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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Simulation of Wake Vortex Radiometric Detection via Jet Exhaust Proxy

This paper describes an analysis of the potential of an airborne hyperspectral imaging IR instrument to infer wake vortices via turbine jet exhaust as a proxy. The goal was to determine the requirements for an imaging spectrometer or radiometer to effectively detect the exhaust plume, and by inference, the location of the wake vortices. The effort examines the gas spectroscopy of the various major constituents of turbine jet exhaust and their contributions to the modeled detectable radiance. Initially, a theoretical analysis of wake vortex proxy detection by thermal radiation was realized in a series of simulations. The first stage used the SLAB plume model to simulate turbine jet exhaust plume characteristics, including exhaust gas transport dynamics and concentrations. The second stage used these plume characteristics as input to the Line By Line Radiative Transfer Model (LBLRTM) to simulate responses from both an imaging IR hyperspectral spectrometer or radiometer. These numerical simulations generated thermal imagery that was compared with previously reported wake vortex temperature data. This research is a continuation of an effort to specify the requirements for an imaging IR spectrometer or radiometer to make wake vortex measurements. Results of the two-stage simulation will be reported, including instrument specifications for wake vortex thermal detection. These results will be compared with previously reported results for IR imaging spectrometer performance.

Daniels, Taumi S.↗
NASA NTRS2016

Editorial Introduction: Lunar Reconnaissance Orbiter, Part II

The Lunar Reconnaissance Orbiter (LRO) mission has shifted our understanding of the history of the Moon. The seven instruments on LRO each have contributed to creating new paradigms for the evolution of the Moon by providing unprecedented measurements of the surface, subsurface, and lunar environment. In this second volume of the LRO Special Issue, we present 21 papers from a broad range of the areas of investigation from LRO, from the volatile inventory, to the shape of the Moon's surface, to its rich volcanic history, and the interactions between the lunar surface and the space environment. These themes provide rich science for the instrument teams, as well as for the broader science com- munity who continue to use the LRO data in their research. Each paper uses publicly available data from one or more instruments on LRO, illustrating the value of a robust spacecraft. For example, the production of high-resolution topographic data products from the LRO Camera Narrow Angle Camera (Henriksen et al., pp. 122-137, this issue) rely on the accurate geodetic grid produced by the LOLA instrument (Mao et al., pp. 55-69, this issue; Smith et al., pp. 70-91, this issue). Additionally, analysis of LRO data coupled with other spacecraft data, such as LADEE (Hurley et al., pp. 31-37, this issue) and GRAIL (e.g., Jozwiak et al., pp. 224-231, this issue) illustrate the utility of merging not only data from multiple instruments, but also multiple orbital platforms. These synergistic studies show the value of the inter-team approach adopted by the LRO mission. This second volume represents the culmination of an extensive effort to highlight the high-quality science still being produced by the LRO instrument teams, even after more than seven years in orbit at the Moon.

Petro, Noah E.↗
NASA NTRS2015

NASA Software Cost Estimation Model: An Analogy Based Estimation Model

The cost estimation of software development activities is increasingly critical for large scale integrated projects such as those at DOD and NASA especially as the software systems become larger and more complex. As an example MSL (Mars Scientific Laboratory) developed at the Jet Propulsion Laboratory launched with over 2 million lines of code making it the largest robotic spacecraft ever flown (Based on the size of the software). Software development activities are also notorious for their cost growth, with NASA flight software averaging over 50% cost growth. All across the agency, estimators and analysts are increasingly being tasked to develop reliable cost estimates in support of program planning and execution. While there has been extensive work on improving parametric methods there is very little focus on the use of models based on analogy and clustering algorithms. In this paper we summarize our findings on effort/cost model estimation and model development based on ten years of software effort estimation research using data mining and machine learning methods to develop estimation models based on analogy and clustering. The NASA Software Cost Model performance is evaluated by comparing it to COCOMO II, linear regression, and K-­ nearest neighbor prediction model performance on the same data set.

Hihn, Jairus↗
NASA NTRS2017

Early Estimation of Solar Activity Cycle: Potential Capability and Limits

The variable solar magnetic activity known as the 11-year solar cycle has the longest history of solar observations. These cycles dramatically affect conditions in the heliosphere and the Earth's space environment. Our current understanding of the physical processes that make up global solar dynamics and the dynamo that generates the magnetic fields is sketchy, resulting in unrealistic descriptions in theoretical and numerical models of the solar cycles. The absence of long-term observations of solar interior dynamics and photospheric magnetic fields hinders development of accurate dynamo models and their calibration. In such situations, mathematical data assimilation methods provide an optimal approach for combining the available observational data and their uncertainties with theoretical models in order to estimate the state of the solar dynamo and predict future cycles. In this presentation, we will discuss the implementation and performance of an Ensemble Kalman Filter data assimilation method based on the Parker migratory dynamo model, complemented by the equation of magnetic helicity conservation and longterm sunspot data series. This approach has allowed us to reproduce the general properties of solar cycles and has already demonstrated a good predictive capability for the current cycle, 24. We will discuss further development of this approach, which includes a more sophisticated dynamo model, synoptic magnetogram data, and employs the DART Data Assimilation Research Testbed.

Kitiashvili, Irina N.↗
NASA NTRS2018

Item Retrieval as Utility Estimation

Retrieval systems have greatly improved over the last half century, estimating relevance to a latent user need in a wide variety of areas. One area that has not enjoyed such advancements is searching for items by attribute values, a common activity in e-commerce and science, particularly given numeric values. Existing item retrieval systems assume the user has a firm grasp of their own desires and can formulate a good Boolean or SQL-style query to retrieve items, as one would do with a database. A contrasting approach would be to estimate how well items match the user?s latent desires and return items ranked by this estimation. Towards this end, we present a retrieval model inspired by multi-criteria decision making theory, concentrating on numeric attributes. We evaluate our novel approach, the de-facto standard of Boolean retrieval, and several models proposed in the literature, in two user studies using Amazon Mechanical Turk. We use a competitive game to motivate test subjects and compare methods based on the results of the subjects? initial query and their success in the game. In our experiments, our new method signi cantly outperformed the others, whereas the Boolean approaches had the worst performance.

operations research↗
NASA NTRS2019

VEG-04: the Effects of Light Quality on Mizuna Mustard Growth, Nutritional Composition, and Organoleptic Acceptability for a Space Diet

Space crop production will be important in future long duration exploration missions to supplement the packaged diet with fresh bioactive nutrients. Plant care and the addition of fresh veggies to the diet may also have a role in astronaut well-being. Pick-and-eat salad crops are the best candidates for this near-term supplementation since they require minimal processing or preparation to add to meals. While light quality can strongly influence plant responses on Earth, the impacts of light quality on plant growth and composition in spaceflight remain unclear. The VEG-04 experiment uses two Veggie plant growth chambers on the International Space Station to simultaneously test different red: blue light ratios on the growth of Mizuna mustard, a leafy green salad crop. In addition to plant health and yield, the composition of key nutrients is assessed. Astronauts conduct on-board organoleptic evaluation of the fresh produce. Microbial food safety of returned produce is examined, and a Hazard Analysis Critical Control Point (HACCP) plan has been developed for this crop. VEG-04 consists of two experiments, one lasting 28 days with a single harvest, and the second lasting 56 days, with three cut-and-come-again harvests. These different scenarios provide an opportunity to test two production concepts, examine different fertilizers, monitor microbial changes over time for this crop, and assess potential impacts of interacting with plants on crew behavioral health and performance in spaceflight operations. In ground testing, plant growth was not significantly different across the different light treatments, however nutrient composition did differ significantly. Flight test results will be compared with ground data. This research was co-funded by NASA's Human Research Program and Space Biology in the ILSRA 2015 NRA call.

Massa, Gioia D.↗
NASA NTRS2019

Stress Induced Immune Dysregulation: A Continuum Spanning Antarctica Winterover, Spaceflight, and Terrestrial Patients

Spaceflight is a unique environment characterized by stress, microgravity, isolation, circadian misalignment, and radiation exposure and impacts immune health. Planned long duration missions to Mars are a top priority for NASA and mitigating the negative health consequences of spaceflight is particularly important. Terrestrial analogs are a vital aspect of spaceflight research since data from astronauts is limited and it is costly to receive samples from ISS. The most relevant ground analog would include station lifestyle, stress, disrupted circadian rhythms and isolation. This analysis compares various aspects of immune dysregulation in astronauts during long-duration orbital spaceflight to groundanalogs. Astronaut data were also compared to a clinical immunodeficiency population, shingles patients, to help interpret clinical risks during deep space missions. A comprehensive evaluation was performed across hypoxic interior Antarctica, normoxic coastal Antarctica, HERA, and astronauts which included plasma and mitogen stimulated cytokine profiles, T-cell function, and peripheral leukocyte distribution. A cross platform analysis was then performed to define in-flight immune alterations, determine analog appropriateness, and interpret clinical risk.

Krieger, Stephanie↗
NASA NTRS2021

Determining Planetary Boundary Layer Height by Micro-pulse Lidar with Validation by UAV Measurements

Planetary boundary layer height (PBLH) is often used to characterize the structure of the lower atmosphere. Aerosol lidar, a ground-based remote sensing method, provides the vertical distribution of aerosol at a high temporal resolution observation data, from which, the PBL structure and the position of the PBL top can be comprehensively studied. PBLH determination with lidar data depends primarily on the characteristic turbulent motions in the atmosphere and the geophysical location. However, lidar determination of PBLH over densely populated subtropical locations has rarely been discussed; thus, developing retrieval techniques suitable to these areas is necessary. In this study, four PBLH determination methods (Gradient, δ–threshold, Haar wavelet transform, and hybrid image processing) are applied to estimate the PBLH from lidar observations over an urban area in East Asia, and one—the Gradient method—relied on potential temperature measurements from an unmanned aerial vehicle (UAV) flights to validate our results. Our results indicate that a combination of the gradient method and δ-threshold method can provide better results, in terms of diurnal pattern, than using either method individually. Furthermore, the Haar wavelet and the Hybrid image processing can detect the PBL development comparably well, but both methods are dependent on their initial conditions and optimized algorithm settings. In addition, the accompanying UAV observations are conclusively shown to have a high degree of efficacy for validating the lidar data. This research highlights that a combination of PBLH determination methods can better describe the PBLH evolution throughout a day in some cases, while in others less common determination methods are proving useful, and a suite of retrieval methods should still be explored for precisely mapping the PBL in densely populated subtropical areas.

Yueh-Chen Wang↗
NASA NTRS2021

Effects of Energy Capture and Recovery on an N+3 Technology Level Reference Propulsion System

An initial, parametric study was performed to assess the benefits and drawbacks of waste heat recovery on a gas turbine engine. The NASA N+3 technology level reference propulsion system model, an advanced, single-aisle class, gas turbine engine was the baseline cycle. The amount of thermal energy removed from the high-energy core flow and transferred to lower-energy bypass or removed from the cycle was varied. Total pressure losses were included parametrically, as well as the effects of converting some of that thermal energy to work used within the cycle. Propulsion system thrust and thrust specific fuel consumption (TSFC) were minimally affected by total pressure losses or thermal energy removal from the core stream. However, total pressure losses in the bypass stream had significant thrust and TSFC penalties. Those penalties were partially offset if core thermal energy is transferred to the bypass stream. Core thermal energy converted to work for use within the engine cycle via a bottoming cycle showed significant thrust and TSFC benefits. In addition to these results, an engine dataset is also being made available. The dataset contains engine conditions (mass flow rate, total temperature and pressure, flow velocities, etc.) at four flight conditions (maximum climb limit, cruise, rolling takeoff and sea level static) that can be used for specific information to guide heat exchanger design to best realize these benefits with further research. The data set is a .csv (comma-separated values) file and is provided as a supplement to this report (available online from www.sti.nasa.gov).

propulsion↗
NASA NTRSDate not supplied

FAIR-ness Assessment of NASA’s Earth Observation System Data and Information System (EOSDIS)

This presentation addresses the challenge of evaluating a multi-disciplinary institutional network of data repositories in operation since 1994 against the relatively recent criteria that constitute FAIR (Findable, Accessible, Interoperable, Reusable) data. NASA’s Earth Observation System Data and Information System (EOSDIS), with its 12 discipline-based Distributed Active Archive Centers (DAACs), preceded the definition and popularization of FAIR by over two decades. An assessment is very useful to describe how well the FAIR principles are met and to identify any improvements needed. In 2020, A “self-assessment” of EOSDIS and DAACs was performed by the ESDIS Project staff and the DAACs from the points of view of human actionability and machine actionability. More recently, a draft of a Science Mission Directorate (SMP) Program Directive (SPD-41a) has been released by NASA Headquarters for comment, where it is recommended that all SMD-funded data should follow the FAIR principles. This presentation is timely to initiate community discussion within the Information Quality Cluster (IQC) of the Earth Science Information Partners (ESIP) and help strategize and develop implementation guidelines for EOSDIS and DAACs to conform to FAIR principles.

Remote sensing↗
NASA NTRS2023

Aurora Detection From Nighttime Lights for Earth and Space Science Applications

This research leverages data from the Day/Night Band (DNB) of the Visible Infrared Imaging Radiometer (VIIRS) instrument onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite. We demonstrate the value of mining the VIIRS DNB for aurora and describe our use of unsupervised machine learning to create a binary mask for aurora occurrence. This mask can be used to flag aurora-contaminated observations for NASA's nighttime lights products for Earth science applications. The identification of auroral regions can also be used for Space Weather applications, for example, for comparison with aurora forecast model and with other satellite- or ground-based aurora observations. The DNB is a broadband channel that is sensitive to wavelengths from 500 to 900 nm, which covers most of the visible light spectrum, and as the name implies, captures light even at night with a sensitivity at the nanowatt level. This band is suitable for aurora observations since the light emitted by the aurora tends to be dominated by emissions from atomic oxygen, resulting in a greenish glow at a wavelength of 557.7 nm, especially at an altitude of 110 km. This study compares the global nighttime derived aurora regions for 17 and 18 March with the NOAA Space Weather Prediction Center's (SWPC) probability product for the St. Patrick's Day geomagnetic storm in 2015. VIIRS sensors are slated to be added to the next generation of polar-orbiting operational satellites. Our novel automated approach to aurora identification opens up an efficient way to leverage this unique data source.

Aurora↗
NASA NTRSDate not supplied

Harnessing Large Language Models for Scientific Endeavors

The rapid proliferation of Large Language Models (LLMs) such as GPT, Bard, and Llama has revolutionized various sectors, including the scientific community. These models, with their potential to automate and augment tasks, are increasingly being recognized as both a valuable asset and a potential challenge in the realm of scientific research and data management. However, the current LLMs, primarily trained on general corpora, exhibit a limited understanding of scientific concepts and terminologies due to the lack of scientific corpus in their training data. Recognizing this gap, several groups are now advocating for the development of LLMs specifically tailored for scientific applications. A notable initiative in this direction is the Large Language Model effort initiated by NASA's CSDO. This endeavor aims to align LLM efforts across NASA’s Science Mission Directorate, develop a science-specific corpus and validation test set for model training, and create an encoder-only model for various downstream tasks. Moreover, the initiative also plans to develop a decoder-only model to explore the potential benefits and risks associated with a generative LLM for science. Lastly, the project aims to create a science evaluation suite, encompassing various categories of downstream scientific tasks, to serve as a benchmark for assessing the value of any LLM for future use. This presentation will provide an overview and current status of this ongoing initiative, highlighting its potential to reshape the use of LLMs in the scientific domain.

Rahul Ramachandran↗