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At least 1,153 records · Page 64

Software agents for the dissemination of remote terrestrial sensing data

Remote terrestrial sensing (RTS) data is constantly being collected from a variety of space-based and earth-based sensors. The collected data, and especially 'value-added' analyses of the data, are finding growing application for commercial, government, and scientific purposes. The scale of this data collection and analysis is truly enormous; e.g., by 1995, the amount of data available in just one sector, NASA space science, will reach 5 petabytes. Moreover, the amount of data, and the value of analyzing the data, are expected to increase dramatically as new satellites and sensors become available (e.g., NASA's Earth Observing System satellites). Lockheed and other companies are beginning to provide data and analysis commercially. A critical issue for the exploitation of collected data is the dissemination of data and value-added analyses to a diverse and widely distributed customer base. Customers must be able to use their computational environment (eventually the National Information Infrastructure) to obtain timely and complete information, without having to know the details of where the relevant data resides and how it is accessed. Customers must be able to routinely use standard, widely available (and, therefore, low cost) analyses, while also being able to readily create on demand highly customized analyses to make crucial decisions. The diversity of user needs creates a difficult software problem: how can users easily state their needs, while the computational environment assumes the responsibility of finding (or creating) relevant information, and then delivering the results in a form that users understand? A software agent is a self-contained, active software module that contains an explicit representation of its operational knowledge. This explicit representation allows agents to examine their own capabilities in order to modify their goals to meet changing needs and to take advantage of dynamic opportunities. In addition, the explicit representation allows agents to advertize their capabilities and results to other agents, thereby allowing the collection of agents to reuse each others work.

Toomey, Christopher N.↗

A Perspective on Quantum Computing Applications in Quantum Chemistry Using 25-100 Logical Qubits

The intersection of quantum computing and quantum chemistry represents a promising frontier for achieving quantum utility in domains of both scientific and societal relevance. Owing to the exponential growth of classical resource requirements for simulating quantum systems, quantum chemistry has long been recognized as a natural candidate for quantum computation. This perspective focuses on identifying scientifically meaningful use cases where early fault-tolerant quantum computers, which are considered to be equipped with approximately 25-100 logical qubits, could deliver tangible impact. While recent advances in classical computing have pushed the boundaries of tractable simulations to unprecedented scales, this logical-qubit regime represents the first window where quantum devices can pursue qualitatively distinct strategies, such as polynomial-scaling phase estimation, direct simulation of quantum dynamics, and active-space embedding, that remain challenging for classical solvers, such as multireference charge-transfer and conical-intersection states central to photochemistry and materials design. We highlight near-term opportunities in algorithm and software design, discuss representative chemical problems suited for quantum acceleration, and propose strategic roadmaps and collaborative pathways for advancing practical quantum utility in quantum chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Jupyter notebooks for analyzing transmission SAXS/WAXS from beamline 7.3.3 during operando membrane fouling experiments v1.0

This software consists of python-based Jupyter Notebooks for processing transmission x-ray scattering images collected at beamline 7.3.3 at the Advanced Light Source. The measurements considered in these analyses are collected during membrane fouling experiments, where contaminants in the water deposit on/attach to the membrane surface. This software is used to elucidate the mechanisms of membrane fouling that occur during these operando membrane fouling experiments, but the analyses provided in these scripts can be extended to other scientific cases.

Landsman, Matthew [Lawrence Berkeley National Labo↗

Basic Energy Sciences Exascale Requirements Review. An Office of Science review sponsored jointly by Advanced Scientific Computing Research and Basic Energy Sciences, November 3-5, 2015, Rockville, Maryland

Computers have revolutionized every aspect of our lives. Yet in science, the most tantalizing applications of computing lie just beyond our reach. The current quest to build an exascale computer with one thousand times the capability of today’s fastest machines (and more than a million times that of a laptop) will take researchers over the next horizon. The field of materials, chemical reactions, and compounds is inherently complex. Imagine millions of new materials with new functionalities waiting to be discovered — while researchers also seek to extend those materials that are known to a dizzying number of new forms. We could translate massive amounts of data from high precision experiments into new understanding through data mining and analysis. We could have at our disposal the ability to predict the properties of these materials, to follow their transformations during reactions on an atom-by-atom basis, and to discover completely new chemical pathways or physical states of matter. Extending these predictions from the nanoscale to the mesoscale, from the ultrafast world of reactions to long-time simulations to predict the lifetime performance of materials, and to the discovery of new materials and processes will have a profound impact on energy technology. In addition, discovery of new materials is vital to move computing beyond Moore’s law. To realize this vision, more than hardware is needed. New algorithms to take advantage of the increase in computing power, new programming paradigms, and new ways of mining massive data sets are needed as well. This report summarizes the opportunities and the requisite computing ecosystem needed to realize the potential before us. In addition to pursuing new and more complete physical models and theoretical frameworks, this review found that the following broadly grouped areas relevant to the U.S. Department of Energy (DOE) Office of Advanced Scientific Computing Research (ASCR) would directly affect the Basic Energy Sciences (BES) mission need. Simulation, visualization, and data analysis are crucial for advances in energy science and technology. Revolutionary mathematical, software, and algorithm developments are required in all areas of BES science to take advantage of exascale computing architectures and to meet data analysis, management, and workflow needs. In partnership with ASCR, BES has an emerging and pressing need to develop new and disruptive capabilities in data science. More capable and larger high-performance computing (HPC) and data ecosystems are required to support priority research in BES. Continued success in BES research requires developing the next-generation workforce through education and training and by providing sustained career opportunities.

97 MATHEMATICS AND COMPUTING↗

A multimission three-axis stabilized spacecraft flight dynamics ground support system

The Multimission Three-Axis Stabilized Spacecraft (MTASS) Flight Dynamics Support System (FDSS) has been developed in an effort to minimize the costs of ground support systems. Unlike single-purpose ground support systems, which attempt to reduce costs by reusing software specifically developed for previous missions, the multimission support system is an intermediate step in the progression to a fully generalized mission support system in which numerous missions may be served by one general system. The benefits of multimission attitude ground support systems extend not only to the software design and coding process, but to the entire system environment, from specification through testing, simulation, operations, and maintenance. This paper reports the application of an MTASS FDSS to multiple scientific satellite missions. The satellites are the Upper Atmosphere Research Satellite (UARS), the Extreme Ultraviolet Explorer (EUVE), and the Solar Anomalous Magnetospheric Particle Explorer (SAMPEX). Both UARS and EUVE use the multimission modular spacecraft (MMS) concept. SAMPEX is part of the Small Explorer (SMEX) series and uses a much simpler set of attitude sensors. This paper centers on algorithm and design concepts for a multimission system and discusses flight experience from UARS.

Langston, J.↗

FY 2025 Multidimensional Data Correlation Platform: Unified Software Architecture for Advanced Materials and Manufacturing Technologies Data Management and Processing

The Advanced Materials and Manufacturing Technologies (AMMT) program continues to advance a data-driven approach to demonstrate the utility of additive manufacturing for fabricating components for nuclear applications. A key scientific goal is to leverage data to better understand manufacturing outcomes and thereby improve the performance, reliability, and lifespan of nuclear components. Ultimately, this effort supports the development of standards for certification and qualification of additively manufactured components, enabling broader industry adoption. In support of this objective, the AMMT program is building and deploying a data management platform to record, index, analyze, and make available the manufacturing data generated across the AMMT program. In FY 2023, the team conceptualized the architecture of the platform and, in FY 2024, deployed the first functional version at the Oak Ridge National Laboratory (ORNL) Manufacturing Demonstration Facility (MDF). In FY 2025, the platform was officially opened to all AMMT members. To enable this expansion, core modifications and enhancements were developed, including improvements to the user interface and workflows for data entry and retrieval. Most notably, robust security and access control mechanisms were implemented to protect data and manage information sharing. This effort featured a logging system, protected views, and controlled access mechanisms. This report documents these enhancements and the transition of the platform into program-wide use.

36 MATERIALS SCIENCE↗

Facile Integration of Robots into Experimental Orchestration at Scientific User Facilities

Integration of robots into scientific user facilities, such as the National Synchrotron Light Source II, improves their efficiency and capacity. Many such facilities use the opensource Bluesky project for experimental control and orchestration. However, there remains an open challenge in deploying robotic solutions at these facilities that are reconfigurable, extensible, and compatible with pre-existing software infrastructure. Herein, we introduce a framework that uses the Robotic Operating System 2 (ROS2) and Bluesky to provide extensible robotic applications, while working under the operational constraints of a large-scale user facility. We demonstrated this framework by integrating a robotic arm to pick and place a sample holder at a beamline, recording a 90% repeatability rate. This provides the groundwork for further new robotics applications at large-scale scientific user facilities that depend on Bluesky.

36 MATERIALS SCIENCE↗

Argonne Leadership Computing Facility 2011 annual report: Shaping future supercomputing

The ALCF's Early Science Program aims to prepare key applications for the architecture and scale of Mira and to solidify libraries and infrastructure that will pave the way for other future production applications. Two billion core-hours have been allocated to 16 Early Science projects on Mira. The projects, in addition to promising delivery of exciting new science, are all based on state-of-the-art, petascale, parallel applications. The project teams, in collaboration with ALCF staff and IBM, have undertaken intensive efforts to adapt their software to take advantage of Mira's Blue Gene/Q architecture, which, in a number of ways, is a precursor to future high-performance-computing architecture. The Argonne Leadership Computing Facility (ALCF) enables transformative science that solves some of the most difficult challenges in biology, chemistry, energy, climate, materials, physics, and other scientific realms. Users partnering with ALCF staff have reached research milestones previously unattainable, due to the ALCF's world-class supercomputing resources and expertise in computation science. In 2011, the ALCF's commitment to providing outstanding science and leadership-class resources was honored with several prestigious awards. Research on multiscale brain blood flow simulations was named a Gordon Bell Prize finalist. Intrepid, the ALCF's BG/P system, ranked No. 1 on the Graph 500 list for the second consecutive year. The next-generation BG/Q prototype again topped the Green500 list. Skilled experts at the ALCF enable researchers to conduct breakthrough science on the Blue Gene system in key ways. The Catalyst Team matches project PIs with experienced computational scientists to maximize and accelerate research in their specific scientific domains. The Performance Engineering Team facilitates the effective use of applications on the Blue Gene system by assessing and improving the algorithms used by applications and the techniques used to implement those algorithms. The Data Analytics and Visualization Team lends expertise in tools and methods for high-performance, post-processing of large datasets, interactive data exploration, batch visualization, and production visualization. The Operations Team ensures that system hardware and software work reliably and optimally; system tools are matched to the unique system architectures and scale of ALCF resources; the entire system software stack works smoothly together; and I/O performance issues, bug fixes, and requests for system software are addressed. The User Services and Outreach Team offers frontline services and support to existing and potential ALCF users. The team also provides marketing and outreach to users, DOE, and the broader community.

99 GENERAL AND MISCELLANEOUS↗

TPSAS-NF1676L-11045-DND

The International TOVS Working Group (ITWG) is convened as a sub-group of the International Radiation Commission (IRC) of the International Association of Meteorology and Atmospheric Physics (IAMAP). The ITWG continues to organize international TOVS study conferences which have met approximately every 18 months since 1983. The most recent conference, the seventeenth International TOVS Study Conference (ITSC-XVII) was held in Monterey, California from 12 to 20 April 2010. This report will cover the current ITWG status, objectives, activities, along with recommendations formulated during the recent ITSC conference to be forwarded to space agencies, operational NWP centers and the scientific community on issues ranging from data processing methods, derived products, and the impacts of radiances and inferred atmospheric temperature and moisture fields on numerical weather prediction, and weather and climate studies. Also to be reported on are activities of the technical sub-groups which meet informally to coordinate ATOVS processing software, radiative transfer models, sounding data for climate studies, use of sounding data in data assimilation/NWP, international issues, and future systems and frequency protection issues relevant to ATOVS. As the result of ITSC-XVII, a paper report and electronic proceedings are being formulated and will soon be published and distributed. The conference Working Group Report will summarize the recommendations and actions of these working sub-groups. Technical Proceedings of the scientific presentations and posters will also published. The ITWG web site (http://cimss.ssec.wisc.edu/itwg/) contains electronic versions of the conference papers, presentations and posters from earlier ITSCs. Together, these documents and web pages reflect the conduct of highly successful international collaborations.

Steve English↗

AIMES Final Technical Report

This is the final technical report for the AIMES project. Many important advances in science and engineering are due to large scale distributed computing. Notwithstanding this reliance, we are still learning how to design and deploy large-scale production Distributed Computing Infrastructures (DCI). This is evidenced by missing design principles for DCI, and an absence of generally acceptable and usable distributed computing abstractions. The AIMES project was conceived against this backdrop, following on the heels of a comprehensive survey of scientific distributed applications. AIMES laid the foundations to address the tripartite challenge of dynamic resource management, integrating information, and portable and interoperable distributed applications. Four abstractions were defined and implemented: skeleton, resource bundle, pilot, and execution strategy. The four abstractions were implemented into software modules and then aggregated into the AIMES middleware. This middleware successfully integrates information across the application layer (skeletons) and resource layer (Bundles), derives a suitable execution strategy for the given skeleton and enacts its execution by means of pilots on one or more resources, depending on the application requirements, and resource availabilities and capabilities.

97 MATHEMATICS AND COMPUTING↗

A Strategy for NACS investment in Machine Learning

The Nuclear and Chemical Sciences (NACS) Division furnishes the expertise in the scientific areas of chemical, nuclear and isotopic sciences that are foundational in the Laboratory’s national security missions. This expertise is maintained and advanced through identification, development and application of state-of-the-art theoretical, computational and experimental methods and tools. Recent developments in artificial intelligence and machine learning (AI/ML) techniques enabled by advances in computing capabilities and widespread availability of powerful software implementations have made use of these techniques ubiquitous across both science and industry. While the scope of AI/ML applications is incredibly large and evolves very rapidly, the topics most relevant to NACS missions fall into the general category of detecting, categorizing or identifying features in large, complex datasets using either supervised or unsupervised learning. This covers both basic scientific data analysis and the development of efficient surrogate models of real-life technological systems, experimental detectors, or theoretical models. To remain at the forefront of its core scientific disciplines, NACS must both cultivate ML expertise as well as continuously explore applying this expertise to new problems or utilizing new methods. This document identifies the key areas where this support is critical and provides a strategy for investing in them.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

AIMES Final Technical Report

This is the final technical report for the AIMES project. Many important advances in science and engineering are due to large-scale distributed computing. Notwithstanding this reliance, we are still learning how to design and deploy large-scale production Distributed Computing Infrastructures (DCI). This is evidenced by missing design principles for DCI, and an absence of generally acceptable and usable distributed computing abstractions. The AIMES project was conceived against this backdrop, following on the heels of a comprehensive survey of scientific distributed applications. AIMES laid the foundations to address the tripartite challenge of dynamic resource management, integrating information, and portable and interoperable distributed applications. Four abstractions were defined and implemented: skeleton, resource bundle, pilot, and execution strategy. The four abstractions were implemented into software modules and then aggregated into the AIMES middleware. This middleware successfully integrates information across the application layer (skeletons) and resource layer (Bundles), derives a suitable execution strategy for the given skeleton and enacts its execution by means of pilots on one or more resources, depending on the application requirements, and resource availabilities and capabilities.

97 MATHEMATICS AND COMPUTING↗

Scalability under a Power Bound using the GREMLINs Framework

With the move towards exascale, system and software developers will have to deal with issues of extreme parallelism. The system properties affected most by the increase in node and core count are the shared resources on node and across the system. The increase in parallelism leads to reduced memory and bandwidth when regarding individual cores. Since power is a limiting factor for supercomputers, and power is not fully utilized in current systems, overprovisioning compute resources is a viable approach to maximized power utilization. To maximize system performance in regard to these changing conditions, it is necessary to understand how resource restrictions impact performance and system behavior. For the purpose of understanding anticipated system properties the GREMLINs Framework was developed. The framework gives the opportunity to add power restrictions, hinder memory properties and introduce faults to study resilience, among others. These features give the opportunity to use current petascale technology to study problems system designers and software developers will have to face when moving towards exascale and beyond. This work describes the initial release of the GREMLINs Framework, developed for this work, and shows how it can be used to study the scaling behavior of proxy applications. These proxy applications represent a selection of HPC workloads important to the scientific community. The proxy applications studied are AMG2013, an algebraic multi-grid linear system solver, CoMD, a classical molecular dynamics proxy application and NEKBONE, an application that uses a high order spectral element method to solve the Navier-Stokes equations. The main interest of these studies lies in analysis regarding their power behavior at scale under a power bound. These findings show how the GREMLINs Framework can help systems and software designers to attain better application performance and can also be used as basis for CPU power balancing tools to use power more efficiently.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Report from: US Muon Workshop 2021: A Road Map for a Future Muon Facility February 1-2, 2021

The workshop titled “US Muon Workshop 2021: A road map for a future Muon Facility” was held virtually on February 1-2, 2021. The workshop aimed to bring together world experts in muon spectroscopy (µSR) and other techniques along with interested stakeholders to evaluate the scientific need to construct a new µSR facility in the United States (US). The more than 200 participants highlighted several key scientific areas for µSR research, including quantum materials, hydrogen chemistry, and battery materials, and how each area could benefit from a new, high flux pulsed muon source. Experts also discussed aspects of the µSR technique, such as low-energy µSR, novel software developments, and beam and detector technologies that could enable revolutionary advances in µSR at a next-generation facility. The workshop concluded with discussion of a concept being developed for a new µSR facility at the Spallation Neutron Source (SNS) of Oak Ridge National Laboratory (ORNL). That novel design concept was first envisioned by many of the same µSR experts at a workshop held previously at ORNL in 2016. The participants expressed that the current design had the potential to be a world-leading µSR facility, and strongly encouraged the principal investigators to continue their work in order to refine the concept and determine instrument parameters that would enable new scientific opportunities

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

US Muon Workshop 2021: A road map for a future Muon Facility

The workshop title “US Muon Workshop 2021: A road map for a future Muon Facility” was held virtually on February 1-2, 2021. The workshop aimed to bring together world experts in muon spectroscopy (µSR) and other techniques along with interested stakeholders to evaluate the scientific need to construct a new µSR facility in the United States (US). The more than 200 participants highlighted several key scientific areas for µSR research, including quantum materials, hydrogen chemistry, and battery materials, and how each area could benefit from a new, high flux pulsed muon source. Experts also discussed aspects of the µSR technique, such as low-energy µSR, novel software developments, alongside beam and detector technologies, that could enable revolutionary advances in µSR at a next-generation facility. The workshop concluded with discussion of a concept being developed for a new µSR facility at the Spallation Neutron Source (SNS) of Oak Ridge National Laboratory (ORNL). That novel design concept was first envisioned by many of the same µSR experts at a workshop held previously at ORNL in 2016. The participants expressed that the current design had the potential to be a world-leading µSR facility, and strongly encouraged the principal investigators to continue their work in order to refine the concept and determine instrument parameters that would enable new scientific opportunities.

36 MATERIALS SCIENCE↗

Data preservation at the Fermilab Tevatron

The Fermilab Tevatron collider's data-taking run ended in September 2011, yielding a dataset with rich scientific potential. The CDF and DO experiments each have nearly 9 PB of collider and simulated data stored on tape. A large computing infrastructure consisting of tape storage, disk cache, and distributed grid computing for physics analysis with the Tevatron data is present at Fermilab. The Fermilab Run II data preservation project intends to keep this analysis capability sustained through the year 2020 or beyond. To achieve this, we are implementing a system that utilizes virtualization, automated validation, and migration to new standards in both software and data storage technology as well as leveraging resources available from currently-running experiments at Fermilab. Furthermore, these efforts will provide useful lessons in ensuring long-term data access for numerous experiments throughout high-energy physics, and provide a roadmap for high-quality scientific output for years to come.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

PDFDataExtractor: A Tool for Reading Scientific Text and Interpreting Metadata from the Typeset Literature in the Portable Document Format

The layout of portable document format (PDF) files is constant to any screen, and the metadata therein are latent, compared to mark-up languages such as HTML and XML. No semantic tags are usually provided, and a PDF file is not designed to be edited or its data interpreted by software. However, data held in PDF files need to be extracted in order to comply with opensource data requirements that are now government-regulated. In the chemical domain, related chemical and property data also need to be found, and their correlations need to be exploited to enable data science in areas such as data-driven materials discovery. Such relationships may be realized using text-mining software such as the “chemistry-aware” natural-language-processing tool, ChemDataExtractor; however, this tool has limited data-extraction capabilities from PDF files. This study presents the PDFDataExtractor tool, which can act as a plug-in to ChemDataExtractor. It outperforms other PDF-extraction tools for the chemical literature by coupling its functionalities to the chemical-named entityrecognition capabilities of ChemDataExtractor. The intrinsic PDF-reading abilities of ChemDataExtractor are much improved. The system features a template-based architecture. This enables semantic information to be extracted from the PDF files of scientific articles in order to reconstruct the logical structure of articles. While other existing PDF-extracting tools focus on quantity mining, this template-based system is more focused on quality mining on different layouts. PDFDataExtractor outputs information in JSON and plain text, including the metadata of a PDF file, such as paper title, authors, affiliation, email, abstract, keywords, journal, year, document object identifier (DOI), reference, and issue number. With a self-created evaluation article set, PDFDataExtractor achieved promising precision for all key assessed metadata areas of the document text.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

2015 Annual Report

For more than 20 years, the Atmospheric Radiation Measurement (ARM) Climate Research Facility has blazed the trail in providing the world’s atmospheric scientists with continuous observations of cloud and aerosol properties and their impacts on Earth’s energy balance. The result is an unprecedented data set that has proved invaluable for understanding the atmosphere and improving the predictive capabilities of earth system models. Over the past year, plans have been put in place to create a powerful new capability for furthering ARM’s mission and achieving the vision outlined in the Decadal Vision, the strategy for the ARM Facility for the next 5 to 10 years. The result is a significant reconfiguration for the ARM Facility that will provide more complete data sets to support process studies and model development. The combined observational and modeling elements will enable a new level of scientific inquiry. To achieve the next-generation ARM Facility, plans underway include the following: Establishing observation “megasites” at the Southern Great Plains and North Slope of Alaska sites Enhancing ARM measurement excellence to support U.S. Department of Energy climate science research Producing routine high-resolution model simulations over domains coincident with ARM sites Developing data products and software tools that facilitate analysis and enable the evaluation of models using ARM data Strengthening interactions with the broader atmospheric science and modeling communities. Changes being implemented at the megasites will provide additional spatial sampling of atmospheric and surface information to support a new ARM capability—the routine operation of high-resolution process models at ARM sites. The result will be even more comprehensive scientific data and the processes and tools for scientists to more easily use ARM data for climate model development.

Southern Great Plains, North Slope of Alaska, larg↗