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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Predictability and empirical dynamics of fisheries time series in the North Pacific

Previous studies have documented a strong relationship between marine ecosystems and large-scale modes of sea surface height (SSH) and sea surface temperature (SST) variability in the North Pacific such as the Pacific Decadal Oscillation and the North Pacific Gyre Oscillation. In the central and western North Pacific along the Kuroshio-Oyashio Extension (KOE), the expression of these modes in SSH and SST is linked to the propagation of long oceanic Rossby waves, which extend the predictability of the climate system to ~3 years. Using a multivariate physical-biological linear inverse model (LIM) we explore the extent to which this physical predictability leads to multi-year prediction of dominant fishery indicators inferred from three datasets (i.e., estimated biomasses, landings, and catches). We find that despite the strong autocorrelation in the fish indicators, the LIM adds dynamical forecast skill beyond persistence up to 5-6 years. By performing a sensitivity analysis of the LIM forecast model, we find that two main factors are essential for extending the dynamical predictability of the fishery indicators beyond persistence. The first is the interaction of the fishery indicators with the SST/SSH of the North and tropical Pacific. The second is the empirical relationship among the fisheries time series. This latter component reflects stock-stock interactions as well as common technological and human socioeconomic factors that may influence multiple fisheries and are captured in the training of the LIM. These results suggest that empirical dynamical models and machine learning algorithms, such as the LIM, provide an alternative and promising approach for forecasting key ecological indicators beyond the skill of persistence.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2021

Detection and Tracking of Aircraft in the Far-Field from Small Unmanned Aerial Systems

Onboard far-field aircraft detection is needed for safe non-cooperative traffic mitigation in autonomous small Unmanned Aerial System (sUAS) operations. Machine vision systems, based on standard optics and visible light detectors, possess the ideal size, weight, and power (SWaP) requirements for sUAS. This work presents the design and analysis of a novel aircraft detection and tracking pipeline based on optical sensing alone. Key contributions of the work include a refined range inequality model based on sensing and detection with FAA well-clear separation assurance distances between aircraft in mind, a detector fusion method to maximize the benefit of two image detectors, and a comparative analysis of Linear Kalman-filtering and Extended Kalman-filtering to seek optimal tracking performance. The pipeline is evaluated offline against multiple intruder platforms, using two types of flight encounters: multirotor sUAS vs. fixed-wing sUAS and multirotor sUAS vs. general aviation(GA)plane. Analysis is restricted to the rate-limiting head-on and departing collision volume cases vertically separated for safety. Results indicate that it is feasible to use the proposed optical spatial-temporal tracking algorithm to provide adequate alerting time to prevent penetration of well-clear separation volumes for both sUAS and GA aircraft.

Unmanned Aerial System↗
DOE OSTI2021

Evaluation and modification of ELM seasonal deciduous phenology against observations in a southern boreal peatland forest

Phenological transitions determine the timing of changes in land surface properties and the seasonality of exchanges of biosphere-atmosphere energy, water, and carbon. Accurate mechanistic modeling of phenological processes is therefore critical to understand and correctly predict terrestrial ecosystem feedbacks with changing atmospheric and climate conditions. However, the phenological components in the land model of the US Department of Energy's (DOE) Energy Exascale Earth System Model (ELM of E3SM) were previously unable to accurately capture the observed phenological responses to environmental conditions in a well-studied boreal peatland forest. In this research, we introduced new seasonal-deciduous phenology schemes into version 1.0 of ELM and evaluated their performance against the PhenoCam observations at the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment in northern Minnesota from 2015 to 2018. We found that phenology simulated by the revised ELM (i.e., earlier spring onsets and stronger warming responses of spring onsets and autumn senescence) was closer to observations than simulations from the original algorithms for both the deciduous conifer (Larix laricina) and mixed shrub layers. Moreover, the revised ELM generally produced higher carbon and water fluxes (e.g., photosynthesis and evapotranspiration) during the growing season and stronger flux responses to warming than the default ELM. A parameter sensitivity analysis further indicated the significant contribution of phenology parameters to uncertainty in key carbon and water cycle variables, underscoring the importance of precise phenology parameterization. Furthermore, this phenological modeling effort demonstrates the potential to enhance the E3SM representation of land-climate interactions at broader spatiotemporal scales, especially under anticipated elevated CO 2 and warming conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Chlorophyll- a dynamics in the lower Amazon River: insights from in situ and hyperspectral remote sensing using OCI-PACE

Chlorophyll-a concentration (Chla) is a key indicator of phytoplankton biomass and aquatic trophic status. However, satellite-derived Chla in sediment-rich waters, such as those found in the Lower Amazon River, remains challenging. The present study characterizes in situ Chla levels and their relationships with geographic, physical, and biogeochemical parameters in the Lower Amazon. Data collected between 2014 and 2017 across four hydrological seasons included measurements of Chla, remote sensing reflectance, and water quality parameters such as total suspended sediment, conductivity, water surface temperature, dissolved oxygen, pH, dissolved organic carbon and coloured dissolved organic matter. An empirical model was developed to estimate Chla using simulated hyperspectral bands from NASA’s PACE mission, achieving high performance (R 2 = 0.76; RMSE = 0.11 μg·L −1 ). Red bands proved particularly effective for Chla retrieval, while the addition of ultraviolet bands further enhanced model accuracy. The application of the developed model to satellite imagery yielded results consistent with in situ observations for the same hydrologic season. Seasonal variation and geographic location were major factors influencing Chla dynamics. This study provides a novel contribution to Chla estimation in optically complex, highly turbid waters and highlights the potential of the PACE mission to enhance global aquatic ecosystem monitoring. In conclusion, by offering freely available hyperspectral data with high radiometric resolution, PACE represents a significant advancement in the realm of remote sensing of aquatic environments.

Amazon River↗
NASA NTRS2018

Modeling-Driven Damage Tolerant Design of Graphene Nanoplatelet/Carbon Fiber/Epoxy Hybrid Composite Panels for Full-Scale Aerospace Structures

The objective of this study is to design a new nano graphenecarbon fiberpolymer hybrid composite that can be used for the NASA SLS Composite Exploration Upper Stage (CEUS) forward skirt structure. The new material will improve the resistance to open-hole compression failure of the structure relative to traditional polymer fiber composites. The material is designed rapidly and with little cost using the Integrated Computational Materials Engineering (ICME) approach. Multiscale modeling and experiments are used to synergistically optimize the material design to yield improved properties and performance by controlling key processing parameters for manufacturing nano-enhanced materials. Specifically, the nanocomposite panel showed a 22 reduction in mass relative to the traditional composite panel, while both designs are equal in terms of ease of manufacture. This potential mass savings corresponds to an estimated 45 savings in materials and manufacturing costs. The multiscale ICME workflow developed for this project can be readily applied to the development of nano-enhanced composite materials and large aerospace structures. In addition, all key aspects of ICME were employed to complete this project including multiscale modeling, experimental characterization and visualization, data management, visualization, error and uncertainty quantification, and education. The results presented herein indicate a dramatic level of success, as well as the power and potential of ICME approach and multiscale modeling for composite materials.

computational mechanics↗
DOE OSTI2022

Toward Rational Design of Supported Vanadia Catalysts of Lignin Conversion to Phenol

In sustainable chemical engineering, catalytic upgrading of lignocellulosic biomass has recently gained attention for producing renewable platform chemicals. To achieve maximal biomass utilization, upgrading the underutilized lignin components is essential. Among various catalysts for lignin upgrading, supported vanadia (V2O5) catalysts are promising because of their cost-effectiveness and tunability of either dopant metals or catalyst supports. Here, computational studies are conducted to derive rational design guidelines of supported V2O5 catalysts for accomplishing the high catalytic activity of lignin upgrading to phenol, a key compound for producing bioplastics and biofuel blendstocks. Guaiacol was used as the model compound since it comprises the highest portion of depolymerized lignin. Computational mechanistic studies for the catalytic guaiacol conversion to phenol were performed for the V2O5 catalysts on Titania (TiO2) and silica (SiO2) to explain higher experimental phenol yields on V2O5/SiO2 than V2O5/TiO2. The hydrogen migration from the methoxy group to the aryl ring was identified as a rate-determining step, and the overall activation energies on the two catalysts were compared. A structural analysis was carried out for the catalysts and rate-determining transition states to gain further insights from mechanistic studies. It was concluded that the tilt angle of the aryl group in the hydrogen migration transition state is a key descriptor determining the catalytic activity of phenol formation. These features correlate well with activation energies and experimental phenol yields, indicating that they provide design guidelines for supported metal catalysts for lignin upgrading before experiments.

BIOMASS FUELS,INORGANIC, ORGANIC, PHYSICAL, AND AN↗
DOE OSTI2021

Structure and reactive properties of Nb-impregnated two-dimensional pillared MWW zeolites for total oxidation of volatile organic compounds

In this work, the structure and reactive properties of niobium (Nb)-impregnated MWW-type materials were evaluated for gas-phase total oxidation of volatile organic compounds, including BTX (benzene, toluene and o -xylene). The role of the type of structure (two or three-dimensional) and the loading of Nb were considered. The results indicated most Nb species with a tetrahedral coordination on the external surfaces of both two- and three-dimensional zeolites, together with a minimal contribution of octahedral extra-framework Nb 2 O 5 species. The texture and Nb content played a key role in the gas-phase total oxidation of BTX. With the same Nb content (5 wt%), the pillared zeolite exhibited a higher specific surface, larger pore volume and mesopores between the MWW nanosheets when compared to the MCM-22 zeolites, which resulted in high accessibility of the reactant molecules to the active sites, reflected in higher BTX conversion at lower and higher temperatures (50–300 °C). The best performance was achieved with the pillared zeolite (10 wt% Nb), reaching a BTX conversion at 300 °C of 92%, 69% and 58%, respectively. Here, the catalyst was stable for up to 30 h of reaction.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Borgs are giant genetic elements with potential to expand metabolic capacity

Anaerobic methane oxidation exerts a key control on greenhouse gas emissions1, yet factors that modulate the activity of microorganisms performing this function remain poorly understood. Here we discovered extraordinarily large, diverse DNA sequences that primarily encode hypothetical proteins through studying groundwater, sediments and wetland soil where methane production and oxidation occur. Four curated, complete genomes are linear, up to approximately 1 Mb in length and share genome organization, including replichore structure, long inverted terminal repeats and genome-wide unique perfect tandem direct repeats that are intergenic or generate amino acid repeats. We infer that these are highly divergent archaeal extrachromosomal elements with a distinct evolutionary origin. Gene sequence similarity, phylogeny and local divergence of sequence composition indicate that many of their genes were assimilated from methane-oxidizing Methanoperedens archaea. We refer to these elements as ‘Borgs’. We identified at least 19 different Borg types coexisting with Methanoperedens spp. in four distinct ecosystems. Borgs provide methane-oxidizing Methanoperedens archaea access to genes encoding proteins involved in redox reactions and energy conservation (for example, clusters of multihaem cytochromes and methyl coenzyme M reductase). These data suggest that Borgs might have previously unrecognized roles in the metabolism of this group of archaea, which are known to modulate greenhouse gas emissions, but further studies are now needed to establish their functional relevance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Magnetism and spin dynamics in room-temperature van der Waals magnet Fe 5 GeTe 2

Two-dimensional van der Waals (vdWs) materials have gathered a lot of attention recently. However, the majority of these materials have Curie temperatures that are well below room temperature, making it challenging to incorporate them into device applications. In this work, we synthesized a room-temperature vdW magnetic crystal Fe 5 GeTe 2 with a Curie temperature T c = 332 K, and studied its magnetic properties by vibrating sample magnetometry (VSM) and broadband ferromagnetic resonance (FMR) spectroscopy. The experiments were performed with external magnetic fields applied along the c -axis (H∥ c ) and the ab -plane (H∥ ab ), with temperatures ranging from 300 to 10 K. We have found a sizable Landé g -factor difference between the H∥ c and H∥ ab cases. In both cases, the Landé g -factor values deviated from g = 2. This indicates contribution of orbital angular momentum to the magnetic moment. The FMR measurements reveal that Fe 5 GeTe 2 has a damping constant comparable to Permalloy. With reducing temperature, the linewidth was broadened. Together with the VSM data, our measurements indicate that Fe 5 GeTe 2 transitions from ferromagnetic to ferrimagnetic at lower temperatures. Our experiments highlight key information regarding the magnetic state and spin scattering processes in Fe 5 GeTe 2 , which promote the understanding of magnetism in Fe 5 GeTe 2 , leading to implementations of Fe 5 GeTe 2 based room-temperature spintronic devices.

36 MATERIALS SCIENCE↗
NASA NTRS2002

Liquid Engine Test Facilities Assessment

The John C. Stennis Space Center (SSC) requested The Aerospace Corporation to examine the current testing capability of all existing large liquid engine test facilities located in the United States. That information along with projected liquid rocket engine development was used to examine future liquid rocket engine testing facilities needs in the coming decade. Current domestic liquid engine test facilities capabilities, when examined against engine concepts for the coming decade, indicate there are ample facilities offering altitude simulation during test. In addition, it was observed that many contractor facilities have limited ambient test capability of larger thrust engines under current consideration. Finally, it was concluded that diminished contractor participation engine development testing will drive this activity to the government sector. Only three facilities are seen as key contributors to engine testing in the coming decade, namely John C. Stennis Space Center (SSC), Marshall Space Flight Center (MSFC), and Air Force Research Laboratory (AFRL). Past rocket engine test experience was evaluated as a possible resource for projecting future engine test needs. A database comprised of various engine models and the level of testing performed to flight qualify those systems for their first flight was constructed. For comparison purposes in this study, development and qualification efforts were totaled and treated as one test program. Based on experience with past Air Force programs, the time on the test stand accounts for typically 50% or more of the total program time. Historical data show that the time to design and develop new engines has increased over the last 40 years, most likely due to scarcer resources in today's funding environment.

Adams, Michael J.↗
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↗
DOE OSTI2024

Spectroscopic Insight on Neodymium Solvation in Lithium Borohydride-Supported Electrolyte

Borohydride-based electrolytes have recently emerged as promising media for the electrodeposition of electropositive metals, including rare earth (RE) elements. While the presence of supporting alkali metal cations and RE counteranions provides essential electrochemical conductivity for achieving fast metal electrodeposition, interactions between the host ligand and solvated neodymium (Nd) complexes remain unclear. This study provides insights into the coordination structure of a concentrated and directly solvated Nd salt in a lithium borohydride-supported electrolyte. Our spectroscopic results indicate that the RE coordination environment is significantly influenced by the solvation mechanism, which can vary between metathesis and complexation pathways, primarily dictated by stoichiometric factors. Under dilute conditions, nearly complete metathesis of anions leads to a high coordination number for the host ligand (borohydride), consistent with the previously reported solvated Nd speciation in chlorine-free electrolytes. In contrast, concentrated dissolution of the Nd salt in the supported electrolyte is dominated by a complexation pathway featuring a Li-ion-paired complex with a low coordination number of the host ligand. Density functional theory (DFT) calculations indicated that the observed blue shift in the borohydride vibration was the result of an increase in electron density drawn into the terminal B–H interbond region from the hydride as the coordination changed from Li to Nd. In conjunction with DFT results, vibrational analyses allowed correlation of the experimental shifts associated with changes in Nd ligation and coordination spheres, further consolidating the prevalence of highly chloride-coordinated species under concentrated conditions. In conclusion, the outcomes of this work illuminate the distinctive and heterogeneous coordination structures that the electroactive RE species can adopt at high concentrations in lithium borohydride-supported electrolytes, as a key step to comprehend the reported metal electrodeposition performance in these media.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Hybrid Integration of GaP Photonic Crystal Cavities with Silicon-Vacancy Centers in Diamond by Stamp-Transfer

Optically addressable solid-state defects are emerging as some of the most promising qubit platforms for quantum networks. Maximizing photon-defect interaction by nanophotonic cavity coupling is key to network efficiency. We demonstrate fabrication of gallium phosphide 1-D photonic crystal waveguide cavities on a silicon oxide carrier and subsequent integration with implanted silicon-vacancy (SiV) centers in diamond using a stamp-transfer technique. The stamping process avoids diamond etching and allows fine-tuning of the cavities prior to integration. After transfer to diamond, we measure cavity quality factors (Q) of up to 8900 and perform resonant excitation of single SiV centers coupled to these cavities. For a cavity with a Q of 4100, we observe a 3-fold lifetime reduction on-resonance, corresponding to a maximum potential cooperativity of C = 2. In conclusion, these results indicate promise for high photon-defect interaction in a platform which avoids fabrication of the quantum defect host crystal.

Purcell enhancement↗
DOE OSTI2023

Capacitive Deionization for the Extraction and Recovery of Butyrate

Separation processes underpin chemical manufacturing, energy and fuel production, resource recovery, and water purification. Capacitive deionization (CDI) is an electrochemical separation technique based on electrosorption of charged species from an aqueous solution. This work reports the development and application of CDI for the extraction and recovery of butyrate, a carboxylate anion that is key to bioenergy production, among other applications. Electrosorption of sodium butyrate was evaluated using a bench-scale CDI system with activated carbon cloth electrodes. Applying an external potential (1.2 V) enhanced the adsorption capacity of activated carbon for butyrate by 250%. Reversible electrosorption was also demonstrated by extracting and recovering butyrate at 1.2 and 0 V, respectively. Performance metrics including butyrate adsorption and desorption capacities, adsorption and desorption rates, charge efficiency, energy consumption, and recovery are reported. Furthermore, this study also investigates the long-term operational stability of the system by cycling the cell more than 1000 times using 1.2 and 0 V for charging and discharging, respectively. Subsequent physicochemical characterization indicates increased oxygen content (from similar to 2% to >8%), decreased specific surface area (by similar to 20%), and decreased pore volume (by similar to 20%), attributed to carbon oxidation. Overall, this work informs the design of CDI for organic anion separation and recovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Medium-duty Urban Range Extended Connected Powertrain (Final Scientific Technical Report)

The project goal is to develop and demonstrate a Class 4 delivery vehicle that reduces fuel consumption by 50% or more when compared to an equivalent vehicle with a conventional internal combustion engine (ICE) powertrain driven on a comparable duty cycle. This shall be achieved using a plug-in hybrid electric (PHEV) configuration that optimizes the efficiency of the ICE. The proposed solution aims to be commercially viable for fleets to procure the system without additional incentives. To accomplish this, commercialized light-duty vehicle electric drive components shall be used. A PHEV configuration for Class 4 MD/HD vocational vehicles using commercialized light-duty vehicle electric drive components will require the development of a new topology for the hybrid powertrain applicable to medium-duty vehicles. Prior research indicates that an identified novel power split device could provide a fuel economy improvement potential of up to 51%. Utilizing an advanced battery management algorithm that will allow operation closer to the battery limits, the project will minimize battery capacity to achieve the desired performance results while maintaining the cost target for high commercialization. The solution must be cost effective to purchase and integrate into a Class 4 delivery vehicle, deliver the intended fuel economy improvement, and perform as well, or better, than the current conventional ICE powertrain. MD/HD vehicles typically require higher power, which is one factor that results in high costs for the powerful electric machines typical in larger HEV/PHEV systems. A key element in the project is the use of commercially available Bosch electric drive components (e.g., motors, batteries, and power electronics) from the larger passenger vehicle segment. This leverages the economies of scale to decrease cost and improve reliability beyond current purpose-built low-volume commercial vehicle components. These innovations will result in a game-changing PHEV system that meets DOE’s 50% fuel consumption reduction target, grants the vehicle an uncompromised driving range, and achieves the cost point for widespread adoption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRSDate not supplied

Communicating Metrics of Land Surface Temperature Variability Using Multi-sensor Machine Learning

Land surface temperature (LST) is a key climate observable used to detect changes in the Earth’s surface energy budget that influence carbon and water cycles. Land surface temperature exhibits strong diurnal variability, which geostationary satellites can observe at scale thanks to their temporal resolution. Due to anthropogenic climate and land use changes, the surface energy balance has been considerably modified and may be described by changes in diurnal temperature range and extremes. Using high performance computing and datasets from the NASA Earth Exchange, we exploit co-located, co-temporal observations from low-earth orbit (LEO) and geostationary (GEO) sensors to develop a deep learning-based method for LEO-to-GEO algorithm emulation. Our model is trained to predict MODIS Terra LST from GOES-16 thermal bands and achieves validation error <2K. Application of the model to unseen times of day (observed by MODIS Aqua) and a new GEO sensor (Himawari-8) observing an unseen spatial domain, demonstrate the generalization of the deep learning model across space, time and spectra. Further, time series clustering approaches are examined with the objective of identifying key indicators of change in diurnal cycling and extremes on a continental scale. Communicating LST variability observed by geostationary satellites can have impacts in multiple disciplines, from understanding of snow, vegetation and soil dynamics, to recognizing trends in heat events relevant to human health.

Kate Duffy↗
NASA NTRSDate not supplied

OCI Geolocation Evaluation and Refinement Using Landsat Control Points

The Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission is NASA’s next investment in ocean biology, clouds, and aerosol data records. A key feature of PACE is the inclusion of an advanced satellite radiometer, Ocean Color Instrument (OCI), a global mapping radiometer that combines multispectral and hyperspectral remote sensing. The geolocation processing is performed for OCI using spacecraft navigation data and an instrument geometry model. To evaluate the geolocation accuracy for OCI and develop refinements to the processing methods, control point matching using Landsat data has been implemented as a step in the operational processing of OCI data at the Science Data Segment. This processing provides between 200 and 300 high-quality matchups per day with good global and geometric distribution, allowing rapid evaluation of the OCI geolocation accuracy. The results provided an early indication of the overall quality of the geolocation processing and of specific aspects needing improvement. A standard set of granules was identified to support rapid implementation and testing of geolocation refinements, and this approach has been highly successful in improving the geolocation processing accuracy to meet the science requirements. The evaluation will continue throughout the mission to ensure the ongoing accuracy of geolocation. This paper describes the control point matching methodology, the approach to development of the geolocation processing refinements, and the recent results.

PACE↗