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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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NASA NTRSDate not supplied

Satellite-assisted Evaluation of Irrigation Application Efficiency for Lettuce in the Salinas Valley

The Salinas Valley region of California’s Central Coast is a majorU.S. vegetable producer. Lettuce is a leading commodity, grown on about 100,000 acres with annual value near $1.4B (2022 Monterey County Ag Report). Vegetables crops in the area aretypically well watered and fertilized in pursuit of commercial yield and quality standards. Information on irrigation application efficiency, meanwhile, can enhance waterresource sustainability and mitigate impacts of nitrate infiltrationon groundwater quality. The Crop Consumptive Use Fraction (CCUF), previously recommended by the California Department of Water Resources, is a metric that expresses evapotranspiration (ET) of applied water relative to total applied water. More recently under Assembly Bill 1668 addressing water conservation and drought planning, the metric can be used to help quantify application efficiency to support preparation of agricultural water management plans in the state. This study will report CCUF evaluations from several commercial lettuce plantings in the Salinas Valley during the 2022 dry season (late spring-early fall). The evaluations were derived from satellite-based observations of cropET from the OpenETcloud application, and applied water monitored by in-line flowmetersand supplemented by grower reports of irrigation system runtime. The study will also compare observed (satellite-based) ET with modeled ET from the CropManage irrigationand nutrient management decision-support system operated by Cooperative Extension. Additional study in cool-season vegetables is ongoing in 2023.

Satellite-assisted↗
DOE OSTI2021

Long and Winding Road to Higher Efficiency-The RTU Story: Preprint

Rooftop units (RTUs) and other packaged heating, ventilating, and air-conditioning (HVAC) equipment consume more than four quads of energy annually while conditioning more than 50% of the commercial building floor area in the United States. Historically, these systems have low operating efficiencies and receive infrequent maintenance. In addition, the market has a low first cost, run-to-failure, like-for-like replacement mentality and has been slow to adopt change. This paper explores the broad market transformation that has resulted in higher efficiencies and tremendous energy savings. Although there are many factors in this market transformation, this paper highlights: research behind advancements in components and controls; adoption of an operational efficiency metric; raising the bar for high efficiency with the RTU Challenge; market barriers overcome through the Advanced RTU Campaign; upstream and midstream incentive programs and HVAC distribution networks; alignment of the market efficiency drivers of ASHRAE Standard 90.1, federal minimum efficiency standards, the ENERGY STAR® program, and the Consortium for Energy Efficiency's (CEE's) efficiency tiers. Measures of the market transformation include more than 50% increase in RTU efficiencies, more than 1 billion kWh saved and 160,000 RTUs upgraded with high-efficiency measures by the Advanced RTU Campaign partners, large increases of high-efficiency RTUs purchased through incentive programs, and the largest energy savings from any federal minimum standards action. Although these results are impressive, the market transformation is just beginning, and there remain exciting opportunities for improvements in equipment efficiencies and improved operating performance with advanced controls and fault detection and diagnostics.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Improved Representation of Horizontal Variability and Turbulence in Mesoscale Simulations of an Extended Cold-Air Pool Event

Abstract Cold-air pools (CAPs), or stable atmospheric boundary layers that form within topographic basins, are associated with poor air quality, hazardous weather, and low wind energy output. Accurate prediction of CAP dynamics presents a challenge for mesoscale forecast models in part because CAPs occur in regions of complex terrain, where traditional turbulence parameterizations may not be appropriate. This study examines the effects of the planetary boundary layer (PBL) scheme and horizontal diffusion treatment on CAP prediction in the Weather Research and Forecasting (WRF) Model. Model runs with a one-dimensional (1D) PBL scheme and Smagorinsky-like horizontal diffusion are compared with runs that use a new three-dimensional (3D) PBL scheme to calculate turbulent fluxes. Simulations are completed in a nested configuration with 3-km/750-m horizontal grid spacing over a 10-day case study in the Columbia River basin, and results are compared with observations from the Second Wind Forecast Improvement Project. Using event-averaged error metrics, potential temperature and wind speed errors are shown to decrease both with increased horizontal grid resolution and with improved treatment of horizontal diffusion over steep terrain. The 3D PBL scheme further reduces errors relative to a standard 1D PBL approach. Error reduction is accentuated during CAP erosion, when turbulent mixing plays a more dominant role in the dynamics. Last, the 3D PBL scheme is shown to reduce near-surface overestimates of turbulence kinetic energy during the CAP event. The sensitivity of turbulence predictions to the master length-scale formulation in the 3D PBL parameterization is also explored. Significance Statement In this article, we demonstrate how a new framework for modeling atmospheric turbulence improves cold pool predictions, using a case study from January 2017 in the Columbia River basin (U.S. Pacific Northwest). Cold pools are regions of cold, stagnant air that form within valleys or basins, and improved forecasts could help to mitigate the risks they pose to air quality, transportation, and wind energy production. For the chosen case study, our tests show a reduction in temperature and wind speed errors by up to a factor of 2–3 relative to standard model options. These results strongly motivate continued development of the framework as well as its application to other complex weather events.

17 WIND ENERGY↗
NASA NTRS2014

Link Analysis for Space Communication Links Using ARQ Protocol

In space communications, standard link analysis assumes that messages are sent once. For a communication link that uses an error-correction coding scheme, bit-error-rate (BER) or frame-error-rate (FER), and link margins are common metrics that characterize the quality of a link, and they are used to determine the supportable data rate. With the advent of Automatic Repeat-reQuest (ARQ) protocols, when messages are corrupted during transmission, they can be resent multiple times automatically until they are correctly received and acknowledged. The concept of BER, FER, and link margin cannot be directly applied, and the link analysis approach for ARQ links needs to be re-examined.

Cheung, Kar-Ming↗
NASA NTRS2000

Wind Prediction Accuracy for Air Traffic Management Decision Support Tools

The performance of Air Traffic Management and flight deck decision support tools depends in large part on the accuracy of the supporting 4D trajectory predictions. This is particularly relevant to conflict prediction and active advisories for the resolution of conflicts and the conformance with of traffic-flow management flow-rate constraints (e.g., arrival metering / required time of arrival). Flight test results have indicated that wind prediction errors may represent the largest source of trajectory prediction error. The tests also discovered relatively large errors (e.g., greater than 20 knots), existing in pockets of space and time critical to ATM DST performance (one or more sectors, greater than 20 minutes), are inadequately represented by the classic RMS aggregate prediction-accuracy studies of the past. To facilitate the identification and reduction of DST-critical wind-prediction errors, NASA has lead a collaborative research and development activity with MIT Lincoln Laboratories and the Forecast Systems Lab of the National Oceanographic and Atmospheric Administration (NOAA). This activity, begun in 1996, has focussed on the development of key metrics for ATM DST performance, assessment of wind-prediction skill for state of the art systems, and development/validation of system enhancements to improve skill. A 13 month study was conducted for the Denver Center airspace in 1997. Two complementary wind-prediction systems were analyzed and compared to the forecast performance of the then standard 60 km Rapid Update Cycle - version 1 (RUC-1). One system, developed by NOAA, was the prototype 40-km RUC-2 that became operational at NCEP in 1999. RUC-2 introduced a faster cycle (1 hr vs. 3 hr) and improved mesoscale physics. The second system, Augmented Winds (AW), is a prototype en route wind application developed by MITLL based on the Integrated Terminal Wind System (ITWS). AW is run at a local facility (Center) level, and updates RUC predictions based on an optimal interpolation of the latest ACARS reports since the RUC run. This paper presents an overview of the study's results including the identification and use of new large mor wind-prediction accuracy metrics that are key to ATM DST performance.

Cole, Rod↗
NASA NTRS1995

Metrics and Benchmarks for Visualization

What is a "good" visualization? How can the quality of a visualization be measured? How can one tell whether one visualization is "better" than another? I claim that the true quality of a visualization can only be measured in the context of a particular purpose. The same image generated from the same data may be excellent for one purpose and abysmal for another. A good measure of visualization quality will correspond to the performance of users in accomplishing the intended purpose, so the "gold standard" is user testing. As a user of visualization software (or at least a consultant to such users) I don't expect visualization software to have been tested in this way for every possible use. In fact, scientific visualization (as distinct from more "production oriented" uses of visualization) will continually encounter new data, new questions and new purposes; user testing can never keep up. User need software they can trust, and advice on appropriate visualizations of particular purposes. Considering the following four processes, and their impact on visualization trustworthiness, reveals important work needed to create worthwhile metrics and benchmarks for visualization. These four processes are (1) complete system testing (user-in-loop), (2) software testing, (3) software design and (4) information dissemination. Additional information is contained in the original extended abstract.

Uselton, Samuel P.↗
DOE OSTI2020

Sister Rod Destructive Examinations (FY20) Appendix A: Full Length Rod Heat Treatments (FHT)

As a part of the US DOE-NE High Burnup Spent Fuel Data Project, ORNL is performing destructive examinations (DEs) of high burnup (HBU) (>45 gigawatt days per metric ton uranium) spent nuclear fuel (SNF) rods from the North Anna Nuclear Power Station operated by Dominion Energy. The SNF rods, called the “sister rods,” are all HBU and include four different kinds of fuel rod cladding: standard Zircaloy-4, low-tin Zircaloy-4, ZIRLO®, and M5®. The DEs are being conducted to obtain a baseline of the HBU rod’s condition prior to dry storage and are focused on understanding overall SNF rod strength and durability. Both composite fuel and empty cladding are being tested. While the data generated can be used for multiple purposes, a primary goal for obtaining the post-irradiation examination data will support SNF dry storage licensing and relicensing activities.This report documents the status of the ORNL Phase 1 DE activities related to full length rod heat treatments (FHT) applied to selected sister rods in Phase 1 of the sister rod test program. The results of this work and detailed examinations are summarized in the Sister Rod DE Status Report.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Sister Rod Destructive Examinations (FY20) Appendix B: Segmentation, Defueling, Metallograhic Data and Total Cladding Hydrogen

As a part of the US DOE-NE High Burnup Spent Fuel Data Project, ORNL is performing destructive examinations (DEs) of high burnup (>45 gigawatt days per metric ton uranium) spent nuclear fuel (SNF) rods from the North Anna Nuclear Power Station operated by Dominion Energy. The SNF rods, called the “sister rods,” are all HBU and include four different kinds of fuel rod cladding: standard Zircaloy-4, low-tin Zircaloy-4, ZIRLO®, and M5®. The DEs are being conducted to obtain a baseline of the HBU rod’s condition prior to dry storage and are focused on understanding overall SNF rod strength and durability. Both composite fuel and empty cladding are being tested. While the data generated can be used for multiple purposes, a primary goal for obtaining the post-irradiation examination data and the associated measured mechanical properties is to support SNF dry storage licensing and relicensing activities.This report documents the status of the ORNL Phase 1 DE activities related to: rough segmentation, defueling, optical microscopy, and cladding total hydrogen measurements for 7 Phase 1 sister rods and outlines the DE tasks performed and the data collected to date. The results of these detailed examinations and others are summarized in the Sister Rod DE Status Report.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

ELECTRIFICATION OF A HEAVY-DUTY OFF-ROAD MATERIAL HANDLER: ENERGY SAVINGS AND EMISSION REDUCTIONS

Federal regulations are driving the adoption of electrification technologies to reduce carbon dioxide equivalent (CO2e) emissions, a metric that quantifies the global warming potential of various greenhouse gases in terms of carbon dioxide (CO2). Although no specific CO2 regulations exist for heavy-duty off-road machines, future reductions are likely, given stricter emissions standards for on-road vehicles. The heavy-duty off-road sector offers significant fuel-saving potential, as its focus has traditionally been on reliability and performance rather than fuel efficiency. This dissertation examines fuel and CO2e savings opportunities on a heavy-duty off-road material handler, the Pettibone Cary-Lift 204i, from stock configuration to simple modifications to a complete teardown and reconfiguration of the machine with a plug-in series hybrid architecture using electrified hydraulics. The study begins by modeling the baseline machine’s fuel and energy consumption, calibrating with experimental data from custom operating cycles. An energy analysis identifies key areas for fuel savings. Two simple powertrain modifications result in a combined 16.2% fuel savings. Next, a Pugh-style analysis narrows a list of electrified architectures, leading to high-fidelity models that evaluate total lifetime CO2e and costs. Higher electrification levels reduce CO2e emissions but increase costs, and electricity grid emissions significantly impact CO2e for plug-in architectures. A plug-in series hybrid is chosen for the project. In its base control form, 49% fuel and 29% CO2e savings are expected from the plug-in series hybrid compared to the baseline machine. Further savings are pursued through regenerative braking (6.3%) and load-following hydraulic control (17.8%), totaling 24.1% fuel savings, and leading to a total of 61% fuel and 41% CO2e savings compared to the baseline. Battery chemistries and charging strategies are also analyzed for cost and CO2e impacts, finding LFP batteries as superior due to longevity, and overnight level 2 charging usually at a lower cost but resulting in higher emissions than opportunity DC fast-charging (DCFC). DCFC emissions are highly dependent on grid emissions, and DCFC cost is highly dependent on grid demand charges. Finally, artificial intelligence is applied to operating cycle recognition. Neural network accuracy ranges from 81% to 99%, with applications to worksite efficiency and safety improvements.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Multivariate Drought Monitoring, Propagation, and Projection Using Bias-Corrected General Circulation Models

Understanding how droughts are characterized, propagated, and projected, particularly multivariate droughts, is necessary to explain the variability and changes in drought characteristics. This study aims to understand multimodel global drought monitoring, propagation, and projection by utilizing a multivariate standardized drought index (MSDI) during the historical (1959–2014) and future (2045–2100) periods under two socioeconomic pathways SSPs (370 and 585), derived from the bias-corrected Coupled Model Intercomparison Project Phase 6 (CMIP6). Based on the energy metrics, the multivariate bias correction method outperformed other techniques in correcting the biases in the CMIP6 drought representation. The drought indicators demonstrate distinct categories for meteorological, hydrological, and multivariate droughts. There were significant high cross correlations between Heatwave Total Length (HWTL) and MSDI in Africa and South America for all lagged times. Europe and North America generally saw the maximum MSDI drought duration (228 months) during the historical period. For future projections, Africa recorded the maximum drought duration (197 months), while Europe witnessed the minimum drought duration for SSP 370 (171 months), and North America (149 months) for SSP 585. Furthermore, during the historical period in tropical Africa, the propagation of meteorological to hydrological drought was slower during the wet months than during the dry months. Under the SSP 370 future projection, there was a shift in the long period of meteorological-hydrological propagation from the middle and late wet months to the beginning of the wet months in tropical Africa. Therefore, tracking and projecting drought characteristics is vital for understanding the risk of drought-related consequences.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Physics makes the difference: Bayesian optimization and active learning via augmented Gaussian process

Abstract Both experimental and computational methods for the exploration of structure, functionality, and properties of materials often necessitate the search across broad parameter spaces to discover optimal experimental conditions and regions of interest in the image space or parameter space of computational models. The direct grid search of the parameter space tends to be extremely time-consuming, leading to the development of strategies balancing exploration of unknown parameter spaces and exploitation towards required performance metrics. However, classical Bayesian optimization (BO) strategies based on the Gaussian process (GP) do not readily allow for the incorporation of the known physical behaviors or past knowledge. Here we explore a hybrid optimization/exploration algorithm created by augmenting the standard GP with a structured probabilistic model of the expected system’s behavior. This approach balances the flexibility of the non-parametric GP approach with a rigid structure of physical knowledge encoded into the parametric model. The fully Bayesian treatment of the latter allows additional control over the optimization via the selection of priors for the model parameters. The method is demonstrated for a noisy version of a standard univariate test function used to evaluate optimization algorithms and further extended to physical lattice models. This methodology is expected to be universally suitable for injecting prior knowledge in the form of physical models and past data in the BO framework.

42 ENGINEERING↗
NASA NTRS1973

Accelerating one-dimensional searches.

In the search technique presented, the number of function evaluations is reduced by making use of the derivative of the function. The search method is combined with the variable metric algorithm reported by Davidon (1959) to solve a 17-parameter optimal atmospheric flight of a space shuttle vehicle. In the case of the problem, the proposed method requires one or two function evaluations per iteration less than the standard cubic fit-golden section method.

Johnson, I. L., Jr.↗
NASA NTRS1992

Radiation shielding estimates for manned Mars space flight

In the analysis of the required radiation shielding protection of spacecraft during a Mars flight, specific effects of solar activity (SA) on the intensity of galactic and solar cosmic rays were taken into consideration. Three spaceflight periods were considered: (1) maximum SA; (2) minimum SA; and (3) intermediate SA, when intensities of both galactic and solar cosmic rays are moderately high. Scenarios of spaceflights utilizing liquid-propellant rocket engines, low- and intermediate-thrust nuclear electrojet engines, and nuclear rocket engines, all of which have been designed in the Soviet Union, are reviewed. Calculations were performed on the basis of a set of standards for radiation protection approved by the U.S.S.R. State Committee for Standards. It was found that the lowest estimated mass of a Mars spacecraft, including the radiation shielding mass, obtained using a combination of a liquid propellant engine with low and intermediate thrust nuclear electrojet engines, would be 500-550 metric tons.

Non-NASA Center↗
NASA NTRS2007

Performance of a Borehole XRF Spectrometer for Planetary Exploration

We have designed and constructed a borehole XRF Spectrometer (XRFS) as part of the Mars Subsurface Access program. It will be used to determine the composition of the Mars regolith at various depths by insertion into a pre-drilled borehole. The primary performance metrics for the instrument are the lower limits of detection over a wide range of the periodic table. Power consumption during data collection was also measured. The prototype instrument is complete and preliminary testing has been performed. Terrestrial soil Standard Reference Materials were used as the test samples. Detection limits were about 10 weight parts-per-million for most elements, with light elements being higher, up to 1.4 weight percent for magnesium. Power consumption (excluding ground support components) was 12 watts.

Kelliher, Warren C.↗
NASA NTRS2014

Sentiment of Search: KM and IT for User Expectations

User perceived value is the number one indicator of a successful implementation of KM and IT collaborations. The system known as "Search" requires more strategy and workflow that a mere data dump or ungoverned infrastructure can provide. Monitoring of user sentiment can be a driver for providing objective measures of success and justifying changes to the user interface. The dynamic nature of information technology makes traditional usability metrics difficult to identify, yet easy to argue against. There is little disagreement, however, on the criticality of adapting to user needs and expectations. The Systems Usability Scale (SUS), developed by John Brook in 1986 has become an industry standard for usability engineering. The first phase of a modified SUS, polls the sentiment of representative users of the JSC Search system. This information can be used to correlate user determined value with types of information sought and how the system is (or is not) meeting expectations. Sentiment analysis by way of the SUS assists an organization in identification and prioritization of the KM and IT variables impacting user perceived value. A secondary, user group focused analysis is the topic of additional work that demonstrates the impact of specific changes dictated by user sentiment.

Berndt, Sarah Ann↗
NASA NTRS2015

Evaluating Performance of UAS Detect-And-Avoid System Using a Fast-Time Simulation Tool

Most unmanned aircraft systems will be required to be equipped with a Detect-and-Avoid (DAA) system. The surveillance performance of the DAA system to detect and track intruder aircraft will depend on the encounter geometries that unmanned aircraft are expected to have with other aircraft in the airspace. The performance of DAA alerting and avoidance system is also dependent on the timeliness of alerting for UAS pilots to give a sufficient time to determine and command a resolution maneuver to avoid well clear separation violations. This presentation introduces general background of UAS DAA systems and concept of well clear separation standard to satisfy see and avoid regulations. The presentation shows the several UAS mission profiles and analysis of the encounter geometries that were simulated using historical VFR traffic data and some proposed UAS missions. This presentation introduces several potential metrics for evaluating the performance of a DAA system and shows the results that measured through fast-time simulation with traffic scenarios that include NAS-wide VFR manned aircraft and IFR UAS flights. At the end, some research areas will be briefly discussed.

UAS↗
DOE OSTI2023

An investigation of non-canonical mixing in red giant stars using APOGEE 12 C/ 13 C ratios observed in open cluster stars

Standard stellar evolution theory poorly predicts the surface abundances of chemical species in low-mass, red giant branch (RGB) stars. Observations show an enhancement of p–p chain and CNO cycle products in red giant envelopes, which suggests the existence of non-canonical mixing that brings interior burning products to the surface of these stars. The 12 C/ 13 C ratio is a highly sensitive abundance metric used to probe this mixing. We investigate extra RGB mixing by examining: (1) how 12 C/ 13 C is altered along the RGB, and (2) how 12 C/ 13 C changes for stars of varying age and mass. Our sample consists of 43 red giants, spread over 15 open clusters from the Sloan Digital Sky Survey’s APOGEE DR17, that have reliable 12 C/ 13 C ratios derived from their APOGEE spectra. We vetted these 12 C/ 13 C ratios and compared them as a function of evolution and age/mass to the standard mixing model of stellar evolution, and to a model that includes prescriptions for RGB thermohaline mixing and stellar rotation. We find that the observations deviate from standard mixing models, implying the need for extra mixing. Additionally, some of the abundance patterns depart from the thermohaline model, and it is unclear whether these differences are due to incomplete observations, issues inherent to the model, our assumption of the cause of extra mixing, or any combination of these factors. Nevertheless, the surface abundances across our age/mass range clearly deviate from the standard model, agreeing with the notion of a universal mechanism for RGB extra mixing in low-mass stars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Developing Flexible, Networked Lighting Control Systems That Reliably Save Energy in California Buildings

An important strategy to meet California's ambitious energy efficiency goals is to use innovative wireless communications, embedded sensors, data analytics and controls to significantly reduce lighting energy use in commercial buildings. This project developed a suite of networked lighting solutions to further this goal. The technologies include a platform for low-cost sensing, distributed intelligence and communications, the “PermaMote,” which is a self-powered sensor and controller for lighting applications. The project team also developed a task ambient daylighting system that integrates sensors with data-driven daylighting control using an open communication interface, called the “Readings-At-Desk” (RAD) system. To address the problem of building occupants being confused about how to operate traditional lighting control systems, the research team created content that could be the basis for a user interface standard for lighting controls. Finally, to address the difficulty of ensuring that advanced lighting control systems actually deliver their promised energy savings, the project team developed a new method for evaluating and specifying lighting systems’ performance. The research team validated these technologies in the laboratory, showing significant lighting energy savings, up to 73% for the PermaMote sensor system from occupancy control and daylight dimming features, compared to the same light source (LED replacement lamps) operated via simple on/off scheduling. The project team also developed a proposed standard lighting data model and user interface elements, which were contributed to the ANSI Lighting Systems Committee (C137) for standardization. Existing data models are incomplete and inconsistent, whereas the lighting-specific data model developed here is clear and comprehensive, to serve as a starting point for creating common, universally agreed upon semantic definitions of key lighting parameters, to promote interoperability. For the task on verifiable performance of lighting systems, the project team developed a more effective metric for capturing the actual energy impact of a lighting system over time — the energy usage intensity (kWh/ft2/year). Three commercial lighting systems were tested in FLEXLAB® using this new metric, and the tests show a wide range in the accuracy of the self-reported energy-use metric, from 0.5% to 28% error compared to direct measurement of lighting energy using dedicated submeters. Overall, the project team estimates that these advanced technologies can reduce California office lighting energy use by 20% (above and beyond normal advanced lighting controls mandated by Title 24), resulting in about 1,600 GWh/year in savings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗