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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Multi-Objective Reinforcement Learning-Based Deep Neural Networks for Cognitive Space Communications

Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through virtual environment exploration. Improvements in the multiobjective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located onboard the International Space Station.

space archtiecture↗
NASA NTRS2017

Multi-Objective Reinforcement Learning-based Deep Neural Networks for Cognitive Space Communications

Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through virtual environment exploration. Improvements in the multiobjective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located onboard the International Space Station.

space archtiecture↗
DOE OSTI2024

Novel candidate taxa contribute to key metabolic processes in Fennoscandian Shield deep groundwaters

The continental deep biosphere contains a vast reservoir of microorganisms, although a large proportion of its diversity remains both uncultured and undescribed. In this study, the metabolic potential (metagenomes) and activity (metatranscriptomes) of the microbial communities in Fennoscandian Shield deep subsurface groundwaters were characterized with a focus on novel taxa. DNA sequencing generated 1270 de-replicated metagenome-assembled genomes and single-amplified genomes, containing 7 novel classes, 34 orders, and 72 families. The majority of novel taxa were affiliated with Patescibacteria, whereas among novel archaea taxa, Thermoproteota and Nanoarchaeota representatives dominated. Metatranscriptomes revealed that 30 of the 112 novel taxa at the class, order, and family levels were active in at least one investigated groundwater sample, implying that novel taxa represent a partially active but hitherto uncharacterized deep biosphere component. The novel taxa genomes coded for carbon fixation predominantly via the Wood–Ljungdahl pathway, nitrogen fixation, sulfur plus hydrogen oxidation, and fermentative pathways, including acetogenesis. These metabolic processes contributed significantly to the total community’s capacity, with up to 9.9% of fermentation, 6.4% of the Wood–Ljungdahl pathway, 6.8% of sulfur plus 8.6% of hydrogen oxidation, and energy conservation via nitrate (4.4%) and sulfate (6.0%) reduction. Key novel taxa included the UBA9089 phylum, with representatives having a prominent role in carbon fixation, nitrate and sulfate reduction, and organic and inorganic electron donor oxidation. These data provided insights into deep biosphere microbial diversity and their contribution to nutrient and energy cycling in this ecosystem.

Candidatus↗
DOE OSTI2017

Rapid Response of Eastern Mediterranean Deep Sea Microbial Communities to Oil

Deep marine oil spills like the Deepwater Horizon (DWH) in the Gulf of Mexico have the potential to drastically impact marine systems. Crude oil contamination in marine systems remains a concern, especially for countries around the Mediterranean Sea with off shore oil production. The goal of this study was to investigate the response of indigenous microbial communities to crude oil in the deep Eastern Mediterranean Sea (E. Med.) water column and to minimize potential bias associated with storage and shifts in microbial community structure from sample storage. 16S rRNA amplicon sequencing was combined with GeoChip metagenomic analysis to monitor the microbial community changes to the crude oil and dispersant in on-ship microcosms set up immediately after water collection. After 3 days of incubation at 14 °C, the microbial communities from two different water depths: 824 m and 1210 m became dominated by well-known oil degrading bacteria. The archaeal population and the overall microbial community diversity drastically decreased. Similarly, GeoChip metagenomic analysis revealed a tremendous enrichment of genes related to oil biodegradation, which was consistent with the results from the DWH oil spill. Furthermore, these results highlight a rapid microbial adaption to oil contamination in the deep E. Med., and indicate strong oil biodegradation potential.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2011

Initial Characterization of Optical Communications with Disruption-Tolerant Network Protocols

Disruption-tolerant networks (DTNs) are groups of network assets connected with a suite of communication protocol technologies designed to mitigate the effects of link delay and disruption. Application of DTN protocols to diverse groups of network resources in multiple sub-networks results in an overlay network-of-networks with autonomous data routing capability. In space environments where delay or disruption is expected, performance of this type of architecture (such as an interplanetary internet) can increase with the inclusion of new communications mediums and techniques. Space-based optical communication links are therefore an excellent building block of space DTN architectures. When compared to traditional radio frequency (RF) communications, optical systems can provide extremely power-efficient and high bandwidth links bridging sub-networks. Because optical links are more susceptible to link disruption and experience the same light-speed delays as RF, optical-enabled DTN architectures can lessen potential drawbacks and maintain the benefits of autonomous optical communications over deep space distances. These environment-driven expectations - link delay and interruption, along with asymmetric data rates - are the purpose of the proof-of-concept experiment outlined herein. In recognizing the potential of these two technologies, we report an initial experiment and characterization of the performance of a DTN-enabled space optical link. The experiment design employs a point-to-point free-space optical link configured to have asymmetric bandwidth. This link connects two networked systems running a DTN protocol implementation designed and written at JPL for use on spacecraft, and further configured for higher bandwidth performance. Comparing baseline data transmission metrics with and without periodic optical link interruptions, the experiment confirmed the DTN protocols' ability to handle real-world unexpected link outages while maintaining capability of reliably delivering data at relatively high rates. Finally, performance characterizations from this data suggest performance optimizations to configuration and protocols for future optical-specific DTN space link scenarios.

Space networking↗
DOE OSTI2017

The Abundance of Atmospheric CO{sub 2} in Ocean Exoplanets: a Novel CO{sub 2} Deposition Mechanism

We consider super-Earth sized planets which have a water mass fraction large enough to form an external mantle composed of high-pressure water-ice polymorphs and also lack a substantial H/He atmosphere. We consider such planets in their habitable zone, so that their outermost condensed mantle is a global, deep, liquid ocean. For these ocean planets, we investigate potential internal reservoirs of CO{sub 2}, the amount of CO{sub 2} dissolved in the ocean for the various saturation conditions encountered, and the ocean-atmosphere exchange flux of CO{sub 2}. We find that, in a steady state, the abundance of CO{sub 2} in the atmosphere has two possible states. When wind-driven circulation is the dominant CO{sub 2} exchange mechanism, an atmosphere of tens of bars of CO{sub 2} results, where the exact value depends on the subtropical ocean surface temperature and the deep ocean temperature. When sea-ice formation, acting on these planets as a CO{sub 2} deposition mechanism, is the dominant exchange mechanism, an atmosphere of a few bars of CO{sub 2} is established. The exact value depends on the subpolar surface temperature. Our results suggest the possibility of a negative feedback mechanism, unique to water planets, where a reduction in the subpolar temperature drives more CO{sub 2} into the atmosphere to increase the greenhouse effect.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

DeepZipper: A Novel Deep-learning Architecture for Lensed Supernovae Identification

Large-scale astronomical surveys have the potential to capture data on large numbers of strongly gravitationally lensed supernovae (LSNe). To facilitate timely analysis and spectroscopic follow-up before the supernova fades, an LSN needs to be identified soon after it begins. To quickly identify LSNe in optical survey data sets, we designed ZipperNet, a multibranch deep neural network that combines convolutional layers (traditionally used for images) with long short-term memory layers (traditionally used for time series). We tested ZipperNet on the task of classifying objects from four categories—no lens, galaxy-galaxy lens, lensed Type-Ia supernova, lensed core-collapse supernova—within high-fidelity simulations of three cosmic survey data sets: the Dark Energy Survey, Rubin Observatory’s Legacy Survey of Space and Time (LSST), and a Dark Energy Spectroscopic Instrument (DESI) imaging survey. Among our results, we find that for the LSST-like data set, ZipperNet classifies LSNe with a receiver operating characteristic area under the curve of 0.97, predicts the spectroscopic type of the lensed supernovae with 79% accuracy, and demonstrates similarly high performance for LSNe 1–2 epochs after first detection. We anticipate that a model like ZipperNet, which simultaneously incorporates spatial and temporal information, can play a significant role in the rapid identification of lensed transient systems in cosmic survey experiments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1984

Radio interferometric determination of intercontinental baselines and earth orientation utilizing deep space network antennas - 1971 to 1980

Progress has been made toward the realization of the potential of radio interferometry for measuring crustal motions and global rotations of the earth with accuracies at the centimeter level. In this connection, a series of experiments, primarily with NASA's Deep Space Network (DSN) antennas, has been conducted to develop two generations of very long baseline interferometric (VLBI) systems. A description is presented of the employed techniques, an analysis of the experiments, and the results of geophysical significance. Attention is given to the interferometry technique, the geometric delay model, propagation media calibrations, and the observing strategy.

Sovers, O. J.↗
DOE OSTI2023

Deep anoxic aquifers could act as sinks for uranium through microbial-assisted mineral trapping

Uptake of uranium (U) by secondary minerals, such as carbonates and iron (Fe)-sulfides, that occur ubiquitously on Earth, may be substantial in deep anoxic environments compared to surficial settings due to different environment-specific conditions. Yet, knowledge of U reductive removal pathways and related fractionation between 238 U and 235 U isotopes in deep anoxic groundwater systems remain elusive. Here we show bacteria-driven degradation of organic constituents that influences formation of sulfidic species facilitating reduction of geochemically mobile U(VI) with subsequent trapping of U(IV) by calcite and Fe-sulfides. The isotopic signatures recorded for U and Ca in fracture water and calcite samples provide additional insights on U(VI) reduction behaviour and calcite growth rate. The removal efficiency of U from groundwater reaching 75% in borehole sections in fractured granite, and selective U accumulation in secondary minerals in exceedingly U-deficient groundwater shows the potential of these widespread mineralogical sinks for U in deep anoxic environments.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Earth Source Heat: A Cascaded Systems Approach to DDU of Geothermal Energy on the Cornell Campus

This report documents the completion of the DOE study DE-EE0008103: Earth Source Heat: A Cascaded Systems Approach to DDU of Geothermal Energy on the Cornell Campus. This study involved a comprehensive evaluation of the potential for Earth Source Heat (ESH), Cornell’s specific application of Deep Direct Use (DDU) geothermal energy, to create a viable renewable source of thermal energy for its Ithaca, NY campus district heating system. The study included stochastic modeling that married each of two potential subsurface resources (two specific geological reservoirs) to documented campus heating operations based on hourly campus heating profiles and proposed integrated equipment controls (variable speed pumps and heat pumps). The outputs of the subsurface modeling were used as inputs for a Cornell-developed surface heat use Excel-based modeling program (the program was named “Modeled ENergy Use”, or “MEnU”). This allowed Cornell to compute realistic annual totals of extractable and useable heat for the campus, including details like heat losses, minimum summer demand, and controllable building temperature settings. The Cornell team then evaluated the costs and benefits of each modeled scenario. The primary evaluation was a standard “single bottom line” economic calculation for the Levelized Cost of Heat (LCOH). This represents the annualized cost (per unit heat) for Cornell. Additional valuations were also computed based on the benefit to the environment and to the regional economy (i.e., economic benefits external to campus). The results of this study demonstrate that if suitable reservoir flow can be attained, Earth Source Heat would be a viable technology to supply Cornell’s district heating system. This viability is based on the following criteria: (1) The modeled system produced a total useable heat output that exceeded the minimum annual campus heat load determined at the onset of the project (i.e., offsetting at least 20% of the annual campus thermal load). The output range is substantial depending on both the subsurface resource and the surface applications; at the high end, our modeled solutions produced up to ~70% of existing campus heat load with a single well pair producing 70 kg/s with integrated high-temperature heat pumps, and (2) Modeling demonstrated that multiple geothermal reservoirs could provide economically viable results when heat pumps were strategically integrated, a design that has been proven in at least one European installation already. In this context, “economically viable” means that the LCOH for the project is less than the regional commercial price of heat that would be generated using natural gas (the most common and cheapest fossil alternative in our area). Based on a single-bottom-line (LCOH) valuation, our results show that economic success is likely for any reservoir deeper than about 2.25 km where a sufficient permeability exists (or can be created with stimulation or similar engineering enhancement) and reasonable production temperatures sustained over time. The LCOH values of $\$ 4.77$ to $\$ 6.46$ per MMBtu are all lower than the comparable cost of providing heat energy with a natural gas boiler for a facility in the Northeast U.S. that obtains natural gas at commercial rates (Commercial heat costs would include at least $\$ 9.41$ in fuel costs, representing total boiler/transfer efficiency of 85% using gas at $\$ 8.00$ per MMBtu; LCOH would be higher if capital equipment and other operating costs were included). In addition to LCOH, Cornell’s scope also included evaluation of the Environmental value and Regional Economic value of each scenario. When considering the environmental and regional economic value of such a project, the overall “triple bottom line” cost (i.e., the LCOH less the LCOH ENV and LCOH REG values) is even lower and in some cases negative; i.e., in some cases a project achieving the listed performance would have higher value to the environment and to the regional economy than the total project costs over the 30-year project timeframe.

15 GEOTHERMAL ENERGY↗
NASA NTRS2021

Acoustic Communication in Deep Ice at Ocean Worlds

One of NASA priorities is the in-situ exploration of ocean worlds in the solar system where potentially there might be life under the ice shell. This requires reaching the ocean below extremely cold through significant deep ice. Jupiter’s moon, Europa, is such a challenging body, where it is estimated to have a 40 km thick ice shell. An approach for reaching the ocean has been conceived using a melting probe Cryobot concept that has been studied for a potential future mission. A lander is assumed to be the platform from which the Cryobot would be deployed. The ice penetrating vehicle concept consists of a cylindrical, narrow-body probe that encases a radioisotope heat/power source that would be used to do the penetration by melting through the icy crust. The baseline design of the probe includes a suite of science instruments to analyze the ice during descent and the liquid ocean underneath. For communication, a set of fiber optic wire as well as wireless RF in the very cold porous top layer is assumed, and then acoustic modules would be used for the communication in warmer denser ice over distance of 25 km between the modules. In addition to the acoustic communication modules, a sonar is part of the concept, for obstacle avoidance. The focus of this paper is on the use of elastic waves in the 1kHz range.

Lih, Shyh-Shiuh↗
DOE OSTI2016

Deep Borehole Field Test Research Activities at LBNL

The goal of the U.S. Department of Energy Used Fuel Disposition’s (UFD) Deep Borehole Field Test is to drill two 5 km large-diameter boreholes: a characterization borehole with a bottom-hole diameter of 8.5 inches and a field test borehole with a bottom-hole diameter of 17 inches. These boreholes will be used to demonstrate the ability to drill such holes in crystalline rocks, effectively characterize the bedrock repository system using geophysical, geochemical, and hydrological techniques, and emplace and retrieve test waste packages. These studies will be used to test the deep borehole disposal concept, which requires a hydrologically isolated environment characterized by low permeability, stable fluid density, reducing fluid chemistry conditions, and an effective borehole seal. During FY16, Lawrence Berkeley National Laboratory scientists conducted a number of research studies to support the UFD Deep Borehole Field Test effort. This work included providing supporting data for the Los Alamos National Laboratory geologic framework model for the proposed deep borehole site, conducting an analog study using an extensive suite of geoscience data and samples from a deep (2.5 km) research borehole in Sweden, conducting laboratory experiments and coupled process modeling related to borehole seals, and developing a suite of potential techniques that could be applied to the characterization and monitoring of the deep borehole environment. The results of these studies are presented in this report.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Virioplankton assemblages from challenger deep, the deepest place in the oceans

Hadal ocean biosphere, that is, the deepest part of the world’s oceans, harbors a unique microbial community, suggesting a potential uncovered co-occurring virioplankton assemblage. Herein, we reveal the unique virioplankton assemblages of the Challenger Deep, comprising 95,813 non-redundant viral contigs from the surface to the hadal zone. Almost all of the dominant viral contigs in the hadal zone were unclassified, potentially related to Alteromonadales and Oceanospirillales. 2,586 viral auxiliary metabolic genes from 132 different KEGG orthologous groups were mainly related to the carbon, nitrogen, sulfur, and arsenic metabolism. Lysogenic viral production and integrase genes were augmented in the hadal zone, suggesting the prevalence of viral lysogenic life strategy. Abundant rve genes in the hadal zone, which function as transposase in the caudoviruses, further suggest the prevalence of viral-mediated horizontal gene transfer. This study provides fundamental insights into the virioplankton assemblages of the hadal zone, reinforcing the necessity of incorporating virioplankton into the hadal biogeochemical cycles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

A modeling study of tidal energy extraction and the associated impact on tidal circulation in a multi-inlet bay system of Puget Sound

Previous tidal energy projects in Puget Sound have focused on major deep channels such as Admiralty Inlet that have a larger power potential but pose greater technical challenges than minor tidal channels connecting to small sub-basins. This paper focuses on the possibility of extracting energy from minor tidal channels by using a hydrodynamic model to quantify the power potential and the associated impact on tidal circulation. The study site is a multi-inlet bay system connected by two narrow inlets, Agate Pass and Rich Passage, to the Main Basin of Puget Sound. A three-dimensional hydrodynamic model was applied to the study site and calibrated for tidal elevations and currents. We examined three energy extraction scenarios in which turbines were deployed in each of the two passages and concurrently in both. Extracted power rates and associated changes in tidal elevation, current, tidal flux, and residence time were examined. Maximum instantaneous power rates reached 250 kW, 1550 kW, and 1800 kW, respectively, for the three energy extraction scenarios. The model suggests that with the proposed level of energy extraction, the impact on tidal circulation is very small. It is worth investigating the feasibility of harnessing tidal energy from minor tidal channels of Puget Sound.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Benzobisoxazole cruciforms: A tunable, cross-conjugated platform for the generation of deep blue OLED materials

Four new cross-conjugated small molecules based on a central benzo[1,2-d:4,5-d']bisoxazole moiety possessing semi-independently tunable HOMO and LUMO levels were synthesized and the properties of these materials were evaluated experimentally and theoretically. The molecules were thermally stable with 5% weight loss occurring well above 350 °C. The cruciforms all exhibited blue emission in solution ranging from 433–450 nm. Host–guest OLEDs fabricated from various concentrations of these materials using the small molecule host 4,4'-bis(9-carbazolyl)-biphenyl (CBP) exhibited deep blue-emission with Commission Internationale de L'Eclairage (CIE) coordinates of (0.15 ≤ x ≤ 0.17, 0.05 ≤ y ≤ 0.11), and maximum luminance efficiencies as high as ~2 cd A–1. Lastly, these results demonstrate the potential of benzobisoxazole cruciforms as emitters for developing high-performance deep blue OLEDs.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Hydropower: Supply Chain Deep Dive Assessment

This report examines the hydropower supply chain to identify potential bottlenecks, challenges, and opportunities, particularly if the U.S. demand for hydropower components grows significantly to meet decarbonization targets. It is part of a series of DOE reports directed by Executive Order 14017 "America's Supply Chains"

13 HYDRO ENERGY↗
NASA NTRS2021

Extending the Licklider Transmission Protocol to Multi-Band Links

Most deep space missions return data to Earth using links operating at a single frequency band. Indeed, their data requirements are low enough that bandwidth regulations do not constrain the system. In contrast, spacecraft such as Kepler or Europa Clipper are transitioning to a new operational paradigm where engineering and science data are transmitted through simultaneous links operating at different frequency bands (henceforth termed multi-band links). This ensures, for instance, that critical data is correctly received using a well characterized X-band link, while science data at a much larger data rate can be returned efficiently (both in terms of bandwidth and energy) through a Ka-band link.Having a spacecraft establish two simultaneous links with a ground station opens a large span of potential improvements for space communications and mission operations. In this paper, we consider the problem of running a Licklider Transmission Protocol (LTP) session over a multi-band link. LTP is an implementation of a selective Automatic Repeat reQuest (ARQ) protocol, i.e. it ensures correct delivery of data over an error prone link with potentially long propagation delays. To maximize its efficiency in deep space environments, LTP operates in deferred-ACK mode and is typically included as one of the core protocols in the Delay Tolerant Networking (DTN) suite.The contributions of this paper are as follows: First, we propose an extension to LTP for multi-band links (denoted MBLTP) and sketch how it can be implemented without modifying the current definition of LTP data units. Next, we develop bounds on the performance of MBLTP when transmitting a single data file over a multi-band link. Three metrics are considered, file expected delivery time, total energy spent and bundle jitter. The results of the analytic model are first benchmarked against simulations to ensure validity, and then compared against the performance of both traditional LTP and Parallel LTP (PLTP).We demonstrate that MBLTP can significantly reduce the latency and jitter with which data products are delivered to destination over a deep space link compared to LTP at moderate energy cost. Similarly, we also demonstrate that MBLTP outperforms PLTP in all considered metrics.

Sanchez Net, Marc↗
NASA NTRS1993

The tropopause cold trap in the Australian Monsoon during STEP/AMEX 1987

The relationship between deep convection and tropopause cold trap conditions is examined for the tropical northern Australia region during the 1986-87 summer monsoon season, emphasizing the Australia Monsoon Experiment (AMEX) period when the NASA Stratosphere-Troposphere Exchange Project (STEP) was being conducted. The factors related to the spatial and temporal variability of the cold point potential temperature (CPPT) are investigated. A framework is developed for describing the relationships among surface average equivalent potential temperature in the surface layer (AEPTSL) the height of deep convection, and stratosphere-troposphere exchange. The time-mean pattern of convection, large-scale circulation, and surface AEPTSL in the Australian monsoon and the evolution of the convective environment during the monsoon period and the extended transition season which preceded it are described. The time-mean fields of cold point level variables are examined and the statistical relationships between mean CPPT, surface AEPTSL, and deep convection are described. Day-to-day variations of CPPT are examined in terms of these time mean relationships.

Selkirk, Henry B.↗