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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 253 records · Page 14

Facilitating Science--The International Space Station Fluids and Combustion Facility

Scientists in many fields would like to perform experiments on the International Space Station (ISS) to take advantage of the unique environment of microgravity (which is the near-absence of gravity). The ISS will provide the opportunity for scientists to perform microgravity tests over much longer time periods than previously available on the space shuttle--months rather than hours or days--providing more data that could lead to new discoveries. Many of the experiments on ISS will be conducted through the use of new microgravity science facilities. A microgravity science facility is a complete system of on-orbit and ground (on-Earth) hardware, software, operations, and plans that have been optimized to perform sustained microgravity research in one or two scientific disciplines. The facility concept includes hardware that remains on-orbit (because of its general usefulness) and a small amount of unique hardware that is developed for each principal investigator. Such unique hardware customizes the facility to perform a given principal investigator's experiment effectively. Many facilities are planned for the ISS to accommodate scientists' needs. While the quality and quantity of scientific data are being improved, per-experiment costs will be lowered relative to other ways of performing such experiments. The NASA Lewis Research Center is developing a Fluids and Combustion Facility (FCF) to perform microgravity fluids and combustion experiments on the ISS. The FCF will be the lowest cost, most resource efficient approach to performing fluid physics and combustion science experiments on the ISS. Experiments performed in the FCF will be 3 to 9 times less expensive than similar Spacelab experiments. Moreover, use of key ISS resources, such as upmass, power, cooling, and astronaut crew time, will be cut by the same factor.

Winsa, Edward A.↗

Deep Learning for Land Cover Classification Using Only a Few Bands

There is an emerging interest in using hyperspectral data for land cover classification. The motivation behind using hyperspectral data is the notion that increasing the number of narrowband spectral channels would provide richer spectral information and thus help improve the land cover classification performance. Although hyperspectral data with hundreds of channels provide detailed spectral signatures, the curse of dimensionality might lead to degradation in the land cover classification performance. Moreover, in some practical applications, hyperspectral data may not be available due to cost, data storage, or bandwidth issues, and RGB and near infrared (NIR) could be the only image bands available for land cover classification. Light detection and ranging (LiDAR) data is another type of data to assist land cover classification especially if the land covers of interest have different heights. In this paper, we examined the performance of two Convolutional Neural Network (CNN)-based deep learning algorithms for land cover classification using only four bands (RGB+NIR) and five bands (RGB+NIR+LiDAR), where these limited number of image bands were augmented using Extended Multi-attribute Profiles (EMAP). The deep learning algorithms were applied to a well-known dataset used in the 2013 IEEE Geoscience and Remote Sensing Society (GRSS) Data Fusion Contest. With EMAP augmentation, the two deep learning algorithms were observed to achieve better land cover classification performance using only four bands as compared to that using all 144 hyperspectral bands.

58 GEOSCIENCES↗

Savings in Action: Lessons from Observed and Modeled Residential Solar Plus Storage Systems [Slides]

The study performed two related analyses using data from a new-construction residential community equipped with rooftop solar and storage (S+S) in Arizona. The study analyzed the factors that determine customer electricity cost savings from S+S adoption. The research compared the Arizona case study data to modeled system performance to understand how models deviate from real-world outcomes. Based on these findings, NREL explored ways to improve such models and, conversely, use modeled results to suggest improvements to S+S dispatches.

14 SOLAR ENERGY↗

Predicting future well performance for environmental remediation design using deep learning

Here in this study, we developed a deep learning (DL) framework with a multi-channel three-dimensional convolutional neural network (MC3D-CNN) to predict well performance and thereby assist future environmental remediation design. Such prediction of extraction well performance at designated locations is critical for configuring pump-and-treat (P&T) well network design and operation, setting reasonable target closure dates for overall remedying, and estimating remedy costs. The framework is developed with operational and monitoring data routinely collected during P&T remedy operations, including well extraction and injection rates as well as in situ contaminant concentrations. Traditionally, the collected data were rarely used for purposes other than assessing past well performance and the accuracy of the conceptual site model. However, recent advances in data-driven computational approaches enable better use of the large datasets to inform future well performance, enhance site characterization, and improve remediation planning. In this study, we established a DL framework to integrate transient three-dimensional contaminant plumes and multiple aquifer properties (e.g., hydraulic conductivity and hydrostratigraphic maps) to identify characteristic patterns controlling and representing extraction well mass recovery, aiming at providing future mass recovery estimates for existing wells and candidate wells at any proposed locations. We evaluated our framework by using a realistic synthetic dataset generated from a well-calibrated flow and transport model used in the 200 West Area of the U.S. Department of Energy’s Hanford Site in southeastern Washington state. The multi-channel feature in our framework allows integration of various types and temporal densities of training datasets for DL model development. Overall, we found that the trained DL model achieved an accuracy of over 90% in ranking extraction well performance in validation datasets, and over 80% in predicting high-performance-ranking well locations. This data-informed approach provides a flexible tool to support adaptive site management, streamline decision-making, and potentially reduce remediation time and costs. Our DL framework can be used as a filtering tool to improve the current P&T network optimization design by reducing the number of candidate well locations.

54 ENVIRONMENTAL SCIENCES↗

Mathematical synthesization of complex structures

A mathematical synthesization approach for rapidly modeling and analyzing complex structures comprised of hundreds or thousands of repeating individual structural members, interconnecting hardware, and other components was described. The techniques are applicable to any structure with repeating structural members. The capabilities are embodied within the Interactive Design and Evaluation of Advanced Spacecraft (IDEAS) computer-aided design system. IDEAS has a full range of integrated spacecraft modeling, design, analysis, performance, and cost estimating capabilities which include about 40 technical program and executive, data base, and file management systems. With IDEAS, a single user at an interactive terminal can create, design, analyze, and conduct parametric studies of Earth orbiting spacecraft in a timely, cost-efficient manner. The system is particularly useful in the conceptual design phases of advanced space missions when a multiplicity of concepts must be evaluated. The IDEAS interactive finite-element modeling capabilities are discussed. The mathematical synthesization programs were structured not only to provide a detailed finite-element model of the structure but also to automatically perform the many auxiliary computations needed to analyze the spacecraft in its orbital operational environment.

Garrett, L. B.↗

Photovoltaic module encapsulation design and materials selection, volume 1

Encapsulation material system requirements, material selection criteria, and the status and properties of encapsulation materials and processes available are presented. Technical and economic goals established for photovoltaic modules and encapsulation systems and their status are described. Available encapsulation technology and data are presented to facilitate design and material selection for silicon flat plate photovoltaic modules, using the best materials available and processes optimized for specific power applications and geographic sites. The operational and environmental loads that encapsulation system functional requirements and candidate design concepts and materials that are identified to have the best potential to meet the cost and performance goals for the flat plate solar array project are described. Available data on encapsulant material properties, fabrication processing, and module life and durability characteristics are presented.

Cuddihy, E.↗

Benchmark Comparison of Cloud Analytics Methods Applied to Earth Observations

Cloud computing has the potential to bring high performance computing capabilities to the average science researcher. However, in order to take full advantage of cloud capabilities, the science data used in the analysis must often be reorganized. This typically involves sharding the data across multiple nodes to enable relatively fine-grained parallelism. This can be either via cloud-based file systems or cloud-enabled databases such as Cassandra, Rasdaman or SciDB. Since storing an extra copy of data leads to increased cost and data management complexity, NASA is interested in determining the benefits and costs of various cloud analytics methods for real Earth Observation cases. Accordingly, NASA's Earth Science Technology Office and Earth Science Data and Information Systems project have teamed with cloud analytics practitioners to run a benchmark comparison on cloud analytics methods using the same input data and analysis algorithms. We have particularly looked at analysis algorithms that work over long time series, because these are particularly intractable for many Earth Observation datasets which typically store data with one or just a few time steps per file. This post will present side-by-side cost and performance results for several common Earth observation analysis operations.

science data management↗

Towards Gbps Downlinks from Low-Cost Active Phased Arrays

Spacecraft performing science missions use high-directivity antennas to quickly downlink large amounts of collected data. Movement required to keep gimbaled reflector antennas trained on target receivers can impart blockages or vibrations which perturb precision science instruments. Recent manufacturing advances have made Ka-band electronically-steered antenna arrays a cost-effective option to mitigate these challenges, but only if these devices can be proven to deliver comparable quality of service. In this work we present a hardware and software architecture for high-rate links using an active phased array-based terminal in a 1U (10cm cube) form factor. Over-the-air tests in an antenna range characterize two key features of the architecture: high-order (32APSK and above) modulations and dual carriers. We calculate an optimal modulation-dependent input power backoff from array saturation and perform orbital simulations of the link at this operating point. We conclude that reliable links with rates in excess of 1Gbps are possible with current-generation hardware.

Adam Gannon↗

Distributed Wind Energy Futures Study

To better understand distributed wind opportunities in the United States, researchers at the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory explored cost, performance, and valuation benchmarks necessary for distributed wind to achieve widespread commercial viability in the United States by 2035. Building on DOE's prior benchmark report "Assessing the Future of Distributed Wind: Opportunities for Behind-the-Meter Projects", the new Distributed Wind Futures Study employs higher-resolution data and new modeling techniques to highlight geographic trends in technical and economic potential and to compare the cost and performance of distribution-connected, megawatt-scale wind applications (referred to as "front-of-the-meter" applications) and behind-the-meter systems, thereby informing the case for investment. The report identifies the best locations and sectors for behind-the-meter and front-of-the-meter applications and provides data to inform the trade-offs consumers face when deciding between distributed wind and solar photovoltaic (PV).

17 WIND ENERGY↗

Distributed Wind Energy Futures Study [Slides]

To better understand distributed wind opportunities in the United States, researchers at the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory explored cost, performance, and valuation benchmarks necessary for distributed wind to achieve widespread commercial viability in the United States by 2035. Building on DOE's prior benchmark report "Assessing the Future of Distributed Wind: Opportunities for Behind-the-Meter Projects", the new Distributed Wind Futures Study employs higher-resolution data and new modeling techniques to highlight geographic trends in technical and economic potential and to compare the cost and performance of distribution-connected, megawatt-scale wind applications (referred to as "front-of-the-meter" applications) and behind-the-meter systems, thereby informing the case for investment. The report identifies the best locations and sectors for behind-the-meter and front-of-the-meter applications and provides data to inform the trade-offs consumers face when deciding between distributed wind and solar photovoltaic (PV).

17 WIND ENERGY↗

AI Driven Experiment Calibration and Control

One critical step on the path from data taking to physics analysis is calibration. For many experiments this step is both time consuming and computationally expensive. The AI Experimental Calibration and Control project seeks to address these issues, starting first with the GlueX Central Drift Chamber (CDC). We demonstrate the ability of a Gaussian Process to estimate the gain correction factor (GCF) of the GlueX CDC accurately, and also the uncertainty of this estimate. Using the estimated GCF, the developed system infers a new high voltage (HV) setting that stabilizes the GCF in the face of changing environmental conditions. This happens in near real time during data taking and produces data which are already approximately gain-calibrated, eliminating the cost of performing those calibrations which vary ±15% with fixed HV. We also demonstrate an implementation of an uncertainty aware system which exploits a key feature of a Gaussian process.

Britton, Thomas↗

Systems cost/performance analysis (study 2.3). Volume 2, appendix A: Data base

Data are presented on selected payload equipments (components) which were collected for the purpose of exercising the systems cost/performance model. Although most of the data is accurate, approximations based on engineering judgment and experience are used wherever actual data was unavailable. The equipments are organized according to the following subsystems which use the specific components: stabilization and control, auxiliary propulsion, data processing, communication, and electrical power. The data sheet for each component states which subsystem utilizes the component, which configurations require the component, which equipment type the component is categorized as, and the data base identifier or code number assigned to the component. The data describing the component consist of the following four types: performance, safety, cost, and schedule.

Campbell, B. H.↗

Fuel conservation merits of advanced turboprop transport aircraft

The advantages of a propfan powered aircraft for the commercial air transportation system were assessed by the comparison with an equivalent turbofan transport. Comparisons were accomplished on the basis of fuel utilization and operating costs, as well as aircraft weight and size. Advantages of the propfan aircraft, concerning fuel utilization and operating costs, were accomplished by considering: (1) incorporation of propfan performance and acoustic data; (2) revised mission profiles (longer design range and reduction in; and cruise speed) (3) utilization of alternate and advanced technology engines.

Revell, J. D.↗

Installation and checkout of the DOE/NASA Mod-1 2000-kW wind turbine generator

The paper describes the DOE/NASA Mod-1 wind turbine generator, its assembly and testing, and its installation at Boone, North Carolina. The paper concludes with performance data taken during the initial tests conducted on the machine. The successful installation and initial operation of the Mod-1 wind turbine generator has had the following results: (1) megawatt-size wind turbines can be operated satisfactorily on utility grids; (2) the structural loads can be predicted by existing codes; (3) assembly of the machine on top of the tower presents no major problem; (4) large blades 100 ft long can be transported long distances and over mountain roads; and (5) operating experience and performance data will contribute substantially to the design of future low-cost wind turbines.

Puthoff, R. L.↗

Low-thrust chemical propulsion system pump technology

A study was conducted within the thrust range 450 to 9000 N (100 to 2000 pounds). Performance analyses were made on centrifugal, pitot, Barske, drag, Tesla, gear, piston, lobe, and vane pumps with liquid hydrogen, liquid methane, and liquid oxygen as propellants. Gaseous methane and hydrogen driven axial impulse turbines, vane expanders, piston expanders, and electric motors were studied as drivers. Data are presented on performance, sizes, weights, and estimated service lives and costs.

Meadville, J. W.↗

Contribution of Spaceflight Environmental Factors to Vision Risks

The risk of visual impairment and elevated intracranial pressure as a result of low-earth orbit microgravity exposure has directed our attention and research efforts to the eye. While the alterations observed in astronauts returning from long duration missions include vision and neuroanatomical changes observed by non-invasive methods, other effects and subsequent tissue responses at the molecular and cellular level can only be studied by accessing the tissue itself. As a result of this need, several studies are currently taking place within the Human and Health Countermeasures Element (HHC) that use animal models for eye research. The rodent eye has many similarities to the human eye, and both rats and mice have historically been used as models of human eye disease, aiding in the identification of the disease genes, elucidation of mechanisms of disease, as well as in the assessment of therapeutic treatments. These studies attempt to answer two central questions in the etiology of possible vision alterations in the environment of space exploration missions. The first is: what effects and response mechanisms take place in the different eye structures at the cellular and molecular level? The second question is directed to elucidate the contribution of the various environmental stressors (radiation, nutrition, fluid shift) to these effects. Collaborative approaches with internal and external investigators have allowed performing these studies in a most cost-effective fashion, providing preliminary data and laying the bases for testing further hypotheses in future and specifically designed animal experiments. From a study centered on the radioadaptive response in mice, we have learned that the retina responds to low and high dose gamma radiation by elevating antioxidant-related genes at early time points (4hrs) and that this response returns to control levels after 1 day post-irradiation. We are expanding this research with another collaborative study that investigates the combined effects of radiation exposure and iron overload on sensitivity to radiation injury in rat eyes. All main eye structures will be analyzed in this study: retina, lens and cornea. A study in collaboration with the Space Human Factors and Habitability Element (SHFH) investigates the effects of lunar dust exposure on the rat cornea. It is anticipated that common underlying oxidative stress mechanisms of damage may be observed as a result of these three stressors: radiation, nutritional iron and lunar dust. The contribution of fluid shift is addressed by a study using rats subjected to hindlimb suspension. The hypothesis to be tested in this study is that the mechanical stress imparted by the pressure differential across the optic disc and lamina cribosa will impact oxygenation (therefore causing oxidative stress and hypoxia) and cell survival. This study also includes the assessment of two nutritional antioxidant countermeasures: epigallocatechin gallate (green tea) and resveratrol. Finally, as a result of two successful tissue sharing efforts, we are proceeding with the analysis of eye samples of mice aboard two shuttle missions: STS-133 and STS-135. Results from the STS-133 study are presented in an independent abstract. Briefly, the results show that spaceflight represents a source of environmental stress that directly translates into oxidative and cellular stress in the retina. Similar analysis is also planned for the cornea. These samples add large value to our current vision research as they provide data on the direct effects of low-earth orbit spaceflight on eye structures and physiology.

Zanello, Susana B.↗

The NASA L3 Study

The Astrophysics Implementation Plan calls for a minority role in L3, planned for launch in 2034. L3 The third large mission in ESAs Cosmic Visions 2015-2025 Programme NASA and ESA have been discussing a collaboration for 2 years Gravitational Observatory Advisory Team (GOAT) ESA study evaluating and recommend scientific performance tradeoffs, detection technologies, technology development activities, data analysis capabilities, schedule and cost US representatives: Guido Mueller, Mark Kasevich, Bill Klipstein, RTS Started in October 2014, concluding with a final report in late Marchor early April 2016. ESA solicited interest from ESA Member States in November 2015 NASA is continuing technology development support. ESA is restarting technology development activities.

The L3 Study organization and charter have been es↗

Inventory for Crystalline Silicon Module Recycling: Cooperative Research and Development (Final Report)

A critical challenge for the continued expansion of photovoltaics (PV) is to develop technically feasible, inexpensive and environmentally friendly practices for handling and recycling modules at the end of their usable life. The National Renewable Energy Laboratory (NREL) is requested by the Electric Power Research Institute (EPRI) to collect primary data regarding the environmental performance of currently operational PV module recycling facilities in Europe. Very little has been published regarding crystalline silicon (C-Si) module recycling. Thus, much effort will be needed in direct industry outreach, collection of information and other business intelligence strategies similar to NREL's approaches for developing cost models for PV manufacturing. The goal of this work effort is to produce a detailed inventory that accounts for physical (e.g., energy, water, materials) flows through each step of a C-Si recycling process. The inventory (a life cycle inventory, or LCI) shall be designed so that it can be extended to include an accounting of costs for each process step, inputs, etc. This work effort shall leverage prior LCI data collection NREL performed for the United States Department of Energy, Solar Energy Technologies Office, under the auspices of the U.S. contribution to International Energy Agency's Photovoltaics Power Systems (PVPS) Task 12 (Environmental Health and Safety), which SETO nominated NREL to chair. The primary purpose of this work effort is to augment the prior data collection to increase the sample size of manufacturers' primary data in the LCI.

14 SOLAR ENERGY↗