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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

AECOM Early Career Professional Technology Exchange - 19045

Starting in 2015, technical exchanges with early career professionals across different AECOM sites in the U.S. Department of Energy (DOE) complex have been held semi-annually. The host and location of each exchange alternate between the participating sites and involve rotating groups of early career professionals representing those sites. In the past, the participating sites have included AECOM Technical Services, Los Alamos National Laboratory in Los Alamos, NM; Savannah River Remediation in Aiken, SC; URS/CH2M Oak Ridge LLC in Oak Ridge, TN; Waste Isolation Pilot Plant in Carlsbad, NM; and Washington River Protection Solutions and the Waste Treatment and Immobilization Plant Project in Richland, WA. These exchanges are week-long events that involve presentations, poster sessions, tours and networking events. The main focus of the exchanges are the formal presentations given by early career professionals on site-specific topics which highlight challenges what is being done to address them. In addition to the presentations, early career professionals are also provided the opportunity to present a poster discussing a project on which they have worked. Both the formal presentations and the posters are presented to other early career professionals as well as to senior management. Each exchange also consists of host site tours to allow the early career professionals to not only hear about the work being done at the site, but see it firsthand. The purpose of these exchanges is to expose early career professionals to other sites and their technical issues, give them exposure to senior managers, help them build professional networks, provide them a forum and a motivation to improve their presentation skills, and increase their value to DOE by equipping them with knowledge and skills that can be used to develop better solutions to technical challenges. More often than not, the early career professionals who participate in the exchanges have little to no knowledge about the different sites or the work that is being done at each one. These exchanges serve to inform early career professionals about the different sites and to allow them to build their professional network. This helps promote a collaborative work environment where professionals across different sites can share ideas on how to solve problems that are being faced. Overall, AECOM has seen these exchanges help keep early career professionals enthusiastic about the work they are currently doing at their own site as well as gaining interest in what their peers are doing at other sites. (authors)

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2024

Preliminary Workforce Development and Environmental and Co-use Management Plans for a Floating Offshore Wind Platform - CRADA 609 (Final Report)

Pacific Northwest National Laboratory (PNNL) provided technical assistance to Glosten, Inc. and its affiliate, PelaStar, LLC to advance the development of their floating offshore wind (FOSW) platform. PNNL provided guidance and assessment in two areas that are important to address in the development of FOSW platforms: (1) workforce development and (2) environmental impacts and ocean co-use considerations. This work was funded by the U.S. Department of Energy’s (DOE) Wind Energy Technologies Office (WETO) through Phase 2 of the FLoating Offshore Wind ReadINess (FLOWIN) Prize. It should be noted that the Plans presented in this report are specific to the PelaStar tension-leg platform (TLP) and may not be applicable to all FOSW platforms. Workforce development and environmental/co-use impacts are highly dependent on the geographical region in which activities take place. At the request of PelaStar, PNNL focused on two regions where development may take place: the Gulf of Maine and Northern California. PNNL generated a preliminary Workforce Development Plan for PelaStar, which includes estimated job numbers and skillsets required to establish a workforce to manufacture, install, and operate their platform as part of FOSW projects. The Plan offers methods to increase diversity, equity, and inclusion practices when developing a new workforce and includes colleges and training centers for potential recruitment. Both positive and negative impacts to communities are evaluated, with potential mitigation strategies for reducing negative impacts. The structure of Community Benefit Agreements and Project Labor Agreements are discussed, noting the limitations of the role of a platform manufacturer versus the offshore wind developer. PNNL also drafted a preliminary Environmental and Co-Use Management Plan that serves as a guide to preparing an environmental assessment related to the installation and operation of PelaStar’s unique TLP design, including its potential ecological, socioeconomic, and emissions impacts. The Plan summarizes information on relevant regulatory requirements, potential impact producing factors, monitoring and mitigation measures, and physical and biological resources in the Gulf of Maine and Northern California. One of the primary perceived benefits of the PelaStar TLP is its reduced footprint due to its tensioned tendons versus catenary or taut moorings, but more research must be done as there are no studies on PelaStar’s TLP system to-date. The section also highlights ocean co-use considerations for PelaStar’s TLP system, specifically for fisheries, including existing perspectives, methods, examples, and limitations. The PNNL team established through this preliminary work and review of available literature and resources that there is not yet much research or planning around FOSW. With FOSW being a new industry, many of the findings and planning are adapted from fixed bottom offshore wind, which itself is only just taking off in the United States. More research is needed to establish best practices for workforce development and to assess environmental and ocean co-use impacts and mitigation approaches.

17 WIND ENERGY↗
DOE OSTI2025

Machine learning-accelerated path integral molecular dynamics simulations of reactive organic electrolytes

Hydrogen bonded electrolytes that exhibit accelerated proton transport via sequential reactive hops have drawn interest for their promise in clean energy applications. Molecular dynamics simulations of these electrolytes offer the opportunity to uncover microscopic mechanistic details that could be used to design and tune the properties of candidate electrolyte technologies. However, accurately modeling the proton transfer reactions and transport properties that give rise to high charge conductivites in these electrolytes proves computationally challenging because of the need to perform lengthy condensed phase simulations, treating both the electronic and nuclear degrees of freedom quantum mechanically. In this paper, we demonstrate that such a modeling task can be efficiently achieved with the use of density functional theory (DFT)-trained machine learning potentials (MLP) to accelerate path integral molecular dynamics (PIMD) simulations. We highlight the practical utility of this approach by using it to benchmark how closely PIMD simulations employing different DFT exchange–correlation functionals reproduce the composition-dependent densities, diffusion coefficients, and electrical conductivities of mixtures consisting of imidazole and levulinic acid. Even with the speedup afforded by our MLPs, PIMD simulations remain quite expensive. Furthermore, in order to render PIMD more computationally tractable, we introduce and benchmark the accuracy of a ring polymer contraction approach that leverages a computationally efficient short-range MLP to accelerate our PIMD simulations by an additional factor of four.

Chemical bonding↗
DOE OSTI2023

Searching for Parton Energy Loss in Quark-Gluon Plasma Droplets (Technical Report)

This technical report summarizes the main accomplishments of the research performed under the U.S. Department of Energy (DOE) Office of Science, Early Career Award (ECA), grant number DE-SC0018117, from 9/1/2017 to 8/31/2022, with Prof. Dennis Perepelitsa as the single PI. The grant proposal was to investigate the quark-gluon plasma (QGP) created in ultrarelativistic collisions of large nuclei with the ATLAS experiment at the Large Hadron Collider (LHC) and to prepare for this physics with the sPHENIX experiment at the Relativistic Heavy Ion Collider (RHIC). In particular, the focus was on QGP regions of different sizes and shapes, including the tradtional “large” collision systems such as Pb+Pb as well as small collision systems such as p+Pb, where there has been evidence of QGP “flow” but not yet the accompanying energy loss from hard-scattered partons traversing the QGP medium. Additionally, a particular tool was the use of photon+jet events, where the photon is unaffected by the QGP and thus serves as the “control” while the jet (the result of parton fragmentation) is the “probe” of the QGP. The research was successfully carried out, resulting in over ten publications of experimental measurements in peer-reviewed journals, and the significant training of junior scientists.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Community Resilience Options: A Menu for Enhancing Local Energy Resilience

This document highlights areas of potential community resilience improvements, especially those that relate to clean energy deployment for communities and municipalities. The National Renewable Energy Laboratory (NREL) defines resilience as "a system's ability to anticipate, prepare for, and adapt to changing conditions and withstand, respond to, and recover rapidly from disruptions through sustainable, adaptable, and holistic planning and technical solutions." This document introduces 10 categories of resilience-enhancing projects at a high level, intended for community members and decision-makers new to the topic to build their understanding of which solutions fit their community best. These categories focus primarily on community-scale measures and different options may be available at larger scales. Full implementation of the measures described here requires in-depth, site-specific considerations that go beyond the scope of this document.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Techno-Economic Basis for Coproduct Manufacturing To Enable Hydrocarbon Fuel Production from Lignocellulosic Biomass

Biorefinery process development relies on techno-economic analysis (TEA) to identify primary cost drivers, prioritize research directions, and mitigate technical risk for scale-up through development of detailed process designs. Here, we conduct TEA of a model 2000 dry metric ton-per-day lignocellulosic biorefinery that employs a two-step pretreatment and enzymatic hydrolysis to produce biomass-derived sugars, followed by biological lipid production, lipid recovery, and catalytic hydrotreating to produce renewable diesel blendstock (RDB). On the basis of projected near-term technical feasibility of these steps, we predict that RDB could be produced at a minimum fuel selling price (MFSP) of USD $9.55/gasoline-gallon-equivalent (GGE), predicated on the need for improvements in the lipid productivity and yield beyond current benchmark performance. This cost is significant given the limitations in scale and high costs for aerobic cultivation of oleaginous microbes and subsequent lipid extraction/recovery. In light of this predicted cost, we developed an alternative pathway which demonstrates that RDB costs could be substantially reduced in the near term if upgradeable fractions of biomass, in this case hemicellulose-derived sugars, are diverted to coproducts of sufficient value and market size; here, we use succinic acid as an example coproduct. The coproduction model predicts an MFSP of USD $5.28/GGE when leaving conversion and yield parameters unchanged for the fuel production pathway, leading to a change in biorefinery RDB capacity from 24 to 15 MM GGE/year and 0.13 MM tons of succinic acid per year. Additional analysis demonstrates that beyond the near-term projections assumed in the models here, further reductions in the MFSP toward $2-3/GGE (which would be competitive with fossil-based hydrocarbon fuels) are possible with additional transformational improvements in the fuel and coproduct trains, especially in terms of carbon efficiency to both fuels and coproducts, recovery and purification of fuels and coproducts, and coproduct selection and price. Overall, this analysis documents potential economics for both a hydrocarbon fuel and bioproduct process pathway and highlights prioritized research directions beyond the current benchmark to enable hydrocarbon fuel production via an oleaginous microbial platform with simultaneous coproduct manufacturing from lignocellulosic biomass.

09 BIOMASS FUELS↗
DOE OSTI2024

Theranostic Radiopnictogens: 71 As, 72 As, and 119 Sb (Final Technical Report)

This project has developed new methods for the cyclotron production of medically relevant radionuclides 71 As and 119 Sb. Arsenic and antimony are chemically homologous elements (group 5A, also known as the pnictogens) that have radionuclides that are of considerable interest within nuclear medicine. Such radiopnictogens include the potentially therapeutic radionuclides 119 Sb (t 1/2 = 38 h) that decays with the emission of 24.5 low energy, high potency electrons per decay with little concomitant photon radiation and 77 As (t 1/2 = 39 h) that decays with average beta energy of 230 keV and diagnostic nuclides 71 As (t 1/2 = 65 h, 28% β+) and 72 As (t 1/2 = 26 h, 80% β+) for positron emission tomography (PET). This work has had major success developing new methods for the cyclotron production and radiochemical isolation of 71 As, supporting parallel developments for 119 Sb, and assessing the chemical similarities between these two homologous radionuclides. This project brought into collaboration two universities with complimentary skill sets, proficiencies, expertise, and facilities: the University of Wisconsin (UWisc) and the University of Missouri (Mizzou). Professors Ellison and Engle have experience in the small cyclotron production and radiochemical isolation of radionuclides, including 72 As and 119 Sb. Their recently developed metallurgic methods for fabricating cyclotron targets have great potential to expand and allow for the biomedical cyclotron production of long- lived, lower positron energy 71 As. Professors Hennkens and Jurisson have significant experience in the reactor production, radiochemical isolation, and biological functionalization of radioarsenic. Recent development of trithiol-based chelator molecules for functionalizing radioarsenic provide a platform for the investigation of the fundamental challenges of the promising low-energy-electron emitter, 119 Sb. Through their positions within their respective University’s graduate schools, the PIs and Co-Is effectively trained of graduate students and postdoctoral researchers in nuclear and radiochemistry, sub-specialties specifically identified in the Department of Energy (DOE) Office of Science Isotope Program long-range plan. Annual laboratory research visits for students between UWisc and Mizzou provided essential broad-field experience and scientific networking that is critical for maintaining their path along the training pipeline to productive careers in isotope production. This research collaboration has provided significant benefits to the DOE University Isotope Network and radionuclide-using researchers around the country.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2023

Improving Subsurface Stress Characterization for Carbon Dioxide Storage Projects by Incorporating Machine Learning Techniques

The overall objective of this project is to develop a framework for reliable characterization and prediction of the state of stress in the overburden and underburden (including the basement) in CO 2 storage reservoirs using machine learning and integrated geomechanics and geophysical methods. Specifically, we propose to develop workflow encompassing of technologies and/or methods to predict stress and pressure changes due to CO 2 injection in an active tertiary recovery site and their impacts on subtle fault activation, fractures and occurrence of microseismic events and compare responses to field observations. In this project, we anticipate using dataset from the Farnsworth field Unit (FWU) which is operated by Purdure Petroleum. A novel elastic-waveform VSP inversion technique will be used to estimate high-resolution spatial and temporal changes of elastic moduli in CO 2 storage reservoirs, which will be combined with velocity-stress relationship derived from laboratory tests to obtain subsurface pressure and stress. Clustered microseismic data will be jointly inverted for improved focal mechanisms. Least-squares reverse-time migration of microseismic waveform data will be performed to directly image fracture/fault zones. Additionally, a deep neural network machine learning technique with convolutional and recurrent layers will be used for learning the spectro-temporal structures in microseismic waveforms. The results of this geotechnical data analysis will be integrated to develop a high-resolution 3D mechanical earth model extending from the overburden sealing formations to the underburden including the basement. Mechanical properties will be derived through integration of mechanical logs, tests, available results from chemo-mechanical laboratory tests, and elastic inversion of seismic data using a combination of Bayesian and stochastic methods as well as machine learning technique. Failure features (faults/fractures) will be represented and/or modeled based on seismic and core data analysis. A transient hydrodynamic-geomechanical model will be developed through coupling with the calibrated FWU reservoir simulation model. The full physics coupled model will be used to train a reduced order proxy model using machine learning algorithm for estimating stress which will then be used with appropriate constitutive relationships and forward seismological models to simulate pressure changes and induced microseismicity. An advanced optimization framework will be developed to perform a history match to minimize error between field observations and simulated. The history matched proxy model will be verified against the full-physics equivalent. The field observations that will be used in the coupled model calibration process include pressure/stress inverted from VSP, moment magnitude from microseismic analysis, real time downhole pressure measurements, production and injection data. Parameter sensitivity and uncertainty analysis will be performed to characterize the impact of model parameter uncertainty on stress estimates. The proposed project will have significant impact on future field implementation of the proposed technology. Because the project field site is an ongoing CO 2 EOR development, the value of the new technology will be demonstrated in an operational context and evaluated as a viable risk mitigation strategy. Cost/benefit will be evaluated together with the various commercial incentives for CO 2 sequestration available to oil and gas operators. The extensive available dataset and ongoing data acquisition under the SWP Phase III work plan provides flexibility for investigation of multiple approaches and reduces technical risk.

58 GEOSCIENCES↗
DOE OSTI2020

KENO V.a Primer: Performing Calculations using SCALE’s Criticality Safety Analysis Sequence (CSAS5) with Fulcrum

The SCALE code system developed at Oak Ridge National Laboratory is widely used and accepted around the world for criticality safety analyses. The well-known KENO V.a three-dimensional Monte Carlo criticality computer code is one of the primary criticality safety analysis tools in SCALE. The KENO V.a primer is designed to help a new user understand and use the SCALE/KENO V.a Monte Carlo code for nuclear criticality safety analyses. It assumes that the user has a college education in a technical field. There is no assumption of familiarity with Monte Carlo codes in general or with SCALE/KENO V.a in particular. The primer is designed to teach by example, with each example illustrating two or three features of SCALE/KENO V.a that are useful in criticality analyses. The primer is based on SCALE 6.2 and 6.3, which includes the Fulcrum graphical user interface (GUI). Each example uses Fulcrum to provide the framework for preparing input data and viewing output results. Starting with a Quickstart section, the primer gives an overview of the basic requirements for SCALE/KENO V.a input and allows the user to quickly run a simple criticality problem with SCALE/KENO V.a. The sections that follow Quickstart include a list of basic objectives at the beginning that identifies the goal of the section and the individual SCALE/KENO V.a features that are covered in detail in the sample problems in that section. Upon completion of the primer, a new user should be comfortable using Fulcrum to set up criticality problems in SCALE/KENO V.a. The primer provides a starting point for the criticality safety analyst who uses SCALE/KENO V.a. Complete descriptions are provided in the SCALE/KENO V.a manual. Although the primer is self-contained, it is intended as a companion volume to the SCALE/KENO V.a training and documentation. The SCALE manual and training schedule are available at https://scale.ornl.gov. The primer provides specific examples of using SCALE/KENO V.a for criticality analyses; the SCALE/KENO V.a manual provides information on the use of SCALE/KENO V.a and all its modules. The primer also contains an appendix with sample input files. In addition, this primer, its errata and sample inputs are also available at https://code.ornl.gov/scale/primers/kenova.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2015

Post-closure program streamlining at the Nevada national security site - 15290

More than 200 sites on the Nevada National Security Site (NNSS), Nevada Test and Training Range (NTTR), and Tonopah Test Range (TTR) have been closed in place. At these sites, contamination has been left in place, and protection of human health, safety, and the environment is ensured through the establishment of use restrictions (URs). Post-closure requirements were initially established in the Closure Report (CR) for each site and include a variety of inspection, monitoring, maintenance, and reporting commitments. Post-closure requirements and site controls (fences, monuments, soil covers, and postings) may vary depending on site location, accessibility, land use scenario, and the nature of contaminants left in place. Corrective Action Sites (CASs) on the NNSS, NTTR, and TTR have been identified for closure under the Federal Facility Agreement and Consent Order (FFACO), which was signed in 1996. Over 1,900 CASs have been closed under the framework of the FFACO, and more than 200 of those have URs. Many post-closure requirements have been modified over time. In addition, because the scope of the program has spanned almost 20 years, the post-closure requirements have varied due to changing strategies and expectations. Because of the number of sites closed over the course of the program, post-closure requirements are found in hundreds of closure documents, addendums, errata sheets, Records of Technical Change, inspection reports, permit modifications, and correspondence. Furthermore, resources such as personnel and funding necessary to conduct the post-closure program have diminished, while computer capabilities and configuration control principles have improved since closure activities under the FFACO began. Because of these factors, to effectively manage the post-closure program, ensure that all commitments are being met, and improve the ease of identifying the most current post-closure requirements for each UR, the current requirements for every use-restricted site under the purview of the U.S. Department of Energy, National Nuclear Security Administration Nevada Field Office will be consolidated into a single Post-Closure Plan. The Consolidated Post-Closure Plan will also outline a strategy and present possible criteria that may be used for future evaluation of post-closure requirements. Continual assessment of the post-closure program will ensure that the post-closure requirements for URs across the NNSS, NTTR, and TTR are consistently justifiable and sufficient to protect site workers, the public, and the environment while increasing efficiency. Future changes to post-closure requirements and justification for those changes will be recorded in revisions to the Consolidated Post-Closure Plan. This process will provide a comprehensive, consistent, and streamlined method for evaluation of post-closure requirements and implementation of changes. (authors)

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Explainable Artificial Intelligence Technology for Predictive Maintenance

The domestic nuclear power plant fleet has relied on labor-intensive and time-consuming preventive maintenance programs, thus driving up operation and maintenance costs to achieve high-capacity factors. Artificial intelligence and machine learning can help simplify complex problems, such as diagnosing equipment degradation, to enable more effective decision-making. Benefits will be felt not only within existing analog and digital instrumentation and control, but also work processes, the integration of people with technology, and most importantly, the business case. Together, these hold promise to make nuclear power more efficient and reduce costs associated with operation and maintenance. While the artificial intelligence and machine learning technologies hold significant promise in the nuclear industry, there are challenges or barriers to their adoption. This report outlines the those different machine learning adoption barriers (categorized as historical, technical, economic, regulatory, and user) that the industry must overcome to realize the full benefits of artificial intelligence and machine learning capabilities for long-term economic sustainability. This report also provides solutions for some of these barriers by focusing on improving the explainability of machine learning to encourage trust from the end-user. Trust and explainability are essential to machine learning adoption. This report focuses on research-developed solutions to some of these barriers while analyzing a non-safety-related system, namely the circulating water system. This system frequently experiences waterbox fouling which our models preemptively diagnoses then explains to the operator how those conclusions were reached. This report presents and discusses the inherent trade-off between machine learning performance (in terms of accuracy) and explainability, where highly accurate machine learning methods (such as deep-learning) are the least explainable, and the most explainable methods (such as decision trees) are the least accurate. In addition, explainability of artificial intelligence techniques in terms of transparency and post-hoc metrics are discussed. This report outlines the importance of data novelty and value of new information in evaluating both the explainability and trustworthiness. Novelty detection helps to establish consistency or inconsistency of the new data with respect to the training data. On the other hand, value of information could be a part of the user-centric visualization recommendation system that request additional information to be collected, thereby strengthening the machine learning outcomes. During this project, a copyrighted user-centric visualization that aligns with a human-in-the-loop approach was developed. The user-centric visualization presents different levels of information and can be tailored as per user credentials to gain user confidence. One of the salient features of the user-centric visualization is it presents machine learning methods with explainability metrics. A simplified version of the user-centric visualization was presented to 32 users with varying levels of machine learning expertise. Feedback was solicited to test the hypothesis that the app contained sufficient explainability and that the users would trust the algorithm. Overall, the app was positively received, and the hypothesis was supported. This report discusses the trust-but-verify framework – a potential approach to build user trust artificial intelligence. The framework discusses trust from the human level to artificial intelligence level. The fundamental premise of the trust but verify framework is derived from an observation of nuclear safety culture (i.e., nuclear power plant personnel do not rely on a singular source of data to make a decision). This also ties back to the user-centric visualization that presents different levels of information to achieve both explainability and trustworthiness of artificial intelligence. Even so, the adoption of artificial intelligence and machine learning in the nuclear industry faces additional barriers, namely regulatory and stakeholder readiness. To overcome these challenges, new solutions must gain regulatory approval and cater to stakeholder needs. The Nuclear Regulatory Committee has a 5-year strategic plan which prepares them for reviewing artificial intelligence technologies in licensee submissions. Early and frequent engagement with the regulator is encouraged. Additionally, artificial intelligence solutions should incorporate human-in-the-loop considerations and offer explainability. Stakeholders must prepare by hiring or training staff to adapt to advancing technology in everyday plant tasks.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

FORCE Update 2024

The Framework for Optimization of Resources and Economics (FORCE) tool suite is the U.S. Department of Energy’s Nuclear Integrated Energy Systems (IES) Program flagship tool suite for technoeconomic IES analysis of IES. This tool suite is useful for analysis designed to evaluate and improve the technoeconomics of energy production systems, particularly for systems including nuclear technology. In this report, we document the development activity for the FORCE tool suite to extend its capabilities as performed during fiscal year 2024. In addition to reliability and accessibility, capability is one of the three standards guiding the development of the FORCE tool suite and the software codes that are its constituent parts. Extending the capabilities of the FORCE tool suite allows analysis both within the IES program as well as industry, university, and laboratory partners to perform analysis with more accuracy, insight, and impactful narrative. Four areas of capability development were the focus of activity this year: economic parameter uncertainty quantification, multiresolution analysis, components-to-optimization workflow automation, and statespace construction workflows for real-time optimal control. In economic parameter uncertainty quantification, the ability of HERON to capture risk due to scenarios (weather and energy demand uncertainty) was expanded to also include uncertainties in financial parameters such as capital cost or operation and maintenance costs. By including these sources of uncertainty, which are sometimes very large compared with scenario uncertainty, HERON is better able to capture the risk posed by investment in various IES technology. Because of this, analysts can also consider the reduction in risks that can be realized by choice of some technologies. In multiresolution analysis, development activity extended on work completed previously. In fiscal year 2023, methods for decomposing time series signals, such as demand, solar and wind availability, and price profiles, were analyzed and down-selected to those most effective at splitting signals into different resolutions. These resolutions allow considering the influence of different energy demand and supply behaviors across different time scales. For example, energy demand might be divided into seasonal, weekly, and hourly profiles. In fiscal year 2024, this preliminary work was extended and implemented within the Risk Analysis Virtual Environment (RAVEN) risk and uncertainty analysis platform, which is used throughout the FORCE framework. This development of the “multi-resolution time series analysis” (MR-TSA) module in RAVEN allows training synthetic history generators on complex time series. These synthetic history generators can then be used in HERON for generating scenarios that represent possible market and weather scenarios that can be analyzed on different time scales. We envision completing this work in the future, implementing multiresolution dispatch optimization strategies that can make the most beneficial use of these stratified time histories. In components-to-optimization workflow development, workflows for translating user inputs of components into algorithms for algebraic optimization were selected and implemented. Similar algorithms within the Holistic Energy Resource Optimization Network (HERON) were separated from the main code base of HERON and gathered with the components-to-optimization workflows in the new Dispatch Optimization Variable Engine (DOVE) software library. This modularization allows FORCE users to analyze dispatch optimization and energy system duty cycles independently of HERON, which previously was a burdensome task. Additionally, these dispatch optimization algorithms, set up in an independent library, can now be used across all software applications within FORCE, especially including the real-time optimal control software Optimization of Real-time Capacity Allocation (ORCA). Allowing FORCE software to share dispatch optimization algorithms within a single library allows for improved software maintenance and reliability. In statespace characterization workflow development, alternative workflows for optimizing dispatch with additional technical accuracy was the focus, particularly to improve the real-time optimization decision making in ORCA. Using algorithms and workflows initially developed for the Feasible Actuator Range Modifier (FARM), workflows for determining the statespace representation of IES were identified and demonstrated. The resulting dispatch optimization required a more robust optimization algorithm than that originally used in HERON (and moved to DOVE), which required adding an alternate workflow to DOVE that can more accurately match the behavior of physical systems using a partial differential equation representation. In conclusion, capability developments in the FORCE tool suite in fiscal year 2024 have improved the ability of the FORCE tool suite to perform

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRSDate not supplied

Extended Duration: The SIRIUS 21 Crew Perspective

The SIRIUS (Scientific International Research In a Unique terrestrial Station) missions represent a collaborative effort between NASA and Russia’s Institute for Biomedical Problems (IBMP) to conduct a series of long duration isolation and confinement spaceflight analog missions. Three missions of 17-day, 4-month, and 8-month duration (SIRIUS 17, 19, and 21) have been completed at IBMP’s Ground-Based Experimental Complex / Nazemnyy eksperimental'nyy kompleks (NEK) in Moscow, Russia. The international SIRIUS 21 crew comprising representatives from the United States, United Arab Emirates and Russia recently completed the 8-month analog lunar mission. The extended duration mission included simulated lunar transit, orbital, and surface operations with corresponding deep space communication delay, during which the crew participated in nearly 70 studies, eight of which were sponsored by NASA’s Human Research Program. The studies examined the effect of isolation and confinement on the behavioral health of research subjects, and investigated medical countermeasures, team performance, crew dynamics, crew autonomy, food system risks, consequences of confinement and associated physiological stressors. SIRIUS 21 crewmembers also participated in operational tasks such as Rover and CubeSat assembly, simulated lunar sample assessment, VR activities, robotic arm training, environmental systems monitoring, exercise, greenhouse maintenance and 3D printing. Communication with Mission Control was limited to 30-minute periods every two hours. Since access to the internet and email was restricted, simulated ground support provided the Crew’s primary source of daily news and mission information. This panel discussion will include presentations from the US SIRIUS 21 crewmembers – William Brown and Ashley Kowalski – about their experience participating in the mission and science. A facilitated question and answer session will follow with attendees encouraged to ask questions and join in discussion with the SIRIUS 21 crewmembers about their experiences. William Brown came to SIRIUS 21 with experience spread across multiple industries, including the military, defense contracting, healthcare consulting, software engineering, and logistics. He has lived in the Middle East, Central Asia, and Russia. A former Boren Scholar, Brown is fluent in Russian. He holds a Master of International Business degree from the University of South Carolina’s Darla Moore School of Business. Prior to that, he earned a bachelor’s degree in Russian language, literature, and culture from the University of South Carolina. There, he also completed additional undergraduate coursework in computer science. Ashley Kowalski is a Project Leader in The Aerospace Corporation’s International Partnerships Department, where she works with, represents, and provides technical support to the the U.S. Space Force Space Systems Command International Affairs (SSC/IA) office. Through her numerous national and international assignments (Russia, China, and Germany), she has worked on topics related to international space systems, national security space systems, civil systems (including human spaceflight and civil launch projects), space policy, satellite industry analysis, and satellite manufacturing start-ups. She is proficient in Russian and German, and fluent in Polish. Kowalski received her Bachelor of Science and Master of Science degrees in mechanical and aerospace engineering from George Washington University in 2011 and 2012, respectively.

S. E. Whiting↗
DOE OSTI2022

Technical note: Using long short-term memory models to fill data gaps in hydrological monitoring networks

Abstract. Quantifying the spatiotemporal dynamics in subsurface hydrological flows over a long time window usually employs a network of monitoring wells. However, such observations are often spatially sparse with potential temporal gaps due to poor quality or instrument failure. In this study, we explore the ability of recurrent neural networks to fill gaps in a spatially distributed time-series dataset. We use a well network that monitors the dynamic and heterogeneous hydrologic exchanges between the Columbia River and its adjacent groundwater aquifer at the U.S. Department of Energy's Hanford site. This 10-year-long dataset contains hourly temperature, specific conductance, and groundwater table elevation measurements from 42 wells with gaps of various lengths. We employ a long short-term memory (LSTM) model to capture the temporal variations in the observed system behaviors needed for gap filling. The performance of the LSTM-based gap-filling method was evaluated against a traditional autoregressive integrated moving average (ARIMA) method in terms of error statistics and accuracy in capturing the temporal patterns of river corridor wells with various dynamics signatures. Our study demonstrates that the ARIMA models yield better average error statistics, although they tend to have larger errors during time windows with abrupt changes or high-frequency (daily and subdaily) variations. The LSTM-based models excel in capturing both high-frequency and low-frequency (monthly and seasonal) dynamics. However, the inclusion of high-frequency fluctuations may also lead to overly dynamic predictions in time windows that lack such fluctuations. The LSTM can take advantage of the spatial information from neighboring wells to improve the gap-filling accuracy, especially for long gaps in system states that vary at subdaily scales. While LSTM models require substantial training data and have limited extrapolation power beyond the conditions represented in the training data, they afford great flexibility to account for the spatial correlations, temporal correlations, and nonlinearity in data without a priori assumptions. Thus, LSTMs provide effective alternatives to fill in data gaps in spatially distributed time-series observations characterized by multiple dominant frequencies of variability, which are essential for advancing our understanding of dynamic complex systems.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Evolving the SpaceFOM: Lessons Learned and Future Development

For over fifty years, simulation has been a cornerstone technology for space missions. In many cases, one single simulator, developed by one team, is not enough to meet the simulation objectives. Astronaut crew training, docking, vehicle testing and complex mission planning all require several simulations to be connected and to interoperate, in order to achieve the goal of the simulation. To facilitate the development of interoperable simulations, an open standard, the SISO SpaceFOM was developed in collaboration between government, industry and academia. The standard was released in 2020. The initial release of SpaceFOM focuses on the core interoperability topics for space simulation: (i) specifying spatial data using several, well defined reference frames, (ii) managing time (including real-time, hard real-time, and as-fast-as-possible execution), (iii) composition of systems with subsystems such as space vehicles, and (iv) execution control, such as initializing, running, pausing, and terminating simulations. A number of requirements for the next version of SpaceFOM have been identified and proposed solutions are already under development. One key area is the object classes used for data exchange, where a richer set of classes have been proposed, based on practical use cases. For time management, the use of variable time resolutions and variable time steps is also proposed. For execution control, save and restore of simulations is considered as well as improved robustness, to handle failing components. A number of clarifications are also under consideration. This paper provides both a forward-looking view of the technical developments underway and a retrospective on the standard's evolution. The authors emphasize that prioritizing core challenges and delivering a practical first version were crucial steps. While not every idea was implemented in the initial release, the timely delivery of a functional standard enabled real-world applications, the growth of a user community, and the collection of valuable insights to shape future versions. The authors look forward to working with the next version of SpaceFOM together with the growing user community.

FOMs↗
DOE OSTI2024

Application of aerosol-ice nucleating particle closure to establish the leading parameters governing ice crystal number concentration under commonly observed mixed-phase cloud conditions

This is the final technical report for DOE DE-SC0021034 award entitled “Application of aerosol-ice nucleating particle closure to establish the leading parameters governing ice crystal number concentration under commonly observed mixed-phase cloud conditions”. The overarching objective of this project was to gain a predictive understanding of the processes that lead from aerosols to ice-nucleating particles (INPs) to ice crystal number concentrations (ICNCs) in stratiform mixed-phase clouds where supercooled water droplets and ice crystals coexist, and to inform climate model parameterizations. During this four-year project we addressed the three main research goals of this objective: 1) Study the aerosol-INP link; 2) Develop an aerosol-cloud column model (AC-1D); and 3) Study the INP-ICNC link. Those activities significantly advanced our predictive understanding of how to represent INPs in could models and its implications on ice crystal number concentrations. The results have been published in five peer-reviewed publications with three more in review and preparation. It allowed for collaboration resulting in additional fourteen peer-reviewed publications that are concerned with the objective of this research project. This research has been communicated to the scientific community at national and international meetings and conferences by numerous talks, seminars, and posters including fifteen invited presentations. This project allowed training of four graduate students and one postdoctoral research associate resulting in one M.S. thesis and advancement to Ph.D. candidacy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

A Multi-State Model for Catalyzing the National Home Energy Retrofit Market (Final Technical Report)

In the fall of 2010, the Alabama Department of Economic and Community Affairs (ADECA) launched the Multi-State Model for Catalyzing the National Home Energy Retrofit Market Project (Multi-State Project). This residential energy efficiency pilot program was a collaborative effort among the states of Alabama, Massachusetts, Virginia, and Washington, and was funded by competitive State Energy Program (SEP) awards through the U.S. Department of Energy (DOE). The objective of this project was to catalyze the home energy efficiency retrofit market in select areas within the state of Alabama. To achieve this goal, the project addressed a variety of marketplace elements that did not exist, or were underdeveloped, at the outset of the effort. These included establishing minimum standards and credentials for marketplace suppliers, educating and engaging homeowners on the benefits of energy efficiency and addressing real or perceived financial barriers to investments in whole-home energy efficiency, among others. The anticipated effect of the activities would be increased market demand for retrofits, improved audit to retrofit conversion rates and growth in overall community understanding of energy efficiency. The four-state collaborative was created with the intent of accelerating market transformation by allowing each state to learn from their peers, each of whom possessed different starting points, resources, and strategies for achieving the overall objective. The four partner states engaged the National Association of State Energy Officials (NASEO) to oversee a project steering committee and to manage the project evaluation for all four states. The steering committee, comprised of key program partners, met on a regular basis to provide overall project coordination, guidance, and progress assessment. While there were variances in program design among the states, there were several common elements: use of the Energy Performance Score (EPS) platform; an audit and home energy rating tool; emphasis on community based coordination and partnerships; marketing and outreach to increase homeowner participation; training for market actors; access to financing options including rebates, incentives, and loan products; and an in depth process evaluation to support continual program improvement and analysis. In Alabama, Nexus Energy Center operated energy efficiency retrofit programs in Huntsville and Birmingham. In the Huntsville community the AlabamaWISE program was available in five Alabama counties: Cullman, Lawrence, Limestone, Madison, and Morgan. In Birmingham, the program was available to residents in Jefferson and Shelby Counties. In both communities, the program was similar in terms of program design but tailored marketing and partnerships to address the unique local conditions and population of each community. ADECA and the Southeast Energy Efficiency Alliance (SEEA) provided overall project management services and common resources to the local program administrator Nexus Energy Center, including contracted services for contractor training, quality assurance testing, data collection and reporting, and compliance. The fundamental components of the AlabamaWISE program included a vertical contractor-based business model; comprehensive energy assessments; third-party quality assurance; rebates for installation of energy saving measures; accessible, low-interest financing; targeted and inbound marketing; Energy Performance Score (EPS) tool to engage and educate homeowners; training for auditors, contractors, and real estate professionals; and online resources for education and program enrollment. Program participants were eligible to receive rebates or financing toward the assessments and upgrades to their home provided they reached at least 20 percent deemed or modeled energy savings. The design of each program focused on addressing several known barriers including: limited homeowner knowledge on the benefits of energy efficiency, lack of financing options, lack of community support for energy efficiency programs, and lack of trained market actors including contractors and real estate professionals. The programs were able to make progress on addressing all of these barriers and were most successful in offering financing options and training market actors. The most challenging barriers proved to be the act of building a market for energy efficiency where none previously existed, convincing homeowners of the value in investing in energy efficiency (and therefore completing retrofits), engaging electric and natural gas utilities to partner on delivery, and achieving the overall project target of 1,365 completed retrofits. The components that proved to be the most valuable to program success were engaged contractor networks that could promote and endorse the program, partnerships with local business and organizations, and the access to rebates, incentives and financing mechanisms. The programs were successful in building relationships with a variety of community participants including: local contractors, Associations of REALTORS, home builders associations, universities, utilities, local and state governments, and other non-profit organizations. Throughout this program, 933 building audits and 795 building retrofits were completed making homes in Alabama more comfortable, less expensive to operate, more valuable to the marketplace, and safer and healthier for families. Continuing on this momentum, Nexus Energy Center plans to continue operating and expanding operations in Alabama as a Home Performance with ENERGY STAR sponsor and will continue to provide energy services and education to communities in Alabama.

Grimes, Elizabeth M.↗
NASA NTRS2002

Space Ops 2002: Bringing Space Operations into the 21st Century. Track 3: Operations, Mission Planning and Control. 2nd Generation Reusable Launch Vehicle-Concepts for Flight Operations

With the successful implementation of the International Space Station (ISS), the National Aeronautics and Space Administration (NASA) enters a new era of opportunity for scientific research. The ISS provides a working laboratory in space, with tremendous capabilities for scientific research. Utilization of these capabilities requires a launch system capable of routinely transporting crew and logistics to/from the ISS, as well as supporting ISS assembly and maintenance tasks. The Space Shuttle serves as NASA's launch system for performing these functions. The Space Shuttle also serves as NASA's launch system for supporting other science and servicing missions that require a human presence in space. The Space Shuttle provides proof that reusable launch vehicles are technically and physically implementable. However, a couple of problems faced by NASA are the prohibitive cost of operating and maintaining the Space Shuttle and its relative inability to support high launch rates. The 2nd Generation Reusable Launch Vehicle (2nd Gen RLV) is NASA's solution to this problem. The 2nd Gen RLV will provide a robust launch system with increased safety, improved reliability and performance, and less cost. The improved performance and reduced costs of the 2nd Gen RLV will free up resources currently spent on launch services. These resource savings can then be applied to scientific research, which in turn can be supported by the higher launch rate capability of the 2nd Gen RLV. The result is a win - win situation for science and NASA. While meeting NASA's needs, the 2nd Gen RLV also provides the United States aerospace industry with a commercially viable launch capability. One of the keys to achieving the goals of the 2nd Gen RLV is to develop and implement new technologies and processes in the area of flight operations. NASA's experience in operating the Space Shuttle and the ISS has brought to light several areas where automation can be used to augment or eliminate functions performed by crew and ground controllers. This experience has also identified the need for new approaches to staffing and training for both crew and ground controllers. This paper provides a brief overview of the mission capabilities provided by the 2nd Gen RLV, a description of NASA's approach to developing the 2nd Gen RLV, a discussion of operations concepts, and a list of challenges to implementing those concepts.

Hagopian, Jeff↗