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NASA NTRS2024

Effects of alloying elements on twinning in Ni-based superalloys

Micro-twinning is the major creep deformation mechanism in Ni-based superalloys at temperatures above 700 °C. Recent experiments suggest that superlattice stacking faults in y' phase may serve as the precursors to twin formation. Segregation of alloying elements to these precursors may have a significant effect on formation and extension of micro-twins. Using atomistic modeling we investigate and explain the effects of Nb and Cr alloying additions on these processes. The simulation shows that Nb increases the creep resistance which is mostly associated with impeding the reordering of the high energy double complex stacking fault. Cr, on the other hand, promotes twin growth, degrading the high temperature creep properties. These results can help to understand the effects of elemental composition of the alloy on creep resistance.

Ni-based superalloys↗

NASA NTRSDate not supplied

Effects of Alloying Elements on Twinning in Ni-Based Superalloys

Ni-based superalloys↗

NASA NTRSDate not supplied

NASA Earth System Digital Twins (ESDT) For a Sustainable Future

An Earth System Digital Twin (or ESDT) is an Information System for Understanding, Forecasting, and Conjecturing the complex interconnections among Earth systems, including anthropomorphic forcings and impacts to humanity. More specifically, an Earth System Digital Twin is a dynamic and interactive information system that first provides a digital replica of the past and current states of the Earth or Earth system, as accurately and timely as possible (i.e., the “What Now”); second allows for computing forecasts of future states under nominal assumptions and based on the current replica (i.e., the “What Next”); and third offers the capability to investigate many hypothetical scenarios under varying impact assumptions (i.e., the “What If”). The full power of digital twins is that, through an integrated representation and standardized tools and software technologies, the same digital replica can address the needs of multiple users at various resolutions (spatial and temporal) and for various applications (science, economic, policy, etc.) – “from farmer to scientist”. Since 2020, NASA’s Earth Science Technology’s Intelligent Systems Programs have started defining and investigating ESDTs. After several workshops, more than 15 projects have been funded to develop technologies and components as well as a few prototype ESDT systems. An ESDT architecture framework has been defined, and it is now being used to develop a Coastal Zone Digital Twin (CZ-DT), in coordination with NOAA and CNES. Additional projects have also just been selected to build additional ESDT technologies and prototypes. The details of these Programs will be detailed at the conference.

Earth Science Remote Sensing; Information Systems↗

DOE OSTI2026

Developing a Digital Twin for SRF Cavity Assembly at Fermilab

When assembling Superconducting Radio Frequency (SRF) Cavities, maintaining an environment devoid of particulates like dust and other small particles is essential. If a single spec of dust enters the cavity a significant degradation of performance can occur. To avoid a cavity failure Fermilab assembles the SRF cavities within a ISO-4 (Class 10) environment. This environment though is still susceptible to foreign contaminants when technicians enter and new components are added to the cleanroom. To reduce the risk even more Fermilab has introduced a cobot manipulator into the cleanroom environment to speed up the assembly time which will reduce the time that the technicians operate in the cleanroom. But, this still leaves the potential of contaminants to enter the cleanroom if new components need to be tested within the cleanroom. This project aims to lay the groundwork to develop a Digital Twin environment of the cleanroom to aid in manufacturing processes and testing. In its simplest form, a digital twin is a bidirectional link between a physical system and its digital counterpart or twin. NVIDIA Isaac Sim is used as the digital twin foundation for the digital representation of the cleanroom, specifically for the UR16e assembly area. A simulated UR16e was used to validate the performance of Isaac Sim as a testing environment by comparing the tool center points (TCP) positional data between the simulated and digital representation of the UR16e. Due to a new vision based robotic assembly process being introduced to the cleanroom a digital representation of the physical camera was tested and validated to ensure that it will produce close to the same outcome as the physical environment. The TCP comparison results showed a peak translational error of approximately 0.1mm and rotational errors of up to 8 between the simulated and digital UR16es. While the camera validation performed with high repeatability across multiple runs, it still requires minor tuning before it can accurately replicate a physical camera.

Imburgia, Joseph [Northern Illinois U.]↗

NASA NTRS2003

Evaluation of Treadmill Exercise in a Lower Body Negative Pressure Chamber as a Countermeasure for Weightlessness-Induced Bone Loss: a Bed Rest Study with Identical Twins

Counteracting bone loss is required for future space exploration. We evaluated the ability of treadmill exercise in a LBNP chamber to counteract bone loss in a 30-day bed rest study. Eight pairs of identical twins were randomly assigned to sedentary control or exercise groups. Exercise within LBNP decreased the bone resorption caused by bed rest and may provide a countermeasure for spaceflight. INTRODUCTION: Bone loss is one of the greatest physiological challenges for extended-duration space missions. The ability of exercise to counteract weightlessness-induced bone loss has been studied extensively, but to date, it has proven ineffective. We evaluated the effectiveness of a combination of two countermeasures-treadmill exercise while inside a lower body negative pressure (LBNP) chamber-on bone loss during a 30-day bed rest study. MATERIALS AND METHODS: Eight pairs of identical twins were randomized into sedentary (SED) or exercise/LBNP (EX/LBNP) groups. Blood and urine samples were collected before, several times during, and after the 30-day bed rest period. These samples were analyzed for markers of bone and calcium metabolism. Repeated measures ANOVA was used to determine statistical significance. Because identical twins were used, both time and group were treated as repeated variables. RESULTS: Markers of bone resorption were increased during bed rest in samples from sedentary subjects, including the collagen cross-links and serum and urinary calcium concentrations. For N-telopeptide and deoxypyridinoline, there were significant (p < 0.05) interactions between group (SED versus EX/LBNP) and phase of the study (sample collection point). Pyridinium cross-links were increased above pre-bed rest levels in both groups, but the EX/LBNP group had a smaller increase than the SED group. Markers of bone formation were unchanged by bed rest in both groups. CONCLUSIONS: These data show that this weight-bearing exercise combined with LBNP ameliorates some of the negative effects of simulated weightlessness on bone metabolism. This protocol may pave the way to counteracting bone loss during spaceflight and may provide valuable information about normal and abnormal bone physiology here on Earth.

Twin Study↗

DOE OSTI2026

Cross-domain digital twin architecture for predictive maintenance via machine learning and Large Language Models

This research introduces a comprehensive framework for creating and deploying a digital twin platform for continuous monitoring and predictive maintenance within industrial settings. Through utilizing advanced technologies, including Unreal Engine 5, Unity 3D, the Message Queue Telemetry Transport protocol, Random Forest machine learning algorithms, and Large Language Models (LLMs), we establish a platform that digitally reproduces physical equipment and translates digital controls into real-world actions. This facilitates preventive maintenance approaches and improves operational effectiveness. The digital twin platform gathers sensor data from operational equipment, analyzes it using machine learning, and delivers practical insights to prevent potential malfunctions and enhance equipment performance. Furthermore, the incorporation of a web portal enables efficient monitoring and access to historical data, educational materials, and equipment status information. Preliminary findings indicate that digital twins can transform industrial equipment management and maintenance methodologies.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Regional surrogates for predictive control of digital twins

Digital twins of complex systems must involve a model that is fast, generalizable, and usable for real-time control. For example, high-fidelity nonlinear multiphysics simulations can capture laser-material interactions, but are too slow for optimization or model predictive control (MPC). Reduced-order models, used to accelerate such computation, frequently fail to generalize to unseen inputs or control states. We show theoretically that this failure is intrinsic, i.e., that a learned model is non-unique outside the sampled subspace when its low-rank structure arises from limited excitation and clustered eigenvalues, rather than from a user-imposed truncation alone. Motivated by this result, we propose a control-ready regional surrogate-construction framework for both autonomous and nonautonomous dynamics; it employs Koopman lifting to represent nonlinearities, while preserving spatial locality. We illustrate our approach by constructing a control-ready surrogate for the digital twin of a thermal component of additive-manufacturing process. Our surrogate, localized in space through a von Neumann stencil, is learned from noisy high-fidelity simulations that emulate thermal-camera images collected during the manufacturing. It is linear in thermo-physically augmented states so that MPC reduces to a convex quadratic program. The surrogate requires no online correction, generalizes to unseen scan paths and power profiles of the laser, and is more than three orders of magnitude faster than a finite-difference solver. Furthermore, when the MPC sequence computed on the digital twin is applied to this solver, closed-loop temperature regulation is recovered, showing that the surrogate preserves control-relevant input-output behavior.

Data-driven model↗

DOE OSTI2025

Enhancing traffic safety analysis with digital twin technology: integrating vehicle dynamics and environmental factors into microscopic traffic simulation

Traffic safety is a critical concern in transportation engineering and urban planning. Traditional traffic safety analysis requires trained observers to collect data in the field, which is time-consuming, labor-intensive, and sometimes inaccurate. In recent years, microscopic traffic simulation, which simulates individual vehicles’ movements within a transportation network, have been utilized to study traffic safety. However, microscopic traffic simulation only focuses on traffic-related factors, such as traffic volume, traffic signals, and lane configurations, neglecting vehicle dynamics and environment-related factors like weather and lighting conditions, which can significantly impact traffic safety. In light of this, this paper explores the application of digital twin technology in traffic safety analysis, integrating vehicle simulators, which consider vehicle dynamics and environmental factors, and microscopic traffic simulators, which simulate the operations of traffic flow, for enhanced safety evaluations. Various scenarios, including different weather conditions and visibility levels, are simulated using a digital twin of a road segment in Tuscaloosa, Alabama. The simulations employ Surrogate Safety Measures (SSMs) like Time to Collision (TTC) and Deceleration Rate to Avoid a Crash (DRAC) to assess safety under varying conditions. The results demonstrate that traffic digital twin can identify potential safety issues that traditional microscopic simulation cannot, providing insights for improving traffic control strategies and transportation infrastructure to enhance traffic safety.

Civil engineering↗

DOE OSTI2026

Optimisation of the Kaplan hydropower system via PID 2 and digital twin

Here, this paper proposes a proportional–integral-double–derivative (PID 2 ) optimisation method for the Kaplan hydropower system by building a digital twin. The study first uses one multilayer perceptron (MLP) to model the hydroturbine dynamic and then adopts three connected MLPs to model the generator dynamic, both in an open-loop fashion. Inspired by stochastic distribution control (SDC) theory, we regard the training of the turbine's neural network model as a process control problem, and we propose minimising entropy loss to update the network parameters. The next step is to build the digital twin by connecting the neural network models with a PID 2 controller and a lead-lag exciter and run the whole model in a closed-loop fashion. After that, a binary search approach is applied to optimise the PID 2 parameters based on the obtained digital twin model. The simulation results show that the proposed method can reduce the mean square tracking error by more than 90%. Furthermore, the method is extended to jointly optimise the PID 2 controller and excitation system gains through multiobjective optimisation, leveraging Pareto frontier analysis to balance active power and voltage tracking performance. Simulation results confirm the effectiveness of the proposed method, achieving a 83.46% reduction in relative mean square error of active power, a 47.13% reduction in terminal voltage tracking error, and an 82.78% improvement in the overall scalarized objective.

Hydropower system↗

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 OSTI2025

Development of a Digital Twin for Hydrogen Dispersion and Safety Assessment in an Electrolyzer Based Hydrogen Production Facility

Digital twin models are virtual representations of physical systems that use real-time data to simulate and optimize performance. This study presents the development and initial implementation of a digital twin (DT) for the electrolyzer-based hydrogen production facility at NREL's Advanced Research on Integrated Energy Systems (ARIES), focused on enhancing safety and optimizing sensor placement through physics-based simulations and metadata integration. The DT incorporates detailed facility-specific information, including component layout, leak locations, and controlled release parameters, to model hydrogen dispersion under varying environmental conditions. Using steady-state computational fluid dynamics (CFD) simulations informed by real meteorological data, such as wind speed, direction, and vertical wind profiles, the DT enables visualization of hydrogen plume behavior and spatial concentration distributions. Comparative analysis between high and low wind speed scenarios illustrates the significant influence of wind dynamics on plume shape and extent, with horizontal momentum dominating dispersion at higher speeds, while buoyancy effects become more prominent under low wind conditions. These simulations generate a rich dataset embedded within the DT, allowing users to assess potential leak outcomes and identify optimal sensor locations based on concentration thresholds. The model supports scenario-based analysis to guide safety strategies and equipment deployment for open-area hydrogen infrastructure. The digital twin thus serves as a dynamic platform for virtual prototyping, providing predictive insight into hydrogen behavior and enhancing risk-informed decision-making. This initial phase establishes a validated foundation for future integration of transient, uncontrolled leak scenarios and real-time sensor feedback, positioning the DT as a critical tool for safety design, operational planning, and adaptive monitoring in hydrogen systems. Overall, the approach demonstrates the value of combining environmental data with digital simulations to inform safer and more efficient deployment of hydrogen technologies.

08 HYDROGEN↗

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 NTRS2012

Genesis of Twin Tropical Cyclones as Revealed by a Global Mesoscale Model: The Role of Mixed Rossby Gravity Waves

In this study, it is proposed that twin tropical cyclones (TCs), Kesiny and 01A, in May 2002 formed in association with the scale interactions of three gyres that appeared as a convectively coupled mixed Rossby gravity (ccMRG) wave during an active phase of the Madden-Julian Oscillation (MJO). This is shown by analyzing observational data, including NCEP reanalysis data and METEOSAT 7 IR satellite imagery, and performing numerical simulations using a global mesoscale model. A 10-day control run is initialized at 0000 UTC 1 May 2002 with grid-scale condensation but no sub-grid cumulus parameterizations. The ccMRG wave was identified as encompassing two developing and one non-developing gyres, the first two of which intensified and evolved into the twin TCs. The control run is able to reproduce the evolution of the ccMRG wave and thus the formation of the twin TCs about two and five days in advance as well as their subsequent intensity evolution and movement within an 8-10 day period. Five additional 10-day sensitivity experiments with different model configurations are conducted to help understand the interaction of the three gyres, leading to the formation of the TCs. These experiments suggest the improved lead time in the control run may be attributed to the realistic simulation of the ccMRG wave with the following processes: (1) wave deepening (intensification) associated with a reduction in wavelength and/or the intensification of individual gyres, (2) poleward movement of gyres that may be associated with boundary layer processes, (3) realistic simulation of moist processes at regional scales in association with each of the gyres, and (4) the vertical phasing of low- and mid-level cyclonic circulations associated with a specific gyre.

forecast↗

NASA NTRSDate not supplied

Orion SysML Model, Digital Twin, and Lessons Learned for Artemis I

In 2015 it was recognized by NASA’s Orion Chief Engineer that NASA’s design insight into the Orion subsystems for Artemis I were not sufficient to provide traditional engineering support to flight operations. To address these concerns and provide an opportunity to apply emerging model-based systems engineering and digital twin methodologies and provide opportunities for employees across NASA to get hands-on training, an Orion digital twin pilot project was initiated in 2020. With the increase in complexities of spacecraft, and decreased time to made decisions during missions in critical or emergency situations, digital modeling and integration of design can reduce the time to answer questions by days and required human resources by an order of magnitude over historical approaches and was identified to be critical capability for NASA’s future. This paper describes the genesis of this digital twin pilot project, efforts undertaken, a reproducible methodology to take available system information from a mature program to create an executable SysML model that supports a link to unit-specific data, thus forming a connection to the physical asset, and associated lessons learned and project deliverables.

MBSE↗

NASA NTRS2024

Effects of Alloying Elements on Twinning in Ni-Based Superalloys

Micro-twinning is the major creep deformation mechanism in Ni-based superalloys at temperatures above 700 C. Recent experiments suggest that superlattice stacking faults in   phase may serve as the precursors to twin formation. Segregation of alloying elements to these precursors may have a significant effect on formation and extension of micro-twins. Using atomistic modeling we investigate and explain the effects of Cr and Nb alloying additions on these processes. Our results help to rationalize the experimentally observed puzzling effects of elemental composition of the alloy on creep resistance.

Ni-based superalloys↗

DOE OSTI2026

Development of a Digital Twin for Hydrogen Dispersion and Safety Assessment in an Electrolyzer-Based Hydrogen Production Facility: Preprint

Digital twin models are virtual representations of physical systems that use real-time data to simulate and optimize performance. This study presents the development and initial implementation of a digital twin (DT) for the electrolyzer-based hydrogen production facility at the National Renewable Energy Laboratory (NREL)'s Advanced Research on Integrated Energy Systems (ARIES), focused on enhancing safety and optimizing sensor placement through physics-based simulations and metadata integration. The DT incorporates detailed facility-specific information, including component layout, leak locations, and controlled release parameters, to model hydrogen dispersion under varying environmental conditions. Using steady-state computational fluid dynamics (CFD) simulations informed by real meteorological data, such as wind speed, direction, and vertical wind profiles, the DT enables visualization of hydrogen plume behavior and spatial concentration distributions. Comparative analysis between high and low wind speed scenarios illustrates the significant influence of wind dynamics on plume shape and extent, with horizontal momentum dominating dispersion at higher speeds, while buoyancy effects become more prominent under low wind conditions. These simulations generate a rich dataset embedded within the DT, allowing users to assess potential leak outcomes and identify optimal sensor locations based on concentration thresholds. The model supports scenario-based analysis to guide safety strategies and equipment deployment for open-area hydrogen infrastructure. The digital twin thus serves as a dynamic platform for virtual prototyping, providing predictive insight into hydrogen behavior and enhancing risk-informed decision-making. This initial phase establishes a validated foundation for future integration of transient, uncontrolled leak scenarios and real-time sensor feedback, positioning the DT as a critical tool for safety design, operational planning, and adaptive monitoring in hydrogen systems. Overall, the approach demonstrates the value of combining environmental data with digital simulations to inform safer and more efficient deployment of hydrogen technologies.

08 HYDROGEN↗

DOE OSTI2026

A Physics-Based Digital Twin for Wave Elevation and Seabed Moment Estimation of Offshore Monopiles: Preprint

In this work, we present a proof of concept of a physics-based digital twin for a monopile structure (with overhead inertia) subjected to wave loading. The digital twin is formulated using reduced-order models derived from first principles and combined with a Kalman filter for state estimation. The proposed framework estimates the monopile top motion, the wave elevation, and the section forces and moments along the pile using primarily acceleration measurements at the monopile top. Key innovations include the use of a hydrodynamic shape function to represent distributed wave loading in a compact and computationally efficient manner, and the introduction of a shaping filter to augment the state-space with wave kinematics. Synthetic measurement data are generated using OpenFAST and used as a reference to assess the performance of the digital twin. Results demonstrate that the wave elevation can be accurately reconstructed without direct sea-state measurements as long as the wave regime is inertia-dominated. Under the ideal tested conditions, the total hydrodynamic force and sea-bed bending moment are estimated with relative errors on the order of 1% and correlation coefficients exceeding 96%. Future work will evaluate the estimator's performance under operational uncertainties and more complex loading conditions.

17 WIND ENERGY↗

DOE OSTI2026

Latency Analysis of the Nexus Digital Twin Framework

Real-time digital catalogs are increasingly relied upon to track metadata and connect disparate data sources for cloud-based data integration efforts. One such tool, Deeplynx Nexus is supporting real-time digital twin efforts through event-driven data integration and time-series queries. Nexus’s usefulness for these applications depends critically on how quickly individual records can be uploaded and downloaded, since delays directly affect the responsiveness of any system built on top of it. However, the actual latency a user should expect from Nexus has not been systematically measured before, particularly for the small, frequent transactions typical of live sensor feeds. Here we show that single-record round-trip latency is 61.1 ms on a local Nexus instance and 391.7 ms on the hosted production infrastructure, a roughly 6.4x difference driven primarily by fixed per-request overhead rather than data volume. This overhead dominates at small scale: comparing single-record and ten-record trials suggests approximately 56 ms of each single-record request is fixed connection and authentication cost rather than data-transfer time, meaning batching even a handful of records is substantially more efficient than transmitting them individually. At large batch sizes, this pattern reverses for uploads, which converge to near parity between local and hosted environments by 25,000-50,000 records, while download latency remains persistently 5.7-6.4x slower on hosted infrastructure even at scale. These results suggest that Nexus deployments intended for real-time digital twin applications should prioritize record batching over single-record transactions, and that download-path optimization on hosted infrastructure offers the largest remaining opportunity to reduce latency at scale. We anticipate these baseline measurements will serve as a reference point for future digital twin projects evaluating whether Nexus’s latency profile meets their real-time requirements, and as a benchmark for tracking the effect of future infrastructure or API changes.

99 - GENERAL AND MISCELLANEOUS↗