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Results for “geometry optimization”

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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Thermal Spray toolpath development for a capped cylinder (“cake pan”) substrate

A near net shape coating is desired to be applied to the outer surface of a capped cylinder (“cake pan”) type substrate using thermal spray technology. A capped cylinder geometry is more complex than simple coupon-level substrate substrates (e.g., flat panels, cylinders) and thus requires a more complex toolpath to deposit a uniform coating. This report documents a practical theoretical approach to calculating relative torch-to-substrate speeds for coating the cylindrical, corner, and cap region of a rotating capped cylinder based on fundamental thermal spray toolpath principles. A preliminary experimental test deposited a thermal spray coating onto a mock substrate using toolpath speeds calculated by the theoretical approach proposed. The mock substrate was metallographically inspected to assess coating uniformity across the cylindrical, corner, and cap region. Inspection of the mock substrate revealed qualitatively uniform coating microstructure and thickness where theoretically predicted, demonstrating the viability of the proposed toolpath method and associated calculations. Pathways forward to optimizing coating uniformity at the cap center are proposed as near term suggested future work.

42 ENGINEERING↗
DOE OSTI2020

Utilizing Essential Symmetry Breaking in Auxiliary-Field Quantum Monte Carlo: Application to the Spin Gaps of the C 36 Fullerene and an Iron Porphyrin Model Complex

We present three distinct examples where phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC) can be reliably performed with a single-determinant trial wave function with essential symmetry breaking. Essential symmetry breaking was first introduced by Lee and Head-Gordon [ Phys. Chem. Chem. Phys. 2019, 21, 4763-4778, 10.1039/C8CP07613H]. We utilized essential complex and time-reversal symmetry breaking with ph-AFQMC to compute the triplet–singlet energy gap in the TS12 set. We found statistically better performance of ph-AFQMC with complex-restricted orbitals than with spin-unrestricted orbitals. We then showed the utilization of essential spin symmetry breaking when computing the singlet–triplet gap of a known biradicaloid, C 36 . ph-AFQMC with spin-unrestricted Hartree–Fock (ph-AFQMC+UHF) fails catastrophically even with spin-projection and predicts no biradicaloid character. With approximate Brueckner orbitals obtained from regularized orbital-optimized second-order Møller–Plesset perturbation theory (κ-OOMP2), ph-AFQMC quantitatively captures strong biradicaloid character of C 36 . Lastly, we applied ph-AFQMC to the computation of the quintet–triplet gap in a model iron porphyrin complex where brute-force methods with a small active space fail to capture the triplet ground state. We show unambiguously that neither triplet nor quintet is strongly correlated using UHF, κ-OOMP2, and coupled-cluster with singles and doubles (CCSD) performed on UHF and κ-OOMP2 orbitals. There is no essential symmetry breaking in this problem. By virtue of this, we were able to perform UHF+ph-AFQMC reliably with a cc-pVTZ basis set and predicted a triplet ground state for this model geometry. The largest ph-AFQMC in this work correlated 186 electrons in 956 orbitals. Our work highlights the utility, scalability, and accuracy of ph-AFQMC with a single-determinant trial wave function with essential symmetry breaking for systems mainly dominated by dynamical correlation with little static correlation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

High-Fidelity CFD Modeling of Cryogenic Hydrogen Isotope Extrusion for Fusion Reactor Pellet Fueling

This study investigates the extrusion processes of deuterium and protium using ANSYS-Polyflow. The geometries and computational fluid dynamics (CFD) settings closely replicate the experimental setups and data acquired from the extruder experiments at Oak Ridge National Laboratory (ORNL) for validation purposes. We explore the impacts of (1) slip versus non-slip boundary conditions and (2) the use of constant, temperature-, and shear rate–dependent viscosities, concluding that the implementation of non-slip wall boundary conditions combined with shear rate–dependent viscosity produced more accurate predictions. The simulations achieved excellent agreement with the experimental data, with relative differences of only 5% for deuterium, and 3% to 6% for protium. This is the first time that experimental extrusion data at ORNL have been accurately predicted through high-fidelity CFD modeling. In conclusion, the advancements offer valuable insights and a foundational modeling tool for optimizing pellet injectors for ITER and other future reactor-scale devices.

ANSYS-Polyflow↗
DOE OSTI2026

Geothermal Heat Pump System Showcase: Short-Term Validation of Borehole Heat Exchanger Performance from Field Data to Numerical Modeling: Preprint

Since 2011, a geothermal heat pump (GHP) system has been operating to provide space heating and cooling for the Solar Radiation and Research Laboratory building at the National Laboratory of the Rockies (NLR) in Golden, Colorado. The system consists of 23 vertical boreholes, each extending to a depth of 300 ft (91 m), connected to 11 water-to-air heat pump units and four circulation pumps. Between fiscal years 2023 and 2025, additional power meters and temperature sensors were retrofitted to support detailed system performance assessment and model development. This study presents preliminary monitoring results and the development of an initial numerical model of the borehole heat exchanger field. The model incorporated site-specific geometry, ground thermal properties derived from thermal response tests, and ambient temperatures, and simulated system behavior over a representative operating day in September. Model predictions of outlet temperatures were compared against corresponding field measurements. Results showed that modeling initialized with a simplified linear subsurface temperature gradient presents systematic discrepancies in outlet temperature, whereas incorporating depth-resolved borehole temperature measurements for initialization yields substantially improved agreement with observations. The findings highlight the sensitivity of short-term predictive modeling to the representation of initial subsurface thermal conditions and underscore the value of high-resolution field measurements for model calibration and validation. These preliminary results inform ongoing efforts to extend the modeling framework to longer time horizons and to refine monitoring and modeling strategies that support the design guidance and operational optimization of GHP systems in research and commercial buildings.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

An End-To-End Earthquake Detection Method for Joint Phase Picking and Association Using Deep Learning

Earthquake monitoring by seismic networks typically involves a workflow consisting of phase detection/picking, association, and location tasks. In recent years, the accuracy of these individual stages has been improved through the use of machine learning techniques. Here, in this study, we introduce a new end-to-end approach that improves overall earthquake detection accuracy by jointly optimizing each stage of the detection pipeline. We propose a neural network architecture for the task of multi-station processing of seismic waveforms recorded over a seismic network. This end-to-end architecture consists of three sub-networks: a backbone network that extracts features from raw waveforms, a phase picking sub-network that picks P- and S-wave arrivals based on these features, and an event detection sub-network that aggregates the features from multiple stations to associate and detect earthquakes across a seismic network. We use these sub-networks together with a shift-and-stack module based on back-projection that introduces kinematic constraints on arrival times, allowing the neural network model to generalize to different velocity models and to variable station geometry in seismic networks. We evaluate our proposed method on the STanford EArthquake Dataset (STEAD) and on the 2019 Ridgecrest, CA earthquake sequence. The results demonstrate that our end-to-end approach can effectively pick P- and S-wave arrivals and achieve earthquake detection accuracy rivaling that of other state-of-the-art approaches. Because our approach preserves information across tasks in the detection pipeline, it has the potential to outperform approaches that do not.

58 GEOSCIENCES↗
DOE OSTI2023

Covariant bit threads

We derive several new reformulations of the Hubeny-Rangamani-Takayanagi covariant holographic entanglement entropy formula. These include: (1) a minimax formula, which involves finding a maximal-area achronal surface on a timelike hypersurface homologous to D(A) (the boundary causal domain of the region A whose entropy we are calculating) and minimizing over the hypersurface; (2) a max V-flow formula, in which we maximize the flux through D(A) of a divergenceless bulk 1-form V subject to an upper bound on its norm that is non-local in time; and (3) a min U-flow formula, in which we minimize the flux over a bulk Cauchy slice of a divergenceless timelike 1-form U subject to a lower bound on its norm that is non-local in space. The two flow formulas define convex programs and are related to each other by Lagrange duality. For each program, the optimal configurations dynamically find the HRT surface and the entanglement wedges of A and its complement. The V-flow formula is the covariant version of the Freedman-Headrick bit thread reformulation of the Ryu-Takayanagi formula. We also introduce a measure-theoretic concept of a “thread distribution”, and explain how Riemannian flows, V-flows, and U-flows can be expressed in terms of thread distributions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Comparison of the Energy-Transfer Rates in Structural and Spectral Variants of the B800–850 Complex from Purple Bacteria

Photosynthetic light harvesting can occur with a remarkable near-unity quantum efficiency. The B800–850 complex, also known as light-harvesting complex 2 (LH2), is the primary light-harvesting complex in purple bacteria and has been extensively studied as a model system. The bacteriochlorophylls of the B800–850 complex are organized into two concentric rings, known as the B800 and B850 rings. However, depending on the species and growth conditions, the number of constituent subunits, the pigment geometry, and the absorption energies vary. While the dynamics of some B800–850 variants have been exhaustively characterized, others have not been measured. Furthermore, a direct and simultaneous comparison of how both structural and spectral differences between variants affect these dynamics has not been performed. In this work, we utilize ultrafast transient absorption measurements to compare the B800 to B850 energy-transfer rates in the B800–850 complex as a function of the number of subunits, geometry, and absorption energies. The nonameric B800–850 complex from Rhodobacter (Rb.) sphaeroides is 40% faster than the octameric B800–850 complex from Rhodospirillum (Rs.) molischianum, consistent with structure-based predictions. In contrast, the blue-shifted B800–820 complex from Rs. molischianum is only 20% faster than the B800–850 complex from Rs. molischianum despite an increase in the spectral overlap between the rings that would be expected to produce a larger increase in the energy-transfer rate. These measurements support current models that contain dark, higher-lying excitonic states to bridge the energy gap between rings, thereby maintaining similar energy-transfer dynamics. Altogether, these results demonstrate that energy-transfer dynamics in the B800–850 complex are robust to the spectral and structural variations between species used to optimize energy capture and flow in purple bacteria.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Surrogate models for development of unconventional shale reservoirs by an integrated numerical approach of hydraulic fracturing, flow and geomechanics, and machine learning

We develop well-completion surrogate models by taking an integrated workflow of hydraulic fracturing, flow, geomechanics, and machine learning simulation. There are three steps in the proposed workflow. First, history-matching processes are conducted with the field data including pumping and production data for characterization. Second, full-physics simulation is performed with various parameters of the field development (e.g., cluster spacing, clusters per stage, pumping rates and times, amount of proppant, and well spacing) to generate multiple simulation results by changing the parameters of the completion design with well-known hydraulic fracturing, reservoir, geomechanics simulators to calculate fracture geometry, reservoir depressurization, induced stress changes. The workflow is demonstrated over a field in the Southern Midland Basin. Here, we take two completion scenarios: a single well case followed by a multi-well case. Finally, a Long Short-Term Memory (LSTM) machine learning algorithm is employed to create surrogate models that can replicate the full-physics simulation results. Furthermore, results show that the trained models applied in the single well and multi-well cases for a particular geological system can provide good accuracy close to those provided by full-physics simulations. Specifically, the site-specific surrogate models can predict fracture parameters (length, height, and surface area) and cumulative production accurately with computational efficiency, suggesting our proposed workflow can be used as a pragmatic tool for expediting the well completion optimization process.

Geomechanics↗
DOE OSTI2020

Compound pulse characteristics of a heterogeneous composite scintillator in a gamma-ray field

An important aspect of radiation detection in scintillators is the time dependence of emitted fluorescence, which results in characteristic measured pulse shape. In some materials, a relatively strong dependence of the scintillation pulse shape on stopping power exists, which can provide reliable identification of the incident particle. An alternative method to realize particle identification is by combining materials with different fluorescence lifetimes into heterogeneous structures. Such composite scintillators derive their properties from both the constituent material characteristics and the geometry of the composite structure. In composite scintillators with a high degree of heterogeneous loading, a superposition of fluorescence contributions originating in multiple materials, which is observed as single waveform with an intermediate pulse shape, may affect its ability to reject rays. We measure the time dependence of light output from a scintillator composed of 6 Li-containing glass shards and scintillating polyvinyl toluene and identify events that exhibit such compound behavior when exposed to rays and fast neutrons. We develop a modeling and simulation framework that reproduces the pulse shapes in heterogeneous scintillators and use it study the effect that the weight percentage of 6 Li glass has on rejection. The modeling framework is applied to the experimentally studied scintillator, finding a good agreement. Here, the developed modeling and simulation approach will help optimize the design of heterogeneous scintillators to meet the desired trade-o between neutron capture efficiency and -ray rejection.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Additive Manufacturing of Cryogenic Austenitic Steel JK2LB via Wire-Fed Directed Energy Deposition (DED) for Fusion Energy Applications

This study explores the feasibility of fabricating cryogenic austenitic steel JK2LB via both laser-based directed energy deposition (laser-DED) and arc-based directed energy deposition (arc-DED) additive manufacturing processes for potential application in fusion reactors. JK2LB, a low-nickel, high-manganese stainless steel developed for ITER, offers excellent cryogenic toughness, radiation resistance, and decay-to-clearance characteristics. Although JK2LB was originally designed to endure cyclic stresses at cryogenic temperatures in tokamaks, its low-temperature mechanical integrity and radiation tolerance also make it a promising candidate for structural components, such as the coil case/support structure in nonplanar high-temperature superconducting magnet assemblies in stellarators. Directed energy deposition (DED) additive manufacturing was selected for this study due to its capability to fabricate large structures with complex geometries. Here, to address the long lead time and high cost associated with acquiring conventional JK2LB solid wire, JK2LB powder-cored wire was developed as the feedstock material. Testing blocks were then fabricated using both wire-fed laser-DED and arc-DED processes. Microstructural and compositional analyses revealed that both DED approaches yield fully austenitic phase and columnar grain structures. Mechanical testing at room temperature revealed that both DED routes achieved yield strength and elongation comparable to those of conventionally processed JK2LB via vacuum melting, electroslag remelting, extrusion, and drawing, though ultimate tensile strength was reduced due to Mn loss and large columnar grains. As a study mainly focusing on the additive manufacturing process, this work demonstrates the potential of additive manufacturing for fusion energy applications and provides a basis for optimization and future cryogenic mechanical evaluation.

Cryogenic steel↗
DOE OSTI2023

Enabling off-highway diesel engine downsizing and performance improvement using electrically assisted turbocharging

Internal combustion engine (ICE) downsizing through various turbocharging configurations is generally known by the powertrain design community as an effective means to reduce frictional losses, increase waste heat recovery, and improve fuel efficiency while increasing engine power density. However, often is the case that turbocharging strategies, including variable geometry turbochargers, and regulated two-stage turbochargers, incur the performance tradeoff between transient response and fuel economy (pumping losses) at high engine speeds. For off-highway vehicles having particularly transient and high-powered duty cycles, efforts to improve this tradeoff and increase operational flexibility have turned to evaluating various electrified air system architectures. In this study, a 4.5 L diesel-ICE configured with an electrically driven compressor (eBooster ® ) is placed in series with a conventional turbocharger and integrated into a 48 V mild-hybrid powertrain architecture. The objective of this powertrain configuration is to enable engine downsizing by 34%, replacing the current 6.8 L ICE platform with the hybridized 4.5 L ICE concept. The commercial 1-D simulation software GT-SUITE is used for powertrain system development and system optimization. Development and validation of the GT-SUITE model and air system controls is concurrently supported through experimental data collection. The simulation model development includes using machine learning methods for optimizing exhaust gas dilution, injection timing, and eBooster ® power to improve steady-state and transient brake-specific fuel consumption while minimizing criteria pollutant emissions. It was found that total specific fluid consumption over the standardized non-road transient engine duty cycle could be reduced by 18% over the current 6.8 L engine by using an optimized eBoosted 4.5 L engine. The hybridized 4.5 L engine concept concurrently showed sufficient transient response capability and nearly an order of magnitude reduction in duty cycle total soot production.

25 ENERGY STORAGE↗
DOE OSTI2020

Revolutionizing Turbine Cooling with Micro-Architectures Enabled by Direct Metal Laser Sintering

The objective of this research effort was to explore innovative cooling architectures enabled by additive manufacturing techniques for improved turbine cooling performance. The ability to create complex internal geometries was leveraged to better distribute coolant as well as to integrate inherently unstable flow devices to enhance internal and external heat transfer. This was accomplished with a multi-faceted approach including analytical, experimental, and computational components. This final report documents progress during the total 4.25 year effort that was extended (at no additional cost) from the original 3-year cooperative agreement. Prior to starting the project, significant effort was invested in investigating innovative cooling designs from the open literature. When the project started, we quickly down-selected to 4 configurations: impingement jet fluidic oscillators (for internal leading edge cooling), reverse film cooling (for pressure surface), sweeping film cooling jets (for suction surface), and trailing edge slot cooling with microchannels. During the 2nd year, the reverse film cooling design was shown to be sub-optimal and work on that topic was halted. The three remaining technologies were integrated into a large scale nozzle guide vane and installed into a low-speed linear cascade facility for further interrogation. Initial results showed the sweeping film cooling jets (on the suction surface) to be the most promising technology compared to a baseline diffusion shaped film hole (777 design). The benefit was particularly evident at high blowing ratios (>1.5) when the 777 coolant film separated from the downstream surface. Benefits were also evident at elevated freestream turbulence levels. The leading edge cooling with unsteady jets was less effective in terms of peak or average cooling – however it was superior to round hole impingement cooling in terms of spatial uniformity. Finally, the trailing edge cooling design with micro-channels was scrapped in favor of a pinned arrangement with centerbody. During the 3rd year, the same three technologies were integrated into a transonic linear cascade for an assessment of compressibility effects. Again, the sweeping film cooling jets proved superior at high blowing ratios while the unsteady leading edge impingement and trailing edge pin-fins with centerbody designs yielded mixed results. Finally, during the 4th and final year, these 3 technologies were integrated into a direct metal laser sintered (DMLS) nozzle guide vane for testing in a high temperature, transonic annular vane cascade. The facility matches the flow temperature, Mach number, and coolant pressure ratios of an actual gas turbine. Before doing this, an additional series of tests were completed to validate a redesigned trailing edge cooling architecture. This final design included a centerbody with triangular pins between the centerbody and the vane external skin. The majority of these triangular pins are fabricated with a 30% gap to the centerbody – reducing their pressure drop considerably while still providing excellent heat transfer augmentation. This additional test campaign required an additional 3-month extension request to complete testing in the high temperature NGV test facility (Turbine Reacting Flow Rig – TuRFR). Testing of the DMLS vane in TuRFR pitted the 3 innovative cooling technologies against more traditional technologies (shaped 777 film hole, round impingement jet, and full pin arrangement in the trailing edge. The sweeping film cooling jets (on the suction surface) showed approximately 15% improvement in overall effectiveness compared to the 777 film hole while the trailing edge showed up to 20% improvement. The leading edge impingement was disappointing with a substantially lower effectiveness than traditional direct impingement. In summary, the study was successful in demonstrating that DMLS-enabled cooling technologies can yield significant gains in cooling performance.

03 NATURAL GAS↗
DOE OSTI2021

Hybrid Large Eddy Simulation/Reynolds-Averaged Navier–Stokes Analysis of a Premixed Ethylene-Fueled Dual-Mode Scramjet Combustor

Hydrocarbon fuels offer optimal high energy per volume for scramjet applications for sustained hypersonic flight but require additional residence time due to slower ignition delays (compared with hydrogen fuel). The injection of ethylene at the start of the isolator of a dual-mode scramjet combustor, operating in ramjet mode, allows sufficient mixing to achieve efficient premixed turbulent combustion. A cavity flameholder anchors the flame, supplying sufficient radicals to sustain a stable flame in the high-speed environment. This work investigates flame structure and stabilization limits of a new configuration with a scaled-down cavity embedded in the flow path of the combustor with a strut and insert. The cavity is reduced in size by one-third to enable eventual direct numerical simulations of the flame stabilization process. This work, however, focuses on modeling the full isolator/combustor geometry using a hybrid large eddy simulation/Reynolds-averaged Navier–Stokes simulation strategy. Additionally, particle image velocimetry, planar laser-induced fluorescence, coherent anti-Stokes Raman spectroscopy, and pressure measurements are compared with numerical predictions to analyze and characterize the conditions within the combustor, including flame structure, flow velocities, species composition, and wall pressure. An adjustable air throttle in the extender is able to control the placement of the shock train in the isolator and maintain a stable flame at various equivalence ratios. The simulations show reasonably good agreement with the experimental scalar and velocity data and predict a flame angle consistent with premixed turbulent flame-speed correlations.

42 ENGINEERING↗
DOE OSTI2026

First-Principles Evaluation of Proton Hopping in Tetrahedral Oxide Motifs

Proton-conducting oxides (PCOs) are important materials used as ionic conductors for energy conversion technologies. Existing research efforts on PCO optimization and discovery generally focus on complex perovskite-based oxides that require doping and alloying to engineer oxygen deficiency and high proton conductivity. However, the variety of chemical compositions and coordination environments in oxides poses challenges for efficient materials design. In this computational study, we construct a database of simplified motifs to elucidate the relationship between fundamental materials chemistry and proton kinetics. Specifically, we focus on the zincblende crystal structure as a proxy for tetrahedral metal–oxide (M–O) coordination environments. We systematically quantified the effects of cation type, oxidation states, and M–O bond lengths on the proton hopping barrier, and found that strong M–O bonds and metal cations with large and variable oxidation states (e.g., Mo 6+ , V 5+ ) lead to smaller proton hopping barriers. By mapping the candidate cations and their preferred bond geometries onto materials databases such as the Inorganic Crystal Structure Database (ICSD) and Materials Project, we identified real materials containing the corresponding metal–oxide units. In general, we observed good agreement between the calculated proton hopping barriers obtained in real crystal structures and those predicted by our motif database. We also discuss the limitations of our model and possible future extensions to improve its predictive capabilities. Overall, our model provides a first step for the rational design and quick screening of energy-efficient PCOs.

organic↗
DOE OSTI2026

High-rate heavy-ion tracking using MWPCs and PPACs with an Anti-Discharge Unit

This work reports on the development of two robust, heavy-ion beam tracking concepts operating at low pressure (< 15 Torr) for high rate applications (> 200 kHz). The first concept consists of a Multi-Wire Proportional Counter (MWPC) with a central anode consisting of 12 μm Au-plated Tungsten wires spaced 1 mm from each other. The anode grid is sandwiched between two segmented cathodes aligned orthogonally in the two dimensions for (x,y) particle localization. The second detector is a Parallel-Plate Avalanche Counter (PPAC) that uses the same readout geometry as the MWPC, but replaces the wire anode with a 150 nm silver layer deposited on both sides of a thin (< 1 mg/cm 2 ) polypropylene foil. Additionally, the bias circuitry for the PPAC anode central foil is equipped with an Anti-Discharge Unit (ADU) to prevent transitions from proportional operation to streamer formation, thereby avoiding damaging discharges. The localization capability of both detectors was tested with a low-rate alpha-particle source (241-Am). A position resolution of < 1 mm (FWHM) was achieved under stable, high-gas-gain (> 1000) operating conditions. Their performance in terms of detection efficiency as a function of the isotope charge (Z) was determined by irradiating the detectors with a cocktail beam (Z ≤ 15) with energy of ∼ 100 MeV/u. Full detection efficiency is maintained for all available fragments under optimal operational conditions (i.e., voltage bias). Full detection efficiency was achieved at rates above 200 kHz by irradiating the detectors with a 1 cm diameter 238 U beam at an energy of 143 MeV/u.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
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↗
DOE OSTI2024

DEM simulation of the compression of crushable sand: does the initial particle shape matter?

Advances in DEM modeling, combined with high-resolution X-ray tomography, opened the way for computer models based on virtual replicas of the particles which preserve nearly all facets of their geometry. This leads to simulation advantages, but also high computational costs. Here we tackle a question stemming from this trend: how accurate should particle models be to ensure accuracy? We address this question for the case of the compression of crushable sand. LS-DEM was used to generate three models of Ottawa sand (exact replicas, ellipsoids, and spheres) from digital images of its grains. Compression-induced crushing was simulated for all sets by tracking evolving size and shape distribution. The results confirm that exact replicas provide the closest match of the measurements. However, intermediate degrees of rendering (e.g. ellipsoids preserving volume and aspect ratio of the real grains) led to satisfactory results only marginally different from those of exact replicas. In conclusion, these findings provide an example of the protocols that may be followed to identify the optimal degree of particle approximation which should be regarded as mandatory to achieve a conscious, sustainable use of computational resources.

58 GEOSCIENCES↗