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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 361 records · Page 20

αAMG based on Weighted Matching for Systems of Elliptic PDEs Arising From Displacement and Mixed Methods

Adaptive Algebraic Multigrid (or Multilevel) Methods (αAMG) are introduced to improve robustness and efficiency of classical algebraic multigrid methods in dealing with problems where no a-priori knowledge or assumptions on the near-null kernel of the underlined matrix are available. Recently we proposed an adaptive (bootstrap) AMG method, αAMG, aimed to obtain a composite solver with a desired convergence rate. Each new multigrid component relies on a current (general) smooth vector and exploits pairwise aggregation based on weighted matching in a matrix graph to define a new automatic, general-purpose coarsening process, which we refer to as “the compatible weighted matching”. In this work, we present results that broaden the applicability of our method to different finite element discretizations of elliptic PDEs. In particular, we consider systems arising from displacement methods in linear elasticity problems and saddle-point systems that appear in the application of the mixed method to Darcy problems.

97 MATHEMATICS AND COMPUTING↗

Ligand placement based on prior structures: the guided ligand-replacement method

A new module, Guided Ligand Replacement (GLR), has been developed in Phenix to increase the ease and success rate of ligand placement when prior protein-ligand complexes are available. The process of iterative structure-based drug design involves the X-ray crystal structure determination of upwards of 100 ligands with the same general scaffold (i.e. chemotype) complexed with very similar, if not identical, protein targets. In conjunction with insights from computational models and assays, this collection of crystal structures is analyzed to improve potency, to achieve better selectivity and to reduce liabilities such as absorption, distribution, metabolism, excretion and toxicology. Current methods for modeling ligands into electron-density maps typically do not utilize information on how similar ligands bound in related structures. Even if the electron density is of sufficient quality and resolution to allow de novo placement, the process can take considerable time as the size, complexity and torsional degrees of freedom of the ligands increase. A new module, Guided Ligand Replacement (GLR), was developed in Phenix to increase the ease and success rate of ligand placement when prior protein–ligand complexes are available. At the heart of GLR is an algorithm based on graph theory that associates atoms in the target ligand with analogous atoms in the reference ligand. Based on this correspondence, a set of coordinates is generated for the target ligand. GLR is especially useful in two situations: (i) modeling a series of large, flexible, complicated or macrocyclic ligands in successive structures and (ii) modeling ligands as part of a refinement pipeline that can automatically select a reference structure. Even in those cases for which no reference structure is available, if there are multiple copies of the bound ligand per asymmetric unit GLR offers an efficient way to complete the model after the first ligand has been placed. In all of these applications, GLR leverages prior knowledge from earlier structures to facilitate ligand placement in the current structure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

ARENA: Asynchronous Reconfigurable Accelerator Ring to Enable Data-Centric Parallel Computing

The next generation HPC and data centers are likely to be reconfigurable and data-centric due to the trend of hardware specialization and the emergence of data-driven applications. In this work, we propose ARENA – an asynchronous reconfigurable accelerator ring architecture as a potential scenario on how the future HPC and data centers will be like. Despite using the coarse-grained reconfigurable arrays (CGRAs) as the substrate platform, our key contribution is not only the CGRA-cluster design itself, but also the ensemble of a new architecture and programming model that enables asynchronous tasking across a cluster of reconfigurable nodes, so as to bring specialized computation to the data rather than the reverse. We presume distributed data storage without asserting any prior knowledge on the data distribution. Hardware specialization occurs at runtime when a task finds the majority of data it requires are available at the present node. In other words, we dynamically generate specialized CGRA accelerators where the data reside. The asynchronous tasking for bringing computation to data is achieved by circulating the task token, which describes the dataflow graphs to be executed for a task, among the CGRA cluster connected by a fast ring network. Evaluations on a set of HPC and data-driven applications across different domains show that ARENA can provide better parallel scalability with reduced data movement (53.9 percent). Compared with contemporary compute-centric parallel models, ARENA can bring on average 4.37× speedup. The synthesized CGRAs and their task-dispatchers only occupy 2.93mm 2 chip area under 45nm process technology and can run at 800MHz with on average 759.8mW power consumption. ARENA also supports the concurrent execution of multi-applications, offering ideal architectural support for future high-performance parallel computing and data analytics systems.

97 MATHEMATICS AND COMPUTING↗

Width-Based Discharge Partitioning in Distributary Networks: How Right We Are

River deltas are home to large populations and can be composed of complex channel networks which convey flows of matter to the shoreline. Knowledge of flow within individual channels is needed to quantify the distribution of discharge across the delta, and thus its sustainability over time. Due to a lack of field measurements at the local channel scale, researchers leverage remote sensing data to estimate the partitioning of flow. We compare data from 15 river deltas to discharge partitioning estimates based on channel network graphs derived from remote sensing imagery. We quantify errors in the common width-based method and test alternative partitioning techniques to find that width-based discharge partitioning is universally applicable, suggesting that absent any site-specific information, discharge partitioning by average channel width is an appropriate approach. We also provide networks, streamflow measurements, and flux partitioning estimates for 28 delta networks as the Discharge In Distributary NeTworks (DIDNT) dataset.

58 GEOSCIENCES↗

A Semi-Automated Approach for Curating a Glossary of Key Terms for Open-Source Data Queries

In FY20, the Savannah River National Laboratory (SRNL) was funded by the National Nuclear Security Administration’s Office of Defense Nuclear Non-Proliferation Research and Development (NA-22) to build a machine learning based modeling pipeline that could extract proliferation events of interest from open text-based data sources. As a test case, the research team targeted the identification/fusion of events and indicators that fissile core fabrication would be executed at the Savannah River Site prior to its official announcement in May of 2018. The demonstration prototype proved successful by applying natural language processing and graph theoretical techniques to identify contextual shifts in key words and phrases that acted as indicators that pit production would be carried out at the Savannah River Site up to two years prior to the official announcement.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Adaptive AMG with Coarsening Based on Compatible Weighted Matching

We introduce a new composite adaptive Algebraic Multigrid (composite αAMG) method to solve systems of linear equations without a-priori knowledge or assumption on characteristics of near-null components of the AMG preconditioned problem referred to as algebraic smoothness. Our version of αAMG is a composite solver built through a bootstrap strategy aimed to obtain a desired convergence rate. The coarsening process employed to build each new solver component relies on a pairwise aggregation scheme based on maximum weighted matching in a graph and on principles of compatible relaxation. The latter replaces the commonly used characterization of strength of connection in both the coarse space selection and in the interpolation scheme. The goal is to design a method leading to scalable AMG for a wide class of problems that go beyond the standard elliptic Partial Differential Equations (PDEs). In the present work, we introduce the method and demonstrate its potential when applied to symmetric positive definite linear systems arising from finite element discretization of highly anisotropic elliptic PDEs on structured and unstructured meshes.

97 MATHEMATICS AND COMPUTING↗

The Strategic Environment Assessment bibliographic network: A quantitative literature review analysis

Academic literature has been continuously growing at such a pace that it can be difficult to follow the progression of scientific achievements; hence, the need to dispose of quantitative knowledge support systems to analyze the literature of a subject. In this article we utilize network analysis tools to build a literature review of scientific documents published in the multidisciplinary field of Strategic Environment Assessment (SEA). The proposed approach helps researchers to build unbiased and comprehensive literature reviews. We collect information on 7662 SEA publications and build the SEA Bibliographic Network (SEABN) employing the basic idea that two publications are interconnected if one cites the other. We apply network analysis at macroscopic (network architecture), mesoscopic (sub graph) and microscopic levels (node) in order to i) verify what network structure characterizes the SEA literature, ii) identify the authors, disciplines and journals that are contributing to the international discussion on SEA, and iii) scrutinize the most cited and important publications in the field. Results show that the SEA is a multidisciplinary subject; the SEABN belongs to the class of real small world networks with a dominance of publications in Environmental studies over a total of 12 scientific sectors. Christopher Wood, Olivia Bina, Matthew Cashmore, and Andrew Jordan are found to be the leading authors while Environmental Impact Assessment Review is by far the scientific journal with the highest number of publications in SEA studies. - Highlights: • We utilize network analysis to analyze scientific documents in the SEA field. • We build the SEA Bibliographic Network (SEABN) of 7662 publications. • We apply network analysis at macroscopic, mesoscopic and microscopic network levels. • We identify SEABN architecture, relevant publications, authors, subjects and journals.

54 ENVIRONMENTAL SCIENCES↗

Probabilistic Modeling of Microbial Metabolic Networks for Integrating Partial Quantitative Knowledge Within the Nitrogen Cycle

Understanding the interactions between microbial communities and their environment sufficiently to predict diversity on the basis of physicochemical parameters is a fundamental pursuit of microbial ecology that still eludes us. However, modeling microbial communities is problematic, because (i) communities are complex, (ii) most descriptions are qualitative, and (iii) quantitative understanding of the way communities interact with their surroundings remains incomplete. One approach to overcoming such complications is the integration of partial qualitative and quantitative descriptions into more complex networks. Here we outline the development of a probabilistic framework, based on Event Transition Graph (ETG) theory, to predict microbial community structure across observed chemical data. Using reverse engineering, we derive probabilities from the ETG that accurately represent observations from experiments and predict putative constraints on communities within dynamic environments. These predictions can feedback into the future development of field experiments by emphasizing the most important functional reactions, and associated microbial strains, required to characterize microbial ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗

The OEOP Duties of Reasonable Accommodation

I was fortunate enough to be assigned two assignments during my ten weeks here at NASA's Langley Research Center, in the Office of Equal Opportunity Programs (OEOP). One of my projects gave me the chance to gain experience in developing calculation formulas for the EXCEL computer system, while my second project gave me the chance to put my research skills and legal knowledge to use. The function of the OEOP is to ensure the adherence to personnel policy and practices in the employment, development, advancement and treatment of Federal employees and applicants for employment. This includes veterans and disabled as well. My initial project involved the research of hiring and promotion among the different minorities and females employed here at Langley. The objective of my first project was to develop graphs that showed the number of promotions during the past five years for each minority group here on the Center. I also had to show the average number of years it took for each promotion. The objective of my second and main research project was to find and research cases regarding the reasonable accommodation of disabled workers. The research of these cases is to ensure that individuals with disabilities are provided the necessary accommodations that are essential to the function of their job.

Coppedge, Angela↗

Reanalysis of Rodent Data from Spacelab Life Sciences-1

The space bioscience field has long been plagued by the challenge of spaceflight with effects of radiation and microgravity. Having multiple and repeated spaceflight experiments for model organisms to solve these space stressors is costly and time consuming. Therefore, reusing and reanalyzing legacy experiments is one way that scientists can draw new conclusions in a timely manner and without using too many resources. Moreover, advances in general biological knowledge allows legacy experiments to be placed into more complete context.Here we aim to analyze all data and metadata taken from rats flown on the SLS-1 mission to create a comprehensive biological model that can be supplemented with current data to allow new discoveries in how space flown organisms adapt to the space environment. Our approach begins with the identification of all the data and metadata, including graphs and tables, for SLS-1 in NASA archives and other sources. Then, each piece of data and metadata will be digitized, reformatted and analyzed. Lastly, a previously developed astronaut model will be used to create the data framework and a comprehensive biological rodent model. The datasets we are using is from the 1991 SpaceLab Life Science 1 (SLS-1) NASA Mission. This was the first designated spacelab mission flown. All 29 rodents were tested for nine days in two different habitats: Research Animal Holding Facility (RAHF) and Animal Enclosure Module (AEM). The rodents were prepared for a live return and compared to a ground control. A total of 30 rodent experiments were accepted as flight studies on the mission. By digitization and reorganizing SLS-1 rat data we will both directly generate new insights and indirectly enable other scientists to by providing the data and metadata in a digitized form.

Space Biology↗

Reanalysis of Rodent Data from Spacelab Life Science-1

The space bioscience field has long been plagued by the challenge of spaceflight with effects of radiation and microgravity. Having multiple and repeated spaceflight experiments for model organisms to solve these space stressors is costly and time consuming. Therefore, reusing and reanalyzing legacy experiments is one way that scientists can draw new conclusions in a timely manner and without using too many resources. Moreover, advances in general biological knowledge allows legacy experiments to be placed into more complete context.Here we aim to analyze all data and metadata taken from rats flown on the SLS-1 mission to create a comprehensive biological model that can be supplemented with current data to allow new discoveries in how space flown organisms adapt to the space environment. Our approach begins with the identification of all the data and metadata, including graphs and tables, for SLS-1 in NASA archives and other sources. Then, each piece of data and metadata will be digitized, reformatted and analyzed. Lastly, a previously developed astronaut model will be used to create the data framework and a comprehensive biological rodent model. The datasets we are using is from the 1991 SpaceLab Life Science 1 (SLS-1) NASA Mission. This was the first designated spacelab mission flown. All 29 rodents were tested for nine days in two different habitats: Research Animal Holding Facility (RAHF) and Animal Enclosure Module (AEM). The rodents were prepared for a live return and compared to a ground control. A total of 30 rodent experiments were accepted as flight studies on the mission. By digitization and reorganizing SLS-1 rat data we will both directly generate new insights and indirectly enable other scientists to by providing the data and metadata in a digitized form.

Space Biology↗

Figure Descriptive Text Extraction Using Ontological Representation

Abstract Experimental research publications provide figure form resources including graphs, charts, and any type of images to effectively support and convey methods and results. To describe figures, authors add captions, which are often incomplete, and more descriptions reside in body text. This work presents a method to extract figure descriptive text from the body of scientific articles. We adopted ontological semantics to aid concept recognition of figure-related information, which generates human- and machine-readable knowledge representations from sentences. Our results show that conceptual models bring an improvement in figure descriptive sentence classification over word-based approaches.

97 MATHEMATICS AND COMPUTING↗

A computational approach for the annotation of hydrogen-bonded base interactions in crystallographic structures of the ribozymes

A fundamental understanding of the atomic level interactions in ribonucleic acid (RNA) and how they contribute towards RNA architecture is an important knowledge platform to develop through the discovery of motifs from simple arrangements base pairs, to more complex arrangements such as triples and larger patterns involving non-standard interactions. The network of hydrogen bond interactions is important in connecting bases to form potential tertiary motifs. Therefore, there is an urgent need for the development of automated methods for annotating RNA 3D structures based on hydrogen bond interactions. COnnection tables Graphs for Nucleic ACids (COGNAC) is automated annotation system using graph theoretical approaches that has been developed for the identification of RNA 3D motifs. This program searches for patterns in the unbroken networks of hydrogen bonds for RNA structures and capable of annotating base pairs and higher-order base interactions, which ranges from triples to sextuples. COGNAC was able to discover 22 out of 32 quadruples occurrences of the Haloarcula marismortui large ribosomal subunit (PDB ID: 1FFK) and two out of three occurrences of quintuple interaction reported by the non-canonical interactions in RNA (NCIR) database. These and several other interactions of interest will be discussed in this paper. These examples demonstrate that the COGNAC program can serve as an automated annotation system that can be used to annotate conserved base-base interactions and could be added as additional information to established RNA secondary structure prediction methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bringing Fenton Hill into the Digital Age: Data Conversion in Support of the Geothermal Technologies Office Code Comparison Study Challenge Problems

The Geothermal Technologies Office Code Comparison Study (GTO-CCS) was established by the U.S. Department of Energy to facilitate collaboration among members of the geothermal modeling community and to evaluate and improve upon the ability of existing codes to simulate thermal, hydrological, mechanical, and chemical processes associated with complex enhanced geothermal systems (EGS). The first stage of the project, which has been completed, involved comparing simulations for seven benchmark problems that were primarily designed using well-prescribed, simplified data sets. In the second stage, the participating teams are tackling two challenge problems based on the EGS research conducted in hot dry rock (HDR) at Fenton Hill, near Los Alamos, New Mexico. The Fenton Hill project, conducted by Los Alamos National Laboratory (LANL) from 1970 to 1995, was the world’s first HDR demonstration project. One of the criteria for selecting this experiment as the basis for the challenge problems was the amount and availability of data for generating model inputs. The Fenton Hill HDR system consisted of two reservoirs – an earlier Phase I reservoir tested from 1974 to 1981 and a deeper Phase II reservoir tested from 1980 to 1995. Detailed accounts of both phases of the HDR project have been presented in a number of books and reports, including a recently published summary of the lessons learned and a final report with a chronological description of the Fenton Hill project, prepared by LANL. Project documents and records have been archived and made public through the National Geothermal Data System (NGDS). Some of the data acquired from Phase II are available in electronic format readable on modern computers. These include the microseismic data from some of the important experiments (e.g. the massive hydraulic fracturing test conducted in 1983) and the injection/production wellhead data from the circulation tests conducted between 1992-1995. However, much of the data collected during the project, while publicly available, currently only exist in the form of tables or graphs within scanned documents. Therefore, in support of the GTO-CCS, the data needed for developing simulation inputs are being compiled and converted to platform independent, open readable formats so that all participating teams will have access to the same electronic data set. In some cases this requires conversion using optical character recognition, digitizing existing images, and generating the appropriate metadata from project documents. The GTO-Velo knowledge management framework, developed by Pacific Northwest National Laboratory (PNNL), was used for the benchmark problem stage of the comparison study and will also be used as the data repository for the challenge problem data sets. It is staggering and impractical to convert all published data for the Fenton Hill site, so the focus is on data that supports simulations for the three topical areas defined by the study for the challenge problems: 1) reservoir creation/stimulation, 2) reactive and passive transport, and 3) thermal recovery. Conversion of these data provide value not only to GTO-CCS participants, but also to members of the geothermal community at large who may be interested in revisiting the Fenton Hill experiment in the future.

Code Comparison Study↗

Public Communication of Technical Issues in Today's Changing Visual Language - 12436

Communication regarding the management of radioactive materials is a well-established challenge. Residents and consumers have suspected for years that companies and governments place short-term economic concerns ahead of health and safety. This skepticism is compounded with increased attention to safety issues at nuclear power plants everywhere after Fukushima. Nonetheless, today's environment presents unexpected opportunities to transform public fear into teachable moments that bring knowledge and facts to discussions on nuclear energy. In the weeks following Japan's crisis, the lack of reliable information on radiation levels saw citizens taking to the streets with dosimeters and Geiger counters in crowd-sourced radiation monitoring efforts. Efforts, based mainly online, represent a growing set of examples of how internet and cell-phone technology are being put to use in emergency situations. The maps, graphs and tables created to meet public interest also exemplify some of the psychological priorities of audiences and present learning tools that can improve future education efforts in non-emergency situations. Industry outreach efforts often consist of technical details and quantitative data that are difficult for lay audiences to interpret. The intense attention to nuclear energy issues since last March has produced a wide array of visual samples. Citizen monitors, news organizations, government agencies and others have displayed quantitative information in innovative ways. Their efforts offer new perspective on what charts, maps and info graphics do - or need to do - to illustrate requirements, record assessments and promote understanding of nuclear-waste issues. Surveying the best examples, nuclear communicators can improve their offerings of easy-to-use, evidence-based visuals to inform stakeholders. Familiar to most communications professionals in the nuclear industry, risk communication is a science-based approach with over three decades of research evidence informing the discipline. Risk communication principles address the fact that often perception is reality. Scientific evidence for decision making must be approached differently in situations where stakeholders have high levels of concern and low levels of trust. Visual communications must take this into account to be successful. (author)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A Space-Filling Visualization Technique for Multivariate Small World Graphs

We introduce an information visualization technique, known as GreenCurve, for large sparse graphs that exhibit small world properties. Our fractal-based design approach uses spatial cues to approximate the node connections and thus eliminates the links between the nodes in the visualization. The paper describes a sophisticated algorithm to order the neighboring nodes of a large sparse graph by solving the Fiedler vector of its graph Laplacian, and then fold the graph nodes into a space-filling fractal curve based on the Fiedler vector. The result is a highly compact visualization that gives a succinct overview of the graph with guaranteed visibility of every graph node. We show in the paper that the GreenCurve technology is (1) theoretically sustainable by introducing an error estimation metric to measure the fidelity of the new graph representation, (2) empirically rigorous by conducting a usability study to investigate its strengths and weaknesses against the traditional graph layout, and (3) pragmatically feasible by applying it to analyze stressed conditions of the large scale electric power grid on the west coast.

99 GENERAL AND MISCELLANEOUS↗

Automated descriptor selection, volcano curve generation, and active site determination using the DescMAP software

The material space for catalyst discovery is expansive. Volcano curves are traditionally employed to provide physical insights into optimal catalyst characteristics for new material selection. Their generation lies on a single descriptor picked using expert knowledge. Here we present DescMAP, a Python-based software, to automate the selection of descriptors, the generation of volcano maps, and the identification of active sites for structure-sensitive reactions. Here, we consider traditional energy-based and geometric descriptors for structure-sensitive reactions. DescMAP is integrated with the Virtual Kinetic Laboratory (VLab) to provide multiple functionalities. It inputs spreadsheets or template files for flexibility and outputs interactive graphs for post-processing. We demonstrate its features using the non-oxidative dehydrogenation of ethane to ethylene over (111) closed-packed surfaces and the methane total oxidation over various Pt facets. It can be easily applied to other complex chemistries and achieves quick screening of potential catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

GRAPH — an readout ASIC for large MCP based detectors

We present a programmable 16 channel, mixed signal, low power readout ASIC, having the project historically named Gigasample Recorder of Analog waveforms from a PHotodetector (GRAPH). It is designed to read large aperture single photon imaging detectors using micro channel plates for charge multiplication, and measuring the detector's response on crossed strips anodes to extrapolate the incoming photon position. Each channel consists of a fast, low power and low noise charge sensitive amplifier, which provides a myriad of coarse and fine programmable options for gain and shaping settings. Further, the amplified signal is recorded using, to our knowledge novel, the Hybrid Universal sampLing Architecture (HULA) ADC. A kind of mixed signal double buffer memory, that enables concurrent waveform recording, and selected event digitized data extraction. The sampling frequency is freely adjustable between few kHz up to 125 MHz, while the chip's internal digital memory holds a history 2048 samples for each channel, with a digital headroom of 12 bits. An optimized region of interest sample-read algorithm allows to extract the information just around the event pulse peak, while selecting the next event, thus substantially reducing the operational dead time. The chip is designed in 130 nm TSMC CMOS technology, and its power consumption is around 47 mW per channel.

47 OTHER INSTRUMENTATION↗