Results for “digitalization” — Page 23

DOE OSTI2025

A Digital Twin for an Inverter-Based Resource Power Plant: Real-time data streaming unlocks situation awareness

Here, this study presents the development and successful implementation of a digital twin specifically designed for a grid-connected IBR power plant. By integrating a reduced-order model of the IBR system and dynamically updating the grid impedance with real-time data, the digital twin effectively captures and replicates the behavior of the physical system. Its accuracy and reliability are validated through critical test scenarios, including a three-phase fault and a line-tripping event. The results confirm that the digital twin closely emulates its physical counterpart, demonstrating its strong potential for real-time analysis, system monitoring, and predictive decision making in modern power systems.

Digital twins↗

DOE OSTI2024

Digital risk analysis in nuclear engineering projects: Designing for safety, performance, reliability, and security

Cyber-informed engineering and security-by-design frameworks are important in promoting the need to identify cybersecurity concerns early in the systems engineering lifecycle so risks from adversarial cyber-attacks can be eliminated or reduced through engineering design practices. In addition to adversarial risk, risk in operational technology systems also includes non-adversarial and unintentional risk from other factors such as human performance errors, environmental conditions, design flaws, and device degradation or failure. This paper introduces a new concept for characterizing digital risk, both adversarial and non-adversarial, and provides the basis for initial research into a novel digital risk analysis approach focused on incorporating attack difficulty into a multi-attribute analysis technique using robust decision-making. This digital risk characterization is also used to frame a discussion on the challenges of competing objectives and competing stakeholder requirements in an integrated energy system project that incorporates a small modular reactor and industrial facility.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Simulator Data Analysis to Inform Digitalized Environment Impacts on Human Reliability

The U.S. Nuclear Regulatory Commission (NRC) has developed a human reliability analysis (HRA) method, termed the Integrated Human Event Analysis System for Event and Condition Assessment (IDHEAS-ECA), in order to estimate human error probabilities (HEPs) in risk-informed regulatory applications. To update the quantification part of IDHEAS-ECA, the NRC required human performance and error data from fully digitalized main control rooms (MCRs); therefore, it requested that Idaho National Laboratory (INL) revisit previous data collection studies and investigate how the following three factors impact human reliability: self-checking, peer-checking, and automation. The HRA data collection studies revisited were the Human Reliability Data Extraction (HuREX) project, developed by the Korea Atomic Energy Research Institute (KAERI), and the Simplified Human Error Experimental Program (SHEEP), developed by INL. HuREX is a representative HRA data collection study that collects human reliability data from full-scope simulators staffed by licensed operators. SHEEP, on the other hand, has been proposed to complement such full-scope studies by collecting data via simplified simulators staffed by non-licensed student operators. In the HuREX study, KAERI collected HRA data from fully digitalized MCRs for the Advanced Power Reactor (APR)–1400. The SHEEP data were obtained from simplified simulators that partially mimicked the features of digitalized MCRs. The present report mainly discusses how the impacts of the aforementioned three factors on human errors were derived from these two data collection studies.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2024

Digital Twin + AI: Control Room of the Future [Slides]

The control room functions as the central brain of the grid, essential for balancing supply and demand and ensuring moment-to-moment grid reliability. Like the human brain, which processes sensory data to make decisions, control room operators analyze operational data from power generation, transmission, and distribution to make informed decisions. Currently, decision-making primarily rests with operators due to hardware and software limitations. However, with technological advancements, Digital Twins and AI are becoming high interest points in the control room's decision-making pilot programs. NREL is developing a comprehensive decision-making platform that integrates Digital Twins, AI, and advanced visualization techniques. As this integration progresses, the role of Digital Twins will evolve from conducting automated simulations to serving as a Trustworthy AI enabler, offering verification and validation of AI-generated response for power systems or providing physics-aware synthetic data of AI pre-training.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Data Management for Digital Twin Implementation: Enhancing Existing SCADA Architecture for INL's CITRC Test Distribution System

The United States power grid will continue to experience stress from aging infrastructure, extreme weather, and increasing loads. In order to strengthen resiliency, researchers need to run tests and simulations that model real-life infrastructure. Idaho National Laboratory (INL) is creating a digital twin of its Critical Infrastructure Test Range Complex (CITRC). CITRC is an at-scale grid testbed which can be configured in utility-realistic distribution scenarios for a variety of tests, such as advanced grid protection and control. A digital twin of this infrastructure would support in-depth tests/simulations without risking physical consequences, before trialing devices under test at-scale. This project focuses on the data acquisition part of constructing a digital twin. It investigates the Supervisory Data Acquisition and Control (SCADA) system of CITRC and explores ways to utilize this system for the twin. Future “ideal” at-scale implementations such as upgraded equipment, modern communication protocols, and automation applications are also explored.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Unconventional compute methods and future challenges for superconducting digital computing

Superconducting digital computing (SDC) based on Josephson junctions (JJs) offers significant potential for enhancing compute throughput and reducing energy consumption compared to conventional room-temperature CMOS-based approaches. Current superconducting logic families exhibit diverse characteristics in clocking strategies, power management, and information encoding techniques. This paper reviews recent advancements in unconventional computing methods specifically designed for superconducting digital circuits, emphasizing temporal computing and pulse-train representations. Notable techniques include race logic (RL), temporal pulse train computing (U-SFQ), and temporal multipliers, each offering unique performance and area advantages suited to superconducting implementations. Additionally, this paper reviews innovations in superconducting coarse-grain reconfigurable architectures (CGRA), superconducting-specific on-chip communication architectures, cryogenic sensor interfaces, and quantum computing control electronics. Finally, we highlight research challenges that should be addressed to facilitate the widespread adoption of superconducting digital computing.

EDA tools↗

DOE OSTI2024

An Advanced Synchronized Time Digital Grid Twin Testbed for Relay Misoperation Analysis of Electrical Fault Type Detection Algorithms

Distributed energy resources and the number of relays are expected to rise in modern electrical grids; consequently, relay misoperations are also expected to grow. Relays can detect electrical fault types using an internal algorithm and can display the result using light indicators on the front of the relay. However, some relays’ internal algorithms for predicting types of electrical faults could be improved. This study assesses a relay’s external and internal algorithms with an Advanced Synchronized Time Digital Grid Twin (ASTDGT) testbed with paired relays. A misoperation relay analysis focused on measuring the accuracy of using the boundary admittance (the external algorithm) versus the set-default (the internal algorithm) relay method to determine the electrical fault types was performed. In this study, the internal and external relay algorithms were assessed with a synchronized time digital grid twin testbed using a real-time simulator. This testbed evaluated two sets of logic at the same time with the digital grid twin and paired relays in the loop. Different types of electrical faults were simulated, and the relays’ recorded events and electrical fault light indicator states were collected from the human–machine interfaces. This ASTDGT testbed with paired relays successfully evaluated the relay algorithm misoperations. The boundary admittance method had an accuracy of 100% for line-to-line, line-to-ground, and line-to-line ground faults.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2011

Implementation of a Digital Signal Processing Subsystem for a Long Wavelength Array Station

This paper describes the implementation of a Digital Signal Processing (DP) subsystem for a single Long Wavelength Array (LWA) station.12 The LWA is a radio telescope that will consist of many phased array stations. Each LWA station consists of 256 pairs of dipole-like antennas operating over the 10-88 MHz frequency range. The Digital Signal Processing subsystem digitizes up to 260 dual-polarization signals at 196 MHz from the LWA Analog Receiver, adjusts the delay and amplitude of each signal, and forms four independent beams. Coarse delay is implemented using a first-in-first-out buffer and fine delay is implemented using a finite impulse response filter. Amplitude adjustment and polarization corrections are implemented using a 2x2 matrix multiplication

Long Wavelength Array↗

NASA NTRS2009

Scientific Digital Libraries, Interoperability, and Ontologies

Scientific digital libraries serve complex and evolving research communities. Justifications for the development of scientific digital libraries include the desire to preserve science data and the promises of information interconnectedness, correlative science, and system interoperability. Shared ontologies are fundamental to fulfilling these promises. We present a tool framework, some informal principles, and several case studies where shared ontologies are used to guide the implementation of scientific digital libraries. The tool framework, based on an ontology modeling tool, was configured to develop, manage, and keep shared ontologies relevant within changing domains and to promote the interoperability, interconnectedness, and correlation desired by scientists.

Information Model↗

NASA NTRS2017

Robotically Assembled Aerospace Structures: Digital Material Assembly using a Gantry-Type Assembler

This paper evaluates the development of automated assembly techniques for discrete lattice structures using a multi-axis gantry type CNC machine. These lattices are made of discrete components called digital materials. We present the development of a specialized end effector that works in conjunction with the CNC machine to assemble these lattices. With this configuration we are able to place voxels at a rate of 1.5 per minute. The scalability of digital material structures due to the incremental modular assembly is one of its key traits and an important metric of interest. We investigate the build times of a 5x5 beam structure on the scale of 1 meter (325 parts), 10 meters (3,250 parts), and 30 meters (9,750 parts). Utilizing the current configuration with a single end effector, performing serial assembly with a globally fixed feed station at the edge of the build volume, the build time increases according to a scaling law of n4, where n is the build scale. Build times can be reduced significantly by integrating feed systems into the gantry itself, resulting in a scaling law of n3. A completely serial assembly process will encounter time limitations as build scale increases. Automated assembly for digital materials can assemble high performance structures from discrete parts, and techniques such as built in feed systems, parallelization, and optimization of the fastening process will yield much higher throughput.

Mechanical Structure↗

NASA NTRS2017

Characteristic of a Digital Correlation Radiometer Back End with Finite Wordlength

The performance characteristic of a digital correlation radiometer signal processing back end (DBE) is analyzed using a simulator. The particular design studied here corresponds to the airborne Hurricane Imaging radiometer which was jointly developed by the NASA Marshall Space Flight Center, University of Michigan, University of Central Florida and NOAA. Laboratory and flight test data is found to be in accord with the simulation results. Overall design seems to be optimum for the typical input signal dynamic range. It was found that the performance of the digital kurtosis could be improved by lowering the DBE input power level. An unusual scaling between digital correlation channels observed in the instrument data is confirmed to be a DBE characteristic.

digital correlation radiometer↗

NASA NTRSDate not supplied

OSMA Digital Evolution: R&M Physics of Failure (PoF) Handbook

At the intersection of mission, technology, and place is NASA’s need to modernize for a digital-forward future. Therefore, NASA’s Reliability & Maintainability (R&M) Enterprise Data Sharing team is working to leverage both Digitization and Digital Transformation to develop and share best practices and methodologies across NASA. One such cutting edge methodology is Physics of Failure. Therefore NASA OSMA's R&M office is developing a Reliability Physics of Failure Handbook in order to keep our engineers current and on the cutting edge of anlayis methodologies to help ensure NASA’s optimize and achieve continued success.

Digital Transformation↗

NASA NTRSDate not supplied

OSMA Digital Evolution: R&M Physics of Failure (PoF) Handbook

At the intersection of mission, technology, and place is NASA’s need to modernize for a digital-forward future. Therefore, NASA’s Reliability & Maintainability (R&M) Enterprise Data Sharing team is working to leverage both Digitization and Digital Transformation to develop and share best practices and methodologies across NASA. One such cutting edge methodology is Physics of Failure. Therefore NASA OSMA's R&M office is developing a Reliability Physics of Failure Handbook in order to keep our engineers current and on the cutting edge of analysis methodologies to help ensure NASA’s optimize and achieve continued success. "

Digital transformation↗

NASA NTRSDate not supplied

The Measurement of Shear Strain in Impact Ice Using a Modified Lap Joint Test and Digital Image Correlation

The results of ice adhesion testing efforts are typically quantified using the maximum shear stress sustained at the interface before the ice detaches from the underlying substrate. While this singular value can be useful for understanding the role icing wind tunnel conditions and substrate surface properties have on the strength of the ice-substrate interface, it does not capture the mechanical behavior of the ice during an experiment. To better understand the deformation of the ice sample and ice-substrate interface during testing, digital image correlation was applied to the lap-joint shear test methodology utilized at NASA Glenn Research Center. Preparation of the sample surface for digital image correlation, initial parsing of the correlation data, and the time synchronization of data from multiple sources are discussed. Using the directional components of deformation measured via digital image correlation, a novel approach to calculating the interfacial shear strain is presented. Results from analyzing several impact ice samples consistently reveals a non-linear response in the ice during mechanical loading which occurs prior to sample delamination, a behavior not observable in the force and displacement data gathered from the testing apparatus. Both the full and small angle forms of the engineering shear strain are evaluated, with the full shear strain form providing considerably lower noise levels. The transition of sample response from near the interface to the bulk behavior of the ice under shear loading is discussed with results from several samples being presented.

Ice adhesion↗

NASA NTRSDate not supplied

The Measurement of Shear Strain in Impact Ice Using a Modified Lap Joint Test and Digital Image Correlation

The results of ice adhesion testing efforts are typically quantified using the maximum shear stress sustained at the interface before the ice detaches from the underlying substrate. While this singular value can be useful for understanding the role icing wind tunnel conditions and substrate surface properties have on the strength of the ice-substrate interface, it does not capture the mechanical behavior of the ice during an experiment. To better understand the deformation of the ice sample and ice-substrate interface during testing, digital image correlation was applied to the lap-joint shear test methodology utilized at NASA Glenn Research Center. Preparation of the sample surface for digital image correlation, initial parsing of the correlation data, and the time synchronization of data from multiple sources are discussed. Using the directional components of deformation measured via digital image correlation, a novel approach to calculating the interfacial shear strain is presented. Results from analyzing several impact ice samples consistently reveals a non-linear response in the ice during mechanical loading which occurs prior to sample delamination, a behavior not observable in the force and displacement data gathered from the testing apparatus. Both the full and small angle forms of the engineering shear strain are evaluated, with the full shear strain form providing considerably lower noise levels. The transition of sample response from near the interface to the bulk behavior of the ice under shear loading is discussed with results from several samples being presented.

: Ice Adhesion, Digital Image Correlation, Experim↗

NASA NTRS2023

NASA’s Digital Information Platform to Accelerate the Transformation of the National Airspace System

In order to accelerate the digital transformation of airspace operations, a foundational framework and infrastructure for providing sustainable, data-driven, and cohesive decision-making digital services for both traditional and emergent air vehicles is being developed. The reference implementation of Digital Information Platform builds an ecosystem for the aviation community by providing access to a secure and trusted source of aviation data and services. Several key features and services have been implemented to enable secure data sharing, communication, and service registration on the Platform. The technical approach used to implement these features is presented here. NASA-developed integrated aviation data and machine learning based prediction services to optimize airspace operations are available on the Platform. These services are being evaluated in an operational environment by flight operators and the real-world benefits are being captured. The Platform fosters collaboration among industry and researchers to develop complex aviation services and the aim is to make it publicly accessible for consumption by the aviation community.

Digital Transformation↗

NASA NTRSDate not supplied

NASA’s Digital Information Platform to Accelerate the Transformation of the National Airspace System

In order to accelerate the digital transformation of airspace operations, a foundational framework and infrastructure for providing sustainable, data-driven, and cohesive decision-making digital services for both traditional and emergent air vehicles is being developed. The reference implementation of Digital Information Platform builds an ecosystem for the aviation community by providing access to a secure and trusted source of aviation data and services. Several key features and services have been implemented to enable secure data sharing, communication, and service registration on the Platform. The technical approach used to implement these features is presented here. NASA-developed integrated aviation data and machine learning based prediction services to optimize airspace operations are available on the Platform. These services are being evaluated in an operational environment by flight operators and the real-world benefits are being captured. The Platform fosters collaboration among industry and researchers to develop complex aviation services and the aim is to make it publicly accessible for consumption by the aviation community.

Digital Transformation↗

NASA NTRS2023

Harnessing the Digital Transformation for Development of Electrified Aircraft Propulsion Control Systems

Hybrid electric aircraft propulsion is an emerging technology that presents a variety of potential benefits along with technical integration challenges. Developing these new propulsion architectures with their complex control systems, and ultimately proving their benefit, is a multistep process. This process includes concept development and analysis, dynamic simulation, hardware-in-the-loop testing, full-scale testing, and so on. This effort is being revolutionized and indeed enabled by new digital tools that support increasing the technology readiness level throughout the maturation process. As part of this Digital Transformation, NASA has developed a suite of publicly available digital tools that facilitate the path from concept to implementation. This paper describes the NASA-developed tools and puts them in the context of control system development for hybrid electric aircraft propulsion. The three MATLAB®-based software packages are the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS), the Electrical Modeling and Thermal Analysis Toolbox (EMTAT), and the Thermal Systems Analysis Toolbox (TSAT). These tools are interactive, complementary, and compatible with each other. T-MATS is a modular thermodynamic modeling framework designed for creating custom component level models of jet engines. EMTAT is a modeling framework used to simulate a variety of power electronic devices, using both physics-based and power flow calculations. TSAT is a framework for modeling and analysis of dynamic heat transfer. These packages all consist of graphical, drag-and-drop, parameterizable building blocks representing various components of the system to be modeled, e.g., compressors, turbines, motors, energy storage devices, etc. They are designed to enable the user to model and simulate the end-to-end dynamic operation of a hybrid electric gas turbine engine powertrain at the timescale of the turbomachinery, capturing mechanical, electrical, and thermal interactions. This paper demonstrates through multiple examples how these tools have been used successfully in a variety of applications, including several of the early stages of hybrid electric gas turbine engine propulsion system development, from the initial system modeling to real-time interactive pilot-in-the-loop simulation to physical hardware-in-the-loop testing, each step bringing the technology closer to fruition.

hybrid electric propulsion↗