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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Optimized bioregenerative space diet selection with crew choice

Previous studies on optimization of crew diets have not accounted for choice. A diet selection model with crew choice was developed. Scenario analyses were conducted to assess the feasibility and cost of certain crew preferences, such as preferences for numerous-desserts, high-salt, and high-acceptability foods. For comparison purposes, a no-choice and a random-choice scenario were considered. The model was found to be feasible in terms of food variety and overall costs. The numerous-desserts, high-acceptability, and random-choice scenarios all resulted in feasible solutions costing between 13.2 and 17.3 kg ESM/person-day. Only the high-sodium scenario yielded an infeasible solution. This occurred when the foods highest in salt content were selected for the crew-choice portion of the diet. This infeasibility can be avoided by limiting the total sodium content in the crew-choice portion of the diet. Cost savings were found by reducing food variety in scenarios where the preference bias strongly affected nutritional content.

Non-NASA Center↗
NASA NTRS2022

Exploring Applications of Machine Learning for Wildfire Monitoring and Detection using Unmanned Aerial Vehicles

Wildfires are increasing in frequency and severity around the world, including the United States. The losses caused by wildfires could be mitigated if high-risk areas, hotspots, and flare-ups could be monitored continuously, such as through the use of Unmanned Aerial Vehicles (UAVs). This paper documents exploratory efforts using machine learning to determine efficient flight paths for UAVs and to detect wildfires using image classification. On path planning, three machine learning techniques—Genetic Algorithm, Simulated Annealing, and Dynamic Programming—were explored. Genetic Algorithm was found to be an effective approach for path planning for wildfire monitoring and surveillance by UAVs. For a scenario of 25 locations in a circular arrangement, the algorithm was able to return the optimal path. The accuracy and execution time was found to be sensitive to the algorithm hyperparameters selected, which was especially evident in scenarios with hundreds or thousands of locations. Simulated Annealing was also found to be an effective approach for UAV path planning, with a major benefit of avoiding getting trapped in local minima and being straightforward to implement. Like Genetic Algorithm, the performance of Simulated Annealing was also found to be sensitive to the algorithm hyperparameters selected. By comparison, Dynamic Programming guarantees optimality for any number of locations, but it was found to be less practical in terms of execution time for scenarios with more than about a couple dozen locations. On wildfire detection, image classification using deep learning with a convolutional neural network was explored. Transfer learning was found to be a useful technique to efficiently train deep learning models. Also, it was determined that GPU processing can increase training speed by an order of magnitude, which enables significantly faster development. For a validation test set of 500 images, there were only two false negatives and zero false positives. These results demonstrate that detecting wildfires in static cameras using machine learning is feasible and establish a baseline for using images captured by UAVs in flight for wildfire detection.

Wildfire management↗
DOE OSTI2020

How Do Electricity Pricing Programs Impact the Selection of Energy Efficiency Measures? - A Case Study with U.S. Medium Office Buildings

Building owners usually select energy efficiency measures (EEMs) by referring to return on investment (ROI). Current studies tend to apply static energy price to estimate ROI. However, more and more buildings are adopting dynamic electricity pricing programs. To understand how electricity pricing programs impact the selection of EEMs, this paper presents an analysis of the ROIs of EEMs under different pricing programs using U.S. medium office buildings as an example. Eight EEMs in four typical cities are selected as case studies. Considering five electricity pricing programs scenarios (one static program and four dynamic programs), EEMs are selected based on their ROIs. The main findings are: (1) The ROIs of EEMs change under different pricing programs. (2) In Honolulu, Buffalo, and Denver, replacing interior fixtures with higher-efficiency fixtures has a significantly higher ROI than the rest EEMs under all five pricing programs. However, the ROI of this EEM in Honolulu ranges from 28% to 47% for different pricing programs. (3) Similarly, in Fairbanks, replace heating coil with higher-efficiency coil produce higher ROI than the rest under all five pricing programs. (4) For other EEMs, their ROI rankings vary according to electricity pricing programs.

demand response↗
NASA NTRSDate not supplied

Assured Contingency Landing Management for Advanced Air Mobility

Advanced Air Mobility (AAM) is quickly developing as a new air transportation system that moves people and packages in the regions previously not / less served by the current aviation systems. Such AAM must operate safely despite the potential to encounter hazards and experience anomalies and failures in-flight. It becomes especially important to have systematic auto-mitigation strategies to perform safe contingency actions in AAM flight operations, as pilots have limited Situational Awareness (SA) and limited time to make prompt decisions when encountering failures/anomalies in high-density low altitude airspace. This paper presents Assured Contingency Landing Management (ACLM) with an online landing strategy selection to decide between the following three options when a contingency landing is required: (1) Return-to-launch landing site, (2) Land immediately at a nearby clear but unprepared site, (3) Land at a prepared landing site from the approximate footprint. Our presented algorithm shows a real-time auto-mitigation loop with multiple threads that run simultaneously to check controllability, reachability, and intermediate decisions to hold/ loiter or continue the flight plan as the landing strategy solution is being computed. Case study simulation is demonstrated with the safety-critical propulsion system and battery system and shows how different failure scenarios impact the landing strategy selection.

Autonomous Mitigation↗
DOE OSTI2023

Probing the muon ( g − 2) anomaly at the LHC in final states with two muons and two taus

The longstanding muon (g - 2) anomaly, as well as some hints of lepton flavor universality violation in B-meson decays, could be signaling new physics beyond the Standard Model (SM). A minimal R-parity-violating supersymmetric framework with light third-generation sfermions (dubbed as ‘RPV3’) provides a compelling solution to these flavor anomalies, while simultaneously addressing other pressing issues of the SM. We propose a new RPV3 scenario for the solution of the muon (g - 2) anomaly, which leads to an interesting LHC signal of $µ$ + $µ$ - $τ$ + $τ$ - final state. We analyze the Run-2 LHC multilepton data to derive stringent constraints on the sneutrino mass and the relevant RPV coupling in this scenario. We then propose dedicated selection strategies to improve the bound even with the existing dataset. We also show that the high-luminosity LHC will completely cover the remaining muon (g - 2)-preferred parameter space, thus providing a robust, independent test of the muon (g - 2) anomaly.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Bio-inspired gas sensing: boosting performance with sensor optimization guided by “machine learning”

The performance of existing gas sensors often degrades in field conditions because of the loss of measurement accuracy in the presence of interferences. Thus, new sensing approaches are required with improved sensor selectivity. We are developing a new generation of gas sensors, known as multivariable sensors, that have several independent responses for multi-gas detection with a single sensor. In this study, we analyze the capabilities of natural and fabricated photonic three-dimensional (3-D) nanostructures as sensors for the detection of different gaseous species, such as vapors and non-condensable gases. We employed bare Morpho butterfly wing scales to control their gas selectivity with different illumination angles. Next, we chemically functionalized Morpho butterfly wing scales with a fluorinated silane to boost the response of these nanostructures to the vapors of interest and to suppress the response to ambient humidity. Further, we followed our previously developed design rules for sensing nanostructures and fabricated bioinspired inorganic 3-D nanostructures to achieve functionality beyond natural Morpho scales. These fabricated nanostructures have embedded catalytically active gold nanoparticles to operate at high temperatures of ≈300 °C for the detection of gases for solid oxide fuel cell (SOFC) applications. Our performance advances in the detection of multiple gaseous species with specific nanostructure designs were achieved by coupling the spectral responses of these nanostructures with machine learning (a.k.a. multivariate analysis, chemometrics) tools. Our newly acquired knowledge from studies of these natural and fabricated inorganic nanostructures coupled with machine learning data analytics allowed us to advance our design rules for sensing nanostructures toward the required gas selectivity for numerous gas monitoring scenarios at room and high temperatures for industrial, environmental, and other applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Spent Nuclear Fuel and Reprocessing Waste Inventory

This report provides information on the inventory of spent nuclear fuel (SNF) in the United States located at Nuclear Power Reactor (NPR) and Independent Spent Fuel Storage Installation (ISFSI) sites, as well as SNF and reprocessing waste located at U.S. Department of Energy (DOE) sites and other research and development (R&D) centers. Actual or estimated quantitative values for current inventories are provided along with inventory forecasts derived from examining different future nuclear power generation scenarios. The report also includes select information on the characteristics associated with the wastes examined (e.g., type, packaging, heat generation rate, decay curves).

Peters, Shan↗
DOE OSTI2020

Spent Nuclear Fuel and Reprocessing Waste Inventory

This report provides information on the inventory of commercial spent fuel (SNF) and high-level radioactive waste in the United States, as well as non-commercial SNF and reprocessing waste in the U.S. Department of Energy (DOE) complex. Actual or estimated quantitative values for current inventories are provided along with inventory forecasts derived from examining different future commercial nuclear power generation scenarios. The report also includes select information on the characteristics associated with the wastes examined (e.g., type, packaging, heat generation rate, decay curves).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Spent Nuclear Fuel and Reprocessing Waste Inventory

This report provides information on the inventory of spent nuclear fuel (SNF) in the United States located at Nuclear Power Reactor (NPR) and Independent Spent Fuel Storage Installation (ISFSI) sites, as well as SNF and reprocessing waste located at U.S. Department of Energy (DOE) sites and other research and development (R&D) centers. Actual or estimated quantitative values for current inventories are provided along with inventory forecasts derived from examining different future nuclear power generation scenarios. The report also includes select information on the characteristics associated with the wastes examined (e.g., type, packaging, heat generation rate, decay curves).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

An Integrated Feasibility Study of Reservoir Thermal Energy Storage (RTES) in Portland, OR, USA

In regions with long cold overcast winters and sunny summers, Deep Direct-Use (DDU) can be coupled with Reservoir Thermal Energy Storage (RTES) technology to take advantage of pre-existing subsurface permeability to save summer heat for later use during cold seasons. Many aquifers worldwide are underlain by permeable regions (reservoirs) containing brackish or saline groundwater that has limited beneficial use due to poor water quality. We investigate the utility of these relatively deep, slow flowing reservoirs for RTES by conducting an integrated feasibility study in the Portland Basin, Oregon, USA, developing methods and obtaining results that can be widely applied to RTES systems elsewhere. As a case study, we have conducted an economic and social cost-benefit analysis for the Oregon Health and Science University (OHSU), a teaching hospital that is recognized as critical infrastructure in the Portland Metropolitan Area. Our investigation covers key factors that influence feasibility including 1) the geologic framework, 2) heat and fluid flow modeling, 3) capital and maintenance costs, 4) the regulatory framework, and 5) operational risks. By pairing a model of building seasonal heat demand with an integrated model of RTES resource supply, we determine that the most important factors that influence RTES efficacy in the study area are operational schedule, well spacing, the amount of summer heat stored (in our model, a function of solar array size), and longevity of the system. Generally, heat recovery efficiency increases as the reservoir and surrounding rocks warm, making RTES more economical with time. Selecting a base-case scenario, we estimate a levelized cost of heat (LCOH) to compare with other sources of heating available to OHSU and find that it is comparable to unsubsidized solar and nuclear, but more expensive than natural gas. Additional benefits of RTES include energy resiliency in the event that conventional energy supplies are disrupted (e.g., natural disaster) and a reduction in fossil fuel consumption resulting in a smaller carbon footprint. Key risks include reservoir heterogeneity and a possible reduction in permeability through time due to scaling (mineral precipitation). Lastly, a map of thermal energy storage capacity for the Portland Basin yields a total of 43,400 GWh, suggesting tremendous potential for RTES in the Portland Metropolitan Area.

14 SOLAR ENERGY↗
DOE OSTI2022

Design Considerations for Fermilab Multi-MW Proton Facility in the DUNE/LBNF era

Fermilab has submitted two Snowmass whitepapers on a future 2.4~MW upgrade for DUNE/LBNF featuring a 2 GeV extension of the PIP-II linac and the construction of a new rapid-cycling-synchrotron. This paper summarizes the relationship between these two scenarios, emphasizing the commonalities and tracing the differences to their original design questions. In addition to a high-level summary of the two 2.4~MW upgrade scenarios, there is a brief discussion of staging, beamline capabilities, subsequent upgrades, and relevant R&D. We are proposing a vigorous program to address various challenges associated with each scenario and to down-select the concept, most suitable to provide proton beams for years to come.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Dark Matter Search in the Muon g-2 experiment at Fermilab

Dark matter is one of the most interesting research topics in physics. Many particle physicists are trying to identify it because we know that dark matter could be a major component of a complete fundamental description of nature. The Muon g-2 Experiment at Fermilab measures the anomalous precession frequency of the muon. Oscillations of this precession frequency could be produced by dark matter coupling to muons. This talk will describe how we could observe DM signals in the Muon g-2 data. I will explain how we determine the Muon g-2 DM mass range sensitivity, and analysis strategies throughout the mass range. Finally, I will present the expected Muon g-2 experiment discovery/exclusion reach in selected DM model-dependent scenarios.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1975

Examination of the costs, benefits and enery conservation aspects of the NASA aircraft fuel conservation technology program

The costs and benefits of the NASA Aircraft Fuel Conservation Technology Program are discussed. Consideration is given to a present worth analysis of the planned program expenditures, an examination of the fuel savings to be obtained by the year 2005 and the worth of this fuel savings relative to the investment required, a comparison of the program funding with that planned by other Federal agencies for energy conservation, an examination of the private industry aeronautical research and technology financial posture for the period FY 76 - FY 85, and an assessment of the potential impacts on air and noise pollution. To aid in this analysis, a computerized fleet mix forecasting model was developed. This model enables the estimation of fuel consumption and present worth of fuel expenditures for selected commerical aircraft fleet mix scenarios.

Source record↗
NASA NTRS1986

Design and development of a Space Station proximity operations research and development mockup

Proximity operations (Prox-Ops) on-orbit refers to all activities taking place within one km of the Space Station. Designing a Prox-Ops control station calls for a comprehensive systems approach which takes into account structural constraints, orbital dynamics including approach/departure flight paths, myriad human factors and other topics. This paper describes a reconfigurable full-scale mock-up of a Prox-Ops station constructed at Ames incorporating an array of windows (with dynamic star field, target vehicle(s), and head-up symbology), head-down perspective display of manned and unmanned vehicles, voice- actuated 'electronic checklist', computer-generated voice system, expert system (to help diagnose subsystem malfunctions), and other displays and controls. The facility is used for demonstrations of selected Prox-Ops approach scenarios, human factors research (work-load assessment, determining external vision envelope requirements, head-down and head-up symbology design, voice synthesis and recognition research, etc.) and development of engineering design guidelines for future module interiors.

Haines, Richard F.↗
NASA NTRS1990

Estimation Of Interference In Satellite/Ground Communications

Relative strengths of desired and interfering signals computed for known orbits. Satellite Interference Analysis and Simulation Using Personal Computers (AKSATINT) computer program calculates interference experienced by generic satellite communications receiving station from interfering satellite. Also computes interference-to-signal-power ratio, taking into account losses suffered by links. Of general use to designers of systems and managers of frequencies in selecting proper frequencies under interference scenarios. Written in BASIC.

Kantak, Anil V.↗
NASA NTRS2013

End of Mission Considerations

While a great deal of effort goes into planning and executing successful mission operations, it is also important to consider the End of the Mission during the planning, design, and operations phases of any mission. Spacecraft and launch vehicles must be disposed of properly in order to limit the generation of orbital debris, and better preserve the orbital environment for all future missions. Figure 30-1 shows a 1990's projected growth of debris with and without the use of responsible disposal techniques. This requires early selection of a responsible disposal scenario, so that the necessary capabilities can be incorporated into the hardware designs. The mission operations must then be conducted in such a way as to preserve, and then actually perform, the planned, appropriate end of mission disposal.

Hull, Scott M.↗
NASA NTRS2017

Selection of a Representative Subset of Global Climate Models that Captures the Profile of Regional Changes for Integrated Climate Impacts Assessment

We present the Representative Temperature and Precipitation (T&P) GCM Subsetting Approach developed within the Agricultural Model Intercomparison and Improvement Project (AgMIP) to select a practical subset of global climate models (GCMs) for regional integrated assessment of climate impacts when resource limitations do not permit the full ensemble of GCMs to be evaluated given the need to also focus on impacts sector and economics models. Subsetting inherently leads to a loss of information but can free up resources to explore important uncertainties in the integrated assessment that would otherwise be prohibitive. The Representative T&P GCM Subsetting Approach identifies five individual GCMs that capture a profile of the full ensemble of temperature and precipitation change within the growing season while maintaining information about the probability that basic classes of climate changes (relatively cool/wet, cool/dry, middle, hot/wet, and hot/dry) are projected in the full GCM ensemble. We demonstrate the selection methodology for maize impacts in Ames, Iowa, and discuss limitations and situations when additional information may be required to select representative GCMs. We then classify 29 GCMs over all land areas to identify regions and seasons with characteristic diagonal skewness related to surface moisture as well as extreme skewness connected to snow-albedo feedbacks and GCM uncertainty. Finally, we employ this basic approach to recognize that GCM projections demonstrate coherence across space, time, and greenhouse gas concentration pathway. The Representative T&P GCM Subsetting Approach provides a quantitative basis for the determination of useful GCM subsets, provides a practical and coherent approach where previous assessments selected solely on availability of scenarios, and may be extended for application to a range of scales and sectoral impacts.

Climate Change; GCMs; Climate Model Subset; Repres↗
NASA NTRSDate not supplied

The Origin of Palimpsests

Palimpsests are the most enigmatic impact features observed on icy worlds of the Solar System. Palimpsests are large impact features which are bright, old, mostly flat, and roughly circular. They range from >150 to ~350 km in diameter and sometimes exhibit recognizable associated radial secondary ejecta crater strings beyond their rims. Curiously, among all the Solar System's icy worlds, palimpsests are exclusively seen on the icy Galilean moons. Palimpsests are obviously different than similarly sized impact features seen on other icy satellites. For example, Evander, a 350 km diameter peak-ring impact basin on Saturn’s moon Dione, has a very low depth/diameter ratio of 0.008, indicating significant viscous relaxation. Nevertheless, it still retains short wavelength topography including a prominent central peak, peak ring, and a continuous rim, none of which are seen at palimpsests. Palimpsests display an approximately circular, and dominating, expanse of undulating plains, which is level with surrounding terrain and shows no recognizable rim. At the center of palimpsests are smooth central plains that are enclosed by a low scarp. Central plains material superposes the surrounding undulating plains and is littered with small blocks reminiscent of “small chaos” on Europa. Palimpsests have yet to be explored using modern impact simulation tools. We have begun to investigate two competing hypotheses: (A) Palimpsests form on targets which have a preexisting near-subsurface layer that is liquid or solid but very weak, and is excavated as proximal ejecta; or (B) They form in a solid ice target underlain by a steep thermal gradient that strongly influences the resulting impact feature, including the production of impact-induced melting at depth that is then a major component of proximal ejecta. Our results will have profound implications for the early thermal history of the icy Galilean satellites. We will test our two hypotheses for the formation of palimpsests on Ganymede (where they are both best observed and preserved) by means of 2D iSALE hydrodynamic simulations of impacts into ice targets that will be structured according to the scenarios for each hypothesis, with select runs in 3D. We have already conducted a pilot study using 2D iSALE that has yielded promising results, which we will report out at the meeting.

palimpsests↗