Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Digitalization”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Quantum error thresholds for gauge-redundant digitizations of lattice field theories

In the quantum simulation of lattice gauge theories, gauge symmetry can be either fixed or encoded as a redundancy of the Hilbert space. While gauge-fixing reduces the number of qubits, keeping the gauge redundancy can provide code space to mitigate and correct quantum errors by checking and restoring Gauss’s law. In this work, we consider the correctable errors for generic finite gauge groups and design the quantum circuits to detect and correct them. We calculate the error thresholds below which the gauge-redundant digitization with Gauss’s law error correction has better fidelity than the gauge-fixed digitization involving only gauge-invariant states. Our results provide guidance for fault-tolerant quantum simulations of lattice gauge theories. Published by the American Physical Society 2024

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Digitization and subduction of S U ( N ) gauge theories

The simulation of lattice gauge theories on quantum computers necessitates digitizing gauge fields. One approach involves substituting the continuous gauge group with a discrete subgroup, but the implications of this approximation still need to be clarified. To gain insights, we investigate the subduction of S U ( 2 ) and S U ( 3 ) to discrete crystal-like subgroups. Using classical lattice calculations, we show that subduction offers valuable information based on subduced direct sums, helping us identify additional terms to incorporate into the lattice action that can mitigate the effects of digitization. Furthermore, we compute the static potentials of all irreducible representations of Σ ( 360 × 3 ) at a fixed lattice spacing. Our results reveal a percent-level agreement with the Casimir scaling of S U ( 3 ) for irreducible representations that subduce to a single Σ ( 360 × 3 ) irreducible representation. This provides a diagnostic measure of approximation quality, as some irreducible representations closely match the expected results while others exhibit significant deviations. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Digital Filter Design for Point-on-Wave Sensors: Highlighting Frequency Response Limitations and Enhancing Grid Simulation Accuracy

Data is proving to be the backbone of today's and, more importantly, tomorrow's grid. As the system changes and introduces fast-acting devices like power electronics, overall observability tends to decrease from the utility point-of-view. This can be mitigated by adding more high-fidelity sensors onto the grid, although this incurs a cost. These sensors are never ideal, and each have unique frequency responses that may influence the data produced. This may, in turn, impact the protection and control of the power grid. This paper presents a methodology of representing these point-on-wave sensors digitally by estimating digital-filter representations of them, thereby introducing means of improving the sensor models used in electromagnetic-transient (EMT) simulations. This may help with identifying potential high-frequency, sensor-induced distortions, and system resonance compensation. Three commercial-grade medium-voltage point-on-wave sensors are utilized in a lab environment to obtain experimental frequency responses with a frequency sweep, and it is shown that both Infinite Impulse Response (IIR) and Finite Impulse Response (FIR) filter representations may approximate these responses with varying degrees of accuracy, though each has their own strengths and weaknesses. It is found that, in general, FIR estimation better approximates these sensors than IIR estimation does.

Wilson, Aaron [ORNL] (ORCID:0000000327331697)↗
DOE OSTI2026

Digital Twin Based Condition Monitoring of LCC-LCC Inductive Power Transfer Systems

Inductive power transfer (IPT) systems provide a flexible, hands-free charging opportunity to electric vehicles (EV). The resonant network components and the transmitter and receiver coils are often subjected to high voltages or currents. Component aging in the compensation network and coils of resonant IPT systems is detrimental to the reliability and power transfer efficiency of the IPT system. Monitoring the component health of such multi-element complex systems requires robust optimization algorithms. This paper discusses condition monitoring of a resonant IPT system for an EV charger using a digital twin model. A hybrid estimation algorithm based on genetic algorithms and adaptive particle swarm optimization is developed to estimate the parameters of the digital twin model. Simulation results are used to verify the monitoring capabilities of the developed algorithm under various operating conditions of the IPT system.

Weldehawaryat, Lidya Mussie [graduate research ass↗
DOE OSTI2022

A multi-modal scanning system to digitize CBRNE emergency response scenes

A handheld system developed to digitize a contextual understanding of the scene at a chemical, biological, radiological, nuclear and/or explosives (CBRNE) events is described. The system uses LiDAR and cameras to create a colorized 3D model of the environment, which helps domain experts that are supporting responders in the field. To generate the digitized model, a responder scans any suspicious objects and the surroundings by carrying the system through the scene. The scanning system provides a real-time user interface to inform the user about scanning progress and to indicate any areas that may have been missed either by the LiDAR sensors or the cameras. Currently, the collected data are post-processed on a different device, building a colorized triangular mesh of the encountered scene, with the intention of moving this pipeline to the scanner at a later point. The mesh is sufficiently compressed to be sent over a reduced bandwidth connection to a remote analyst. Furthermore, the system tracks fiducial markers attached to diagnostic equipment that is placed around the suspicious object. The resulting tracking information can be transmitted to remote analysts to further facilitate their supporting efforts. The paper will discuss the system's design, software components, the user interface used for scanning a scene, the necessary procedures for calibration of the sensors, and the processing steps of the resulting data. The discussion will close by evaluating the system's performance on 11 scenes.

Salathe, Marco↗
DOE OSTI2022

A Novel Method for Preoperative Positioning of Total Ankle Replacement Using 3D Digital Model

Abstract Objective To establish a digital model of the ankle joint through 3D imaging technology and explore the preoperative placement of ankle replacement prostheses. Methods Computed tomography images of intact ankle joints from 54 cases in the outpatient and inpatient departments of our hospital were collected; according to the INBONE® total ankle system surgery process, the surgery model and surgical osteotomy were finished using MIMICS based on computer simulation method. The shortest distance was measured between the center point and the anterior, posterior, medial, and lateral, respectively, to ensure the precise position of the ankle replacement prosthesis by digital simulation surgery. The relationship between the two variables was analyzed by bivariate correlation analysis. Results The dataset of this study included 48 cases of the sub‐data set (26 males and 22 females) and included 27 cases of left ankle and 21 cases of right ankle. The average medial malleolar angle was 18.67°± 2.87°, the average amount of bone resection was 12.13 ± 1.86 cm 3 , the mid‐anterior distance was 1.72 ± 0.19 cm, the mid‐posterior distance was 2.00 ± 0.19 cm, the ratio of mid‐anterior to mid‐posterior was 0.87, the mid‐medial distance was 1.26 ± 0.17 cm, the mid‐lateral distance was 1.19 ± 0.16 cm, and the ratio of mid‐medial to mid‐lateral was 1.06. After osteotomy, the anteroposterior diameter was 3.73 ± 0.32 cm, the transverse diameter was 2.46 ± 0.27 cm, and the ratio of anteroposterior diameter to transverse diameter was 1.53. In the bottom view, the shape after osteotomy is rectangular. The mid‐anterior distance was strongly negatively correlated with age, the mid‐anterior distance and the amount of bone resection, the mid‐medial distance and the amount of bone resection, the mid‐lateral distance and the amount of bone resection, the mid‐lateral distance and the anteroposterior diameter, the anteroposterior diameter and the transverse diameter were all strongly positively correlated. Conclusion The projection point of the lower tibia centerline on the tibial horizontal osteotomy surface is located at a position slightly anterior to the midpoint of the transverse diameter after ankle arthroplasty. The rational positioning of the total ankle replacement is located at both a position slightly anterior to the midpoint of the transverse diameter and midpoint of the anteroposterior diameter, which can be used as a reference method before total ankle arthroplasty surgery.

Wu, Shi‐xun↗
DOE OSTI2021

Measurement of Deformation Heterogeneity During Shale Swelling Using Digital Image Correlation

Abstract Rock-fluid interactions in shale formations are one of the main sources of wellbore instability issues and inadequate stimulation performance. For better planning of fracturing operations and optimizing production from these reservoirs, it is important to understand the mechanisms behind these interactions. These issues are especially prevalent in clay-rich shales, such as Tuscaloosa Marine Shale, which is the subject of this study. Conventional techniques to quantify these shale-fluid interactions comprise of measuring swelling in powdered rock grains or measurement of deformation in the whole pieces of the core using a linear variable differential transformer and strain gages. However, the contribution from individual laminae to overall deformation cannot be evaluated using these methods. In this study, we developed an experimental setup to evaluate the spatial deformation in shale during interaction with water using digital image correlation (DIC). Deformation of two shale samples, with 34 wt% to 51 wt% clay content, was studied. White paint was used to generate a random speckle pattern on the specimen and then immersed in deionized water. The deformation process was captured using a digital camera and images were analyzed using DIC to quantify the deformation. The implementation of the DIC technique enables the visualization and quantification of spatial deformation in the specimen during interacting with water. The results show the localization of large strains in select laminations. The results provide a better understanding of shale deformation when interacting with water in comparison to traditional measurements that can provide only an average strain value.

Energy & Fuels↗
DOE OSTI2025

A Digital Twin Framework Utilizing Machine Learning for Robust Predictive Maintenance: Enhancing Tire Health Monitoring

We introduce a novel digital twin (DT) framework for the predictive maintenance of long-term physical systems. Using monitoring tire health as an application, we show how the DT framework can be used to enhance automotive safety and efficiency, and how the technical challenges can be overcome using a three-step approach. First, to manage the data complexity over a long operation span, we employ data reduction techniques to concisely represent physical tires using historical performance and usage data. Relying on these data, for fast real-time prediction, we train a transformer-based model offline on our concise dataset to predict future tire health over time, represented as remaining casing potential (RCP). Based on our architecture, our model quantifies both epistemic and aleatoric uncertainties, providing reliable confidence intervals around predicted RCP. Second, to incorporate real-time data, we update the predictive model in the DT framework, ensuring its accuracy throughout its lifespan with the aid of hybrid modeling and the use of the discrepancy function. Third, to assist decision-making in predictive maintenance, we implement a tire state decision algorithm, which strategically determines the optimal timing for tire replacement based on RCP forecasted by our transformer model. This approach ensures that our DT accurately predicts system health, continually refines its digital representation, and supports predictive maintenance decisions. Furthermore, our framework effectively embodies a physical system, leveraging big data and machine learning (ML) for predictive maintenance, model updates, and decision-making.

advanced computing infrastructure↗
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 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 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 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 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↗