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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Fabrication and testing of a three-channel integrated optical data preprocessor

As a precursor to the construction of a 16-channel device, a 3-channel integrated optical data preprocessor has been fabricated and tested. The device, which is fabricated in an outdiffused LiNbO3 waveguide, provides a signal related to the channel-by-channel difference between a prerecorded reference set and an incoming data set which is presented in the form of parallel analog voltages. The data are impressed upon the guided wave as a set of electrooptically induced phase shifts, and the comparison to the reference set is performed by holographic subtraction. The reference set can either be introduced as a separate operation or it can be 'learned' by the preprocessor during operation.

Verber, C. M.↗
NASA NTRS1983

Use of simultaneous Doppler-derived ranges in the geometric mode

A mathematical model for the use of ranges derived from integrated Doppler-shifted frequency observations in a satellite trilateration is presented. The model is tested with data taken during the Second European Doppler Observation Campaign (EDOC-2) campaign. The results of this adjustment are compared with the EDOC-2 results.

Schneeberger, R.↗
NASA NTRS1984

High-resolution, far-ultraviolet study of Beta Draconis (G2 Ib-II) - Transition region structure and energy balance

High-resolution far ultraviolet spectra of the star Beta Draconis have been obtained with the IUE satellite. The observations and emission line data from the spectra are presented, the interpretation of the emission line widths and shifts is discussed, and the implications are given in terms of atmospheric properties. The emission measure distribution is derived, and density diagnostics involving both line ratios and line opacity arguments is investigated. The methods for calculating spherically symmetric models of the atmospheric structure are outlined, and several such models are presented. The extension of these models to log T(e) greater than 5.3 using the observed X-ray flux is addressed, the energy balance of an 'optimum' model is investigated, and possible models of energy transport and deposition are discussed.

Brown, A.↗
NASA NTRS1983

Airborne Doppler-lidar and ground-based Doppler radar observations of a thunderstorm in Oklahoma

The results of airborne Doppler-lidar and ground-based Doppler radar observations of multicellular storms, marked by heavy rainfall, strong surface outflow, and a gust-front tornado, on June 30, 1981 are analyzed. The airborne lidar comprised a CO2-laser operating in the IR region, which was discharged once each second at 20 deg fore and aft, alternatively, of the normal to the aircraft's heading, and a quarter-wave plate for registering the returning frequency-shifted beams. Wind fields are plotted taking into account the advection effects. The lidar data set is noted for its self-consistency, though limited to a range of 5 km by the high moisture levels. Fair agreement was found between the lidar-derived and radar-derived average ground-based radial wind fields, with discrepancies on the order of 1.5 m/s.

Bluestein, H. B.↗
NASA NTRS1988

Remote sensing of forest canopy and leaf biochemical contents

Recent research on the remote sensing of forest leaf and canopy biochemical contents suggests that the shortwave IR region contains this information; laboratory analyses of dry ground leaves have yielded reliable predictive relationships between both leaf nitrogen and lignin with near-IR spectra. Attention is given to the application of these laboratory techniques to a limited set of spectra from fresh, whole leaves of conifer species. The analysis of Airborne Imaging Spectrometer data reveals that total water content variations in deciduous forest canopies appear as overall shifts in the brightness of raw spectra.

Peterson, David L.↗
NASA NTRS1999

Fluid and Electrolyte Nutrition

Studies of fluid and electrolyte homeostasis have been completed since the early human space flight programs, with comprehensive research completed on the Spacelab Life Sciences missions SLS-1 and SLS-2 flights, and more recently on the Mir 18 mission. This work documented the known shifts in fluids, the decrease in total blood volume, and indications of reduced thirst. Data from these flights was used to evaluate the nutritional needs for water, sodium, and potassium. Interpretations of the data are confounded by the inadequate energy intakes routinely observed during space flight. This in turn results in reduced fluid intake, as food provides approximately 70% water intake. Subsequently, body weight, lean body mass, total body water, and total body potassium may decrease. Given these issues, there is evidence to support a minimum required water intake of 2 L per day. Data from previous Shuttle flights indicated that water intake is 2285 +/- 715 ml/day (mean +/- SD, n=26). There are no indications that sodium intake or homeostasis is compromised during space flight. The normal or low aldosterone and urinary sodium levels suggest adequate sodium intake (4047 +/- 902 mg/day, n=26). Because excessive sodium intake is associated with hypercalciuria, the recommended maximum amount of sodium intake during flight is 3500 mg/day (i.e., similar to the Recommended Dietary Allowance, RDA). Potassium metabolism appears to be more complex. Data indicate loss of body potassium related to muscle atrophy and low dietary intake (2407 +/- 548 mg/day, n=26). Although possibly related to measurement error, the elevations in blood potassium suggest alterations in potassium homeostasis. The space RDA for minimum potassium intake is 3500 mg/day. With the documented inadequate intakes, efforts are being made to increase dietary consumption of potassium.

Lane, Helen W.↗
NASA NTRS2005

Nexus: Planning Tomorrow, Today

To prepare for future human space flight programs, the Mission Operations Laboratory (MOL) at the Marshall Space Flight Center (MSFC) has been investigating new planning and scheduling paradigms. To support and prove this investigation, MOL technologists have developed a working prototype of a scheduling system to support the new paradigms. The new planning and scheduling system is called Nexus and has a web site at http://nexus.nasa.gov/. Nexus is based on a comprehensive modeling schema to capture all scheduling requirements typical to human space missions, an incremental scheduling engine tailored to the modeling schema, and remote access (including Personal Data Assistant (PDA) access) to the scheduling system. This paper describes the proposed paradigm shift and the enabling software. It also describes a typical Nexus demonstration which emphasizes how it works, how it enables the paradigm shift, and possible applications. Demonstrations include access to the full functionally of Nexus from a personal computer and access to limited functionally via a PDA. An appendix includes a description and screen shots of the demonstrations.

Jaap, John↗
NASA NTRS2007

Recent Changes in the Arctic Melt Season

Melt-season duration, melt-onset and freeze-up dates are derived from satellite passive microwave data and analyzed from 1979 to 2005 over Arctic sea ice. Results indicate a shift towards a longer melt season, particularly north of Alaska and Siberia, corresponding to large retreats of sea ice observed in these regions. Although there is large interannual and regional variability in the length of the melt season, the Arctic is experiencing an overall lengthening of the melt season at a rate of about 2 weeks decade(sup -1). In fact, all regions in the Arctic (except for the central Arctic) have statistically significant (at the 99% level or higher) longer melt seasons by greater than 1 week decade(sup -1). The central Arctic shows a statistically significant trend (at the 98% level) of 5.4 days decade(sup -1). In 2005 the Arctic experienced its longest melt season, corresponding with the least amount of sea ice since 1979 and the warmest temperatures since the 1880s. Overall, the length of the melt season is inversely correlated with the lack of sea ice seen in September north of Alaska and Siberia, with a mean correlation of -0.8.

Stroeve, Julienne↗
NASA NTRS2010

Data Acquisition and Processing System for Airborne Wind Profiling with a Pulsed, 2-Micron, Coherent-Detection, Doppler Lidar System

A data acquisition and signal processing system is being developed for a 2-micron airborne wind profiling coherent Doppler lidar system. This lidar, called the Doppler Aerosol Wind Lidar (DAWN), is based on a Ho:Tm:LuLiF laser transmitter and 15-cm diameter telescope. It is being packaged for flights onboard the NASA DC-8, with the first flights in the summer of 2010 in support of the NASA Genesis and Rapid Intensification Processes (GRIP) campaign for the study of hurricanes. The data acquisition and processing system is housed in a compact PCI chassis and consists of four components such as a digitizer, a digital signal processing (DSP) module, a video controller, and a serial port controller. The data acquisition and processing software (DAPS) is also being developed to control the system including real-time data analysis and display. The system detects an external 10 Hz trigger pulse and initiates the data acquisition and processing process, and displays selected wind profile parameters such as Doppler shift, power distribution, wind directions and velocities. Doppler shift created by aircraft motion is measured by an inertial navigation/GPS sensor and fed to the signal processing system for real-time removal of aircraft effects from wind measurements. A general overview of the system and the DAPS as well as the coherent Doppler lidar system is presented in this paper.

Beyon, J. Y.↗
NASA NTRS1973

Tropospheric Transmissivity Measurements Using the Raman Nitrogen Lidar Technique

LIDAR measurements in Azusa, California, during October 1972, were made in which the backscattered Raman-shifted nitrogen return was ratioed at different altitudes in order to obtain transmissivity. Rawinsonde data from nearby El Monte were used to determine the temperature and nitrogen number density altitude profiles. These data and other meteorological data are compared to the vertical aerosol and transmissivity structure determined by LIDAR. Also data analysis techniques are shown for obtaining q2 (transmissivity) and beta (attenuation coefficient) as a function of altitude.

McCormick, M. P.↗
NASA NTRS2017

An Evolving Worldview: Making Open Source Easy

NASA Worldview is an interactive interface for browsing full-resolution, global satellite imagery. Worldview supports an open data policy so that academia, private industries and the general public can use NASA's satellite data to address Earth science related issues. Worldview was open sourced in 2014. By shifting to an open source approach, the Worldview application has evolved to better serve end-users. Project developers are able to have discussions with end-users and community developers to understand issues and develop new features. New developers are able to track upcoming features, collaborate on them and make their own contributions. Getting new developers to contribute to the project has been one of the most important and difficult aspects of open sourcing Worldview. A focus has been made on making the installation of Worldview simple to reduce the initial learning curve and make contributing code easy. One way we have addressed this is through a simplified setup process. Our setup documentation includes a set of prerequisites and a set of straight forward commands to clone, configure, install and run. This presentation will emphasis our focus to simplify and standardize Worldview's open source code so more people are able to contribute. The more people who contribute, the better the application will become over time.

open dat↗
NASA NTRS2018

New Levels of High Angular Resolution EBSD Performance via Inverse Compositional Gauss-Newton Digital Image Correlation

Conventional high angular resolution electron backscatter diffraction (HREBSD) uses cross-correlation to track features between diffraction patterns, which are then related to the relative elastic strain and misorientation between the diffracting volumes of material. This paper adapts inverse compositional Gauss Newton (ICGN) digital image correlation (DIC) to be compatible with HREBSD. ICGN works by efficiently tracking not just the shift in features, but also the change in their shape. Modeling a shape change as well as a shift results in greater accuracy. This method, ICGN HREBSD, is applied to a simulated data set, and its performance is compared to conventional cross-correlation HREBSD, and cross-correlation HREBSD with remapping. ICGN HREBSD is shown to have about half the strain error of the best cross-correlation method with a comparable computation time.

T. J. Ruggles↗
DOE OSTI2020

Ground Transportation at Airports: Ridehailing Uptake and Travel Shifts to Test Mode Choice Modeling Assumption

Ground transportation at airports poses a unique opportunity to understand mode shifts after introduction of ride-hailing services. Using five years of monthly transaction data for five modes (transit, parking, car rental, taxis, and ride-hailing) at the Seattle-Tacoma and Denver airports, this paper presents findings on how ride-hailing uptake impacts mode share for ground transportation trips to and from the airport. More specifically, the results explore how well the Independence of Irrelevant Alternatives facilitates estimation and forecasts prediction used in travel demand modeling for the uptake of new modes, as simply drawing from present modes in proportion to their existing shares.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Trustworthiness and Trust: Identifying Factors that Drive Successful Human-AI Interaction in Nuclear Power Plant Applications

Emerging technologies such as artificial intelligence (AI) and machine learning (ML) are rapidly evolving and considered a promising tool for efficient and continued safe operations of the U.S. nuclear power plants (NPPs). Emerging AI techniques like large language models (LLMs) are one such technology that may support personnel at existing NPPs perform work more efficiently. For example, operators may query the current operational status of a power plant via a chat interface leveraging LLMs to access plant-related information in an interactive manner rather than manually collecting various sensor data for tasks such as surveillances or completing work orders. This is a fundamental shift in the way operators currently perform their tasks today. The literature of human-automation interaction indicates that trust is a crucial factor that drives successful interaction between a human operator and an automated system, like an AI-infused NPP application. This work presents the results of a literature review on key factors that relate to trust in AI/LLM technologies for NPP applications. The relevant literature of human factors and cognitive engineering has identified various factors related to trust including trustworthiness, performance characteristics, operator skill and perceived risk. This preliminary literature review will guide development and evaluation of models involving the identified factors influencing trust in AI and develop a framework for human-centered design for interface between humans and AI. By addressing trust, this work supports developing a technical basis for designing key characteristics of AI/LLM to support calibrated trust, which will ultimately support wide-scale adoption of AI/LLM technologies, as well as ensure safe, effective, and reliable use.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

SimLBR: Learning to Detect Fake Images by Learning to Detect Real Images

The rapid advancement of generative models has made the detection of AI-generated images a critical challenge for both research and society. Recent works have shown that most state-of-the-art fake image detection methods overfit to their training data and catastrophically fail when evaluated on curated hard test sets with strong distribution shifts. In this work, we argue that it is more principled to learn a tight decision boundary around the real image distribution and treat the fake category as a sink class. To this end, we propose SimLBR, a simple and efficient framework for fake image detection with Latent Blending Regularization (LBR). Our method significantly improves cross-generator generalization, achieving up to +24.85% accuracy and +69.62% recall on the challenging Chameleon benchmark. SimLBR is also highly efficient, training orders of magnitude faster than existing approaches. Furthermore, we emphasize the need for reliability-oriented evaluation in fake image detection, introducing risk-adjusted metrics and worst-case estimates to better assess model robustness. All the code and models are availabe at: https://github.com/mvrl/SimLBR

Dhakal, Aayush [Washington University, St. Louis]↗
DOE OSTI2022

Artificial Intelligence and Machine Learning for Bioenergy Research: Opportunities and Challenges

The integration of artificial intelligence and machine learning (AI/ML) with automated experimentation, genomics, biosystems design, and bioprocessing technologies is poised to revolutionize scientific investigation and, particularly, bioenergy research. To identify the opportunities and challenges in this emerging research area, the U.S. Department of Energy’s (DOE) Biological and Environmental Research program (BER) and Bioenergy Technologies Office (BETO) held a joint virtual workshop on AI/ML for Bioenergy Research (AMBER) on August 23–25, 2022. These interests have since been amplified in a September 2022 Executive Order, “Advancing Biotechnology and Biomanufacturing Innovation for a Sustainable, Safe, and Secure U.S. Bioeconomy,” to promote a whole-of government approach to biotechnology development (White House 2022). Approximately 50 scientists with various backgrounds and expertise from academia, industry, and DOE national laboratories met to discuss the opportunities and challenges of AI/ML for bioenergy research. Workshop participants were tasked with assessing the potential for AI/ML and laboratory automation to advance biological understanding and engineering in general. They particularly examined how integrating AI/ML tools with laboratory automation could accelerate biosystems design and optimize biomanufacturing. Discussions included the data and computational infrastructure needed to augment biosystems design applications and the expertise and workforce development efforts urgently required to shift integrated systems toward bioenergy research more broadly. Participants discussed many existing and future applications of AI/ML for biosystems design ranging from enzymes to plants and microbes, microbiomes, and bioprocess development. They also identified three key categories of scientific and technical opportunities and challenges: high-quality data, AI/ML algorithms, and laboratory automation. Several main takeaways emerged from the workshop: 1. Numerous AI/ML and automated experimentation applications exist for a variety of DOE mission needs in energy and the environment; 2. Exemplary research grand challenges for which AI/ML could provide solutions include: building microbes and microbial communities to specifications, developing closed-loop autonomous design and control for biosystems design, and advancing scale-up and automation; 3. Lack of sufficient high-quality, annotated data hinders the development of AI/ML applications; 4. New and improved AI/ML tools are needed, particularly those meeting the specific needs of the BER and BETO research communities; 5. Trade-offs in performance, cost, and reliability exist between deploying commercially available versus building custom-developed instrumentation and software for automated or autonomous experimentation; translation of manual to automated or autonomous methods is often a nontrivial endeavor; 6. Training a new generation of young scientists who can develop and apply AI/ML tools is needed to solve long-standing scientific challenges in bioenergy research. The integration of AI/ML tools and automated experimentation represents a new data-driven research paradigm complementary to the traditional hypothesis-driven research paradigm. This paradigm accelerates design and optimization of biological systems and processes for a variety of DOE mission needs in energy and the environment. The AMBER workshop broadly explored the potential of this new paradigm for bioenergy research, of particular interest to BER and BETO, and identified key challenges and opportunities that DOE can address in the coming years by leveraging its unique capabilities and resources.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1996

Dust in the small Magellanic cloud. 1: Interstellar polarization and extinction data

The typical extinction curve for the Small Magellanic Cloud (SMC), in contrast to that for the Galaxy, has no bump at 2175 A and has a steeper rise into the far ultraviolet. For the Galaxy the interpretation of the extinction and, therefore, the dust content of the interstellar medium has been greatly assisted by measurements of the wavelength dependence of the polarization. For the SMC no such measurements existed. Therefore, to further elucidate the dust properties in the SMC we have for the first time measured linear polarization with five colors in the optical region of the spectrum for a sample of reddened stars. For two of these stars, for which there were no existing UV spectrophotometric measurements, but for which we measured a relatively large polarization, we have also obtained data from the International Ultraviolet Explorer (IUE) in order to study the extinction. We also attempt to correlate the SMC extinction and polarization data. The main results are: the wavelength of maximum polarization, lambda(sub max), in the SMC is typically smaller than that in the Galaxy; however, AZC 456, which shows the UV extinction bump, has a lambda(sub max) typical of that in the Galaxy, but its polarization curve is narrower and its bump is shifted to shorter wavelengths as compared to the Galaxy; and from an analysis of both the extinction and polarization data it appears that the SMC has typically smaller grains than those in the Galaxy. The absence of the extinction bump in the SMC has generally been thought to imply a lower carbon abundance in the SMC compared to the Galaxy. We interpret our results to mean that te size distribution of the interstellar grains, and not only the carbon abundance, is different in the SMC as compared to the Galaxy. In Paper 2 we present dust model fits to these observations.

Magalhaes, A. M.↗
NASA NTRS1980

Advanced communications satellites

The increase in demand for satellite communications services brought about shortages in available transponder capacity, especially at C-band. Interest shifted to the Ku-band frequency and currently carriers are rapidly moving to secure orbital slots for future satellite development. Projections of communications service demands over the next decade indiate growth in voice, data, and video services such that saturation of both C-band and Ku-band will occur by 1990. Emphasis must and will shift to Ka-band (20/30 GHz) frequency for fixed-satellite service. Advanced technologies such as multibeam antennas coupled with on-board satellite switching to allow implementation in this band of very high capacity satellite systems will be applied to meet the demand. Satellite system concepts that are likely in the 1990's and are likely to bring a new dimension to satellite delivered communication service are presented. The NASA 30/20 GHz communications satellite system demonstration program is discussed with emphasis on the related technology development.

Sivo, J. N.↗