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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A Two-Stage Quantum Reinforcement Learning Method for Multi-Objective Transmission Switching

Multi-objective transmission switching (MO-TS) problems involve the strategic reconfiguration of network topology to simultaneously optimize multiple objectives. As the system scale increases, finding feasible solutions becomes increasingly challenging due to the problem's nonlinearity and high computational complexity. To address these challenges, this paper proposes a two-stage quantum reinforcement learning method that leverages potential quantum advantages for MO-TS. In the first stage, candidate switching lines are identified using a graph-theoretical approach to reduce the problem's dimensionality. The second stage introduces a quantum-classical reinforcement learning framework, where a learnable measurement-based CNN-ResVQC architecture is developed to effectively reduce the input dimension for quantum processing, mitigate vanishing gradients, and enhance trainability while improving the quantum circuit's flexibility in modeling complex decision policies for MO-TS. Numerical studies on IEEE 14-bus, 57-bus, and 118-bus systems demonstrate that the proposed algorithm achieves superior training stability and faster convergence with approximately 1% of the network parameters required by classical algorithms, highlighting its effectiveness, efficiency, and scalability. Furthermore, the practicality is validated through its stable convergence under three common quantum noise channels.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

RANGERS: Methodology Report on Design and Performance Assessment of Engineered Barrier Systems in a Salt Repository for HLW/SNF

Salt formations are one of the potential host rocks for the final disposal of high-level radioactive waste (HLW) in deep geological repositories, both in Germany and the United States. The safe isolation of radioactive waste in these repositories relies on a multi-barrier system, combining engineered and natural barriers. The natural barrier is provided by the salt rock itself, known for its self-sealing properties and long-term stability. The engineered barrier, on the other hand, comprises sealing components strategically placed within the repository to enhance its containment capabilities. In both Germany and the United States, long-term safety assessments require demonstrating the integrity of the natural barrier for a period of up to 1 million years. Concurrently, the engineered barrier system (EBS) must maintain its structural and functional integrity until the long-term sealing, such as the granular salt backfill material, has re-consolidated to its final low porosity and permeability. Based on extensive expertise and experience with engineered barriers in salt formations, BGE TECHNOLOGY GmbH and Sandia National Laboratories have partnered to develop a robust methodology for the integrity and performance assessment of EBS in HLW repositories through the RANGERS project. This collaborative effort aims to establish a unified approach to geotechnical engineering, repository design, integrity and performance evaluation of EBS in salt repositories.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

ARM Aerosol Measurement Science Group 2019 Strategic Planning Workshop Report

This report summarizes the results of a U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility workshop held in November 2019 to advance a science-based strategy for ARM’s aerosol measurement program. This was the second such workshop since the Aerosol Measurement Science Group (AMSG) was chartered in 2015 to enhance coordination of ARM observations of aerosols and atmospheric trace gases with the needs of ARM users. The results presented here reflect the AMSG’s focus in recent years on science-based strategies that will contribute to the increased use of ARM data to fulfill its mission of improving process representations and predictability in climate models. Sessions held during the workshop range from interfacing with models through aerosol sampling strategies to calibration protocols and data products. The strategies set forth here were also developed to be directly relevant to ARM’s updated Decadal Vision. The AMSG workshops have been designed to recommend actions that will enable ARM to evolve and continue to meet its mission. To that end, the AMSG will develop an actionable plan from the recommendations outlined here. Some are well defined and can reasonably be accomplished in the short term. Others are less definite or of a larger scope that calls for a longer-term implementation. Further discussion will be required to develop and prioritize actionable items related to such areas. Task teams comprising the appropriate expertise and perspective from the AMSG and other members of the community will be formed to achieve this outcome. Some particular topics are recognized as high priority, so plans are underway to develop task teams and to hold follow-on discussions to address them. Four areas currently being considered for short, focused discussion are 1) aerosol measurements on the North Slope of Alaska, 2) improving data usability for modeling, 3) strategies for advancing remote sensing, vertical profiling, and distributed measurements of aerosols, and 4) aerosol sampling strategies at existing ARM sites to provide intensive modes of operation to promote data usage for process and modeling studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Radioisotope Science and Technology Division FY 2025 Core R&D Summary Report: Competitive Projects, Postdoctoral Researchers, and Student Interns

R&D efforts in support of the Oak Ridge National Laboratory (ORNL) Isotope Program Radioisotope Portfolio are led by the Radioisotope Science and Technology Division (RSTD). In addition to supporting the ORNL Isotope Program Radioisotope Portfolio, RSTD supports a portfolio of research related to fundamental properties of radioisotopes and radioisotope applications, including diagnostic and therapeutic uses of medical radioisotopes, radioisotopes for national security, and the production of 238 Pu for the National Aeronautics and Space Administration (NASA) and US Department of Energy (DOE) Office of Nuclear Energy. RSTD is organized into functional science and engineering groups, with most staff members supporting multiple programs. The goal of this organization is to enable synergy between programs such that R&D advances coming from other programs may provide benefit to the ORNL Isotope Program. R&D within RSTD is focused around addressing five grand challenges, as documented in the strategic plan for the DOE Office of Isotope R&D and Production, or DOE Isotope Program (IP), Radioisotope Production R&D activities at ORNL: 1. Maximizing the scientific output of radioisotope transmutation resources, 2. Maximizing the scientific output of radioisotope processing resources, 3. Minimizing waste and having optimal waste disposition, 4. Focusing on product quality and reliability, and 5. Expanding the use of beneficial isotopes. The ORNL Core R&D program, one of the primary R&D components within the ORNL Isotope Program Radioisotope Portfolio, ranges from benchtop to demonstration activities, with a focus on researching enhanced production techniques, developing emerging isotopes, and developing the talent pipeline for radioisotope science and technology. Projects within the Core R&D Program are led primarily by RSTD staff members. In supporting enhanced production techniques, the Core R&D program presents an opportunity to fund novel R&D that might not be tied to a specific radioisotope product but still presents a high potential for broad applicability in the longer term. In supporting the development of emerging isotopes, the Core R&D program develops high-priority isotopes that are not able to be fully supported through production funds.

07 ISOTOPE AND RADIATION SOURCES↗
NASA NTRS2005

Remotely Operated Aircraft (ROA) Impact on the National Airspace System (NAS) Work Package, 2005: Composite Report on FAA Flight Plan and Operational Evaluation Plan. Version 7.0

The purpose of this document is to present the findings that resulted from a high-level analysis and evaluation of the following documents: (1) The OEP (Operational Evolution Plan) Version 7 -- a 10-year plan for operational improvements to increase capacity and efficiency in U.S. air travel and transport and other use of domestic airspace. The OEP is the FAA commitment to operational improvements. It is outcome driven, with clear lines of accountability within FAA organizations. The OEP concentrates on operational solutions and integrates safety, certification, procedures, staffing, equipment, avionics and research; (2) The Draft Flight Plan 2006 through 2010 -- a multi-year strategic effort, setting a course for the FAA through 2001, to provide the safest and most efficient air transportation system in the world; (3) The NAS System Architecture Version 5 -- a blueprint for modernizing the NAS and improving NAS services and capabilities through the year 2015; and (4) The NAS-SR-1000 System Requirements Specification (NASSRS) -- a compilation of requirements which describe the operational capabilities for the NAS. The analysis is particularly focused on examining the documents for relevance to existing and/or planned future UAV operations. The evaluation specifically focuses on potential factors that could materially affect the development of a commercial ROA industry, such as: (1) Design limitations of the CNS/ATM system, (2) Human limitations, The information presented was taken from program specifications or program office lead personnel.

Source record↗
DOE OSTI2024

Integrated design of aluminum-enriched high-entropy refractory B2 alloys with synergy of high strength and ductility

Refractory high-entropy alloys (RHEAs) are promising high-temperature structural materials. Their large compositional space poses great design challenges for phase control and high strength-ductility synergy. The present research pioneers using integrated high-throughput machine learning with Monte Carlo simulations supplemented by ab initio calculations to effectively navigate phase selection and mechanical property predictions, developing single-phase ordered B2 aluminum-enriched RHEAs (Al-RHEAs) demonstrating high strength and ductility. These Al-RHEAs achieve remarkable mechanical properties, including compressive yield strengths up to 1.7 gigapascals, fracture strains exceeding 50%, and notable high-temperature strength retention. They also demonstrate a tensile yield strength of 1.0 gigapascals with a ductility of 9%, albeit with B2 ordering. Furthermore, we identify valence electron count domains for alloy ductility and brittleness with the explanation from density functional theory and provide crucial insights into elemental influence on atomic ordering and mechanical performance. The work sets forth a strategic blueprint for high-throughput alloy design and reveals fundamental principles governing the mechanical properties of advanced structural alloys.

Science & Technology - Other Topics↗
NASA NTRS1992

Projected NASA power requirements for space science and exploration missions

NASA's Office of Space Science and Applications has recently completed its long-range strategic plan which describes a number of exciting space science missions into the early 21st century. In parallel, NASA's new Office of Exploration has begun defining in more detail the architectures of the Space Exploration Initiative (SEI) for returning to the Moon and going to Mars. Both the space science missions and the SEI missions are dependent upon power sources and energy storage with strong requirements for reliability, long life, ease of assembly, autonomy, and light weight. This paper reviews the currently planned space science and SEI missions and focuses upon the power requirements with a view toward guiding technology developers and power designers.

Gary L Bennett↗
NASA NTRS2016

AFSPC Innovation and Science and Technology Outreach to Industry and Academia

The U.S. Air Force is taking a strategic approach to ensuring that we are at the cutting edge of science and technology. This includes fostering game-changing approaches and technologies that are balanced with operational needs. The security of the Nation requires a constant pursuit of science, technical agility, and a rapid adoption of innovation. This includes pursuits of game-changing technologies and domains that perhaps we cannot even imagine today. This paper highlights the Air Force Space Command (AFSPC) collaboration and outreach to other government agencies, military and national laboratories, industry, and academia on long term science and technology challenges. In particular we discuss the development of the AFSPC Long Term Science and Technology Challenges that include both space and cyberspace operations within a multi-domain environment and the subsequent Innovation Summits.

Science Technology S&T Forum↗
NASA NTRS2017

NASA Near Earth Network (NEN) Support for Lunar and L1/L2 CubeSats

The NASA Near Earth Network (NEN) consists of globally distributed tracking stations, including NASA, commercial, and partner ground stations, that are strategically located to maximize the coverage provided to a variety of orbital and suborbital missions, including those in LEO, GEO, HEO, lunar and L1/L2 orbits. The NENs future mission set includes and will continue to include CubeSat missions. The first NEN supported CubeSat mission will be the Cubesat Proximity Operations Demonstration (CPOD) launching into low earth orbit (LEO) in early 2017. The majority of the CubeSat missions destined to fly on EM-1, launching in late 2018, many in a lunar orbit, will communicate with ground based stations via X-band and will utilize the NASA Jet Propulsion Laboratory (JPL) developed IRIS radio. The NEN recognizes the important role CubeSats are beginning to play in carrying out NASAs mission and is therefore investigating the modifications needed to provide IRIS radio compatibility. With modification, the NEN could potentially expand support to the EM-1 lunar CubeSats. The NEN could begin providing significant coverage to lunar CubeSat missions utilizing three to four of the NENs mid-latitude sites. This coverage would supplement coverage provided by the JPL Deep Space Network (DSN). The NEN, with smaller apertures than DSN, provides the benefit of a larger beamwidth that could be beneficial in the event of uncertain ephemeris data. In order to realize these benefits the NEN would need to upgrade stations targeted based on coverage ability and current configurationease of upgrade, to ensure compatibility with the IRIS radio.In addition, the NEN is working with CubeSat radio developers to ensure NEN compatibility with alternative CubeSat radios for Lunar and L1/L2 CubeSats. The NEN has provided NEN compatibility requirements to several radio developers who are developing radios that offer lower cost and, in some cases, more capabilities with fewer constraints. The NEN is ready to begin supporting CubeSat missions. The NEN is considering network upgrades to broaden the types of CubeSat missions that can be supported and is supporting both the CubeSat community and radio developers to ensure future CubeSat missions have multiple options when choosing a network for their communications support.

Global Tracking Network Ground Station↗
DOE OSTI2021

Igiugig Site Visit Report

The National Renewable Energy Laboratory (NREL) team conducted a site visit during January 23-25, 2019 with the Igiugig Village Council (IVC) and other stakeholders to assist the community of Igiugig in refining their long-term energy strategy. The agenda included a tour of the village, data collection, presentations, long-term visioning exercises, identification of energy scenarios, and a school presentation. Participants in the site visit activities spanned a range of local, regional, government, and industry participation. There were 24 attendees at the all-day community workshop on Thursday, January 24th, with participants from the IVC, NREL, Bristol Bay Native Association (BBNA), Bristol Bay Native Corporation (BBNC), Lake and Peninsula Borough, Alaska Energy Authority, Intergrid, ORPC, Deer Stone Consulting, the Southwest Alaska Municipal Conference, and University of Alaska Fairbanks - Alaska Center for Energy and Power. Igiugig is a well-organized rural Alaskan community, with a leadership team that appears to have broad community support. The use of consensus-based decision making is one tangible example of how the leadership team actively invokes and promotes community-focused thinking. The NREL team observed anecdotal evidence of how this approach seems to be strengthening the community: active participation in the visioning exercise, a student hosted fund-raiser dinner at the school, a clean and organized landfill, and well-maintained roads and buildings. Igiugig has wind, solar, and river hydrokinetic resources readily available within the community. Wind has shown to be a promising resource in the region, and has been integrated into microgrids around the state, but the community has had mixed success with wind technologies: some devices failed quickly and others continue to operate. The economics of solar energy are improving in Alaska, and economical solar projects are being installed around the state. Considering that economic activity in Igiugig peaks during the summer sport fishing season, solar could prove to be a valuable supplement to the electrical system. Igiugig has been a test site for two different river hydrokinetic devices, and they have began a third project to operate ORPC's RivGen device, which is delivering valuable device performance data, operations and maintenance experience, and design refinement information. Already, this device has made over 7-million revolutions, and delivered over 8 MWh of power to the community. Igiugig's river resource is fairly unique because it is available year-round and has the potential to provide reliable base-load power for months at a time. A preliminary investigation of this diverse resource mix suggests that Igiugig could achieve very high levels (70% or more) of annual renewable generation contributions. A critical step in pursuing this path is identifying the mix of energy assets (generation and storage) that best meets the community's budget, needs, and goals. The assets that a community installs early in their grid-modernization initiative can constrain the options that are economical at later stages, which may lead to sub-optimal solutions. This is where technical and economic analysis of potential scenarios (i.e., distinct mixes of energy assets) can be useful in identifying the most promising pathways so that a community can make informed and strategic decisions about the assets they install. These analyses are most accurate and informative when they are based on actual technology performance and cost data. As the RivGen project continues to operate and generate this data, we will be better prepared to evaluate the technology's long-term viability and to identify research areas that would improve it. Igiugig's energy projects are at the cutting edge of two intersecting technology areas: 1) deploying an operational river hydrokinetic turbine, and 2) integrating renewable energy sources to achieve very high percent renewables. If these projects are successful, the lessons learned and technologies developed could be valuable for other microgrids around the world. Igiugig's unique resource mix make it an ideal location for this work, and the community's organizational strength make it an ideal partner in this ground-breaking work. Ongoing support for technical assistance to manage and address technical challenges along the way will maximize the probability of project success.

13 HYDRO ENERGY↗
DOE OSTI2024

Advanced HVAC Humidity Control for Hot-Humid Climates

During this project we develop and validate a cost-effective, integrated control solution to improve humidity control and comfort for energy-efficient homes in hot-humid climates. This study focuses on developing a strategy that is effective, field tested, and practical for builders to install with minimal disruption to standard practices. A successful solution would simplify the transition to high-performance humidity control and be the basis for design and installation guidance. By relying on the central system as a starting point, the strategy employed minimizes system complexity and cost for builders, while improving comfort and operating cost for homeowners. The solution strategy was to coordinate the cooling, dehumidification, and ventilation functions of central, ducted HVAC systems to better control indoor humidity, improve occupant thermal comfort, and capture energy savings. The primary strategic goals were to: (1) optimize dehumidification by the central air-conditioning system, particularly during part-load conditions, using conventional equipment with modified control settings and lower system airflows; (2) maximize ventilation during heating/cooling on-cycles, to “bank” and condition outdoor ventilation air, and minimize ventilation during off-cycles; (3) quantify the effectiveness and energy impact of the dehumidification and ventilation strategies, while identifying a metric that would be useful to evaluate latent effectiveness. For the test houses in our study, located in Richmond Hill, Georgia; Houston, Texas; and Monroe, Louisiana we observed: (1) the indoor humidity did not exceed 60% RH during the monitored cooling season for 99% of the time in Richmond Hill, 96% of the time in Houston, and 90% of the time in Monroe; (2) the dehumidification strategy improved the steady-state latent capacity of the HVAC system at design conditions by 16% to 49% at the Houston test house and by 28% to 71% at the Monroe test house, depending on which mode the system was operating in; and (3) the good results at the test houses were primarily due to the amount of time the air-conditioning system operated in ramping or dehumidification modes, or both, particularly during the early cooling season. This study demonstrates that air conditioners or heat pumps with a single-stage compressor can provide good humidity control without the need for a two-stage or variable-stage compressor system. The airflow and control settings for ramping and dehumidification modes are critical to control indoor humidity in hot-humid climates, particularly during part-load and shoulder season conditions. The dehumidification strategy used in this study did not jeopardize the mechanical reliability of the cooling equipment. The strategies used in this study are applicable across various equipment brands, models, and efficiency levels, and also applicable to a broad range of homes in hot-humid climates. Results will vary by specific equipment, location, and house configuration and construction.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Commercial integration of advanced nuclear energy with Artificial Intelligence (AI): Possible implications

The integration of advanced nuclear technologies (both fission and fusion) with artificial intelligence (AI) presents unprecedented national security challenges and opportunities. As fusion energy approaches commercial viability alongside advanced Small Modular Reactors (SMRs), their integration with AI and Artificial General Intelligence (AGI) systems could fundamentally transform the global energy and AI landscapes — two pillars of national security. This document briefly examines how AI could accelerate nuclear energy development and deployment while altering existing power structures, a lot could be done to deepen the discussions. Simultaneously, it observes how nuclear-powered AI may expedite advances toward AGI and beyond. These issues are deeply interconnected and thus need to be examined as a whole and more comprehensively than what’s being summarized here. For instance, AI-powered autonomous operation of nuclear facilities could reduce human error but introduce new cybersecurity vulnerabilities and uncertainties. Further investigation would also address how AI-enhanced nuclear technologies might complicate proliferation concerns through advanced fuel cycle management, nuclear materials production and safeguard. The strategic advantage gained by first entities achieving successful AI-nuclear integration could reshape global and national security framework. Timely analysis of these implications may be crucial for policymakers seeking to harness these technologies' benefits while effectively mitigating their potential risks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2000

Goals Analysis Procedure Guidelines for Applying the Goals Analysis Process

One of the key elements to successful project management is the establishment of the "right set of requirements", requirements that reflect the true customer needs and are consistent with the strategic goals and objectives of the participating organizations. A viable set of requirements implies that each individual requirement is a necessary element in satisfying the stated goals and that the entire set of requirements, taken as a whole, is sufficient to satisfy the stated goals. Unfortunately, it is the author's experience that during project formulation phases' many of the Systems Engineering customers do not conduct a rigorous analysis of the goals and objectives that drive the system requirements. As a result, the Systems Engineer is often provided with requirements that are vague, incomplete, and internally inconsistent. To complicate matters, most systems development methodologies assume that the customer provides unambiguous, comprehensive and concise requirements. This paper describes the specific steps of a Goals Analysis process applied by Systems Engineers at the NASA Langley Research Center during the formulation of requirements for research projects. The objective of Goals Analysis is to identify and explore all of the influencing factors that ultimately drive the system's requirements.

Motley, Albert E., III↗
NASA NTRS2007

Automated Target Planning for FUSE Using the SOVA Algorithm

The SOVA algorithm was originally developed under the Resilient Systems and Operations Project of the Engineering for Complex Systems Program from NASA s Aerospace Technology Enterprise as a conceptual framework to support real-time autonomous system mission and contingency management. The algorithm and its software implementation were formulated for generic application to autonomous flight vehicle systems, and its efficacy was demonstrated by simulation within the problem domain of Unmanned Aerial Vehicle autonomous flight management. The approach itself is based upon the precept that autonomous decision making for a very complex system can be made tractable by distillation of the system state to a manageable set of strategic objectives (e.g. maintain power margin, maintain mission timeline, and et cetera), which if attended to, will result in a favorable outcome. From any given starting point, the attainability of the end-states resulting from a set of candidate decisions is assessed by propagating a system model forward in time while qualitatively mapping simulated states into margins on strategic objectives using fuzzy inference systems. The expected return value of each candidate decision is evaluated as the product of the assigned value of the end-state with the assessed attainability of the end-state. The candidate decision yielding the highest expected return value is selected for implementation; thus, the approach provides a software framework for intelligent autonomous risk management. The name adopted for the technique incorporates its essential elements: Strategic Objective Valuation and Attainability (SOVA). Maximum value of the approach is realized for systems where human intervention is unavailable in the timeframe within which critical control decisions must be made. The Far Ultraviolet Spectroscopic Explorer (FUSE) satellite, launched in 1999, has been collecting science data for eight years.[1] At its beginning of life, FUSE had six gyros in two IRUs and four reaction wheels. Over time through various failures, the satellite has been left with one reaction wheel on the vehicle skew axis and two gyros. To remain operational, a control scheme has been implemented using the magnetic torque rods and the remaining momentum wheel.[2] As a consequence, there are attitude regions where there is insufficient torque authority to overcome environmental disturbances (e.g. gravity gradient torques). The situation is further complicated by the fact that these attitude regions shift inertially with time as the spacecraft moves through earth s magnetic field during the course of its orbit. Under these conditions, the burden of planning targets and target-to-target slew maneuvers has increased significantly since the beginning of the mission.[3] Individual targets must be selected so that the magnetic field remains roughly aligned with the skew wheel axis to provide enough control authority to the other two orthogonal axes. If the field moves too far away from the skew axis, the lack of control authority allows environmental torques to pull the satellite away from the target and can potentially cause it to tumble. Slew maneuver planning must factor the stability of targets at the beginning and end, and the torque authority at all points along the slew. Due to the time varying magnetic field geometry relative to any two inertial targets, small modifications in slew maneuver timing can make large differences in the achievability of a maneuver.

Heatwole, Scott↗
NASA NTRSDate not supplied

Physics Informed Neural Nets for Systems Health Management

To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Development in data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. The research work presents application of physics-informed neural nets application to a representative electric powertrain for unmanned aerial vehicles. The model is composed of physics-derived and empirical equations, integrated with connected networks that are strategically placed within the model to substitute equations that are subject to large uncertainty. Polynomial fit driven by heuristics or empirical observations can be substituted by more flexible networks that can minimize the error between model predictions and observations without being restricted to a predefined functional form. This modeling strategy allows training of networks deep inside the model and unknown parameters in a single learning stage.

Physics Informed↗
DOE OSTI2021

Severity factor kinetic model as a strategic parameter of hydrothermal processing (steam explosion and liquid hot water) for biomass fractionation under biorefinery concept

Hydrothermal processes are an attractive clean technology and cost-effective engineering platform for bio-refineries based in the conversion of biomass to biofuels and high-value bioproducts under the basis of sustainability and circular bioeconomy. The deep and detailed knowledge of the structural changes by the severity of biomasses hydrothermal fractionation is scientifically and technological needed in order to improve processes effectiveness, reactors designs, and industrial application of the multi-scale target compounds obtained by stream explosion and liquid hot water systems. The concept of the severity factor [log 10 (R 0 )] established > 30 years ago, continue to be a useful index that can provide a simple description of the relationship between the operational conditions for biomass fractionation in second generation of biorefineries. Furthermore, this review develops a deep explanation of the hydrothermal severity factor based in lignocellulosic biomass fractionation with emphasis in research advances, pretreatment operations and the applications of severity factor kinetic model.

09 BIOMASS FUELS↗
DOE OSTI2021

Argonne Leadership Computing Facility: 2021 Operational Assessment Report

This Operational Assessment Report describes how the Argonne Leadership Computing Facility (ALCF) met or exceeded every one of its goals for calendar year (CY) 2021 as an advanced scientific computing center. In CY 2021, the ALCF operated its production resource, Theta, an Intel-based Cray XC40 system (11.7-petaflops) augmented with 24 NVIDIA DGX A100-based nodes (3.9-petaflops) that supports diverse workloads, integrating data analytics with artificial intelligence (AI) training and learning in a single platform. In 2021, we began deploying Polaris, our newest 40- petaflops system, and augmented this powerful testbed system with an additional 28 nodes to support the integration of real-time experiments and HPC resources. We also deployed our two largest storage systems yet, named Grand and Eagle, that will bring new services to our users and will power data-driven research for years to come. Last year, Theta delivered a total of 20.8 million node-hours to 16 Innovative and Novel Computational Impact on Theory and Experiment (INCITE) projects and 7.2 million node-hours to ASCR Leadership Computing Challenge (ALCC) projects (32 awarded during the 2020–2021 ALCC year and 17 awarded during the 2021–2022 ALCC year), as well as substantial support to Director’s Discretionary (DD) projects (5.5 million node-hours). As Table ES.1 shows, Theta performed exceptionally well in terms of overall availability (95.1 percent), scheduled availability (99.4 percent), and utilization (98.1 percent; Table 2.1). As of the submission date of this document, ALCF’s user community has published 249 papers in high-quality, peer-reviewed journals and technical proceedings. At the 2021 International Conference for High Performance Computing, Networking, Storage and Analysis (SC’21), Argonne researchers won two HPCwire Readers’ Choice Awards and were part of a Gordon Bell Prize finalist team recognized for developing an AI-enabled, multi-resolution simulation framework for studying complex biomolecular machines. Their framework was used to observe the SARS-CoV-2 replication-transcription machinery in action, by directly integrating experimental data. ALCF also provided a comprehensive program of high-performance computing (HPC) support services to help our community make productive use of the facility’s diverse and growing collection of resources. We are now entering the exascale era, with exascale machines being planned for national laboratories across the country, including Aurora at Argonne National Laboratory (Argonne) in 2023. ALCF researchers have been leading and guiding numerous strategic activities that will push the boundaries of what’s possible in computational science and engineering and allow us to deliver science on day one.

97 MATHEMATICS AND COMPUTING↗