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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Multiphysics Meshfree Degradation Modeling of Energy Storage Materials with Kernel Enrichment

Energy storage materials exhibit strong electro-chemo-mechanical coupling and highly anisotropic material properties, contributing to the formation and propagation of micro-cracking during charge/discharge cycling and ultimately diminishing performance and service life. With microstructural images supplied by the National Renewable Energy Laboratory (NREL), pixel-based meshfree model construction by the reproducing kernel particle method (RKPM) is used to represent the complex material microstructures that dictate the coupled physics of these systems. Traditional electro-chemo-mechanical models rely on mesh-based finite element methods, which can lead to difficulties in meshing such complex geometries and capturing crack propagation due to mesh dependency. The first kernel enrichment discussed will be the interface modified reproducing kernel (IM-RK) [1, 2], constructed by scaling a smooth kernel function with an interface-distance function to achieve strategic discontinuity types (i.e. weak discontinuities for strain discontinuities and strong discontinuities for cracks) and alleviate Gibbs oscillations near these transition zones. The IM-RK is especially useful for areas in which a known discontinuity-type is expected a priori. The second kernel enrichment to be discussed is a neural network-enhanced reproducing kernel (NN-RK) [3, 4], which is introduced to effectively model non-obvious damage and crack propagation in the material microstructures; the location, orientation, and solution transition near a localization are automatically captured by superimposed block-level NN optimizations. This NN enrichment approach allows for effective modeling of localizations via a fixed background discretization, relieving tedious efforts for adaptive refinement in traditional mesh-based methods. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. NN-RK is additionally used to inform how crack opening and closure in turn affect the electro-chemo-mechanical responses in the material microstructure. Reference: [1] Wang, Y., Baek, J., Tang, Y. et al. "Support vector machine guided reproducing kernel particle method for image-based modeling of microstructures," Comput Mech 73, 907-942 (2024). https://doi.org/10.1007/s00466-023-02394-9. [2] Susuki, K., Allen, J. & Chen, J. S.. "Image-based modeling of coupled electro-chemo-mechanical behavior of Li-ion battery cathode using an interface-modified reproducing kernel particle method," Engineering with Computers (2024). https://doi.org/10.1007/s00366-024-02016-9. [3] Baek, J., Chen, J. S., Susuki, K., "Neural Network enhanced Reproducing Kernel Particle Method for Modeling Localizations," International Journal for Numerical Methods in Engineering, Vol. 123, 4422-4454 (2022). https://doi.org/10.1002/nme.7040.

25 ENERGY STORAGE↗
DOE OSTI2026

Kernel Enriched Meshfree Multiphysics Degradation Modeling of Energy Storage Materials

Energy storage materials exhibit strong electro-chemo-mechanical coupling and highly anisotropic material properties, contributing to the formation and propagation of micro-cracking during charge/discharge cycling and ultimately diminishing performance and service life. With microstructural images supplied by the National Laboratory of the Rockies (NLR), pixel-based meshfree model construction by the reproducing kernel particle method (RKPM) is used to represent the complex material microstructures that dictate the coupled physics of these systems. Traditional electro-chemo-mechanical models rely on mesh-based finite element methods, which can lead to difficulties in meshing such complex geometries and capturing crack propagation due to mesh dependency. The first kernel enrichment discussed will be the interface modified reproducing kernel (IM-RK) [1, 2], constructed by scaling a smooth kernel function with an interface-distance function to achieve strategic discontinuity types (i.e. weak discontinuities for strain discontinuities and strong discontinuities for cracks) and alleviate Gibbs oscillations near these transition zones. The IM-RK is especially useful for areas in which a known discontinuity-type is expected a priori. The second kernel enrichment to be discussed is a neural network-enhanced reproducing kernel (NN-RK) [3, 4], which is introduced to effectively model non-obvious damage and crack propagation in the material microstructures; the location, orientation, and solution transition near a localization are automatically captured by superimposed block-level NN optimizations. This NN enrichment approach allows for effective modeling of localizations via a fixed background discretization, relieving tedious efforts for adaptive refinement in traditional mesh-based methods. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. NN-RK is additionally used to inform how crack opening and closure in turn affect the electro-chemo-mechanical responses in the material microstructure. References: [1] Wang, Y., Baek, J., Tang, Y. et al. "Support vector machine guided reproducing kernel particle method for image-based modeling of microstructures," Comput Mech 73, 907-942 (2024). https://doi.org/10.1007/s00466-023-02394-9. [2] Susuki, K., Allen, J. & Chen, J. S.. "Image-based modeling of coupled electro-chemo-mechanical behavior of Li-ion battery cathode using an interface-modified reproducing kernel particle method," Engineering with Computers (2024). https://doi.org/10.1007/s00366-024-02016-9. [3] Baek, J., Chen, J. S., Susuki, K., "Neural Network enhanced Reproducing Kernel Particle Method for Modeling Localizations," International Journal for Numerical Methods in Engineering, Vol. 123, 4422-4454 (2022). https://doi.org/10.1002/nme.7040.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1994

Aircraft fatigue and crack growth considering loads by structural component

The indisputable 1968 C-130 fatigue/crack growth data is reviewed to obtain additional useful information on fatigue and crack growth. The proven Load Environment Model concept derived empirically from F-105D multichannel recorder data is refined to a simpler method by going from 8 to 5 variables in the spectra without a decrease in accuracy. This approach provides the true fatigue/crack growth and load environment by structural component for both fatigue and strength design. Methods are presented for defining fatigue scatter and damage at crack initiation. These design tools and criteria may be used for both metal and composite aircraft structure.

Yost, J. D.↗
DOE OSTI2020

Application and Certification of Comparative Vacuum Monitoring Sensors for Structural Health Monitoring of 737 Wing Box Fittings

Multi-site fatigue damage, hidden cracks in hard-to-reach locations, disbonded joints, erosion, impact, and corrosion are among the major flaws encountered in today's extensive fleet of aging aircraft and space vehicles. The use of in-situ sensors for real-time health monitoring of aircraft structures are a viable option to overcome inspection impediments stemming from accessibility limitations, complex geometries, and the location and depth of hidden damage. Reliable, structural health monitoring systems can automatically process data, assess structural condition, and signal the need for human intervention. Prevention of unexpected flaw growth and structural failure can be improved if on-board health monitoring systems are used to continuously assess structural integrity. Such systems are able to detect incipient damage before catastrophic failures occurs. Condition-based maintenance practices could be substituted for the current time-based maintenance approach. Other advantages of on-board distributed sensor systems are that they can eliminate costly, and potentially damaging, disassembly, improve sensitivity by producing optimum placement of sensors and decrease maintenance costs by eliminating more time- consuming manual inspections. This report presents a Sandia Labs-aviation industry effort to move SHM into routine use for aircraft maintenance. This program addressed formal SHM technology validation and certification issues so that the full spectrum of concerns, including design, deployment, performance and certification were appropriately considered. The Airworthiness Assurance NDI Validation Center (AANC) at Sandia Labs, in conjunction with Boeing, Delta Air Lines, Structural Monitoring Systems Ltd., Anodyne Electronics Manufacturing Corp. and the Federal Aviation Administration (FAA) carried out a certification program to formally introduce Comparative Vacuum Monitoring (CVM) as a structural health monitoring solution to a specific aircraft wing box application. Validation tasks were designed to address the SHM equipment, the health monitoring task, the resolution required, the sensor interrogation procedures, the conditions under which the monitoring will occur, the potential inspector population, adoption of CVM into an airline maintenance program and the document revisions necessary to allow for routine use of CVM as an alternate means of performing periodic structural inspects. To carry out the validation process, knowledge of aircraft maintenance practices was coupled with an unbiased, independent evaluation. Sandia Labs designed, implemented, and analyzed the results from a focused and statistically-relevant experimental effort to quantify the reliability of the CVM system applied to the Boeing 737 Wing Box fitting application. All factors that affect SHM sensitivity were included in this program: flaw size, shape, orientation and location relative to the sensors, as well as operational and environmental variables. Statistical methods were applied to performance data to derive Probability of Detection (POD) values for CVM sensors in a manner that agrees with current nondestructive inspection (NDI) validation requirements and also is acceptable to both the aviation industry and regulatory bodies. This report presents the use of several different statistical methods, some of them adapted from NDI performance assessments and some proposed to address the unique nature of damage detection via SHM systems, and discusses how they can converge to produce a confident quantification of SHM performance An important element in developing SHM validation processes is a clear understanding of the regulatory measures needed to adopt SHM solutions along with the knowledge of the structural and maintenance characteristics that may impact the operational performance of an SHM system. This report describes the major elements of an SHM validation approach and differentiates the SHM elements from those found in NDI validation. The activities conducted in this program demonstrated the feasibility of routine SHM usage in general and CVM in particular for the application selected. They also helped establish an optimum OEM-airline-regulator process and determined how to safely adopt SHM solutions. This formal SHM validation will allow aircraft manufacturers and airlines to confidently make informed decisions about the proper utilization of CVM technology. It will also streamline the regulatory actions and formal certification measures needed to assure the safe application of SHM solutions.

42 ENGINEERING↗
NASA NTRS2008

STS-118 Radiator Impact Damage

During the August 2007 STS-118 mission to the International Space Station, a micro-meteoroid or orbital debris (MMOD) particle impacted and completely penetrated one of shuttle Endeavour s radiator panels and the underlying thermal control system (TCS) blanket, leaving deposits on (but no damage to) the payload bay door. While it is not unusual for shuttle orbiters to be impacted by small MMOD particles, the damage from this impact is larger than any previously seen on the shuttle radiator panels. A close-up photograph of the radiator impact entry hole is shown in Figure 1, and the location of the impact on Endeavour s left-side aft-most radiator panel is shown in Figure 2. The aft radiator panel is 0.5-inches thick and consists of 0.011 inch thick aluminum facesheets on the front and back of an aluminum honeycomb core. The front facesheet is additionally covered by a 0.005 inch thick layer of silver-Teflon thermal tape. The entry hole in the silver-Teflon tape measured 8.1 mm by 6.4 mm (0.32 inches by 0.25 inches). The entry hole in the outer facesheet measured 7.4 mm by 5.3 mm (0.29 inches by 0.21 inches) (0.23 inches). The impactor also perforated an existing 0.012 inch doubler that had been bonded over the facesheet to repair previous impact damage (an example that lightning can strike the same place twice, even for MMOD impact). The peeled-back edge around the entry hole, or lip , is a characteristic of many hypervelocity impacts. High velocity impact with the front facesheet fragmented the impacting particle and caused it to spread out into a debris cloud. The debris cloud caused considerable damage to the internal honeycomb core with 23 honeycomb cells over a region of 28 mm by 26 mm (1.1 inches by 1.0 inches) having either been completely destroyed or partially damaged. Figure 3 is a view of the exit hole in the rear facesheet, and partially shows the extent of the honeycomb core damage and clearly shows the jagged petaled exit hole through the backside facesheet. The rear facesheet exit hole damage including cracks in the facesheet measures 14 mm by 14 mm (0.55 inches by 0.55 inches). The remnants of the impacting particle and radiator panel material blown through the rear facesheet hole also created two penetrations in the TCS blanket 115 mm (4.5 inches) behind the rear facesheet. Figure 4 shows these two impacts, which are located 75 mm (3 inches) apart. Some deposits of material were found on the payload bay door beneath the TCS blanket, but no additional damage occurred to the door. Figure 5 illustrates the relationship of the facesheet entry hole to the TCS blanket damage, which may indicate the direction of the impacting particle. The image on the left side of Figure 5 shows an overhead view of the damaged radiator after the facesheet holes were cored out of the panel. The entry hole location and the two underlying TCS blanket damage sites are annotated on the image. Section A-A, running through the entry hole and TCS blanket damage locations, describes a 25 angle from the longitudinal axis of the shuttle. The 2nd impact angle can be seen in section A-A on the right side of Figure 5. An average 17 angle of impact to the surface normal was derived by measuring the angles of the two damage sites in TCS blanket to the entry hole.

Lear, Dana M.↗
DOE OSTI2024

A mean field homogenization model for the mechanical response of ceramic matrix composites

SiC/SiC composites offer exceptional mechanical stability at high temperatures and under irradiation. These ceramic matrix composites are therefore strong candidate materials for future nuclear energy applications. Their mechanical response, which exhibits pseudo-plasticity, is mediated by matrix cracking, fiber debonding, and fiber pull-out due to slip. Here, this study introduces a mechanistic model for the behavior of unidirectionally reinforced SiC/SiC composites. Specifically a mean field homogenization approach is proposed to account for all deformation and degradation modes during mechanical deformation. The homogenization scheme relies on a Mori Tanaka method that is extended to consider the effects of the coating’s elasto-plastic response on the development of micromechanical fields. Further, the model proposed introduces a method to effectively account for the role of localized damage (i.e., cracks) on mechanical fields within both the fiber and the matrix. Upon validating the model against experimental data, the roles of interface sliding, coating dimensions and intrinsic elastic response, as well as of microstructure (e.g. porosity, fiber volume fraction) are discussed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Electrochemical performance of ionic polymer metal composite under tensile loading

Abstract Cracks in polymer composites can lead to premature failure, which can be disastrous for polymer-based energy storage devices. Detecting these cracks is essential to guarantee the reliability and safety of such devices. However, detecting cracks in composite polymers such as ionic polymer metal composites (IPMCs) is a challenging task, which makes it difficult to ensure their performance and safety. The overall goal of this study is to investigate the effect of cracks or damage caused by tensile loading on the mechanical properties and electrochemical characteristics of IPMC based capacitors. During tensile testing, the deformation of the IPMC strips causes changes in the ion distribution and concentration in the polymer matrix, influencing the performance of the material. The measurements were conducted utilizing electrochemical impedance spectroscopy at a room temperature ( 21 ∘ C ) and frequency range of 10 KHz to 1 Hz. The method utilized in this study proved to be easy and quick with consistent results. The IPMC capacitor was found to increase its capacitance after major cracking in the Pt electrodes from high tensile mechanical loads. Furthermore, at lower frequency range (<100 Hz), the real ( ε ′ ) and imaginary ( ε ′ ′ ) part of permittivity increase with the addition of loads. This displays that the dielectric property of the material is affected due to the increasing of the loads. It is concluded that, at frequencies above 100 Hz, the permittivity is weakly load dependent.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Multiphysics Degradation Modeling of Energy Storage Materials via RKPM with a Neural Network-Enhancement

In energy storage materials, strong electrochemical-mechanical coupling and highly anisotropic material properties contribute to the formation and propagation of micro-cracking during charge/discharge cycling, resulting in reduced performance and service life. A coupled electro-chemo-mechanical reproducing kernel particle method (RKPM) formulation is developed, and a patch-test is formulated to certify optimal convergence of the proposed RKPM method for the coupled physics system. With microstructural images supplied by the National Renewable Energy Laboratory (NREL), pixel-based model construction by RKPM is then used to represent the complex material microstructures for modeling the coupled physics of these systems. Further, a neural network-enhanced reproducing kernel particle method (NN-RKPM) [1, 2] is introduced to effectively model damage and crack propagation in the material microstructures; the location, orientation, and solution transition near a localization are automatically captured by superimposed block-level NN optimizations. This NN enrichment approach allows for effective modeling of localizations via a fixed background discretization, relieving tedious efforts for adaptive refinement in traditional mesh-based methods. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. Reference: [1] Baek, J., Chen, J. S., Susuki, K., "Neural Network enhanced Reproducing Kernel Particle Method for Modeling Localizations," International Journal for Numerical Methods in Engineering, Vol. 123, pp 4422-4454, https://doi.org/10.1002/nme.7040, 2022. [2] Baek, J., Chen, J. S., "A Neural Network-Based Enrichment of Reproducing Kernel Approximation for Modeling Brittle Fracture", Computer Methods in Applied Mechanics and Engineering Vol. 410, 116590, 2024.

electro-chemo-mechanical coupling↗
NASA NTRS1990

Thermomechanical testing techniques for high-temparature composites: TMF behavior of SiC(SCS-6)/Ti-15-3

Thermomechanical testing techniques recently developed for monolithic structural alloys were successfully extended to continuous fiber reinforced composite materials in plate form. The success of this adaptation was verified on a model metal matrix composite (MMC) material, namely SiC(SCS-6)/Ti-15V-3Cr-3Al-3Sn. Effects of heating system type and specimen preparation are also addressed. Cyclic lives determined under full thermo-mechanical conditions were shown to be significantly reduced from those obtained under comparable isothermal and in-phase bi-thermal conditions. Fractography and metallography from specimens subjected to isothermal, out-of-phase and in-phase conditions reveal distinct differences in damage-failure modes. Isothermal metallography revealed extensive matrix cracking associated with fiber damage throughout the entire cross-section of the specimen. Out-of-phase metallography revealed extensive matrix damage associated with minimal (if any) fiber cracking. However, the damage was located exclusively at surface and near-surface locations. In-phase conditions produced extensive fiber cracking throughout the entire cross-section, associated with minimal (if any) matrix damage.

Castelli, Michael G.↗
NASA NTRS1992

Thermomechanical testing of high-temperature composites - Thermomechanical fatigue (TMF) behavior of SiC(SCS-6)/Ti-15-3

Thermomechanical testing techniques recently developed for monolithic structural alloys were successfully extended to continuous fiber reinforced composite materials in plate form. The success of this adaptation was verified on a model metal matrix composite (MMC) material, namely SiC(SCS-6)/Ti-15V-3Cr-3Al-3Sn. Effects of heating system type and specimen preparation are also addressed. Cyclic lives determined under full thermomechanical conditions were shown to be significantly reduced from those obtained under comparable isothermal and in-phase bi-thermal conditions. Fractography and metallography from specimens subjected to isothermal, out-of-phase and in-phase conditions reveal distinct differences in damage-failure modes. Isothermal metallography revealed extensive matrix cracking associated with fiber damage throughout the entire cross-section of the specimen. Out-of-phase metallography revealed extensive matrix damage associated with minimal (if any) fiber cracking. However, the damage was located exclusively at surface and near-surface locations. In-phase conditions produced extensive fiber cracking throughout the entire cross-section, associated with minimal (if any) matrix damage.

Castelli, Michael G.↗
NASA NTRS1981

The effect of lamination-induced stresses on fatigue damage development at internal flaws

The effects of stresses induced by the lamination of off-axis plies to O-deg lamina on the development of damage during the fatigue loading of the O-deg plies are discussed. The transverse normal stresses in the plane of the laminae and the laminate created by the laminating constraints when an axial force is applied to the laminate are calculated in terms of a differential Poisson ratio between the ply in question in the unconstrained and constrained states, and significant differences in the constraint environments of an unnotched specimen joined to plies of 45 and 90 deg inclination are noted which correspond to an increase in longitudinal splitting in the 90 deg case and a marked decrease in longitudinal splitting in the 45 deg case. If a notch is present, shear and crack-opening damage is found to be very effectively suppressed in 45-deg laminates, and less so in the 90-deg case. It is pointed out that whereas the 45-deg laminate represents the least damage situation, it does not have the greatest notched strength. It is concluded that an understanding and prediction of damage development in laminates requires knowledge of the stress fields caused by the lamination constraints.

Reifsnider, K. L.↗
DOE OSTI2025

MPEX AI Digital Twins

All magnetically confined plasma fusion power plant concepts (Tokamak, Spherical Tokamak, Stellarator, Mirror, ...) must exhaust the heat and plasma from the core confinement region to the material walls. The primary channel for this exhaust is through a plasma divertor which directs plasma along open magnetic field lines to a material target. The Material Plasma Exposure eXperiment (MPEX) illustrated in Figure 1, is a high-power, steady-state linear plasma device designed to produce the plasma material interaction (PMI) conditions of the divertor of future magnetic confinement fusion power plants: energy flux 20MW/m 2 , ion fluence 1031/m 2 , pulse duration 106 sec. These goals of plasma exposure in MPEX are well beyond those achieved in magnetic fusion experimental devices. Successfully achieving these high power steady state conditions for long pulses requires operational control of the heating and particle sources and the plasma flux to the walls and target. The MPEX AI Hot Spot Controller, proposed in this project, will help achieve the operational milestones of MPEX. The MPEX device will begin commissioning at the end of FY26. A smaller proto-MPEX was operated for 14,666 plasma discharges and will resume operation in September of 2025 as proto-MPEX-lite, with reduced capability, to test a new window for the Helicon plasma source. The proto-MPEX data has undergone surrogate modeling with machine learning methods (R. Archibald, 2022 IEEE International Conference on Big Data). This proto-MPEX data will be used to begin development of the AI digital twins described in this white paper. The scientific mission of MPEX is to qualify materials of different composition for use in the high energy and plasma flux conditions of a fusion power plant. The materials exposed in MPEX will in some cases be exposed to high neutron fluxes at other ORNL facilities to measure the changes to their PMI properties. The targets exposed in MPEX will be transported under vacuum to a Surface Analysis Station (SAS). The SAS will be equipped with the following diagnostics: Focused Ion Beam (FIB) for trench milling, 100-400 angstrom resolution scanning electron microscope (SEM), surface mapping x-ray spectrometer, high resolution camera, and a future upgrade to a laser induced breakdown spectroscopy quadruple mass spectrometer (LIBS-QMS). The MPEX experiments will generate diverse pre- and post-exposure measurement data of detailed material properties down to the crystal grain level in 3D for post-exposure assessment of PMI damage (e.g. cracking, melting, erosion and redeposition of the material). Physics models for the PMI, and how the material composition and manufacturing impact its performance under high energy plasma exposure, need to be validated with MPEX data to guide the selection of new candidate materials. Our vision for the MPEX AI Digital Twins project is to supply experimental and physics model simulation data to train Artificial Intelligence (AI) models for data processing, analysis, operational control, PMI and materials simulation to maximize the scientific output of the MPEX device. Ultimately, an AI digital twin of MPEX material assessment metrics for tested and synthetic material types with simulated PMI will be trained by the AI Modeling Teams on the experimental and physics simulation data submitted to the American Science Cloud by this project. A purely empirical search for the best material is inefficient given the finite number of samples that can be tested on MPEX. In order to expand the material properties database for training the MPEX Material Assessment AI Digital Twin, and to gain physics understanding of the PMI processes, physics models of the material properties and PMI processes are required. The physics simulations provide detailed simulation data, like impact angles for plasma ions, sputtering yields, transport of the ionized sputtered target material in the plasma, and redeposition locations. This simulation data expands the measurement data for deeper physics understanding. The experimental data is essential to validate the PMI and material structure simulation models. The validated models can then be used to generate new simulation data of MPEX material assessments for synthetic material compositions that have not been exposed in MPEX. These predictive simulations, plus the whole experimental dataset, will be used to train the MPEX Material Assessment AI Digital Twin allowing a rapid generative AI search for new materials with reduced PMI damage by interpolating the domain of the training set. These new optimum materials can be simulated with the physics codes and/or tested in MPEX. The ability of AI neural networks to interpolate multi-dimensional parameter spaces and generate virtual data is exploited for a more efficient search for optimum materials. The advent of the Transformational AI Models Consortium (TAIMC) is an opportunity to engage with state of the art private and public AI developers to achieve the goals of the AI digital twins and AI accelerated physics models proposed in this project. Our partners at ORNL from the Advance Scientific Computing Research (ASCR) organization will collaborate in accelerating the integrated plasma material interaction simulation framework. This simulation framework will provide a platform for generating simulation data across a range of physical fidelities, including hybrid methods that produce multi-fidelity results. This data will be leveraged for AI model development, both for generation of surrogates and the automation of simulation campaigns. A part of the research below will include collaborative efforts with the TAIMC to (i) adapt data storage approaches to ensure AI-readiness, (ii) provide a protypical exemplar to inform and exercise constructed workflows, and (iii) generate and share data, using the TAIMC unified AI data standard, for foundational models that will be trained from multiple sources across the DOE complex. We will also collaborate with the TAIMC, as well as the planned AI modeling teams, to develop approaches for reducing the cost of data generation. These include tailored multi-fidelity approaches as well as fine-tuning strategies to augment general, large-scale foundational models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Improvement in the spatial resolution for imaging with fast neutrons

In this paper, we report on the realization of an improved concept for the detection of fast neutrons using a specific setup of scintillators with the aim to overcome limitations in spatial resolution. While fast neutron imaging (FNI) is a technique to investigate very thick material layers in transmission mode, currently there is a limit in the spatial resolution at ~1 mm, which hinders the performance for the detection of features like cracks, material damage or pores in large objects ($\gg$1 cm 3 ). The improved concept presented here is based on the separation of the converter material from the scintillation layer in a suitable way, which was successfully tested and referenced to the standard devices at the NECTAR facility (FRM-2, MLZ, Garching) under realistic beamline conditions. The results imply a break-through in enabling detection of structures on the order of 0.2 to 0.5 mm (a more precise estimation is not possible due to other resolution determing factors in a realistic setup). Potential additional improvements are discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Three-Dimensional Heat Flux and Thermal Analysis of Angled Tungsten Samples on DIII-D

ITER-grade tungsten and dispersoid-strengthened tungsten samples with the top surface angled at ~15° towards the incident plasma flux were exposed to 9 H-mode discharges with edge-localized modes (ELMs) in the lower divertor of DIII-D tokamak using the Divertor Material Evaluation System (DiMES). Surface damage included cracking and flaking of material on the two samples farthest away from the plasma strike point, and significant melting of the two samples closest to the strike point. Heat flux and thermal analysis tools new to DIII-D have been applied to better understand this material response and to help optimize the exposure conditions for future experiments. SMITER field-line tracing simulations based on IRTV data and EFIT equilibria estimate an average inter-ELM perpendicular heat flux, 𝑞⊥,𝑖nter−𝐸LM , on the angled surfaces of 10.1 – 19.6 MW/m² for a majority of the 9 discharges, increasing to 15.6 – 24.5 MW/m² for the single, higher-power shot where samples melted. Fast camera data showed shallow intra-ELM melting and re-solidification, which transitioned to bulk inter-ELM melting with melt motion in the 𝐽⃗ 𝑥 𝐵⃗ direction. About 50% of the protruding volume of the most affected sample was displaced via melt-motion. SIERRA thermal modeling software was able to reproduce an onset time of melting consistent with fast camera data and final sample conditions, within < 200 ms. Maximum surface temperatures of 3122 K and 2787 K are estimated for the samples farthest away from the strike point, while the closest samples achieve melting at 4067 ms and 4750 ms into the ~5000 ms plasma exposure. A +10% increase in both the SMITER 𝑞⊥,𝑖nter−𝐸LM calculations and the estimated ELM heat loads 𝑞⊥, 𝐸LM was required to achieve this result, which is within the uncertainty of the diagnostic data but likely accounts for non-ideal geometry effects plus other physics uncertainties not included in this first iteration of modeling. This work provided valuable estimates of the 3D temperature evolution to help better understand the observed surface morphology and internal recrystallization of samples, which are discussed in detail in a complementary manuscript [1]. Benchmarking efforts with more diagnosed DIII-D experiments are underway to further refine the SMITER and SIERRA models for DiMES. Future use of these tools will enable researchers to precisely target heat flux exposure conditions in DIII-D to test, but not exceed, the thermomechanical limitations of novel plasma-facing materials.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Deuterium plasma induced preferential erosion in ultra-high temperature ceramics TiB 2 and ZrB 2 *

Abstract Steady-state deuterium plasma exposures were performed on ultra-high temperature ceramics titanium diboride (TiB 2 ) and zirconium diboride (ZrB 2 ) using the PISCES-RF linear plasma device (LPD) as early screening for first wall, plasma-facing applications. Deuterium plasma exposures were performed using 40 eV ion energies at 240, 525, and 800 °C sample temperatures and 90 eV ion energies at 240 °C sample temperatures to analyze TiB 2 and ZrB 2 surface morphology and chemistry evolution behavior. Post-plasma exposure chemistry characterization of the near surface ( < 50 nm) region of the samples all show transition metal enrichment, indicating boron preferential erosion. Transition metal to boron fractions vary with plasma exposure temperature under the 40 eV ion energy; metal enrichment is maximized at 800 °C and then minimized at 525 °C. SEM micrographs of all plasma exposed sample surfaces show no significant or noticeable plasma induced damage from cracking or blistering.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Detailed space–time variations of the seismic response of the shallow crust to small earthquakes from analysis of dense array data

SUMMARY We compute high-resolution space–time variations of subsurface seismic properties from autocorrelation functions (ACF’s) of noise and local earthquakes, recorded by the Sage Brush Flat dense array deployed around the Clark branch of the San Jacinto fault. The resolved temporal changes are referred to as apparent velocity changes because they reflect both nonlinear response and variations of material properties such as cracking and damage. Apparent velocity changes are estimated at four frequency bands (10–15, 10–20, 15–30 and 20–40 Hz) for two local earthquake data sets. In one analysis, ACF’s from P- and S-wave windows of 31 small events with magnitudes below 3.1 are used to compute the apparent velocity variations with respect to the mean ACF of each phase, and we also use the mean ACF of noise data as reference to estimate the changes. In a further analysis, the temporal evolution of properties is computed using moving time windows in continuous waveform over one-hour long data with noise and earthquake signals. The apparent velocity changes and recovery times are frequency dependent and present a strong spatial variability across the array. The resolved changes are larger and recovery time shorter with data associated with higher frequencies. At frequencies larger than 15 Hz, and using the mean ACF of noise data as a reference, the apparent average velocity changes across the array during the passage of the P and S waves from the small local events are 2.5 per cent and 6 per cent, respectively. The apparent velocity changes decrease by one order of magnitude when the earthquake data are used as a reference. The relatively large changes in response to very low ground motion have important implications on nonlinear processes involving degradation and healing of the subsurface material during common earthquake shaking.

Geochemistry & Geophysics↗
DOE OSTI2022

A New Perspective of Post-Weld Baking Effect on Al-Steel Resistance Spot Weld Properties through Machine Learning and Finite Element Modeling

The root cause of post-weld baking on the mechanical performance of Al-steel dissimilar resistance spot welds (RSWs) has been determined by machine learning (ML) and finite element modeling (FEM) in this study. A deep neural network (DNN) model was constructed to associate the spot weld performance with the joint attributes, stacking materials, and other conditions, using a comprehensive experimental dataset. The DNN model positively identified that the post-weld baking reduces the joint performance, and the extent of degradation depends on the thickness of stacking materials. A three-dimensional finite element (FE) model was then used to investigate the root cause and the mechanism of the baking effect. It revealed that the formation of high thermal stresses during baking, from the mismatch of thermal expansion between steel and Al alloy, causes damage and cracking of the brittle intermetallic compound (IMC) formed at the interface of the weld nugget during welding. This in turn reduces the joint performance by promoting undesirable interfacial fracture when the welds were subjected to externally applied loads. The FEM model further revealed that increase in structural stiffness, because of increase in steel sheet thickness, reduces the thermal stresses at the interface caused by the thermal expansion mismatch and consequently lessens the detrimental effect of post-weld baking on the joint performance.

36 MATERIALS SCIENCE↗
NASA NTRS1980

Notched graphite polymimide composites at room and notched graphite polymide composites at room and elevated temperatures

The fracture behavior in graphite/polyimide (Gr/PI) Celion 6000/PMR-15 composites was characterized. Emphasis was placed on the correlation between the observed failure modes and the deformation characteristics of center-notched Gr/Pl laminates. Crack tip damage growth, fracture strength and notch sensitivity, and the associated characterization methods were also examined. Special attention was given to nondestructive evaluation of internal damage and damage growth, techniques such as acoustic emission, X-ray radiography, and ultrasonic C-scan. Microstructural studies using scanning electron microscopy, photomicrography, and the pulsed nuclear magnetic resonance technique were employed as well. All experimental procedures and techniques are described and a summary of representative results for Gr/Pl laminates is given.

Awerbuch, J.↗