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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

User’s Manual for RESRAD-RDD&IND Code Version 2: Vol. 2—User’s Guide for RESRAD-RDD&IND Code

Version 2.0 of the RESRAD-RDD&IND computer code is designed to support the implementation of protective action guides (PAGs) after a nuclear emergency incident including a radiological dispersal device (RDD) and/or an improvised nuclear device (IND) incident (EPA 2017). Eight different group types, addressing various decisions, are available for selection. The RESRAD-RDD&IND code calculates radiological doses, stay times, etc., for the selected group that the user wishes to focus on. (That is, the results for all the groups are not calculated simultaneously, and the input for those other groups do not matter, although some parameter values are shared between groups.) Version 2.0 has a user-friendly interface so that the RESRAD-RDD&IND code can be used with minimal training. For example, the user can select the major characteristics of the problem-event type, source term, and decision type from the left side of the interface and then calculate the results with the default assumptions for the exposure scenarios. More in-depth analysis would include specifying site-specific exposure scenario characteristics in the right side of the interface. The procedures for data entry and results viewing are self-explanatory. This is because common window maneuvering features and text instructions were incorporated in the interface design. General and context-specific help are available to aid users entering parameter values, as well. The RESRAD-RDD&IND computer code gives the user the option to select either an RDD or IND incident for analysis. For an RDD event analysis, 11 radionuclides (Am-241, Cf-252, Cm-244, Co-60, Cs-137, Ir-192, Po-210, Pu-238, Pu-239, Ra-226, and Sr-90) are included. These 11 radionuclides are the radionuclides most likely used for an RDD. More than 90 radionuclides can be selected for an IND event analysis. Initial default concentrations are provided for 44 radionuclides for a uranium-fueled IND event. These 44 radionuclides are those that would contribute significantly to the radiation dose associated with a uranium-fueled bomb detonation. The radionuclides generated from ingrowth of these 44 initial radionuclides are also automatically included in the analysis. Pu-239, Cs-134m, Ru-105, and Rb-89 and their progeny can be selected for analysis if they are detected and their concentrations are determined. This user’s guide, which is Volume 2 of the User’s Manual for RESRAD-RDD&IND Code Version 2, provides instructions to users on how to install the RESRAD-RDD&IND code, navigate the interface, and use the various features, including those discussed above, to set up an analysis and view/print the results in text outputs. Volume 1 of the User’s Manual for RESRAD-RDD&IND Code Version 2 (Yu et al. 2026), which contains descriptions of the methodology and theoretical basis for dose modeling and the mathematical equations implemented in the code, can be accessed and viewed through the Help menu in the code or can be downloaded from the RESRAD website (https://resrad.evs.anl.gov).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Concise Guide on Hydrogen for Ports

This Concise Guide on Hydrogen for Ports provides port stakeholders with a comprehensive overview of hydrogen as an emerging energy solution for maritime and land-based operations. It explains hydrogen’s fundamental properties, production pathways, and emissions profiles, while highlighting its potential benefits and associated challenges. The document explores practical applications for hydrogen at ports alongside considerations for storage, delivery, and integration. It also outlines implementation frameworks, stakeholder engagement approaches, and risk assessment methodologies to support informed decision-making. The guide aims to provide a pathway forward for ports that choose to consider implementation of hydrogen technology at their facility.

08 HYDROGEN↗
DOE OSTI2026

Distribution System Plan Template and Guide for Electric Utilities for Adaptation by States and Utilities [Slides]

LBNL researchers developed a template and companion guide for structuring distribution system plans. The template covers 10 key sections in utility distribution system plans and underlying topics: -Executive Summary -Planning Objectives -Current Distribution System -Planning Approach -Asst Management, Reliability and Resilience -O&M Expenses -Capacity Expansion Planning -Solution Identification -Cost-effectiveness -Implementation For each section in the template, the companion guide provides: a description of the topics covered and their importance; the type of content to include in the plan; an example utility approach; and references to other utility plans that serve as models for the topic.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Physics guided machine learning for multi-material decomposition of tissues from dual-energy CT scans of simulated breast models with calcifications

We introduce a physics guided data-driven method for image-based multi-material decomposition for dual-energy computed tomography (CT) scans. The method is demonstrated for CT scans of virtual human phantoms containing more than two types of tissues. The method is a physics-driven supervised learning technique. We take advantage of the mass attenuation coefficient of dense materials compared to that of muscle tissues to perform a preliminary extraction of the dense material from the images using unsupervised methods. We then perform supervised deep learning on the images processed by the extracted dense material to obtain the final multi-material tissue map. The method is demonstrated on simulated breast models with calcifications as the dense material placed amongst the muscle tissues. The physics-guided machine learning method accurately decomposes the various tissues from input images, achieving a normalized root-mean-squared error of 2.75%.

Gopalakrishnan Meena, Murali↗
DOE OSTI2022

Encoding Diel Hysteresis and the Birch Effect in Dryland Soil Respiration Models through Knowledge-Guided Deep Learning

Soil respiration in dryland ecosystems is challenging to model due to its complex interactions with environmental drivers. Knowledge-guided deep learning provides a much more effective means of accurately representing these complex interactions than traditional Q10-based models. Mutual information analysis revealed that future soil temperature shares more information with soil respiration than past soil temperature, consistent with their clockwise diel hysteresis. We explicitly encoded diel hysteresis, soil drying, and soil rewetting effects on soil respiration dynamics in a newly designed Long Short Term Memory (LSTM) model. The model takes both past and future environmental drivers as inputs to predict soil respiration. The new LSTM model substantially outperformed three Q10-based models and the Community Land Model when reproducing the observed soil respiration dynamics in a semi-arid ecosystem. The new LSTM model clearly demonstrated its superiority for temporally extrapolating soil respiration dynamics, such that the resulting correlation with observational data is up to 0.7 while the correlations of the Q10-based models and the Community Land Model (CLM) are less than 0.4. Our results underscore the high potential for knowledge-guided deep learning to replace Q10-based soil respiration modules in Earth system models.

Jiang, Peishi↗
DOE OSTI2020

Physics-guided Deep Learning for Power System State Estimation

In the past decade, dramatic progress has been made in the field of machine learning. This paper explores the possibility of applying deep learning in power system state estimation. Traditionally, physics-based models are used including weighted least square (WLS) or weighted least absolute value (WLAV). These models typically consider a single snapshot of the system without capturing temporal correlations of system states. In this paper, a physics-guided deep learning (PGDL) method is proposed. Specifically, inspired by autoencoders, deep neural networks (DNNs) are used to learn the temporal correlations. The estimated system states from DNNs are then checked against physics laws by running through a set of power flow equations. Hence, the proposed PGDL is both data-driven and physics-guided. The accuracy and robustness of the proposed PGDL method are compared with traditional methods in standard IEEE cases. Simulations show promising results and the applicability is further discussed.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Role of Parallel Solenoidal Electric Field on Energy Conversion in 2.5D Decaying Turbulence with a Guide Magnetic Field

We perform 2.5D particle-in-cell simulations of decaying turbulence in the presence of a guide (out-of-plane) background magnetic field. The fluctuating magnetic field initially consists of Fourier modes at low wavenumbers (long wavelengths). With time, the electromagnetic energy is converted to plasma kinetic energy (bulk flow+thermal energy) at the rate per unit volume of J· E for current density J and electric field E. Such decaying turbulence is well known to evolve toward a state with strongly intermittent plasma current. Here we decompose the electric field into components that are irrotational, E ir , and solenoidal (divergence-free), E so . E ir is associated with charge separation, and J · E ir is a rate of energy transfer between ions and electrons with little net change in plasma kinetic energy. Therefore, the net rate of conversion of electromagnetic energy to plasma kinetic energy is strongly dominated by J · E so , and for a strong guide magnetic field, this mainly involves the component E so,∥ parallel to the total magnetic field B. We examine various indicators of the spatial distribution of the energy transfer rate J ∥ · E so,∥ , which relates to magnetic reconnection, the best of which are (1) the ratio of the out-of-plane electric field to the in-plane magnetic field, (2) the out-of-plane component of the nonideal electric field, and (3) the magnitude of the estimate of current helicity.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Inferred inflow forecast horizons guiding reservoir release decisions across the United States

Abstract. Medium- to long-range forecasts often guide reservoir release decisions to support water management objectives, including mitigating flood and drought risks. While there is a burgeoning field of science targeted at improving forecast products and associated decision support models, data describing how and when forecasts are applied in practice remain undeveloped. This lack of knowledge may prevent hydrological modelers from developing accurate reservoir release schemes for large-scale, distributed hydrology models that are increasingly used to assess the vulnerabilities of large regions to hydrological stress. We address this issue by estimating seasonally varying, regulated inflow forecast horizons used in the operations of more than 300 dams throughout the conterminous United States (CONUS). For each dam, we take actual forward observed inflows (perfect foresight) as a proxy for forecasted flows available to the operator and then identify for each week of the year the forward horizon that best explains the release decisions taken. Resulting “horizon curves” specify for each dam the inferred inflow forecast horizon as a function of the week of the water year. These curves are analyzed for strength of evidence for contribution of medium- to long-range forecasts in decision making. We use random forest classification to estimate that approximately 80 % of large dams and reservoirs in the US (1553±50 out of 1927 dams with at least 10 Mm3 storage capacity) adopt medium- to long-range inflow forecasts to inform release decisions during at least part of the water year. Long-range forecast horizons (more than 6 weeks ahead) are detected in the operations of reservoirs located in high-elevation regions of the western US, where snowpack information likely guides the release. A simulation exercise conducted on four key western US reservoirs indicates that forecast-informed models of reservoir operations may outperform models that neglect the horizon curve – including during flood and drought conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Cyber-Informed Engineering (CIE) Power Generation Guide [Slides]

This guide offers suggestions for applying CIE principles to technologies used to generate electric power. It addresses issues of design, implementation, and maintenance, preemptively addressing cybersecurity threats to electric generation. The intended audience for this guide includes practitioners across the energy and cybersecurity sectors, such as energy industry professionals (e.g., engineers, system designers, operators, and researchers) and cybersecurity experts (e.g., communication system designers, information technology/operational technology [IT/OT] administrators, and penetration testers).

13 HYDRO ENERGY↗
DOE OSTI2026

Cyber-Informed Engineering: Standards Development Organization Quick Start Guide

Cyber-Informed Engineering (CIE) is an emerging methodology focused on identifying and reducing high-consequence events that may affect physical critical infrastructure systems as a result of their dependence on digital technology. CIE, developed by National Laboratories and promoted by the Department of Energy (DOE), incorporates consequence-focused planning into the design and engineering process from the earliest stages of a project. This guide provides a concise overview of CIE and offers practical insight into how Standards Development Organizations (SDOs) can interpret CIE principles and apply those concepts in updates to various standards. It is important to remember that CIE extends beyond a compliance checklist, emphasizing a broader, interpretive approach. Instead, it encourages an interpretive mindset - a "turning of 'what if' to 'even if'" approach that anticipates and engineers out high-consequence events. The authors encourage SDOs to establish and promote CIE principles as enhancements for more resilient-by-design outcomes across critical infrastructure energy sectors. The 12 core principles of CIE outline specific behaviors and actions that SDOs and engineers may adopt to enhance system resilience. This guide applies these principles in a manner intended to be relevant across various technologies and threat landscapes. We welcome institutions and vendors to identify new or different framework alignments and mappings as we collectively work towards a safer and more reliable digital landscape.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Inertia and the Power Grid: A Guide Without the Spin

This fact sheet summarizes the report “Inertia and the Power Grid: A Guide Without the Spin” (NREL/TP-6A20-73856), which provides an overview of inertia’s role in the evolving power system. It describes the sources of inertia in the grid, the intrinsic interplay of inertia and other grid services, the factors that impact the amount of and need for inertia, and the changes that can be made to maintain reliability as it declines. The guide is intended for nontechnical audiences.

grid frequency↗
DOE OSTI2022

Lighting: Development, Adoption, and Compliance Guide

The guide provides information for anyone dealing with a lighting energy code or standard. It provides background and development information to help readers understand the basis for requirements and their intent. The guide also provides detailed explanations of the major types of requirements such that users can more effectively design to meet compliance while applying the most flexibility possible.

Luminaires, IECC, code compliance, high-intensity ↗
DOE OSTI2022

Overview of Light Weight Radioisotope Heating Unit (LWRHU) User’s Guide

Idaho National Laboratory (INL) has recently compiled a user’s guide for the LightWeight Radioisotope Heating Unit (LWRHU). This guide gives an overview of the LWRHU to potential users. Information and data on mass properties, dimensions, thermal loads, and interfaces are discussed.

42 ENGINEERING↗
DOE OSTI2022

Battery state monitoring using ultrasonic guided waves

A method of battery state monitoring includes: (1) providing a battery cell and at least one ultrasonic actuator and at least one ultrasonic sensor mounted to the battery cell; (2) using the ultrasonic actuator, generating a guided wave that propagates in-plane of the battery cell; (3) using the ultrasonic sensor, receiving an arriving wave corresponding to the guided wave; and (4) determining a state of the battery cell based on the arriving wave.

Ladpli, Purim↗
DOE OSTI2024

Task 3.1: Research and Development Guiding Technoeconomic Analysis and Life-Cycle Assessment

Technologies under development aim to increase yields of desired end products, reduce overall raw material costs, and/or develop more energy-efficient strategies for product recovery. Techno-economic analysis (TEA) and life-cycle assessments (LCA) help assure that economic and sustainability predictions of the technologies are unbiased and compelling and provide guidance to experimentalists on areas that need focus. Building on previous work, the performance-advantaged bioproducts and bioprocessing separations project (SepCon) continues to use the integrated TEA and LCA to evaluate and guide technologies under development and target challenges relevant to the industry and the Bioenergy Technologies Office (BETO) priority pathways. The analysis team aims to provide credible, unbiased assessments for each technology under development, with ongoing assessments to guide experimental teams. Additionally, the team also supports journal publications highlighting key findings.

biofuels↗
DOE OSTI2024

ATR Gamma Facility User Guide

Advanced Test Reactor Gamma Facility User Guide provides guidance to assist Test Sponsors in meeting the administrative requirements associated with ATR Gamma Facility irradiations. The sections in the guide provide a brief discussion of each step, including purpose, party responsible for execution, typical order of events, general methodology, and location at which each step takes place. The length of time to complete an experiment will vary depending on the complexity of the irradiation test (i.e., experiment design) and irradiation duration.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Utility Energy Service Contract Guide

This guide serves as a key resource for acquisition teams developing utility energy service contracts (UESC) with an emphasis on using a task order to acquire energy management services under a General Services Administration areawide contract. The guide features a compilation of templates to assist your efforts from acquisition planning through awarding a task order for design and installation.

Cali, Peter [National Renewable Energy Laboratory ↗
DOE OSTI2026

A Practical Guide to E-waste Education and Events in Schools

The Practical Guide to E-waste Education and Events in Schools is a comprehensive resource that equips educators and outreach professionals to deliver impactful lessons on electronic waste (e-waste), critical materials, and battery recycling, while launching effective school-based e-waste recycling programs. It offers step-by-step guidance for starting and managing outreach efforts, including tips on student engagement, selecting recycling partners, planning collection logistics, creating promotional materials, and overcoming common challenges. The guide also supports curriculum development and scaling initiatives across schools to foster lasting recycling habits.

school outreach↗