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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.

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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Technical Assistance for Digital Assurance: DistribuTECH Workshop

Idaho National Laboratory, the Department of Energy’s Grid Deployment Office, and other national laboratories are collaborating to ensure the U.S. energy infrastructure is reliable, resilient, and secure. This involves strategically leveraging digital technologies to modernize the grid, enhance its resilience against all hazards and disruptions, and fortify national energy security across a diverse energy portfolio. In this workshop you will learn about Idaho National Lab’s Technical Assistance programs, where organizations will be matched with a national laboratory subject matter expert to focus on their key topical area. The technical assistance offered through this track is designed to be responsive to a rapidly changing regulatory landscape and cutting-edge technologies that enhance grid reliability and efficiency. Users will be guided through a tailored analysis and mitigation program to determine their current security posture and given assistance in evaluating supply chain and protection choices against potential consequences.

Digital assurance↗
DOE OSTI2021

Digital quantum simulation of non-equilibrium quantum many-body systems

Digital quantum simulation uses the capabilities of quantum computers to determine the dynamics of quantum systems, which are beyond the computability of modern classical computers. A notoriously challenging task in this field is the description of non-equilibrium dynamics in quantum many-body systems. In this study, we used the IBM quantum computers to simulate the non-equilibrium dynamics of few spin and fermionic systems. Our results reveal that with a combination of error mitigation, noise extrapolation and optimized initial state preparation, one can tackle the most important drawbacks of modern quantum devices. The systems we simulate demonstrate the potential for large-scale quantum simulations of light–matter interactions in the near future.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Interlaboratory Study of Digital Volume Correlation Error Due to X-Ray Computed Tomography Equipment and Scan Parameters: an Update from the DVC Challenge

Background: The quality of Digital Volume Correlation (DVC) full-field displacement measurements depends directly on the characteristics of the X-ray Computed Tomography (XCT) equipment, and scan procedures used to acquire the tomographic images. Objective: In this work, we seek to experimentally study the effects of XCT equipment and tomographic scan procedures on the quality of these images for DVC analysis, and to survey the level of DVC error that may be achieved using standard XCT operating procedures. Methods: Six participants in an interlaboratory study acquired high-quality XCT scans of a syntactic foam before and after rigid body motion. The resulting images were correlated using commercial DVC software to quantify error sources due to random image noise, reconstruction artifacts, as well as systematic spatial or temporal distortion. Results: In the absence of rigid body motion, the standard deviation of the displacement measurements ranged from 0.012 to 0.043 voxels using a moderate subvolume size, indicating that subvoxel measurement resolution could readily be achieved with a variety of XCT equipment and scan recipes. Comparison of consecutive scans without rigid body motion showed transient dilatational displacement gradients due to self-heating of the X-ray source and/or thermal expansion of the foam. Evaluation of the scans after rigid body motion showed significant, machine-specific spatial distortion in the displacement fields of up to 0.5 voxels; new approaches to remove this error need to be developed. Conclusions: Analysis of the scan protocols used in the interlaboratory study, as well as a complementary parametric sensitivity study, showed that the DVC error was strongly influenced by the XCT equipment, but could be mitigated by adjusting the total scan duration.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Digital Image Correlation as an Experimental Modal Analysis Capability

Digital image correlation (DIC) is an established test technique in several fields including quasi-static displacement measurements. Recently there has been growing interest in using DIC to measure structural dynamic response and even extract modal parameters from that information. Although high-speed cameras have become more ubiquitous, there are no commercial end-to-end packages for modal analysis based on image data, particularly when combined with traditional data acquisition systems. As such, the practitioner is left to develop several key data processing capabilities, hardware interface equipment, and testing practices themselves. This work highlights several practical aspects that have been encountered while establishing DIC as a viable modal testing capability in a laboratory environment.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

High-Speed X-Ray Stereo Digital Image Correlation in a Shock Tube

X-ray stereo digital image correlation (DIC) measurements were performed at 10 kHz on the internal surface of a jointed structure in a shock tube at a shock Mach number of 1.42 and compared with optical stereo DIC measurements on the outer, visible surface of the structure. The shock tube environment introduces temperature and density gradients in the gas through which the structure was imaged, resulting in spatial and temporal index of refraction variations. These variations cause bias errors in optical DIC measurements due to beam-steering but have minimal influence on x-ray DIC measurements. These results demonstrate the utility of time-resolved x-ray DIC measurements in complicated environments where optical measurements suffer severe errors and/or are precluded by lack of optical access.

42 ENGINEERING↗
DOE OSTI2024

Path-Integrated X-Ray Digital Image Correlation using Synthetic Reference Images

X-rays can provide images when an object is visibly obstructed, allowing for motion measurements via x-ray digital image correlation (DIC). However, x-ray images are path-integrated and contain data for all objects between the source and detector. If multiple objects are present in the x-ray path, conventional DIC algorithms may fail to correlate the x-ray images. A new DIC algorithm called path-integrated (PI)-DIC addresses this issue by reformulating the matching criterion for DIC to account for multiple, independently-moving objects. PI-DIC requires a set of reference x-ray images of each independent object. However, due to experimental constraints, such reference images might not be obtainable from the experiment. Here, this work focuses on the reliability of synthetically-generated reference images, in such cases. A simplified exemplar is used for demonstration purposes, consisting of two aluminum plates with tantalum x-ray DIC patterns undergoing independent rigid translations. Synthetic reference images based on the “as-designed” DIC patterns were generated. However, PI-DIC with the synthetic images suffered some biases due to manufacturing defects of the patterns. A systematic study of seven identified defect types found that an incorrect feature diameter was the most influential defect. Synthetic images were re-generated with the corrected feature diameter, and PI-DIC errors were improved by a factor of 3-4. Final biases ranged from 0.00-0.04 px, and standard uncertainties ranged from 0.06-0.11 px. In conclusion, PI-DIC accurately measured the independent displacement of two plates from a single series of path-integrated x-ray images using synthetically-generated reference images, and the methods and conclusions derived here can be extended to more generalized cases involving stereo PI-DIC for arbitrary specimen geometry and motion. This work thus extends the application space of x-ray imaging for full-field DIC measurements of multiple surfaces or objects in extreme environments where optical DIC is not possible.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Measuring thermomechanical response of large-format printed polymer composite structures via digital image correlation

Large-format additive manufacturing (LFAM) is a branch of additive manufacturing (AM) research with the ability to create large structures typically measuring several meters in scale. LFAM is advantageous for tooling applications, not only because it offers the ability to create complex geometries not easily made using subtractive manufacturing processes, but the cost savings of pelletized feedstock used by these systems result in larger parts printed at faster speeds than traditional AM systems. Fiber reinforced polymer (FRP) is a commonly used feedstock material in LFAM structures because it reduces the distortion experienced during printing. However, FRP introduces highly anisotropic thermomechanical properties and contributes to a nonhomogeneous microstructure that can result in critical distortion of dimensions during tooling. Measuring the global thermomechanical response of LFAM structures requires a more representative method that accounts for not only anisotropic properties but also the nonhomogeneous nature of the final part. This is where traditional techniques to measure thermomechanical response, such as thermomechanical analysis (TMA), fall short as they assume homogeneity. This study evaluated the coefficient of thermal expansion (CTE) of LFAM structures as measured by TMA as compared to a novel digital image correlation oven (DIC Oven) system. The LFAM structures were made from 20 % by weight carbon fiber reinforced acrylonitrile butadiene styrene (CF-ABS). TMA measurements showed significant variations in CTE across a single LFAM bead, confirming the need for a global technique that captures overall thermomechanical response. The CTE values measured using the DIC Oven compared well to average TMA values obtained from localized measurements across the sample. The DIC Oven was also used to quantify the effects of different layer orientations on thermomechanical properties, which cannot be easily captured using TMA. A predictive model was also developed by using localized TMA values across an LFAM bead to predict the overall thermomechanical response of an LFAM structure.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Digital-twin-based improvements to diagnosis, prognosis, strategy assessment, and discrepancy checking in a nearly autonomous management and control system

We report the Nearly Autonomous Management And Control System (NAMAC) is a comprehensive control system to assist plant operations by furnishing control recommendations to operators in a broad class of situations. This study refines a NAMAC system for making reasonable recommendations during complex loss of flow (LOF) scenarios with a validated EBR-II simulator, digital twins improved by machine-learning algorithms, a multi-attribute decision-making scheme, and a discrepancy checker for identifying unexpected recommendation effects. The performance of each NAMAC component is assessed, while the capability of NAMAC is demonstrated and evaluated in a class of LOF scenarios.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Development and assessment of prognosis digital twin in a NAMAC system

The nearly autonomous management and control (NAMAC) system is a comprehensive control system to assist plant operations by furnishing control recommendations to operators. Prognosis digital twin (DT-P) is a critical component in NAMAC for predicting action effects and supporting NAMAC decision-making during normal and accident scenarios. To quantifying and reducing uncertainty of machine-learning-based DT-Ps in multi-step predictions, this work investigates and derives insights from the application of three techniques for optimizing the performance of DT-P by long short-term memory recurrent neural networks, including manual search, sequential model-based optimization, and physics-guided machine learning. Finally, sequential model-based optimization and physics-guide machine learning result in smallest errors when the predicting transients are similar to the training data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Data coverage assessment on neural network based digital twins for autonomous control system

We report in a recently developed Nearly Autonomous Management and Control (NAMAC) system, neural networks (NNs) are used to develop digital twins for diagnosis (DT-Ds). However, NNs are not usually considered extrapolation models and may result in large errors if they are applied to unseen data outside the training data (uncovered). In this study, we propose a data coverage assessment (DCA) to determine if the NN-based DT-Ds are extrapolated based on their epistemic uncertainty. The uncertainty quantification algorithms and uncertainty thresholds are selected based on the confusion matrix of classifying evaluation data into covered or uncovered data. To demonstrate the adaptability of the proposed framework, we applied it to a basic feedforward neural network and a more advanced recurrent neural network based on a more nonlinear database. Case studies show that the proposed framework can distinguish unseen data for both basic and advanced applications with proper uncertainty quantification algorithms and thresholds.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Autonomous anomaly detection of proliferation in the AGN-201 nuclear reactor digital twin

The expansion of global nuclear power necessitates advanced methods for analyzing proliferation indicators. This study introduces a novel application of the Isolation Forest Machine Learning (IFML) algorithm within a digital twin (DT) of the AGN-201 nuclear reactor to autonomously detect anomalies. Leveraging real-time operational data from the AGN-201 DT, the IFML algorithm identifies outliers without prior data labeling and operates as a lightweight, complementary approach to traditional physics-based anomaly detection methods for nuclear safeguards. In a simulated Red vs. Blue team exercise, the IFML algorithm successfully detected six significant unseen anomalies related to reactivity changes, achieving an accuracy of 99% for identifying operational deviationxs. These anomalies, caused by deliberate perturbations, were detected alongside known physics-based models, underscoring the potential of IFML to enhance real-time monitoring without displacing traditional methods. Further, this study highlights the applicability of IFML in nuclear environments by providing an additional, redundant layer of anomaly detection to improve safeguards and operational safety in complex systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Explainable discrepancy checker and diagnosis for digital Twin-based supervisory control system

By virtually representing a physical object and process, a digital twin (DT) enables optimal autonomous operations by combining classical and novel frameworks in sensors, state predictions, and multi-input/multi-output systems. A DT’s values depend on how well models estimate quantities of interest and on how uncertainty is handled. Moreover, DTs often combine physics-based and data-driven models with mixed fidelities, where classical uncertainty quantification (UQ) struggles with many sources of uncertainty and real-time constraints. Here, this work presents a UQ-based discrepancy checking and diagnosis tool for a DT-based supervisory control system. The tool is developed using metadata from an automated DT development process to learn correlations between sources of uncertainties and outcomes. During operation, it compares predictions with measurements, attributes discrepancies to dominant sources, and recommends parameter and configuration updates. We verify the workflow on a synthetic temperature-control problem and deploy it on a virtual Thermal Energy Delivery System, reducing mismatch and improving control robustness.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Additive manufacturing of mullite ceramic by digital light processing

Mullite material was successfully additively manufactured using digital light processing (DLP). The printed geometry involves a one-step process of pyrolysis, de-binding, and sintering under a plain atmosphere to achieve an average of 76 % ceramic yield and linear shrinkage of 12 %. Furthermore, the thermal profile was carefully controlled to obtain consistent phases in which the XRD shows a mullite phase. Here, in addition, the Weibull analysis was conducted on the sintered flexural specimens, showing a Weibull modulus (m) of 13.05 with a characteristic strength (σ 0 ) of 94.96 MPa. Synchrotron microtomography was performed on the sintered specimens, which showed two distinct porosity distributions (small and large). Large porosity (non-spherical elongated) is the primary cause of decreased material strength, while small porosity (spherical) is the sintering product. The measured thermal conductivity of the specimens was in the range of 2.7–3.1 W/m∙k and decreased with an increase in temperature. Lastly, large-scale prototypes were printed concurrently with a fine resolution of 25 μm without any compromise on the predetermined design and structure.

Additive manufacturing↗
DOE OSTI2021

An innovative digital image correlation technique for in-situ process monitoring of composite structures in large scale additive manufacturing

As additive manufacturing (AM) continues to develop and become a standardized manufacturing method, there will be a continued need to provide in-situ monitoring during the manufacturing of polymer composite printed components. Thermal residual stress is a primary cause of failures such as interlayer disbonds or delamination, micro cracking, and dimensional instability, which can occur during or after the build. Here, we report a novel digital image correlation (DIC) adaptation to monitor thermal residual stresses during the entire print process for large-scale AM. In this work, DIC has been investigated (a) by the natural speckle produced by the polymer surface for correlation, (b) to monitor AM build, and (c) to evaluate the effect of thermal residual stress on warpage of the printed component. The natural speckle pattern of the AM material resulted in a respectable 3.57% error compared to the traditional painted speckle pattern of 3.05% error. DIC measured a 190% increase in vertical displacement at the edge of the wall compared to the center, indicating warpage during AM. This work is a step towards a non-intrusive residual stress measuring technique using DIC for large-scale AM.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Extremized nonlinear and linearized responses in soft metamaterials enabled by gradient-based design and grayscale digital light processing

In this study, we develop a gradient-based design approach that exploits grayscale digital light processing (DLP) 3D printing for extremizing the nonlinear and linearized response of soft metamaterials — materials that harness engineered geometric instabilities to undergo large and programmable changes in configuration. Grayscale DLP approaches modulate local mechanical properties at the pixel scale by tuning the light intensity within a single grayscale image, unlocking an exceptionally large design space. To effectively navigate this space, we develop smooth mappings between local light intensity values and global quantities of interest that characterize the behavior of soft metamaterials. Enabling these smooth mappings are robust and differentiable nonlinear finite element simulations powered by a trust region solver. A PDE-constrained optimization problem is then solved to invert these mappings and produce light intensity distributions that endow the printed part with varying stiffness and flexibility in distinctive regions. It is shown that optimizing the distribution of soft and stiff phases throughout a metamaterial structure results in markedly different buckling and self-contact configurations to drive extremized nonlinear compression and linearized vibration responses. Optimized light intensity distributions are translated to grayscale images and directly used to print soft metamaterial samples, showing remarkable agreement between the buckling and self-contact response in simulated and measured deformed configurations.

Additive manufacturing↗
DOE OSTI2023

Automatic voltage regulation application for PV inverters in low-voltage distribution grids – A digital twin approach

This paper proposes a hierarchical coordinated control strategy for PV inverters to keep voltages in low-voltage (LV) distribution grids within specified limits. The top layer of the proposed architecture consists of the designed automatic voltage regulation (AVR) application, which has access to voltage measurements and grid parameters from the LV distribution grid, both current and historical. The AVR application solves a constrained optimization problem, which provides a set of local control set-points that bring the voltage across the grid within bounds. The middle layer consists of a local Volt/VAR controller, which is adjusted by the AVR app, while the bottom layer is the inner-loop controller of the PV inverter. The proposed method not only improves the voltage quality in the grid but also manages the reactive power outputs of PV inverters efficiently. Further, a digital twin of the cyber-physical system has also been employed that interacts with the control system to ensure its appropriate operation. The effectiveness of the proposed methodology is demonstrated on a representative low-voltage feeder located in Denmark.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Analysis of time-dependent strain heterogeneity in shales using X-ray microscopy and digital volume correlation

In this paper, we report the results of a 4-dimensional (3 spatial dimensions plus time) in-situ creep experiment on a milli-core shale plug from Barnett formation in Texas. An outstanding challenge in shale mechanics is connecting observable characteristics to predictable mechanical and hydraulic behavior. We employ novel imaging and analysis techniques to statistically link sample mineralogy and structure to observed deformation. In particular, we focus on mechanisms of porosity reduction during transient response to step changes in stress, analogous to the aseismic deformation that occurs after an episode of fracturing. Our main goal in this study is to take the first steps to visualize and capture the small-scale deformation mechanisms involved in creep of shales, using imaging techniques. To do so, we conducted a uniaxial creep experiment inside an Xradia Versa 520 micro-CT system for 12 h at room temperature under a constant uniaxial stress of 25 MPa. We employed a Digital Volume Correlation (DVC) method to measure micro-scale deforspmation of the sample by comparing the resulting volumetric images with a high-resolution scan of the sample obtained prior to the creep experiment. The results indicate that the time-dependent deformation in the compliant clay plus kerogen matrix constituents facilitates rigid grain rotation and compaction of intergranular porosity at the boundary between rigid grains and matrix.

58 GEOSCIENCES↗
DOE OSTI2022

Quantifying deformation during Zry-4 burst testing: a comparison of BISON and a combined in-situ digital image correlation and infrared thermography method

The development and verification of nuclear fuel-cladding performance codes require extensive testing to establish empirical correlations, necessitating more accelerated testing methods that can replace large validation studies. Here, in the present work, a technique was developed and implemented to experimentally quantify the relationship between temperature, cladding internal pressure, and strain in-situ during a burst test, with the specific aim of generating data for code validation and model refinement. Digital image correlation was used to measure hoop, axial, and radial strain, and infrared thermography to quantify axial temperature gradients. Several key experimental modifications to traditional LOCA burst testing were necessary, but are shown to effectively have little impact on burst temperatures. The time/temperature dependent pressure and time/spatially dependent thermal gradient data were used with BISON to simulate cladding burst and strain rates. Although the measured DIC strains reach appreciable amounts at slightly lower temperatures than BISON simulated strains, there is good agreement between the measured and simulated strains in terms of magnitude and rates leading up to burst. However, in the few seconds prior to and during burst, the BISON simulated strains are significantly lower than the measured strains, indicating the potential for model improvement. The combined experiment and simulation technique may be applied to any new cladding concept to accelerate fuel qualification.

36 MATERIALS SCIENCE↗