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DOE OSTI2025

AI-Assisted Conceptual Development of a Pre-Geometric Cosmological Model - An Exercise in AI-Assisted Conceptual Framework Generation, Paper I: Foundations and Replication Dynamics

We develop a pre-geometric cosmological framework in which existence is identified with a finite amount of unstructured energy possessing vibration as its only intrinsic property. This vibrational substrate occupies an open, bounded spectral interval $(\omega_{\min},\omega_{\max})$, ensuring finiteness of total energy and excluding infinitely stable configurations. The substrate evolves under two fundamental and competing tendencies---excitation, which amplifies coherence, and randomization, which scrambles it. Their balance produces a metastable unstructured regime in which rare fluctuations may form long-lived self-consistent spectral configurations. Because the substrate is finite and subject to competing order--disorder dynamics, no coherent configuration can be perpetually stable. We show that the only mechanism capable of sustaining long-lived organization is a replication instability: a coherent unit may reproduce into multiple offspring according to a general $1\!\to n$ rule. Replication consumes energy from the finite substrate, breaks the metastable symmetry, and induces a discrete notion of event time through the replication tick $\Delta\tau$. Temporal succession is defined through correlation ordering of spectral microstates, producing an intrinsic pre-causal structure. The compactness of the spectral domain imposes minimal and maximal timescales, bounds the internal coherence of emergent units, and limits their proliferation. These spectral constraints serve as precursors for the emergence of geometry, adjacency, and a limiting propagation speed, developed in subsequent papers of this series. Paper I provides the foundational axioms (PG1--PG9) governing the spectral substrate, its metastable dynamics, the formation of coherent units, and the necessity of replication, establishing a fully pre-geometric stage from which causal and geometric structure naturally emerge.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRSDate not supplied

Human-Autonomy Teaming Assistant to Support Small Uncrewed Aircraft Systems for Wildland Firefighting Operations

An exploratory human-in-the-loop simulation was conducted to investigate and characterize a Human-Autonomy Teaming (HAT) Assistant to support a remote operator of multiple small Uncrewed Aircraft Systems (sUAS) using a ground control station (GCS) in the context of a wildland fire surveillance mission. Operator performance using the GCS with the HAT Assistant (Assisted Mode) was compared to operator performance using the GCS without the HAT Assistant (Unassisted Mode) during two types of contingency-event scenarios (Low and High Complexity). In the Assisted Mode, the HAT Assistant provided updates to the level of risk to the mission along with recommendations for risk mitigation, which were not provided in the Unassisted Mode. No significant differences in objective performance and subjective ratings of workload, situation awareness, and trust in automation between the Assisted and Unassisted Modes were detected, however there were indications that participants preferred the Assisted GCS over the Unassisted GCS and directions for further development were explored. Additional work is necessary to further refine the HAT Assistant and better characterize its effects on remote operator performance while managing multiple sUAS assets. Future work is recommended to optimize the implementation of an assistant to support operator performance during different missions and across vehicle classes.

Human-Autonomy Teaming↗

NASA NTRSDate not supplied

Human-Autonomy Teaming Assistant to Support Small Uncrewed Aircraft Systems for Wildland Firefighting Operations

Human-Autonomy Teaming↗

DOE OSTI2020

Establishing a Technical Assistance Network to Build Capacity in Southwest Alaska (Southwest Alaska Energy Network - Final Report)

The Southwest Alaska Municipal Conference (SWAMC) is a non-profit regional membership economic development organization that represents the Aleutian/Pribilof Islands, Bristol Bay, and Kodiak regions of southwest Alaska. SWAMC applied for the DOE-OIE Establishment of an Inter-Tribal Technical Assistance Energy Providers Network grant FOA to work with our partners to provide energy planning and project development technical assistance. The project team was made up of SWAMC, three regional organizations, a management consulting firm, and a panel of technical consultants. SWAMC sub-contracted with the three Alaska Native regional non-profit organizations – Aleutian Pribilof Islands Association (APIA), Bristol Bay Native Association (BBNA), and Kodiak Area Native Association (KANA) – to fund full or partial Regional Energy Coordinator (REC) positions. The project period ran from September 2016 to March 2020. The project goal was to help southwest Alaska regional tribal partners and communities to develop efficient and financially sustainable structures for identifying and developing energy projects that enhance community resiliency and energy sustainability. This project established energy coordinators and management structures in the Aleutian, Bristol Bay, and Kodiak regions to expand technical assistance capacity of regional residents; demonstrate this capacity by advancing energy efficiency, heat, and power supply projects; and secure long-term funding commitments to establish a sustained technical assistance structure. The project team expanded technical assistance capacity of energy coordinators and regional stakeholders in several ways: by providing funding for the SWAMC project manager to attend three Office of Indian Energy trainings; for energy coordinators to attend numerous energy conferences; for utility clerks from several villages to receive one-on-one reporting training on Alaska’s Power Cost Equalization electric subsidy program; and for the Kodiak REC to complete the Arctic Remote Energy Networks Academy and NREL’s Executive Energy Leadership Academy. The energy coordinators demonstrated and shared their increased capacity by hosting several public events: SWAMC hosted two full-day energy workshops in February 2017 and 2018; the Kodiak REC hosted seven Energy Committee meetings for Kodiak stakeholders and gave several presentations at other events; and SWAMC and BBNA organized a Bristol Bay Regional Energy Visioning Session in May 2019. The project team created platforms to both share and request information to involve energy stakeholders in this project, including an energy website, a Facebook group, a periodic newsletter, surveys, mass emails, and paper mailers. An increase in regional capacity was demonstrated through several grant awards, including a $1.2 million USDA grant for Akhiok for an electric distribution infrastructure replacement; an AHFC Kickstarter grant for Aleknagik to audit 2 Tribal and 3 City buildings; and installation of an Air Source Heat Pump demonstration project in Atka. Two communities and one region – Ouzinkie (May 2017), Ugashik (July 2017), and the Bristol Bay region (May 2019) – utilized DOE’s technical assistance services to hold Strategic Energy Planning sessions with NREL and DOE facilitation assistance. And in early 2018, SWAMC established a parallel program, funded through a USDA Energy Audit and Renewable Energy Development grant to provide subsidized energy audits for small businesses in the region. SWAMC and partners have now completed energy audits of over 60 businesses (buildings and fishing vessels) and are currently operating a third round of the USDA program. Fifteen of those business owners have now received additional grant funding to cover 25% of the cost of the energy efficiency upgrades identified in the audit. This technical assistance structure will be sustained beyond DOE grant funding in several forms. As a sign of increased grant writing and project management capacity, the Kodiak Regional Energy Coordinator applied for and received a USDA Community Facilities Technical Assistance and Training grant to continue work begun under this program. Energy coordination tasks have been folded into existing economic development positions at SWAMC and at BBNA, ensuring long-term outreach and support in the region.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS2013

Comparison of Precision of Biomass Estimates in Regional Field Sample Surveys and Airborne LiDAR-Assisted Surveys in Hedmark County, Norway

Airborne scanning LiDAR (Light Detection and Ranging) has emerged as a promising tool to provide auxiliary data for sample surveys aiming at estimation of above-ground tree biomass (AGB), with potential applications in REDD forest monitoring. For larger geographical regions such as counties, states or nations, it is not feasible to collect airborne LiDAR data continuously ("wall-to-wall") over the entire area of interest. Two-stage cluster survey designs have therefore been demonstrated by which LiDAR data are collected along selected individual flight-lines treated as clusters and with ground plots sampled along these LiDAR swaths. Recently, analytical AGB estimators and associated variance estimators that quantify the sampling variability have been proposed. Empirical studies employing these estimators have shown a seemingly equal or even larger uncertainty of the AGB estimates obtained with extensive use of LiDAR data to support the estimation as compared to pure field-based estimates employing estimators appropriate under simple random sampling (SRS). However, comparison of uncertainty estimates under SRS and sophisticated two-stage designs is complicated by large differences in the designs and assumptions. In this study, probability-based principles to estimation and inference were followed. We assumed designs of a field sample and a LiDAR-assisted survey of Hedmark County (HC) (27,390 km2), Norway, considered to be more comparable than those assumed in previous studies. The field sample consisted of 659 systematically distributed National Forest Inventory (NFI) plots and the airborne scanning LiDAR data were collected along 53 parallel flight-lines flown over the NFI plots. We compared AGB estimates based on the field survey only assuming SRS against corresponding estimates assuming two-phase (double) sampling with LiDAR and employing model-assisted estimators. We also compared AGB estimates based on the field survey only assuming two-stage sampling (the NFI plots being grouped in clusters) against corresponding estimates assuming two-stage sampling with the LiDAR and employing model-assisted estimators. For each of the two comparisons, the standard errors of the AGB estimates were consistently lower for the LiDAR-assisted designs. The overall reduction of the standard errors in the LiDAR-assisted estimation was around 40-60% compared to the pure field survey. We conclude that the previously proposed two-stage model-assisted estimators are inappropriate for surveys with unequal lengths of the LiDAR flight-lines and new estimators are needed. Some options for design of LiDAR-assisted sample surveys under REDD are also discussed, which capitalize on the flexibility offered when the field survey is designed as an integrated part of the overall survey design as opposed to previous LiDAR-assisted sample surveys in the boreal and temperate zones which have been restricted by the current design of an existing NFI.

Comparison↗

NASA NTRS1988

Using a simulation assistant in modeling manufacturing systems

Numerous simulation languages exist for modeling discrete event processes, and are now ported to microcomputers. Graphic and animation capabilities were added to many of these languages to assist the users build models and evaluate the simulation results. With all these languages and added features, the user is still plagued with learning the simulation language. Futhermore, the time to construct and then to validate the simulation model is always greater than originally anticipated. One approach to minimize the time requirement is to use pre-defined macros that describe various common processes or operations in a system. The development of a simulation assistant for modeling discrete event manufacturing processes is presented. A simulation assistant is defined as an interactive intelligent software tool that assists the modeler in writing a simulation program by translating the modeler's symbolic description of the problem and then automatically generating the corresponding simulation code. The simulation assistant is discussed with emphasis on an overview of the simulation assistant, the elements of the assistant, and the five manufacturing simulation generators. A typical manufacturing system will be modeled using the simulation assistant and the advantages and disadvantages discussed.

Schroer, Bernard J.↗

NASA NTRSDate not supplied

Extravehicular Activity on the Lunar Surface: Mapping Mitigation Risk Consequence for Crew Needing Assistance or Rescue

Extravehicular activity (EVA) on the lunar surface presents unique risks to crew with possibility for injury. Without appropriate assistance or rescue capability, inability to nominally ambulate and return to a lander, especially during early Artemis missions, could have catastrophic consequences. Mapping likelihood and consequence safety risk associated with identified injury scenarios establishes a baseline from which to assess potential mitigation solutions to ensure crew health and safety. Causes leading to the need for incapacitated crew rescue (ICR) during EVA on the lunar surface were previously identified and classified using an ICR/Acute Injury scenario spectrum. Severe scenarios are those when the affected astronaut requires either partial or full continuous assistance from the rescuer. Evaluation of these continual reliance conditions included calculating event probabilities (likelihoods) associated with an early Artemis mission and mapping them to established Exploration System Directorate (ESD) probability thresholds; safety consequences were analyzed and correlated to defined ESD personnel safety categories. These resulting likelihood and consequence values served as a baseline for assessing risk reduction of three mitigation capabilities: crew assistance (rescuer crew) only, walking assist devices, and a wheeled transport device. Of the twenty-five continual reliance conditions, ten were evaluated as “catastrophic” (Level 5, loss of life) during EVA on the lunar surface with probabilities ranging from moderate to very low during an early Artemis mission. Crew assistance only and walking assist devices showed similar potential for risk reduction, with four of the ten causes decreasing to Level 4. A wheeled transport device further increased risk reduction with six of the ten conditions decreasing to Level 4. Given the catastrophic consequence of several identified conditions, assessments should be performed to determine the feasibility of mitigation capabilities. It is currently unknown whether a rescuer astronaut could effectively provide continuous assistance to enable both crew to return safely to the lander from the standpoint of both suit geometry and human performance. Although resulting in an increase in resources, providing a wheeled transport provides the highest risk reduction potential, and walking assist devices may have prevention as well as mitigation benefits.

lunar surface↗

DOE OSTI2022

Review on robot-assisted polishing: Status and future trends

Nowadays, precision components have been extensively used in various industries such as biomedicine, photonics, and optics. To achieve nanometric surface roughness, high-precision polishing is mandatory. Compared with the conventional polishing techniques, the robot-assisted polishing has the advantages of flexible working ranges and low cost. Therefore, it has been more widely deployed in demanding polishing tasks. However, few review articles were found on this topic to provide a general progress on the development of the robot-assisted polishing technology. Here in this paper reviews the recent advancement of the robot-assisted polishing. Firstly, the integration of robots with various polishing techniques is overviewed, followed by the introduction of the research status of constant force control in robot-assisted polishing. Then, the errors in typical robot-assisted polishing systems are analyzed, together with the corresponding compensation methods. At last, the future trends in the development of robot-assisted polishing are discussed. This review is intended as a roadmap for researchers or engineers who are interested in robot-assisted polishing or machining.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Evaluating technology upgrades as a complement to traditional bill assistance programs

State programs to improve energy affordability and reduce energy burden (the share of income spent on energy) could mitigate concerns about rising electricity prices. Many states offer bill assistance and rebates for weatherization and rooftop solar to income-qualifying households. Here, we analyse how these approaches may complement one another to improve energy affordability. Results illustrate trade offs between program costs and energy burden reduction, as well as between a program’s upfront and ongoing costs. Generally, the three strategies complement one another to improve energy affordability at lower net present cost than bill assistance alone, with varying effects across regions. Weatherization can reduce the solar installation capacity needed, and both together can reduce or eliminate ongoing reliance on bill assistance. Under full uptake among cost-effective households, fully rebated weatherization and solar rebated at $0.48/Watt, combined with bill assistance, yield the same modelled net present cost as bill assistance alone while reducing the share of low-income owner-occupied households with high energy burdens from 66% to 19%, compared with 34% under bill assistance alone. Absent tax credits, weatherization still reduces energy burden and bill assistance program costs, whereas solar may not be cost-competitive.

Forrester, Sydney P↗

DOE OSTI2024

Technical Assistance for Rural Alaska Tribal Energy Solutions (Final Technical Report)

The original intent of this project was to provide technical assistance (TA) to rural Tribal communities across all regions of Alaska with a focus on public infrastructure. The Alaska Native Tribal Health Consortium (ANTHC) met this goal by providing more than 48 instances of energy-related technical assistance to rural Alaska Native communities, many of which led to them securing funding and implementing new projects that contributed to reducing the high cost of energy. Additionally, the Department of Energy (DOE) Office of Indian Energy staff saw the benefits of the energy technical assistance services being provided by ANTHC and, recognizing the value of having a trusted tribal non-profit entity providing technical support to its membership, amended the project to include standardization of TA services, internal capacity building, and regional outreach. This amended scope allowed ANTHC to streamline and standardize its technical assistance process, provide outreach to rural Alaska Native communities about DOE and ANTHC’s technical assistance program, and improve the ability of staff to provide even higher quality technical deliverables in support of energy projects. Overall, this project was successful in using technical assistance to empower both rural Alaska Native communities and the Alaska Native Tribal Health Consortium to develop and deploy energy efficiency and renewable energy solutions that will reduce the extremely high energy cost burdens facing Tribal communities in Alaska.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Plasma-based global pathway analysis to understand the chemical kinetics of plasma-assisted combustion and fuel reforming

The Global Pathway Analysis (GPA) algorithm helps analyze the chemical kinetics of complex combustion systems by identifying important global reaction pathways connecting a source species to a sink species through various important intermediate species (i.e., hub species). Here, the present work aims to extend GPA algorithm to plasma-assisted combustion and fuel reforming systems to identify the dominant global pathways in such systems at various conditions. In addition, the present study extends the ability of GPA algorithm to identify reaction cycles involving the excitation of high-concentration species (e.g., O 2 , N 2 , and fuel) to their vibrational and electronic states and the subsequent de excitation to their ground state, based on their significance on the reactivity of plasma-assisted systems in terms of gas heating and radical production. Provisions are made in the GPA algorithm to evaluate the reactivity of identified re action pathways and cycles based on the element-flux transfer (i.e., dominance), heat release, and radical production rate. The newly developed Plasma-based Global Pathway Analysis (PGPA) algorithm is then used to analyze the plasma assisted combustion of ammonia and reforming of methane. The PGPA analyses elucidated the significance of vibrational-translational cycles on the reactivity of NH 3 /air mixtures. Further, analyses on the production of NO ascribed the early reforming of NH 3 to N 2 and H 2 in impeding the production of NO during plasma-assisted NH 3 ignition. Lastly, the enhanced reforming of CH 4 /N 2 mixtures using plasma has been attributed to electron impact dissociation of CH 4 when compared to thermal reforming. In contrast, conventional path-Flux analysis (PFA) was found to require significant manual effort and pre-analysis intuitions from expert knowledge, making it arduous to provide valuable in sights into plasma chemistry. The user-friendly and automated nature of PGPA thus provides a valuable tool for assessing the kinetics of plasma-assisted systems helpful in analyzing and, further, a foundation in reducing plasma-assisted chemistry, without the needs of expert knowledge.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS1997

Left ventricular diastolic filling with an implantable ventricular assist device: beat to beat variability with overall improvement

OBJECTIVES: We studied the effects of left ventricular (LV) unloading by an implantable ventricular assist device on LV diastolic filling. BACKGROUND: Although many investigators have reported reliable systemic and peripheral circulatory support with implantable LV assist devices, little is known about their effect on cardiac performance. METHODS: Peak velocities of early diastolic filling, late diastolic filling, late to early filling ratio, deceleration time of early filling, diastolic filling period and atrial filling fraction were measured by intraoperative transesophageal Doppler echocardiography before and after insertion of an LV assist device in eight patients. A numerical model was developed to simulate this situation. RESULTS: Before device insertion, all patients showed either a restrictive or a monophasic transmitral flow pattern. After device insertion, transmitral flow showed rapid beat to beat variation in each patient, from abnormal relaxation to restrictive patterns. However, when the average values obtained from 10 consecutive beats were considered, overall filling was significantly normalized from baseline, with early filling velocity falling from 87 +/- 31 to 64 +/- 26 cm/s (p < 0.01) and late filling velocity rising from 8 +/- 11 to 32 +/- 23 cm/s (p < 0.05), resulting in an increase in the late to early filling ratio from 0.13 +/- 0.18 to 0.59 +/- 0.38 (p < 0.01) and a rise in the atrial filling fraction from 8 +/- 10% to 26 +/- 17% (p < 0.01). The deceleration time (from 112 +/- 40 to 160 +/- 44 ms, p < 0.05) and the filling period corrected by the RR interval (from 39 +/- 8% to 54 +/- 10%, p < 0.005) were also significantly prolonged. In the computer model, asynchronous LV assistance produced significant beat to beat variation in filling indexes, but overall a normalization of deceleration time as well as other variables. CONCLUSIONS: With LV assistance, transmitral flow showed rapidly varying patterns beat by beat in each patient, but overall diastolic filling tended to normalize with an increase of atrial contribution to the filling. Because of the variable nature of the transmitral flow pattern with the assist device, the timing of the device cycle must be considered when inferring diastolic function from transmitral flow pattern.

Non-NASA Center↗

DOE OSTI2024

Web-Based Weatherization Assistant Getting Started Guide

This guide provides introductory information on how to get started in using the web-based Weatherization Assistant audit tool and running the National Energy Audit Tool, Manufactured Home Energy Audit, Multifamily Tool for Energy Audits, and Health and Safety Audit. For new users, this guideline also outlines how you can create a client and start an audit for that client. The Weatherization Assistant is a family of advanced audit tools designed specifically to help states and local weatherization agencies implement the US Department of Energy (DOE) Weatherization Assistance Program. The Weatherization Assistant is developed and maintained by DOE’s Oak Ridge National Laboratory (ORNL). It applies engineering and economic calculations to assist states and agencies in selecting energy-efficient retrofit measures that meet government criteria for cost effectiveness and that can be installed in homes of low-income families enrolled in the program. The Weatherization Assistant can be used to select and rank measures for individual houses, or to establish a priority list of weatherization measures for nearly identical housing types.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2008

Preliminary Design of a Ramjet for Integration with Ground-Based Launch Assist

This viewgraph presentation reviews the preliminary design of a ramjet for integration with a ground based launch assist. The reasons for the use of ground-based launch assist and the proposed mechanism for a system are reviewed. The use of a Optimal Trajectory by Implicit Simulation (OTIS), to model the flight and comparison with an actual rocket trajectory is given. The OTIS system is reviewed, The benefits of a launch assist system are analyzed concluding that a launch assist can provide supersonic speeds thus allowing ignition of ramjet without an onboard compressor. This means a further reduction in total launch weight. The Ramjet study is reviewed next. This included a review of the ONX simulations, the verification of the ONX results with the use of Holloman Sled experiment data as derived from the Feasibility of Ramjet Engine Test Capability on The Holloman AFB Sled Track. The conclusion was that the ONX system was not sufficient to meet the needs for the modeling required. The GECAT (Graphical Engine Cycle Analysis Tool) is examined. The results of the GECAT simulations was verified with data from Stataltex and D21 flights. The Next steps are: to create a GECAT Model of a launch assist ramjet, to adjust the geometry to produce the desired thrust, and to survey the ramjet's performance over a range of Mach numbers. The assumptions and requirements of a launch assist ramjet are given, and the acceptable flight regimes are reviewed.

Sayles, Emily L.↗

DOE OSTI2026

Sustainable H 2 -Rich Syngas Production via Microwave-Assisted vs Conventional Catalysis of Pinewood

Catalytic gasification of biomass is a promising method for producing hydrogen-rich syngas, which is a valuable resource for cleanenergy applications. In this study, microwave-assisted biomass gasification was compared with conventional thermally driven biomass gasification using pinewood as the biomass without the use of external gasifying agents (such as air, steam, and CO 2 ), under non-catalytic and catalytic conditions. The catalysts consisted of either an iron or a nickel catalyst, and the pinewood used as biomass contained 42% oxygen. This comparative analysis explores the differences in reaction chemistry, product yields, and the role of key reactions such as the water gas shift (WGS) reaction, Boudouard reaction, etc. The gas-phase and liquid-phase products were analyzed using online gas chromatography, and the fresh and spent catalysts were analyzed using X-ray diffraction (XRD) techniques. It was found that microwave-assisted gasification offers advantages in terms of enhanced reaction efficiency, catalyst stability, and hydrogen yield. For the microwave-assisted reaction, the gas yield reached 87%, the char yield was 12.1%, and the tar yield was less than 1% (0.793%) at 550 °C. In contrast, thermal-assisted gasification using the same catalyst produced a gas yield of 85.796%, char yield of 11.438%, and higher tar yield of 2.8% at 900 °C. The higher microwave-assisted performance was attributed to faster heating and better control over reaction conditions, higher reaction rates, and more favorable conditions for hydrogen production.

biomass↗

DOE OSTI2023

Trap characterization of high-growth-rate laser-assisted MOCVD GaN

A detailed study comparing defect incorporation between laser-assisted metal-organic chemical vapor deposition (MOCVD)-grown GaN and conventional low- and high-growth-rate MOCVD GaN was conducted. Using deep-level transient and optical spectroscopy, traps throughout the bandgap were characterized where traps were found at EC-0.25 eV, EC-0.57 eV, EC-0.72 eV, EC-0.9 eV, EC-1.35 eV, EC-2.6 eV, and EC-3.28 eV in all three samples. This indicates no new traps were observed in the laser-assisted MOCVD GaN sample. Overall, the trap concentrations in the laser-assisted MOCVD sample were ∼2× higher than the optimal low-growth-rate sample, but this is primarily due to the increase in gallium vacancy EC-2.6 eV and carbon-related EC-3.28 eV trap concentrations. The EC-0.9 eV trap concentration was ∼2× higher in the laser-assisted sample, so proton irradiation experiments were conducted to identify the physical source of this level. The results indicated this was a native point defect likely related to gallium interstitials. Overall, this study shows that the laser-assisted MOCVD growth method is promising for future thick, high-quality GaN epilayers after further growth optimizations.

Physics↗

DOE OSTI2024

Outcomes of HPC User Support using a Science Gateway AI Assistant

High Performance Computing (HPC) is a vital resource for nuclear energy research, facilitating advanced simulations and complex modeling of the quantification and qualification of advanced reactor technology. However, a common gap in knowledge exists around utilizing HPC systems, particularly for nuclear energy researchers unfamiliar with specific HPC systems. A researcher may be well-versed in using one HPC system and understanding its associated processes. Yet, they might struggle when faced with a different HPC system and its unique processes. HPC support staff play a crucial role in addressing these challenges by providing educational resources and assisting users. However, they also face the challenge of maintaining these systems and ensuring they run efficiently for all users, a responsibility that can be challenging to scale effectively with the increasing demand and expansion of HPC systems. This paper addresses this knowledge gap with an artificial intelligence (AI) assistant that offers on-demand, site-specific HPC support for researchers. Idaho National Laboratory (INL) has deployed an AI assistant that is intended to supplement expert HPC support staff and assist nuclear energy researchers. This paper reports on a four-and-a-half-month study evaluating the integration of an AI assistant within a science gateway, with the goal of enhancing existing HPC support.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

RAG for FLAG: AI Assistance for a Physics Code

Artificial intelligence (AI) has quickly become an important tool in scientific research, where significant efforts are underway to develop tools that will expedite the research process. One area of particular impact is scientific software, which can be particularly complex, and therefore time consuming to learn and use effectively. AI assistants are increasingly helping to streamline the process by performing tasks such as interactively answering user questions or suggesting solutions. Los Alamos National Laboratory (LANL) develops several advanced scientific codes, such as FLAG, which can be used to run multiphysics simulations. With this study, our goal was to develop an AI assistant for FLAG that could help make the process of understanding the software and running physics simulations more efficient. To develop an AI assistant for FLAG, we used a method called retrieval-augmented generation (RAG), which is a technique that uses information from relevant data sources to enhance the accuracy of large language models (LLMs). We used the FLAG user manual and other FLAG documentation as the knowledge base for the RAG system. When a user provides a query, RAG retrieves relevant sections from the knowledge base in response, then uses those excerpts to generate grounded and contextually rich answers. We found that our AI assistant was able to provide context aware answers and source references to user queries. To evaluate performance, we developed a set of 40 benchmark questions and compared the accuracy of the responses to those of two standard LLMs without retrieval. Our AI assistant significantly outperformed the standard LLMs at answering FLAG-related questions, with an 82.5% accuracy rate, compared to 47.5% for both of the standard LLMs. This has the potential to make the process of learning and using FLAG much easier, especially for new users. Ultimately, it supports LANL’s broader mission by empowering scientists and engineers to focus more on discovery and analysis rather than on navigating complex software systems.

97 MATHEMATICS AND COMPUTING↗