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At least 433 records · Page 24

Generation Mechanisms UV and X-ray Emissions During SL9 Impact

The purpose of this grant was to study the ultraviolet and X-ray emissions associated with the impact of comet Shoemaker-Levy 9 with Jupiter. The University of Michigan task was primarily focused on theoretical calculations. The NAGW-4788 subtask was to be largely devoted to determining the constraints placed by the X-ray observations on the physical mechanisms responsible for the generation of the X-rays. Author summarized below the ROSAT observations and suggest a physical mechanism that can plausibly account for the observed emissions. It is hoped that the full set of activities can be completed at a later date. Further analysis of the ROSAT data acquired at the time of the impact was necessary to define the observational constraints on the magnetospheric-ionospheric processes involved in the excitation of the X-ray emissions associated with the fragment impacts. This analysis centered around improvements in the pointing accuracy and improvements in the timing information. Additional pointing information was made possible by the identification of the optical counterparts to the X-ray sources in the ROSAT field-of-view. Due to the large number of worldwide observers of the impacts, a serendipitous visible plate image from an observer in Venezuela provided a very accurate location of the present position of the X-ray source, virtually eliminating pointing errors in the data. Once refined, the pointing indicated that the two observed X-ray brightenings that were highly correlated in time with the K and P2 events were brightenings of the X-ray aurora (as identified in images prior to the impact).Appendix A "ROSAT observations of X-ray emissions from Jupiter during the impact of comet Shoemaker-Levy 9' also included.

Waite, J. Hunter, Jr.↗

Virtual Observatories for Space Physics Observations and Simulations: New Routes to Efficient Access and Visualization

New tools for data access and visualization promise to make the analysis of space plasma data both more efficient and more powerful, especially for answering questions about the global structure and dynamics of the Sun-Earth system. We will show how new existing tools (particularly the Virtual Space Physics Observatory-VSPO-and the Visual System for Browsing, Analysis and Retrieval of Data-ViSBARD; look for the acronyms in Google) already provide rapid access to such information as spacecraft orbits, browse plots, and detailed data, as well as visualizations that can quickly unite our view of multispacecraft observations. We will show movies illustrating multispacecraft observations of the solar wind and magnetosphere during a magnetic storm, and of simulations of 3 0-spacecraft observations derived from MHD simulations of the magnetosphere sampled along likely trajectories of the spacecraft for the MagCon mission. An important issue remaining to be solved is how best to integrate simulation data and services into the Virtual Observatory environment, and this talk will hopefully stimulate further discussion along these lines.

Roberts, Aaron↗

Further analysis of EVA self-rescue data

Results of an EVA study performed in the Virtual Interactive Environment Workstation at the NASA Ames Research Center are presented. Three initial separation velocities (0.5, 1.0, and 1.5 m/s) were crossed with five initial spin velocities (0, +/-0.1, +/-0.3) to yield 15 different trials. An attitude hold system was also modeled, which, when combined with the 15 combinations of separation and spin velocity, provided 30 distinct trials. Recent examinations of the data reveal that initial separation velocity and initial spin velocity each produced the main effects and combined to produce an interaction effect on the solution time. The solution time increased with the initial velocity and absolute initial spin velocity. The final roll angle also increased the initial spin velocity. The attitude hold fuel increased with absolute initial spin velocity. Interaction effects revealed that the main effects were less pronounced at the lowest initial velocity level.

Brody, Adam R.↗

Enhancement of the NMSU Channel Error Simulator to Provide User-Selectable Link Delays

This is the third in a continuing series of reports describing the development of the Space-to-Ground Link Simulator (SGLS) to be used for testing data transfers under simulated space channel conditions. The SGLS is based upon Virtual Instrument (VI) software techniques for managing the error generation, link data rate configuration, and, now, selection of the link delay value. In this report we detail the changes that needed to be made to the SGLS VI configuration to permit link delays to be added to the basic error generation and link data rate control capabilities. This was accomplished by modifying the rate-splitting VIs to include a buffer the hold the incoming data for the duration selected by the user to emulate the channel link delay. In sample tests of this configuration, the TCP/IP(sub ftp) service and the SCPS(sub fp) service were used to transmit 10-KB data files using both symmetric (both forward and return links set to 115200 bps) and unsymmetric (forward link set at 2400 bps and a return link set at 115200 bps) link configurations. Transmission times were recorded at bit error rates of 0 through 10(exp -5) to give an indication of the link performance. In these tests. we noted separate timings for the protocol setup time to initiate the file transfer and the variation in the actual file transfer time caused by channel errors. Both protocols showed similar performance to that seen earlier for the symmetric and unsymmetric channels. This time, the delays in establishing the file protocol also showed that these delays could double the transmission time and need to be accounted for in mission planning. Both protocols also showed a difficulty in transmitting large data files over large link delays. In these tests, there was no clear favorite between the TCP/IP(sub ftp) and the SCPS(sub fp). Based upon these tests, further testing is recommended to extend the results to different file transfer configurations.

Horan, Stephen↗

Virtual Observatories: Are We Virtually There Yet?

Virtual observatories are tools for simplifying access to and use of astronomical data from an increasing number of data sources of rapidly growing volume. Now that a variety of virtual observatory development efforts are under way around the world, a cursory review of the efforts outside solar physics, and an only slightly more detailed consideration of those within, demonstrates a commonality of conceptual model if not of approach or application. The linkages among virtual observatories optimized for different scientific communities present an interesting challenge to the designers: should virtual observatories be designed for the most expert users? For the least? For everyone? It is too early to provide definitive answers, but examination of current efforts does offer some clues.

Gurman, J. B.↗

Scientific Uses and Directions of SPDF Data Services

From a science user's perspective, the multi-mission data and orbit services of NASA's Space Physics Data Facility (SPDF) project perform as a working and highly functional heliophysics virtual observatory. CDAWeb enables plots, listings and file downloads for current data across the boundaries of missions and instrument types (and now including data from THEMIS and STEREO), VSPO access to a wide range of distributed data sources. SSCWeb, Helioweb and our 3D Animated Orbit Viewer (TIPSOD) provide position data and query logic for most missions currently-important to heliophysics science. OMNIWeb with its new extension to 1- and 5- minute resolution provides interplanetary parameters at the Earth's bow shock as a unique value-added data product. To enable easier integrated use of our capabilities by developers and by the emerging heliophysics VxOs, our data and services are available through webservices-based APls as well as through our direct user interfaces. SPDF has also now developed draft descriptions of its holdings in SPASE-compliant XML In addition to showcasing recent enhancements to SPDF capabilities, we will use these systems and our experience in developing them: to demonstrate a few typical science use cases; to discuss key scope and design issues among users, service providers and end data providers; and to identify key areas where existing capabilities and effective interface design are still inadequate to meet community needs.

Fung, Shing↗

An Intelligent Archive Testbed Incorporating Data Mining

Many significant advances have occurred during the last two decades in remote sensing instrumentation, computation, storage, and communication technology. A series of Earth observing satellites have been launched by U.S. and international agencies and have been operating and collecting global data on a regular basis. These advances have created a data rich environment for scientific research and applications. NASA s Earth Observing System (EOS) Data and Information System (EOSDIS) has been operational since August 1994 with support for pre-EOS data. Currently, EOSDIS supports all the EOS missions including Terra (1999), Aqua (2002), ICESat (2002) and Aura (2004). EOSDIS has been effectively capturing, processing and archiving several terabytes of standard data products each day. It has also been distributing these data products at a rate of several terabytes per day to a diverse and globally distributed user community (Ramapriyan et al. 2009). There are other NASA-sponsored data system activities including measurement-based systems such as the Ocean Data Processing System and the Precipitation Processing system, and several projects under the Research, Education and Applications Solutions Network (REASoN), Making Earth Science Data Records for Use in Research Environments (MEaSUREs), and the Advancing Collaborative Connections for Earth-Sun System Science (ACCESS) programs. Together, these activities provide a rich set of resources constituting a value chain for users to obtain data at various levels ranging from raw radiances to interdisciplinary model outputs. The result has been a significant leap in our understanding of the Earth systems that all humans depend on for their enjoyment, livelihood, and survival. The trend in the community today is towards many distributed sets of providers of data and services. Despite this, visions for the future include users being able to locate, fuse and utilize data with location transparency and high degree of interoperability, and being able to convert data to information and usable knowledge in an efficient, convenient manner, aided significantly by automation (Ramapriyan et al. 2004; NASA 2005). We can look upon the distributed provider environment with capabilities to convert data to information and to knowledge as an Intelligent Archive in the Context of a Knowledge Building system (IA-KBS). Some of the key capabilities of an IA-KBS are: Virtual Product Generation, Significant Event Detection, Automated Data Quality Assessment, Large-Scale Data Mining, Dynamic Feedback Loop, and Data Discovery and Efficient Requesting (Ramapriyan et al. 2004).

Ramapriyan, H.↗

Virtual Log-Structured Storage for High-Performance Streaming

Over the past decade, given the higher number of data sources (e.g., Cloud applications, Internet of things) and critical business demands, Big Data transitioned from batch-oriented to real-time analytics. Stream storage systems, such as Apache Kafka, are well known for their increasing role in real-time Big Data analytics. For scalable stream data ingestion and processing, they logically split a data stream topic into multiple partitions. Stream storage systems keep multiple data stream copies to protect against data loss while implementing a stream partition as a replicated log. This architectural choice enables simplified development while trading cluster size with performance and the number of streams optimally managed. This paper introduces a shared virtual log-structured storage approach for improving the cluster throughput when multiple producers and consumers write and consume in parallel data streams. Stream partitions are associated with shared replicated virtual logs transparently to the user, effectively separating the implementation of stream partitioning (and data ordering) from data replication (and durability). We implement the virtual log technique in the KerA stream storage system. When comparing with Apache Kafka, KerA improves the cluster ingestion throughput by up to 4x when multiple producers write over hundreds of data streams.

consistent stream ordering↗

Physics-Informed Recurrent Neural Networks to Predict Reactor Operations of the AGN-201 Nuclear Reactor

4 page paper submitted to ANS Student conference. Summary of paper similar to the following abstract: The ability to predict how a reactor will operate, understand when anomalous conditions arise, and ensure a reactor is being operated as expected is crucial for deploying new nuclear facilities. Digital twins serve as a unique solution to recognizing reactor behavior; however, they require data to be useful. For next-generation reactors, this data may not currently be available. To explore how synthetic physics-informed reactor data can be used to predict reactor operations, a recurrent neural network was implemented for the Idaho State University AGN-201 digital twin. The goal of this work is to determine how synthetic data can be used to train a recurrent neural network model for predicting the reactor power of the AGN-201. The recurrent neural network was validated using both synthetic and real operational data. We envision this approach will help bridge the gap between the virtual and physical sides of a digital twin, where reactor physics models based on as-built data can be corrected for actual operating parameters to ensure the virtual model mirrors reality.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Comparisons of the dimensionality and features of simulated Landsat-4 MSS and TM data

The spectral characteristics of the Landsat-4 MSS and TM are compared using signal counts simulated from field-measured reflectance spectra. The Dave atmospheric model and prelaunch sensor characteristics are also used in the simulation. Comparison is made based on individual bands and Tasseled Cap transformed data. TM bands 2, 3, and 4 are shown to contain virtually all the information contained in the four MSS bands. Tasseled Cap transformed data from the six reflective bands of the TM are shown to contain at least one and possibly two additional dimensions of information beyond the two dimensions in MSS data, while still providing a direct association with the MSS Tasseled Cap features.

Crist, E. P.↗

Interactive Metadata Integration with Brick

Many different digital representations of a building are produced over the course of its lifecycle. While these representations individually contain metadata required to support different stages of the building's lifecycle, they are largely not interoperable due to differences in structure, syntax and semantics. This impedes the development and deployment of data-driven applications providing fault detection and diagnosis, virtual metering or optimal control. [4] introduces a new platform for the continuous curation of a unified, Brick [1]-based metadata model that can be maintained throughout the building lifecycle. In this demonstration, we present a live proof-of-concept implementation of the platform with support for several metadata representations in the context of a simulated building lifecycle.

Fierro, Gabe↗

Structural stability of thin overhanging walls during material extrusion additive manufacturing of thermoset-based ink

Recent developments have enabled material extrusion additive manufacturing of thermoset-based composite inks on the large scale. In addition, printing out-of-plane components is of broad interest to the polymer material extrusion community. Here, we address some of the challenges associated with both large-scale and out-of-plane thermoset material extrusion additive manufacturing by studying the height at which thin overhanging walls collapse. Walls at a range of overhang angles were printed until they collapsed. An optical camera captured the profile of each wall throughout the print, allowing the collapse height to be identified and the geometric fidelity to the programmed angle to be evaluated. Using previously measured rheological properties, predictive models were generated to approximate the collapse height and profile of the deflected walls. First, an analytical model was created to predict the height at which the walls would yield. The analytical model assumes the walls exhibit a perfectly linear profile; however, experiments proved this assumption to be false. Therefore, a finite element simulation was developed to account for the elastic deflection that occurs during printing. The finite element simulation predicts both the yield height and the deflected profile after the deposition of each layer. For the properties of the thermoset ink used here, the yield height predicted by the analytical model and finite element simulation are virtually identical. These predictions match experimental data reasonably well, but minor errors are observed. Accounting for the fully plastic moment appears to explain the small mismatch between experimental data and predictions. Additionally, the finite element simulation provides an excellent prediction of the deflected profile before the wall begins to collapse. Finally, by demonstrating that the collapse height and deflected profile of thin overhanging walls can be predicted, this work illustrates how the soft viscoelastic properties of thermoset-based composite inks limit the scale of a key feature required to print some nonplanar components. It also provides a basis to tailor in-process curing systems to suppress deflection and collapse of thin overhanging walls.

36 MATERIALS SCIENCE↗

IRIS: A Performance-Portable Framework for Cross-Platform Heterogeneous Computing

From edge to exascale, computer architectures are becoming more heterogeneous and complex. The systems typically have fat nodes, with multicore CPUs and multiple hardware accelerators such as GPUs, FPGAs, and DSPs. This complexity is causing a crisis in programming systems and performance portability. Several programming systems are working to address these challenges, but the increasing architectural diversity is forcing software stacks and applications to be specialized for each architecture. As we show, all of these approaches critically depend on their software framework for discovery, execution, scheduling, and data orchestration. To address this challenge, we believe that a more agile and proactive software framework is essential to increase performance portability and improve user productivity. To this end, we have designed and implemented IRIS: a performance-portable framework for cross-platform heterogeneous computing. IRIS can discover available resources, manage multiple diverse programming platforms (e.g., CUDA, Hexagon, HIP, Level Zero, OpenCL, OpenMP) simultaneously in the same execution, respect data dependencies, orchestrate data movement proactively, and provide for user-configurable scheduling. To simplify data movement, IRIS introduces a shared virtual device memory with relaxed consistency among different heterogeneous devices. IRIS also adds an automatic kernel workload partitioning technique using the polyhedral model so that it can resize kernels for a wide range of devices. Our evaluation on three architectures, ranging from Qualcomm Snapdragon to a Summit supercomputer node, shows that IRIS improves portability across a wide range of diverse heterogeneous architectures with negligible overhead.

97 MATHEMATICS AND COMPUTING↗

Dynamic Bayesian Networks for Fault Prognosis

A dynamic Bayesian Network (DBN)-based fault prognosis framework is proposed in this study to predict the future fault probabilities of gradual faults. The proposed framework utilizes the trend in prediction error generated from data driven forecasting models to estimate the future fault beliefs. The accuracy and scalability of the proposed method is evaluated using the data from a Modelica-based virtual testbed. Overall, the developed framework demonstrates good potential in estimating future fault probabilities of gradual faults.

Pradhan, Ojas↗

Sensor enabled data-driven predictive analytics for modeling and control with high penetration of DERs in distribution systems

The electric power grid is undergoing a tremendous transformation due to the increasing penetration of renewable energy resources beginning with wind and more recently with the distributed energy resources (DERs) such as solar and battery storage. DERs have dramatically changed the role of the distribution systems in the overall power grid, and they are expected to contribute a significant portion of power generation in the future. If current trends for DERs continue, system operation and control will need to change dramatically for improved grid reliability and resiliency. As renewable resources increase in penetration, new and challenging operational, planning, and design problems are expected to emerge. Some of the key challenges that arise in the planning and operation of the future grid are: 1) Quantifying the impact of high DER penetration in distribution systems on bulk grid behavior over multiple time scales. 2) Identifying whether a particular DER configuration/settings have a large impact on the overall grid behavior. These challenges can be addressed in an offline manner using detailed T&D grid models and they can also be addressed in an online manner using sensor measurements. In particular, the advancement and planned growth in sensor technology in power grid over various voltage levels provide us with a unique opportunity to tackle these challenges from a data analytic perspective without needing detailed T&D grid models. A few questions that naturally arise when addressing the challenges from DERs using sensor data are: 1) How can we use limited sensor measurements to monitor & control voltage stability and small signal stability of the bulk system? 2) How can we ensure that the developed data analytic methods are robust to data availability and quality issues? 3) How can we compute the developed analytics in a scalable manner using streaming measurements? In this project, we addressed the aforementioned challenges arising from DERs and answered the questions raised above on how to effectively use the sensor measurements to enhance the reliability and performance of the electric grid. Thus, the overarching goal of this project is to develop effective reduced/representative system models from data that make the computational complexity sufficiently manageable so as to be useful to simulate, analyze, and even control complex non-linear power systems dynamics with large penetrations of DERs. In order to achieve the objective, the project team established a four-fold technical approach 1) Formulated a combined transmission-distribution co-simulation framework for data generation and validation, 2) Derived reduced/representative models of power systems based on data-driven methods for efficient computation and appropriate representation of system behavior, 3) Developed data driven characterization of power system behavior based on transfer operator theory, machine learning and optimization for model estimation, 4) Incorporated a scalable data management and processing architecture using distributed Kafka streaming applications that coordinate input data streams to the developed data analytics. The key accomplishments of the project are: 1) Development of a scalable multi-timescale T&D co-simulation framework (both for steady state and for dynamic co-simulation) using commercial solvers (PSSE and GridLAB-D). The steady-state T&D co-simulation interface is shared with our industry partner (PJM). 2) A structured reduced order dynamic model of distribution systems that can represent partial motor stalling along with a systematic procedure to derive the model parameters. 3) A PMU based online method to monitor, localize and mitigate fault-induced delayed voltage recovery using DER reactive support and load control in distribution systems. 4) Development of linear operator based robust methodologies for dynamic state estimation, uncertainty quantification, system identification and trajectory prediction for power system dynamics. 5) An adaptive damping control for utilizing wind energy resources to provide oscillation damping and system stability. 6) Implementation of Kafka-based framework for efficient processing of streaming data using Linux-based local virtual environment.

DER integration↗

Visualization for Scientific Discovery, Decision-Making, and Communication

Visualization–the use of visual elements to explore data, form hypotheses, or convey conclusions–is an integral part of the scientific process. Starting from an initial exploration of new data to illustrating outcomes to the general public, visualization is one of the most intuitive and powerful modes of communication. With the explosion of new data sources and types, unprecedented volumes of data, and new technologies, such as virtual reality and AI, visualization has become increasingly essential but also ever more challenging. Department of Energy’s (DOE) Office of Advanced Scientific Computing Research (ASCR) sponsored a Basic Research Needs workshop in January 2022 to understand the major opportunities and grand challenges in visualization tools and technologies for scientific computing, with a special focus on DOE-relevant applications and goals. The workshop identified five priority research directions (PRDs) for visualization to support scientific discovery, decision-making, and communication.

97 MATHEMATICS AND COMPUTING↗

New Baryon State N'(1720)3/2+ from the CLAS pi^+pi^--p Photo- and Electroproduction Data

Combined studies of exclusive meson photo- and electroproduction have extended the capabilities in the search for new excited states of the nucleon, the so called ?missing? resonances. New excited state of the nucleon, N?(1720)3/2+ has been observed in the combined studies of the pi^+pi^-p photo- and electroproduction off protons data measured with the CLAS detector at Jlab. The results on the new baryon state observation will be presented and discussed in the talk. A successful description of the pi^+pi^-p photo- and electroproduction data achieved with independent from photon virtualities (Q^2) mass, total and partial hadronic decay widths of N?(1720)3/2^+ state offers a strong evidence for the existence of this new resonance. Currently, N?(1720)3/2^+ resonance is the only observed new baryon state for which the results on Q^2-evolution of the electroexcitation amplitudes have become available. They offer an insight into the ?missing? resonance structure for the first time. Future analyses of the N?(1720)3/2^+ electroexcitation amplitudes will shed light on the particular structural features of ?missing? resonances which made their observation so challenging for decades

Mokeev, Viktor↗

Aerodynamic heat transfer to a hypersonic research aircraft model /X-24C/ at Mach 6

The paper reports on results of heat-transfer tests conducted on a 1/29-scale model of the X-24C-12I hypersonic research aircraft configuration in a Mach 6 tunnel at a Reynolds number of thirteen million using the phase-change heat transfer technique. Sequences of phase-change heat transfer pattern photographs are presented showing windward side and leeward side heating processes. Theoretical predictions of dimensionless heat transfer coefficients along a data line on lower fuselage and on fuselage side bracket the experimental values. A turbulent heating theory gives good agreement with data when shifted to a new virtual origin.

Lawing, P. L.↗