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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 127 records · Page 7

Internal structure of the San Jacinto fault zone at Blackburn Saddle from seismic data of a linear array

Local and teleseismic earthquake waveforms recorded by a 180-m-long linear array (BB) with seven seismometers crossing the Clark fault of the San Jacinto fault zone northwest of Anza are used to image a deep bimaterial interface and core damage structure of the fault. Delay times of P waves across the array indicate an increase in slowness from the southwest most (BB01) to the northeast most (BB07) station. Automatic algorithms combined with visual inspection and additional analyses are used to identify local events generating fault zone head and trapped waves. The observed fault zone head waves imply that the Clark fault in the area is a sharp bimaterial interface, with lower seismic velocity on the southwest side. The moveout between the head and direct P arrivals for events within ~40 km epicentral distance indicates an average velocity contrast across the fault over that section and the top 20 km of 3.2 per cent. A constant moveout for events beyond ~40 km to the southeast is due to off-fault locations of these events or because the imaged deep bimaterial interface is discontinuous or ends at that distance. The lack of head waves from events beyond ~20 km to the northwest is associated with structural complexity near the Hemet stepover. Events located in a broad region generate fault zone trapped waves at stations BB04–BB07. Waveform inversions indicate that the most likely parameters of the trapping structure are width of ~200 m, S velocity reduction of 30–40 per cent with respect to the bounding blocks, Q value of 10–20 and depth of ~3.5 km. The trapping structure and zone with largest slowness are on the northeast side of the fault. The observed sense of velocity contrast and asymmetric damage across the fault suggest preferred rupture direction of earthquakes to the northwest. This inference is consistent with results of other geological and seismological studies.

58 GEOSCIENCES↗

Biolink Model: A universal schema for knowledge graphs in clinical, biomedical, and translational science

Abstract Within clinical, biomedical, and translational science, an increasing number of projects are adopting graphs for knowledge representation. Graph‐based data models elucidate the interconnectedness among core biomedical concepts, enable data structures to be easily updated, and support intuitive queries, visualizations, and inference algorithms. However, knowledge discovery across these “knowledge graphs” (KGs) has remained difficult. Data set heterogeneity and complexity; the proliferation of ad hoc data formats; poor compliance with guidelines on findability, accessibility, interoperability, and reusability; and, in particular, the lack of a universally accepted, open‐access model for standardization across biomedical KGs has left the task of reconciling data sources to downstream consumers. Biolink Model is an open‐source data model that can be used to formalize the relationships between data structures in translational science. It incorporates object‐oriented classification and graph‐oriented features. The core of the model is a set of hierarchical, interconnected classes (or categories) and relationships between them (or predicates) representing biomedical entities such as gene, disease, chemical, anatomic structure, and phenotype. The model provides class and edge attributes and associations that guide how entities should relate to one another. Here, we highlight the need for a standardized data model for KGs, describe Biolink Model, and compare it with other models. We demonstrate the utility of Biolink Model in various initiatives, including the Biomedical Data Translator Consortium and the Monarch Initiative, and show how it has supported easier integration and interoperability of biomedical KGs, bringing together knowledge from multiple sources and helping to realize the goals of translational science.

60 APPLIED LIFE SCIENCES↗

Data-Parallel Algorithm for Contour Tree Construction

The goal of this project is to develop algorithms for additional visualization and analysis filters in order to expand the functionality of the VTK-m toolkit to support less critical but commonly used operators.

97 MATHEMATICS AND COMPUTING↗

Image Information Mining Utilizing Hierarchical Segmentation

The Hierarchical Segmentation (HSEG) algorithm is an approach for producing high quality, hierarchically related image segmentations. The VisiMine image information mining system utilizes clustering and segmentation algorithms for reducing visual information in multispectral images to a manageable size. The project discussed herein seeks to enhance the VisiMine system through incorporating hierarchical segmentations from HSEG into the VisiMine system.

Tilton, James C.↗

Integration of Dynamic Models in Range Operations

This work addresses the various model interactions in real-time to make an efficient internet based decision making tool for Shuttle launch. The decision making tool depends on the launch commit criteria coupled with physical models. Dynamic interaction between a wide variety of simulation applications and techniques, embedded algorithms, and data visualizations are needed to exploit the full potential of modeling and simulation. This paper also discusses in depth details of web based 3-D graphics and applications to range safety. The advantages of this dynamic model integration are secure accessibility and distribution of real time information to other NASA centers.

Bardina, Jorge↗

Artificial Intelligence Software for Assessing Postural Stability

A software package reads and analyzes pressure distributions from sensors mounted under a person's feet. Pressure data from sensors mounted in shoes, or in a platform, can be used to provide a description of postural stability (assessing competence to deficiency) and enables the determination of the person's present activity (running, walking, squatting, falling). This package has three parts: a preprocessing algorithm for reading input from pressure sensors; a Hidden Markov Model (HMM), which is used to determine the person's present activity and level of sensing-motor competence; and a suite of graphical algorithms, which allows visual representation of the person's activity and vestibular function over time.

Lieberman, Erez↗

Dense 3D-Reconstruction from Monocular Image Sequences for Computationally Constrained UAS

The ability to find safe landing sites over complex 3D terrain is an essential safety feature for fully autonomous small unmanned aerial systems (UAS), which requires on-board perception for 3D reconstruction and terrain analysis if the overflown terrain is unknown. This is a challenge for UAS that are limited in size, weight and computational power, such as small rotorcrafts executing autonomous missions on Earth, or in planetary applications such as the Mars Helicopter. For such a computationally constraint system, we propose a structure from motion approach that uses inputs from a single downward facing camera to produce dense point clouds of the overflown terrain in real time. In contrast to existing approaches, our method uses metric pose information from a visual-inertial odometry algorithm as camera pose priors, which allows deploying a fast pose refinement step to align camera frames such that a conventional stereo algorithm can be used for dense 3D reconstruction. We validate the performance of our approach with extensive evaluations in simulation, and demonstrate the feasibility with data from UAS flights.

Brockers, Roland↗

View-Dependent Streamline Deformation and Exploration

Occlusion presents a major challenge in visualizing 3D flow and tensor fields using streamlines. Displaying too many streamlines creates a dense visualization filled with occluded structures, but displaying too few streams risks losing important features. We propose a new streamline exploration approach by visually manipulating the cluttered streamlines by pulling visible layers apart and revealing the hidden structures underneath. Here this paper presents a customized view-dependent deformation algorithm and an interactive visualization tool to minimize visual cluttering for visualizing 3D vector and tensor fields. The algorithm is able to maintain the overall integrity of the fields and expose previously hidden structures. Our system supports both mouse and direct-touch interactions to manipulate the viewing perspectives and visualize the streamlines in depth. By using a lens metaphor of different shapes to select the transition zone of the targeted area interactively, the users can move their focus and examine the vector or tensor field freely.

97 MATHEMATICS AND COMPUTING↗

Visualization at exascale: Making it all work with VTK-m

The VTK-m software library enables scientific visualization on exascale-class supercomputers. Exascale machines are particularly challenging for software development in part because they use GPU accelerators to provide the vast majority of their computational throughput. Algorithmic designs for GPUs and GPU-centric computing often deviate from those that worked well on previous generations of high-performance computers that relied on traditional CPUs. Fortunately, VTK-m provides scientific visualization algorithms for GPUs and other accelerators. VTK-m also provides a framework that simplifies the implementation of new algorithms and adds a porting layer to work across multiple processor types. This paper describes the main challenges encountered when making scientific visualization available at exascale. Here, we document the surprises and obstacles faced when moving from pre-exascale platforms to the final exascale designs and the performance on those systems including scaling studies on Frontier, an exascale machine with over 37,000 AMD GPUs. We also report on the integration of VTK-m with other exascale software technologies. Finally, we show how VTK-m helps scientific discovery for applications such as fusion and particle acceleration that leverage an exascale supercomputer.

97 MATHEMATICS AND COMPUTING↗

Unexpected series of regular frequency spacing of δ Scuti stars in the non-asymptotic regime - I. The methodology

In this study, a sequence search method was developed to search the regular frequency spacing in δ Scuti stars through visual inspection and an algorithmic search. We searched for sequences of quasi-equally spaced frequencies, containing at least four members per sequence, in 90 δ Scuti stars observed by CoRoT. We found an unexpectedly large number of independent series of regular frequency spacing in 77 δ Scuti stars (from one to eight sequences) in the non-asymptotic regime. We introduce the sequence search method presenting the sequences and echelle diagram of CoRoT 102675756 and the structure of the algorithmic search. Four sequences (echelle ridges) were found in the 5–21 d –1 region where the pairs of the sequences are shifted (between 0.5 and 0.59 d –1 ) by twice the value of the estimated rotational splitting frequency (0.269 d –1 ). The general conclusions for the whole sample are also presented in this paper. The statistics of the spacings derived by the sequence search method, by FT (Fourier transform of the frequencies), and the statistics of the shifts are also compared. In many stars more than one almost equally valid spacing appeared. The model frequencies of FG Vir and their rotationally split components were used to formulate the possible explanation that one spacing is the large separation while the other is the sum of the large separation and the rotational frequency. In CoRoT 102675756, the two spacings (2.249 and 1.977 d –1 ) are in better agreement with the sum of a possible 1.710 d –1 large separation and two or one times, respectively, the value of the rotational frequency.

79 ASTRONOMY AND ASTROPHYSICS↗

Classification of posture maintenance data with fuzzy clustering algorithms

Sensory inputs from the visual, vestibular, and proprioreceptive systems are integrated by the central nervous system to maintain postural equilibrium. Sustained exposure to microgravity causes neurosensory adaptation during spaceflight, which results in decreased postural stability until readaptation occurs upon return to the terrestrial environment. Data which simulate sensory inputs under various conditions were collected in conjunction with JSC postural control studies using a Tilt-Translation Device (TTD). The University of West Florida proposed applying the Fuzzy C-Means Clustering (FCM) Algorithms to this data with a view towards identifying various states and stages. Data supplied by NASA/JSC were submitted to the FCM algorithms in an attempt to identify and characterize cluster substructure in a mixed ensemble of pre- and post-adaptational TTD data. Following several unsuccessful trials with FCM using a full 11 dimensional data set, a set of two channels (features) were found to enable FCM to separate pre- from post-adaptational TTD data. The main conclusions are that: (1) FCM seems able to separate pre- from post-TTD subject no. 2 on the one trial that was used, but only in certain subintervals of time; and (2) Channels 2 (right rear transducer force) and 8 (hip sway bar) contain better discrimination information than other supersets and combinations of the data that were tried so far.

Bezdek, James C.↗

Classification of posture maintenance data with fuzzy clustering algorithms

Sensory inputs from the visual, vestibular, and proprioreceptive systems are integrated by the central nervous system to maintain postural equilibrium. Sustained exposure to microgravity causes neurosensory adaptation during spaceflight, which results in decreased postural stability until readaptation occurs upon return to the terrestrial environment. Data which simulate sensory inputs under various sensory organization test (SOT) conditions were collected in conjunction with Johnson Space Center postural control studies using a tilt-translation device (TTD). The University of West Florida applied the fuzzy c-meams (FCM) clustering algorithms to this data with a view towards identifying various states and stages of subjects experiencing such changes. Feature analysis, time step analysis, pooling data, response of the subjects, and the algorithms used are discussed.

Bezdek, James C.↗

A Rotor Tip Vortex Tracing Algorithm for Image Post-Processing

A neurite tracing algorithm, originally developed for medical image processing, was used to trace the location of the rotor tip vortex in density gradient flow visualization images. The tracing algorithm was applied to several representative test images to form case studies. The accuracy of the tracing algorithm was compared to two current methods including a manual point and click method and a cross-correlation template method. It is shown that the neurite tracing algorithm can reduce the post-processing time to trace the vortex by a factor of 10 to 15 without compromising the accuracy of the tip vortex location compared to other methods presented in literature.

Overmeyer, Austin D.↗