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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 91 records · Page 5

Micromechanics-Based Computational Simulation of Ceramic Matrix Composites

Advanced high-temperature Ceramic Matrix Composites (CMC) hold an enormous potential for use in aerospace propulsion system components and certain land-based applications. However, being relatively new materials, a reliable design properties database of sufficient fidelity does not yet exist. To characterize these materials solely by testing is cost and time prohibitive. Computational simulation then becomes very useful to limit the experimental effort and reduce the design cycle time, Authors have been involved for over a decade in developing micromechanics- based computational simulation techniques (computer codes) to simulate all aspects of CMC behavior including quantification of scatter that these materials exhibit. A brief summary/capability of these computer codes with typical examples along with their use in design/analysis of certain structural components is the subject matter of this presentation.

Murthy, Pappu L. N.↗

The Next Frontier for Remote Sensing of Freshwater HABS: Utilizing Imaging Spectroscopy Data to Identify Cyanobacteria Bloom Types

Cyanobacteria Harmful Algal Blooms (HABs) and their associated toxicity are a concern for inland waters. Due to the extensive spatial coverage and frequent data availability of satellite-based sensors, multi-spectral remote sensing tools have demonstrated utility for monitoring, understanding, and managing these blooms. The next frontier is utilizing high spectral resolution imaging spectroscopy data, such as from NASA’s upcoming PACE, GLIMR, and SBG missions planned for this decade, which allow for the development of more sophisticated cyanobacteria detection algorithms. We evaluate the performance of cyanobacteria genera differentiation algorithms using precursor datasets in support of these upcoming hyperspectral missions. In situ measurements of lake optical, biological, chemical, and physical properties are used to characterize cyanobacteria blooms in hypereutrophic Clear Lake, CA, USA, which supports large, diverse algal and cyanobacteria populations. Data collection occurred during 12 field events in 2021-2022 across all seasons. Three field events were conducted concurrently with hyperspectral data acquisitions from the DESIS sensor on the International Space Station. The results of this study will support the development of future tools utilizing satellite-based imaging spectroscopy data to identify the cyanobacteria genera present in a bloom, and thus the potential for cyanotoxin production. This outcome – the ability to quickly characterize a cyanobacteria bloom at a low cost – will have enormous benefits for public health.

remote sensing↗

Environment of Space Interactions with Space Systems

The primary product of this research project was a computer program named SAVANT. This program uses the Displacement Damage Dose (DDD) method of calculating radiation damage to solar cells. This calculation method was developed at the Naval Research Laboratory, and uses fundamental physical properties of the solar cell materials to predict radiation damage to the solar cells. This means that fewer experimental measurements are required to characterize the radiation damage to the cells, which results in a substantial cost savings to qualify solar cells for orbital missions. In addition, the DDD method makes it easier to characterize cells that are already being used, but have not been fully tested using the older technique of characterizing radiation damage. The computer program combines an orbit generator with NASA's AP-8 and AE-8 models of trapped protons and electrons. This allows the user to specify an orbit, and the program will calculate how the spacecraft moves during the mission, and the radiation environment that it encounters. With the spectrum of the particles, the program calculates how they would slow down while traversing the coverglass, and provides a slowed-down spectrum.

Source record↗

Development of Methodology for Programming Autonomous Agents

A brief report discusses the rationale for, and the development of, a methodology for generating computer code for autonomous-agent-based systems. The methodology is characterized as enabling an increase in the reusability of the generated code among and within such systems, thereby making it possible to reduce the time and cost of development of the systems. The methodology is also characterized as enabling reduction of the incidence of those software errors that are attributable to the human failure to anticipate distributed behaviors caused by the software. A major conceptual problem said to be addressed in the development of the methodology was that of how to efficiently describe the interfaces between several layers of agent composition by use of a language that is both familiar to engineers and descriptive enough to describe such interfaces unambivalently

Erol, Kutluhan↗

High-Altitude Air Mass Zero Calibration of Solar Cells

Air mass zero calibration of solar cells has been carried out for several years by NASA Glenn Research Center using a Lear-25 aircraft and Langley plots. The calibration flights are carried out during early fall and late winter when the tropopause is at the lowest altitude. Measurements are made starting at about 50,000 feet and continue down to the tropopause. A joint NASA/Wayne State University program called Suntracker is underway to explore the use of weather balloon and communication technologies to characterize solar cells at elevations up to about 100 kft. The balloon flights are low-cost and can be carried out any time of the year. AMO solar cell characterization employing the mountaintop, aircraft and balloon methods are reviewed. Results of cell characterization with the Suntracker are reported and compared with the NASA Glenn Research Center aircraft method.

Woodyard, James R.↗

Analysis of defect structure in silicon. Characterization of SEMIX material. Silicon sheet growth development for the large area silicon sheet task of the low-cost solar array project

Statistically significant quantitative structural imperfection measurements were made on samples from ubiquitous crystalline process (UCP) Ingot 5848 - 13C. Important correlation was obtained between defect densities, cell efficiency, and diffusion length. Grain boundary substructure displayed a strong influence on the conversion efficiency of solar cells from Semix material. Quantitative microscopy measurements gave statistically significant information compared to other microanalytical techniques. A surface preparation technique to obtain proper contrast of structural defects suitable for quantimet quantitative image analyzer (QTM) analysis was perfected and is used routinely. The relationships between hole mobility and grain boundary density was determined. Mobility was measured using the van der Pauw technique, and grain boundary density was measured using quantitative microscopy technique. Mobility was found to decrease with increasing grain boundary density.

Natesh, R.↗

Characterization of solar-grade silicon produced by the SiF4-Na process

A process was developed for producing low cost solar grade silicon by the reaction between SiF4 gas and sodium metal. The results of the characterization of the silicon are presented. These results include impurity levels, electronic properties of the silicon after crystal growth, and the performance of solar photovoltaic cells fabricated from wafers of the single crystals. The efficiency of the solar cells fabricated from semiconductor silicon and SiF4-Na silicon was the same.

Sanjurjo, A.↗

Clock performance, reliability and cost interrelationships

Problems encountered by clock manufacturers in attempting to supply reasonably priced, reliable clocks for critical aerospace applications arise from the inherent technical difficulties of designing and fabricating equipment to provide performance at the limits of the state of the art in demanding environments. The difficulties are compounded by inconsistent and unstandardized specification practices, and by an emphasis on initial acquisition costs, rather than on life cycle costs. Conventional parts stress analyses, which do not provide a useful indication of the reliability of a clock, lead to increased parts costs for high performance aerospace clocks without comensurate benefits in improved reliability or performance. The characterization of clocks in terms of the mean time between resynchronizations, facilitates the estimation of life cycle costs and provides a means to evaluate clocks in a realistic fashion for specific systems applications.

Levine, M. W.↗

FY12 End of Year Report for NEPP DDR2 Reliability

This document reports the status of the NEPP Double Data Rate 2 (DDR2) Reliability effort for FY2012. The task expanded the focus of evaluating reliability effects targeted for device examination. FY11 work highlighted the need to test many more parts and to examine more operating conditions, in order to provide useful recommendations for NASA users of these devices. In order to develop these approaches, it is necessary to develop test capability that can identify reliability outliers. To do this we must test many devices to ensure outliers are in the sample, and we must develop characterization capability to measure many different parameters. For FY12 we increased capability for reliability characterization and sample size. We increased sample size by moving from loose devices to DIMMs with an approximate reduction of 20 to 50 times in terms of per DUT cost. By increasing sample size we have improved our ability to characterize devices that may be considered reliability outliers. This report provides an update on the effort to improve DDR2 testing capability. Although focused on DDR2, the methods being used can be extended to DDR and DDR3 with relative ease.

temperature stress↗

LANDSAT D position determination and correction study

An assessment of accuracy of the knowledge of LANDSAT D spacecraft ephemeris data, an evaluation of the impact of expected attitude and alignment accuracies and analysis of the various options for the combining of precision ephemeris and attitude data with scene image data are provided. The potential geometric correction system in order to determine overall system costs and impact on other system elements is characterized.

Source record↗

Mechanical properties of a fiberglass prepreg system at cryogenic and other temperatures

The compressor driving the flow in the National Transonic Facility, which is nearing completion at the Langley Research Center, has 25 fiberglass blades. E-glass cloth with a pre-impregnated epoxy resin has been selected as the material for the fan blades because of its low cost, high damping, and fatigue resistance. A complete characterization is presented of this fan blade fiberglass system at temperatures of 367 K, room temperature, and 89 K. The characterization test results suggest that the material follows the general trends of metals and other glass-reinforced plastics at cryogenic temperatures. A slight diminution in strength was observed at the elevated temperature. The tests included the following: tensile, compression, fatigue, inplane shear, interlaminar shear, thermal expansion, creep, and thermal cycle.

Klich, P. J.↗

Are Current SEE Test Procedures Adequate for Modern Devices and Electronics Technologies?

Believe it or not, this has been a simplistic look at starting a checklist for SEE testing. Given a memory that has 68 operating modes, when a SEU occurs that changes the mode, just how do you determine what's going on? Laser and microbeam tests can help, but not easily for modern packaged devices. Expanding this approach to other more complex devices such as ADCs or processors as well as analog devices should be considered. The recommendation is to use the existing text standards as the starting point. Just make your own checklist for the device/technology/issues being considered. At HEART 2007, we presented some of the burgeoning challenges associated with single event effect(SEE) testing of modern commercial memories: a) Package, device complexity, test fixture, and data analysis issues were discussed; b) "Complete" SEE Characterization would take 15 years; c) Qualification test costs have a greater than 4 times increase over the last decade. In this talk, we continue to explore the roles of technology with an emphasis on the existing SEE Test Procedures and some of the concerns related to modern devices. The primary objective of the briefing is to provide some overarching guidance concerning the many considerations involved in the formulation of a SEE test plan provided in a " Checklist" format.we note that there is no such thing as a complete check list and that the best approach is to develop a flexible test plan that takes into account the device type and functions, the device technology, circuit and package design, and, of course, test facility and beam characteristics.

LaBel, Kenneth A.↗

Photothermal characterization of encapsulant materials for photovoltaic modules

A photothermal test matrix and a low cost testing apparatus for encapsulant materials of photovoltaic modules were defined. Photothermal studies were conducted to screen and rank existing as well as future encapsulant candidate materials and/or material formulations in terms of their long term physiochemical stability under accelerated photothermal aging conditions. Photothermal characterization of six candidate pottant materials and six candidate outer cover materials were carried out. Principal products of photothermal degradation are identified. Certain critical properties are also monitored as a function of photothermal aging.

Liang, R. H.↗

Characterization of Forested Landscapes From Remotely Sensed Data Using Fractals and Spatial Autocorrelation

The characterization of forested areas is frequently required in resource management practice. Passive remotely sensed data, which are much more accessible and cost effective than are active data, have rarely, if ever, been used to characterize forest structure directly, but rather they usually focus on the estimation of indirect measurement of biomass or canopy coverage. In this study, some spatial analysis techniques are presented that might be employed with Landsat TM data to analyze forest structure characteristics. A case study is presented wherein fractal dimensions, along with a simple spatial autocorrelation technique (Moran s I), were related to stand density parameters of the Oakmulgee National Forest located in the southeastern United States (Alabama). The results of the case study presented herein have shown that as the percentage of smaller diameter trees becomes greater, and particularly if it exceeds 50%, then the canopy image obtained from Landsat TM data becomes sufficiently homogeneous so that the spatial indices reach their lower limits and thus are no longer determinative. It also appears, at least for the Oakmulgee forest, that the relationships between the spatial indices and forest class percentages within the boundaries can reasonably be considered linear. The linear relationship is much more pronounced in the sawtimber and saplings cases than in samples dominated by medium sized trees (poletimber). In addition, it also appears that, at least for the Oakmulgee forest, the relationships between the spatial indices and forest species groups (Hardwood and Softwood) percentages can reasonably be considered linear. The linear relationship is more pronounced in the forest species groups cases than in the forest classes cases. These results appear to indicate that both fractal dimensions and spatial autocorrelation indices hold promise as means of estimating forest stand characteristics from remotely sensed images. However, additional work is needed to confirm that the boundaries identified for Oakmulgee forest and the linear nature of the relationship between image complexity indices and forest characteristics are generally evident in other forests. In addition, the effects of other parameters such ,as topographic relief and image distortion due to sun angle and cloud cover, for example, need to be examined.

Al-Hamdan, Mohammad Z.↗

Cost-effective technology advancement directions for electric propulsion transportation systems in earth-orbital missions

The directions that electric propulsion technology should take to meet the primary propulsion requirements for earth-orbital missions in the most cost effective manner are determined. The mission set requirements, state of the art electric propulsion technology and the baseline system characterized by it, adequacy of the baseline system to meet the mission set requirements, cost optimum electric propulsion system characteristics for the mission set, and sensitivities of mission costs and design points to system level electric propulsion parameters are discussed. The impact on overall costs than specific masses or costs of propulsion and power systems is evaluated.

Regetz, J. D., Jr.↗

Using Deep Learning to Automate Inference of Meteoroid Pre-Entry Properties

Properly assessing the asteroid threat depends on the knowledge of asteroid pre-entry parameters, such as size, velocity, mass, density, and strength. Although a vast number of possible bodies to study exist, such characterization of asteroid populations is currently limited by substantial costs associated with space rendezvous missions and rare meteorite findings. As asteroids fragment, ablate, and decelerate in the atmosphere, they emit light detectable by ground-based and space-borne instruments. Earth’s atmosphere, thus, becomes an accessible laboratory that enables impactor risk assessments by facilitating inference of the pre-entry parameters. These asteroid pre-entry conditions are typically deduced by modeling the entry and breakup physics that best reproduce the observed light or energy deposition curve. However, this process requires extensive manual trial-and-error of uncertain modeling parameters. Automating meteor modeling and inference would improve property distributions used in risk assessments and enable population characterization as more light curves become more readily available through the presence of space assets and ground-based camera networks. We previously developed a genetic algorithm to automate meteor modeling by using the fragment-cloud model (FCM) to search for the values of the FCM input parameters (e.g., diameter) that generate energy deposition profiles that match the observed one. Now, we apply deep learning to infer asteroid diameter, velocity, and density from observed energy deposition curves. We trained and tested our neural network models with synthetic energy deposition curves modeled using the FCM rubble pile implementation. We present an application of a 1D convolutional neural network and compare its performance to other attempted regressors and machine learning techniques, such as a fully connected neural network and Random Forest regression, to demonstrate its capabilities. We validate our model weights and approach using the Chelyabinsk, Tagish Lake, Benešov, Košice, and Lost City meteors.

Tarano, Ana Maria↗

From Low-Cost Sensors to High-Quality Data: A Review of Challenges and Summary of Best Practices for Effectively Using Low-Cost Particulate Matter Mass Sensors

Low-cost sensors for particulate matter mass (PM) enable spatially dense, high temporal resolution measurements of air quality that traditional reference monitoring cannot. Low-cost PM sensors are especially beneficial in low and middle-income countries where few, if any, reference grade measurements exist and in areas where the concentration fields of air pollutants have significant spatial gradients. Unfortunately, low-cost PM sensors also come with a number of challenges that must be addressed if their data products are to be used for anything more than a qualitative characterization of air quality. The various PM sensors used in low-cost monitors are all subject to biases and calibration dependencies, corrections for which range from relatively straightforward(e.g. meteorology, age of sensor) to complex (e.g. aerosol source, composition, refractive index). The methods for correcting and calibrating these biases and dependencies that have been used in the literature likewise range from simple linear and quadratic models to complex machine learning algorithms. Here we review the needs and challenges when trying to get high-quality data from low-cost sensors. We also present a set of best practices to follow to obtain high-quality data from these low-cost sensors.

low-cost sensors↗

The role of NDE in ceramic turbine engine component development

A systematic approach to the use of nondestructive evaluation (NDE) throughout the ceramic engine component development cycle is necessary to achieve the high reliability required for turbine engine applications. Specifically, NDE techniques must be developed and applied to component design, development, fabrication, and test to ensure adequate materials characterization. This approach has the potential of reducing ceramic component cost by optimizing the initial design and eliminating unacceptable components early in the fabrication cycle. Although research NDE techniques have been developed that have the potential to solve the problems of ceramic component inspection, systematic application of these NDE techniques for inspection and process control has not yet occurred. The application of NDE techniques for both material characterization and flaw detection is discussed as well as an approach for applying NDE throughout the fabrication process to achieve highly reliable ceramic components.

Minter, Janet↗