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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Wavelet Analysis of Satellite Images for Coastal Watch

The two-dimensional wavelet transform is a very efficient bandpass filter, which can be used to separate various scales of processes and show their relative phase/location. In this paper, algorithms and techniques for automated detection and tracking of mesoscale features from satellite imagery employing wavelet analysis are developed. The wavelet transform has been applied to satellite images, such as those from synthetic aperture radar (SAR), advanced very-high-resolution radiometer (AVHRR), and coastal zone color scanner (CZCS) for feature extraction. The evolution of mesoscale features such as oil slicks, fronts, eddies, and ship wakes can be tracked by the wavelet analysis using satellite data from repeating paths. Several examples of the wavelet analysis applied to various satellite Images demonstrate the feasibility of this technique for coastal monitoring.

Liu, Antony K.↗
DOE OSTI2012

High Performance Computing Productivity Study - Evaluation of Parallel Tools Platform (PTP) Eclipse Plug-In

This report is a DARPA funded Work For Others (WFO) evaluation of the Parallel Tools Platform (PTP) version 5.0.3 (Released October 18, 2011). PTP is currently being developed and supported as an open source product managed by Project Lead Greg Watson and team at IBM plus several other contributors. The tool has been in development since 2005 with a goal of providing an infrastructure for the integration of high performance computing tools. Basic functionality such as source code editing, compiling, launching, and debugging, plus more advanced features including performance monitoring and deployment have been bundled into an Eclipse Integrated Development Environment (IDE) plug-in to give parallel application programmers the features and improved productivity gained from using a common, well established development platform. The evaluation encompasses the basic aspects of using PTP, beginning with the installation and configuration of the plug-in, followed by code development and debugging. Each aspect is evaluated based on the expectations of my experience as an Eclipse user and is presented in the following format: • Feature description • User Experience • Evaluation The feature description is based on the provided documentation for PTP and the ‘generic’ expectations of what the feature should provide. The user experience reveals the actual use and exercise of the feature – specifically in the context and perspective of the evaluation platform provided by Lawrence Livermore National Laboratory. The evaluation of each feature includes the overall outcome of the user experience, along with the expectations that were not met, met, or exceeded along with any issues that were encountered.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Chemometric modeling of power conversion efficiency of organic dyes in dye sensitized solar cells for the future renewable energy

The present study reports chemometric modeling of power conversion efficiency (PCE) of dye sensitized solar cells (DSSCs) using the biggest available data set till date which comprises around 1200 dyes covering 7 chemical classes. To extract the best structural features required for higher PCE, we have developed multiple partial least squares (PLS) quantitative structure-property relationship (QSPR) models for the Triphenylamine, Phenothiazine, Indoline, Porphyrin, Coumarin, Carbazole and Diphenylamine chemical classes using descriptors derived from the best subset selection method followed by selection of best five models in each dataset based on the Mean Absolute Error (MAE) values. The models were validated both internally and externally followed by the consensus predictions employing “Intelligent Consensus Predictor” tool to examine whether the quality of predictions can be improved with the “intelligent” selection of multiple PLS models. The quality of predictions for the respective external sets showed that the consensus models (CM) are better than the individual models (IM) in most of the cases. From the insights of the developed models, we concluded that attributes like a packed structure toward higher conductivity of electrons, auxiliary donor fragment of aromatic tertiary amines, number of thiophenes inducing the bathochromic shift and augmenting the absorption, presence of additional electron donors, enhancement of electron-donating abilities, number of non-aromatic conjugated C(sp 2 ) which helps as conjugation extension units to broaden the absorption and highly conjugated $π$-systems exert positive contributions to the PCE. On the contrary, features negatively contributing to PCE are the followings: fragments which lower the tendency of localized $π–π*$ transition, fragments related to larger volume and surface area of dyes along with hydrophobicity resulting in poor adhesion, fragment RC = N causing dye hydrolysis, steric hindrance for π electronic mobility, fragments enhancing polarity, etc. Finally, the identified features from the best QSPR model of the coumarin dataset was employed in designing of ten more efficient coumarin dyes (predicted %PCE ranging from 8.93 to 10.62) than the existing ones.

14 SOLAR ENERGY↗
DOE OSTI2024

High-Fidelity Multiphysics Modeling of a Heat Pipe Microreactor Using BlueCrab

Researchers who are actively developing nuclear microreactors are planning to employ innovative designs and features using traditional commercial modeling tools that may be inadequate for their design and licensing activities. The codes developed under the U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) program provide flexibility in terms of geometry modeling and multiphysics coupling and are particularly well suited for modeling novel microreactor concepts. To test the maturity of these codes, this paper introduces a conceptual heat pipe microreactor (HP-MR) designed to gather various technologies of interest to microreactor developers such as control drums, heat pipes, and hydride moderators. Here, the objective of this effort is to demonstrate NEAMS tools capability to perform high-fidelity multiphysics simulations, using coupled neutronics (via the Griffin code), heat conduction (via the BISON code), heat pipe modeling (via the Sockeye code), and hydrogen redistribution in hydride metal moderator (via the SWIFT code). Codes are coupled in-memory through the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, which permits flexible multiphysics data transfer schemes. The analysis confirmed two key aspects of the HP-MR concept: (1) its ability to follow the power load requested from the heat pipe and (2) its ability to avoid heat pipe cascading failure unless designed with high power close to operating failure limits of its heat pipes. The developed computational model was distributed publicly on the Virtual Test Bed for training purposes to accelerate adoption by industry and to provide a high-fidelity multiphysics solution for benchmarking against other tools. Additional multiphysics analyses including other transients and coupled physics were identified as necessary future work, together with a focus on validating multiphysics behavior against experiments.

Microreactor↗
DOE OSTI2020

Process Image Analysis using Big Data, Machine Learning, and Computer Vision

The development of algorithms for machine learning and data analysis for the 3013 MIS corrosion surveillance program is a collaborative effort by SRNL, USC and GT. For corrosion detection, LCM image data is extracted from large binary files, with software written to convert the data to physical attributes (i.e. height, color and grayscale values; all as functions of a location in a plane projection). The user interface for the software permits selective downloading of binary data and interrogation of attributes. User input thresholds are used to flag attributes of interest. Machine learning algorithms, developed for this application, are used to determine whether the features are the result of corrosion. To address the fundamental mechanisms of corrosion, machine learning algorithms are being developed to derive interatomic potential force-fields from ab-initio DFT calculations. The goal is to apply molecular modeling on a large enough scale to guide the design of resistant materials.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Tailored Microstructure and Properties in UO{sub 2}

Advanced fuels with enhanced safety margin and accident tolerance are of vital importance for safe operation of current light water reactor fleet and the development of future reactor systems. The current UO{sub 2} fuel for LWRs has low thermal conductivity, which will be further reduced upon burn-up. The intrinsically low thermal transfer efficiency of the oxide fuels results in a large temperature gradient within the fuel pellet and high center-line temperature. Thermal swelling of the pellets and fission product accommodation and retention limit the lifetime of UO{sub 2} fuel in the reactor, presenting the great challenges for extending burn-up, effective utilization of nuclear resources and minimization of nuclear waste accumulation. Critical needs also exist in developing accident tolerant fuels that can tolerate loss of coolant accident or improve fuel performance under regular operation or beyond design scenario. Key properties of advanced fuels include high thermal conductivity, oxidation resistance, high temperature mechanical properties, fission gas retention capability and thus improved accident tolerance. The US Nuclear Energy Advanced Modeling and Simulation (NEAMS) program is developing science-based next generation fuel performance modeling capability as part its Fuel Product Line in order to facilitate the predictive capability of nuclear fuel performance and assist the design and analysis of reactor systems. Critical experimental data are needed to validate MARMOT models, particularly on effective thermal transport, fracture mechanisms, grain growth kinetics and fission gas behavior. The fabrication of sintered fuel pellets with well-controlled microstructure is prerequisite to establish the correlation of the microstructure features and fuel behavior in order to develop high fidelity fuel performance models. In this talk, recent advancements on developing advanced UO{sub 2} fuels and properties improvement are overviewed with the emphasis on different accident tolerant fuel (ATF) concepts and tailoring microstructures for MARMOT validation. Current efforts on ATFs include composite fuels and high-density fuels to improve thermal-mechanical properties and fission gas retention capabilities. Different composite UO{sub 2} fuels are fabricated with heterogeneous phases as sintering additives for microstructure and property control, and the potential application of the composites as advanced fuels with enhanced accident tolerance will be discussed. In addition, recent progresses of using field-assisted sintering technologies, specifically spark plasma sintering (SPS), in tailoring and engineering fuel matrix as the target systems for validating MARMOT physics models will be highlighted. Particularly, monolithic UO{sub 2} with tailored microstructure including grain size across multiple length scales from nano-metered to micron-sizes, porosity and stoichiometry can be sintered. The impacts of tailored microstructure on thermal-mechanical properties and grain growth kinetics are discussed within the context of the MARMOT modeling. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2016

SLS Flight Software Testing: Using a Modified Agile Software Testing Approach

NASA's Space Launch System (SLS) is an advanced launch vehicle for a new era of exploration beyond earth's orbit (BEO). The world's most powerful rocket, SLS, will launch crews of up to four astronauts in the agency's Orion spacecraft on missions to explore multiple deep-space destinations. Boeing is developing the SLS core stage, including the avionics that will control vehicle during flight. The core stage will be built at NASA's Michoud Assembly Facility (MAF) in New Orleans, LA using state-of-the-art manufacturing equipment. At the same time, the rocket's avionics computer software is being developed here at Marshall Space Flight Center in Huntsville, AL. At Marshall, the Flight and Ground Software division provides comprehensive engineering expertise for development of flight and ground software. Within that division, the Software Systems Engineering Branch's test and verification (T&V) team uses an agile test approach in testing and verification of software. The agile software test method opens the door for regular short sprint release cycles. The idea or basic premise behind the concept of agile software development and testing is that it is iterative and developed incrementally. Agile testing has an iterative development methodology where requirements and solutions evolve through collaboration between cross-functional teams. With testing and development done incrementally, this allows for increased features and enhanced value for releases. This value can be seen throughout the T&V team processes that are documented in various work instructions within the branch. The T&V team produces procedural test results at a higher rate, resolves issues found in software with designers at an earlier stage versus at a later release, and team members gain increased knowledge of the system architecture by interfacing with designers. SLS Flight Software teams want to continue uncovering better ways of developing software in an efficient and project beneficial manner. Through agile testing, there has been increased value through individuals and interactions over processes and tools, improved customer collaboration, and improved responsiveness to changes through controlled planning. The presentation will describe agile testing methodology as taken with the SLS FSW Test and Verification team at Marshall Space Flight Center.

Bolton, Albanie T.↗
DOE OSTI2022

Highly Loaded Sulfur Cathode, Coated Separator and Gel Electrolyte for High Rate Li-Sulfur Batteries

As one of DOE Battery 500 Seedling projects, Cornell University and EIC Labs investigated and developed i) highly loaded sulfur cathodes (> 3 mg/cm 2 ), ii) hybrid separators, and iii) gel ceramic electrolytes (GCE) to mitigate the low rate capability, shuttling effect and limited cycle life in high performance Li-Sulfur batteries. Scalable nanomanufacturing processes such as air-controlled electrospray (ACES) and gas-assisted electrospinning (GAES) have been utilized to develop directly deposited electrodes and polymer/ceramic hybrid separators. First, in the development of highly loaded cathodes, alternating layers of sulfur impregnated mesoporous carbon and graphene were fabricated via ACES and the resulting layered cathodes and coated separators exhibit higher capacity and capacity retention (about 1,000 mAh/g capacity with less than 0.02% fade/cycles) than single layer cathode or cathode prepared by conventional slurry cast. Alternating layer approach via ACES has been applied to high loading systems (3 - 5 mg S/cm 2 ), demonstrating the potential to increase sulfur utilization and capacity retention. We have also incorporated iron oxides (Fe 3 O 4 ) into S/mesoporous carbon/graphene cathodes to enhance sulfur utilization and mitigation of polysulfide shuttling. and the effect of Fe 3 O 4 in mesoporous carbon and Gr is highly pronounced at high C rates of 1C and 2C cycling performance. To further improve the cathodes at high rates, graphene nanoribbons (GNR) which can promote ion transport were incorporated in the cathode, resulting in 550 mAh/g at 5C/5C rates. Hybrid Li-ion/Li-S cathodes has also been explored to better engage unreacted polysulfides during charge/discharge. S/LFP hybrid cathodes offer higher sulfur utilization and enhanced rate capability, as well as higher areal loading. This study suggests inclusion of iron phosphide (Fe2P) which can chemically interact with polysulfides can further enhance sulfur utilization and mitigation of soluble polysulfides at high rates. Secondly, in the development of hybrid separators, we first employed graphene coating on the commercial polyolefin separators, which exhibits higher capability, better capacity retention and enhanced rate capability. To improve the rate capability with enhanced safety features such as thermal stability and nonflammability, we developed polymer/ceramic hybrids based on thermally stable polyimide (PI) and room temperature curable ceramic precursors such as organopolysilazane (OPSZ) or polysilsesquioxanes (PSSQ), which exhibit no shrinkages up to 300 ºC and non-flammability. To improve mechanical properties and electrochemical stability, polybenzimidazole (PBI) and alumina have been incorporated in polymer/ceramic hybrid separator, replacing PI and OPSZ/PSSQ, respectively. Finally, the gel ceramic electrolyte (GCE) based on ceramic cross linkers have been applied to make Li-S cells even safer and also to mitigate the polysulfide shuttling further. The resulting gel ceramic electrolyte offers improved capacity retention and rate capability, and also effectively mitigates polysulfide shuttling which was also confirmed by modeling. Inclusion of high ion conducting additives into GCE together with polymer/ceramic hybrid separators exhibit the higher ionic conductivity than liquid electrolyte with commercial polyolefin separator. We demonstrated that the developed highly loaded sulfur cathodes, polymer/ceramic hybrid separators and gel ceramic electrolyte can effectively mitigate the low rate capability, shuttling effect and limited cycle life in high performance Li-Sulfur batteries with improved safety.

25 ENERGY STORAGE↗
NASA NTRS1979

Multiclass Bayes error estimation by a feature space sampling technique

A general Gaussian M-class N-feature classification problem is defined. An algorithm is developed that requires the class statistics as its only input and computes the minimum probability of error through use of a combined analytical and numerical integration over a sequence simplifying transformations of the feature space. The results are compared with those obtained by conventional techniques applied to a 2-class 4-feature discrimination problem with results previously reported and 4-class 4-feature multispectral scanner Landsat data classified by training and testing of the available data.

Mobasseri, B. G.↗
DOE OSTI2026

Machine Learning-Based Anomaly Detection for PMT Data Quality Monitoring in the SBN and DUNE

Maintaining high-quality detector data is essential for achieving the scientific objectives of the Short-Baseline Neutrino (SBN) Program at Fermilab. Current data quality monitoring (DQM) procedures rely primarily on threshold-based metrics and manual inspection of detector monitoring plots, making the detection of subtle or gradually developing anomalies both time-consuming and dependent on expert interpretation. This project developed and evaluated a machine-learning workflow for automatically identifying anomalous photomultiplier tube (PMT) channels in the Short-Baseline Near Detector (SBND) using optical-hit amplitude data. A Python-based analysis program was developed to process ROOT files, extract statistical features describing individual PMT amplitude distributions, and generate feature vectors for anomaly detection. These features were used to train an Isolation Forest model using data representing normal detector operation. The trained model was subsequently applied to independent detector runs to identify channels exhibiting statistically unusual behavior relative to the learned reference response. To support expert interpretation, the workflow generated complementary diagnostic products, including anomaly score distributions, normalized amplitude comparisons, decision-tree visualizations, and principal component analysis (PCA) projections. This project demonstrated the feasibility of integrating unsupervised machine learning into detector data-quality monitoring and developed a complete workflow for automated PMT performance assessment to aid expert-driven review. Beyond its technical contributions, the VFP appointment fostered a research collaboration between Aurora University and Fermilab and provided direct workforce development benefits by training the visiting faculty member in detector-scale machine-learning methods that are now being incorporated into undergraduate coursework and research. The methodology developed here provides a foundation for future applications to ProtoDUNE and other liquid argon time projection chamber (LArTPC) detectors, contributing to ongoing efforts to improve detector reliability, reduce manual monitoring requirements, and enable scalable data quality monitoring for future large-scale neutrino experiments, including the Deep Underground Neutrino Experiment (DUNE).

Colón Santana, Juan A. [Unlisted, US, IL]↗
DOE OSTI2016

CLUSTERING-BASED FEATURE LEARNING ON VARIABLE STARS

The success of automatic classification of variable stars depends strongly on the lightcurve representation. Usually, lightcurves are represented as a vector of many descriptors designed by astronomers called features. These descriptors are expensive in terms of computing, require substantial research effort to develop, and do not guarantee a good classification. Today, lightcurve representation is not entirely automatic; algorithms must be designed and manually tuned up for every survey. The amounts of data that will be generated in the future mean astronomers must develop scalable and automated analysis pipelines. In this work we present a feature learning algorithm designed for variable objects. Our method works by extracting a large number of lightcurve subsequences from a given set, which are then clustered to find common local patterns in the time series. Representatives of these common patterns are then used to transform lightcurves of a labeled set into a new representation that can be used to train a classifier. The proposed algorithm learns the features from both labeled and unlabeled lightcurves, overcoming the bias using only labeled data. We test our method on data sets from the Massive Compact Halo Object survey and the Optical Gravitational Lensing Experiment; the results show that our classification performance is as good as and in some cases better than the performance achieved using traditional statistical features, while the computational cost is significantly lower. With these promising results, we believe that our method constitutes a significant step toward the automation of the lightcurve classification pipeline.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2011

Standards and Specifications for Ground Processing of Space Vehicles: From an Aviation-Based Shuttle Project to Global Application

Proprietary or unique designs and operations are expected early in any industry's development, and often provide a competitive early market advantage. However, there comes a time when a product or industry requires standardization for the whole industry to advance...or survive. For the space industry, that time has come. Here, we will focus on standardization of ground processing for space vehicles and their ground systems. With the retirement of the Space Shuttle, and emergence of a new global space race, affordability and sustainability are more important now than ever. The growing commercialization of the space industry and current global economic environment are driving greater need for efficiencies to save time and money. More RLV's (Reusable Launch Vehicles) are being developed for the gains of reusability not achievable with traditional ELV's (Expendable Launch Vehicles). More crew/passenger vehicles are also being developed. All of this calls for more attention needed for ground processing-repeatedly before launch and after landing/recovery. RLV's should provide more efficiencies than ELV's, as long as MRO (Maintenance, Repair, and Overhaul) is well-planned-even for the unplanned problems. NASA's Space Shuttle is a primary example of an RLV which was supposed to thrive on reusability savings with efficient ground operations, but lessons learned show that costs were (and still are) much greater than expected. International standards and specifications can provide the commonality needed to simplify design and manufacturing as well as to improve safety, quality, maintenance, and operability. There are standards organizations engaged in the space industry, but ground processing is one of the areas least addressed. Challenges are encountered due to various factors often not considered during development. Multiple vehicle elements, sites, customers, and contractors pose various functional and integration difficulties. Resulting technical publication structures and methods are incongruent. Some processing products are still done on paper, some electronic, and many being converted in between. Business systems then are not fully compatible, and paper as well as electronic conversions are time-consuming and costly. NASA and its Shuttle contractors setup rules and systems to handle what has produced over 130 RLV launches, but they have had many challenges. Attempts have been made to apply aviation industry specifications to make the Shuttle more efficient with its ground processing. One efficiency project example was to make a Shuttle Maintenance Manual (SMM) based on the commercial ATA (Air Transport Association of America) Spec 100 for technical publications. This industry standard, along with others, has been a foundation for efficient global MRO of commercial airlines for years. A modified version was also made for some military aircraft. The SMM project found many similarities in Spec 100 which apply to the Shuttle, and room for expansion for space systems/structures not in aircraft. The SMM project team met with the ATA and representatives from NASA's X-33 and X-34 programs to discuss collaboration on a national space standard based on Spec 100. A pilot project was enabled for a subset of Shuttle systems. Full implementation was not yet achieved, X-33 and X-34 were cancelled, and the Shuttles were then designated for retirement. Nonetheless, we can learn from this project how to expand this concept to all space vehicle products. Since then, ATA has joined with ASD (AeroSpace and Defence Industries Association of Europe) and AIA (Aerospace Industries Association) to form a much-enhanced and expanded international specification: Sl000D, International Specification for Technical Publications. It includes air, land, and sea vehicles, missiles, support equipment, ordnance, and communications. It is used by a growing number of countries for commercial and government products. Its modular design is supported by a Common Source Dabase (CSDB), and COTS (commercial off-the-shelf) software is available for production of IETP's (Interactive Electronic Technical Publications). A few space industry products in Europe have begun to apply Sl000D already. Also, there are other related standards/specifications which have global implications. We have an opportunity to adapt Sl000D and possibly other standards for use with space vehicles and ground systems. Sl000D has plenty of flexibility to apply to any product needed. To successfully grow the viability of the space industry, all members, commercial and government, will need to engage cooperatively in developing and applying standards to move toward interoperability. If we leverage and combine the best existing space standards and specifications, develop new ones to address known gaps, and adapt the best applicable features from other industries, we can establish an infrastructure to not only accelerate current development, but also build longevity for a more cohesive international space community.

Ingalls, John↗
NASA NTRS1991

Low power DIPS design for NASA missions

Conceptual designs of low power dynamic isotope power systems (DIPS) for NASA's future deep space missions are being developed to characterize the power system's unique features in the 0.5-1.0 kilowatt-electric (kWe) range. The August 1990 Mariner Mark II spacecraft design was used for the spacecraft integration study. One basic design with slight mission specific variations was developed for the Cassini, Comet Nucleus Sample Return, and Outer Planet Orbiter Probe missions. A low power DIPS flight unit offers comparable specific power values to the MOD-RTG unit with a factor-of-three improvement in radioisotope fuel requirements. This was accomplished by fully exploiting the dynamic power conversion technology available in the DIPS program.

Johnson, Richard A.↗
DOE OSTI2024

Large-Scale Visualization of 3D Unstructured Groundwater Model Using Cave Automated Virtual Environment

The immersive three-dimensional (3D) virtual reality (VR) visualization of groundwater models allows us to deepen our understanding of aquifer systems and provide better solutions to present groundwater-related problems, such as groundwater recharge, water quality, and sustainability. Visualization assists in accurately developing groundwater models and revealing important subsurface features, including faulting, folding, and unconformity. However, assessing model accuracy poses challenges due to the complexity of geology and groundwater systems. This research demonstrates a workflow to visualize and analyze raw 3D unstructured groundwater model data using an immersive Cave Automated Virtual Environment (CAVE). To visualize the unstructured groundwater model data, the raw dataset is converted into interactive CAVE-compatible formats utilizing a set of tools: ParaView, Blender, and Unity. This enables researchers to immerse themselves in the data, identifying influential patterns and relationships. e resulting insights can inform the development of sophisticated machine-learning models for groundwater level prediction. The CAVE’s immersive capabilities allow intuitive exploration from various perspectives, providing a more holistic understanding of the factors affecting groundwater levels. These insights are crucial to improve predictive models. The CAVE results also facilitate collaborative analysis and have potential applications in training and education. is research demonstrates the value of immersive VR tools such as the CAVE for unraveling intricacies within high-dimensional scientific data to drive real-world forecasting and modeling applications.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2007

Automated Recognition of 3D Features in GPIR Images

A method of automated recognition of three-dimensional (3D) features in images generated by ground-penetrating imaging radar (GPIR) is undergoing development. GPIR 3D images can be analyzed to detect and identify such subsurface features as pipes and other utility conduits. Until now, much of the analysis of GPIR images has been performed manually by expert operators who must visually identify and track each feature. The present method is intended to satisfy a need for more efficient and accurate analysis by means of algorithms that can automatically identify and track subsurface features, with minimal supervision by human operators. In this method, data from multiple sources (for example, data on different features extracted by different algorithms) are fused together for identifying subsurface objects. The algorithms of this method can be classified in several different ways. In one classification, the algorithms fall into three classes: (1) image-processing algorithms, (2) feature- extraction algorithms, and (3) a multiaxis data-fusion/pattern-recognition algorithm that includes a combination of machine-learning, pattern-recognition, and object-linking algorithms. The image-processing class includes preprocessing algorithms for reducing noise and enhancing target features for pattern recognition. The feature-extraction algorithms operate on preprocessed data to extract such specific features in images as two-dimensional (2D) slices of a pipe. Then the multiaxis data-fusion/ pattern-recognition algorithm identifies, classifies, and reconstructs 3D objects from the extracted features. In this process, multiple 2D features extracted by use of different algorithms and representing views along different directions are used to identify and reconstruct 3D objects. In object linking, which is an essential part of this process, features identified in successive 2D slices and located within a threshold radius of identical features in adjacent slices are linked in a directed-graph data structure. Relative to past approaches, this multiaxis approach offers the advantages of more reliable detections, better discrimination of objects, and provision of redundant information, which can be helpful in filling gaps in feature recognition by one of the component algorithms. The image-processing class also includes postprocessing algorithms that enhance identified features to prepare them for further scrutiny by human analysts (see figure). Enhancement of images as a postprocessing step is a significant departure from traditional practice, in which enhancement of images is a preprocessing step.

Park, Han↗
DOE OSTI2012

Atomic Force Microscopy of Arrays of Asymmetrical DNA Motifs

DNA can easily be assembled into wide and relatively flat nanostructures that lend themselves to study via Atomic Force Microscopy (AFM). It is often important to know which side of an assembly the AFM is imaging. This is particularly crucial for characterizing nanomachines, where the movement must be measured relative to fiducial features visible to the AFM. We have developed a cheap and simple technique for building DNA arrays with distinguishable sides, a technique requiring 10 or fewer strands - dozens or hundreds of strands fewer than used for these purposes previously. Our approach involves constructing arrays out of DNA tiles that have low apparent symmetry when imaged via AFM. We have surveyed the effects of varying degrees of motif asymmetry in AFM micrographs. Even at resolutions where the individual tiles cannot be resolved (either because of sub-optimal tip quality, or very gentle tapping by the AFM tip) the larger scale features of the arrays have predictable structures that allow the determination of which side of the array is facing up. We have used this information to verify that DNA hairpins attached to either the up- or down-facing side of an array on mica can be detected in AFM height scans. We have also characterized differences in appearance between hairpins attached to different sides of the arrays.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1986

MMIC antenna technology development in the 30/20 gigahertz band

This paper presents a progress summary of NASA's efforts in developing 20 and 30 GHz GaAs MMIC devices and an advanced satellite communications antenna system using these devices. In the interest of preserving resources such as frequency spectrum and orbital space the antenna system is being developed with multiple fixed spot beams and multiple scanning spot beams. NASA set high goals for the MMIC development to pushc GaAs technology. These goals and the main features of the MMIC devices are discussed. Some packaging and characterization considerations are also discussed. The 20 GHz transmit antenna and 30 GHz receive antenna are being developed separately. The approach selected is to perform contractual configuration studies, purchase a 20-GHz experimental antenna system (EAS) and perform in-house evaluation. The features and key specifications of the EAS are discussed. Additional supporting technologies such as effects of coupling on modest sized arrays, MMIC matching techniques, in-house analytical capability, wideband and dual frequency microstrip patch array development, and MMIC packaging techniques are described. Some plans for future are also discussed.

Smetana, J.↗
NASA NTRS1986

MMIC antenna technology development in the 30/20 gigahertz band

This paper presents a progress summary of NASA's efforts in developing 20 and 30 GHz GaAs MMIC devices and an advanced satellite communications antenna system using these devices. In the interest of preserving resources such as frequency spectrum and orbital space the antenna system is being developed with multiple fixed spot beams and multiple scanning spot beams. NASA set high goals for the MMIC development to push GaAs technology. These goals and the main features of the MMIC devices are discussed. Some packaging and characterization considerations are also discussed. The 20 GHz transmit antenna and 30 GHz receive antenna are being developed separately. The approach selected is to perform contractual configuration studies, purchase a 20-GHz experimental antenna system (EAS) and perform in-house evaluation. The features and key specifications of the EAS are discussed. Additional supporting technologies such as effects of coupling on modest sized arrays, MMIC matching techniques, in-house analytical capability, wideband and dual frequency microstrip patch array development, and MMIC packaging techniques are described. Some plans for future work are also discussed.

Smetana, J.↗