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At least 73 records · Page 4

All sources NASA NTRS DOE OSTI

NASA NTRS2010

Simulation and 'TWINS Observations of the 22 July 2009 Storm

TWINS is the first mission to perform stereo imaging of the Earth's ring current. The magnetic storm on 22 July 2009 is the largest storm observed since TWINS began routine stereo imaging in June 2008. On 22 July 2009, the Dst dropped to nearly -80nT at 7:00 and 10:00 UT. During the main phase and at the peak of the storm, TWINS 1 and 2 were near apogee and moving from pre-dawn to post-dawn local time. The energetic neutral atom (ENA) imagers on the 2 spacecraft captured the storm intensification and the formation of the partial ring current. The peak of the ENA emissions was seen in the midnight-to-dawn local-time sector. The development of this storm has been simulated using the Comprehensive Ring Current Model (CRCM) to understand and interpret the observed signatures. We perform CRCM runs with constant and time-varying magnetic field. The model calculations are validated by comparing the simulated ENA and ion flux intensities with TWINS ENA images and in-situ ion data from THEMIS satellites. Simulation with static magnetic field produces a strong shielding electric field that skews the ion drift trajectories toward dawn. The model's corresponding peak ENA emissions are always eastward than those in the observed TWINS images. On the other hand, simulation with a dynamic magnetic field gives better spatial agreements with both ENA and insitu particle data, suggesting that temporal variations of the geomagnetic field exert a significant influence upon global ring current ion dynamics.

Fok, Mei-Ching↗

NASA NTRS2011

Simulation and Twins Observations of the 22 July 2009 Storm

TWINS is the first mission to perform stereo imaging of the Earth's ring current. The magnetic storm on 22 July 2009 was at the time the largest storm observed since TWINS began routine stereo imaging in June 2008. On 22 July 2009, the Dst dropped to nearly .80 nT at 0700 and 1000 UT. During the main phase, and at the peak of the storm, TWINS 1 and 2 were near apogee and moving between predawn and postdawn local time. The energetic neutral atom (ENA) imagers on the two spacecraft captured the storm intensification and the formation of the partial ring current. The peak of the high-altitude ENA emissions was seen in the midnight-to-dawn local time sector. The development of this storm has been simulated using the comprehensive ring current model (CRCM) to understand and interpret the observed signatures. We perform CRCM runs with constant and time-varying magnetic field. The model calculations are validated by comparing the simulated ENA and ion flux intensities with TWINS ENA images and in situ ion data from a THEMIS satellite. Simulation with a static magnetic field produces a strong shielding electric field that skews the ion drift trajectories toward dawn. The model's corresponding peak ENA emissions are always more eastward than those in the observed TWINS images. On the other hand, the simulation with a dynamic magnetic field gives better spatial agreement with both ENA and in situ particle data, suggesting that temporal variations of the geomagnetic field exert a significant influence upon global ring current ion dynamics.

Fok, M.-C.↗

NASA NTRS2014

Coupling Damage-Sensing Particles to the Digitial Twin Concept

The research presented herein is a first step toward integrating two emerging structural health management paradigms: digital twin and sensory materials. Digital twin is an emerging life management and certification paradigm whereby models and simulations consist of as-built vehicle state, as-experienced loads and environments, and other vehicle-specific history to enable high-fidelity modeling of individual aerospace vehicles throughout their service lives. The digital twin concept spans many disciplines, and an extensive study on the full domain is out of the scope of this study. Therefore, as it pertains to the digital twin, this research focused on one major concept: modeling specifically the as-manufactured geometry of a component and its microstructure (to the degree possible). The second aspect of this research was to develop the concept of sensory materials such that they can be employed within the digital twin framework. Sensory materials are shape-memory alloys that undergo an audible phase transformation while experiencing sufficient strain. Upon embedding sensory materials with a structural alloy, this audible transformation helps improve the reliability of crack detection especially at the early stages of crack growth. By combining these two early-stage technologies, an automated approach to evidence-based inspection and maintenance of aerospace vehicles is sought.

Hochhalter, Jacob↗

NASA NTRS2015

The Twins Study: NASA's First Foray into 21st Century Omics Research

The full array of 21st century omics-based research methods should be intelligently employed to reduce the health and performance risks that astronauts will be exposed to during exploration missions beyond low Earth Orbit. In March of 2015, US Astronaut Scott Kelly will launch to the International Space Station for a one year mission while his twin brother, Mark Kelly, a retired US Astronaut, remains on the ground. This situation presents an extremely rare flight opportunity to perform an integrated omics-based demonstration pilot study involving identical twin astronauts. A group of 10 principal investigators has been competitively selected, funded, and teamed together to form the Twins Study. A very broad range of biological function are being examined including the genome, epigenome, transcriptome, proteome, metabolome, gut microbiome, immunological response to vaccinations, indicators of atherosclerosis, physiological fluid shifts, and cognition. The plans for the Twins Study and an overview of initial results will be described as well as the technological and ethical issues raised for such spaceflight studies. An anticipated outcome of the Twins Study is that it will place NASA on a trajectory of using omics-based information to develop precision countermeasures for individual astronauts.

Kundrot, C. E.↗

NASA NTRS2015

Research from the NASA Twins Study and Omics in Support of Mars Missions

The NASA Twins Study, NASA's first foray into integrated omic studies in humans, illustrates how an integrated omics approach can be brought to bear on the challenges to human health and performance on a Mars mission. The NASA Twins Study involves US Astronaut Scott Kelly and his identical twin brother, Mark Kelly, a retired US Astronaut. No other opportunity to study a twin pair for a prolonged period with one subject in space and one on the ground is available for the foreseeable future. A team of 10 principal investigators are conducting the Twins Study, examining a very broad range of biological functions including the genome, epigenome, transcriptome, proteome, metabolome, gut microbiome, immunological response to vaccinations, indicators of atherosclerosis, physiological fluid shifts, and cognition. A novel aspect of the study is the integrated study of molecular, physiological, cognitive, and microbiological properties. Major sample and data collection from both subjects for this study began approximately six months before Scott Kelly's one year mission on the ISS, continue while Scott Kelly is in flight and will conclude approximately six months after his return to Earth. Mark Kelly will remain on Earth during this study, in a lifestyle unconstrained by this study, thereby providing a measure of normal variation in the properties being studied. An overview of initial results and the future plans will be described as well as the technological and ethical issues raised for spaceflight studies involving omics.

Kundrot, C.↗

DOE OSTI2025

A digital twin platform for building performance monitoring and optimization: Performance simulation and case studies

Advancements in sensor technology, data analytics, affordable compute, and communication infrastructure have paved the way for Digital Twin technology in optimizing building operations and controls. This study presents the development of an open and interoperable web-based Digital Twin platform for integrating diverse data streams and facilitating effective user interactions. The platform utilizes modern technologies for the web framework and time-series data management, ensuring scalability and responsiveness. The backend supports seamless integration of diverse data sources and emulators, incorporating data from building sensors and meters, external weather Application Programming Interfaces, and advanced EnergyPlus simulation models of the building and its energy systems including the Distributed Energy Resources that are formulated in Functional Mockup Units. A simulation case study was conducted with FlexLab, a test facility on Lawrence Berkeley National Laboratory campus. The case study includes normal operations, Distributed Energy Resource integration, and power outage scenarios, to illustrate the Digital Twin’s ability to provide critical insights into energy performance and thermal resilience. The results demonstrated the platform’s potential as a decision-support tool for optimizing building energy performance and enhancing resilience against extreme weather events. Future work will focus on deploying the Digital Twin platform to a real building for field validation, extending its capabilities to cover more scenarios such as bidirectional Electric Vehicle interactions, and enhancing user engagement.

EnergyPlus↗

DOE OSTI2026

Effects of interstitial oxygen on ω transformations and twin formation in bcc NbTaTiHf multi-principal element alloy from first-principles

Transformation- and twinning-induced plasticity (TRIP and TWIP) have been reported to contribute to the low-temperature deformation of some body-centered cubic (bcc) multi-principal element alloys (MPEAs) containing large fractions of group IV transition metals. The influence of interstitial solutes on the mechanisms underlying these forms of plasticity, however, remains unclear. Using first-principles calculations, we study the effects of interstitial O atoms on the relative stability of bcc and ω phases and on unstable and twin boundary stacking fault energy profiles in a representative bcc MPEA with high group-IV elemental fraction: NbTaTiHf. We find that O additions generally promote the relaxation of ω configurations back to their parent bcc structure, therefore inhibiting ω transformation. Calculations of the Rice parameter for bulk bcc and phases, as well as bcc-ω interfaces, further show that ω formation is a potent embrittlement factor, an effect that is enhanced by O additions, suggesting that the formation of bcc-ω interfaces is energetically preferred over the formation of the bulk ω phase. By contrast, the Rice parameter for twin boundaries indicates that these interfaces do not embrittle the material, even with O atoms at twin boundaries, providing a more favorable pathway for plastic deformation compared to ω transformation.

Density functional theory↗

DOE OSTI2026

Deep learning–based digital twins for heat pumps

Heat pumps are effective cooling and heating appliances to save energy in buildings. However, traditional heat pump models are challenging to integrate with building demands in a co-simulation environment because of the nonlinear thermodynamics of refrigerants. Developing digital twin representatives for heat pumps capable of faster calculations with good accuracy is desirable. This study aimed to establish a generic deep learning–based digital twin for heat pumps with a large amount of high-fidelity data. Two refrigerants for two different heat pumps were considered: an air source heat pump with refrigerant R-410A, an air source heat pump with refrigerant CO 2 , a water source heat pump with refrigerant R-410A, and a water source heat pump with refrigerant CO 2 . Furthermore, results showed that the deep learning (long short-term memory) models effectively represented these four heat pumps as a digital twin: (a) accuracy for training and testing showed smaller than 0.02 for heating electricity and heating demands, and (b) the digital twins showed good consistency with original data for heating electricity and heating demands (root mean square errors of less than 0.12 W and 0.19 W, respectively). Therefore, deep learning–based heat pump models can be used in the co-simulation of building mechanical systems.

Air source heat pump↗

DOE OSTI2024

Digital Twins for Data Centers

Fueled by an unprecedented adoption of AI (Artificial Intelligence), data centers are becoming the largest growing consumers of energy. Digital Twins provide living digital models of physical systems that enable data-driven analysis and application of AI to better manage selective aspects of the data center and drive efficiency for sustainability. Digital twins have emerged as a way to create virtual prototypes of physical artifacts, which may be used in a variety of contexts. Physical artifacts include airplanes, factories, or even static objects, such as bridges or dams. Digital twin helps monitor changes and assist in predicting planned or unplanned behaviors of physical objects. In this paper, we discuss digital twins for data centers.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Immersive Digital Twin Laboratory for Engineering Education (CRADA Final Report)

This project aimed to create an immersive digital twin laboratory that incorporates advanced tracking and visualization capabilities. In collaboration with Fort Lewis College, NREL designed a state-of-the-art physical visualization laboratory, developed a software platform to enable interaction with tracked physical objects in the laboratory, and provided proof-of-concept curricula that included manipulating these tracked objects. The project was initiated to address the growing need for innovative educational tools in engineering education. As renewable energy systems, particularly solar installations, become more complex, there is a pressing need to bridge the gap between theoretical knowledge and practical application. Traditional methods of teaching solar engineering concepts often fall short of providing students with a comprehensive, hands-on understanding. This immersive digital twin laboratory was conceived to fill that gap by creating a safe, non-energized setting where students can interact with augmented solar installation objects, gaining valuable insights into system performance, design, and maintenance. The project utilized extended reality (XR) technologies, including head-mounted displays (HMDs) and a whole-room optical motion tracking system, to connect physical objects with their digital twins in real time. The laboratory was equipped with MagicLeap 2 HMDs, supported by a Vicon Vero 2.2 Optical Tracking System, which provided precise 6-degrees-of-freedom (6-DOF) tracking. We developed a software platform to manage the interaction between the tracked physical objects and their virtual counterparts, enabling real-time data synchronization, object recognition, and virtual overlays. We designed the system to be flexible and extendable, allowing for future integration of additional objects and curriculum. This research advances the field of engineering education by demonstrating the potential of immersive digital twin environments. The laboratory provides a dynamic learning space where students can experiment, collaborate, and learn without the risks associated with live experimentation. The ability to simulate and manipulate solar installation objects under various conditions has broad implications for workforce development, particularly in renewable energy. The project also highlights the economic feasibility of using XR technologies in educational settings, offering a cost-effective solution for institutions looking to enhance their curriculum. By fostering a deeper understanding of solar energy systems, this work contributes to the broader goal of supporting the global energy transition and preparing the next generation of engineers and technicians.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

High Fidelity Digital Twins for BWRX-300 Critical Systems

This project developed and demonstrated digital-twin technology for advanced nuclear systems under the ARPA-E GEMINA program, with a focus on the BWRX-300 small modular reactor. The primary objective was to reduce operation and maintenance (O&M) costs through predictive health monitoring and model-based fault detection. The project combined MIT’s high-fidelity physics models and machine-learning and digital-twin algorithms, and GE Hitachi’s digital-twin algorithms and operational expertise to build physics-based digital twins capable of real-time system monitoring and maintenance scheduling.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

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↗

NASA NTRSDate not supplied

Digital Twins and Living Models at NASA

The idea of a “digital twin” was born at NASA in the 1960s as a “living model” of the Apollo mission. In response to Apollo 13’s oxygen tank explosion and subsequent damage to the main engine, NASA employed multiple simulators to evaluate the failure and extended a physical model of the vehicle to include digital components. This “digital twin” was the first of its kind, allowing for a continuous ingestion of data to model the events leading to up to the accident for forensic analysis and exploration of next steps. Fast forward half a century and NASA, along with others in the aerospace community, continues to develop and utilize high-fidelity digital models of physical systems and components as well as the extreme environments in which they operate. NASA aims to travel further and stay longer in space as we realize the Artemis program, taking us from the moon to Mars by establishing a sustainable presence on the Moon to prepare for missions to Mars. We will no longer be able to rely on constant connectivity with an asset nor be in-the-loop for on-demand human intervention in the event of an anomaly. Further, the importance of digital twins is increasing as we seek alternatives for certification of structures so large that they cannot be fully evaluated in existing test facilities and autonomous systems that are not deterministic. The idea of a digital twin is not a new one. What is new is the scale, ordinality, and non-deterministic nature of the models that are critical to achieving NASA’s goals. Their number and autonomy from each other as well as the reference system is suggestive of a changing ecosystem, returning us the idea of a living model.

Digital Twin↗

NASA NTRS2020

The NASA Twins Study: The Effect of One Year in Space on Long-Chain Fatty Acid Desaturases and Elongases

Background: To date, there is no clear understanding of the effect of long-duration spaceflight on the major enzymes that govern the metabolism of omega-6 and omega-3 fatty acids. To address this gap in knowledge, we used data from the NASA Twins Study, which includes a multi-scale omic investigation of the changes that occurred during a year-long (340 days) human spaceflight. Embedded within the NASA Twins data are specific analytes associated with fatty acid metabolism. Objectives: To examine the long-chain fatty acid desaturases and elongases in a single human during one year in space. Method: One male twin was on board the International Space Station (ISS) for one year, while his monozygotic twin served as a genetically matched ground control. Longitudinal assessments included the genome, epigenome, transcriptome, proteome, metabolome, microbiome, and immunome during the mission, as well as six months before and after. The gene-specific fatty acid desaturase and elongase transcriptome data (FADS1, FADS2, ELOVL2 and ELOVL5) were extracted from untargeted RNA-seq measurements derived from white blood cell fractions. Results: Most data from the elongases and desaturases exhibited relatively similar expression profiles (R2>0.6) over time for the CD8, CD19, and LD cell fractions, indicating overall conservation of function within and between the subjects. Both cell-type and temporal specificity was observed in some cases, and some differences were also apparent between the poly-adenylated fraction (polyA) of processed RNAs vs. the ribo-depleted (ribo-) fraction. The flight subject showed a stronger enrichment of the Fatty Acid Metabolic processes pathway across almost all cell types (columns, CD4, CD8, CPT, LD), most especially in the ribodepleted fraction of RNA, but also with the polyA+ fraction of RNA. GSEA enrichment measures across three related Fatty Acid Metabolism pathways showed a differential between the ground and flight subject. Conclusions: There appears to be no persistent alteration of desaturase and elongase gene expression associated with one year in space. However, these data provide evidence that cellular lipid metabolism can be responsive and dynamic to spaceflight, even though it appears cell-type- and context-specific, most notably in terms of the fraction of RNA measured and the collection protocols. These results also provide new evidence of mid-flight spikes in expression of selected genes, which may indicate transient responses to specific insults during spaceflight.

Elongase↗

NASA NTRS2024

Effect of Cr 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 indicate that formation and extension of micro-twins is reliant on the segregation of gamma phase formers (e.g., Co and Cr) along the twin interface in gamma prime phase. In this study we use molecular dynamics simulation to investigate the effect of site preference of Cr in Ni 3 Al gamma prime phase on deformation twinning. We demonstrate that, depending on the site preference (Cr on Ni sites, or Cr on Al sites), two drastically different deformation behaviors can be expected.

Ni-based superalloys↗

NASA NTRSDate not supplied

Effect of Cr Twinning in Ni-Based Superalloys

Ni-based superalloys↗

NASA NTRSDate not supplied

Development of a Digital Twin for Electrified Aircraft Powertrain Health Management

The augmentation of aircraft powertrains with electrical power systems is a promising path to reducing aircraft fuel consumption, emissions, and noise. Like conventional propulsion systems, electrified aircraft propulsion (EAP) systems will be subject to wear and tear throughout their lifecycles. System health management for EAP will enable efficient flight and maintenance scheduling, realizing economic, safety, and reliability benefits. A digital twin is, broadly, a dynamically updated virtual representation of an individual physical asset. This paper presents a Kalman filter-based approach for the development of a digital twin for an electrified powertrain and applies the approach to an EAP controls testbed. Measurements from nominal testbed operations are used to update a nonlinear model of the testbed. A Kalman filter is then created and used to identify and isolate anomalous testbed behavior based on measurements from off- nominal operations. Results show that the Kalman filter-based digital twin can monitor individual powertrain components’ health for degradation or other changes in performance. The applicability of the presented digital twin approach to any hybrid- or fully-electrified powertrain is emphasized.

Electrified Aircraft Propulsion↗

NASA NTRSDate not supplied

Enabling Interoperability in Earth System Digital Twins (ESDT): Integrating Observations, Models, and AI for Actionable Insights Through NASA'S Intelligent Systems Technology Program

NASA’s Intelligent Systems Technology Program (IST) is driving a paradigm shift in Earth science through the development of Earth System Digital Twins (ESDT). These integrated information systems create a dynamic "digital replica" of the Earth by harmonizing continuous, multi-source observations with high-fidelity models and state-of-the-art artificial intelligence (AI) that enable “What now?”, “What next?”, and “What if?” scenario building. These scenarios are reflected in NASA IST’s series of ESDTs, from the Coastal Zone Digital Twin that integrates complex data on the current state of the Chesapeake Bay to the Terrestrial Environmental Rapid-Replication and Assimilation Hydrometeorological (TerraHydro) AI-based ESDT that forecasts water movement across Earth’s surface, to the Agriculture Land Information System (AgLIS) which can be used to assess optimal planting dates and crop yield estimates. By bridging the gap between vast data archives and actionable insights, these projects enable a system-of-systems approach to understanding complex, interacting Earth processes. This poster will highlight recent innovations and future directions from NASA’s ESDT initiatives: Continuous Data Assimilation & Multi-Source Fusion. A core requirement of the ESDT work is the transition from static models to dynamic "living" replicas. This involves creating frameworks for the continual assimilation of near-real-time data from uncoordinated, heterogeneous sources, including satellite observations and airborne assets, and ground-based Internet of Things (IoT) sensors. These systems link design, operational status, and environmental data, ensuring the digital twin accurately reflects the current state of the physical Earth system. High-Fidelity Hybrid Modeling & Computational Acceleration to enable interactive "what-if" explorations, programs are moving beyond traditional, slow physical solvers by developing fast surrogate machine learning models and Deep Generative Models (DGMs). These hybrid approaches use neural networks to emulate complex physics, such as cloud feedback or ocean dynamics, at a fraction of the original computing cost, often leveraging advanced hardware like Graphics Processing Units (GPUs) to achieve the necessary scale. Federated Ecosystems & Interoperable Frameworks rather than building isolated tools, NASA IST is moving toward federated ESDTs and reusable analytic collaborative frameworks. This theme focuses on interoperability standards and common ontologies that allow specialized digital twins to interact and share data. This system-of-systems architecture supports multi-discipline investigations, such as analyzing how upstream watershed changes impact downstream urban flooding or how wildfire emissions affect regional air quality. By leveraging these advancements, ESDTs empower researchers and decision-makers to conduct real-time analysis and run complex hypothetical scenarios, ultimately improving our understanding of Earth’s evolving systems and informing critical real-world applications.

Earth System↗