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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Population balance modeling of polyurethane foam formation with pressure‐dependent growth kernel

Abstract Polyurethane foams are widely used materials often chosen for their useful characteristics such as low thermal conductivity, ease of application, and high strength‐to‐weight ratios. Computational models are needed to predict the dynamics of the flow and expansion, and the resulting material properties, to improve manufacturing processes. In this paper, a model for PMDI, a water‐blown polyurethane foam, is presented. By extending a kinetics‐based approach by adding bubble‐scale information via a population balance equation (PBE) using the quadrature method of moments, we can track bubble size distributions during foaming. We present results from a three‐dimensional computational fluid dynamics model using arbitrary Lagrangian–Eulerian interface tracking implemented in finite element software. The model compares favorably with experimental data, including dynamics, bubble distributions measured by both camera and diffusion wave spectroscopy, and post‐test bubble size from scanning electron microscopy and density measurements from x‐ray computed tomography.

Ortiz, Weston↗
DOE OSTI2025

Derivation of A Representative Elementary Volume (REV) for Upscaled Two-Phase Flow in Porous Media

Relative permeability plays an important role in the upscaling of multiphase flow in porous media from the pore scale to the Darcy scale. The entire concept of relative permeability is contingent on the existence of a representative elementary volume (REV). As we move to smaller samples to measure relative permeability, such as with digital core analysis, the concept of a classical REV has become increasingly unlikely when using the conventional approach to defining a representative volume. The “‘conventional”’ understanding of an REV is that a large enough volume must be considered such that spatial variability averages out. In digital rock methods, such as pore-scale simulations based on micro-computed tomography (CT) images, the domain size is typically 2 to 4 mm. This is approximately the length scale of a single-phase flow REV using the classic REV approach. However, the single-phase perspective does not consider the complex dynamics and fluctuations often observed in multiphase flow systems, even at centimeter-scale experiments and/or simulations. A fundamental question is, therefore, whether the domain size commonly used in digital rock simulations can provide a consistent energy budget such that the concept of relative permeability exists. Based on first principles, relative permeability accounts for the rate of energy dissipated in a stationary process. If the dynamics are fluctuating, the energy dissipated can vary but will average out over a long enough timescale. The key to determining the validity of the relative permeability is the timescale of the measurement, not the spatial scale. The conventional REV theory assumes that spatial, temporal, and ensemble averages are equivalent in an ergodic system, but it does not provide a way to test this assumption. We provide a formal way to identify the timescale where the relative permeability accurately captures energy dissipation as a way to validate relative permeability measurements and quantitatively assess their accuracy. This result will be tested for a practical SCAL test, determining how long a flow experiment needs to be run to accurately characterize the rate of energy dissipation by the flow. The outcome will be a best practice guide for the determination of relative permeability from core-scale experiments and/or digital core simulations that ensure the energy budget is fully accounted for in the relative permeability coefficient.

Mcclure, James [Virginia Tech, Blacksburg]↗
DOE OSTI2022

Monte Carlo Simulation and Reconstruction: Assessment of Myocardial Perfusion Imaging of Tracer Dynamics With Cardiac Motion Due to Deformation and Respiration Using Gamma Camera With Continuous Acquisition

Purpose: Myocardial perfusion imaging (MPI) with single photon emission computed tomography (SPECT) is routinely used for stress testing in nuclear medicine. Recently, our group extended its potential going from 3D visual qualitative image analysis to 4D spatiotemporal reconstruction of dynamically acquired data to capture the time variation of the radiotracer concentration and the estimated myocardial blood flow (MBF) and coronary flow reserve (CFR). However, the quality of reconstructed image is compromised due to cardiac deformation and respiration. The work presented here develops an algorithm that reconstructs the dynamic sequence of separate respiratory and cardiac phases and evaluates the algorithm with data simulated with a Monte Carlo simulation for the continuous image acquisition and processing with a slowly rotating SPECT camera. Methods: A clinically realistic Monte Carlo (MC) simulation is developed using the 4D Extended Cardiac Torso (XCAT) digital phantom with respiratory and cardiac motion to model continuous data acquisition of dynamic cardiac SPECT with slowly rotating gamma cameras by incorporating deformation and displacement of the myocardium due to cardiac and respiratory motion. We extended our previously developed 4D maximum-likelihood expectation-maximization (MLEM) reconstruction algorithm for a data set binned from a continuous list mode (LM) simulation with cardiac and respiratory information. Our spatiotemporal image reconstruction uses splines to explicitly model the temporal change of the tracer for each cardiac and respiratory gate that delineates the myocardial spatial position as the tracer washes in and out. Unlike in a fully list-mode data acquisition and reconstruction the accumulated photons are binned over a specific but very short time interval corresponding to each cardiac and respiratory gate. Reconstruction results are presented showing the dynamics of the tracer in the myocardium as it continuously deforms. These results are then compared with the conventional 4D spatiotemporal reconstruction method that models only the temporal changes of the tracer activity. Mean Stabilized Activity (MSA), signal to noise ratio (SNR) and Bias for the myocardium activities for three different target-to-background ratios (TBRs) are evaluated. Dynamic quantitative indices such as wash-in (K1) and wash-out (k2) rates at each gate were also estimated. Results: The MSA and SNR are higher with higher TBRs while biases were improved with higher TBRs to less than 10%. The correlation between exhalation-inhalation sequence with the ground truth during respiratory cycle was excellent. Our reconstruction method showed better resolved myocardial walls during diastole to systole as compared to the ungated 4D image. Estimated values of K1 and k2 were also consistent with the ground truth. Conclusion: The continuous image acquisition for dynamic scan using conventional two-head gamma cameras can provide valuable information for MPI. Our study demonstrated the viability of using a continuous image acquisition method on a widely used clinical two-head SPECT system. Our reconstruction method showed better resolved myocardial walls during diastole to systole as compared to the ungated 4D image. Precise implementation of reconstruction algorithms, better segmentation techniques by generating images of different tissue types and background activity would improve the feasibility of the method in real clinical environment.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2011

A Novel Automated Method for Analyzing Cylindrical Computed Tomography Data

A novel software method is presented that is applicable for analyzing cylindrical and partially cylindrical objects inspected using computed tomography. This method involves unwrapping and re-slicing data so that the CT data from the cylindrical object can be viewed as a series of 2-D sheets in the vertical direction in addition to volume rendering and normal plane views provided by traditional CT software. The method is based on interior and exterior surface edge detection and under proper conditions, is FULLY AUTOMATED and requires no input from the user except the correct voxel dimension from the CT scan. The software is available from NASA in 32- and 64-bit versions that can be applied to gigabyte-sized data sets, processing data either in random access memory or primarily on the computer hard drive. Please inquire with the presenting author if further interested. This software differentiates itself in total from other possible re-slicing software solutions due to complete automation and advanced processing and analysis capabilities.

Roth, D. J.↗
DOE OSTI2020

Pore-scale view of microbial turnover: combining 14 C imaging, μCT, and zymography after adding soluble carbon to soil pores of specific sizes

The location of microorganisms and substrates within soil pore networks plays a crucial role for organic carbon (C) processing, its microbial utilization and turnover, and has direct consequences for C and nutrient cycling. An optimal approach to quantify responses to new C inputs from microorganisms residing in specific pores is the addition of new C to pores of target sizes in undisturbed soil cores. We used the matric potential approach to add 14 C labeled glucose to small (< 40 μm, root free) or large (60-180 μm, potentially inhabited by roots) pores of undisturbed soil cores. Localization of glucose-derived C via 14 C imaging was related to pore size distributions and connectivity, characterized via X-ray computed micro-tomography (μCT), and to β-glucosidase activity, characterized via zymography. After two-week incubations, 1.3 times more glucose was mineralized ( 14 CO 2 ) when it was added to the large pores, however more 14 C remained in microbial biomass when glucose was added to the small pores. Consequently, while utilizing the same amounts of easily available C, the microorganisms localized in the large pores had faster turnover compared to microorganisms in small pores. Stronger associations between β-glucosidase activity and glucose-derived C were observed when glucose was added to the large pores. We conclude that 1) the matric potential approach allows placing, albeit not exactly, soluble substrates into pores of target diameter range, and 2) microorganisms localized in large pores respond to new C inputs with faster turnover, greater growth, and more intensive enzyme production compared to those inhabiting the small pores.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2015

International Space Station (ISS) 3D Printer Performance and Material Characterization Methodology

In order for human exploration of the Solar System to be sustainable, manufacturing of necessary items on-demand in space or on planetary surfaces will be a requirement. As a first step towards this goal, the 3D Printing In Zero-G (3D Print) technology demonstration made the first items fabricated in space on the International Space Station. From those items, and comparable prints made on the ground, information about the microgravity effects on the printing process can be determined. Lessons learned from this technology demonstration will be applicable to other in-space manufacturing technologies, and may affect the terrestrial manufacturing industry as well. The flight samples were received at the George C. Marshall Space Flight Center on 6 April 2015. These samples will undergo a series of tests designed to not only thoroughly characterize the samples, but to identify microgravity effects manifested during printing by comparing their results to those of samples printed on the ground. Samples will be visually inspected, photographed, scanned with structured light, and analyzed with scanning electron microscopy. Selected samples will be analyzed with computed tomography; some will be assessed using ASTM standard tests. These tests will provide the information required to determine the effects of microgravity on 3D printing in microgravity.

Bean, Q. A.↗
NASA NTRS2018

Operational Transition from the First-Generation Heidelberg Spectralis Optical Coherence Tomography [OCT("OCT1")] to the Second-Generation Heidelberg Spectralis OCT("OCT2")

The Heidelberg Spectralis "OCT2", which recently became commercially available, is going to be implemented at the Johnson Space Center Flight Medicine Clinic and on board the International Space Station. Due to the increased scan rate of the "OCT2", this upgrade will allow for significant reduction in valuable crew testing time and also allow for additional capabilities, like OCT Angiography and Multi-Color Fundus Imaging. Due to the custom scans used to monitor Space Flight-Associated Neuro-ocular Syndrome (SANS) in our crewmembers, an evaluation to assess the impacts of transitioning from "OCT1" to "OCT2" was performed. An engineering assessment (N=1) was performed to identify any potential impacts of maintaining an "OCT1" on board ISS while implementing an "OCT2" in the JSC Clinic. "OCT2" implementation will lag JSC FMC clinical implementation due to the flight certification/manifestation process. The clinical assessment was performed (n=12) to identify any impacts due to the replacement of the "OCT1" with the "OCT2" to the longitudinal OCT data across a crewmember's mission/lifetime. The qualitative results from the engineering and clinical evaluation will be reported, as well as the quantitative assessment of the clinical variables

Mason, S.↗
DOE OSTI2025

Black-box optimization of CT acquisition and reconstruction parameters: a reinforcement learning approach

Protocol optimization is critical in Computed Tomography (CT) for achieving desired diagnostic image quality while minimizing radiation dose. Due to the inter-effect of influencing CT parameters, traditional optimization methods rely on the testing of exhaustive combinations of these parameters. This poses a notable limitation due to the impracticality of exhaustive parameter testing. This study introduces a novel methodology leveraging Virtual Imaging Trials (VITs) and reinforcement learning to more efficiently optimize CT protocols. Computational phantoms with liver lesions were imaged using a validated CT simulator and reconstructed with a novel CT reconstruction Toolkit. The optimization parameter space included tube voltage, tube current, reconstruction kernel, slice thickness, and pixel size. The optimization process was done using a Proximal Policy Optimization (PPO) agent which was trained to maximize the Detectability Index (d’) of the liver lesion for each reconstructed image. Results showed that our reinforcement learning approach found the absolute maximum d’ across the test cases while requiring 79.7% fewer steps compared to an exhaustive search, demonstrating both accuracy and computational efficiency, offering a efficient and robust framework for CT protocol optimization. The flexibility of the proposed technique allows for use of varying image quality metrics as the objective metric to maximize for. Our findings highlight the advantages of combining VIT and reinforcement learning for CT protocol management.

Fenwick, David [Duke University Medical Center]↗
DOE OSTI2022

Reduced diffusion and enhanced retention of multiple radionuclides from pore structure characterization of barrier materials for enhanced repository performance

Fluid flow and chemical transport in porous media are the macroscopic consequences of pore structure, which integrates geometry (e.g., pore size and surface area, pore-size distribution) and topology (e.g., pore connectivity). Low-permeability geological media whose pores are poorly interconnected will exhibit the characteristics of anomalous diffusion and sample size-dependent effective porosity, which will strongly impact long-term net diffusion and retention of radionuclides in geological repository settings involving different host rocks and barrier materials. A suite of innovative and complementary experimental approaches is utilized to study the microscopic pore structure and macroscopic fluid flow & chemical transport for a range of host rocks and barrier materials, in addition to standard clay minerals and reference rocks. With a particular focus on quantifying the presence and magnitude of “isolated” pores for a reduced effective porosity in low-permeability geomedia, the integrated methodologies for basic properties and pore structure characterization of these geomedia include X-ray diffraction, thin section petrography, grain size distribution, water immersion porosimetry after vacuum-pulling for full saturation, mercury intrusion porosimetry, nitrogen physisorption, scanning electron microscopy, X-ray computed tomography, and (ultra-)small angle neutron (X-ray) scattering. In addition, custom-designed gas diffusion, tracer recipe involving a range of anionic and cationic chemicals with subsequent analyses by laser ablation and inductively coupled plasma-mass spectrometry, along with batch sorption, column transport, and imbibition tests were conducted for coupled effects of pore structure and chemical retention/transport. From the perspectives of pore structure in conjunction with multiple and complementary approaches to examining a range of sample sizes under different observational scales, we find that the poor pore connectivity is prevalent in low-permeability media (mudstone and crystalline rock) that is related to geological processes (e.g., compaction, diagenesis and thermal maturation). For example, the deep and organic matter-rich mudstones have a much smaller effective porosity than the total porosity (as a result of poor pore connectivity) and associated diffusion coefficient, and the effective porosity & diffusion coefficients are also dependent upon the sample sizes used in the measurement. Similarly, most of the pore space in the shallow mudstone is also controlled by pore-throat diameters in the 5-50 nm range of intergranular pore types from its fine-grained nature, but with an overall good pore connectivity. However, the nm-sized pore space (physically pore-network architecture) and strong sorption capacities (chemical retention from clay minerals) of both shallow and deep mudstones lead to the synergistic retention of cationic radionuclides and their utilities as effective host rocks and barrier materials. Our unique approaches of studying how the micro-scale pore structure affect macro-scale fluid flow, diffusion & retention, and chemical transport produce improved mechanistic understanding, and realistic quantification, of diffusion and retention of typical radionuclides in a range of generic host rocks and barrier materials (clay/shale, salt, crystalline rock, and tuff), with the overall results leading to scientifically-based understanding of enhanced isolation (from both diffusion and retention) of radionuclides and improved confidence on the long-term performance of geological repository to store high-level radioactive wastes. In addition to the training of 25 undergraduates, graduates, and postdocs of UTA, the scientists (organizations) involved in performing this work (e.g., discussion, sample sharing, and operation of SANS and SAXS instruments) include Ed Matteo, Yifeng Wang, and Kristopher Kuhlman (Sandia National Laboratories), Jens Birkholzer, Liange Zheng, Tim Kneafsey, and Sharon Borglin (Lawrence Berkeley National Laboratory), Mavrik Zavarin (Lawrence Livermore National Laboratory), Yukio Tachi and Yuta Fukatsu (Japan Atomic Energy Agency), Mieke de Craen (Euridice, Belgium), Markus Bleuel (NIST), Wei-Ren Chen, Gergely Nagy, Changwoo Do, William Heller, Larry Anovitz, and Kenneth Littrell (ORNL), as well as Jan Illvsky, Ivan Kuzmenko, Ju-Sang Park and Jon Almers (ANL). Key deliverables include a total of 13 peer-reviewed journal articles (nine published and three under review), 23 presentations at scientific conferences (AAPG, AAPG Southwest Section, AGU, Asian Clay Conference, GSA, GSA South-Central Section, IHLRWM, InterPore, International Conference on Chemistry and Migration Behavior of Actinides and Fission Products in the Geosphere, International Conference on Coupled Processes in Fractured Geological Media: Observation, Modeling and Application), and academic institutions (UTA, New Mexico State University; University of Poitiers, France; University of Helsinki, Finland; Uppsala University, Sweden; Istanbul Technical University, Turkey) and other organizations (Andra, France; Posiva Oy, Finland).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Understanding Fracture Aperture and Permeability Evolution due to Carbonate Mineralization Utilizing 3D Printing

Caprock formations are a crucial part of subsurface-engineered systems. Composed largely of shale, caprocks act as natural barriers that prevent the upward migration of fluids, thereby ensuring the containment of stored substances in subsurface formations. Fractures in these formations are potential leakage pathways for stored fluids. Mineral precipitation reactions in these fractures, particularly calcite, can significantly restrict the fluid permeability, reducing leakage potential. However, predictive capabilities of mineral precipitation in fractures and associated permeability evolution are limited due to a lack of fundamental understanding of such reactions in natural samples, complicated by mineral heterogeneity and the complexity of the fracture structure. In this study, 3D-printed fracture samples are used to understand the impact of carbonate mineralization on fracture aperture and permeability evolution. Samples were printed using a digital light processing (DLP) 3D printer and commercial liquid resin. Calcite precipitation was first tested on printed 2D films before conducting plug flow column experiments aimed to understand fracture permeability changes due to mineral precipitation. Contact angle measurement and Fourier transform infrared (FTIR) spectroscopy on printed 2D films show evidence of a substantial amount of surface energy for calcite nucleation and precipitation. Surface topography analysis of printed fractured surfaces reveals comparable values, highlighting the high replicability of the printed samples. During the column experiments, the permeability reduces exponentially due to a decrease in fracture aperture. Reductions in fracture aperture estimated from effluent concentration and 3D X-ray computed tomography (CT) show comparable results. Moreover, 3D X-ray CT images suggest the impact of local flow velocities on precipitation. The insights gained from this research contribute to a deeper understanding of the permeability evolution due to carbonate mineralization in caprock formations.

3D printing↗
DOE OSTI2021

IACMI Project 4.2: Thermoplastic Composite Development for Wind Turbine Blades

(Section 5.1) Composites made from Arkema’s Elium® thermoplastic resin and Johns Manville fiberglass were researched during this project for applications in wind blade manufacturing. A techno-economic model was developed to model this wind blade manufacturing process using these materials in place of traditional composites made with thermoset resin. This model was based on manufacturing a 61.5-meter wind blade, which showed a 4.7% reduction in wind blade cost as compared traditional thermoset materials. These cost savings were not from the thermoplastic material costing less than traditional thermoset materials, but rather from decreased capital costs, faster cycle times and reduced energy requirements and labor costs. (Section 5.2) An infusion and curing model was developed for thermoplastic composite wind blades using PAM-RTM. The primary goal was to demonstrate the infusion simulation for the Elium® resin system on a 13-meter wind blade. Additionally, the exotherm temperature was predicted and compared to measurements, which showed model results within 10% of actual measurements. (Section 5.3) Composite laminate panels and composite sandwich panels with a balsa core were produced; specimens were cut and characterized. Similar composite specimens were made with Elium® thermoplastic resin and Hexion thermoset epoxy (RIMR135/RIMH1366) to enable comparisons between these resin systems. The static test methods included: tensile, compression, in-plane shear, interlaminar shear, flexural, sandwich core shear flexure, and single cantilever beam tests for sandwich beams. Fatigue testing at room temperature was completed to composite laminate panels at a stress ratio of R=0.1 and R=10. In addition, fatigue testing to laminate panels was completed at -30°C, and at room temperature after conditioning specimens at 70°C and 90% relative humidity. Overall, mechanical test results from Elium® composites are similar to epoxy composites. (Section 5.4) Elium composite panels were produced with intentional defects such as voids and nonwetting of fibers to begin to understand performance sensitivity to defects. A thermal digital image correlation (TDIC) method provides high spatial resolution strain field at elevated temperatures and can be used to identify defective regions within composite panels. Flexural modulus differences of 21% were seen between defect and non-defect panels. Other Elium® composite panels were forced to be defective by boiling the resin after infusion, which created voids throughout the composite laminate. X-ray computed tomography scanning was used to view the internal structure of the defect panels. Defect panels had a significant reduction in fatigue life as compared to baseline panels produced without intentional defects. (Section 5.5) Lap shear specimens were fabricated to compare the lap shear strength of an off-the-shelf adhesive (Plexus MA590) and two new adhesives developed by Arkema (Bostik SAF30 90 and Bostik SAF30 120). ISO standard 4587:2003 was used to standardize the testing method and sample fabrication. Lap shear specimens were made at 1mm, 3mm, and 10mm thicknesses. The Bostik adhesive lap shear test results were similar to Plexus for all thicknesses. (Section 5.6) Fiber-reinforced polymer (FRP) composites are typically used in high-performance applications (e.g., aerospace), and their expansion into high-volume industries (e.g. consumer automotive and wind turbine blade manufacturer or similar) is hindered by their cost and a lack of efficient manufacturing techniques. Monitoring the curing process of these composites during manufacturing can improve the efficiency of the process, and therefore reduce the manufacturing cost. Cure monitoring techniques were developed that use probabilistic estimation methods and surface temperature measurements made using infrared cameras. These techniques enable real-time monitoring of the infusion process to locate manufacturing flaws, and they can, potentially, estimate residual stresses in the part. Their commercialization will help facilitate expansion of FRP composites in high-volume industries. (Section 5.7) A 13-meter composite wind blade was produced with Elium® resin and Johns Manville fiberglass; this blade was made with VARTM processing similar to how megawatt-scale wind blades are currently manufactured, but no post-mold heating was used for this thermoplastic composite blade. The wind blade underwent full-scale validation for static loading (4-different load orientations) and flapwise fatigue loading to simulate 20-years of operational loads. The thermoplastic composite wind blade withstood the loading without any noted issues and performed similar to results from a previous full-scale validation to an equivalent epoxy composite wind blade produced with the same blade molds. (Section 5.8) A study was conducted to determine the feasibility of recycling composite wind turbine blade components fabricated with glass fiber reinforced Elium® thermoplastic resin. Dissolution, which is a process unique to thermoplastic matrices, allows recovery of both the polymer matrix and full-length glass fibers, while maintaining their stiffness and strength throughout the recovery process. The economics of recycling is favorable if 50% of the glass fiber is recovered and resold for a process of $\$$ 0.28/kg, and 90% of the resin is recovered and resold at a price of $\$$ 2.50/kg.(Section 10) Recommendations are outlined for commercializing thermoplastic resin for composite wind blade production, in addition to recommended areas for future research.

17 WIND ENERGY↗
DOE OSTI2024

Machine Learning for Predictive Performance Analysis in Charged Particle Beam Tools

Imaging methods driven by probes, electrons, and ions have played a dominant role in modern science and engineering. Opportunities for machine vision and AI that focus on consumer problems like driving and feature recognition, are now presenting themselves for automating aspects of the scientific processes. This proposal aims to enable and drive discovery in ultra-low energy implantation by taking advantage of faster processing, flexible control and detection methods, and architecture-agnostic workflows that will result in higher efficiency and shorter scientific development cycles. Custom microscope control, collection and analysis hardware will provide a framework for conducting novel in situ experiments revealing unprecedented insight into surface dynamics at the nanoscale. Ion implantation is a key capability for the semiconductor industry. As devices shrink, novel materials enter the manufacturing line, and quantum technologies transition to being more mainstream. Traditional implantation methods fall short in terms of energy, ion species, and positional precision. Here we demonstrate 1 keV focused ion beam Au implantation into Si and validate the results via atom probe tomography. We show the Au implant depth at 1 keV is 0.8 nm and that identical results for low energy ion implants can be achieved by either lowering the column voltage, or decelerating ions using bias – while maintaining a sub-micron beam focus. We compare our experimental results to static calculations using SRIM and dynamic calculations using binary collision approximation codes TRIDYN and IMSIL. A large discrepancy between the static and dynamic simulation is found that is due to lattice enrichment with high stopping power Au and surface sputtering. Additionally, we demonstrate how model details are particularly important to the simulation of these low-energy heavy-ion implantations. Finally, we discuss how our results pave a way to much lower implantation energies, while maintaining high spatial resolution.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

A Percolating Path to Green Iron

About 1.9 gigatonnes of steel is produced every year emitting 7% (2.7 gigatonnes) of global CO 2 in the process. More than 50% of the CO 2 emissions come from a single step of steelmaking, known as ironmaking. Hydrogen based direct reduction (HyDR) of iron oxide to iron has emerged as an emissions free ironmaking alternative. However multi-scale phenomena ranging from nanometers to meters inside HyDR reactors exhibit detrimental microstructure evolution which resists gaseous transport of H 2 /H 2 O, slows reaction rates and disrupts continuous reactor operation. To resolve the conundrum between atomic and reactor scales, we devise a percolation-theory model to reconcile nanoscale porosity with macroscopic properties relevant to reactor design models. Using synchrotron nano X-ray computed-tomography, we quantify the evolution of pores in iron oxide pellets, and demonstrate how nano-scale pore networks influence micro and macro-scale flow properties such as permeability, diffusivity and tortuosity. Our new modeling framework bridges the gap between scales and offers the criteria to accelerate HyDR by at least 5x via feedstock-reactor synergies based on percolation.

Paul, Subhechchha↗
NASA NTRSDate not supplied

Quantitative Characterization of 3D Woven Composites Via Fourier Analysis and Structure Tensors Applied to CT Scans

NASA's development of advanced 3D woven carbon composites, such as HEEET and 3MDCP, represents a significant leap in materials designed to endure extreme atmospheric entry conditions. However, the internal complexity of these materials introduces a variety of structures and novel defect types. Traditional characterization methods rely on labor-intensive, manual examination of X-ray CT scans, demanding considerable time and expertise. This process, while thorough, is not sustainable for large-scale analysis and defect tracking. Addressing this critical challenge, this presentation introduces an innovative suite of automated tools and analytical techniques, pioneered by the Mars Sample Return (MSR) Earth Entry System (EES) Thermal Protection System (TPS) project. These advancements offer a more efficient and accurate approach for quantifying CT data and characterizing the defects of 3D woven composites.

3D Woven↗
DOE OSTI2023

Shedding light on shadow generalized parton distributions

The feasibility of extracting generalized parton distributions (GPDs) from deeply virtual Compton scattering (DVCS) data has recently been questioned because of the existence of an infinite set of so-called “shadow GPDs” (SGPDs). These SGPDs depend on the process and manifest as multiple solutions (at a fixed scale 𝑄 2 ) to the inverse problem that needs to be solved to infer GPDs from DVCS data. SGPDs therefore pose a significant challenge for extracting GPDs from DVCS data. With this motivation we study the extent to which QCD evolution can provide constraints on SGPDs. This is possible because the known classes of SGPDs begin to contribute to observables after evolution, and can then be constrained (at the input scale 𝑄$^{2}_{0}$) by data that has a finite 𝑄 2 range. The impact that SGPDs could have on determining the total angular momentum, pressure and sheer force distributions, and tomography is also discussed. We find that 𝑄 2 evolution, given empirical data over a wide range of skewness (𝜉 ) and 𝑄 2 scales, constrains the SGPDs studied at low 𝑥 and low 𝜉. If this finding generalizes to all SGPDs—and we have not been able to find any SGPDs with qualitatively different behavior—then this potentially makes extraction of GPDs from DVCS possible over a limited range of 𝑥 and 𝜉.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

A New Residual Strain Mapping Program Using Energy Dispersive X-Ray Diffraction at the Advanced Photon Source

Here, the ability to non-destructively map the residual strain field inside an engineering component is important for predicting its fatigue life or developing processing methods to prevent failure or enhance performance. In this paper, we describe a new residual strain mapping program at the Advanced Photon Source, Argonne National Laboratory. The new program is based on energy dispersive x-ray diffraction (EDXRD). It is capable of non-destructively penetrating a several- cm thick polycrystalline sample fabricated from engineering alloys using high-energy x-rays and measuring the residual strain field with mm or better spatial resolution and approximately ±1 x 10 -4 strain resolution. A multi-element detector array is employed to measure multiple strain components simultaneously. The residual strain mapping setup is augmented with a high-energy tomography capability, allowing precise alignment of the material volume of interest for residual strain mapping and providing a complementary view of the structure to understand the measured strain field. These measurement capabilities are demonstrated using several strain mapping examples ranging from polycrystalline structural alloys to biological materials. We also provide some guidance for the future users of the program for a successful residual strain mapping experiment. We are expanding the capabilities of the new setup with various in situ capabilities including thermo-mechanical loading.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Development of PNNL’s Plutonium Metallography Capability

The goal of this project was to develop plutonium metallography capabilities and establish workflows for characterization at PNNL’s Radiological Processing Facility (RPL). Developing and expanding on this capability opens more opportunities for PNNL to better support science through collaborations with other labs, plants, and sites withing the Department of Energy Complex and through programs within the National Nuclear Security Administration. This project established metallography equipment in an air glovebox, polishing protocols, as well as radiological and facility controls and procedures so that gram quantities of plutonium metal could be analyzed on multiple characterization tools. Data was collected and analyzed on two different delta phase plutonium - Gallium samples and a calciothermically reduced alpha plutonium metal using a combination of optical and electron microscopy, powder X-ray diffraction, and atom probe tomography. This report highlights the metallography capabilities, some preliminary data collections, and plans at PNNL to support plutonium material science.

36 MATERIALS SCIENCE↗
DOE OSTI2026

ODIN: Confirmation and 3D Reconstruction of Six Massive Protoclusters at Cosmic Noon

Protoclusters represent sites of accelerated galaxy formation and extreme astrophysical activity characteristic of dense environments. Identifying massive protoclusters and mapping their spatial structures are therefore crucial for understanding how large-scale environment influences galaxy evolution. We combine wide-field Lyα imaging from the One-hundred-deg$^{2}$ DECam Imaging in Narrowbands survey with extensive Dark Energy Spectroscopic Instrument and ancillary spectroscopy across the extended COSMOS and XMM Large Scale Structure (LSS) fields (≈14 deg$^{2}$) to search for massive protoclusters. We confirm six systems at z ≈ 2.4 and ≈ 3.1, including three newly identified structures and three which overlap with previously known structures and/or systems detected using other tracers. We reconstruct their three-dimensional structures, estimate descendant halo masses, and for one structure at z ≈ 3.12, demonstrate that overlapping narrowband filters (NB497 and N501) provide accurate redshift tomography for emission-line galaxies. One protocluster at z ≈ 2.45 overlaps with one of the LATIS tomographic fields, enabling direct comparison between galaxy and H i overdensities traced by Lyα forest absorption. Another at z ≈ 3.12 hosts a massive quiescent galaxy (M$_{*}$ ≈ 1.2 × 10$^{11}$M$_{⊙}$), suggesting that overdense environments may play a role in accelerating galaxy assembly and quenching. Comparing Lyα emission properties across environments, we find that protocluster galaxies exhibit higher median line fluxes and a deficit of faint emitters relative to the field. The effect is strongest when combining 2D and 3D density information, indicating that galaxies in the densest protocluster cores are most affected by environmental processes. This effect is stronger at z ≈ 3.1 than at z ≈ 2.4, suggesting possible redshift evolution.

Ortiz, Ashley [Purdue U.] (ORCID:000900083184304X)↗