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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 OSTI2020

Evaluation of Exterior Shades at PNNL Lab Homes and Occupied Field Sites (Final Report)

In residential applications, heat transfer through windows accounts for a significant portion of a home’s cooling load. Exterior shades are window attachments that can be applied on the exterior-side of windows in a home. Exterior shades can reduce solar heat gain, reduce glare through a window, and improve comfort in the home. To assess the performance of residential exterior shades, the U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy (EERE), Building Technologies Office (BTO) commissioned a series of field studies for exterior fabric shades to be performed by Pacific Northwest National Laboratory (PNNL) during the cooling seasons of 2019 and 2020. This report describes the experimental setup and results of these exterior shade field studies. PNNL, in collaboration with Lawrence Berkeley National Laboratory (LBNL), evaluated exterior shades at the PNNL Lab Homes and three occupied field sites in Richland, Washington. At the Lab Homes, the energy performance of exterior shades was evaluated in a controlled side-by-side environment. At the occupied field sites, exterior shades were characterized by measuring shade usage, documenting installation practices, and surveying customer perspectives.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Predicting Si-Anode Calendar Life Using Machine Learning: Correlating Electrolyte Properties and Electrochemical Signals

This study evaluates novel electrolytes tailored for Si-containing anodes to promote calendar-life. Drawing inspiration from advancements in electrolytes for Li-metal cells, the work investigates correlations between predicted electrolyte properties and measured electrochemical performance using several machine-learning models. By leveraging machine learning and advanced modeling techniques, this study aims to establish predictive frameworks that accelerate calendar-aging experiments and inform rational electrolyte design for Si-containing cells. In the present study, fifteen different electrolytes are evaluated in a Si-containing cell using an accelerated calendar-life protocol. For each electrolyte considered, 87 properties (features) from the Advanced Electrolyte Model were produced to identify key property/performance relationships. In this study, the best performing electrolytes were generally those formulations that included non-coordinating fluoroether solvents, and the most predictive features for long-term calendar-life were features related to salt concentration and electrolyte viscosity as well as early capacity, ionic conductivity, and Coulombic efficiency measurements. The framework developed in this study correlating electrolyte properties to measured electrochemical performance is expected to accelerate electrolyte design for Si-containing anodes and ultimately enable high-energy-density, long-life Li-ion batteries.

25 - ENERGY STORAGE↗
DOE OSTI2023

Performance Analyses of Supercritical Carbon Dioxide-Based Parabolic Trough Collectors with Double-Glazed Receivers

Supercritical carbon dioxide is becoming a hot research topic as a potential heat transfer fluid in parabolic trough concentrators since it enables operating the solar system at high temperatures for a higher quality of energy. However, the corresponding inflated thermal losses necessitate alternative receiver designs. This work examines four double-glazed receivers, with each annular space being evacuated or non-evacuated, in terms of the absorber tube's diameter (53-80 mm) and the diameter ratios of the two glass shells (1.2-2.0). An analytical model is developed and validated for this purpose, and the four designs are further examined using ground-level solar and meteorological measurements. The results demonstrate higher performance in the case of fully evacuating the receiver and using the smallest possible diameters of the three concentric cylinders, where the energy and exergy efficiencies reach 65.3 and 40.3%, respectively. Yet, evacuating only the inner annular space is sufficient to achieve virtually the same performance level. This energy efficiency decreases to 62% in case of increasing the tube diameter to 80 mm. As the operating temperature increases from 423 to 850 K, the specific thermal losses increase by 3.98-4.34 folds, depending on the receiver design. Double glazing the receivers is favorable only at high operating temperatures of sCO2, where the reduction in thermal losses overcomes the drop in optical efficiency. For an inlet sCO2 temperature of 850 K, thermal losses are reduced by 33.64 and 53.92%, compared to evacuated and non-evacuated single-glazed receivers, respectively. Throughout the year, the fully evacuated and fully non-evacuated double-glazed receivers have energy efficiencies of 54.96 and 52.39%, exergy efficiencies of 33.64 and 32.06%, and thermal losses of 348.8 and 402.5 W/m, respectively.

analytical model↗
DOE OSTI2020

High-Resolution Measurement of Soil Thermal Properties and Moisture Content Using a Novel Heated Fiber Optics Approach

Hydrological parameters are scale dependent. Efficient monitoring techniques capable of measuring hydrological parameters, such as soil moisture content (θ), over a wide range of spatial scales are essential for understanding the complexity of water and energy movement across the landscape. Techniques to measure θ over spatial scales in the range from centimeters to thousands of meters, however, are sorely lacking. Recent improvements in the distributed temperature sensing (DTS) technology supported the development of novel techniques to fill that gap. However, improvements in the accuracy and applicability of DTS techniques are still needed. This study investigates the possibility of improving the accuracy of the fiber optics dual-probe heat-pulse (FO-DPHP) DTS technique by using a new design to maintain the spacing between the FO-DPHP probes and by introducing a novel data interpretation approach. The accuracy of the novel FO-DPHP design was tested at different θ in a sand column experiment. The FO-DPHP measurements obtained using traditional and novel data interpretation approaches were compared against independent measurements from several calibrated soil water content (EC5) sensors. Monte-Carlo analyses were also performed to assess the impact of DTS measurement errors on the accuracy achieved using the data interpretation approaches. The novel design and data interpretation approach allowed for accurate measurements of soil thermal properties and θ without the need to perform a hard-to-achieve soil-specific calibration. Measured θ had mean errors and standard deviations <0.03 and <0.01 m 3 m -3 , respectively, for moisture conditions ranging from dry to near saturation. The standard deviation in the measured heat capacity was <0.01 MJ m -3 K -1 .

42 ENGINEERING↗
DOE OSTI2026

Toward an AI-Powered Software Pipeline for Real-Time Tracking and Analysis of Wildfire and Smoke

Real-time tracking of wildfires and smoke is crucial for effective response, minimizing damage, protecting lives, and efficiently managing resources during fire emergencies. We develop a web-based AI-powered pipeline that detects wildfires in aerial video and estimates deployment-relevant behavior metrics, including cumulative burned area, burned-area growth rate, fire spread direction, and smoke dispersion. The system combines a YOLO-based detector with YCbCr-based fire segmentation, HSV-based smoke segmentation, Farneback optical flow, and centroid-based spatiotemporal tracking. Using ground sampling distance (GSD), pixel-level fire masks are converted to physical burned-area measurements by correlating fire pixel counts with camera altitude and tilt angle. We benchmark YOLO variants and non-YOLO baselines (GoogLeNet, CNN, DBN, Autoencoder, U-Net, and AlexNet) on the IEEE FLAME dataset and a newly created aerial frame dataset, Wildfire-DB. Cross-dataset evaluation uses a strict threshold-transfer protocol: decision thresholds are selected on FLAME validation and transferred unchanged to Wildfire-DB to quantify generalization under domain shift. YOLOv6 achieves the strongest cross-dataset frame-level fire detection on Wildfire-DB (ROC-AUC 0.8200, PR-AUC 0.8044, and transferred-threshold F1 0.7596). For tracking-oriented deployment requiring oriented localization, YOLO11-OBB provides the most reliable cross-dataset behavior among OBB-capable models while remaining computationally feasible. To analyze the feasibility of UAV deployment, we further measure inference efficiency using synchronized GPU and CPU power logs on a fixed workload of 1569 frames. YOLO-family models process the video in 5.73–12.47 seconds with net energy of 1247.28–1775.39 J, substantially lower latency and energy than heavier classification and reconstruction baselines. Overall, model optimality depends on operational objectives: YOLOv6 is best for cross-dataset detection robustness, whereas YOL...

Color segmentation↗
DOE OSTI2022

Seamless Wireless Communication Platform for Internet of Things Applications

The rapid growth of the Internet of Things (IoT) devices resulted in the proliferation of wireless technologies to cater to their increasing data rate requirements and support multiple applications. However, such ever-increasing wireless technologies present numerous challenges such as incompatible wireless standards, increased energy consumption, and insecure communication. The traditional gateways proposed in the literature suffers from limitations such as computational complexity, resource requirements, increased cost, and device size. We vision an era of seamless wireless communication to alleviate the aforementioned challenges in IoT applications. through three inter-dependent functionalities namely detection and identification of wireless technologies, energy-efficient transmit power control, and secure end-to-end communication. To prove the concept, a new gateway is proposed to achieve these three functionalities with only physical layer measurements so that the different communication protocols in the higher layers can be avoided. Novel schemes are conceptualized for resource-limited seamless IoT applications. Moreover, the conceptual seamless IoT platform is validated through software-based computer simulation and software-defined radio-based testbed implementation. Finally, the preliminary analysis demonstrates that the proposed platform has great potential in advancing seamless IoT applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Demonstration of Advanced Experimental and Theoretical Characterization of Hydrogen Dynamics and Associated Behavior in Advanced Reactors

Advanced materials development, manufacturing, and modeling capabilities for innovative reactor designs support nuclear security and mission-focused science through enhanced technology for safer and more efficient and secure production of nuclear energy. The research in this project has established: 1) a state-of-the-art neutron-based hydrogen mapping and cross-section measurement capability as well as detailed crystallographic characterization of hydrogen atoms at LANSCE, and 2) a multi-physics framework for simulating behavior of moderator materials and other material performance in advanced nuclear reactors. Through the course of this project, we successfully developed and demonstrated measurement techniques for hydrogen distribution and atomistic-scale behavior of hydrogen atoms using pulsed neutron techniques. In parallel, advanced multi-physics simulation tools to predict the behavior of hydrogen atoms, e.g. in a moderator for a nuclear reactor, through materials performance, neutron transport, and thermal mechanical behavior were enhanced. Multi-discipline areas across the laboratory were involved in the project as the integration of improved experimental capabilities with enhanced modeling and simulation through MST, NEN, SIGMA, and XCP division subject matter experts.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Nuclear Data for Spallation Neutron Radioisotope Production (Final Technical Report)

Over 50 million nuclear medicine procedures are performed annually, leading to a multi-billion dollar market for radioisotope production. The demand for new medical and research isotopes is growing, and radioisotope supply is insufficient. Most radioisotope production today utilizes charged particle or low-energy neutron irradiation of a target. Isotope production with tens to hundred MeV incident energies is a relatively unexplored option. There is a tremendous opportunity associated with a growing number of suitable domestic and international facilities buttressed by hundred million dollar global investments (e.g., the Los Alamos and Brookhaven Isotope Production Facilities, the European Spallation Source in Lund, and the Korean Multi-purpose Accelerator Complex in Gyeongbuk). In part due to a lack of supporting nuclear data that would make modeling radioisotope yields and purities possible, these facilities do not utilize their high-energy neutron fluxes for isotope production. This project attempted to measure neutron reaction excitation functions relevant to the large-scale production of critical radioisotopes, enabling development of cost-efficient isotope production methods, contributing to the improvement of theoretical models, and enhancing the value of national isotope production facilities. Reactions which form 67 Cu, 32 Si, and alpha-emitting isotopes like 225 Ac were chosen for their consistent prioritization by expert panels, representation of diverse reaction mechanisms, and relative lack of supporting nuclear data. Accurate measurement of these data is presently made only using quasi-monoenergetic neutron beams, which are produced by bombarding thin lithium targets with protons at only a few laboratories in the world. Ultimately, the projects efforts were incompletely accomplished due to a combination of multi-year technical issues at the only laboratory in the world which can make the proposed measurements, iThemba Labs in South Africa, and the onset of a global pandemic, which precluded the significant effort and time required to develop an independent measurement capability in the United States.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2026

Near Detector Selection for Neutral Current Disappearance Search at the Short-Baseline Neutrino Program

Various short baseline neutrino experiments observe anomalies that challenge the three-flavor neutrino oscillation model, consistent with a hypothetical “sterile” neutrino that does not interact via the weak force. This poster presents a near detector event selection at the Short-Baseline Near Detector (SBND), developed for the first search for neutral current (NC) disappearance at short-baseline experiments. NC disappearance provides ``smoking gun” insight into the sterile neutrino question because NC interactions are equally sensitive to all three active neutrinos, meaning any change in the NC interaction rate between near and far detectors cannot be explained by oscillations among known flavor states. This analysis focuses on the NC1p topology, the most common NC interaction type at the Short-Baseline Neutrino (SBN) Program. NC topologies are inherently challenging due to their low light yield and the absence of an outgoing charged lepton, which complicates identification and leads to poor energy reconstruction as the outgoing neutrino carries away a large portion of the neutrino’s initial energy. This work presents an NC1p event selection at the near detector, highlighting SBND’s impressive detector capabilities, including trigger efficiency studies. Combined with a novel kinematic energy reconstruction technique leveraging the detector’s outstanding hadronic detail, this analysis establishes a robust near detector foundation to target an NC disappearance measurement consistent with the 3$+$1 sterile neutrino model. This SBND selection will soon be combined with the far detector to conduct an NC disappearance search, providing unique insight and complementary information to traditional charged current searches and advancing the SBN Program’s goal to resolve the sterile neutrino question, including 3$+$1 searches and beyond.

Nicole Pallat, Nicole Pallat [Minnesota U.] (ORCID↗
DOE OSTI2019

Permanent Electrical Loads in New Homes

Numerous electrical products and components are installed by the builder during construction and prior to occupancy. Some of these components are required by safety codes, such as smoke detectors, others are needed to support the communications infrastructure, and still others provide features that future occupants will find useful, such as remotely controlled garage door openers. We compiled a list of over 50 builder-installed devices that are likely to have continuous power consumption, and measured the power consumptions for a smaller group. A procedure to measure these loads in a home was developed based on readings from the smart meter. A typical American home can easily have 80 W of continuous power – over 650 kWh/year – devoted to these components. New homes are likely to have more of these devices and higher loads. Techniques to reduce this energy use include: selection of lowest-power solutions when a range of power consumptions are available, more efficient circuitry and power management, a separate DC circuit to serve DC-powered appliances, and use of energyscavenging sensors and controls in place of grid-powered components. A protocol to define and measure builder-installed loads, along with a recommended ceiling, might also stimulate savings.

Meier, Alan↗
DOE OSTI2022

Real-Time Highly Resolved Spatial-Temporal Vehicle Energy Consumption Estimation Using Machine Learning and Probe Data

Real-time highly resolved spatial-temporal vehicle energy consumption is a key missing dimension in transportation data. Most roadway link-level vehicle energy consumption data are estimated using average annual daily traffic measures derived from the Highway Performance Monitoring System; however, this method does not reflect day-to-day energy consumption fluctuations. As transportation planners and operators are becoming more environmentally attentive, they need accurate real-time link-level vehicle energy consumption data to assess energy and emissions; to incentivize energy-efficient routing; and to estimate energy impact caused by congestion, major events, and severe weather. This paper presents a computational workflow to automate the estimation of time-resolved vehicle energy consumption for each link in a road network of interest using vehicle probe speed and count data in conjunction with machine learning methods in real time. The real-time pipeline can deliver energy estimates within a couple seconds on query to its interface. The proposed method was evaluated on the transportation network of the metropolitan area of Chattanooga, Tennessee. The volume estimation results were validated with ground truth traffic volume data collected in the field. To demonstrate the effectiveness of the proposed method, the energy consumption pipeline was applied to real-world data to quantify road transportation-related energy reduction because of mitigation policies to slow the spread of COVID-19 and to measure energy loss resulting from congestion.

Severino, Joseph↗
DOE OSTI2023

Perspectives on future research directions in green manufacturing for discrete products

With the increasing concern due to climate change caused by a higher atmospheric concentration of CO 2 and other greenhouse gases, reducing environmental impact is becoming more important for every part of society. Manufacturing is responsible for a significant amount of energy/material consumption and environmental burden and, therefore, has a great opportunity to reduce its impact through green manufacturing. Green manufacturing presents opportunities across the manufacturing enterprise to increase the efficient usage of energy and material resources. These opportunities include designing products to consume fewer materials and energy during manufacturing and use, incorporating more efficient manufacturing processes, streamlining and optimizing manufacturing schedules and plans, and circularizing products. The goal of this paper will be to provide a perspective from the authors on the opportunities that exist within green manufacturing for discrete products through a review of pertinent topics and future directions. The paper will focus on processes, manufacturing equipment, manufacturing systems, recovering value at a product’s end-of-life, and additional thoughts that include metrics and indicators, techno-economic assessment, and a discussion of efficiency and effectiveness. Key findings from this review include a need for social indicators and renewable energy considerations in scheduling and process planning, integrating Industry 4.0 into circular economy along with social and institutional dimensions, consistency in the ability to measure and conceptualize metrics and indicators, a detailed evaluation of the life cycle impacts and cost of Addit Manuf, and more human and environment-oriented considerations for smart manufacturing.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Zero carbon solid-state rechargeable redox fuel for long duration and seasonal storage

Here, this work presents a unique thermochemical process for charging magnesium-manganese-oxide-based solid-state rechargeable redox fuel. High-temperature heating of the processing furnace can be driven by either renewable electricity or concentrated solar power. The simple recyclable fuel charging concept is based on a tubular falling bed reactor with countercurrent oxygen-depleted gas flow for complete heat recuperation. The main focus of this work is achieving solid flowability at high temperatures (1,450°C) and extracting chemically charged solid at ambient temperature with minimal energy loss. The operation strategies described in this work have enabled consistent magnesium-manganese-oxide particle flow up to 1,450°C. The measured extent of the thermal reduction reaction after cooling the particles is more than 90% of the fully reduced state at equilibrium. The thermal-to-chemical efficiency and overall system efficiency are 96% and 35% respectively, which are the highest reported for thermochemical fuels to date.

25 ENERGY STORAGE↗
DOE OSTI2020

A Comparative Study of Redox Mediators for Improved Performance of Li-Oxygen Batteries.

Redox meditators (RMs) are soluble catalysts located in an electrolyte that can improve the energy efficiency (reduced overpotential) and cyclability of Li-oxygen (Li-O-2) batteries. In this work, 20 RMs within a Li-O-2 system with dimethyl sulfoxide and tetraethylene glycol dimethyl ether electrolytes are studied and their electrochemical features such as redox potential, the separation of cathodic and anodic peaks, and their current intensities are measured using cyclic voltammetry (CV) experiments. Six RMs are selected as "primary" choices based on their electrochemical performance, and stability tests are then performed to examine their electrochemical responses after consecutive cycles. Moreover, galvanostatic cycling tests are performed within a Li-O-2 battery system assembled with selected six RMs for real case consistency investigations. It is found that results from CV to galvanostatic cycling tests are consistent for halides and organometallic RMs, where the former exhibit much higher stability. However, the organic RMs show high reversibility in CV but low in battery cycling results. Density functional theory calculations are carried out to gain more understanding of the stability and redox potentials of the RMs. This study provides comparative information to select the most reliable RMs for Li-O-2 batteries along with new fundamental understanding of their electrochemical activity and stability.

cyclic voltammetry↗
DOE OSTI2020

Movable Thermometer System in ProtoDUNE

The movable temperature profiler is a 7 m vertical array of 24 sensors that measures cryogenic temperatures with a precision of a few mK. This precision is necessary to monitor the efficiency of re-circulation and purification of liquid-argon inside large liquid-argon based neutrino detectors. Liquid argon temperature impacts electron (signal) drift velocity, flow, purity distribution and thus the overall energy calibration. The temperature profiler is motorized and moves vertically, while in the detector, and cross-calibrates neighboring sensors. The temperature offsets between each sensor cancel the effects of electromagnetic noise. This poster reports on the temperature measurements and such in-situ cross-calibrations at ProtoDUNE (single phase) at CERN.}

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Field-Aging Test Bed for Behind-the-Meter PV + Energy Storage

Small DC-coupled battery test systems are deployed at the National Renewable Energy Laboratory to evaluate capacity fade models and report on performance parameters such as round-trip efficiency under indoor and outdoor deployment scenarios. Initial commercial battery products include LG Chem RESU lithium-ion (Li-ion) and Avalon vanadium redox flow batteries. Adapting indoor lab-scale test methods to outdoor systems has challenges, including maintaining constant temperature and fully controlling batteries through standard discharge curves. Initial measurements show the Li-ion battery systems performing within expectations, near 85% round-trip efficiency. Initial lifetime modeling and measurements indicate that battery capacity could degrade by 20%-35% over 10 years at current rates.

14 SOLAR ENERGY↗
DOE OSTI2020

Linkages between Policy and Business Innovation in the Development of China’s Energy Performance Contracting Market

China has a large and growing energy performance contracting (EPC) market, which has played a significant role in driving energy efficiency retrofits and improvements This paper evaluates how policies and business innovations have worked synergistically to expand China’s EPC market. We analyze the interconnected roles of four key factors: incentive policies, China’s Five-Year Plans, and business innovations in diversifying contract models and strengthening measurement and verification. We use multiple data sources for the analysis, including detailed information on business choices in 21 pilot projects, industry-wide surveys, and policy information. Our study indicates that supportive policies were important for the initial market development. As the market was established and continued to grow, the private sector started to take initiatives to address the issues that are left out of the policies, which helped overcome certain market barriers and enabled the sustainable growth of the market. Future policies could incorporate the successful innovations from the businesses to ensure long-term development of China’s EPC market. Understanding these policy and business drivers in a holistic way is critical to understanding how China was able to leverage its relatively small policy investments into much larger transformation of its existing buildings and industrial facilities through energy efficiency retrofits. This in turn can be informative for other countries seeking to achieve large-scale energy efficiency improvements.

Zhou, Yuanrong↗
DOE OSTI2022

Enhanced energy conversion efficiency promoted by cavitation in gasoline direct injection

High-pressure direct fuel injection plays the most crucial role in energy conversion and improving engine combustion efficiency and emission. The optimization of turbulent and multiphase fuel injection has focused on controlling hydrodynamic parameters such as injection pressure. While the thermodynamic influence is often considered in the flash boiling situation, we inquire into how gasoline-type fuel’s hydro- and thermodynamic properties impact the injection dynamics by fuel-temperature induced cavitation. The turbulent and cavitating flows emanating from the direct-injection nozzle is visualized by ultrafast x-ray imaging with an unprecedented spatiotemporal resolution. The ultrafast liquid-fuel dynamics are dominated by injection pressure as well as fuel temperature through cavitation, an important thermodynamic parameter but often difficult to control in engine combustion. With the most direct and quantitative measurement, we discovered that the near-nozzle fuel-jet dynamics can be perfectly scaled by a single dimensionless parameter, cavitation number, particularly sensitive to the fuel temperature, in a wide operation range. This universal scaling shows that cavitation can be harnessed to elevate the pneumatic-hydraulic to kinetic energy conversion efficiency, critical for promoting fuel atomization and engine combustion performance. This enhancement effect will have even more impact on engine combustion using alternative low-emission fuels with higher saturated vapor pressure.

30 DIRECT ENERGY CONVERSION↗