy cost sensitivity, and available residentially-owned power sources such as photovoltaic (PV) generation and home battery systems. The proposed control architecture ensures both the DR event and indoor thermal comfort are satisfied with a high probability given the uncertainty in available PV generation and the outdoor temperature forecast. The uncertainties are incorporated into the MPC formulation using probabilistic constraints instead of computationally limiting sampling-based approaches. Simulation results for various user preferences and probabilistic model parameters show the effectiveness of the HEMS algorithm response to DR requests.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Custom Controls for Improved Demand Response from Heat Pump Water Heaters

As part of a Grid Modernization Laboratory Consortium (GMLC) project looking at defining grid services for a range of devices, NREL used a custom controller to investigate the ability of a HPWH to provide load add and load shed in hybrid and electric resistance mode using standard set point control. Based on those results, changes were made to the controls to increase the amount of grid services delivered, especially in the load-add case, and speed up the recovery from those events. The custom controls also include less common methods, such as duty cycling of the heat pump or elements. The improved controls led to an increase the amount of demand response that could be provided and enabled faster recovery. Results from the laboratory experiments will be presented, along with details about the custom controls that were implemented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Carl's Jr. Installs Demand-Based Defrost Controller

This case study describes CKE Restaurants, Inc’s efforts to cut energy waste by field testing an advanced demand defrost control system for walk-in coolers and freezers at Carl’s Jr. restaurants.

advanced demand defrost control system, walk-in co↗
DOE OSTI2022

Physically Realistic Estimates of Electric Water Heater Demand Response Resource

Multiple grid integration studies have examined the value of demand response, including from water heaters, to bulk power systems. Common shortcomings of these studies include physically unrealistic assumptions. For example, studies often assume that all electric water heater load can be shed for up to an hour to provide capacity or contingency service, that all electric water heater load is shiftable, and that round-trip efficiencies for shifting service are 100%. Another issue is that simply summing up estimates of individual water heaters' flexibility bounds, an attractive idea for constructing the MW-scale resources necessary for direct inclusion in grid investment and operational models, can result in significant overestimates of actual resource, because, e.g., a water heater with the ability to reduce load may not be able sustain the reduction for as long as the aggregate model suggests is possible. This presentation demonstrates the impact of estimating the flexibility of electric water heaters with physically realistic models suitable for grid service analysis. Electric water heater flexibility representations are constructed based on ResStock simulations of New England. Specifically, we examine contingency resource (related to capacity, shed, and contingency reserve services) and energy shifting resource from electric resistance and heat pump water heaters. Different estimation methods are compared; and the surrogate models' event responses are validated against events directly simulated in EnergyPlus. We also demonstrate the impact of using electric water heaters for contingency reserves and energy shifting in detailed models of possible future ISO New England power systems.

building energy modeling↗
DOE OSTI2024

A Mobility Energy Productivity Evaluation of On-Demand Transit: A Case Study in Arlington, Texas

On-demand transit (ODT) systems are increasing in number and size. In order to evaluate and quantify outcomes, we use the Mobility Energy Productivity (MEP) metric, a holistic tool to analyze, quantify, and compare the mobility and accessibility of various transportation modes in a specific area. In this paper, we apply the MEP tool to the ODT system in Arlington, Texas, and compare the results among four existing transportation modes (drive, transportation network company, transit, and bike) and five additional ODT scenarios. We focus our analysis on the opportunities that an ODT system presents such as serving disadvantages communities. While the results in Arlington show the typical U.S. pattern of driving receiving the highest MEP score, the ODT system best serves those in disadvantaged communities, helping with an equity design goal. ODT improved the average MEP score across the service area by 100% when considering only non-private vehicle modes (bike, transit, and ODT). For the ODT scenarios, decreasing the wait time 50% compared to the baseline scenario led to a nearly 160% increase in MEP score, while increasing the ODT travel speed by 21% led to an 80% improvement in MEP score. The decreased wait time scenario had the highest MEP score out of the six ODT scenarios. This paper demonstrates how ODT can enhance mobility, particularly for disadvantaged communities. The results of a MEP analysis can be used by researchers and transit agencies to compare transportation modes and improve the effectiveness of transportation systems in subareas across a service area.

accessibility↗
DOE OSTI2024

Community Public Mobility Using On-Demand, Low-Speed Electric Vehicles: A Case Study in Downtown St. Louis, Missouri

Legacy fixed route transit systems designed to serve commuters struggle to provide efficient and effective service for short neighborhood trips and for population groups unable to access and egress transit stops using active modes (e.g., elderly, disabled). Neighborhood on-demand transit (ODT) services using low-speed electric vehicles (LSEV) are an innovative technological solution that can help fill this gap in service (e.g., short, high-frequency trips) for diverse populations and trip types. This study evaluated user characteristics and travel behavior for a neighborhood ODT service (using LSEVs) in downtown St. Louis, Missouri using responses from a community survey (n=244), ridership data, and vehicle trajectory information. A comparative analysis between neighborhood ODT, fixed route transit, and transportation network companies (TNC) was also conducted from the perspectives of total travel time, cost, and greenhouse gas emissions. Ultimately, the goal of the analysis was to motivate and inform holistic public mobility systems where different services are optimized to meet specific community needs. Findings indicate that the neighborhood ODT was effective at reaching diverse populations (elderly (20%), lower income (27%), and households with limited access to private vehicles (34%)). ODT reduced total travel time by 32% compared to fixed route transit, produced 2.4 - 4.3 times less greenhouse gas emissions per passenger mile (compared to transit and TNCs), and was more affordable (free to users) than alternative options ($1 for transit, $10-12 for TNCs). Overall satisfaction rates were high, with 80% of respondents rating the service a 4 or 5 out of 5.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2016

Effect of Aging and Demand for Reliability Analysis of Degrading Components

According to the U.S Energy Information Administration (EIA), the U.S fossil fuel share of energy consumption in 2015 was 67%. Furthermore, the Ecotricity UK report based on the CIA World Factbook states that with the current rate of consumption of fossil fuels, petroleum would run out by 2052, natural gas by 2060, and coal by 2088. No fossil fuel will remain by the next century. Besides the limited reserves of fossil fuel, massive consumption of fossil fuel also raises concerns about global warming and pollution. Therefore, there has been a growing interest in reducing fossil fuel consumption in the energy structure and in increasing the proportion of clean energy. Renewable energy (e.g. wind, solar) has the potential for distributed generation. However, the availability for renewable energy fluctuates and is uncontrollable. Therefore, additional energy sources need to be coupled with renewable energy to produce a stable electricity generation profile. Nuclear energy can serve this purpose as it is a clean energy source, has low greenhouse gas emission and possesses high power density and baseload power supply with low fuel cost. It is desirable to develop a hybrid energy system that combines both renewable energy and nuclear energy to meet low carbon emission goals and to utilize renewable energy. Such a nuclear hybrid energy system, consisting of different energy subsystems such as nuclear, solar, and wind, involves frequent switching between different energy subsystems. Since the primary loop in a nuclear power plant generates constant heat, the turbine bypass line in the secondary loop is required to switch frequently to meet the gap in the energy demand and that generated by the renewables. The increased usage of the turbine bypass system is considered to be the major difference between a nuclear hybrid energy system and a traditional nuclear power plant. Reliability analysis for designing such a complex system involves both high level fault propagation analysis at the conceptual design stage and low level failure prediction for specific components. The main focus of this summary to derive a degradation model of hardware components which can later help in the high level fault propagation analysis. The degradation model is a low level failure mode model that combines the effects of natural aging and frequent switching. The model can be used for predicting components' failure due to specific failure modes. The results can serve as indicators for conducting repair actions and maintenance to minimize Operation and Maintenance (O and M) costs. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Sustainable Public Transport: Providing Responsive, On-Demand Service with Clean Energy

The National Renewable Energy Laboratory (NREL) uses the Mobility Energy Productivity (MEP) as a metric and a lens to guide applied research into high performance public mobility. In the current initiative to abate global warming, the US needs not only zero-emission vehicles in the transit fleet (such as buses and shuttles) but also time- and cost-effective services to connect people with goods, services and employment toward a high-quality of life. Our current transportation system is overly dependent on personally-owned automobiles for high quality mobility, with public modes being less viable in many areas. Simply electrifying the drivetrains of existing public transit modes will fail to improve the quality of mobility for those that do not have access to private automobiles. The slow rebound by transit from the pandemic reveals the need to reinvent public transit service. Using the MEP lens, NREL researchers have tracked various novel developments in the public mobility space, with the confluence of shared, on-demand transit (ODT) services using light duty vehicles emerging as a key enabler of high-efficiency public mobility. Deployments such as those in Arlington, TX, Dallas, TX, Fort Erie, ON, and Innisfil, ON showcase the use of fleets of light-duty vehicles as the basis for community circulation and first/last mile to intra-regional transit. ODT services have demonstrated improvements in being more time efficient for riders, more energy efficient in operation (even before the introduction of fully electric vehicles), as well as being cost effective. It appears that aspects of the long-awaited promise of Personal Rapid Transit from the 1970s are beginning to be realized through ODT deployments, leveraging transportation network company (TNC) logistics, popularized by Uber and Lyft, but applied to public mobility. Currently, manually driven ODT operations are already cost competitive with traditional transit systems on a cost per ride basis, and full automation promises to reduce costs by 50% while providing additional safety and verified customer service. Connecting these ODT systems with efficient and effective intra-regional backbone transit service is the next step, with transit agencies like DART providing early results. This discussion will walk through the evidence for this postulated outcome and show results from a series of case-studies.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗