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DOE OSTI2023

Toward accurate prediction of partial-penetration laser weld performance informed by three-dimensional characterization – Part II: μCT based finite element simulations

The mechanical behavior of partial-penetration laser welds exhibits significant variability in engineering quantities such as strength and apparent ductility. Understanding the root cause of this variability is important when using such welds in engineering designs. In Part II of this work, we develop finite element simulations with geometry derived from micro-computed tomography (μCT) scans of partial-penetration 304L stainless steel laser welds that were analyzed in Part I. We use these models to study the effects of the welds’ small-scale geometry, including porosity and weld depth variability, on the structural performance metrics of weld ductility and strength under quasi-static tensile loading. We show that this small-scale geometry is the primary cause of the observed variability for these mechanical response quantities. Additionally, we explore the sensitivity of model results to the conversion of the μCT data to discretized model geometry using different segmentation algorithms, and to the effect of small-scale geometry simplifications for pore shape and weld root texture. The modeling approach outlined and results of this work may be applicable to other material systems with small-scale geometric features and defects, such as additively manufactured materials.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Nondestructive neutron imaging diagnosis of acidic gas reduction catalyst after 400-Hour operation in natural gas furnace

Residential natural gas furnaces are the primary space-heating devices in US homes, leading to substantial environmental impact caused by the acidic components in the furnace combustion gases. Here, to experimentally demonstrate acidic gas reduction in a furnace, a monolithic catalyst was fabricated and was called the AGR. A commercially-available condensing furnace was retrofitted with the AGR, and a 400-hour reliability and durability test was conducted. The results showed that the AGR significantly reduced acidic gases in the flue gas and produced condensate with neutral pH. Challenges were also revealed: inappropriate condensate drainage caused incomplete combustion and amorphous carbon deposits. To nondestructively survey the internal state of the AGR, neutron computed tomography (NCT) was employed to produce spatially resolved 2D and 3D representations of the 2-L, aged AGR component. The NCT results confirm the integrity of the AGR component, which consists of two blocks, without deformation or damage to AGR channels. The distribution of the particle accumulation in the middle of the top block was visibly heavier than the entrance and exit of the top block. The representative cross-section views revealed significant aggregation in the central region but not at the rim. The spatially resolved details provide in-depth diagnosis, evaluation, and understanding of the AGR. The insights can enable new AGR designs that realize a uniform and self-cleaning flow pattern, alleviate significant particle aggregation, and thus enhance AGR-enabled furnace performance. The neutron imaging method demonstrates the good potential that can diagnose faults and improve the design, optimization, and production processes of novel catalysts and other components or systems with heavy metal shell.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

AnisONet: A deep neural operator-based anisotropic permeability upscaler from pore to Darcy scale

Directional permeability variations, which govern directional fluid flow in porous media with anisotropy, are important to accurately predict flow behavior, reactive transport, and fluid–solid interactions for various processes such as enhanced geothermal systems, energy storage devices, and biological systems. However, the intricate architecture of porous media makes it difficult to predict directional permeabilities. In this work, we present a novel machine learning (ML) framework, AnisONet, built upon an integration of a convolutional neural network, Swin transformer, and the deep operator network architecture, designed to predict anisotropic permeability and upscale predictions to larger spatial domains. First, AnisONet was evaluated with three classes of two-dimensional (2D) porous media, including synthetic circular and elliptical grains and natural sandstone grains from micro-computed tomography images. A lattice Boltzmann model (LBM) was used to calculate directional permeabilities at every 10° angle, producing 19 data points per image of porous media. AnisONet is then trained to predict permeability as a function of rotation angle. AnisONet showed strong predictive capability of directional permeability. Second, we tested our model for five upscaling cases with a large image size in the finite-element method (FEM) for 2D Darcy flow with various permeability tensor construction methods. Overall, upscaled permeability tensors in FEM simulations produce a reasonably good match with LBM results, highlighting the importance of selecting appropriate tensor formation strategies for accurate permeability upscaling. AnisONet, as a directional permeability estimator, could be further developed for more complex geometries, with the potential to develop a foundational ML model for various applications in porous media.

42 ENGINEERING↗

DOE OSTI2021

Algorithm-Driven Advances for Scientific CT Instruments: From model-based to deep learning-based approaches

Multiscale 3D characterization is widely used by materials scientists to further their understanding of the relationships between microscopic structure and macroscopic function. Scientific computed tomography (SCT) instruments are one of the most popular choices for 3D nondestructive characterization of materials at length scales ranging from the angstrom scale to the micron scale. These instruments typically have a source of radiation (such as electrons, X-rays, or neutrons) that interacts with the sample to be studied and a detector assembly to capture the result of this interaction (see Figure 1 ). A collection of such high-resolution measurements is made by reorienting the sample, which is mounted on a specially designed stage/holder after which reconstruction algorithms are used to produce the final 3D volume of interest. The specific choice of which instrument to use depends on the desired resolution and properties of the materials being imaged. Additionally, the end goal of SCT scans includes determining the morphology, chemical composition, or dynamic behavior of materials when subjected to external stimuli. In summary, SCT instruments are powerful tools that enable 3D characterization across multiple length scales and play a critical role in furthering the understanding of the structure–function relationships of different materials.

42 ENGINEERING↗

DOE OSTI2024

Reinforcement induced microcracking during the conversion of polymer-derived ceramics

This study investigates the role of discontinuous reinforcement on the microcracking of a preceramic polymer matrix during polymer to ceramic conversion. The material system comprised a carbosilane-based, preceramic polymer reinforced with mullite particles. The preceramic resin slurry was formulated for photopolymerization on a digital light projection 3D printer. Micro X-ray computed tomography, using a synchrotron light source, monitored a printed composite part during pyrolysis. The conversion of the carbosilane matrix into Si(O)C generated microcracks in the matrix that radially extended from particles. The likelihood of microcrack formation positively correlated with particle size. The largest particles (>10 4 µm 3 volume or >60 µm side length) always abutted microcracks, while the matrix surrounding smaller particles (<5 µm) was free of microcracks. Numerical calculations showed the particles resist the shrinking matrix during its conversion. This created tensile stresses within the matrix. The driving force for microcrack growth was also analyzed with regard to the influence of matrix material parameters, particle form-factor and crack length. These results reveal the need to consider the form factor of discontinuous reinforcements, with regard to the material properties of the polymer-derived ceramic, in order to reduce or eliminate defects in the final part.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Off-spec fly ash-based lightweight aggregate properties and their influence on the fresh, mechanical, and hydration properties of lightweight concrete: A comparative study

An off-spec fly ash-based spherical lightweight aggregate (LWA), designated as Spherical Porous Reactive Aggregate (SPoRA), was manufactured through a lab pilot-scale production and its engineering properties, including specific gravity, dry rodded unit weight, water absorption, mechanical performance, and pore structure, were evaluated. Using SPoRA, lightweight concrete (LWC) samples were made and their fresh, mechanical, and hydration properties were assessed and compared with LWC samples made using two commercial LWA available in the US market. The results indicated that fine and coarse SPoRA had 72 h water absorption capacities of 16.4 % and 20.9 %, respectively, which were higher than that of the two commercial LWAs. Higher saturated surface dry specific gravity of SPoRA compared to commercial LWAs led to a higher fresh density for the corresponding LWC. Using X-ray computed tomography, large spherical type pores were observed in SPoRA similar to those in the commercial slate-based LWA. Additionally, the pore size distribution of SPoRA, characterized by a dynamic vapor sorption analyzer, indicated that more than 97 % of the pores had diameters greater than 50 nm. SPoRA’s average bulk crushing strength was 6.8 MPa which was smaller than commercial LWA and was potentially attributed to the differences in manufacturing processes. Nonetheless, SPoRA LWC with 28 days compressive strength of 29 MPa passed the ASTM C330 requirement and had a comparable strength with LWC prepared with the commercial LWAs indicating lesser importance for the LWA strength. SPoRA LWC had a flowability of 5 % compared to LWC prepared with commercial LWAs having flowability of 18 %. This observation was potentially related to the fluxing agent used in the SPoRA production. SPoRA had a 70 % degree of hydration at 12 days which was comparable with that of LWC prepared with commercial LWA.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Gamma Spectrometry Examination of the AGR-3/4 Irradiation

The results from gamma spectrometry examination of the different components from the combined third and fourth U.S. Advanced Gas Reactor (AGR) TRISO-coated particle fuel irradiation tests (AGR-3/4) have been analyzed. This experiment was designed to provide information about in-pile fission product migration. In each of the 12 capsules, a single stack of four compacts with designed-to-fail (DTF) particles surrounded by inner and outer graphite and/or graphitic matrix rings and a graphite sink ring were irradiated in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). Gamma spectrometry has been used to evaluate the gamma-emitting fission product inventory of compacts from the irradiation and evaluate the burnup of these compacts based on the activity of the radioactive cesium isotopes (i.e., Cs-134 and Cs-137) in the compacts. Burnup from gamma spectrometry compares well with predicted burnup from simulations. The inner and outer rings were also examined by gamma spectrometry to evaluate the total fission product inventory of the rings, and gamma emission computed tomography (GECT) was used to investigate the spatial distribution of gamma-emitting fission products within the rings. This report focuses on results obtained via the Precision Gamma Scanner (PGS) for the compacts and inner and outer rings. These non-destructive gamma measurements are currently being compared to recent destructive measurements of spatial fission product distributions in the rings and to predictions made via mathematical modeling. A separate report discusses the entire AGR-3/4 fission product mass balance for all irradiation capsule components including the inner and outer rings, graphite sink rings, capsule spacers, capsule foils, through tubes, and felts. This report is similar to the conference proceedings: Harp, J.M., Demkowicz, P.A., and Stempien, J.D., “Initial gamma spectrometry examination of the AGR-3/4 irradiation,” International Topical Meeting High Temperature Reactor Technology (HTR 2016), Las Vegas, NV, USA, November 2016, Paper HTR2016-18593, but it has been updated to reflect all the data that has been collected on AGR-3/4 using PGS. The Appendices contain extensive data from the collected gamma spectra.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Gamma Spectrometry Examination of the AGR-3/4 Irradiation

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Influence of Process Parameter and Build Rate Variations on Defect Formation in Laser Powder Bed Fusion SS316L

Laser powder bed fusion (LPBF) is an additive manufacturing process that has gained interest for its material fabrication due to multiple advantages, such as the ability to print parts with small feature sizes, good mechanical properties, reduced material waste, etc. However, variations in the key process parameters in LPBF may result in the instantiation of porosity defects and variation in build rate. Particularly, volumetric energy density (VED) is a variable that encapsulates a number of those parameters and represents the amount of energy input from the laser source to the feedstock. VED has been traditionally used to inform the quality of the printed part but different values of VED are presented as optimal values for certain material systems. An optimal VED value can be maintained by changing the key process parameters so that various combinations yield a constant value. In this study, an optimal constant VED value is maintained while printing SS316L with variable key processing parameters. Porosity analysis is performed using optical microscopy, as well as X-ray computed tomography, to reveal the volume density and distribution of those pores. Two primary defect categories are identified, namely lack of fusion and porosity induced by balling defects. The findings indicate that, even at optimal VED, variations in process parameters can significantly influence defect type, underscoring the sensitivity of defect formation to the variation of these parameters. Furthermore, a minor change in the build rate, driven by adjustments in process parameters, was found to influence defect categories. These findings emphasize that fine tuning the process parameters and build rate is essential to minimize defects. Finally, fiducial marks have been identified as a source of unintentional porosity defects. These results enable the refinement of process parameters, ultimately optimizing LPBF to achieve enhanced material density and expedite the printing.

36 MATERIALS SCIENCE↗

DOE OSTI2025

CT Scans of Cores Metadata, Utqiagvik (Barrow), Alaska, 2015

Individual ice cores were collected from Barrow Environmental Observatory in Barrow, Alaska, throughout 2013 and 2014. Cores were drilled along different transects to sample polygonal features (i.e. the trough, center and rim of high, transitional and low center polygons). Most cores were drilled around 1 meter in depth and a few deep cores were drilled around 3 meters in depth. Three-dimensional images of the frozen cores were constructed using a medical X-ray computed tomography (CT) scanner. TIFF files can be uploaded to ImageJ (an open-source imaging software) to examine soil structure and soil densities within each core.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Automated Scoring of Morphological Changes in Images of Pentaerythritol Tetranitrate

Recent advances in characterization techniques that generate large datasets of material microstructure images require robust, automated image-processing. We applied an unsupervised anomaly detection method called feature anomaly detection system (FADS) to automatically detect and quantify microstructure changes in images of the explosive pentaerythritol tetranitrate (PETN) aged at various temperatures. We demonstrated the FADS approach on two-dimensional images extracted from computed tomography scans, but the same technique can be readily applied to other imaging modalities. FADS calculates anomaly scores on the basis of differences in filter activations of nominal and test data in pretrained convolutional neural networks. The FADS scores successfully differentiated between pristine PETN and PETN aged at a temperature where material coarsening occurred. Morphological metric analysis of segmented images verified observed trends in FADS scores as a function of aging temperature and aging time, specifically by calculating volume fractions, specific boundary lengths, two-point correlation functions, and local thicknesses. Here, the FADS technique has two important advantages compared to traditional morphological analysis: First, it uses grayscale images as input, rather than images that are segmented to separate the appropriate phases; and second, FADS scores capture any type of changes among image sets, rather than requiring prior knowledge or selection of a relevant set of metrics.

Accelerated aging↗

DOE OSTI2025

Influence of gradation on shear behavior and pore water response of sand

Here, this paper examines the influence of particle size distribution (PSD) on the shearing behavior of sand using axisymmetric triaxial compression (ATC) testing in conjunction with 3D imaging using synchrotron micro-computed tomography (SMT). Angular sand was sieved to obtain a narrow gradation (uniform) and a wide gradation (non-uniform) with uniformity coefficients (C u ) of 1.2 and 3.0, respectively. Experiments were conducted under drained conditions and a constant effective cell pressure (σ$^{'}_3$) of 50 kPa at low and high back pressures (BP). Results of paired ATC-SMT were analyzed in terms of global constitutive behavior, strain localization, and localized flow characteristics. A new particle tracking algorithm is developed to expose strain localization. Relative particle translation gradient (RPTG) results revealed that gradation affects how early the shear band develops and a tendency for narrow gradation to exhibit varying degrees of diffused shear band at high axial strain (ε 1 ) even though a clear single shear band was observed at the peak strength. Geometric tortuosity (τ) is used as a quantitative parameter to assess flow changes and the efficiency of the flow path. Representative elementary volumes (REVs) inside and outside the shear band were analyzed and the results showed a variation in flow path characteristics where wide gradation specimens had preferential flow paths.

Computed tomography↗

DOE OSTI2023

Low-Cost X-Ray CT System for Imaging of Roots

The goal of this project was to develop and demonstrate an innovative, low cost, field deployable, stationary 3D x-ray computed tomography (CT) system that will image total root phenotypes with a micron size resolution at a throughput of hundreds of plants per cycle. This system is based on UHV’s unique low cost linear x-ray tube technology and sophisticated reconstruction & image segmentation algorithms developed at University of Massachusetts, Lowel and University of Nottingham; and was tested for several types of soils at University of Wisconsin and Texas A&M University. Currently, no technologies exist that have been designed to image roots in complex media such as agricultural field conditions. Due to its small size, high resolution & fast imaging of fine roots, low power consumption, large penetration depth (i.e. ability to see through several feet of soil) and ease of field deployability, this CT system will increase the speed and efficacy of discovery, field translation, and deployment of improved crops and systems that improve soil carbon accumulation and storage, decrease N2O emissions, and improve water efficiency leading towards advancements that could mitigate 10% of the total US Greenhouse gases. This degree of imaging in the field has never been available and would be invaluable to scientists in understanding how environmental conditions and phenotypic variations contribute to carbon deposition through root development.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Material Identification Using Dual Energy X-ray Absorptiometry

Two implementations of dual energy X-ray absorptiometry were studied to identify materials using X-ray attenuation data taken with the Digital Radiography and Computed Tomography (DRCT) systems that were developed for the Recovered Chemical Materiel Directorate (RCMD). Maitrejean et al.’s approach utilizes eigen effects through Principal Component Analysis, while Osipov et al.’s approach proposed a physics-based method. Both approaches approximate mass attenuation coefficients of materials as a linear combination of basis functions (eigen effects) or physics-based equations. A set of coefficients {a 1 , a 2 , a 3 } or {B, D} were found by parameter optimization in EXCEL Solver. The identification parameters, {$\frac{a_{2}}{a_{1}}$, $\frac{a_{3}}{a_{1}}$} or estimated effective atomic number $\hat{Z}$ from {B, D}, were calculated to identify material of an aluminum 8 step wedge and a steel 8 step wedge in X-ray radiography images taken by a DRCT system. Maitrejean et al.’s approach was unable to provide reliable $\frac{a_{3}}{a_{1}}$ ratio values for identification of materials. Osipov et al.’s approach was found to be more robust in identify materials with a semi-empirical formula derived from test results in this study.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Simulating Catalysis with Realistic Pellet Geometries Using Mesoflow: A Case Study of Catalytic Propane Dehydrogenation

We present a case study of catalytic propane dehydrogenation with our open-source multiphysics solver, Mesoflow. The solver was developed to simulate reactive flow coupled to heterogeneous catalytic reactions and deactivation in the context of complex, mesoscale geometry. The method leverages cartesian block-structured adaptive mesh refinement to capture realistic catalyst microstructural features acquired directly from X-ray computed tomography data. A kinetic model for propane dehydrogenation and catalyst deactivation was developed based on temporal analysis of products (TAP) reactor experiments. The TAP reactor experiments allow for precise characterization of intrinsic kinetic reaction steps which are implemented into Mesoflow simulations to model the spatial and temporal evolution of reactants, products, and catalyst active sites. The short-term and long-term deactivation behavior is studied by using XCT data collected from fresh and aged catalyst pellets, which exhibit different microstructural features. This study employs time-splitting algorithms to connect disparate reaction and flow timescales, enabling the simulations to achieve realistic deactivation timescales on the order of minutes while the flow time-scales for small particles (100 microns) are several milliseconds. We also introduce a flexible automated python script that writes the necessary files to construct a Mesoflow simulation from user-created chemical mechanisms. We will also introduce a few new features that are added to Mesoflow such as higher order schemes, implicit chemistry integrators and the ability to run on AMD and NVIDIA graphics-processing-units.

AMReX↗

DOE OSTI2022

Utilization of the Critic Subnetwork of a Generative Adversarial Network as Detector of Morphological Material Change in Image Data

The resolution of computed tomography (CT) has become high enough to monitor morphological changes due to aging in materials in long-term applications. For this work, we explored the utility of the critic of a generative adversarial network (GAN) to automatically detect such changes. The GAN was trained with images of pristine Pharmatose, which is used as a surrogate energetic material. It is important to note that images of the material with altered morphology were only used during the test phase. The GAN-generated images reproduced the microstructure of Pharmatose well, although some unrealistic particle fusion was seen. Calculated morphological metrics (volume fraction, interfacial line length, and local thickness) for the synthetic images also showed good agreement with the training data, albeit with signs of mode collapse in the interfacial line length. While the critic exposed changes in particle size, it showed limited ability to distinguish images by particle shape. The detection of shape differences was also a more challenging task for the selected morphological metrics that related to energetic material performance. We further tested the critic with images of aged Pharmatose. Subtle changes due to aging are difficult for the human analyst to detect; but both critic and morphological metrics analysis showed image differentiation.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Parametrically designed surface topography on CAD models of additively manufactured lattice structures for improved design validation

Additively Manufactured (AM) lattice structures of the laser powder bed fusion (LPBF) process generally have different surface geometries depending on the overhang angle and location. This means that the design validation stage is often challenging, considering it is based on an ideal Computer Aided Design (CAD) model that is not truly representative, since the AM part will be different in terms of dimensional accuracy and surface finish. Previous studies have relied on the design of surface textures that are independent of the overhang angle, or techniques based on directly using X-ray Computed Tomography (XCT) data. In this paper, a new technique for designing surface texture on the CAD of lattices has been investigated and correlated with areal surface roughness parameters. After extracting areal surface parameters from the XCT data of the lattice, the method allowed for the design of this surface texture on the part CAD taking in consideration if its up skin or down skin, without using XCT data as the main input. By applying this method, it is possible to obtain a lattice CAD model with a designed surface texture and geometry that is more representative of the actual AM lattice. The mean deviation between the CAD model with the designed surface and the XCT was a third of the one between the XCT and the initial CAD. The proposed method allows for designing and replicating LPBF AM surfaces on the CAD of a lattice, taking into consideration the dimensional deviation caused by AM surfaces, especially on overhangs. Assuming that an LPBF AM process is stable and produces approximately the same AM surface, this method can be used to predict the geometry of a lattice, providing a cost-effective and efficient methodology that minimizes the time needed for design validation.

42 ENGINEERING↗

DOE OSTI2026

Accelerating Laboratory-Based, All-Solid-State Battery Research and Development: Industrially Relevant Small-Batch Dry-Processing, Small and Low-Cost Test Fixtures, and Short-Tolerant Separators

This work presents improvements to mixing (for dry-processed electrodes), separator robustness, and cell testing jigs for all-solid-state batteries (ASSBs). These developments combine synergistically to enable rapid research and development of ASSB catholytes. A mechanical "kneader" is designed and built which emulates the mixing and fibrillation of poly-tetrafluoroethylene binder that occurs in industrially relevant twin-screw extruders. A modest improvement in the mixing and dispersion catholyte materials is observed using micro-resolution X-ray computed tomography (X-ray CT). Catholytes are paired with an In-metal anode and separated by a novel, dual-layer, polyaramid-fiber-supported, sulfide-solid electrolyte (Li6 PS5 Cl) separator. This separator achieves high short tolerance which enabled a 95% success rate across 20 attempted cells and to date over 100 successful cells have been built. ASSBs were tested in a 2032 coin-cell format. Simultaneous cycling of a large number of cells is further enabled by a compact and low cost (~ 38 USD per jig) pressure application jig of which 100 have been constructed to date. The utility of these advances is demonstrated through a brief study on the effect cathode-side conductive carbon and current collector type has on capacity and rate performance.

25 ENERGY STORAGE↗