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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Automated Tracking of Shallow Maritime Clouds on Geostationary Imagery to Extract Lifecycle Characteristics

Shallow moist convection is ubiquitous throughout the tropics and represents a key player in boundary layer processes. Satellites have provided many statistics on shallow clouds, such as size, structure, and geographical coverage, from static views of recurring cloud fields. But determining why certain cloud features appear and persist for different periods requires a time-evolving view of their behaviors. Geostationary satellites provide a unique opportunity to follow the time evolution of individual convective features, given their enhanced spatial and temporal sampling. A cloud-tracking tool was developed to identify properties of cloud lifecycle from the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2EX) field campaign of 2019. The mission conducted intensive sampling of shallow cumulus in the West Pacific Ocean, in tandem with Rapid Scan imagery from the Advanced Himawari Imager (AHI) on the Japan Meteorological Agency’s (JMA) Himawari-8 satellite. Shallow cumulus was segmented according to thresholds in 0.5-km visible reflectance and with blurring techniques. Despite being limited to daytime hours, the segmentations yielded the best resolution possible for capturing cloud initiation and decay. The tracking procedure is based on a computer vision package that includes Kalman filters for motion prediction, object overlap search, and the Hungarian (or Kuhn-Munkres) matching algorithm for track designation. AHI radiances available within the tracked cloud boundaries are assembled to form individual spectral histories. The resulting catalog provides thousands of cloud histories for domains measuring only a few degrees in latitude and longitude. We present an overview of the cloud-tracking tool, strategies to identify development stages from cloud tracks, and preliminary results that document cumulus lifecycle properties from satellite. The application of AHI 0.5-km reflectance has both strengths and limitations when attempting to track lifecycles of the smallest resolvable clouds. We show that by aggregating cloud tracks from a few case studies of CAMP2EX, we can discern differences in cloud lifetime and development according to ensembles selected from areas of interest. The results demonstrate an ability to quantify lifetimes and assess rates of change in cloud characteristics that are likely controlled by the surrounding environment and meteorology.

Cloud Tracking↗
NASA NTRS2023

Using the Potassium-Argon Laser Experiment (KArLE) to Date Ancient, Low-K Chondritic Meteorites

Several laboratories have been investigating the feasibility of in situ K-Ar dating for use in future landing planetary missions. One drawback of these laboratory demonstrations is the insufficient analogy of the analyzed analog samples with expected future targets. We present the results obtained using the K-Ar laser experiment (KArLE) on two old and K-poor chondritic samples, Pułtusk and Hvittis, as better lunar analogs. The KArLE instrument uses laser ablation to vaporize rock samples and quantifies K content by laser-induced breakdown spectroscopy (LIBS), Ar by quadrupole mass spectrometry (QMS), and ablated mass by laser profilometry. We performed 64 laser ablations on the chondrites to measure spots with a range of K 2 O and Ar content and used the data to construct isochrons to determine the chondrite formation age. The KArLE isochron ages on Pułtusk and Hvittis are 5059 ± 892 Ma and 4721 ± 793 Ma, respectively, which is within the uncertainty of published reference ages, and interpreted as the age of their formation. The uncertainty (2σ) on the KArLE ages obtained in this study is better than 20% (18% for Pułtusk and 17% for Hvittis). The precision, which compares our obtained ages to the reference ages, is also better than 20% (11% for Pułtusk and 4% for Hvittis). These results are encouraging for understanding the limits of this technique to measure ancient planetary samples and for guiding future improvements to the instrument.

Fanny Cattani↗
NASA NTRSDate not supplied

Automated Tracking of Shallow Maritime Clouds on Geostationary Imagery to Extract Lifecycle Characteristics

Shallow moist convection is ubiquitous throughout the tropics and represents a key player in boundary layer processes. Satellites have provided valuable insight on shallow clouds, such as size, structure, and geographical coverage, from static views of recurring cloud fields. But determining why certain cloud features appear and persist for different periods requires a time-evolving view of their behaviors. Geostationary satellites provide a unique opportunity to follow the time evolution of individual convective features, given their enhanced spatial and temporal sampling. A cloud-tracking tool was developed to identify properties of cloud lifecycle from the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2EX) field campaign of 2019. The mission conducted intensive sampling of shallow cumulus in the West Pacific Ocean, in tandem with Rapid Scan imagery from the Advanced Himawari Imager (AHI) on the Japan Meteorological Agency’s (JMA) Himawari-8 satellite. Shallow cumulus were segmented according to thresholds in 0.5-km visible reflectance and with blurring techniques. Despite being limited to daytime hours, the segmentations yielded the best resolution available for capturing cloud initiation, growth, and decay. The tracking procedure is based on a computer vision package that includes Kalman filters for motion prediction, object overlap search, and the Hungarian (or Kuhn-Munkres) matching algorithm for track designation. AHI radiances available within the tracked cloud boundaries are assembled to form individual spectral histories. The resulting catalog provides thousands of cloud histories for domains measuring only a few degrees in latitude and longitude. We present an overview of the cloud-tracking tool and its results for cloud fields sampled throughout CAMP2EX by the airborne P-3. Cloud tracks were selected from about 10 flights to form ensembles, specific groups of tracks occurring in a region with airborne sampling. Cloud lifecycle properties, including duration and maximum area, are calculated for all ensemble members, and analyzed for cloud behavior and P-3 coincidences. By following this strategy, we quantitatively assess the degree of airborne sampling for specific cloud classes defined by the lifecycle calculations. We can summarize which cloud classes had more sampling, the stage of development during sampling, and general differences in character (e.g., isolated congestus vs. cold-pool producer).

Cloud Tracking↗
DOE OSTI2020

Critical Infrastructure Classification via CNN-based Modeling and Image Analysis

With recent advances in the fields of satellite imagery and machine learning we now have the ability to develop explainable deep learning models that enhance critical infrastructure analysis. Funded through Idaho National Laboratory’s (INL) Laboratory Directed Research and Development (LDRD) office we are in the process of developing a deep learning model capable of identifying critical infrastructure facilities and embedded features within those facilities. Utilizing current limit of practice techniques in the machine learning areas of explainability and transfer learning our model, once complete, will have the capacity to be used on multiple different imagery data sets and produce results that not only classify critical infrastructure facilities, but also explain why a critical infrastructure facility was classified as a certain type of facility. These advancements eliminate the ‘black box’ approach deep learning models have had in the past, where a user will have to trust the conclusion of a model without understanding what reasoning when into the model’s classification process. They also expand a model’s usefulness, traditionally a deep learning model will have to use the same data set it was originally trained on. Given the long training times of deep learning models this is impractical in a number of scenarios. By utilizing transfer learning advancements, we are eliminating the need to train our model on the same data set it is then run on to classify critical infrastructure facilities. We are also enabling the analysis and classification of data sets that are potentially too small to be divided into a training and testing data set. Once completed this model can provide a foundation to enhanced critical infrastructure analysis, dependency analysis, and potential disaster relief efforts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

CEFAS Poster for Advanced Manufacturing Workshop 3/26/24

Electric-field assisted sintering (EFAS) is an advanced manufacturing method for the consolidation and processing of ceramic and metal materials. It is a particularly excellent candidate for efficient materials processing as it has greater than 90% energy cost savings and improved CO2 emissions compared to traditional sintering in a furnace. This is due to direct rapid heating of the materials and molds leveraging an electrification phenomenon called Joule heating where electrical current is passed through the sample/mold assemblies causing direct heating. The technique does have limitations though as it is traditionally a batch-process and suffers from scale up difficulties. To overcome this, researchers at Idaho National Laboratory changed the form factor of traditional EFAS instruments to develop and construct a continuous rolling electric-field assisted sintering (CEFAS) device.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Comprehensive characterization of the structure of Zr-based metallic glasses

Structure of metallic glasses fascinates as the generic amorphous structural template for ubiquitous systems. Its specification necessitates determination of the complete hierarchical structure, starting from short-range-order (SRO) → medium-range-order (MRO) → bulk structure and free volume (FV) distribution. This link has largely remained elusive since previous investigations adopted one-technique-at-a-time approach, focusing on limited aspects of any one domain. Reconstruction of structure from experimental data inversion is non-unique for many of these techniques. As a result, complete and precise structural understanding of glass has not emerged yet. In this work, we demonstrate the first experimental pathway for reconstruction of the integrated structure, for and glasses. Our strategy engages diverse (×7) multi-scale techniques [XAFS, 3D-APT, ABED/NBED, FEM, XRD, PAS, FHREM] on the same glass. This strategy complemented mutual limitations of techniques and corroborated common parameters to generate complete, self-consistent and precise parameters. Further, MRO domain size and inter-void separation were correlated to identify the presence of FV at MRO boundaries. This enabled the first experimental reconstruction of hierarchical subset: SRO → MRO → FV → bulk structure. The first ever image of intermediate region between MRO domains emerged from this link. We clarify that determination of all subsets is not our objective; the essence and novelty of this work lies in directing the pathway towards finite solution, in the most logical and unambiguous way.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

NDE Methods and Capabilities Handbook - Resources for the Composites NDE Community

Composite structures are often difficult to inspect due to the anisotropic nature of the material systems and the range of flaws and defects that can arise in the manufacturing process. NASA’s Advanced Composites Project, a public-private partnership between government, universities and industry, sought to address improved methods, tools, and protocols to reduce the development and certification timeline for composite materials and structures. The rapid inspection of composites was one of the three focused research areas of the project. One deliverable of the project was to develop an NDE Methods and Capabilities Handbook. This Handbook provides a publicly available guidance document that facilitates the selection of appropriate NDE techniques and provides recommended protocols for detecting and characterizing common flaw types in solid laminate carbon fiber reinforced polymer composite (CFRP) structures. The Handbook seeks to reduce the time required to develop qualified inspection processes for composite aircraft structures during the development, certification, and manufacturing phases by providing a reference that helps minimize trial and error and provides guidance on best practices, techniques, and settings, for specific flaw types and geometries. Techniques include, but are not limited to ultrasound, laser based ultrasound, infrared thermography, and x-ray CT. Flaw types include, but are not limited to porosity, delaminations, voids, Automated Fiber Placement (AFP) defects and impact damage. The Handbook contains details such as inspection parameters, data analysis techniques, inspection efficiency and limitations. This paper describes key Handbook activities with examples of the techniques and flaw types examined by the Advanced Composite Consortium members. Availability to the NDE community of the fabricated NDE standards as well as the raw data collected on the standards by the Consortium members is discussed.

nondestructive evaluation↗
NASA NTRS1987

Detection of large-scale organized motions in a turbulent boundary layer

This paper presents and discusses experimental data from an investigation of organized motions in a supersonic turbulent boundary layer. Conditional sampling of crossed-wire and multiple normal-wire signals is performed. A comparison is made between events detected using the VITA conditional sampling technique and those found by thresholding the UV signal. Based on this comparison, limitations of the VITA technique are discussed. The conditional sampling results indicate that most organized motions are consistent with hairpin vortices.

Fernando, E. M.↗
NASA NTRSDate not supplied

NDE Methods and Capabilities Handbook - Resources for the Composites NDE Community

Composite structures are often difficult to inspect due to the anisotropic nature of the material systems and the range of flaws and defects that can arise in the manufacturing process. NASA’s Advanced Composites Project, a public-private partnership between government, universities and industry, sought to address improved methods, tools, and protocols to reduce the development and certification timeline for composite materials and structures. The rapid inspection of composites was one of the three focused research areas of the project. One deliverable of the project was to develop an NDE Methods and Capabilities Handbook. This Handbook provides a publicly available guidance document that facilitates the selection of appropriate NDE techniques and provides recommended protocols for detecting and characterizing common flaw types in solid laminate carbon fiber reinforced polymer composite (CFRP) structures. The Handbook seeks to reduce the time required to develop qualified inspection processes for composite aircraft structures during the development, certification, and manufacturing phases by providing a reference that helps minimize trial and error and provides guidance on best practices, techniques, and settings, for specific flaw types and geometries. Techniques include, but are not limited to ultrasound, laser based ultrasound, infrared thermography, and x-ray CT. Flaw types include, but are not limited to porosity, delaminations, voids, Automated Fiber Placement (AFP) defects and impact damage. The Handbook contains details such as inspection parameters, data analysis techniques, inspection efficiency and limitations. This presentation will describe key Handbook activities with examples of the techniques and flaw types examined by the Advanced Composite Consortium members. Availability to the NDE community of the fabricated NDE standards as well as the raw data collected on the standards by the Consortium members is discussed.

Nondestructive Evaluation↗
NASA NTRS2005

Non-contact Creep Resistance Measurement for Ultra-High Temperature Materials

Conventional techniques for measuring creep are limited to about 1700 C, so a new technique is required for higher temperatures. This technique is based on electrostatic levitation (ESL) of a spherical sample, which is rotated quickly enough to cause creep deformation by centrifugal acceleration. Creep of samples has been demonstrated at up to 2300 C in the ESL facility at NASA MSFC, while ESL itself has been applied at over 3000 C, and has no theoretical maximum temperature. The preliminary results and future directions of this NASA-funded research collaboration will be presented.

Lee, J.↗
NASA NTRS2019

Analysis of WFPC-2 Core Samples for MMOD Discrimination

An examination of the Hubble Space Telescope Wide Field Planetary Camera 2 (WFPC-2) radiator assembly was conducted at NASA Goddard Space Flight Center during the summer of 2009. Immediately apparent was the predominance of impact features, identified as simple or complex craters, resident only in the thermal paint layer; similar features were observed during a prior survey of the WFPC-1 radiator. Larger impact features displayed spallation zones, darkened areas, and other features not observed in impacts onto bare surfaces. Craters were extracted by coring the radiator in the NASA Johnson Space Center’s Space Exposed Hardware cleanroom and were subsequently examined using scanning electron microscopy/energy dispersive X-ray spectroscopy to determine the likely origin, e.g., micrometeoritic or orbital debris, of the impacting projectile. Recently, a selection of large cores was re-examined using a new technique developed to overcome some limitations of traditional crater imaging and analysis. This technique, motivated by thin section analysis, examines a polished, lateral surface area revealed by cross-sectioning the core sample. This paper reviews the technique, the classification rubric as extended by this technique, and results to date.

Anz-Meador, P.↗
NASA NTRS1989

Multiplex gas chromatography: an alternative concept for gas chromatographic analysis of planetary atmospheres

Gas chromatography (GC) is a powerful technique for analyzing gaseous mixtures. Applied to the earth's atmosphere, GC can be used to determine the permanent gases--such as carbon dioxide, nitrogen, and oxygen--and to analyze organic pollutants in air. The U.S. National Aeronautics and Space Administration (NASA) has used GC in spacecraft missions to Mars (the Viking Biology Gas Exchange Experiment [GEX] and the Viking Gas Chromatograph-Mass Spectrometer [GC-MS]) and to Venus (the Pioneer Venus Gas Chromatograph [PVGC] on board the Pioneer Venus sounder probe) for determining the atmospheric constituents of these two planets. Even though conventional GC was very useful in the Viking and Pioneer missions, spacecraft constraints and limitations intrinsic to the technique prevented the collection of more samples. With the Venus probe, for instance, each measurement took a relatively long time to complete (10 min), and successive samples could not be introduced until the previous samples had left the column. Therefore, while the probe descended through the Venusian atmosphere, only three samples were acquired at widely separated altitudes. With the Viking mission, the sampling rate was not a serious problem because samples were acquired over a period of one year. However, the detection limit was a major disadvantage. The GC-MS could not detect simple hydrocarbons and simple alcohols below 0.1 ppm, and the GEX could not detect them below 1 ppm. For more complex molecules, the detection limits were at the parts-per-billion level for both instruments. Finally, in both the Viking and Pioneer missions, the relatively slow rate of data acquisition limited the number of analyses, and consequently, the amount of information returned. Similar constraints are expected in future NASA missions. For instance, gas chromatographic instrumentation is being developed to collect and analyze organic gases and aerosols in the atmosphere of Titan (one of Saturn's satellites). The Titan-Cassini entry probe, which is being jointly planned by NASA and the European Space Agency (ESA), might be launched as early as 1994. As in the Pioneer mission, limited time--perhaps only 3-4 h--will be available for the completion of all analyses while the probe descends through the atmosphere. A conventional GC or GC-MS system would be able to analyze no more than two aerosol and two gas samples during the probe's descent. Conventional GC also is limited by the sensitivity of the detector and by the sample volume. For the Titan mission, the sensitivity problems will be worse because the atmospheric pressure at the time of instrument deployment is expected to be < 3 torr. Consequently, the sample volume might not be large enough to satisfy the detector sensitivity requirements. Because of such limitations, alternative GC analysis techniques have been investigated for future NASA missions. Multiplex gas chromatography has been investigated as a possible candidate for chemical analysis within a spacecraft or other restricted environment, and chemical modulators have been developed and used when needed with this technique to reduce the size and weight of the instrumentation. Also, several new multiplex techniques have been developed for use in specific applications.

NASA Center ARC↗
NASA NTRS1980

An assessment of ground-based techniques for detecting other planetary systems. Volume 1: An overview

The feasibility and limitations of ground-based techniques for detecting other planetary systems are discussed as well as the level of accuracy at which these limitations would occur and the extent to which they can be overcome by new technology and instrumenation. Workshop conclusions and recommendations are summarized and a proposed high priority program is considered.

Black, D. C.↗
NASA NTRS2014

A Comparison of Fabrication Techniques for Hollow Retroreflectors

Despite the wide usage of hollow retroreflectors, there is limited literature involving their fabrication techniques and only two documented construction methods could be found. One consists of an adjustable fixture that allows for the independent alignment of each mirror, while the other consists of a modified solid retroreflector that is used as a mandrel. Although both methods were shown to produce hollow retroreflectors with arcsecond dihedral angle errors, a comparison and analysis of each method could not be found which makes it difficult to ascertain which method would be better suited to use for precision-aligned retroreflectors. Although epoxy bonding is generally the preferred method to adhere the three mirrors, a relatively new method known as hydroxide-catalysis bonding (HCB) presents several potential advantages over epoxy bonding. HCB has been used to bond several optical components for space-based missions, but has never been applied for construction of hollow retroreflectors. In this paper we examine the benefits and limitations of each bonding fixture as well as present results and analysis of hollow retroreflectors made using both epoxy and HCB techniques.

optics↗
DOE OSTI2025

Small-Signal Stability of Grid-Forming Inverters Using Current-Limiting and Frequency Stabilization

This paper presents a small-signal stability analysis of grid-forming (GFM) inverters under current-limiting conditions. It examines how adjustments in virtual impedance angles, implemented through advanced current-limiting and frequency stabilization techniques, influence small-signal stability. This paper studies a GFM inverter control integrating a fictitious power technique stabilizing primary control by adding a virtual power term and a hybrid current limiter integrating virtual impedance in the anti-wind-up feedback with current reference saturation limiting. A small-signal model is developed to assess the impact of virtual impedance angles on GFM inverter dynamics during grid disturbances, such as voltage drops. The findings indicate that although increasing the virtual impedance angle (to make it more inductive) enhances large-signal stability and voltage support during faults, it can induce oscillations and lead to instability if the angle exceeds certain thresholds. Based on the small-signal models, this paper provides design considerations for the current-limiter impedances to ensure reliable GFM inverter behavior under grid disturbances while maintaining small-signal stability.

current limiting↗
NASA NTRS1989

A search for a dynamical attractor in Cygnus X-1

A method used for searching for low-dimensional attractors in fluctuating signals is applied to the aperiodicity observed in Cyg X-1. The analysis technique for determining the dimension of an attractor given its light curve, and the practical limitations in applying the technique, are described. The requirement of large amounts of low-noise data is found to be very important in using the technique. No low-dimensional attractor is found for the set of Cyg X-1 data used, but evidence of an attractor with large dimension may be present.

Lochner, James C.↗
DOE OSTI2020

Overcoming small minirhizotron datasets using transfer learning

Minirhizotron technology is widely used to study root growth and development. Yet, standard approaches for tracing roots in minirhiztron imagery is extremely tedious and time consuming. Machine learning approaches can help to automate this task. However, lack of enough annotated training data is a major limitation for the application of machine learning methods. Transfer learning is a useful technique to help with training when available datasets are limited. In this paper, we investigated the effect of pre-trained features from the massives-cale, irrelevant ImageNet dataset and a relatively moderate-scale, but relevant peanut root dataset on switchgrass root imagery segmentation applications. We compiled two minirhizotron image datasets to accomplish this study: one with 17,550 peanut root images and another with 28 switchgrass root images. Both datasets were paired with manually labeled ground truth masks. Deep neural networks based on the U-net architecture were used with different pre-trained features as initialization for automated, precise pixel-wise root segmentation in minirhizotron imagery. We observed that features pre-trained on a closely related but relatively moderate size dataset like our peanut dataset were more effective than features pre-trained on the large but unrelated ImageNet dataset. Here, we achieved high quality segmentation on peanut root dataset with 99.04% accuracy at the pixel-level and overcame errors in human-labeled ground truth masks. By applying transfer learning technique on limited switchgrass dataset with features pre-trained on peanut dataset, we obtained 99% segmentation accuracy in switchgrass imagery using only 21 images for training (fine tuning). Furthermore, the peanut pre-trained features can help the model converge faster and have much more stable performance.

59 BASIC BIOLOGICAL SCIENCES↗