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At least 667 records · Page 37

Process Model Development and Experimental Investigation for Spent Fuel Disposal in Crystalline Rocks: FY20 Report.

The U.S. Department of Energy Office of Spent Fuel Waste Disposition (SFWD) established in fiscal year 2010 (FY10) the Spent Fuel Waste Science & Technology (SFWST) Program (formerly the Used Fuel Disposition Campaign - UFDC) program to conduct the research and development (R&D) activities related to storage, transportation and disposal of used nuclear fuel and high level nuclear waste. The Mission of the SFWST is: To identify alternatives and conduct scientific research and technology development to enable storage, transportation and disposal of used nuclear fuel and wastes generated by existing and future nuclear fuel cycles. Significant progress has been made in FY20 in both experimental and modeling arenas in evaluation of used fuel disposal in crystalline rocks, especially in model demonstration using field data. The work covers a wide range of research topics identified in the R&D plan.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Using Machine Learning to Identify Optimum Prospects for Offshore Geologic CO 2 Storage and Enhanced Oil Recovery in the Gulf of Mexico

The SECARB Offshore Partnership is a government-industry partnership focused on assembling the knowledge base required for secure, long-term, large-scale CO 2 subsea storage in saline formations and mature oil reservoirs. The SECARB Offshore Partnership is evaluating potential storage opportunities in the Central and Eastern planning areas of the outer continental shelf (OCS) of the Gulf of Mexico. The evaluation focuses on active and depleted oil and gas fields and potentially associated CO 2 -enhanced oil recovery (CO 2 -EOR), as well as, deep saline storage resources. As part of Subtask 3.0 (Offshore Storage Resources Characterization) and Subtask 4.0 (Risk Assessment, Simulation, and Modeling), Oklahoma State University (OSU) is developing a machine learning system that employs the SAS Institute’s Viya platform with visual data mining and machine learning to identify and characterize optimum prospects for enhanced oil recovery and stacked storage in saline reservoirs. This report summarizes this effort to date and discusses the many variables that can be used to characterize these storage objectives, as well as, the design vision of the Viya machine learning system.

02 PETROLEUM↗

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↗

Satellite Precipitation and Cloud Experiment (SPACE)

An experiment plan was formulated to support an investigation of the precipitation processes associated with mesoscale systems and the interaction of rain producing cloud complexes with the meso and macro-scale environment. The field program necessary to accomplish the scientific goals is designed to incorporate satellite information (VIS and IR as well as VAS data), special radiosonde and surface observing capabilities, radar observations of storms development, special observations from aircraft and ground based lightning measurements. The observing network comprises rawinsonde stations located in northern Alabama and eastern Tennessee. A high density raingauge network and the MSFC lightning location network also cover the area. Coordination with NASA U2 and ER2 aircraft programs and with the operational requirements of the microburst severe thunderstorm program can assure the most efficient utilization of the observing resources.

Arnold, J. E.↗

Comparison of Orbiter PRCS Plume Flow Fields Using CFD and Modified Source Flow Codes

The Space Shuttle Orbiter will use Reaction Control System (RCS) jets for docking with the planned International Space Station (ISS). During approach and backout maneuvers, plumes from these jets could cause high pressure, heating, and thermal loads on ISS components. The object of this paper is to present comparisons of RCS plume flow fields used to calculate these ISS environments. Because of the complexities of 3-D plumes with variable scarf-angle and multi-jet combinations, NASA/JSC developed a plume flow-field methodology for all of these Orbiter jets. The RCS Plume Model (RPM), which includes effects of scarfed nozzles and dual jets, was developed as a modified source-flow engineering tool to rapidly generate plume properties and impingement environments on ISS components. This paper presents flow-field properties from four PRCS jets: F3U low scarf-angle single jet, F3F high scarf-angle single jet, DTU zero scarf-angle dual jet, and F1F/F2F high scarf-angle dual jet. The RPM results compared well with plume flow fields using four CFD programs: General Aerodynamic Simulation Program (GASP), Cartesian (CART), Unified Solution Algorithm (USA), and Reacting and Multi-phase Program (RAMP). Good comparisons of predicted pressures are shown with STS 64 Shuttle Plume Impingement Flight Experiment (SPIFEX) data.

Rochelle, Wm. C.↗

NASA Classroom Bioreactor

Exploration of space provides a compelling need for cell-based research into the basic mechanisms that underlie the profound changes that occur in terrestrial life that is transitioned to low gravity environments. Toward that end, NASA developed a rotating bioreactor in which cells are cultured while continuously suspended in a cylinder in which the culture medium rotates with the cylinder. The randomization of the gravity vector accomplished by the continuous rotation, in a low shear environment, provides an analog of microgravity. Because cultures grown in bioreactors develop structures and functions that are much closer to those exhibited by native tissue than can be achieved with traditional culture methods, bioreactors have contributed substantially to advancing research in the fields of cancer, diabetes, infectious disease modeling for vaccine production, drug efficacy, and tissue engineering. NASA has developed a Classroom Bioreactor (CB) that is built from parts that are easily obtained and assembled, user-friendly and versatile. It can be easily used in simple school settings to examine the effect cultures of seeds or cells. An educational brief provides assembly instructions and lesson plans that describes activities in science, math and technology that explore free fall, microgravity, orbits, bioreactors, structure-function relationships and the scientific method.

Scully, Robert↗

Engineering America's Future in Space: Systems Engineering Innovations for Sustainable Exploration

The National Aeronautics and Space Administration (NASA) delivers space transportation solutions for America's complex missions, ranging from scientific payloads that expand knowledge, such as the Hubble Space Telescope, to astronauts and lunar rovers destined for voyages to the Moon. Currently, the venerable Space Shuttle, which has been in service since 1981, provides U.S. capability for both crew and cargo to low-Earth orbit to construct the International Space Station, before the Shuttle is retired in 2010, as outlined in the 2006 NASA Strategic Plan. I In the next decade, NASA will replace this system with a duo of launch vehicles: the Ares I Crew Launch Vehicle/Orion Crew Exploration Vehicle and the Ares V Cargo Launch Vehicle/Altair Lunar Lander. The goals for this new system include increased safety and reliability, coupled with lower operations costs that promote sustainable space exploration over a multi-decade schedule. This paper will provide details of the in-house systems engineering and vehicle integration work now being performed for the Ares I and planned for the Ares V. It will give an overview of the Ares I system-level test activities, such as the ground vibration testing that will be conducted in the Marshall Center's Dynamic Test Stand to verify the integrated vehicle stack's structural integrity against predictions made by modern modeling and simulation analysis. It also will give information about the work in progress for the Ares I-X developmental test flight planned in 2009 to provide key data before the Ares I Critical Design Review. Activities such as these will help prove and refine mission concepts of operation, while supporting the spectrum of design and development tasks being performed by Marshall's Engineering Directorate, ranging from launch vehicles and lunar rovers to scientific spacecraft and associated experiments. Ultimately, the work performed will lead to the fielding of a robust space transportation solution that will carry international explorers and essential payloads for sustainable scientific discovery beyond planet Earth.

Dumbacher, Daniel L.↗

Coastal-Urban-Rural Atmospheric Gradient Experiment (CoURAGE) Science Plan

Understanding the mechanisms governing the urban atmospheric environment is critical for informing urban populations regarding the impacts of climate change and associated mitigation and adaptation measures. Earth system (climate and weather) models have not yet been adapted to provide accurate predictions of climate and weather variability within cities, nor do they provide well-tested representations of the impacts of urban systems on the atmospheric environment. These limitations are largely due to limited field data available for testing and development of these models. We will deploy the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility’s first Mobile Facility (AMF1) to the mid-Atlantic region surrounding the city of Baltimore for the Coast-Urban-Rural Atmospheric Gradient Experiment (CoURAGE). This deployment will create a four-node regional atmospheric observatory network including Baltimore and its three primary surrounding environments – rural, urban, and bay. CoURAGE investigators will study the interactions among the Earth’s surface, the atmospheric boundary layer, aerosols and atmospheric composition, clouds, radiation, and precipitation at each site, and examine how the spatial gradients across the region interact to create the climate conditions in Baltimore. This study will determine the degree to which Baltimore’s atmospheric environment depends on interactive feedbacks in the atmospheric system and the degree to which conditions in Baltimore depend on the surrounding environment. Some topics of interest include how urban land management exacerbates heat waves, the impact of regional mesoscale winds (nocturnal jet, bay breeze) on urban air pollution and cloud cover, and the impact of the urban heat island and aerosol production on heavy precipitation events. Understanding this integrated coast-urban-rural system quantitatively and with good accuracy and precision is critical to informing climate adaptation and mitigation efforts in the city of Baltimore. The understanding gained should be applicable to many similar coastal, mid-latitude urban centers. Another important objective of CoURAGE is to improve the representation of the climate of coastal cities in Earth systems models (ESMs). CoURAGE investigators will use the observations to test current ESMs, identify weaknesses and work towards improved simulations of this complex environment. The ARM core facility will be deployed in the city of Baltimore, complementing the Baltimore Social-Environmental Collaborative (BSEC), a DOE urban integrated field laboratory (UIFL). Ancillary sites will be deployed to rural Maryland northwest of Baltimore, and to the southern end of Kent Island within Chesapeake Bay. The fourth node will be a long-term atmospheric observatory operated in Beltsville, Maryland by Howard University and the Maryland Department of the Environment. Measurements will be conducted for one year, starting in December of 2024. There will be two intensive operational periods (IOPs), one in summer and one in winter, when the ancillary sites will be enhanced with additional balloon launches, tethered balloon system (TBS) operation, and added atmospheric composition measurements.

54 ENVIRONMENTAL SCIENCES↗

A risk-informed assessment tool to support review of license amendment requests for spent nuclear fuel dry cask storage systems

We report that while risk-informed safety evaluations are common methodologies used by the U.S. Nuclear Regulatory Commission (NRC), their application in the field of commercial spent nuclear fuel (SNF) dry storage has received limited attention. For instance, license amendment requests (LARs) for SNF dry cask storage systems (DCSSs) are evaluated according to U.S. NRC standard review plans (SRPs). However, risk-informed LAR review strategies could improve the understanding of critical system modifications, and lead to more predictable, efficient, and consistent LAR review processes. A methodology to develop a risk-informed LAR review tool is presented. Although focused on DCSSs, this methodology can be used to develop similar tools for a broad spectrum of safety-relevant systems. The end product (i.e., the tool) includes a tree diagram to help visualize the review risk significances assigned to a predefined set of system modifications and supporting rationale documentation. Instructions support correct tool application and provide the user with a path to incorporate currently unevaluated modifications in the tool structure. The demonstration of the methodology leads to the conclusion that risk-informed reviews of DCSS LARs are possible, although the tool precision could benefit from additional risk information. Further, the results indicate that many typical LARs involve low-risk or medium-risk modifications.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Legacy surface change analyses of the 1993 Rock Valley earthquake sequence for direct comparison to planned NA-22 underground conventional high-explosive experiments (Source Physics Experiment 3 (SPE3) - RV/DC Task 1.3 FY22 Final Report)

Recent work under two previous phases of the NNSA NA-22 Source Physics Experiment (SPE) have shown that underground chemical high-explosive experiments can produce detectable surface changes that differ in spatial extent and vertical magnitude depending on the geologic media at the site (Schultz-Fellenz et al., 2018; 2020; Crawford et al., 2021). Neither of these two prior phases of SPE identified natural earthquake-related surface effects in the same region that occurred at a similar depth as the explosive experiments for direct comparison. While earthquakes can also produce surface changes that are detectable using remote sensing data analyses, it is expected that the pattern and spatial extent of surface changes would vary between earthquakes and explosions. However, no direct-observed surface-change signature comparison between earthquakes and explosions has ever been performed. The SPE Phase 3 Rock Valley/Direct Comparison (RV/DC) program presents a unique opportunity to investigate and characterize co-occurrence of both earthquakes and explosions. In this project, we worked to address five tasks in a workflow, as follows: 1. Identify and obtain existing high-resolution legacy satellite and aerial imagery as close in time before and after the 1993 Rock Valley earthquake sequence to temporally constrain the analyses. 2. Transform these pre-earthquake and post-earthquake datasets into digital elevation models (DEMs) using geospatial analysis software packages (e.g., ArcGIS, Agisoft Metashape, and Google Earth Engine). 3. Perform DEM differencing analyses to assess and quantify earthquake-related changes from the 1993 sequence, and develop map products that visualize these analyses. 4. Use the analyses from (3) to: (a) assess spatial distribution and magnitude of surface changes due to the 1993 Rock Valley earthquake sequence, and (b) determine parameters of forthcoming, planned explosion-related surface change data collection from sensors mounted on unmanned aerial vehicles (UAVs) (e.g., spatial extent of collection, design and density of survey control, sensors to deploy, forward speed and line spacing of UAV flight lines, flight altitude). 5. Develop a summary report on the analyses, including how the analyses define parameters and identify focus areas for any future surface change analytical field campaigns related to the explosive experiment. Analyzing these legacy data and identifying whether they can detect any surface changes related to the earthquake sequence facilitates opportunities for direct signature comparison of surface change from explosions at one location, which has never previously been performed. Comparing the surface change signatures from a co-located and depth-equivalent earthquake and an explosion could help to advance remote sensing event discrimination techniques. This report summarizes the work completed toward this ambitious goal.

42 ENGINEERING↗

Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations

Background: Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here, we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022. Methods: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1–4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models’ predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models’ forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models’ past predictive performance. Results: Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models’ forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models’ forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models’ forecasts of deaths (N=763 predictions from 20 models). Across a 1–4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident death forecasts. In every forecast across 32 countries, the ensemble outperformed most contributing models when forecasting either cases or deaths, frequently outperforming all of its individual component models. Among several choices of ensemble methods we found that the most influential and best choice was to use a median average of models instead of using the mean, regardless of methods of weighting component forecast models. Conclusions: Our results support the use of combining forecasts from individual models into an ensemble in order to improve predictive performance across epidemiological targets and populations during infectious disease epidemics. Our findings further suggest that median ensemble methods yield better predictive performance more than ones based on means. Our findings also highlight that forecast consumers should place more weight on incident death forecasts than incident case forecasts at forecast horizons greater than 2 weeks. Funding: AA, BH, BL, LWa, MMa, PP, SV funded by National Institutes of Health (NIH) Grant 1R01GM109718, NSF BIG DATA Grant IIS-1633028, NSF Grant No.: OAC-1916805, NSF Expeditions in Computing Grant CCF-1918656, CCF-1917819, NSF RAPID CNS-2028004, NSF RAPID OAC-2027541, US Centers for Disease Control and Prevention 75D30119C05935, a grant from Google, University of Virginia Strategic Investment Fund award number SIF160, Defense Threat Reduction Agency (DTRA) under Contract No. HDTRA1-19-D-0007, and respectively Virginia Dept of Health Grant VDH-21-501-0141, VDH-21-501-0143, VDH-21-501-0147, VDH-21-501-0145, VDH-21-501-0146, VDH-21-501-0142, VDH-21-501-0148. AF, AMa, GL funded by SMIGE - Modelli statistici inferenziali per governare l'epidemia, FISR 2020-Covid-19 I Fase, FISR2020IP-00156, Codice Progetto: PRJ-0695. AM, BK, FD, FR, JK, JN, JZ, KN, MG, MR, MS, RB funded by Ministry of Science and Higher Education of Poland with grant 28/WFSN/2021 to the University of Warsaw. BRe, CPe, JLAz funded by Ministerio de Sanidad/ISCIII. BT, PG funded by PERISCOPE European H2020 project, contract number 101016233. CP, DL, EA, MC, SA funded by European Commission - Directorate-General for Communications Networks, Content and Technology through the contract LC-01485746, and Ministerio de Ciencia, Innovacion y Universidades and FEDER, with the project PGC2018-095456-B-I00. DE., MGu funded by Spanish Ministry of Health / REACT-UE (FEDER). DO, GF, IMi, LC funded by Laboratory Directed Research and Development program of Los Alamos National Laboratory (LANL) under project number 20200700ER. DS, ELR, GG, NGR, NW, YW funded by National Institutes of General Medical Sciences (R35GM119582; the content is solely the responsibility of the authors and does not necessarily represent the official views of NIGMS or the National Institutes of Health). FB, FP funded by InPresa, Lombardy Region, Italy. HG, KS funded by European Centre for Disease Prevention and Control. IV funded by Agencia de Qualitat i Avaluacio Sanitaries de Catalunya (AQuAS) through contract 2021-021OE. JDe, SMo, VP funded by Netzwerk Universitatsmedizin (NUM) project egePan (01KX2021). JPB, SH, TH funded by Federal Ministry of Education and Research (BMBF; grant 05M18SIA). KH, MSc, YKh funded by Project SaxoCOV, funded by the German Free State of Saxony. Presentation of data, model results and simulations also funded by the NFDI4Health Task Force COVID-19 ( https://www.nfdi4health.de/task-force-covid-19-2 ) within the framework of a DFG-project (LO-342/17-1). LP, VE funded by Mathematical and Statistical modelling project (MUNI/A/1615/2020), Online platform for real-time monitoring, analysis and management of epidemic situations (MUNI/11/02202001/2020); VE also supported by RECETOX research infrastructure (Ministry of Education, Youth and Sports of the Czech Republic: LM2018121), the CETOCOEN EXCELLENCE (CZ.02.1.01/0.0/0.0/17-043/0009632), RECETOX RI project (CZ.02.1.01/0.0/0.0/16-013/0001761). NIB funded by Health Protection Research Unit (grant code NIHR200908). SAb, SF funded by Wellcome Trust (210758/Z/18/Z).

60 APPLIED LIFE SCIENCES↗

A study of radar cross section measurement techniques

Past, present, and proposed future technologies for the measurement of radar cross section were studied. The purpose was to determine which method(s) could most advantageously be implemented in the large microwave anechoic chamber facility which is operated at the antenna test range site. The progression toward performing radar cross section measurements of space vehicles with which the Orbital Maneuvering Vehicle will be called upon to rendezvous and dock is a natural outgrowth of previous work conducted in recent years of developing a high accuracy range and velocity sensing radar system. The radar system was designed to support the rendezvous and docking of the Orbital Maneuvering Vehicle with various other space vehicles. The measurement of radar cross sections of space vehicles will be necessary in order to plan properly for Orbital Maneuvering Vehicle rendezvous and docking assignments. The methods which were studied include: standard far-field measurements; reflector-type compact range measurements; lens-type compact range measurement; near field/far field transformations; and computer predictive modeling. The feasibility of each approach is examined.

Mcdonald, Malcolm W.↗

Lunar gravitational field estimation and the effects of mismodeling upon lunar satellite orbit prediction

Lunar spherical harmonic gravity coefficients are estimated from simulated observations of a near-circular low altitude polar orbiter disturbed by lunar mascons. Lunar gravity sensing missions using earth-based nearside observations with and without satellite-based far-side observations are simulated and least squares maximum likelihood estimates are developed for spherical harmonic expansion fit models. Simulations and parameter estimations are performed by a modified version of the Smithsonian Astrophysical Observatory's Planetary Ephemeris Program. Two different lunar spacecraft mission phases are simulated to evaluate the estimated fit models. Results for predicting state covariances one orbit ahead are presented along with the state errors resulting from the mismodeled gravity field. The position errors from planning a lunar landing maneuver with a mismodeled gravity field are also presented. These simulations clearly demonstrate the need to include observations of satellite motion over the far side in estimating the lunar gravity field. The simulations also illustrate that the eighth degree and order expansions used in the simulated fits were unable to adequately model lunar mascons.

Davis, John H.↗

Update on the Fire (solar probe) mission study

Since mid-1994 the U.S. and Russia have been studying the technical feasibility of a joint solar probe mission as part of the 'Fire and Ice' concept to explore close to the Sun, and Pluto, together. In the current concept of the 'Fire' mission, separate spacecraft built by each country would be launched together, fly by Jupiter to shed orbital angular momentum and achieve a solar polar orbit, and arrive 3.6 years later at 4 and 10 R(sub s). The Fire mission would measure basic parameters of the modes of energy and momentum flow and transfer to the coronal plasma that are not observable remotely. Specifically, measurement of magnetic fields, waves, suprathermal particles, and critical features of the plasma particle composition and distribution function would be made from 4 to 30 R(sub s) where the solar wind is known to be accelerated. In addition, the Fire spacecraft should image coronal structures unambiguously and relate the underlying and flown-through structures to plasma characteristics measured in situ. Each country is developing a backup plan to pursue the solar probe objectives alone if the other side is unable to carry out its mission.

Jones, W. Veron↗

Bubbly Suspension Generated in Low Gravity

Bubbly suspensions are crucial for mass and heat transport processes on Earth and in space. These processes are relevant to pharmaceutical, chemical, nuclear, and petroleum industries on Earth. They are also relevant to life support, in situ resource utilization, and propulsion processes for long-duration space missions such as the Human Exploration and Development of Space program. Understanding the behavior of the suspension in low gravity is crucial because of factors such as bubble segregation, which could result in coalescence and affect heat and mass transport. Professors A. Sangani and D. Koch, principal investigators in the Microgravity Fluid Physics Program managed by the NASA Glenn Research Center at Lewis Field, are studying the physics of bubbly suspension. They plan to shear a bubbly suspension in a couette cell in microgravity to study bubble segregation and compare the bubble distribution in the couette gap with the one predicted by the suspension-averaged equations of motion. Prior to the Requirement Definition Review of this flight experiment, a technology for generating a bubbly suspension in microgravity has to be established, tested, and verified.

Nahra, Henry K.↗

The Autonomous Precision Landing and Hazard Detection and Avoidance Technology (ALHAT)

As NASA plans to send humans back to the Moon and develop a lunar outpost, technologies must be developed to place humans and cargo safely, precisely, repeatedly, on the lunar surface with the capability to avoid surface hazards. Exploration Space Architecture Study requirements include the need for global lunar surface access with safe, precise landing without lighting constraints on terrain that may have landing hazards for human scale landing vehicles. Landing accuracies of perhaps 1,000 meters for sortie crew missions to 10 s of meters for Outpost class missions are required. The Autonomous precision Landing Hazard Avoidance Technology (ALHAT) project will develop the new and unique descent and landing Guidance, Navigation and Control (GNC) hardware and software technologies necessary for these capabilities. The ALHAT project will qualify a lunar descent and landing GNC system to a Technology Readiness Level (TRL) of 6 capable of supporting lunar crewed, cargo, and robotic missions. The (ALHAT) development project was chartered by NASA Headquarters in October 2006. The initial effort to write a project plan and define an ALHAT Team was followed by a fairly aggressive research and analysis effort to determine what technologies existed that could be developed and applied to the lunar landing problems indicated above. This paper describes the project development, research, analysis and concept evolution that has occurred since the assignment of the project. This includes the areas of systems engineering, GNC, sensors, sensor algorithms, simulations, fielding testing, laboratory testing, Hardware-In-The-Loop testing, system avionics and system certification concepts.

Epp, Chirold D.↗

Real-Time Optimization and Control of Next-Generation Distribution Infrastructure

This presentation highlights the key developments of the ARAP-e NODES project, including the innovative real-time optimal power flow (RT-OPF) algorithm for distributed energy resource (DER) management, trip planning for T+D coordination, and extensive validation of the RT-OPF algorithm in NREL ESIF laboratory with 100+ physical hardware devices, controller-hardware-in-the-loop test at Southern California Edison (SCE), and two field demonstrations.

hardware-in-the-loop↗

Large Language Models (LLMs) for Energy Systems Research

The integration of Large Language Models (LLMs) in energy systems research promises transformative results, as demonstrated in this work, particularly in the realms of information retrieval and legal document analysis. We have developed a chat-based interface, specifically designed to query an extensive corpus of technical reports from the National Renewable Energy Laboratory (NREL). This interface capitalizes on the natural language processing capabilities of LLMs, providing future consumers of NREL research with a user-friendly platform to access and extract valuable information from technical documents, thus enhancing the dissemination of research to the public. In addition to information retrieval, we have employed LLMs to extract renewable energy siting ordinances from a variety of legal documents, a task traditionally driven by significant human labor. This automated extraction not only supports the ongoing development of the high-impact NREL siting ordinance database but also ensures the database's accuracy and comprehensiveness. Crucially, we have augmented the performance of LLMs through the integration of a decision tree framework, resulting in a substantial improvement in extraction accuracy. Comparative analysis with manual efforts has shown that this approach not only rivals but also significantly surpasses human accuracy, heralding increased reliability in legal document analysis for energy systems research. To democratize access to these advancements and foster collaborative research, we introduce the "Energy Language Model" (ELM), an open-source software package. ELM encapsulates the methodologies and tools developed in this work, providing researchers and practitioners with a robust toolkit to conduct similar analyses within their respective domains. Through these contributions, this work underscores the immense potential of LLMs in revolutionizing energy systems research, improving accuracy, efficiency, and accessibility in the field.

automation↗