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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Energy Efficient Thermoplastic Composite Manufacturing

The objective of the project was to establish an effective and affordable method to lay-up and consolidate/join large thermoplastic composite aerospace structure with cycle times measured in minutes rather than hours. Composite airplane designs have proven efficient and effective however future potential product production rates are challenging what the current systems can efficiently produce due to material lay-down constraints and extended thermal cycle times. The ability to lay-up then rapidly heat, consolidate, and cool large complex composite structures plus very accurately tool them (i.e. matching CTE of composite materials) along with very precise thermal control is a difficult challenge. Current systems such as autoclave processing of thermoset materials require long cycle times due to method of heating and the large associated thermal masses. These extended cycle times inhibit the ability to meet higher rate production scenarios due to the need for multiple sets of equipment and tools. Thermoplastic composite materials were used to facilitate more rapid cycle times via the elimination of a need for a cure dwell at temperature. Also, utilized induction heating along with smart susceptors to enable the quick cycle times needed while providing precise intrinsic thermal control. The intrinsic control of the induction heating process via the smart susceptors along with the use of laser assisted fiber placement were the key innovations areas developed. The ability to rapidly heat and then precisely control the temperature of the consolidation component was paramount to the success of this project. It is this unique processing attribute coupled with the thermoplastic material characteristics along with rapid lay-up methods that are novel and advantageous. While many requirements and influencing factors decide the materials and processes utilized for future airplane construction, the forecast of accelerated production rates and the recent performance successes of composites in airplane construction provide an opportunity for this processing technology to have significant influence. During the course of this project a number of key accomplishments were completed. They are as follows: The needed laser assisted fiber placement capabilities have been developed and validated on a component of meaningful scale and complexity. Subsequently, a thermoplastic preform of the part scale-up part design was laser assisted fiber placed and made availalbe for consolidation. An induction consolidation system was sized, designed, and fabricated resulting in the full capability to consolidate the scale-up component. The tool for induction consolidating of the scale-up component was designed and fabricated. An aluminum pressure bladder was welded and formed for use as the pressurization membrane to perform the needed application of pressure on the part at temperature to achieve consolidation. The induction consolidation system consisting of the restraint, induction power supply, induction tool with integrated induction coils and smart susceptor liners, along with the aluminum bladder were successfully used to consolidate a large thermoplastic skin. The capability of accomplishing rapid heat-up rates and cool down rates for consolidation of large thermoplastic skins with precise thermal control and even pressure application at the consolidation temperature was validated. The general conclusion is that the use of induction consolidation with smart susceptors is an effective method to rapidly and efficiently consolidate large thermoplastic composite components and enable affordable high rate manufacturing of composites. More specific conclusions generated by this project are as follows: A restraint type induction consolidation system provides an affordable option over the standard press when using the induction consolidation processing method. Aluminum bladders can be formed to the complex shapes needed and supply uniform pressure for consolidation and co-consolidation of thermoplastic composite materials. Straightforward modifications can be made to existing fiber placement robotic systems to enable their use for thermoplastic lay-up applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Unmanned Aerial Vehicle Synthetic Aperture RADAR for Surface Change Monitoring

Space-based and airplane-based synthetic aperture RADAR (SAR) can monitor ground height using interferometric SAR (InSAR) collections. However, fielding the airplane-based SAR is expensive and coordinating the frequency and timing of ground experiments with space-based SAR is challenging. This research explored the possibility of using a small, mobile unmanned aerial vehicle- base (UAV) SAR to see if it could provide a quick and inexpensive InSAR option for the Source Physics Experiment (SPE) Phase III project. Firstly, a local feasibility collection using a UAV-based SAR showed that InSAR products and height measurements were possible, but that in-scene fiducials were needed to assist in digital elevation model (DEM) construction. Secondly, an InSAR collection was planned and executed over the SPE Phase III site using the same platform configuration. We found that the image formation by the SAR manufacturer creates discontinuities, and that noise impacted the generation and accuracy of height maps. These processing artifacts need to be overcome to generate an accurate height map.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Acoustic Properties of Aerogels: Current Status and Prospects

Noise reduction remains an important priority in the modern society, in particular, for urban areas and highly populated cities. Insulation of buildings and transport systems such as cars, trains, and airplanes has accelerated the need to develop advanced materials. Various porous materials, such as commercially available foams and granular and fibrous materials, are commonly used for sound mitigating applications. In this review, a special class of advanced porous materials, aerogels, is examined, and an overview of the current experimental and theoretical status of their acoustic properties is provided. Aerogels can be composed of inorganic matter, synthetic or natural polymers, as well as organic/inorganic composites and hybrids. Aerogels are highly porous nanostructured materials with a large number of meso‐ and small macropores; the mechanisms of sound absorption partly differ from those of traditional porous absorbers possessing large macropores. The understanding of the acoustic properties of aerogels is far from being complete, and experimental results remain scattered. It is demonstrated that the structure of the aerogel provides a complex three‐dimensional architecture ideally suited for promising high‐performance materials for acoustic mitigation systems. This is in addition to the numerous other desirable properties that include low density, low thermal conductivity, and low refractive index.

36 MATERIALS SCIENCE↗
DOE OSTI2025

deadtrees.earth — An open-access and interactive database for centimeter-scale aerial imagery to uncover global tree mortality dynamics

Excessive tree mortality is a global concern and remains poorly understood as it is a complex phenomenon. We lack global and temporally continuous coverage on tree mortality data. Ground-based observations on tree mortality, e.g., derived from national inventories, are very sparse, and may not be standardized or spatially explicit. Earth observation data, combined with supervised machine learning, offer a promising approach to map overstory tree mortality in a consistent manner over space and time. However, global-scale machine learning requires broad training data covering a wide range of environmental settings and forest types. Low altitude observation platforms (e.g., drones or airplanes) provide a cost-effective source of training data by capturing high-resolution orthophotos of overstory tree mortality events at centimeter-scale resolution. Here, we introduce deadtrees.earth, an open-access platform hosting more than two thousand centimeter-resolution orthophotos, covering more than 1,000,000 ha, of which more than 58,000 ha are manually annotated with live/dead tree classifications. This community-sourced and rigorously curated dataset can serve as a comprehensive reference dataset to uncover tree mortality patterns from local to global scales using space-based Earth observation data and machine learning models. This will provide the basis to attribute tree mortality patterns to environmental changes or project tree mortality dynamics to the future. The open nature of deadtrees.earth, together with its curation of high-quality, spatially representative, and ecologically diverse data will continuously increase our capacity to uncover and understand tree mortality dynamics.

Citizen science↗
DOE OSTI2025

Flow Reactor Study of the Soot Precursors of Novel Cycloalkanes as Synthetic Jet Fuel Compounds: Octahydroindene, p -Menthane, and 1,4-Dimethylcyclooctane

Sustainable aviation fuels (SAFs) or Synthetic aviation turbine fuels (SATFs) derived from nonpetroleum sources are essential for energy security and a strong rural and agricultural economy. Airplanes operating on SAF can have lower particle emissions compared to those of conventional jet fuel, reducing air quality impacts near airports. Processing biobased isoprene or wood and agricultural waste can produce cycloalkane-rich fuels with properties meeting ASTM International’s SATF requirements. The unique structures of these cycloalkanes yield lower soot emissions because of their lack of aromatic rings. We measured the soot formation tendency as yield sooting index (YSI) and used laminar flow reactor experiments to evaluate soot precursors formed for isoprene-derived compounds p-menthane and 1,4-dimethylcyclooctane (DMCO), and octahydroindene (OHI)─ produced from woody biomass via catalytic fast pyrolysis. The combustion chemistry of the OHI and DMCO has not been previously studied. Experiments were conducted at 10 bar from 800 to 1200 K, equivalence ratios of 1.0 and 3.0, and residence times of 1.0 and 0.6 s, respectively. Experimentally detected species were used to elucidate the mechanisms of soot precursor formation. OHI exhibited the highest YSI (94.5) and formed a high concentration of benzene primarily by direct dehydrogenation of the six-membered ring. p-Menthane (YSI 92.0) and DMCO (YSI 85.0) oxidation products included fewer aromatic components but higher benzene precursors, including 1,3-butadiene, propyne, and allene. This suggests that the ring-opening pathway is dominant over the dehydrogenation pathway in the benzene formation for these compounds. This experimental speciation provides insight into the influence of the cycloalkane structure on the sooting tendencies of potential SAF blend components, thereby aiding in fuel design processes.

09 BIOMASS FUELS↗
DOE OSTI2021

Engineering Li/Na selectivity in 12-Crown-4–functionalized polymer membranes

Significance Lithium is a key ingredient in batteries, which are integral components of next-generation automobiles, airplanes, grid energy storage, and electronic devices. Unfortunately, lithium extraction from natural sources is laborious, slow, and costly, motivating the search for more efficient isolation techniques. While polymeric membranes could reduce the cost of lithium recovery, current membrane materials lack sufficient lithium-ion selectivity. To address this challenge, we introduce a class of polymeric membranes that incorporate ion binding sites, which significantly increases the transport selectivity of LiCl over NaCl. These studies provide guidelines and practical considerations for incorporating specific interactants into polymers that mediate selective ion transport.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Digital Twins for Data Centers

Fueled by an unprecedented adoption of AI (Artificial Intelligence), data centers are becoming the largest growing consumers of energy. Digital Twins provide living digital models of physical systems that enable data-driven analysis and application of AI to better manage selective aspects of the data center and drive efficiency for sustainability. Digital twins have emerged as a way to create virtual prototypes of physical artifacts, which may be used in a variety of contexts. Physical artifacts include airplanes, factories, or even static objects, such as bridges or dams. Digital twin helps monitor changes and assist in predicting planned or unplanned behaviors of physical objects. In this paper, we discuss digital twins for data centers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

A Fast VANET-Assisted Scheme for Event Data Recorders

An event data recorder (EDR) is a device installed in a vehicle to record information. Similar to a black box in an airplane, an EDR is used in the study of automobile accidents. Many schemes have been proposed that use vehicle network technology to help record EDR data, including schemes involving storing data on roadside units or nearby vehicles and schemes leveraging blockchain technology. However, these schemes do not take into account the vehicle company’s server; with the increased use of autonomous vehicles, the data related to these vehicles are always uploaded to the vehicle company’s server. In this scenario, we classify the situation into different cases, according to whether or not it is an emergency and whether the vehicle and the server are connected. For these cases, we propose a scheme whereby a vehicle uploads the EDR data to a cloud server and sends the evidence of storage to the nearby vehicle through a vehicular ad hoc network. Our scheme offers a fast response due to the use of symmetric cryptography algorithms while also considering security requirements.

Liu, Wei↗
DOE OSTI2022

Can we use antipredator behavior theory to predict wildlife responses to high-speed vehicles?

Animals seem to rely on antipredator behavior to avoid vehicle collisions. There is an extensive body of antipredator behavior theory that have been used to predict the distance/time animals should escape from predators. These models have also been used to guide empirical research on escape behavior from vehicles. However, little is known as to whether antipredator behavior models are appropriate to apply to an approaching high-speed vehicle scenario. We addressed this gap by (a) providing an overview of the main hypotheses and predictions of different antipredator behavior models via a literature review, (b) exploring whether these models can generate quantitative predictions on escape distance when parameterized with empirical data from the literature, and (c) evaluating their sensitivity to vehicle approach speed using a simulation approach wherein we assessed model performance based on changes in effect size with variations in the slope of the flight initiation distance (FID) vs. approach speed relationship. The slope of the FID vs. approach speed relationship was then related back to three different behavioral rules animals may rely on to avoid approaching threats: the spatial, temporal, or delayed margin of safety. We used literature on birds for goals (b) and (c). Our review considered the following eight models: the economic escape model, Blumstein’s economic escape model, the optimal escape model, the perceptual limit hypothesis, the visual cue model, the flush early and avoid the rush (FEAR) hypothesis, the looming stimulus hypothesis, and the Bayesian model of escape behavior. We were able to generate quantitative predictions about escape distance with the last five models. However, we were only able to assess sensitivity to vehicle approach speed for the last three models. The FEAR hypothesis is most sensitive to high-speed vehicles when the species follows the spatial (FID remains constant as speed increases) and the temporal margin of safety (FID increases with an increase in speed) rules of escape. The looming stimulus effect hypothesis reached small to intermediate levels of sensitivity to high-speed vehicles when a species follows the delayed margin of safety (FID decreases with an increase in speed). The Bayesian optimal escape model reached intermediate levels of sensitivity to approach speed across all escape rules (spatial, temporal, delayed margins of safety) but only for larger (> 1 kg) species, but was not sensitive to speed for smaller species. Overall, no single antipredator behavior model could characterize all different types of escape responses relative to vehicle approach speed but some models showed some levels of sensitivity for certain rules of escape behavior. We derive some applied applications of our findings by suggesting the estimation of critical vehicle approach speeds for managing populations that are especially susceptible to road mortality. Overall, we recommend that new escape behavior models specifically tailored to high-speeds vehicles should be developed to better predict quantitatively the responses of animals to an increase in the frequency of cars, airplanes, drones, etc. they will face in the next decade.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A Machine Learning Approach to the Detection of Ghosting Artifacts in Dark Energy Survey Images

Unwanted artifacts that often plague astronomical images arise from a number of sources that include imperfect optics, faulty image sensors, cosmic ray hits, and even airplanes and satellites. One major source that is dicult to avoid is known as ghosting, and is caused by the scattering and internal reflections of light o of the telescope’s mechanical and optical components. Detecting ghosting artifacts eciently in the large cosmological surveys that will acquire petabytes of data can be a daunting task. In this paper, we use data from the Dark Energy Survey to develop, train, and validate a machine learning model to detect ghosts based on convolutional neural networks. The model architecture and training procedure is discussed in detail, and the performance on the training and validation set presented. Testing is performed on data and results are compared with those from a ray-tracing algorithm. A proof-of-principle is demonstrated that shows promise for Stage IV surveys and beyond.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

A look back 75 years at Little Boy, the crew, the plane and the Lab’s first mission

Hours before the sun would rise over Tinian island on the morning of August 6, 1945, a B- 29 airplane was positioned above a specially built bomb-loading pit, as crews readied it with cargo unlike anything the world had ever known. Preparations on the tiny Pacific island—nearly 6,600 miles from Los Alamos and about 1,500 miles from its intended target in Japan—had begun months before on April 3. And months before that, pilot Paul Tibbets Jr. and his crew had practiced dropping dummy concrete bombs on targets in Utah. Even years before that, development of this cargo destined for Japan began in secrecy under the direction of a physicist and an Army general in the mountains of Northern New Mexico. It was all leading to one day that would help end years of bloodshed and change the world forever.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

Radiation Hardening – Test Capabilities (LANSCE) [Slides]

The Los Alamos Neutron Science Center (LANSCE) has exceptional facilities for research and testing of radiation effects in electronics. We have the best terrestrial neutron source for sea-level and airplane-altitude environments. We have a thermal neutron test capability at the Lujan Center and a proton beam test capability at the “Blue Room”. LANL has the programmatic mission to develop this radiation-effects program, namely space and satellite environments, high-performance computing (silent data corruption), and weapons delivery systems. We have a strong connection to industry which continues to grow.

42 ENGINEERING↗
DOE OSTI2021

Maximizing Solar and Transportation Synergies

This report considers the technological and market pathways that will enable better use of photovoltaic (PV) electricity as fuel for future transportation demand. Most of the pathways identified will require collaborative research and development (R&D) efforts to improve the capabilities of multiple technologies, including PV, energy storage, vehicles, electrolyzers, electrofuels, and infrastructure. For plug-in electric vehicles (PEVs), technologies that enable wide-scale managed and coordinated charging are among the highest priorities for continued research, development, and deployment in the near term. Furthermore, managed and coordinated charging capabilities are foundational for future vehicle-to-grid (V2G) functionality in the long term. For hydrogen fuel cell electric vehicles (FCEVs), the use of PV electricity for electrolysis provides an opportunity to increase PV deployment. For rail, air, and maritime transportation, the feasibility of increased PV use varies in the near term; opportunities for synergies with solar include the electrification of rail, increased reliability from airport microgrids, and switching from heavy fuel oil to clean maritime electrofuels made from PV-based hydrogen. Over the longer term, battery swap stations for electric airplanes and the co-location of solar with hydrogen fueling stations at shipping ports may enable greater synergies between PV and transportation.

14 SOLAR ENERGY↗
DOE OSTI2024

Field Emission Current Transfer for Homopolar Machines

With the increasing electrification of transportation, the need for high power density electric machines is higher than ever. The required specific power for the more demanding applications, such as airplane propulsion, is over 20 kW/kg for multi-megawatt range power levels. Fully superconducting synchronous machines could reach the required performance, but significant challenges remain to be addressed such as AC losses management and rotating cryogenics implementation. Homopolar machines constitute the simplest electro-mechanical conversion systems possible, however the difficulty of establishing reliable and efficient low voltage, high DC current transfer from a stationary to a rotating system has prevented homopolar machines from competing with AC electrical machines. While sliding contacts or liquid metal contacts are feasible, they lead to high losses, high maintenance requirements and the use of environmentally unfriendly materials. We investigated field emission current transfer as an alternative to sliding contacts. We have demonstrated field emission current transfer in vacuum between a copper electrode and carbon nanotubes and diamond pyramids to evaluate the feasibility of contact-free current transfer for homopolar machines. The initial field emission testing was successfully demonstrated with current densities in the 10 mA/cm 2 range. The initial experiments validated the concept and supported the development of a roadmap for the development of contactless current transfer for homopolar machines, helped understand the limitations of the current test system and identify the key parameters that will lead to better performance.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

A Review of Parameter Ranges for Uncertainty Estimation for Decomposing Carbon Fiber Epoxy Composites

Carbon fiber epoxy composites are increasingly used in systems requiring a material that is both strong and light weight, as in airplanes, cars, and pressure vessels. In fire environments, carbon fiber epoxy composites are a fuel source subject to oxidation. This literature review seeks to provide material properties as well as uncertainty bounds for those properties for computational models of decomposing carbon fiber epoxy composites. The goal is to guide analysts when measurements are lacking and increase credibility of uncertainty quantification ranges.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Measurements of TRACER pre-convective conditions and mesoscale circulations using small unmanned aircraft systems (sUAS)

Improved comprehension of the physical processes governing convective cloud formation and lifecycle are of critical importance for understanding and predicting future climate states. The influence of these clouds on the planetary energy budget, including on precipitation, is significant. Things are particularly complex in coastal regimes, where gradients in aerosol particle properties, localized circulations such as sea breezes, and large population centers are found. To date, numerical models struggle to accurately represent these critical clouds and are therefore challenged to provide a realistic view on the planetary energy budget. Through the proposed research, we deployed two uncrewed aircraft systems (UAS) equipped with a variety of instruments alongside sensors deployed by the US Department of Energy Atmospheric Radiation Measurement (ARM) program for the TRACER (Tracking Aerosol Convection Interactions Experiment) field campaign. The two small UAS platforms consisted of a CU RAAVEN fixed-wing airplane and an OU CopterSonde system, with the copter collecting frequent vertical profiles of thermodynamic and kinematic variables such as temperature, pressure, wind and humidity. At the same time, the fixed-wing captured horizontal gradients of these quantities and aerosol size distribution. These systems were deployed south of the Houston metro area, in an area that is impacted by the Gulf of Mexico sea breeze on a daily basis. These observations offer enhanced and complementary perspectives to those provided by the DOE ARM Mobile Facility (AMF) which is was deployed in southeast Houston, and an ancillary site in a more rural location west of the urban Houston area. Quality-controlled versions of the UAS data were collected and posted on the DOE ARM data archive after the conclusion of the campaign where they are accessible by the research community and general public. The UAS perspective offers revolutionary insight into key spatial and temporal effects that have not been evaluated previously.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Energy Impacts of Electric Aircraft: An Overview

Commercial aviation represents approximately 2% of the global emissions of greenhouse gases, yet presently relies exclusively on fossil fuels as a source of energy. This paper evaluates to what extent an all-electric aircraft can provide an alternative. First, three classes of aircraft are modeled at various timelines in the future: 50/100/150 passenger capacity in 2030/2040/2050. Technology is assumed to improve over time, especially with regards to battery specific energy, resulting in aircraft with increased range. A database of all domestic flights in the US in 2019 is then used to filter and aggregate flights suited for replacement by electric aircraft. In the short term (2030), no viable aircraft can meet the requirements of each class. By 2040, a third of the flights can be done by an all-electric aircraft, but only short ones, as the range does not exceed 500 mi, resulting in 3% of total passenger-miles. By 2050, owing to the most optimistic technology assumptions, a quarter of all passenger-miles can be flown by electric airplanes. The resulting displaced jet fuel is also calculated.

Aviation sustainability↗
DOE OSTI2020

Fast Evaluation of Aircraft Icing Severity Using Machine Learning Based on XGBoost

Aircraft icing represents a serious hazard in aviation which has caused a number of fatal accidents over the years. In addition, it can lead to substantial increase in drag and weight, thus reducing the aerodynamics performance of the airplane. The process of ice accretion on a solid surface is a complex interaction of aerodynamic and environmental variables. The complex relationship makes machine learning-based methods an attractive alternative to traditional numerical simulation-based approaches. In this study, we introduce a purely data-driven approach to find the complex pattern between different flight conditions and aircraft icing severity prediction. The supervised learning algorithm Extreme Gradient Boosting (XGBoost) is applied to establish the prediction framework which makes prediction based on any set of observations. The input flight conditions for the proposed prediction framework are liquid water content, droplet diameter and exposure time. The proposed approach is demonstrated in three cases: maximum ice thickness prediction, icing area prediction and icing severity level evaluation. Performance comparison studies and error analysis are also conducted to verify the effectiveness and performance of the proposed method. Results show that the proposed method has reasonable capability in evaluating aircraft icing severity.

Li, Sibo (ORCID:000000021705844X)↗