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At least 523 records · Page 29

A multi-mode manipulator display system for controlling remote robotic systems

The objective and contribution of the research presented in this paper is to provide a Multi-Mode Manipulator Display System (MMDS) to assist a human operator with the control of remote manipulator systems. Such systems include space based manipulators such as the space shuttle remote manipulator system (SRMS) and future ground controlled teleoperated and telescience space systems. The MMDS contains a number of display modes and submodes which display position control cues position data in graphical formats, based primarily on manipulator position and joint angle data. Therefore the MMDS is not dependent on visual information for input and can assist the operator especially when visual feedback is inadequate. This paper provides descriptions of the new modes and experiment results to date.

Massimino, Michael J.↗

Recent Enhancements to NASA’s PCBoom Sonic Boom Propagation Code

This paper presents the recent updates the author has made to PCBoom sonic boom propagation code on its computational efficiency, predictive capability, and file operations. The updated version has recently been released and has a Burgers’ equation solver, which is computationally more efficient than that in the older version by 2 to 3 orders of magnitude. The updated version also enhances the accuracy of the sonic boom propagation prediction by accounting for the full wind effects on the shock wave propagation. Predictions from the updated PCBoom are compared with predictions from the older version and with data from flight tests. Other upgrades and changes that have been made in the latest version include support for Unix-like operating systems, bug fixes, and generation of new types of output files that allow for better manipulation of PCBoom-generated data.

Lonzaga, Joel B.↗

Manual control in space research on perceptual-motor functions under zero gravity conditions (L-10)

Are human abilities to control vehicles and other machines the same in space as those on Earth? The L-10 Manual Control Experiment of the First Materials Processing Tests (FMPT) started from this question. Suppose a pilot has the task to align the head of a space vehicle toward a target. His actions are to look at the target, to determine the vehicle movement, and to operate the manipulator. If the activity of the nervous system were the same as on Earth, the movements, of the eye and hand would become excessive because the muscles do not have to oppose gravity. The timing and amount of movement must be arranged for appropriate actions. The sensation of motion would also be affected by the loss of gravity because the mechanism of the otolith, the major acceleration sensor, depends on gravity. The possible instability of the sensation of direction may cause mistakes in the direction of control of manipulator movement. Thus, the experimental data can be used for designing man-machine systems in space, as well as for investigation of physiological mechanisms. In this experiment, the direction of vehicle heading is expressed by a light spot on an array of light emitting diodes and the manipulator is of a finger stick type. As the light spot moves up and down, the Japanese Payload Specialist, and the subject, must move the manipulator forward and backward to keep the movement of the light spot within the neighborhood of the central point of the display. The position of the light spot is computed in such a manner that when the stick is kept at the neutral position, a motion whose acceleration is proportional to the angle of deflection is added to the movement of the light spot. The Operator Describing Function, which is an expression of human control characteristics, can be calculated from 2 minutes of raw data of the light spot position and stick deflection. The 2 minutes of operation is called a run, and 8 runs with resting periods composes a session. The on-orbit experiment will be conducted on the second, fourth, and seventh days. One session of experiment of each of these days is conducted following the L-4 experiment, which uses the same apparatus. The Payload Specialist, aided by a Mission Specialist, will take our apparatus from a rack container, set up the apparatus, attach electrodes for measurements of eye movement and muscle activity, conduct the L-4 Visual Stability Experiment, conduct one session of the manual control experiment, and then dissemble and stow the apparatus. In addition to the flight experiment, pre-flight and post-flight experiments will be conducted. The data of three sessions on orbit will reflect adaption of physiological systems to microgravity. The data of post-flight experiments, on the other hand, will reflect re-adaptation of physiological systems to the gravity condition on the ground. Control data collected with and without psychological tension will be scheduled just prior to and long before launch.

Tada, Akira↗

Laboratory time series moisture manipulative experiment from sediment across San Antonio, Texas: time series aerobic respiration and geochemistry

This dataset supports a broader study examining the effects of wetting and drying on hyporheic zone respiration. The dataset provides data generated from a laboratory moisture manipulation experiment. The contents include time series aerobic respiration and moisture; dissolved oxygen; sediment geochemistry data; and field metadata (including qualitative information on instream and river corridor characteristics). Samples were collected as part of the WHONDRS Allison Veach collaboration (AV1). The data package associated with the AV1 study is available at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2529428. AV1 sampling occurred across 7 perennial and 7 intermittent streams in San Antonio, Texas. Each stream/site was visited both in summer during base flow (July-September 2023) and winter during peak flow (January-February 2024). This study uses subsamples from a subset of AV1 samples. The original field samples were labeled as AV1_###. Subsequent subsamples for this study were labeled as EV_###. The labels from the field samples and the EV subsamples can be mapped directly based on the digits following the prefix and underscore (i.e., EV_001 is a subsample from AV1_001). See the critical details section below for more details on sample naming. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) field protocol; and a (6) a subfolder with sediment sample data from the incubation experiment. The sample data subfolder contains (1) effect size; (2) iron (II); (3) gravimetric moisture; (4) respiration rates; (5) raw dissolved oxygen values and plots; (6) specific conductance; (7) pH; (8) temperature; (9) a summary containing mean, median, and standard deviation values of each data type for each treatment (wet and dry); and (10) methods codes. All files are .csv or.pdf.

54 ENVIRONMENTAL SCIENCES↗

Analysis of Archived Prompt Pulse Data from the SNS HYSPEC Instrument - Paper 68

This is an investigation by the Neutronics team at the Spallation Neutron Source (SNS) to understand the Hybrid-Spectrometer (HYSPEC) pulsed background problem and ultimately lend qualitative insight toward future shielding considerations. The archived user data from HYSPEC was accessed and manipulated via Mantidplot. Algorithms have been written to identify the background feature, or 'prompt pulse', in these data files and how it fluctuates as a function of time. Correlations between these fluctuations and external/internal physical changes are being analyzed in an attempt to model the behavior of the pulsed background in the SNS target building. Understanding the contributing factors of the background may help mitigate current effects as well as potential effects in future target facilities. This information is initially being used to indicate how the local shielding arrangements and general geometry of the target building and/or greater facility affect the prompt pulse as received by HYSPEC. Additionally, this better understanding of the pulsed background will continue to help our team lend increasingly accurate advice concerning future shielding improvements, minimization of prompt pulse features in the HYSPEC data, other inelastic instruments in the current target facility and suggestions for second target station planning. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

To Derive or Not to Derive: I/O Libraries Take Charge of Derived Quantities Computation

The ever-increasing volume of data produced by HPC simulations necessitates scalable methods for data exploration and knowledge extraction. Scientific data analysis often involves complex queries across distributed datasets, requiring manipulation of multiple primary variables and generating derived data that needs to be handled efficiently, creating challenges for applications that need to parse many large datasets. Relying on individual applications to handle all intermediate data generally leads to redundant computations across studies and unnecessary data transfers. In this paper, we investigate the performance of different approaches where applications define derived variables as quantities of interest (QoIs) and offload the computation and transfer of these QoIs to the I/O library. This significantly reduces redundancy and optimizes data movement across the distributed storage and processing infrastructure by allowing control over when and where derived variables are computed. We present a detailed analysis of the performance-storage trade-offs associated with different solutions and showcase results for our study on two large-scale datasets created from climate and combustion simulations.

Gainaru, Ana↗

First Order Temporal Logic Monitoring with BDDs

Runtime verification is aimed at analyzing execution traces stemming from a running program or system. The traditional purpose is to detect the lack of conformance with respect to a formal specification. Numerous efforts in the field have focused on monitoring so-called parametric specifications, where events carry data, and formulas can refer to such. Since a monitor for such specifications has to store observed data, the challenge is to have an efficient representation and manipulation of Boolean operators, quantification, and lookup of data. The fundamental problem is that the actual values of the data are not necessarily bounded or provided in advance. In this work we explore the use of Binary Decision Diagrams (BDDs) for representing observed data. Our experiments show a substantial improvement in performance compared to related work.

Ulus, Dogan↗

A farewell to arms: using X-ray synchrotron imaging to investigate autotomy in brittle stars

Autotomy, the self-induced loss of a body structure, occurs in every living class of echinoderms and is related to the remarkable regeneration capabilities of the group. It is particularly prevalent in brittle stars (Class Ophiuroidea). Autotomy is facilitated by mutable collagenous tissue (MCT), which undergoes nervous system-mediated changes in tensile stiffness, tensile strength, and viscosity. Previous investigations of autotomy have been based on observations of the external surface, surgical manipulation of internal structures, or data on the morphology of structures post-autotomy. We used fast phase-contrast X-ray synchrotron imaging to visualize full autotomy events in vivo in the arms of specimens of the brittle star Ophioderma brevispina . This method requires no chemical or surgical manipulation and enabled us to identify several key stages in the autotomy process. We used this methodology to observe critical changes within the internal structure of the arm as it transitions from a functional mechanical apparatus to a dysfunctional disarticulated state. This method is the first in which the full intersegmental plane of the arm can be observed during autotomy. In conclusion, it can be applied to visualize autotomy and motion in vivo in other brittle star taxa, as well as in other groups such as asteroids and arthropods.

59 BASIC BIOLOGICAL SCIENCES↗

Portable Extensible Viewer

The use of Nonuniform Rational B-Splines (NURBS) to represent geometry and data offers a standard way to facilitate the multidisciplinary analysis and design of aeropropulsion products. Using standard geometry defined by NURBS throughout design, analysis, part definition, manufacture, and test processes saves money and time. The Portable Extensible Viewer (PEV) offers engineers of different disciplines a means to view and manipulate NURBS geometry and associated data. Under the guidance of a team of Lewis, Boeing Company, and Navy personnel, PEV was developed by NASA Lewis Research Center's Computer Services Division for Lewis' Interdisciplinary Technology Office. The aeropropulsion industry provided input to the design requirements.

Horowitz, Jay G.↗

Laboratory time series moisture manipulative experiment from sediment across the contiguous US: time series aerobic respiration and geochemistry (v2)

This dataset supports a broader study examining the effects of wetting and drying on hyporheic zone respiration across the contiguous United States (CONUS). The dataset provides data generated from a laboratory moisture manipulation experiment. The contents include time series aerobic respiration and moisture; dissolved oxygen; sediment geochemistry data; and field metadata (including qualitative information on instream and river corridor characteristics). Samples were collected as part of the WHONDRS CONUS-Scale Model-Sample Study (CM). This study was designed following ICON (integrated, coordinated, open, and networked) principles to facilitate a model-experiment (ModEx) iteration approach, leveraging crowdsourced sampling across the CONUS. The data package associated with the CM study is available at https://data.ess-dive.lbl.gov/view/doi:10.15485/1923689. CM sampling began in April 2022 and ended in October 2023. This study uses subsamples from a subset of CM samples collected between June 2022 and June 2023. The original field samples were labeled as CM_###. Subsequent subsamples for this study were labeled as EC_###. The labels from the field samples and the EC subsamples can be mapped directly based on the digits following the prefix and underscore (i.e., EC_001 is a subsample from CM_001). See the critical details section below for more details on sample naming. This data package was originally published in August 2024. It was updated in February 2026 (v2; new and modified files). See the change history section in the readme for more details. For details on how to navigate this data package, see this infographic from the River Corridor SFA https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of one folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data and one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) field protocol; and a (6) a subfolder with sediment sample data from the incubation experiment. The sample data subfolder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC); (2) total nitrogen (TN); (3) adenosine triphosphate (ATP); (4) percent carbon and nitrogen; (5) effect size; (6) iron (II); (7) gravimetric moisture; (8) respiration rates and raw dissolved oxygen values; (9) specific conductance; (10) pH; (11) temperature; (12) a summary containing median values of each data type for each treatment (wet and dry); (13) methods codes; (14) FTICR-MS methods; and (15) a subfolder of 9.4 Tesla FTICR-MS data. This folder contains three subfolders, one containing the sediment .xml data files, one containing the sediment CoreMS output files, the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .ref, or .xml.

54 ENVIRONMENTAL SCIENCES↗

WHONDRS laboratory time series moisture manipulative experiment from soil core layers across eastern contiguous US: time series aerobic respiration, geochemistry, and aggregates

This dataset supports a broader study examining the effects of wetting and drying on soil layers across the eastern contiguous United States (CONUS). The dataset provides data generated from a laboratory moisture manipulation experiment. The contents include time series aerobic respiration and moisture; dissolved oxygen; sediment geochemistry data; and field metadata. Samples were collected as part of a collaboration between WHONDRS (Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems; https://whondrs.pnnl.gov) and MONet (Molecular Observation Network; https://www.emsl.pnnl.gov/monet). The field samples (soil cores) were labeled as MEL_##_COR and subsequent subsamples begin with MEL_##. Additional subsamples were taken for the laboratory experiment and were labeled as EL_##. The labels from the MEL field samples and the EL subsamples can be mapped directly based on the digits following the prefix and underscore (i.e., EL_01 is a subsample from MEL_01). See the critical details section below for more details on sample naming and experimental design.For details on how to navigate this data package, see this infographic from the River Corridor SFA https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About.In addition to this readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions.This dataset is comprised of (1) a folder containing environmental context photos; (2) file-level metadata; (3) data dictionary; (4) field metadata; (5) readme; (6) international generic sample number (IGSN) mapping file; and (7) a subfolder with soil sample data from field samples and the incubation experiment. The sample data subfolder contains (1) effect size; (2) gravimetric moisture from field samples and incubation experiment; (3) respiration rates, raw dissolved oxygen values, and plots; (4) specific conductance, pH, and temperature from the incubation; (5) soil aggregates; (6) a summary containing median values of each data type for each treatment (wet and dry) in the incubation; (7) a summary containing averages for each data type of each soil layer; and (8) methods codes. All files are .csv, .pdf, .jpeg, or .jpg.

54 ENVIRONMENTAL SCIENCES↗

Lunar Instrument Data Integration Into the Virtual Reality Mission Simulation System for Decision Communication and Situational Awareness

In situ resource utilization (ISRU) technologies are a key advancement required to make human habitation on the Moon and Mars viable. The upcoming Volatiles Investigating Polar Exploration Rover (VIPER) mission will provide crucial correlations between volatiles and lunar geology to understand the water content available for ISRU on the moon. The mission will require the coordination of multi-disciplinary teams across the country making real time decisions based on rover instrument data. The virtual reality Mission Simulation System (vMSS) is a virtual reality platform designed at MIT by the Resource Exploration and Science of our Cosmic Environment (RESOURCE) team to provide teams with a collaboration interface for planetary missions like VIPER. Herein we determine the integration pathway for analog based datasets that are examples of VIPER's two main instruments, the near-infrared volatile spectrometer subsystem (NIRVSS) and the neutron spectrometer subsystem (NSS), into vMSS to provide the most valuable visualization tools. Focusing on improving situational awareness, decision making, reducing task load and incorporating comments from scientists working previous analogs and on the current VIPER mission, we recommend critical elements to implement into vMSS and the best approaches for data visualization. We present a review of relevant analogs and state of the art mission software. We have developed a design concept and path to flight of analysed instrument data integrated with data maps that allow for virtual manipulation and annotation between non-co-located team members. We focus on pre-mission mapping of a priori data for improved situational awareness, layering of analysed instrument data, correlative mapping and interactive capabilities for in-mission decision making, as well as archiving and annotation tools for post-mission analysis. Finally, we lay out the roadmap for the future development of immersive sample site visualization capabilities and the use of integrated instrument data in vMSS with automated temporal and geospatial planning.

Cody Alison Paige↗

Dynamic radionuclide determination of regional left ventricular wall motion using a new digital imaging device

In 47 men with arteriographically defined coronary artery disease comparative studies of left ventricular ejection fraction and segmental wall motion were made with radionuclide data obtained from the image intensifier camera computer system and with contrast cineventriculography. The radionuclide data was digitized and the images corresponding to left ventricular end-diastole and end-systole were identified from the left ventricular time-activity curve. The left ventricular end-diastolic and end-systolic images were subtracted to form a silhouette difference image which described wall motion of the anterior and inferior left ventricular segments. The image intensifier camera allows manipulation of dynamically acquired radionuclide data because of the high count rate and consequently improved resolution of the left ventricular image.

Steele, P.↗

Managing Data in a GIS Environment

A Geographic Information System (GIS) is a computer-based system that enables capture, modeling, manipulation, retrieval, analysis and presentation of geographically referenced data. A GIS operates in a dynamic environment of spatial and temporal information. This information is held in a database like any other information system, but performance is more of an issue for a geographic database than a traditional database due to the nature of the data. What distinguishes a GIS from other information systems is the spatial and temporal dimensions of the data and the volume of data (several gigabytes). Most traditional information systems are usually based around tables and textual reports, whereas GIS requires the use of cartographic forms and other visualization techniques. Much of the data can be represented using computer graphics, but a GIS is not a graphics database. A graphical system is concerned with the manipulation and presentation of graphical objects whereas a GIS handles geographic objects that have not only spatial dimensions but non-visual, i e., attribute and components. Furthermore, the nature of the data on which a GIS operates makes the traditional relational database approach inadequate for retrieving data and answering queries that reference spatial data. The purpose of this paper is to describe the efficiency issues behind storage and retrieval of data within a GIS database. Section 2 gives a general background on GIS, and describes the issues involved in custom vs. commercial and hybrid vs. integrated geographic information systems. Section 3 describes the efficiency issues concerning the management of data within a GIS environment. The paper ends with a summary of the main concerns of this paper.

Beltran, Maria↗

Forecasting Solar Photovoltaic Power Production: A Comprehensive Review and Innovative Data-Driven Modeling Framework

The intermittent and stochastic nature of Renewable Energy Sources (RESs) necessitates accurate power production prediction for effective scheduling and grid management. This paper presents a comprehensive review conducted with reference to a pioneering, comprehensive, and data-driven framework proposed for solar Photovoltaic (PV) power generation prediction. The systematic and integrating framework comprises three main phases carried out by seven main comprehensive modules for addressing numerous practical difficulties of the prediction task: phase I handles the aspects related to data acquisition (module 1) and manipulation (module 2) in preparation for the development of the prediction scheme; phase II tackles the aspects associated with the development of the prediction model (module 3) and the assessment of its accuracy (module 4), including the quantification of the uncertainty (module 5); and phase III evolves towards enhancing the prediction accuracy by incorporating aspects of context change detection (module 6) and incremental learning when new data become available (module 7). This framework adeptly addresses all facets of solar PV power production prediction, bridging existing gaps and offering a comprehensive solution to inherent challenges. By seamlessly integrating these elements, our approach stands as a robust and versatile tool for enhancing the precision of solar PV power prediction in real-world applications.

14 SOLAR ENERGY↗

A Science Information Infrastructure for Access to Earth and Space Science Data through the Nation's Science Museums

In this project, we worked with the University of California at Berkeley/Center for Extreme Ultraviolet Astrophysics and five science museums (the National Air and Space Museum, the Science Museum of Virginia, the Lawrence Hall of Science, the Exploratorium., and the New York Hall of Science) to formulate plans for computer-based laboratories located at these museums. These Science Learning Laboratories would be networked and provided with real Earth and space science observations, as well as appropriate lesson plans, that would allow the general public to directly access and manipulate the actual remote sensing data, much as a scientist would.

Murray, S.↗

SNNPG: Using Spiking Neural Networks to Detect Attacks in the Power Grid

We explore the potential of Spiking Neural Networks (SNN) to enhance the security of power grid operations by detecting False Data Injection (FDI) attacks. These attacks manipulate PMU readings, leading to erroneous control decisions and grid disruptions. We develop a method to convert Phase Measurement Unit (PMU) data into spike trains, capturing both temporal and spatial dimensions. Using an SNN model, we conduct evaluations with simulated power grid data, showcasing accuracy in detecting FDI attacks. SNN models rapidly identify anomalies in real-time PMU data, safeguarding grid operations by alerting operators to irregular readings and preventing incorrect decisions.

artificial intelligence↗