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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Correcting for digital image correlation speckle inversion at high temperature using color cameras

Digital image correlation (DIC) is a popular, noncontacting technique to measure full-field deformation by using cameras to track the motion of an applied surface pattern. Because it is noncontacting, DIC can be performed for extreme temperature applications (e.g., hot-fire rocket testing of carbon composite rocket nozzles) under harsh conditions during which bonded gauges are damaged. Speckle pattern inversion is a phenomenon that sometimes occurs while performing high-temperature DIC. During speckle pattern inversion, portions of the surface pattern that were initially darker at room temperature (e.g., graphite) may emit more light due to blackbody radiation than the portions that were initially paler, thereby producing images in which the pattern appears inverted at high temperature relative to the initial pattern at room temperature. This phenomenon can prevent the correlation algorithm from being able to resolve the displacements between images. This work compares three methods to mitigate speckle pattern inversion: (A) the subtraction method, a recently-published technique in which two high-temperature images are subtracted to remove unwanted light; (B) the filtering method, a popular technique in which optical bandpass filters screen out unwanted light; and (C) the histogram rescaling method, a proposed new method that pairs a color camera with a blue light source and uses information from the green sensor of the camera to correct against inversion in the blue sensor through postprocessing. The histogram rescaling method is shown to successfully eliminate speckle pattern inversion and has the added advantages that it does not require quasi-static loading to be able to compensate for speckle pattern inversion, nor does it impose thick-glass distortions caused by the optical filter.

Rowley, Lindsey J.↗
DOE OSTI2021

In-situ digital image correlation and thermal monitoring in directed energy deposition additive manufacturing

As in welding, directed energy deposition (DED) additive manufacturing (AM) generates complex residual stresses and distortions commensurate with the complexity of the scan pattern used for deposition. To date, measuring DED distortions on complex geometries has only been achieved post process, discarding the complex thermomechanical history that leads to that final material state. In this work, surround stereo digital image correlation (DIC) is used to 3D map surfaces and strain tensors in-situ in a powder-blown laser DED system. Infrared thermography is then projected onto these surfaces to record the full thermomechanical history of printed parts. DIC presents a unique challenge to DED AM, as no part exists at the beginning of deposition, which (a) prevents application of an appropriate speckle pattern and (b) denies the user a zero strain reference frame. Solutions to these problems are proposed and their limitations explored herein. In sum, this work presents a relatively low-cost solution to monitoring and optimizing the unique temporal artifacts induced by complex scan strategies that was previously unobtainable.

42 ENGINEERING↗
DOE OSTI2023

Evaluation of Desiccation Behavior in Basalt Microfiber–Reinforced Bentonite Clay for Geological Repositories of Nuclear Spent Fuel Using Digital Image Correlation

ABSTRACT Secure storage of nuclear spent fuel (NSF) is of great concern for protecting public health and safety. The preferred long-term solution is underground containment in geological repositories, where one or more engineered barrier materials (EBM) encapsulate the NSF and separate it from the natural rock. Bentonite clay is commonly used as an EBM due to its many advantageous properties including low hydraulic conductivity, which ensures limitation of water infiltration to the system and the subsequent risk of corrosion in NSF canisters. However, bentonite clay subjected to heating from nuclear decay may form desiccation cracking. This study conducted disk-shaped free shrinkage tests and ring-shaped restrained shrinkage tests of bentonite clay samples reinforced with basalt microfibers. Digital image correlation was used as a noncontact full-field displacement measurement to track the time-evolving shrinkage and desiccation cracking phenomena and make quantified comparisons between plain bentonite and bentonite with varying contents of basalt microfibers (i.e., 0.0, 0.5, 1.0, and 1.5 % wt.). Results indicate that plain bentonite and basalt microfiber-reinforced samples showed similar free shrinkage behavior, while desiccation cracking behavior was significantly altered by adding basalt microfibers. Microfiber reinforcement effectively reduced major cracks through a “crack-bridging” effect while causing minor cracks to initiate earlier and at higher moisture contents than plain bentonite. Results infer that reinforcing plain bentonite with inorganic microfibers can potentially control desiccation cracking, leading to safer and improved nuclear waste management.

Materials Science↗
DOE OSTI2024

Canopy reflectance spectroscopy, thermal images and digital photographs, San Lorenzo, Panama, 2020

This data package comprises reflectance spectra, thermal and visible images of top of canopy tree crowns at the San Lorenzo Protected Area, Panama. Data were collected using the Smithsonian Tropical Research Institute (STRI) canopy access crane, from positions approximately 4 m above the target tree canopy. Canopy reflectance spectra were collected using an HR-1024i full range spectroradiometer (350–2500 nm, SVC, Poughkeepsie, NY, USA) with a 14-degree lens. Canopy thermal images were captured using an 8640-S series USB Calibrated Thermal Camera (ICI International, Beaumont, TX, USA). Visible images were collected using an AW130 waterproof/shockproof camera (Nikon, Tokyo, Japan). Data were collected on three days, on 16 canopies from 10 tree species. On both January 30, 2020, and February 27, 2020, we collected spectra at three time points, in the morning, midday, and afternoon. On February 18, 2020, we collected data around midday only. Due to technical issues, digital photography was collected on 30 January only. This dataset includes unprocessed data only, including spectral data (.sig or .sed), thermal images (.i16), and photographs (.raw), a detailed method description (.pdf), species information (.csv) and ESS-DIVE file-level metadata (FLMD.csv).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Digital Light Processing (DLP): 3D printing of polymer-based graphene oxide nanocomposites—Efficient antimicrobial material for biomedical devices

Bacterial infections are one of the major causes of surgical implant inefficiency and failure. Herein, we present a Nanocomposite (NC) produced by the addition of Poly(N-vinyl carbazole)-Graphene Oxide dispersion (PVK-GO) as a nanofiller to a commercial photopolymer acrylate resin and 3D printed as coatings via the Digital Light Processing technique. Characterization and bioassay results against Escherichia coli and Staphylococcus aureus confirmed the elevated thermomechanical properties and efficient antibacterial activity of the printed NC-based coatings. In conclusion, the present study demonstrates the fabrication and optimization of a PVK-GO-based NC and its potential utilization as a 3D-printable material for biomedical applications.

2D materials↗
DOE OSTI2025

Unified differentiable digital twin for the IOTA/FAST facility

As the design complexity of modern accelerators grows, there is more interest in using advanced simulations that have fast execution time or produce insights about accelerator state. One notable example of additional information are gradients of physical observables with respect to design parameters produced by differentiable simulations. The IOTA/FAST facility has recently begun a program to implement and experimentally validate a unified start-to-end differentiable digital twin to serve as a virtual accelerator test stand, allowing for rapid prototyping of new software and experiments with minimal beam time costs. In this contribution we will discuss our plans and progress. Specifically, we will cover the selection and benchmarking of both physics and ML codes, the development of generic interfaces between device models and surrogate or physics-based sections, and the export of the parameters through either a deterministic event loop or a fully asynchronous EPICS soft input/output controller. We will also discuss challenges in model calibration and uncertainty quantification, as well as future plans to support larger proton accelerators like PIPII and Booster.

Kuklev, Nikita [Fermilab]↗
DOE OSTI2023

A Comparative Study of Deep Learning Models for Fracture and Pore Space Segmentation in Synthetic Fractured Digital Rocks

This study focuses on the comparative study of deep learning (DL) models for pore space and discrete fracture networks (DFNs) segmentation in synthetic fractured digital rocks, specifically targeting low-permeability rock formations, such as shale and tight sandstones. Accurate characterization of pore space and DFNs is critical for subsequent property analysis and fluid flow modeling. Four DL models, SegNet, U-Net, U-Net-wide, and nested U-Net (i.e., U-Net++), were trained, validated, and tested using synthetic datasets, including input and label image pairs with varying properties. The model performance was assessed regarding pixel-wise metrics, including the F1 score and pixel-wise difference maps. In addition, the physics-based metrics were considered for further analysis, including sample porosity and absolute permeability. Particularly, We first simulated the permeability of porous media containing only pore space and then simulated the permeability of porous media with DFNs added. The difference between these two values is used to quantify the connectivity of segmented DFNs, which is an important parameter for low-permeability rocks. The pixel-wise metrics showed that the nested U-Net model outperformed the rest of the DL models in pore space and DFNs segmentation, with the SegNet model exhibiting the second-best performance. Particularly, nested U-Net enhanced segmentation accuracy for challenging boundary pixels affected by partial volume effects. The U-Net-wide model achieved improved accuracy compared to the U-Net model, which indicated the influence of parameter numbers. Similarly, nested U-Net has the closest match to the ground truth of physics-based metrics, including the porosity of pore space and DFNs, and the permeability difference quantifying the connectivity of DFNs. The findings highlight the effectiveness of DL models, especially the U-Net++ model with nested architecture and redesigned skip connections, in accurately segmenting pore spaces and DFNs, which are crucial for pore-scale fluid flow and transport simulation in low-permeability rocks.

Wang, Hongsheng↗
DOE OSTI2019

FY19 L2 MRT 6744 Milestone Completion: Digital Time-Resolved Spot Diagnostic (D-TRSD)

This milestone report describes development of the Digital Time-Resolved Spot Diagnostic (D-TRSD) into a functioning diagnostic that has been proven in the laboratory. Laboratory tests complete the MRT 6744 exit criteria with the recording and analysis of a spot size measurement for two consecutive pulses on a two-pulse source. Additional channels will be added in the near future to provide an 84-channel measurement capability. The new modular design is more portable than the previous generations and will be much easier to set up at radiographic facilities across the complex.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Mechanical Behavior of D-Shaped Hiperco Specimens under Tension Measured by Digital Image Correlation

Hiperco, manufactured by Carpenter Technology Corporation, is the trademark name for an alloy of equal composition iron and cobalt, with 2 percent vanadium added for enhanced mechanical properties (49Fe-49Co-2V). The alloy is interesting due to its very high magnetic saturation and flux density, yet undesirable mechanical properties such as brittleness and low strength. Several Hiperco specimens cut to a "D”-shaped geometry were placed under tension in a load frame, with a constant strain rate at room temperature, until failure occurred. Digital image correlation was used to obtain strain field data throughout the experiment. The data is to be used to compare with a finite element model, to investigate if Hiperco's unusual behavior can be modeled accurately with chosen model parameters. Between the five specimens tested, high-level results were consistent. Maximum strain and ultimate tensile strength all fell within acceptable bounds. However, several qualitative results differed from specimen to specimen. These differing results include the point of failure, the start point of Liiders band formation, as well as the presence or absence of Liiders bands on the curved section of the "D” specimens.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Analytics-at-scale of Sensor Data for Digital Monitoring in Nuclear Plants: 2nd Annual Report

For economic reasons, the nuclear industry is witnessing premature closure of nuclear power plants, despite excellent safety records. Operations and Maintenance (O&M) activities are some of the largest costs in operating legacy light-water plants. By reducing O&M costs, nuclear energy can become more economically competitive with other energy sources. This can be achieved by leveraging machine-learning and artificial intelligence technologies to develop data-driven algorithms to better diagnose potential faults within the system. Improved accuracy of the models can lead to a reduction in unnecessary maintenance, thus reducing costs associated with parts, labor, and unnecessary planned, forced, or extended outages. To address these challenges, the goal of this project is to perform research and development in the area of digital monitoring, i.e., the application of advanced sensor technologies (particularly wireless sensor technologies) and data science based analytic capabilities, to advance online monitoring and predictive maintenance in nuclear plants and improve plant performance (efficiency gain and economic competitiveness). This report summarizes the fiscal year 2020 research progress encompassing (1) different wireless vibration sensor and data indicators used to assess the health of a plant asset; (2) development of diagnostic models for fault detection; and (3) development of prognostic models for estimating the health of the system up to 7 days ahead.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Development and Implementation of Digital Image Correlation for Out-of-Cell Burst Testing

This report details the progress made towards utilizing in-situ methods to observe and quantify unirradiated Zircaloy-4 (Zr4) fuel cladding deformation during out-of-cell design basis accident conditions, specifically during loss-of-coolant accident (LOCA) burst testing in the Severe Accident Test Station at Oak Ridge National Laboratory. Digital image correlation (DIC) was implemented to calculate cladding strain during burst and infrared (IR) thermography was used to attempt a correlation of strain with temperature and to investigate thermal gradients. For both techniques, early experimentation revealed experimental modifications were necessary for implementation. For DIC, this manifested as shortened cladding lengths which could be centered in front of the viewing chamber bored through the IR furnace side, and for IR thermography this meant conducting burst tests in air without a reaction tube and the incorporation of a SiC shell to eliminate direct IR reflections from the tungsten lamps. In the following, the technical issues and subsequent origin of these modifications are discussed, laying the framework for a proof-of-concept DIC/IR characterization of a burst test in the final section.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Report Summarizing Progress in Digital Image Correlation Analysis of Burst Phenomenon

This report is an update on the progress made towards utilizing in-situ methods to observe and quantify Zry-4 deformation behavior during burst testing. A heavily modified burst test was developed that allows both digital image correlation and infrared thermography to be utilized during testing to quantify strain and axial thermal gradient data during burst. A variety of tests ranging from 6.2-15.9 MPa internal pressure and utilizing both constant and transient pressure conditions were conducted and presently reported on. The test modifications, which are detailed extensively in a previous report, are effectively found to have no discernible impact on burst temperatures when compared to historical Zircaloy burst data. To support future modeling studies, the IR thermography data was used to approximate the thermal gradient down the axial length at burst for all the claddings. Then, DIC is first correlated to thermocouple temperature for a 10.3 MPa Transient pressure test, and then DIC correlated to IR thermal gradient data down the axial length of a 8.2 MPa Transient pressure test at several points.

36 MATERIALS SCIENCE↗
DOE OSTI2022

From print to digital: Preserving over 10,000 McKibbin Cards

Collections management staff from the National Security Research Center (NSRC) recently digitized more than 10,000 McKibbin Cards to make them accessible on the Lab’s unclassified network, said NSRC collections management team leader Patricia Cote (WRS-NSRCMS). The cards, named after Dorothy McKibbin, who was known as the gatekeeper of Los Alamos because she was often the first point of contact for new hires, have become symbolic of the Lab when the world’s greatest minds secretly gathered to create the first atomic bomb and end World War II.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2022

LLNS Request for Variance from 10 CFR 851 for Construction of LLNL Digital Infrastructure Capabilities Expansion Project

Lawrence Livermore National Security, LLC (LLNS) requests variance to 10 CFR 851 (the Rule) for the construction of the Digital Infrastructure Capabilities Expansion (DICE) project. The request isin continued support of the National Nuclear Security Administration (NNSA) “pilot” to streamline the delivery of commercial-like line-item construction projects under $50 million. This pilot is aligned with the approved NA-50 safety approach. Experience gained in the construction of the new Lawrence Livermore National Laboratory (LLNL) Emergency Operations Facility (EOC) under the variance granted in June 2020 is very encouraging. While detailed analysis will be forthcoming after that project is completed, there are strong indicators that a benefit has been realized by the subcontractors executing the work. The variance has permitted local/regional construction businesses contracted to Management & Operation contractor operated facilities and lower tier subcontractors to bid, operate, execute, and comply with safety and health standards they utilize in their business outside of the Department of Energy (DOE) Complex. While compliance to standards that are as safe and healthful as those in 10 CFR 851: confusion, additional cost, and inefficiencies associated with the burden of compliance to an unfamiliar regulatory spectrum has been avoided. Safety and health performance on the EOC construction project including the number of inspection and surveillance issues is comparable to other subcontractors and projects at LLNL executed under 10 CFR 851.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Specifications of EBR-II Neutron Radiography Method Description and Digitization Approach

All neutron radiography (NRAD) images of fuel pins in Argonne’s collection were originally generated using the NRAD imaging facility established in the Hot Fuel Examination Facility (HFEF) at Idaho National Laboratory (INL). The NRAD reactor facility was built in 1977 and has been operating since. The reactor is a TRIGA-type reactor operating at a power level of 250 kWth to provide a neutron source for radiography imaging. The reactor is equipped with two beam tubes (i.e., east beam tube and north beam tube) to guide the neutron beams to two radiography stations. The east radiography station is directly under the HFEF main cell and is dedicated for specimens already in the HFEF hot cell. The north radiography station is outside of the main HFEF hot cell and allows NRAD imaging of non-irradiated items. The NRAD images of EBR-II irradiated metallic fuel pins were taken in the east radiography station. Thermal neutrons have the capability to transmit through most materials and are ideal for NRAD imaging. However, because of their high thermal neutron absorption cross-section, fissile materials (e.g., highly-enriched nuclear fuels) may not be as transmissible to thermal neutrons. This is also the case for oversize specimens with extraneous thickness. Epithermal neutron imaging is therefore used as a complement to thermal neutron NRAD imaging. At HFEF’s NRAD facility, both thermal and epithermal neutrons can be used for NRAD imaging. Irradiated nuclear fuels emit high levels of γ radiation that can easily darken X-ray films, so direct exposure NRAD cannot be used to image them. Instead, an indirect NRAD imaging method was developed at HFEF’s NRAD facility. In this method, foils made of materials that can be activated by neutrons (i.e., with large neutron absorption cross section) are used to collect transmitted neutron signals. Then the activated foils are then placed against X-ray films and enclosed in a vacuum cassette so that the γ decay from the activated foils can produce images on the X-ray films. Then, general X-ray film processing procedures are used to digitize and store the images. By using different foil materials, different energy neutrons can be used for NRAD imaging. At the HFEF NRAD station, two types of films are commonly used: dysprosium (Dy) foils with thickness of 130 microns are used to capture thermal neutron signal, while indium (In) foils with thickness of 130 microns are used to capture epithermal neutron signal. A cadmium or gadolinium foil is put before the indium foil to work as a thermal neutron filter. The thermal and epithermal NRAD images can be taken simultaneously by using a Dy/Cd/In sandwiched foil combination. The typical NRAD exposure time is approximately 20 minutes. Then the exposed foils are transferred to film vacuum cassettes. The vacuum ensures that there is no gap between the foil and the film. The foil-to-film exposure time is at least three half-lives of the corresponding radioisotopes, which are 3 hours for In and 7.5 hours for Dy, respectively. Exposed films are processed using an automatic film processor to produce completed NRAD images.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Deploying Extended Reality (XR) for Digital Operations and Maintenance (O&M) at the Mechanisms Engineering Test Loop (METL)

This report documents the preliminary efforts to digitize operation and maintenance (O&M) activities for the Mechanisms Engineering Test Loop (METL). METL became operational in September 2018 with the mission to provide an ecosystem for Advanced Reactor Development (ARD). METLs flagship facility’s primary purpose is conducting small to intermediate scale tests for Sodium Fast Reactors (SFR). Its resemblance to commercial SFR’s intermediate heat transport system, prototypic operating conditions, and industrial construction practices/materials provides the overarching benefit of establishing a proving ground for emerging operations and maintenance (O&M) activities such as incorporating Extended Reality (XR) applications throughout the program lifecycle.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Digital Signal Processing Using Deep Neural Networks

Currently there is great interest in the utility of deep neural networks (DNNs) for the physical layer of radio frequency (RF) communications. In this manuscript we describe a custom DNN specially designed to solve problems in the RF domain. Our model leverages the mechanisms of feature extraction and attention through the combination of an autoencoder convolutional network with a transformer network, to accomplish several important communications network and digital signals processing (DSP) tasks. We also present a new open dataset and physical data augmentation model that enables training of DNNs that can perform automatic modulation classification, infer, and correct transmission channel effects, and directly demodulate baseband RF signals.

42 ENGINEERING↗