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DOE OSTI2022

Connecting Matrix Elements to Multi-Hadron Form-Factors

We discuss developments in calculating multi-hadron form-factors and transition processes via lattice QCD. Our primary tools are finite-volume scaling relations, which map spectra and matrix elements to the corresponding multi-hadron infinite-volume amplitudes. We focus on two hadron processes probed by an external current, and provide various checks on the finite-volume formalism in the limiting cases of perturbative interactions and systems forming a bound state. By studying model-independent properties of the infinite-volume amplitudes, we are able to rigorously define form-factors of resonances.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1987

Tectonic domains in the Eastern Hemisphere of Mars

The definition of boundaries of discrete structural provinces on the surface of Mars has previously been made by the assumptions of circular or radial symmetry (in the case of the Tharsis olateau), by artificial quadrangle boundaries for regional studies, or simply by regional geographical features. Much of the planetary structural mapping has been presented in a line or spot format in existing consortium data. Methods are being generated to convert the detailed maps of tectonic features to a format that can be used with standard image processing techniques. In this manner such data can be more readily compared to age and other attributes deduced from geological mapping, gravity results, and topography. The 24 photomosaics covering the Eastern Hemisphere of Mars have already been examined for four types of structural features: erosional remnants, ridges, graben, and scarps. When digitized, each feature was flagged according to feature type, azimuth and length. These values were stored as text files on a quad-by-quad basis for each quad studied.

Maxwell, Ted A.↗

DOE OSTI2017

QSL Squasher: A Fast Quasi-separatrix Layer Map Calculator

Quasi-Separatrix Layers (QSLs) are a useful proxy for the locations where current sheets can develop in the solar corona, and give valuable information about the connectivity in complicated magnetic field configurations. However, calculating QSL maps, even for two-dimensional slices through three-dimensional models of coronal magnetic fields, is a non-trivial task, as it usually involves tracing out millions of magnetic field lines with immense precision. Thus, extending QSL calculations to three dimensions has rarely been done until now. In order to address this challenge, we present QSL Squasher—a public, open-source code, which is optimized for calculating QSL maps in both two and three dimensions on graphics processing units. The code achieves large processing speeds for three reasons, each of which results in an order-of-magnitude speed-up. (1) The code is parallelized using OpenCL. (2) The precision requirements for the QSL calculation are drastically reduced by using perturbation theory. (3) A new boundary detection criterion between quasi-connectivity domains is used, which quickly identifies possible QSL locations that need to be finely sampled by the code. That boundary detection criterion relies on finding the locations of abrupt field-line length changes, which we do by introducing a new Field-line Length Edge (FLEDGE) map. We find FLEDGE maps useful on their own as a quick-and-dirty substitute for QSL maps. QSL Squasher allows construction of high-resolution 3D FLEDGE maps in a matter of minutes, which is two orders of magnitude faster than calculating the corresponding 3D QSL maps. We include a sample of calculations done using QSL Squasher to demonstrate its capabilities as a QSL calculator, as well as to compare QSL and FLEDGE maps.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2005

NASA Langley Trajectory Simulation Capabilities for Mars Reconnaissance Orbiter

Mars Reconnaissance Orbiter will launch in August 2005 and will achieve Mars Orbit Insertion in March of 2006. It will then take approximately six months to use the process of aerobraking to shape its orbit into the desired science mapping orbit. This six-month period is arguably the phase of the Mars Reconnaissance Orbiter mission with the highest risk to the spacecraft, dipping to within 100 km of the planet. This process requires enough atmospheric drag to slow the spacecraft and circularize the orbit while remaining high enough in the Mars atmosphere as to not risk thermal degradation of spacecraft components. This paper will discuss the trajectory simulation and several analyses performed at NASA Langley Research Center to support a successful aerobraking phase of the Mars Reconnaissance Orbiter mission.

Prince, Jill L. Hanna↗

DOE OSTI2020

Selective Sampling for Sensor Type Classification in Buildings

A key barrier to applying any smart technology to a building is the requirement of locating and connecting to the necessary resources among the thousands of sensing and control points, i.e., the metadata mapping problem. Existing solutions depend on exhaustive manual annotation of sensor metadata --- a laborious, costly, and hardly scalable process. To reduce the amount of manual effort required, this paper presents a multi-oracle selective sampling framework to leverage noisy labels from information sources with unknown reliability such as existing buildings, which we refer to as weak oracles, for metadata mapping. This framework involves an interactive process, where a small set of sensor instances are progressively selected and labeled for it to learn how to aggregate the noisy labels as well as to predict sensor types. Two key challenges arise in designing the framework, namely, weak oracle reliability estimation and instance selection for querying. To address the first challenge, we develop a clustering-based approach for weak oracle reliability estimation to capitalize on the observation that weak oracles perform differently in different groups of instances. For the second challenge, we propose a disagreement-based query selection strategy to combine the potential effect of a labeled instance on both reducing classifier uncertainty and improving the quality of label aggregation. We evaluate our solution on a large collection of real-world building sensor data from 5 buildings with more than 11,000 sensors of 18 different types. The experiment results validate the effectiveness of our solution, which outperforms a set of state-of-the-art baselines.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

NASA NTRS2019

Turning Satellite Data into Global Precipitation Maps

It's really obvious how to measure rain and snowfall just put a container out in the yard. But, it turns out the physical processes that create precipitation, and the practicalities of taking measurements everywhere, make satellites key tools in mapping rain and snowfall around the globe. Employing satellites in this meteorological detective story involves some science, some technology, a lot of computing, and, yes, rocket science. The payoff is that we know more about how much rain and snow fell in, say, 2010, than we knew at the time that it fell, and we're ready to make the same kind of estimate for tomorrow's storms. There is still a lot of work to be done to make these estimates more reliable and accurate.Dr. George J. Huffman is a Research Meteorologist at NASA Goddard Space Flight Center (GSFC), Greenbelt, Maryland. After completing a B.S. in Physics at The Ohio State University (1976) and a Ph.D. in Meteorology at Massachusetts Institute of Technology (1982), he was an Assistant Professor at University of Maryland, College Park before moving to GSFC in 1988, where he consulted for 24 years before joining NASA in 2012. Dr. Huffman focuses on the design, implementation, and extension of combined estimates of global precipitation, seeking to incorporate all available precipitation-relevant satellite and global surface data. He is the Deputy Project Scientist for the Global Precipitation Measurement (GPM) mission, the Chair of the GPM Multi-satellite Algorithm Working Group, and Chief of the Mesoscale Atmospheric Processes Lab.

Huffman, George J.↗

DOE OSTI2026

Refractory-based thermal energy storage for industrial process heat: one-dimensional modeling, control, and optimization

The variable and weather-dependent output of wind and solar power plants present a substantial challenge for planning and operating electricity-systems, particularly in the absence of cost-effective and dispatchable energy storage technologies. This study investigates a high-temperature, electrically heated, refractory-based thermal energy storage (RTES) system that stores electrical energy as sensible heat in dense ceramic bricks over the 950–1800 °C range. The stored heat can be discharged as a controlled hot-gas stream for industrial heating, fuel substitution in high-temperature processes, or electricity generation. The main novelty is a comprehensive modelling, control, mapping, and optimization framework that integrates one-dimensional transient gas–solid heat transfer, fan-assisted discharge, bypass-flow regulation, reheating logic, fan-power evaluation, insulation-loss assessment, and genetic-algorithm-based design optimization. The model uses feedback from outlet temperature and delivered power to regulate discharge, while a two-stage genetic algorithm optimizes brick-channel geometry, gas-flow operation, and multilayer insulation thicknesses. Storage capacities below 50 MWh and discharge powers of 5–30 MW are analyzed to evaluate hold time, thermal delivery, fan-power penalty, heat loss, state-of-charge evolution, and indicative capital cost. Results demonstrate that optimized and well-insulated refractory-based thermal energy storage units can provide stable, efficient, and repeatable heat delivery over multiple discharge cycles. The generated performance and cost maps support modular refractory thermal energy storage as a practical option for large-scale integration of wind and solar generation and for high-temperature industrial process heat.

25 ENERGY STORAGE↗

NASA NTRS2011

Hurricane Ike Deposits on the Bolivar Peninsula, Galveston Bay, Texas

In September 2008, Hurricane Ike made landfall on Galveston Bay, close to the NASA Johnson Space Center (JSC). The storm flooded much of the area with a storm surge ranging from 11 -20 feet. The Bolivar peninsula, the southeastern coast of Galveston Bay, experienced the brunt of the surge. Several agencies collected excellent imagery baselines before the storm and complementary data a few days afterward that helped define the impacts of the storm. In April of 2011, a team of scientists and astronauts from JSC conducted field mapping exercises along the Bolivar Peninsula, the section of the Galveston Bay coast most impacted by the storm. Astronauts routinely observe and document coastal changes from orbit aboard the International Space Station. As part of their basic Earth Science training, scientists at the Johnson Space Center take astronauts out for field mapping exercises so that they can better recognize and understand features and processes that they will later observe from the International Space Station. Using pre -storm baseline images of the Bolivar Peninsula near Rollover Pass and Gilchrist (NOAA/Google Earth Imagery and USGS aerial imagery and lidar data), the astronauts mapped current coastline positions at defined locations, and related their findings to specific coastal characteristics, including channel, jetties, and other developments. In addition to mapping, we dug trenches along both the Gulf of Mexico coast as well as the Galveston Bay coast of the Bolivar peninsula to determine the depth of the scouring from the storm on the Gulf side, and the amount of deposition of the storm surge deposits on the Bay side of the peninsula. The storm signature was easy to identify by sharp sediment transitions and, in the case of storm deposits, a layer of storm debris (roof shingles, PVC pipes, etc) and black, organic rich layers containing buried sea grasses in areas that were marshes before the storm. The amount of deposition was generally about 20 -25 cm; the local areas experiencing obvious deposition are readily obvious in post -Ike imagery of the region. We used a March 2010 aerial photograph from the NOAA -Google Earth collection because construction and vegetation recovery was minimal. Based on the before and after aerial imagery and the trenching data collected over two days, we can begin to characterize the material transported and deposited by Hurricane Ike along one stretch of the Bolivar peninsula. We summarize the results from our mapping and trenching data. The basic data collected 2.5 years after the storm are ephemeral as the storm deposits become reworked and overprinted by coastal processes, vegetation regrowth and reconstruction.

Evans, Cynthia A.↗

DOE OSTI2019

Process Mining in Healthcare - A Case Study for the Corporate Data Warehouse of the Veterans Affairs Office

Researchers at Oak Ridge National Laboratory are working with the Veteran’s Affairs Administration Office (VA) on a series of studies having the objective of detecting harmful anomalies (i.e., hazards) in VA health information technology systems using its Corporate Data Warehouse (CDW). This progress report describes an ORNL study focused on applying a process mining methodology to that CDW database. In the approach presented herein, process mining methodology is combined with additional software tools, metrics, and filters to permit a quick examination of large volumes of data to address specific research questions. In this work, a case study is presented in which the performance of the combined ORNL approach is evaluated by applying it to the CDW database. We performed an evidence-based study to effectively identify process models and to define metrics of frequency and performance for four health care domains: Consults, Radiology, Laboratory, and Outpatient Medication (RxOut) orders. Additionally, we classified the termination classes of the different cases by mapping to the OASIS Human Task Specification standard. We demonstrated, via process mining, that extracted raw data can aid the understanding of the flow of information in different clinical order processes. We showed that using the stepby- step approach described herein to discover processes in raw electronic health record data can be extremely effective in revealing irregular state transitions in the data and understanding clinical order information flows that are not apparent in analyzing the CDW as it is, without feature extraction.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2019

A Road Map for the Advanced Manufacturing of Ferritic-Martensitic Steels

Advanced manufacturing (AM) is a disruptive manufacturing process often referred to as “the next industrial revolution” because of its ability to fabricate components with complex geometries and site-specific materials and properties. While other industries, like automotive, aerospace, and fossil-fired power companies, are adopting and evaluating AM processes, the nuclear industry, including the fusion materials community, has been somewhat slow to capitalize on the seemingly beneficial aspects of AM. To address this gap, Oak Ridge National Laboratory is evaluating candidate AM techniques to fabricate nuclear-relevant materials including ferritic-martensitic (FM) steels. This paper discusses the development of a road map for AM approaches for FM steels. Specifically, the connection among alloy composition, additive processes, processing conditions, and postprocessing and the resulting microstructure using both wire-based and powder-based directed energy deposition techniques is detailed. Lastly, strategies to develop specialized alloys for additive manufacturing are outlined.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS2010

DAMAS Processing for a Phased Array Study in the NASA Langley Jet Noise Laboratory

A jet noise measurement study was conducted using a phased microphone array system for a range of jet nozzle configurations and flow conditions. The test effort included convergent and convergent/divergent single flow nozzles, as well as conventional and chevron dual-flow core and fan configurations. Cold jets were tested with and without wind tunnel co-flow, whereas, hot jets were tested only with co-flow. The intent of the measurement effort was to allow evaluation of new phased array technologies for their ability to separate and quantify distributions of jet noise sources. In the present paper, the array post-processing method focused upon is DAMAS (Deconvolution Approach for the Mapping of Acoustic Sources) for the quantitative determination of spatial distributions of noise sources. Jet noise is highly complex with stationary and convecting noise sources, convecting flows that are the sources themselves, and shock-related and screech noise for supersonic flow. The analysis presented in this paper addresses some processing details with DAMAS, for the array positioned at 90 (normal) to the jet. The paper demonstrates the applicability of DAMAS and how it indicates when strong coherence is present. Also, a new approach to calibrating the array focus and position is introduced and demonstrated.

Brooks, Thomas F.↗

DOE OSTI2016

ALMA Cycle 1 observations of the HH 46/47 molecular outflow: structure, entrainment, and core impact

We present Atacama Large Millimeter/sub-millimeter Array Cycle 1 observations of the HH 46/47 molecular outflow using combined 12 m array and Atacama Compact Array observations. The improved angular resolution and sensitivity of our multi-line maps reveal structures that help us study the entrainment process in much more detail and allow us to obtain more precise estimates of outflow properties than in previous observations. We use {sup 13}CO (1–0) and C{sup 18}O (1–0) emission to correct for the {sup 12}CO (1–0) optical depth to accurately estimate the outflow mass, momentum, and kinetic energy. This correction increases the estimates of the mass, momentum, and kinetic energy by factors of about 9, 5, and 2, respectively, with respect to estimates assuming optically thin emission. The new {sup 13}CO and C{sup 18}O data also allow us to trace denser and slower outflow material than that traced by the {sup 12}CO maps, and they reveal an outflow cavity wall at very low velocities (as low as 0.2 km s{sup −1} with respect to the core’s central velocity). Adding the slower material traced only by {sup 13}CO and C{sup 18}O, there is another factor of three increase in the mass estimate and 50% increase in the momentum estimate. The estimated outflow properties indicate that the outflow is capable of dispersing the parent core within the typical lifetime of the embedded phase of a low-mass protostar and that it is responsible for a core-to-star efficiency of 1/4 to 1/3. We find that the outflow cavity wall is composed of multiple shells associated with a series of jet bow-shock events. Within about 3000 au of the protostar the {sup 13}CO and C{sup 18}O emission trace a circumstellar envelope with both rotation and infall motions, which we compare with a simple analytic model. The CS (2–1) emission reveals tentative evidence of a slowly moving rotating outflow, which we suggest is entrained not only poloidally but also toroidally by a disk wind that is launched from relatively large radii from the source.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Improving Cyber Situational Understanding

Effective cybersecurity operations require the ability to analyze large amounts of information to assess security risks and formulate defensive strategies against adversaries. This has become more complex in recent years as the sprawl and interconnectivity of devices grows through implementation of virtualization, cloud computing, and Internet of Things (IoT). The amount of data and analysis required for effective cybersecurity command and control decisions far exceeds humans’ capacity to perform manually. We characterize the analysis problem as cyber situational understanding. The research presented to improve cyber situational understanding focuses on vulnerability analysis and threat intelligence. Regarding vulnerabilities, entities must analyze and plan work for between thousands and tens of thousands of software vulnerabilities annually. Entities heavily use network firewalls to limit vulnerability exposure. As a result, some of these vulnerabilities permit exposure to adversarial exploitation, whereas others are inaccessible and therefore present negligible risk of exploitation. Distinguishing between high and low risk software vulnerabilities requires a deep understanding of the vulnerability, network firewall protection, and characteristics of the targeted device. This problem is solved by extracting network service features from vulnerability data features using both machine-learning and natural language processing. Then, the network firewall topology is parsed to determine which vulnerabilities are reachable by adversaries. Ultimately, a state-based safety analysis ascertains which vulnerabilities are unsafe. A related vulnerability analysis problem occurs in cybersecurity operations when associating an entity’s hardware and software assets to public vulnerability databases. Assets often reveal hardware and software through installation artifacts and network service identification, and entities store these artifacts in inventory databases. However, software and hardware vendors apply a standard Common Platform Enumeration (CPE) naming convention when publicly reporting vulnerabilities. Associating these two datasets often requires many hours to days of manual inspection. The proposed solution automates the mapping approach of human analysts using fuzzy matching techniques, natural language processing, and, ultimately, machine learning to present a small set of recommendations for mapping the two datasets. The result significantly reduces human analysis time and reduces the occurrence of false positives in vulnerability notifications. Finally, cyber threat intelligence (CTI) requires associating cyber observable artifacts, such as IP addresses, URIs, and file hashes, with cyber threat tactics, techniques, and procedures. Unfortunately, most CTI data is compartmentalized across multiple organizations and cannot be shared due to the legal and reputational risk with cyber threat being associated with the entity. The approach to solving this problem inovlves using a distributed ledger with anonymous token spending and authentication. This allows a consortium of semi-trusted entities to share the workload of curating CTI for a threat sharing community’s cooperative benefit.

Huff, Philip↗

NASA NTRS2010

System and method for image mapping and visual attention

A method is described for mapping dense sensory data to a Sensory Ego Sphere (SES). Methods are also described for finding and ranking areas of interest in the images that form a complete visual scene on an SES. Further, attentional processing of image data is best done by performing attentional processing on individual full-size images from the image sequence, mapping each attentional location to the nearest node, and then summing attentional locations at each node.

Peters, II, Richard A.↗

NASA NTRS2011

System and method for image mapping and visual attention

Peters, II, Richard A.↗

NASA NTRS1990

Quantitative computer representation of propellant processing

With the technology currently available for the manufacture of propellants, it is possible to control the variance of the total specific impulse obtained from the rocket boosters to within approximately five percent. Though at first inspection this may appear to be a reasonable amount of control, when it is considered that any uncertainty in the total kinetic energy delivered to the spacecraft translates into a design with less total usable payload, even this degree of uncertainty becomes unacceptable. There is strong motivation to control the variance in the specific impulse of the shuttle's solid boosters. Any small gains in the predictability and reliability of the booster would lead to a very substantial payoff in earth-to-orbit payload. The purpose of this study is to examine one aspect of the manufacture of solid propellants, namely, the mixing process. The traditional approach of computational fluid mechanics is notoriously complex and time consuming. Certain simplifications are made, yet certain fundamental aspects of the mixing process are investigated as a whole. It is possible to consider a mixing process in a mathematical sense as an operator, F, which maps a domain back upon itself. An operator which demonstrates good mixing should be able to spread any subset of the domain completely and evenly throughout the whole domain by successive applications of the mixing operator, F. Two and three dimensional models are developed and graphical visualization two and three dimensional mixing processes are presented.

Hicks, M. D.↗

NASA NTRS2018

Analysis of Simulated and Experimental Noise Sources of Boeing 777 Main Gear Model via CLEAN in 3D

Previously obtained experimental and simulated phased microphone array data for the NASA 26%-scale model of a six-wheel main landing gear, with and without a toboggan-shaped noise reduction fairing, were analyzed using the CLEAN technique in three dimensions. The model is a high-fidelity representation of the Boeing 777-200 aircraft main landing gear. The reprocessing of the acoustic data was undertaken to address the deficiencies encountered in the source localization (beamform) maps and the integrated farfield spectra at mid to high frequencies in our previous study, where conventional array processing techniques were applied to the same data sets. Application of the CLEAN approach resulted in higher quality beamform maps with many of the previously observed side lobes either eliminated or suppressed significantly. As a result, integration of the experimentally and computationally based maps showed substantial improvement in the quality of the high-frequency spectral content relative to the corresponding spectra generated via conventional array processing, thus extending the good agreement achieved between the measured and predicted farfield spectra from 8 kHz to 14 kHz in model-scale frequencies. In addition, an examination of the simulated surface pressure fluctuations, off-surface flow field, and three-dimensionally constructed noise sources was conducted to determine the cause of the subtle discrepancies between measured and predicted sound pressure levels that occur in the 1,800 Hz to 4,000 Hz model-scale frequency range.

Ravetta, Patricio↗

NASA NTRS2004

Gas Density Discontinuities in Merging Clusters

In a number of galaxy clusters, Chandra has discovered a new phenomenon, the sharp gas density edges. Depending on the sign of the temperature jump across the edge, these features may either be bow shocks or cold fronts. While the merger origin of the bow shocks is unambiguous, what causes cold fronts is not entirely clear, as they are observed both in mergers and in relaxed clusters. The purpose of the study of A3376, an interesting cluster with density edges, is to understand the origin of cold fronts and to look for possible shocks. This cluster also has a radio halo, and comparison of an X-ray temperature map and radio image may shed light on the nature of the cluster radio halos, which is our secondary goal. The XMM data for A3376 have been obtained, processed and cleaned. Most of the preliminary analysis, including deriving a temperature map, is complete. We also have Chandra data for this cluster, and intend to compare and combine the two datasets. We are well underway toward determining the dynamical state of A3376 and the nature of its gas density discontinuities.

Mushotzky, Richard↗