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At least 649 records · Page 36

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DOE OSTI2025

An Internal Digital Image Correlation Technique for High-Strain Rate Dynamic Experiments

Full-field, quantitative visualization techniques, such as digital image correlation (DIC), have unlocked vast opportunities for experimental mechanics. However, DIC has traditionally been a surface measurement technique, and has not been extended to perform measurements on the interior of specimens for dynamic, full-scale laboratory experiments. This limitation restricts the scope of physics which can be investigated through DIC measurements, especially in the context of heterogeneous materials. The focus of this study is to develop a method for performing internal DIC measurements in dynamic experiments. The aim is to demonstrate its feasibility and accuracy across a range of stresses (up to 650 MPa), strain rates (10 3 - 10 6 s -1 ), and high-strain rate loading conditions (e.g., ramped and shock wave loading). Internal DIC is developed based on the concept of applying a speckle pattern at an inner-plane of a transparent specimen. The high-speed imaging configuration is coupled to the traditional dynamic experimental setups, and is focused on the internal speckle pattern. During the experiment, while the sample deforms dynamically, in-plane, two-dimensional deformations are measured via correlation of the internal speckle pattern. In this study, the viability and accuracy of the internal DIC technique is demonstrated for split-Hopkinson (Kolsky) pressure bar (SHPB) and plate impact experiments. The internal DIC experimental technique is successfully demonstrated in both the SHPB and plate impact experiments. In the SHPB setting, the accuracy of the technique is excellent throughout the deformation regime, with measurement noise of approximately 0.2% strain. In the case of plate impact experiments, the technique performs well, with error and measurement noise of 1% strain. The internal DIC technique has been developed and demonstrated to work well for full-scale dynamic high-strain rate and shock laboratory experiments, and the accuracy is quantified. Here, the technique can aid in investigating the physics and mechanics of the dynamic behavior of materials, including local deformation fields around dynamically loaded material heterogeneities.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Characterization of the Martensitic Transformation in NiPtAl Alloy Using Digital Holographic Imaging

Surface reliefs due to phase transformations in a 56.8Ni-5.6Pt-37.6Al at. pct alloy were characterized in situ using digital holographic imaging during thermal cycling from room temperature up to 405 K (132 °C). The 3D images of the surface revealed that the austenite plates formed during heating are exactly the same for each cycle, which is not the case for the martensite plates formed during cooling. The martensite start temperature was found to vary by up to ~ 20 K from one grain to another within the same specimen. The absence of Ni 3 Al γ' precipitates, due to the relatively high Al content, results in the propagation of the martensitic transformation over grains up to a millimeter in size. Bright-field optical imaging showed the formation of large martensite plates in some grains, with cracks perpendicular to these plates, upon cycling. Cracks were also observed at grain boundaries and could be related to the height variations across the grain boundaries.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Identification of Post-necking Tensile Stress–Strain Behavior of Steel Sheet: An Experimental Investigation Using Digital Image Correlation Technique

The stress–strain behavior of sheet metal is commonly evaluated by tensile test. However, the true stress–strain curve is restricted up to uniform elongation of the material. Usually, after the uniform elongation of the material the true stress–strain is obtained by extrapolation. The present work demonstrates a procedure to find out the true tensile stress–strain curve of the steel sheet after necking using digital image correlation (DIC) technique. Hill’s normal anisotropic yield criteria and local strains measured by DIC technique are used to correct the local stress and strain states at the diffuse necked area. The proposed procedure is shown to successfully determine the true tensile stress–strain curve of ferritic and dual-phase steel sheets after necking/uniform elongation.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Digital Waveform Technology and the Next Generation of Mass Spectrometers

Ion traps and guides are integral parts of current commercial mass spectrometers. They are currently operated with sinusoidal waveform technology that has been developed over many years. Recently, digital waveform technology has begun to emerge and promises to supplant its older cousin because it presents new capabilities that result from the ability to instantaneously switch the frequency and duty cycle of the waveforms. This manuscript examines these capabilities and reveals their uses and effects on instrumentation. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2018

Chemical Mass Shifts in a Digital Linear Ion Trap as Analytical Identity of o-, m-, and p-Xylene

Chemical mass shifts between isomeric ions of o-, m-, and p-xylene were measured using a digital linear ion trap, and the directions and values of the shifts were found to be correlated to the collision cross sections of the isomers. Both forward and reverse scans were used and the chemical shifts for each pair of isomers in scans of opposite directions were in opposite signs. Using different voltage settings (namely the voltage dividing ratio-VDR) of the ion trap allows adding high order field components in the quadrupole field and results in larger chemical mass shifts. The differential chemical mass shift which combined the shifts from forward and reverse scans doubled the amount of chemical shift, e.g., 0.077 Th between o- and p-xylene, enough for identification of the type of isomer without using an additional ion mobility spectrometer. The feature of equal and opposite chemical mass shifts also allowed to null out the chemical mass shift by calculating the mean m/z value between the two opposite scans and remove or reduce the mass error caused by chemical mass shift. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2026

A meshing framework for digital twins for extrusion based additive manufacturing

Additive manufacturing (AM) allows for manufacturing of complex three-dimensional geometries not typically realizable with standard manufacturing practices. The internal microstructure of AM components has a significant impact on mechanical, vibrational, and shock properties and permits richer design space when this is controllable. Due to complex interactions of internal geometry of an extrusion-based AM component, it is common practice to assume homogeneous behavior or to perform characterization testing on specific toolpath configurations. To avoid testing or material waste, it is necessary to develop a consistently accurate numerical simulation framework with relevant boundary value problems that can handle the complicated geometry of internal material microstructure present in AM components. Herein, a framework is proposed to directly create computational meshes suitable for finite element analysis (FEA) of the fine-scale features generated from extrusion-based AM tool paths to maintain a strong process–structure–property-performance linkage. This mesh can be manually or automatically analyzed using standard FEA simulations such as quasi-static preloading or modal analysis. The framework allows an in-silico assessment of a target AM geometry where fine-scale features greatly impact quantities of design interest such as in soft elastomeric lattices where toolpath infill can greatly influence the self-contact of a structure in compression, which we use as a motivating exemplar. This approach greatly reduces both time and resource waste present in traditional build and test design cycles for non-intuitive design spaces, and acts as a tool for use in the production of a key component of a digital twin, a mesh suitable for finite element analysis. In conclusion, it also further allows for the exploration of toolpath infill to optimize component properties beyond simple linear properties such as density and stiffness.

Additive manufacturing↗

DOE OSTI2025

Survey-wide asteroid discovery with a high-performance computing enabled non-linear digital tracking framework

Modern astronomical surveys detect asteroids by linking together their appearances across multiple images taken over time. This approach faces limitations in detecting faint asteroids and handling the computational complexity of trajectory linking. Here, we present a novel method that adapts “digital tracking” – traditionally used for short-term linear asteroid motion across images – to work with large-scale synoptic surveys such as the Vera Rubin Observatory Legacy Survey of Space and Time (Rubin/LSST). Our approach combines hundreds of sparse observations of individual asteroids across their non-linear orbital paths to enhance detection sensitivity by several magnitudes. To address the computational challenges of processing massive data sets and dense orbital phase spaces, we developed a specialized high-performance computing architecture. We demonstrate the effectiveness of our method through experiments that take advantage of the extensive computational resources at Lawrence Livermore National Laboratory. This work enables the detection of significantly fainter asteroids in existing and future survey data, potentially increasing the observable asteroid population by orders of magnitude across different orbital families, from near-Earth objects (NEOs) to Kuiper belt objects (KBOs).

Asteroid discovery↗

DOE OSTI2026

Physicochemical properties of digital light processing 3D-Printed alumina and mullite ceramics

Alumina ceramics fabricated using conventional techniques such as uniaxial pressing or injection molding are popular due to their low density, excellent insulation, and mechanical properties. However, these methods often limit the fabrication of complex geometries with high dimensional accuracy due to tooling constraints and limited design freedom. To overcome these limitations, this study employed Digital Light Processing (DLP) additive manufacturing (AM), which enables the production of precise structures. In addition, the optimization of sintering parameters to enhance the densification and performance of alumina and mullite ceramics was investigated, with a specific focus on how varying sintering temperatures and hold times affect part shrinkage, geometric accuracy, and material integrity. Flexural strength of both alumina and mullite specimens was clearly influenced by the way the layers was stacked. When layers were arranged across the direction of the applied load (Z = 4; XZ), the strength was higher than when they were stacked along the same direction as the load (Z = 3; XY). Weibull analysis based on these results showed high modulus values across all samples, indicating good reliability in the flexural strength measurements. This reliability, combined with the clear influence of sintering parameters, highlights how processing conditions effect the material properties and mechanical performance of parts produced through DLP additive manufacturing. In conclusion, these findings open new avenues for ceramic AM across various applications, enhancing the potential for innovation in fields such as aerospace, biomedical engineering, and energy.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Simulation toolkit for digital material characterization of large image-based microstructures

In this paper, an efficient image-based simulation toolkit for material characterization is presented, which is scalable to work from personal computers to workstations. The effective thermal conductivity, elasticity, and permeability are evaluated employing a computational homogenization framework based on the Finite Element Method (FEM). Two complementary open-source packages are presented: one developed in Python, which can convert digital images into voxel meshes (pyTomoviewer); the other developed in Julia, that can run numerical simulations to compute effective material properties (chpack). Also, a CUDA C version of chpack is provided (chfem_gpu). They were designed to deal with large multi-phase models, so strategies were devised to minimize their memory footprint, while avoiding a high toll on execution time. The voxel-based approach significantly simplifies the FEM meshes and allows efficient matrix-free implementations. In that sense, to handle large linear systems of equations, the element-by-element (EBE) technique is adopted, in conjunction with a low-memory implementation of the Preconditioned Conjugate Gradient (PCG) method. Finally, the code was thoroughly tested on an artificial geometry made of a square array of cylinders, for which analytical solutions exist, as well as on a real micro-tomographic reconstruction of FiberForm TM , a carbon preform commonly used in thermal protection systems.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Digitalization of an experimental electrochemical reactor via the smart manufacturing innovation platform

The exponential increase in data produced over the last two decades has revolutionized the way we collect, store, process, analyze, model, and interpret information to improve profitability. Manufacturing is no exception. How- ever, Smart Manufacturing, the digital practice, organization, workforce, and infrastructure transformation for collection and deployment of data and models at scale and at all levels of manufacturing, is a complex, costly, and labor-intensive journey that is still seeing slow adoption. The Clean Energy Smart Manufacturing Innovation Institute (CESMII), a national Manufacturing USA public-private partnership sponsored by the Department of Energy, is addressing this scaled use of data and modeling in manufacturing. CESMII has focused on how to col- lect and use operating data for numerous applications that improve productivity, precision, and performance of manufacturing operations from factory floor to supply chain using process simulation, predictive analytics, mon- itoring and control, and real-time optimization. Because contextualized data are key, CESMII has developed the Smart Manufacturing Innovation Platform (SMIP) to lower the barriers to the data that are needed to accelerate data-based model building, improve data visualization, and more quickly gain insights. Reusable, standards-based ways of doing data collection, ingestion, and contextualization are particularly important for scaling access and use of data. The SMIP uses a standards-based definition and construct for reusable information models called an SM Profile. When an SM Profile is used in conjunction with the SMIP, the SMIP ensures the availability of contextualized, operational data for model building. The present work demonstrates Smart Manufacturing and the application of the SMIP for building several data-centered models for the operation and control of an ex- perimental electrochemical reactor that reduces carbon dioxide (CO 2 ) gas to valuable liquid and gas chemicals, such as alcohols, olefins, and syngas. We describe how the SMIP plays a central role in more effective model building and we demonstrate how the electochemical reactor can be controlled and optimized for the desired products. Use of the SMIP involves the transmission of real-time sensor measurements to a cloud resource so that the operating data are available to all model building experts. The data collection and transmission process is fully automated to greatly reduce the need for manual manipulation of the data. Data-driven machine learning models are used for advanced real-time state estimation, real-time optimization, and model-based feedback control for the reactor. The application models are implemented as a system to monitor the data flow and control the electrochemical reactor with a single visualization interface. SM Profiles are used to demonstrate reusability of the information models for the reactor and the instrumentation. The application packages, algorithms, and user interfaces developed are cast as Docker images in a library to facilitate reusability of the application models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Characterization of drop aerodynamic fragmentation in the bag and sheet-thinning regimes by crossed-beam, two-view, digital in-line holography

When a spherical liquid drop is subjected to a step change in relative gas velocity, aerodynamic forces lead to drop deformation and possible breakup into a number of secondary fragments. In order to investigate this flow, a digital in-line holography (DIH) diagnostic is proposed which enables rapid quantification of spatial statistics with limited experimental repetition. To overcome the high uncertainty in the depth direction experienced in previous applications of DIH, a crossed-beam, two-view configuration is introduced. With appropriate calibration, this diagnostic is shown to provide accurate quantification of fragment sizes, three-dimensional positions and three-component velocities in a large measurement volume. We apply these capabilities in order to investigate the aerodynamic breakup of drops at two non-dimensional Weber numbers, We, corresponding to the bag (We = 14) and sheet-thinning (We = 55) regimes. Ensemble average results show the evolution of fragment size and velocity statistics during the course of breakup. Our results indicate that mean fragment sizes increase throughout the course of breakup. For the bag breakup case, the evolution of a multi-mode fragment size probability density is observed. This is attributed to separate fragmentation mechanisms for the bag and rim structures. In contrast, for the sheet-thinning case, the fragment size probability density shows only one distinct peak indicating a single fragmentation mechanism. Compared to previous related investigations of this flow, many orders of magnitude more fragments are measured per condition, resulting in a significant improvement in data fidelity. For this reason, this experimental dataset is likely to provide new opportunities for detailed validation of analytic and computational models of this flow.

42 ENGINEERING↗

DOE OSTI2022

Influence of cementation on the yield surface of rocks numerically determined from digital microstructures

Digital Rock Physics has reached a level of maturity on the characterisation of primary properties that depend on the microstructure – such as porosity, permeability or elastic moduli – by numerically solving field equations on μCT scan images of rock. After small deformations or at depth though, most rocks eventually reach their limit of elasticity and the complementary plastic properties are needed to describe the full mechanical behaviour. Currently, determination of a rock’s yield surface from its microstructure is often restricted to semi-analytical criteria derived by limit analysis or numerical simulations performed on idealised geometries. Such simplification lacks representativeness, particularly for processes that affect directly the pore-grain interface such as the cementation phenomenon, happening during diagenesis. Eventually, only direct numerical simulation of elasto-plasticity performed on digitalised microstructures can be used to assess the strength of different cemented materials and its evolution with the alteration of the microstructure. In this study, we provide a comprehensive parametric study on the impact of cementation on rock strength for real microstructures of cemented granular materials. Compared to most previous studies, the whole yield surface is determined numerically (using Finite Element Method) in order to assess the influence of cementation for different stress-paths. The previously known tendency of rock to strengthen with increasing cementation volume is verified. New results on the influence of cement property namely Young’s modulus, friction and cohesion on the rock’s yield surface are explored. The envelopes obtained are compared to the ones obtained by experimental data and existing models. Finally, the framework presented in this study showcases the wider possibility of determining any rock’s or porous material’s yield surface from its microstructure.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Characterization of mechanical properties and deformation behavior of highly irradiated 316L stainless steel from target modules at the Spallation Neutron Source using digital image correlation analysis

Tensile specimens with irradiation doses ranging from approximately 0.7 to 7.6 displacements per atom (dpa) were fabricated from 316L samples removed from Spallation Neutron Source (SNS) target vessels after service. Tensile tests were performed in conjunction with digital image correlation (DIC) characterization, which permitted detailed analysis of the strain distribution and deformation behavior of the specimen gauge sections during testing. The results show, while considerable hardening (500–700 MPa increase in yield strength) occurred in the 316L SNS target material with increasing dose, appreciable ductility (19–23% total elongation) remained in the material after irradiation to 7.6 dpa in the mixed neutron/proton environment of the SNS target region. The DIC data showed the strain distribution and deformation behavior of all irradiated specimens were nonuniform during testing. Strain localization in the form of deformation bands or “hotspots” was observed during testing, and in some specimens, the bands propagated as deformation waves along the gauge section. The “traveling wave” deformation behavior affected the amount of elongation each specimen achieved, and the scatter in the elongation data was attributed to the large variation in deformation behavior observed among different specimens. Bands of localized strain, or deformation bands, oriented at specific angles were observed in two-dimensional plots of the strain distribution in the gauge sections of some specimens. Overall, this paper describes the experimental procedures, results, and deformation behavior of tensile specimens from SNS targets after service and illustrates the value of DIC characterization during tensile testing of irradiated materials.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Dosimetric evaluation of MLC-based dynamic tumor tracking radiotherapy using digital phantom: Desired setup margin for tracking radiotherapy

The purpose of this study is to evaluate the dosimetric impact of the margin on the multileaf collimator-based dynamic tumor tracking plan. Furthermore, an equivalent setup margin (EM) of the tracking plan was determined according to the gated plan. A 4-dimensional extended cardiac-torso was used to create 9 digital phantom datasets of different tumor diameters (TDs) of 1, 3, and 5 cm and motion ranges (MRs) of 1, 2, and 3 cm. For each dataset, respiratory gating (30% to 70% phase) and tumor tracking treatment plans were prepared using 8-field 3-dimensional conformal radiation therapy by 4-dimensional dose calculation. The total lung V20 was calculated to evaluate the dosimetric impact for each case and to estimate the EM with the same impact on lung V20 obtained with the gating plan with a setup margin of 5 mm. The EMs for {TD = 1 cm, MR = 1 cm}, {TD = 1 cm, MR = 2 cm}, and {TD = 1 cm, MR = 3 cm} were estimated as 5.00, 4.16, and 4.24 mm, respectively. The EMs for {TD = 5 cm, MR = 1 cm}, {TD = 5 cm, MR = 2 cm}, and {TD = 5 cm, MR = 3 cm} were estimated as 4.24 mm, 6.35 mm, and 7.49 mm, respectively. This result showed that with a larger MR, the EM was found to be increased. In addition, with a larger TD, the EM became smaller. Our result showing the EMs provided the desired accuracy for multileaf collimator-based dynamic tumor tracking radiotherapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2023

Digital polycrystalline microstructure generation using diffusion probabilistic models

Accurate micromechanical simulation of polycrystalline materials requires a realistic digital representation of the grain scale microstructure. Here, this work demonstrates the use of a generative diffusion probabilistic model for synthesizing single phase polycrystalline realizations. The model performs well and is capable of producing realistic microstructures consisting of not just simple equiaxed structures but also structures exhibiting more complex spatial arrangements. Masked microstructure generation reveals that the model is context aware of morphological descriptors which may be encoded in the latent space. Training on more diverse data sets, with scaled up architectures, may enable development of future models capable of synthesizing even more complex microstructural features.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Design of a Time-to-Digital Converter ASIC and a mini-DAQ system for the Phase-2 upgrade of the ATLAS Monitored Drift Tube detector

We present the second prototype of a time-to-digital (TDC) ASIC for the upgrade of the ATLAS Monitored Drift Tube (MDT) detector for High-Luminosity LHC operations. Compared to the first prototype, triple modular redundancy has been implemented for the configuration and flow control logic. Here, the total power consumption is increased by less than 10 mW while achieving the same time resolution and channel uniformity. A mini-DAQ system has been built to verify the front-end electronics chain with the new prototype together with other ASICs and boards in triggered mode. Cosmic ray tests with a small-diameter MDT chamber indicate that the configuration and data transmission of the readout electronics perform well. It is expected that this prototype design will be used in the final production.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Digital pixel test structures implemented in a 65 nm CMOS process

The ALICE ITS3 (Inner Tracking System 3) upgrade project and the CERN EP R&D on monolithic pixel sensors are investigating the feasibility of the Tower Partners Semiconductor Co. 65 nm process for use in the next generation of vertex detectors. The ITS3 aims to employ wafer-scale Monolithic Active Pixel Sensors thinned down to 20–40 µm and bent to form truly cylindrical half barrels. Among the first critical steps towards the realisation of this detector is to validate the sensor technology through extensive characterisation both in the laboratory and with in-beam measurements. The Digital Pixel Test Structure (DPTS) is one of the prototypes produced in the first sensor submission in this technology and has undergone a systematic measurement campaign whose details are presented in this article. The results confirm the goals of detection efficiency and non-ionising and ionising radiation hardness up to the expected levels for ALICE ITS3 and also demonstrate operation at + 20 °C and a detection efficiency of 99% for a DPTS irradiated with a dose of 10 15 1 MeV n eq cm -2 . Furthermore, spatial, timing and energy resolutions were measured at various settings and irradiation levels.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Automatic recognition system for document digitization in nuclear power plants

With the increasing number of data-driven models in nuclear applications, large volumes of numerical data are required to accurately model and predict the health status of a plant component. However, many historical operation logs that contain useful information are not fully utilized due to the lack of a systematic approach of digitization. To overcome this issue, this study proposes an automatic pipeline for extracting information from handwritten tabular documents collected from nuclear power plants. In our pipeline, we first denoise scanned documents with morphological operations, and then extract relevant parts from individual pages using both traditional computer vision and neural network methods. Handwriting recognition is applied to obtain text and numbers. As the most challenging step is how to crop only relevant information, the main focus of our paper is to detect tables and cells from scanned handwritten documents. Here we evaluate the efficiency and accuracy of our proposed method on handwritten operational reports obtained from a real-world case study. The results demonstrate the high accuracy and practicality of our proposed method.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗