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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A Digital Twin of Scalable Quantum Clouds

Quantum computing has emerged as a transformative technology capable of solving complex problems beyond the limit of classical systems. The rapid development of quantum processors has led to the proliferation of cloud-based quantum computing services offered by platforms such as IBM, Google, and Amazon. These platforms introduce unique challenges in resource allocation, job scheduling, and multi-device orchestration as quantum workloads become increasingly complex. In this work, we present a digital twin of quantum cloud infrastructures: a framework designed to model and simulate the behavior of real quantum cloud systems. Developed in Python using the SimPy discrete-event simulation library, the framework replicates key aspects of quantum cloud environments, including detailed quantum device modeling, job lifecycle management, and job fidelity. It incorporates noise-aware fidelity estimation, making it the first of its kind to simulate superconducting gate-based quantum cloud systems at an administrative level with job fidelity. We present use cases as proof of concept, demonstrating that our quantum cloud simulation framework can act as a digital twin of a quantum cloud and support the modeling and implementation of practical systems.

Luo, Waylon [Kent State University]↗
DOE OSTI2015

Digital Image Correlation Engine v.3.0

DICe is an open source digital image correlation (DIC) tool intended for use as a module in an external application or as a standalone analysis code. It's primary capability is computing full-field displacements and strains from sequences of digital These images are typically of a material sample undergoing a materials characterization experiment, but DICe is also useful for other applications (for example, trajectory tracking). DICe is machine portable (Windows, Linux and Mac) and can be effectively deployed on a high performance computing platform. Capabilities from DICe can be invoked through a library interface, via source code integration of DICe classes or through a graphical user interface.

Turner, Dan↗
DOE OSTI2023

Toward a Smart Metaverse City: Immersive Realism and 3D Visualization of Digital Twin Cities

Metaverse and its related extended reality technologies can enable immersive, realistic, and participatory visualization of 3D data, and their use and the potential within a smart city can be effective for supporting urban research and urban operations management. This book chapter describes a vision for prototyping a “Smart Metaverse City” to combine the unique advantage of the Metaverse technology with the two-way connectivity of a digital twin city application. This synergy aims to create a virtual environment for immersive geovisualization to help researchers and the public understand the complex urban system through science-based and data-driven approaches. This book chapter selectively reviews past technological and paradigm advancements for collecting, analyzing, and visualizing 3D urban big data. Then we present a prototyping Geographic Information System (GIS) framework, together with some relevant data sources and open-source web technologies, to help researchers create a smart Metaverse city. We demonstrate our vision and discuss its application opportunities through a real-world example, a digital twin city developed at the Oak Ridge National Laboratory, to facilitate participatory, smart, and sustainable campus management.

Xu, Haowen↗
DOE OSTI2021

REGULATORY REQUIREMENTS, GUIDANCE, AND REVIEW OF EMBEDDED DIGITAL DEVICES IN SAFETY SYSTEMS

Interest in embedded digital devices (EDDs) for monitoring and providing control of components is increasing in the nuclear power market as more and more users both within and outside the nuclear sector are employing EDDs. EDDs in other industries or countries may be known by the related terms as smart devices, devices of limited functionality, or intelligent devices. EDDs can sometimes perform a safety role when embedded in components such as temperature transmitters, pressure transmitters, voltage regulators, gas analyzers, boiler controllers, relays, and radiation monitors. The introduction of EDDs can affect safety by creating new hazards, vulnerabilities, failure modes, triggering mechanisms, and other potential safety concerns at both the component and system levels. The U.S. Nuclear Regulatory Commission’s (NRC’s) existing regulations and guidance cover the use of EDDs in safety-related and important to safety systems in nuclear power plants (NPPs). In addition to potential future challenges, the nature of EDDs being implemented in similar or identical manners between different plants and industries opens up the potential of leveraging the reviews of other regulators or utilization of industry certifications.Key words: embedded digital device, firmware

Halverson, D. S.↗
DOE OSTI2013

High Temperature Measurements Of Martensitic transformations Using Digital Holography

During thermal cycling of nickel-aluminum-platinum (NiAlPt) and single crystal Fe-15Cr-15Ni alloys, the structural changes associated with the martensite to austenite phase transformation were measured using dual-wavelength digital holography. Real-time in-situ measurements reveal the formation of striations within the NiPtAl alloy at 70 C and the FeCrNi alloy at 520 C. The results demonstrate that digital holography is an effective technique for acquiring non-contact, high precision information of the surface evolution of alloys at high temperatures.

martensite holography high temperature↗
DOE OSTI2015

Integrated digital metamaterials enables ultra-compact optical diodes

We applied nonlinear optimization to design integrated digital metamaterials in silicon for unidirectional energy flow. Two devices, one for each polarization state, were designed, fabricated, and characterized. Both devices offer comparable or higher transmission efficiencies and extinction ratios, are easier to fabricate, exhibit larger bandwidths and are more tolerant to fabrication errors, when compared to alternatives. Furthermore, each device footprint is only 3μm × 3μm, which is the smallest optical diode ever reported. To illustrate the versatility of digital metamaterials, we also designed a polarization-independent optical diode.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Ultraviolet digital holographic microscopy (DHM) of micron-scale particles from shocked Sn ejecta

A cloud of very fast, O (km/s), and very fine, O (µm), particles may be ejected when a strong shock impacts and possibly melts the free surface of a solid metal. To quantify these dynamics, this work develops an ultraviolet, long-working distance, two-pulse Digital Holographic Microscopy (DHM) configuration and is the first to replace film recording with digital sensors for this challenging application. A proposed multi-iteration DHM processing algorithm is demonstrated for automated measures of the sizes, velocities, and three-dimensional positions of non-spherical particles. Ejecta as small as 2 µm diameter are successfully tracked, while uncertainty simulations indicate that particle size distributions are accurately quantified for diameters ≥4 µm. These techniques are demonstrated on three explosively driven experiments. Measured ejecta size and velocity statistics are shown to be consistent with prior film-based recording, while also revealing spatial variations in velocities and 3D positions that have yet to be widely investigated. Having eliminated time-consuming analog film processing, the methodologies proposed here are expected to significantly accelerate future experimental investigation of ejecta physics.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Towards a Stronger Foundation: Digitizing Commercial Buildings with Brick to Enable Portable Advanced Applications

Most large commercial buildings have digital controls for their heating, ventilation, and air-conditioning (HVAC) and lighting systems with the potential to implement advanced control strategies and data analytics. However, advanced control strategies and data analytics are rarely deployed at scale due to non-standard naming conventions and heterogenous building configurations. Semantic metadata standards, like Brick, show promise to proliferate these applications across many buildings, but they have not been widely adopted by industry due to barriers such as perceived risk and unfamiliarity with the technology. This paper describes the workflow we established and evaluated while using it to develop over ten Brick models of existing buildings. Through this process, we observed that digitizing existing commercial buildings is a cost and labor-intensive effort in which understanding the buildings’ data streams is the major bottleneck. Yet, we conclude this investment is worthwhile since various use case applications such as fault detection and diagnostics, thermal comfort analysis, and HVAC control optimization can utilize the same Brick model. The paper also explores the challenges and lessons learned we encountered while creating these data models, such as: 1) difficulties in finding metadata descriptions and relationships for existing buildings; 2) handling missing concepts in the schema needed to model a building; 3) lack of guidance on how to structure the data model or how much detail to include; 4) unfamiliarity with technologies, which makes the learning curve steep for applications developers. Finally, we also describe future directions for semantic metadata research and development to make such transformative technologies more accessible to practitioners.

Roa, Carlos Duarte↗
DOE OSTI2023

Making digital objects FAIR in high energy physics: An implementation for Universal FeynRules Output (UFO) models

Research in the data-intensive discipline of high energy physics (HEP) often relies on domain-specific digital contents. Reproducibility of research relies on proper preservation of these digital objects. This paper reflects on the interpretation of principles of Findability, Accessibility, Interoperability, and Reusability (FAIR) in such context and demonstrates its implementation by describing the development of an end-to-end support infrastructure for preserving and accessing Universal FeynRules Output (UFO) models guided by the FAIR principles. UFO models are custom-made python libraries used by the HEP community for Monte Carlo simulation of collider physics events. Our framework provides simple but robust tools to preserve and access the UFO models and corresponding metadata in accordance with the FAIR principles.

Neubauer, Mark S.↗
DOE OSTI2012

A Detailed Study of FDIRC Prototype with Waveform Digitizing Electronics in Cosmic Ray Telescope Using 3D Tracks

We present a detailed study of a novel Cherenkov imaging detector called the Focusing DIRC (FDIRC) with waveform digitizing electronics. In this test study, the FDIRC prototype has been instrumented with seven Hamamatsu H-8500 MaPMTs. Waveforms from ~450 pixels are digitized with waveform sampling electronics based on the BLAB2 ASIC, operating at a sampling speed of ~2.5 GSa/s. The FDIRC prototype was tested in a large cosmic ray telescope (CRT) providing 3D muon tracks with ~1.5 mrad angular resolution and muon energy of E muon greater than 1.6 GeV. In this study we provide a detailed analysis of the tails in the Cherenkov angle distribution as a function of various variables, compare experimental results with simulation, and identify the major contributions to the tails. We demonstrate that to see the full impact of these tails on the Cherenkov angle resolution, it is crucial to use 3D tracks, and have a full understanding of the role of ambiguities. These issues could not be fully explored in previous FDIRC studies where the beam was perpendicular to the quartz radiator bars. This work is relevant for the final FDIRC prototype of the PID detector at SuperB, which will be tested this year in the CRT setup.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2012

Digital Rock Studies of Tight Porous Media

This technical report summarizes some recently developed approaches to studies of rock properties at a pore scale. Digital rock approach is complementary to laboratory and field studies. It can be especially helpful in situations where experimental data are uncertain, or are difficult or impossible to obtain. Digitized binary images of the pore geometries of natural rocks obtained by different imaging techniques are the input data. Computer-generated models of natural rocks can be used instead of images in a case where microtomography data are unavailable, or the resolution of the tools is insufficient to adequately characterize the features of interest. Simulations of creeping viscous flow in pores produce estimates of Darcy permeability. Maximal Inscribed Spheres calculations estimate two-phase fluid distribution in capillary equilibrium. A combination of both produce relative permeability curves. Computer-generated rock models were employed to study two-phase properties of fractured rocks, or tight sands with slit-like pores, too narrow to be characterized with micro-tomography. Various scenarios can simulate different fluid displacement mechanisms, from piston-like drainage to liquid dropout at the dew point. A finite differences discretization of Stokes equation is developed to simulate flow in the pore space of natural rocks. The numerical schemes are capable to handle both no-slip and slippage flows. An upscaling procedure estimates the permeability by subsampling a large data set. Capillary equilibrium and capillary pressure curves are efficiently estimated with the method of maximal inscribed spheres both an arbitrary contact angle. The algorithms can handle gigobytes of data on a desktop workstation. Customized QuickHull algorithms model natural rocks. Capillary pressure curves evaluated from computer-generated images mimic those obtained for microtomography data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Lessons Learned from Performing a Human Factors Engineering Validation of an Upgraded Digital Control System in a Nuclear Power Plant Control Room

The United States' fleet of nuclear power plants (NPPs) have exceeded their original 40-year licenses and many are seeking license renewals to continue operations into the future. To support continued operation the Department of Energy's (DOE) Light Water Reactor Sustainability Program (LWRS) provides support for utilities to maintain and upgrade their power production capabilities. Control room modernization is one focus area, which aims to modernization the analog control rooms with digital controls and human-system interfaces (HSIs). The Turbine Control System (TCS) is a non-safety related system undergoing modernization efforts at multiple plants and utilities. Considerable human factors research efforts, comprised of expert reviews and operator in the loop studies were performed to develop human factors compliant and usable TCS. This report documents the final phase of the human factors engineering program used to design and validate the new digital TCS. According to the NUREG-0711 review guide, one of the last steps of human factors engineering program prior to implementation is human factors validation. This report details the method, results and conclusions from the human factors validation study of a collaborating utilities TCS slated to be implemented in one of their plants. One control room team consisting of two control room supervisors and two reactor operators participated in the validation. All team members had participated in the BNP TCS training program foregoing the TCS validation. Performance measures included task performance, situation awareness and workload, expert observation of any negative influences of human-system interface features on control room team performance, and interviews with the participating operators. Performance criteria were based on the performance scores and the topics identified by interviews and expert observations. The results showed that the crew using the new TCS clearly could achieve their overall objectives in the test scenarios with sufficient situation awareness. The new TCS compared to the old system provided clear improvements of the control room work regarding shell and chest warming and regarding valve and other system testing. However, a number of Human Engineering Discrepancies (HEDs) were identified. HEDs were prioritized (level 1, 2 or 3) according to potential safety, plant availability, operability or personnel performance consequences. Since no priority 1 HEDs were identified there is no HFE reason not to continue implementation of the TCS. The TCS upgrade is acceptable if the Priority 2 HEDs are resolved and dispositioned in a satisfactory way. Priority 3 HEDs should be noted and considered for future modifications.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Multi-scale experimental study of creep-fatigue failure initiation in a 709 Stainless Steel alloy using high resolution digital image correlation. Final report

This report discusses the efforts made towards the multi-scale study of the creep-fatigue response of stainless steel 709. Multiple experimental techniques, including digital image correlation (DIC) and electron backscatter diffraction (EBSD), were used in assessing the evolution of damage accumulation during fatigue, creep-fatigue, and thermomechanical fatigue of alloy 709. The role of microstructural features, hold times, temperature, and loading profiles were quantified and the interchangeability of temperature and time was investigated. Finally, a thermomechanical fatigue model was shown to predict well the failure of samples with varying loading profiles. Results indicate that strain accumulation in 709 steel happens primarily near grain boundaries (GBs) with the strains around GBs being inversely proportional to their measured residual burgers vector. Furthermore, hot-spots for strain accumulation were shown to be the locations of eventual microcrack nucleation. The introduction of hold times to the periodic loading cycle increases the damage accumulation rate and thus shortens the fatigue life of samples–this was true for both room temperature and high temperature. Thermomechanical cycling was shown to have little effect on the end life of samples, with the damage accumulation rate for in-phase and out-of-phase cycling being similar to isothermal fatigue. The interchangeability of time and temperature was shown to be possible within the studied load, time, and temperature ranges, since deformation mechanisms driving strain accumulation did not change with temperature (up to 650°C). The Neu-Sehitoglu thermomechanical fatigue model, with constants obtained from the literature and in part from our experimental results, was applied to predict failure of isothermal creep-fatigue samples. The main objectives of this work were to:(a) Perform high-resolution digital image correlation measurements (HiDIC) for alloy 709; (b) Quantify and assess damage accumulation at the microstructure under fatigue, TMF, and creep-fatigue conditions of 709; (c) Study of the role of hold times, i.e., adding a creep component, to: Room temperature cycling, High temperature cycling, Failure; (d) Study the mechanisms of thermomechanical fatigue in this alloy; (e) Investigate the existence of a time-temperature interchangeability criterion to aid in accelerated creep-fatigue testing; (f) Establish the validity of a combined creep-fatigue model for life prediction for 709. This report is structured with each subsequent section detailing the efforts, results, and conclusions related to each of the objectives described, mostly in chronological order.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Digital Rock Physics and 3D Printing for Fractured Porous Media

Imaging techniques for the analysis of porous structures have revolutionized our ability to quantitatively characterize geomaterials. Digital representations of rock from CT images and physics modeling based on these pore structures provide the opportunity to further advance our quantitative understanding of fluid flow, geomechanics, and geochemistry, and the emergence of coupled behaviors. Additive manufacturing, commonly known as 3D printing, has revolutionized production of custom parts with complex internal geometries. For the geosciences, recent advances in 3D printing technology may be co-opted to print reproducible porous structures derived from CT-imaging of actual rocks for experimental testing. The use of 3D printed microstructure allows us to surmount typical problems associated with sample-to-sample heterogeneity that plague rock physics testing and to test material response independent from pore-structure variability. Together, imaging, digital rocks and 3D printing potentially enables a new workflow for understanding coupled geophysical processes in a real, but well-defined setting circumventing typical issues associated with reproducibility, enabling full characterization and thus connection of physical phenomena to structure. Here we report on our research exploring the possibilities that these technologies can bring to geosciences for coupled multiscale experimental and numerical analysis using 3D printed fractured rock specimens.

42 ENGINEERING↗
DOE OSTI2020

Comparison of DTRA/NACT Next Generation Digitizer Evaluations

Sandia National Laboratories has tested and evaluated three digitizers, the Affinity, manufactured by Guralp Systems, the Centaur, manufactured by Nanometrics, and the Q330M+, manufactured by Quanterra, a division of Kinemetrics. These digitizers are used to record sensor output for seismic and infrasound monitoring applications. The purpose of this document is to highlight various results and observations collected during comprehensive evaluations conducted on each unit.

42 ENGINEERING↗
DOE OSTI2020

Development of Gamma Background Radiation Digital Twin with Machine Learning Algorithms: Application of Unsupervised Machine Learning to Detection of Anomalies and Nuisances in Gamma Background Radiation Environmental Screening Data

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. The measurement data is a 2D matrix, where one dimension is gamma ray energy, and the other dimension is the number of measurements or total time. In principle, gamma radiation sources can be detected and identified from the measured data by their unique spectral lines. Detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. The objective of this work is to explore unsupervised machine learning (ML) algorithms for development of a digital twin of gamma radiation background, and for detection and identification of weak nuisances and anomalies events in the presence of highly fluctuating background. In one segment of work, we developed a gamma background estimation model using a Longshort term memory (LSTM) network for one-step CPS time series prediction. The LSTM model was validated with two data sets of measurements from two independent NaI detectors positioned on a mobile platform. The data sets contained background radiation only and no orphan isotope sources. The LSTM model was constructed and tested using data from one of the detectors. Performance of the LSTM model was validate through one-step prediction of CPS time series of another NaI detector without re-training. This approach allows to create a digital twin for nuclear background estimation. Using LSTM, it could be possible to detect a source through subtraction of the estimated counts from the measured background. In another segment of work, we investigated detection of gamma emitting sources in the presence of complex background using unsupervised machine learning. Spectral lines of isotopes are difficult to observe in one-second measurements. Averaging over the entire measurement campaign data set reveals spectral lines of most common background isotopes. Spectral lines of orphan sources, which might appear only in a few measurements during the campaign, will be washed out if averaging is performed over the entire measurement data set. The approach we have explored consists of extracting one-second measurements containing weak spectral features through data clustering. Averaging one-second spectra in a cluster should reveal the presence of anomaly sources. We created two ML models using K-means clustering and Neural Network Self-organizing Map (SOM). Performance of these ML models was benchmarked using search data. One data set contained 137 Cs source, and another dataset contained 131 I source.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Robustness and Validation of Model and Digital Twins Deployment

For digital twins (DTs) to become a central fixture in mission critical systems, a better understanding is required of potential modes of failure, quantification of uncertainty, and the ability to explain a model’s behavior. These aspects are particularly important as the performance of a digital twin will evolve during model development and deployment for real-world operations.

97 MATHEMATICS AND COMPUTING↗