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DOE OSTI2023

Energy Resilience Reference Guide Chapter Two: Developing a Shared Framework to Value Resilience Investments

The NARUC Resilience Reference Guide is envisioned as a one-stop primer for state public utility commissions (PUCs) to assist in the development of a shared language, valuation framework, and educational tool on the topic of energy resilience. The resilience of the energy system has increasingly become part of commissions’ regulatory scope so informed decisions are made regarding how to best enhance system resiliency. Several states have already established evaluative resilience criteria (via legislative statute or regulatory directive). This guide is intended to summarize many of the critical topic areas within energy resilience and to facilitate adoption of resilience valuation frameworks by which PUCs can weigh investment decisions regarding energy system resiliency.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Energy Resilience Reference Guide, Chapter Three: Climate Resilience Strategies for Regulators

The NARUC Energy Resilience Reference Guide is envisioned as a one-stop primer for state public utility commissions (PUCs) to assist in the development of a shared language, valuation framework, and educational tool on the topic of energy resilience. The resilience of the energy system has increasingly become part of commissions’ regulatory scope so informed decisions are made regarding how to best enhance system resilience. Several states have already established evaluative resilience criteria (via legislative statute or regulatory directive). This guide is intended to succinctly summarize many of the critical topic areas within energy resilience and to facilitate adoption of resilience valuation frameworks by which PUCs can weigh investment decisions regarding energy system resiliency.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

RNA language models predict mutations that improve RNA function

Structured RNA lies at the heart of many central biological processes, from gene expression to catalysis. RNA structure prediction is not yet possible due to a lack of high-quality reference data associated with organismal phenotypes that could inform RNA function. We present GARNET (Gtdb Acquired RNa with Environmental Temperatures), a new database for RNA structural and functional analysis anchored to the Genome Taxonomy Database (GTDB). GARNET links RNA sequences to experimental and predicted optimal growth temperatures of GTDB reference organisms. Using GARNET, we develop sequence- and structure-aware RNA generative models, with overlapping triplet tokenization providing optimal encoding for a GPT-like model. Leveraging hyperthermophilic RNAs in GARNET and these RNA generative models, we identify mutations in ribosomal RNA that confer increased thermostability to the Escherichia coli ribosome. The GTDB-derived data and deep learning models presented here provide a foundation for understanding the connections between RNA sequence, structure, and function.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Synthetic Biology PacBio/JAWS QC Analysis (PBJ) v3.0

This software was designed as a sequence validation tool for the assembly of synthetic constructs. It analyzes FASTQ files against a list of reference sequences, combining the results from eight sequencing libraries to generate a summary, and the files needed to view the results in the Integrative Genomics Viewer (IGV) application for manual verification. This was developed for FASTQ files generated by PacBio sequencing, but could be used on any FASTQ files that do not have paired end reads. It can be used to analyze one - eight libraries at a time, and assumes that each construct sequence in the reference will be in each pool, however, this is not a requirement. This is used to identify which libraries of pooled sequences contains a perfect match, or fixable match to the reference file. This pipeline uses many freely available open source libraries, the value added is that in our application the steps of the pipeline are defined in Workflow Description Language (WDL) and run through the Cromwell workflow engine in Docker containers, for easy distribution and set up, as well as the user friendly html summary that is generated.

Simirenko, Lisa↗

DOE OSTI2024

SynBio QC Dual Barcode QC (DBC) v1.0

This software was designed as a sequence validation tool for the assembly of synthetic constructs, where the constructs have a high degree of similarity and thus are barcoded prior to the sequencing library prep. It demultiplexes each FASTQ file for each barcode, then analyzes the resulting FASTQ files against a list of reference sequences for that barcode/library, combining the results from eight sequencing libraries to generate a summary, and the files needed to view the results in the Integrative Genomics Viewer (IGV) application for manual verification. This was developed for FASTQ files generated by PacBio sequencing, but could be used on any FASTQ files that do not have paired end reads. It can be used to analyze one - eight libraries at a time. Each construct is independently analyzed with only the sequences with the same barcode, in the same pooled library. Then the results are combined into a user friendly summary. This is used to identify which libraries of pooled sequences contains a perfect match, or fixable match to the reference file. This pipeline uses many freely available open source libraries, the value added is that in our application the steps of the pipeline are defined in Workflow Description Language (WDL) and run through the Cromwell workflow engine in Docker containers, for easy distribution and set up, as well as the user friendly html summary that is generated.

Simirenko, Lisa↗

DOE OSTI2016

Nanomaterials in Extreme Environments: Fundamentals and Applications Rostislav A. Andrievski and Arsen V. Khatchoyan

Nanomaterials in Extreme Environments Rostislav A. Andrievski and Arsen V. Khatchoyan Springer, 2016 106 pages, $99.00 (e-book $69.99) ISBN 978–3-319–25331–2 This slim volume is an extensive review of our current understanding of the response of nanostructured materials to extreme operating conditions, such as high temperature, flux of high energy neutrons, high pressure, mechanical stress, and oxidizing environments. The emphasis is on metallic materials, especially Cu alloys. Graphene-based materials, fullerenes, polymeric materials, nano-glasses and glass-ceramics are not covered by this review. The book has six chapters including an introduction and a brief conclusion. The introduction documents the growth of scientific interest in nanostructured materials and stresses the need to study the behavior of nanomaterials under extreme conditions. This chapter also presents Herbert Gleiter’s classification of nanomaterials into twelve groups based on the shapes of the nanoscale features and chemical composition of the components of the nanostructure. The second chapter deals with the high temperature environment and the thermodynamics and kinetics of grain growth. The authors identify the lack of reliable thermodynamic data as a key limitation in this field. The discussion brings out the interplay of structural relaxation, redistribution of excess free volume, diffusion, and recrystallization in multicomponent nanostructures at elevated temperature. Chapter 3 focuses on the effects of ion and neutron irradiation on the structure and properties of nanomaterials. The authors do a good job of highlighting recent studies on the radiation tolerance of nanocrystalline oxides and rapid grain growth under irradiation. The material addresses both fission and fusion reactor applications. Chapter 4 reviews the effects of severe plastic deformation and cyclic loading on nanostructure formation and phase transformation. This chapter also explores the challenge of achieving high density while retaining nanostructural features during processing under extreme loads and high temperatures. Chapter 5 discusses the effects of corrosion on nanomaterials. The behavior of a variety of alloys and high melting point compounds in liquid media and high temperature oxidizing environments is reviewed. The concluding chapter identifies areas for further research. The book would have benefited from careful copy editing for use of the English language. Moreover, the excessive use of acronyms makes the text difficult to read. Each chapter ends with a section on the application of nanomaterials and a long list of references. The integration of theoretical approaches and simulation results with experimental data offers fresh insights into the behavior of nanomaterials. Overall, this book will serve as useful reference material for researchers interested in nanomaterials driven to extremes. Reviewer: Ram Devanathan is Technical Group Manager of Reactor Materials and Mechanical Design, Pacific Northwest National Laboratory, USA.

Devanathan, Ram↗

DOE OSTI2017

Echo

This document is a white paper marketing proposal for Echo™ is a data analysis platform designed for efficient, robust, and scalable creation and execution of complex workflows. Echo’s analysis management system refers to the ability to track, understand, and reproduce workflows used for arriving at results and decisions. Echo improves on traditional scripted data analysis in MATLAB, Python, R, and other languages to allow analysts to make better use of their time. Additionally, the Echo platform provides a powerful data management and curation solution allowing analysts to quickly find, access, and consume datasets. After two years of development and a first release in early 2016, Echo is now available for use with many data types in a wide range of application domains. Echo provides tools that allow users to focus on data analysis and decisions with confidence that results are reported accurately.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Examining Perceptions of Spanish Language Health Information Among Hispanics Living in the United States: A Qualitative Study Assessing Videos, Brochures, and Websites

Background Nationally, Hispanics experience health disparities manifested as a higher prevalence of chronic diseases in comparison to non-Hispanic Whites. Factors that influence health disparities in this population include inadequate dissemination of culturally and linguistically appropriate health information. Method Our qualitative analysis is based on data obtained from three focus groups with Spanish-speaking Hispanic adults conducted at a clinic in Nebraska. Participants were asked about their perceptions of health information in the form of videos, brochures, and websites. We followed the consolidated criteria for reporting qualitative research and used the theoretical framework of content analysis. Results For videos, attributes associated with higher levels of trust included a friendly health professional, the logo or name of a health care institute, and a reference specifying “se habla Español.” For brochures, attributes associated with trust included use of visual aids, use of numerous colors and big font sizes, the year of printing, and a health care agency logo. For websites, characteristics associated with trust were inclusion of plain language, use of pictures and videos, and date of last update. In all focus groups, participants perceived the use of mixed English/Spanish language in health information from pamphlets and websites as unprofessional. The use of unknown governmental logos in health promotional videos and websites was perceived as untrustworthy information. Conclusions Spanish-speaking Hispanics prefer health information supported by a health care agency or delivered by a health care professional. Health communication strategies should avoid the use of mixed English/Spanish language in sensitive information especially when combined with governmental logos.

De Alba Rosales, Armando↗

DOE OSTI2022

A high-fidelity building performance simulation test bed for the development and evaluation of advanced controls

We present an open-source building performance simulation test bed, the Advanced Controls Test Bed (ACTB), that interfaces high-fidelity Spawn of EnergyPlus building models, with advanced controllers implemented in Python. Additionally, the ACTB leverages the Building Optimization Testing and Alfalfa platforms for managing simulations, providing an external clock, a representational state transfer (REST) application programming interface (API), and key performance indicators for evaluating the effectiveness of control strategies. The REST API allows the development of external controllers programmed in languages such as Python, which provides flexibility and a rich choice of scientific libraries for designing control sequences. We present three test cases based on the U.S. Department of Energy's Reference Small Office Building to demonstrate the ACTB's capabilities: (a) rule-based controls compliant with ASHRAE Guideline 36 control sequences; (b) an economic model predictive control implemented using do-mpc; and (c) a deep Q-network reinforcement learning agent implemented using OpenAI Gym.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Towards a RAG-based summarization for the Electron Ion Collider

Abstract The complexity and sheer volume of information — encompassing documents, papers, data, and other resources — from large-scale experiments demand significant time and effort to navigate, making the task of accessing and utilizing these varied forms of information daunting, particularly for new collaborators and early-career scientists.To tackle this issue, a Retrieval Augmented Generation (RAG)-based Summarization AI for EIC (RAGS4EIC) is under development. This AI-Agent not only condenses information but also effectively references relevant responses, offering substantial advantages for collaborators. Our project involves a two-step approach: first, querying a comprehensive vector database containing all pertinent experiment information; second, utilizing a Large Language Model (LLM) to generate concise summaries enriched with citations based on user queries and retrieved data. We describe the evaluation methods that use RAG assessments (RAGAs) scoring mechanisms to assess the effectiveness of responses. Furthermore, we describe the concept of prompt template based instruction-tuning which provides flexibility and accuracy in summarization. Importantly, the implementation relies on LangChain [1], which serves as the foundation of our entire workflow. This integration ensures efficiency and scalability, facilitating smooth deployment and accessibility for various user groups within the Electron Ion Collider (EIC) community. This innovative AI-driven framework not only simplifies the understanding of vast datasets but also encourages collaborative participation, thereby empowering researchers. As a demonstration, a web application has been developed to explain each stage of the RAG Agent development in detail. The application can be accessed athttps://rags4eic-ai4eic.streamlit.app.[A tagged version of the source code can be found inhttps://github.com/ai4eic/EIC-RAG-Project/releases/tag/AI4EIC2023_PROCEEDING.]

Instruments & Instrumentation↗

DOE OSTI2025

Extraction and Analysis of Time Series Data from Building Automation Systems Using Large Language Models

Semantic schemas like Haystack 4, Brick and ASHRAE standard 223 enable the structured, standardized, and machine-readable representation of building data, facilitating interoperability, data integration, and advanced analytics. However, extracting information from these models requires specialized expertise in SPARQL and other programming languages, skills that are not commonly found among building professionals. Recent advancements in Large Language Models (LLMs), such as ChatGPT, enable the construction of queries using natural language, making it easier for individuals to interact with these systems in a manner that resembles everyday speech. However, these methods have not yet been tested on building semantic ontologies. This paper introduces a novel workflow and tool for enabling users to ask questions about a specific building's data, using natural language and receive answers automatically generated by GPT-4o. Our approach integrates semantic ontologies with advanced LLM capabilities to automate three critical steps: (1) generating SPARQL queries to retrieve time series references from ontological models, (2) extracting the corresponding time series data from the Building Automation System, and (3) performing computations and visualizations tailored to the user's query. The proposed method simplifies access to BAS data, allowing both domain experts and non-specialists to conduct sophisticated analyses without needing extensive technical knowledge of semantic web technologies. By demonstrating this pipeline, we facilitate more accessible and scalable data-driven decision-making in building operations and management.

Mulayim, Ozan Baris↗

DOE OSTI2024

Defining Safe and Efficient Interconnection Policies for Energy Storage and Solar + Storage to Improve Integration and Reduce Costs

Energy storage has a unique and pivotal role to play in the transition to a low-carbon economy because it can help the electric grid accommodate more renewable energy. However, a number of barriers currently impede the process of connecting energy storage systems to the distribution grid. The Toolkit and Guidance for the Interconnection of Energy Storage and Solar-Plus-Storage (the “BATRIES Toolkit”), which is the publication subject to this Final Technical / Scientific Report, provides vetted solutions to eight regulatory and technical barriers to the interconnection of standalone storage and solar-plus-storage systems (referred to as “energy storage”) to the distribution grid. These recommendations are based on over a year of research and analysis by utility and industry experts. The BATRIES Toolkit also includes model language that utilities and utility regulators can use to update state interconnection rules to reduce the costs and time to safely interconnect energy storage and solar-plus-storage systems. The solutions are nationally applicable and can be applied in diverse states and markets across the U.S.

14 SOLAR ENERGY↗

DOE OSTI2025

Extraction and Analysis of Time Series Data from Building Automation Systems Using Large Language Models

Mulayim, Ozan Baris↗

DOE OSTI2016

Addendum to the Closure Report for Corrective Action Unit 411: Double Tracks Plutonium Dispersion (Nellis), Nevada Test and Training Range, Nevada, Revision 0

The Corrective Action Unit (CAU) 411 Closure Report (CR) was published in June 2016 (NNSA/NFO, 2016). The purpose of this addendum is to clarify language in the CR relating to the field instrument for the detection of low-energy radiation (FIDLER), provide the waste disposal documentation for waste generated during the corrective action investigation (CAI), and reference a letter from the U.S. Air Force (USAF) regarding the closure of CAU 411.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Engineering Computational Practices (Rev. 1)

This manual will attempt to motivate the use of an automated build system for the purposes of computational science and engineering. As part of this motivation, the surrounding computational practices of version control, documen tation, compute environment management, and regression testing will also be addressed as applied to the practice of computational engineering. Specifically, this manual intends to motivate the adoption of these traditional software engineering practices for use in research and production engineering simulation projects. This manual is not the first such effort in the greater scientific computing community. In fact, the authors relied heavily on the lesson plans of the Software Carpentry, established to teach computing skills to researchers in 1998. As the intention for this manual is to lay out fundamental practices of engineering computing, it will not attempt to fully teach the underlying concepts and will instead reference the well designed lesson plans of the Software Carpentry. Where possible, this manual will explain to general computing practices and concepts and limit discussion of specific software implementations to examples or vehicles for practice in concrete application. The specific software taught by the Software Carpentry curriculum is an excellent starting point to learn the core concepts of computational engi neering. However, the authors have found that applications to engineering simulation and analysis require translation of these software development concepts into the language and workflows of computational engineers. Adopting these computational tools may require engineers to re-imagine their workflows in some combination of traditional engineer ing and software concepts. It has also been necessary to extend existing software build systems for engineering practices beyond the simple wrap ping of engineering software execution. Where necessary, examples of specific software and their method of extension to engineering simulations will be given, with reference to the User Manual for recommended practical use. Where this manual relies on specific implementation examples, it should be understood that the practicing engineer may find that different software is more amenable to their specific work. It is always the overall collection of computational practices is more important than any specific software implementation. The ability to recognize which concepts are implemented by a software package will make a practicing engineer agile to changing project needs, computing resources, numeric solvers, programming languages, and even available funding.

42 ENGINEERING↗

DOE OSTI2017

Hemisphere partition function and analytic continuation to the conifold point

We show that the hemisphere partition function for certain U(1) gauged linear sigma models (GLSMs) with D-branes is related to a particular set of Mellin-Barnes integrals which can be used for analytic continuation to the singular point in the Kähler moduli space of an $h^{1,1}=1$ Calabi-Yau (CY) projective hypersurface. We directly compute the analytic continuation of the full quantum corrected central charge of a basis of geometric D-branes from the large volume to the singular point. In the mirror language this amounts to compute the analytic continuation of a basis of periods on the mirror CY to the conifold point. However, all calculations are done in the GLSM and we do not have to refer to the mirror CY. We apply our methods explicitly to the cubic, quartic and quintic CY hypersurfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Watch and learn—a generalized approach for transferrable learning in deep neural networks via physical principles

Transfer learning refers to the use of knowledge gained while solving a machine learning task and applying it to the solution of a closely related problem. Such an approach has enabled scientific breakthroughs in computer vision and natural language processing where the weights learned in state-of-the-art models can be used to initialize models for other tasks which dramatically improve their performance and save computational time. Here we demonstrate an unsupervised learning approach augmented with basic physical principles that achieves fully transferrable learning for problems in statistical physics across different physical regimes. By coupling a sequence model based on a recurrent neural network to an extensive deep neural network, we are able to learn the equilibrium probability distributions and inter-particle interaction models of classical statistical mechanical systems. Our approach, distribution-consistent learning, DCL, is a general strategy that works for a variety of canonical statistical mechanical models (Ising and Potts) as well as disordered interaction potentials. Using data collected from a single set of observation conditions, DCL successfully extrapolates across all temperatures, thermodynamic phases, and can be applied to different length-scales. This constitutes a fully transferrable physics-based learning in a generalizable approach.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Empowering Geothermal Research: The Geothermal Data Repository's New AI Research Assistant

The Department of Energy's (DOE) Geothermal Data Repository (GDR) team has integrated a Large Language Model (LLM) with the metadata and supporting documents associated with GDR datasets to create an Artificially Intelligent (AI) research assistant. By leveraging work done to make GDR metadata machine-readable and an open-source LLM integration model called the Energy Language Model, developed by the National Renewable Energy Laboratory, AskGDR serves as a virtual research assistant to GDR users. It provides answers to a variety of user-provided questions using natural language processing and generative machine learning. Users can get answers to questions about specific datasets, including inquiries about the equipment, assumptions and methodologies used in the origination of the data; or more abstract questions, such as the applicability of data to specific research fields. AskGDR improves the discoverability of geothermal data by helping guide users to datasets beyond simple keyword searches. It enables users to find data based on properties of the data, discover information contained within supporting documents, and explore data from projects related to their research objectives. This paper will outline the development, integration, output, and efficacy of the AskGDR LLM, including adherence to scientific rigor through improvements designed to increase the accuracy of generated answers, avoid speculation, and provide proper references for all resources used.

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