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DOE OSTI2014

Artifacts in digital coincidence timing

Digital methods are becoming increasingly popular for measuring time differences, and are the de facto standard in PET cameras. These methods usually include a master system clock and a (digital) arrival time estimate for each detector that is obtained by comparing the detector output signal to some reference portion of this clock (such as the rising edge). Time differences between detector signals are then obtained by subtracting the digitized estimates from a detector pair. A number of different methods can be used to generate the digitized arrival time of the detector output, such as sending a discriminator output into a time to digital converter (TDC) or digitizing the waveform and applying a more sophisticated algorithm to extract a timing estimator.All measurement methods are subject to error, and one generally wants to minimize these errors and so optimize the timing resolution. A common method for optimizing timing methods is to measure the coincidence timing resolution between two timing signals whose time difference should be constant (such as detecting gammas from positron annihilation) and selecting the method that minimizes the width of the distribution (i.e. the timing resolution). Unfortunately, a common form of error (a nonlinear transfer function) leads to artifacts that artificially narrow this resolution, which can lead to erroneous selection of the 'optimal' method. In conclusion, the purpose of this note is to demonstrate the origin of this artifact and suggest that caution should be used when optimizing time digitization systems solely on timing resolution minimization.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Passive Digital Sensing Method and Its Implementation on Passive RFID Temperature Sensors

Benefitting from the advancement of digital electronics in the 20 th century, sensors have also gradually evolved from analog to digital. As semiconductor components are required in digital sensors, a power supply is still needed for the sensor. To eliminate the need for a power supply a concept of passive digital sensing is proposed. Different from the semiconductor-based electrical digital sensing method, the parameter to be measured is first converted to a mechanical signal, then the mechanical signal is encoded to multiple digital bits by a passive digitizer, where each bit is identified as open or short state that is detectable by general IO ports. To demonstrate the proposed sensing concept, a passive RFID temperature sensor is implemented using a bimetallic coil as the temperature sensing unit. The 6-bit binary codes are acquired and transmitted by a passive RFID that is powered by an energy harvester. Furthermore, the test results show that the temperature sensor has a measurement sensitivity of 1.32 °C/bit and a working distance over 10 meters.

47 OTHER INSTRUMENTATION↗

DOE OSTI2015

Light Water Reactor Sustainability Program: Digital Architecture Requirements

The Digital Architecture effort is a part of the Department of Energy (DOE) sponsored Light-Water Reactor Sustainability (LWRS) Program conducted at Idaho National Laboratory (INL). The LWRS program is performed in close collaboration with industry research and development (R&D) programs that provides the technical foundations for licensing and managing the long-term, safe, and economical operation of current nuclear power plants (NPPs). One of the primary missions of the LWRS program is to help the U.S. nuclear industry adopt new technologies and engineering solutions that facilitate the continued safe operation of the plants and extension of the current operating licenses. Therefore, a major objective of the LWRS program is the development of a seamless digital environment for plant operations and support by integrating information from plant systems with plant processes for nuclear workers through an array of interconnected technologies. In order to get the most benefits of the advanced technology suggested by the different research activities in the LWRS program, the nuclear utilities need a digital architecture in place to support the technology. A digital architecture can be defined as a collection of information technology (IT) capabilities needed to support and integrate a wide-spectrum of real-time digital capabilities for nuclear power plant performance improvements. It is not hard to imagine that many processes within the plant can be largely improved from both a system and human performance perspective by utilizing a plant wide (or near plant wide) wireless network. For example, a plant wide wireless network allows for real time plant status information to easily be accessed in the control room, field workers’ computer-based procedures can be updated based on the real time plant status, and status on ongoing procedures can be incorporated into smart schedules in the outage command center to allow for more accurate planning of critical tasks. The goal of the digital architecture project is to provide a long-term strategy to integrate plant systems, plant processes, and plant workers. This include technologies to improve nuclear worker efficiency and human performance; to offset a range of plant surveillance and testing activities with new on-line monitoring technologies; improve command, control, and collaboration in settings such as outage control centers and work execution centers; and finally to improve operator performance with new operator aid technologies for the control room. The requirements identified through the activities in the Digital Architecture project will be used to estimate the amount of traffic on the network and hence estimating the minimal bandwidth needed.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

Editorial: Edge computation and digital distribution networks

The development of digital technologies is penetrating all areas of energy revolution. Based on the in-depth integration of advanced digital technologies, distribution networks are gradually transforming into digital distribution networks (DDNs) with tremendous changes from the structure to the operation mode. DDNs is the digitalized appearance of the physical distribution network, in which ubiquitous connections and massive data are the basic characteristics (Huo et al., 2022). It is an important task to utilize the massive data and propose novel operation modes to construct more efficient and intelligent distribution networks (Jian et al., 2022). Among the advanced digital technologies in DDNs, edge computing has received wide attention (Zhao et al., 2022). It has superior performance in local sensing and intelligent computation, which can effectively relieve huge communication pressure. However, the limited computing resources and the complex computing tasks at the edge side significantly challenge the collaboration of distribution network regulation and advanced digital technologies (Hu et al., 2022). It is necessary to find out proper methods to utilize advanced digital technology to construct DDNs. This Research Topic is organized to introduce the recent progress in the construction, operation and advanced computational methods for DDNs. Finally, seven papers have been accepted, which can be sorted into the following three categories: 1) Evolution and technical features of DDNs, 2) Intelligent operation control of DDNs, 3) Advanced simulation for large-scale DDNs. The three sections below respectively introduce the major research and contributions of the papers covered in each category.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Digital Twins for Materials

Digital twins are emerging as powerful tools for supporting innovation as well as optimizing the in-service performance of a broad range of complex physical machines, devices, and components. A digital twin is generally designed to provide accurate in-silico representation of the form (i.e., appearance) and the functional response of a specified (unique) physical twin. This paper offers a new perspective on how the emerging concept of digital twins could be applied to accelerate materials innovation efforts. Specifically, it is argued that the material itself can be considered as a highly complex multiscale physical system whose form (i.e., details of the material structure over a hierarchy of material length) and function (i.e., response to external stimuli typically characterized through suitably defined material properties) can be captured suitably in a digital twin. Accordingly, the digital twin can represent the evolution of structure, process, and performance of the material over time, with regard to both process history and in-service environment. This paper establishes the foundational concepts and frameworks needed to formulate and continuously update both the form and function of the digital twin of a selected material physical twin. The form of the proposed material digital twin can be captured effectively using the broadly applicable framework of n-point spatial correlations, while its function at the different length scales can be captured using homogenization and localization process-structure-property surrogate models calibrated to collections of available experimental and physics-based simulation data.

36 MATERIALS SCIENCE↗

DOE OSTI2026

EXERGETIC: De-Risking Next-Generation Resilient Geothermal Hybrids via At-Scale Evaluation Using Virtual Emulation Digital Twin Environment for Efficient Operation

The DOE-GTO-funded project, award number 5.1.2.12, entitled "EXERGETIC - De-risking Next Generation Resilient Geothermal Hybrids via at-Scale Evaluation Using a Virtual Emulation Digital Twin Environment for Efficient Operation," advances the solution to these challenges by developing and validating a geothermal co-emulation environment implemented at the National Laboratory of the Rockies (NLR)'s Advanced Research on Integrated Energy Systems (ARIES) platform. This framework enables the de-risking of next-generation geothermal and geothermal hybrid systems through high-fidelity modeling, real-time digital emulation, advanced control strategies, and techno-economic assessment. The project focused on geothermal hybrid configurations that integrate geothermal power plants with concentrated solar power and underground thermal energy storage, enabling enhanced efficiency, flexibility, and grid support capabilities. The main goal of this project was the development of a geothermal digital co-emulation environment to demonstrate the technical and economic value of geothermal hybrid systems and their contribution to grid stability and flexibility. The EXERGETIC framework combined physics-based models, controls, and real assets at ARIES, including digital real-time simulators (DRTS), a 20-MW-scale controllable grid interface (CGI), and a 2-MW conventional generator. Detailed transient models were developed for the key subsystems of a hybrid geothermal plant, including parabolic trough solar collectors, reservoir thermal energy storage (RTES), and a binary Organic Rankine Cycle (ORC) power plant. The ORC model explicitly captured thermal inertia and off-design operation and integrated control strategies to dynamically respond to electric load profiles. The models were validated against published experimental and numerical studies, demonstrating strong agreement and confirming the accuracy and robustness of the modeling approach. The resulting digital twin represents geothermal-solar-storage systems at multiple scales (1 MW to 100 MW) and enables realistic emulation of grid-connected operation. The control architecture allows the geothermal resource to provide stable baseload generation, while solar and stored thermal energy supply flexible, dispatchable support during periods of high demand or variable grid conditions. A key contribution of the EXERGETIC project is the demonstration that geothermal hybrid systems can be designed to be active grid assets rather than passive baseload generators. Using the ARIES platform, the digital twin was evaluated under multiple grid scenarios, including load following, voltage support at the distribution level, and frequency response at the transmission level. Results show that hybrid geothermal systems can respond effectively to dynamic grid conditions, providing inertia-like behavior, primary frequency support, and voltage regulation through coordinated control. In addition to the performance and grid services capability analysis of geothermal and hybrid geothermal systems, the EXERGETIC project also focused on scalability and techno-economic analysis of geothermal hybrid plants. In particular, for the scalability analysis, machine-learning (ML)-based surrogate models were trained using data generated from the geothermal digital twin under different grid-connected scenarios and plant capacities. These ML models demonstrated strong interpolation and extrapolation capabilities across plant sizes, accurately reproducing both steady-state and transient responses with very low errors. Regarding the techno-economic analysis, plant performance results were integrated with cost models for hybrid geothermal systems, and the levelized cost of electricity (LCOE) was used as the main economic metric to evaluate system performance across a range of system capacities, solar shares, solar multiples, and storage durations. Results indicate that economies of scale significantly reduce geothermal LCOE as plant capacity increases, with large-scale systems (25-100 MW) achieving substantially lower costs than small plants. Hybridization with solar thermal energy and storage further improves economic performance by increasing capacity utilization and enabling flexible dispatch. In addition, thermal storage plays a critical role in reducing LCOE by maximizing geothermal, solar, and stored energy resources. In summary, the results from this project demonstrate that geothermal hybrid systems represent a promising alternative for increasing the energy conversion efficiency of geothermal technologies, contributing to the preservation of geothermal resources, and supporting the transition of geothermal plants from traditional baseload resources into flexible, resilient, and cost-competitive energy conversion technologies.

15 GEOTHERMAL ENERGY↗

NASA NTRS1991

Digital Signal Conditioning for Flight Test Instrumentation

This volume in the AGARD Flight Instrumentation Series provides flight test instrumentation engineers with an introduction to digital measurement processes on aircraft. Flight test instrumentation systems are rapidly evolving from analog-intensive to digital-intensive systems, including the use of onboard digital computers. Topics include measurements that are digital in origin, as well as sampling, encoding, transmitting, and storing of data. Particular emphasis is placed on modern avionic data bus architectures and what to be aware of when extracting data from them. Examples of data extraction techniques are given. Tradeoffs between digital logic families, trends in digital development, and design testing techniques are discussed. An introduction to digital filtering is also covered.

Data acquisition↗

NASA NTRS2016

Nisar L-band Digital Electronics Subsystem

The NASA-ISRO Synthetic Aperture Radar (NISAR) L-band SAR instrument employs multiple digital channels to optimize resolution while keeping a large swath on a single pass. High-speed digitization with fine synchronization and digital beam forming are necessary in order to facilitate this new technique called SweepSAR. An architecture employing multiple FPGA based digital signal processors has been conceived to facilitate digital calibration on an individual channel basis as well as digital signal processing to optimize the receive signal. On-board processing and data compression has been implemented to reduce the volume of data in order to satisfy the operational requirements of near global coverage for the desired science targets. A novel command and timing architecture was developed to manage this complex system to meet the challenging project requirements. The NISAR L-band Digital Electronics Subsystem is the combination of the hardware, firmware and software components architected and implemented to operate this radar and return the desired quantity and quality of data for the science community.

SweepSAR↗

NASA NTRS2023

Digital Engineering Design Center (DEDC): Modelling an ISRU System

The DEDC provides immersive project-based learning on digital engineering toolsets and processes supporting NASA’s digital transformation goals: - Digital Engineering uses authoritative sources of systems' data and models as a continuum across disciplines to support integrated digital approach life cycle activities from concept through disposal. - The digital environment provided includes the state-of-the-art digital engineering suite, Siemens Xcelerator. The pilot project is developing an end-to-end integrated model of an In-Situ Resource Utilization (ISRU) system for commodities production: - ISRU uses local resources to provide mission consumables to enable a sustainable Moon or Mars surface presence. - The final digital twin product will include a methanation reactor, condenser, and electrolyzer subsystem.

Digital Engineering Design Center↗

NASA NTRSDate not supplied

TIE02. IGARSS’2024 Townhall on “Digital Twins for Earth Science

NASA, ESA, NOAA, CNES and several other international organizations have started programs to design and develop Digital Twins of the Earth and/or Earth systems. Earth Systems Digital Twins (ESDTs) are dynamic and interactive information systems for understanding, forecasting, and conjecturing the complex interconnections among Earth systems, including anthropomorphic forcings and impacts to humanity. Organized around interconnected, multi-domain, high-scale modeling capabilities, the three major components of an Earth System Digital Twin are a continuously updated Digital Replica of the Earth System of interest (or “What Now”), dynamic Forecasting models (or “What Next”), and Impact Assessment capabilities (or “What If”). ESDTs provide unified, comprehensive representations and predictions that can be utilized for monitoring the health of the Planet, as well as for developing actionable information to support decision making. More generally, Digital Twins will help researchers better understand the fundamental Earth systems that impact everything from wildfires to climate change. This Townhall will provide a status of Destination Earth as well as ESA’s, NASA’s, CNES’s and NOAA’s current independent and common efforts in Digital Twins; then the four organizations will provide information about community building before engaging a dialogue about Digital Twins of the Earth with the IGARSS community.

Earth Science Remote Sensing; Information Systems;↗

NASA NTRSDate not supplied

Discovering Digital Engineering Needs Through Human-Centered Approaches

Digital engineering has the power to transform organizations in profound ways, but digitizing legacy workflows and infusing new technologies into existing practices may not yield the intended results or address the underlying problems or bottlenecks. This paper describes the human-centered approaches used to understand stakeholder challenges and identify digital engineering needs during the design-build-test portion of the systems development lifecycle. Through a series of interactive stakeholder workshops and need-finding activities, key stakeholder needs were identified to help guide the integration of digital engineering technologies. The overarching need was for downstream system development steps to be considered further upstream in the project lifecycle in a manner that allows for proactive and interactive co-constructive idea exploration, problem resolution, and requirements considerations in a collective engagement with engineers and technicians from multiple disciplines to increase efficiency and reduce risks while offering opportunities to improve the final engineered system. Supporting this need was a wide-ranging desire from stakeholders for digital and non-digital support structures for efficient rapid iteration during system development. This work yielded several improvements for system development processes and for digital engineering infusion.

Human-centered Design↗

NASA NTRSDate not supplied

Discovering Digital Engineering Needs Through Human-Centered Approaches

Design Science↗

DOE OSTI2019

Demonstration of Integrated Hazard Analysis for Digital Reactor Trip Systems

Digital instrumentation and control (I&C) upgrades are a vital research area for nuclear industry. Despite their performance benefits, deployment of digital I&C in nuclear power plants (NPPs) has been limited. Digital I&C systems exhibit complex failure modes including common cause failures (CCFs) which can be difficult to identify. This paper describes the development of a redundancy-guided application of the Systems-Theoretic Process Analysis (STPA) and Fault Tree Analysis (FTA) for the hazard analysis of digital I&C in advanced NPPs. The resulting Redundancy-guided System-theoretic Hazard Analysis (RESHA) is applied for the case study of a representative state-of-the-art digital reactor trip system. The analysis qualitatively and systematically identifies the most critical CCFs and other hazards of digital I&C systems. Ultimately, RESHA can help researchers make informed decisions for how, and to what degree, defensive measures such as redundancy, diversity, and defense-in-depth can be used to mitigate or eliminate the potential hazards of digital I&C systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2017

Development of functional requirements specification for digital instrumentation and control systems upgrades used at nuclear power plants (NPPs) - 396

Recent market conditions have driven the nuclear industry to become more innovative at reducing cost in order to remain competitive. Instrumentation and Control (I and C) systems used by many NPPs are based on outdated 1960's and 70's technology. Many of the components used in these digital systems are no longer supported by Original Equipment Manufacturers (OEMs) and are rapidly becoming obsolete. Coping with the high cost of replacing I and C equipment due to obsolescence adds to this economic challenge. While other industries have migrated from analog to modern digital I and C technology, implementation of digital I and C controls within the nuclear industry has been very slow. This is primarily due to the high capital cost related to implementation of digital I and C upgrades, which is compounded by regulatory uncertainties that present significant licensing risks. The Nuclear Regulatory Commission (NRC), Nuclear Energy Institute (NEI) and the industry's Digital I and C Working Group are working to address many of the regulatory barriers that adversely impacts implementation of digital upgrades at NPPs. The NRC has developed an 'Integrated Action Plan to Modernize Digital Instrumentation and Controls Regulatory Infrastructure' (ML16097A182), Reference 1. Once fully implemented, this plan is expected to help reduce regulatory uncertainties that affects project cost. Excluding regulatory uncertainty, most OEM's will concur that one of the most important factors in reducing project cost is assuring that all requirements are well defined and complete prior to starting the project. A detailed and high quality Functional Requirements Specification (FRS) is critical in documenting these requirements. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Digital Twin Enabling Technologies for Online Condition Monitoring of Nuclear Power Plant Components

Online condition monitoring is an area of active research that may enable improved scheduling, maintenance, and safety of nuclear power plant components, reducing unnecessary derate while simultaneously improving operational capacity. Digital twins are one avenue to conduct online condition monitoring and are currently being explored by national laboratories and universities alike. Digital twins for online condition monitoring are, in essence, state concurrent models that emulate a physical process which predicts a parameter and compares it against a measured value. However, digital twins may also provide additional insights by combining and interpreting various sources of information. These insights may be used for preventative maintenance scheduling optimization or early fault detection and are projected to be valuable for meeting requirements under 10 CFR 50.55a. However, digital twin technologies are still under significant development; quantifying model uncertainties, improving unique fault identification, and multimodal sensor fusion are some areas under investigation. Therefore, in this work, we discuss and review the various enabling technologies, in the form of advanced sensors, instrumentation, and modelling methods, that may be used to implement and enhance digital twins for online condition monitoring. A potential use case for pump-motors is presented to demonstrate how these various pieces of enabling digital twin technologies may integrated together for online condition monitoring. Challenges and opportunities associated with the pump-motor digital twin enabling technologies are also identified and discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Digital Transformation for the Existing Fleet: Where to Start?

To remain economically viable in today’s electricity marketplace, nuclear power plants are replacing old analog equipment with modern digital tools. Having information available in an electronic format allows most work processes to become more efficient by automating simple, time-consuming tasks. However, with thousands of routine work processes performed every day, it can be difficult for the plants to know where to begin. We partnered with a nuclear utility to develop a novel assessment tool that measures seven health indicators for each work process performed, providing a rapid digital status report of the plant. The assessment tool is inexpensive and user-friendly, administered remotely, and automatically customized to each employee. Data from 167 employees representing different perspectives were analyzed to identify optimal candidates for digital initiatives that yield the highest payback for increased process efficiencies. We ranked by a priority index to ensure that processes with a good combination of time savings and digital opportunity were at the top. The focus was on determining a maximum investment to ensure that the cost savings from these initiatives are positive over a specified period. We identified potential cost savings of $2.6m, $1.3m and $1.2m for our top priority processes. By using our novel assessment tool to determine the digital status of the plant’s work processes, they were provided with a starting point for target candidates that would most benefit from a digital initiative. Our analysis helps stakeholders understand the financial impact of digital initiatives and identify maximum investment amounts when seeking technical solutions.

assessment↗

DOE OSTI2024

Digital-Twin-Enabling Technologies for Online Condition Monitoring of Nuclear Power Plant Components

Online condition monitoring is an area of active research that may enable improved scheduling, maintenance, and safety of nuclear power plant components, reducing unnecessary derates while simultaneously improving operational capacity. Digital twins are one avenue to conduct online condition monitoring and are currently being explored by national laboratories and universities alike. Digital twins for online condition monitoring are, in essence, state concurrent models that emulate a physical process which predicts a parameter and compares it against a measured value. However, digital twins may also provide additional insights by combining and interpreting various sources of information. These insights may be used for preventative maintenance scheduling optimization or early fault detection and are projected to be valuable for meeting requirements under 10 CFR 50.55a. However, digital twin technologies are still under significant development; quantifying model uncertainties, improving unique fault identification, and multimodal sensor fusion are some areas under investigation. Therefore, in this work, we discuss and review the various enabling technologies, in the form of advanced sensors, instrumentation, and modelling methods, that may be used to implement and enhance digital twins for online condition monitoring. A potential use case for pump-motors is presented to demonstrate how these various pieces of enabling digital twin technologies may integrated together for online condition monitoring. Challenges and opportunities associated with the pump-motor digital twin enabling technologies are also identified and discussed.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Artificial Intelligence and Digital Engineering as Enablers for System Engineering in the Energy Sector

Systems engineering is of utmost importance for the success of high-cost, high-complexity megaprojects, which are common in the energy sector. However, the traditional document-centric systems engineering approach tends to be labor-intensive and time-consuming, which has inhibited its full adoption despite proven metrics on its return on investment. However, with the modern approach of digital engineering and technological advancements in artificial intelligence (AI) technologies, the barriers to systems engineering adoption can finally be broken. This paper goes through the systems engineering V-model for lifecycle management and assesses the current state of implementation of digital engineering (especially, mod-el-based systems engineering, digital twins, and digital threads) and AI for each step. It was observed that a combination of digital engineering and AI is being used across different industries to accelerate and optimize systems engineering processes such as concept development, requirements management, architecture definition, system development, verification and validation, operations, and maintenance. Specifically in the energy sector, AI-augmented digital engineering has shown initial potential in accelerated development and deployment, performance optimization, anomaly detection, predictive maintenance, and configuration management. However, challenges remain in integrating DE and AI into an end-to-end system lifecycle management ecosystem safely and reliably. Addressing these challenges and continuously developing impactful tools will enable fast, efficient, and high-frequency deployment of power generation capabilities to keep up with the world’s energy demands and build energy security.

42 - ENGINEERING↗