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DOE OSTI2022

Coupled Hydromechanical Modeling of Induced Seismicity From CO 2 Injection in the Illinois Basin

Injection of CO 2 for geologic carbon sequestration into deep sedimentary formations involves fluid pressure increases that engage hydromechanical processes that can cause seismicity by activation of existing faults. In this work, we use a coupled multiphase fluid flow and geomechanical simulator to model spatiotemporal fluid pressure and stress changes in order to study the poroelastic effect of CO 2 injection on faults in crystalline basement rock below the injection zone. The seismicity rate along features interpreted to be basement faults is modeled using Dieterich's rate-and-state earthquake nucleation model. The methodology is applied to microseismicity detected during CO 2 injection into the Mount Simon formation during the Illinois Basin—Decatur Project. The modeling accurately captures an observed reduction in seismicity rate when the injection in the second well was into a slightly shallower zone above the base of the Mount Simon formation. Moreover, the modeling shows that it is important to consider poroelastic stress changes, in addition to fluid pressure changes for accurately modeling of the observed seismicity rate.

58 GEOSCIENCES↗

DOE OSTI2024

Energy Gap of the Even-Denominator Fractional Quantum Hall State in Bilayer Graphene

Bernal bilayer graphene hosts even-denominator fractional quantum Hall states thought to be described by a Pfaffian wave function with non-Abelian quasiparticle excitations. Here, in this study, we report the quantitative determination of fractional quantum Hall energy gaps in bilayer graphene using both thermally activated transport and by direct measurement of the chemical potential. We find a transport activation gap of 5.1 K at B = 12 T for a half filled N = 1 Landau level, consistent with density matrix renormalization group calculations for the Pfaffian state. However, the measured thermodynamic gap of 11.6 K is smaller than theoretical expectations for the clean limit by approximately a factor of 2. We analyze the chemical potential data near fractional filling within a simplified model of a Wigner crystal of fractional quasiparticles with long-wavelength disorder, explaining this discrepancy. Our results quantitatively establish bilayer graphene as a robust platform for probing the non-Abelian anyons expected to arise as the elementary excitations of the even-denominator state.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Artificial Intelligence-Driven Management of Sustainable Energy Resources: Visibility, Operation, and Control

The rapid global transition toward sustainable energy resources (SERs) is reshaping how modern power systems are observed, optimized, and controlled. While SERs have significantly advanced decarbonization, their weather dependence, variability, and inverter-dominated characteristics challenge traditional, centralized, and deterministic grid operation. At the same time, the proliferation of high-resolution data from inverters, smart meters, and sensors offers unprecedented visibility into system dynamics. Yet, it also exceeds the analytical capability of conventional model-based approaches. Artificial intelligence (AI) provides a new foundation for addressing these challenges by bridging physical laws with data-driven learning, enabling accurate state awareness, adaptive operation, and coordinated control across distributed assets. This article examines how AI transforms the management of SER-rich power systems along three critical dimensions: 1) enhancing visibility by inferring behind-the-meter (BTM) activities, assessing SER flexibility, and reconstructing system states from sparse or noisy measurements; 2) improving operation through AI-enhanced SER service provision, volt/var control (VVC), and dynamic operating envelopes (DOE) for efficiency and security; and 3) advancing control by embedding learning-based intelligence into inverter coordination, voltage and frequency regulation, and long-term dispatch. Together, these developments reveal how AI can convert the variability of SERs from an operational challenge into a source of flexibility, resilience, and intelligence, paving the way toward sustainable, adaptive, and self-optimizing power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

New Virtual Test Bed Capabilities: Virtual DOME Model and New Updates to Repository

The Department of Energy (DOE) Office of Nuclear Energy National Reactor Innovation Center accelerates the deployment of novel reactor concepts by establishing both physical and virtual spaces for building and testing various components, systems, and complete pilot plants. The Virtual Test Bed represents the virtual arm of the National Reactor Innovation Center and is a joint effort with the DOE Nuclear Energy Advanced Modeling and Simulation Program. The Virtual Test Bed mission is to accelerate the deployment of advanced reactors by facilitating the adoption of cutting-edge DOE advanced modeling and simulation tools to design, evaluate, and license reactors. This is primarily achieved by storing example challenge problems in an externally available repository and by developing models to fill the M&S gaps needed for potential demonstrators. Activities conducted this fiscal year focused on developing of a Demonstration of Microreactor Experiments shield model to help accelerate the confirmatory analysis required for the reactor demonstration. This model and workflow will allow developers to leverage advanced modeling and simulation tools to ensure their reactor demonstration concept will meet dose requirements and that the surrounding shield will stay within concrete temperature limits during steady-state and transient operation conditions. An initial model has been developed to evaluate the temperature distribution in the concrete shield during steady-state operation, including neutron and gamma heating effects. Various modeling strategies have been examined to understand their applicability and limitations with different reactor designs to make the workflow as reactor-agnostic as possible and computationally effective to maximize its usability. In addition to describing the Demonstration of Microreactor Experiments shield model and associated results, this report summarizes other accomplishments regarding repository maintenance and improvement and new external models hosted on the repository.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

A Framework for Characterizing the Initial Thermal Conditions of Light-Duty Vehicles in Response to Representative Utilization Patterns, Ambient Conditions, and Vehicle Technologies

It is widely understood that the thermal state of a light-duty vehicle at the beginning of a trip influences the vehicle performance throughout the drive cycle. Cold starts, or initial states with component temperatures near ambient conditions, are strongly correlated with reduced vehicle performance and energy efficiency and with increased emissions. Despite this understanding, there is little literature available that characterizes initial thermal states beyond empirical studies and simplified analyses of dwell times. We introduce a framework that considers vehicle activity patterns, including the previous drive event, duration of the previous dwell event, and relevant ambient conditions occurring during these events. Moreover, the framework allows for technologies to influence the prominence of cold starts and warm starts. An example application of the methodology using a powertrain model approach revealed the significance of all constituent factors: controlling for ambient conditions, the shortest dwell lengths corresponded to an average initial oil temperature of 70°C versus 23°C for the long dwell length simulations, and aggressive conditioning cycles corresponded to an average initial oil temperature of 51°C versus only 35°C for a short conditioning cycle. The coldest ambient conditions evaluated (-30°C to -10°C) produced a weighted initial oil temperature of 19°C versus 57°C for the warmest ambient conditions evaluated (30°C to 50°C). Finally, we introduce weighting factors that account for the real-world frequency of conditioning cycle and dwell length combinations. The procedure outlined may be useful for discovering real-world performance improvements associated with vehicle technologies, a topic of interest to both vehicle manufacturers and regulators.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS1990

A nonlinear optimization approach for disturbance rejection in flexible space structures

In this paper the design of an active control law for the rejection of persistent disturbances in large space structures is presented. The control system design approach is based on a deterministic model of the disturbances, with a model-based-compensator (MBC) structure, optimizing the magnitude of the disturbance that the structure can tolerate without violating certain predetermined constraints. In addition to closed-loop stability, the explicit treatment of state, control and control rate constraints, such as structural displacement, control actuator effort, and compensator time guarantees that the final design will exhibit desired performance characteristics. The technique is applied for the vibration damping of a simple two bay truss structure which is subjected to persistent disturbances, such as shuttle docking. Preliminary results indicate that the proposed control system can reject considerable persistent disturbances by utilizing most of the available control, while limiting the structural displacements to within desired tolerances. Further work, however, for incorporating additional design criteria, such as compensator robustness to be traded-off against performance specifications, is warranted.

Parlos, Alexander G.↗

NASA NTRS1990

Integrated model of G189A and Aspen-plus for the transient modeling of extravehicular activity atmospheric control systems

A computerized modeling tool, under development for the transient modeling of an extravehicular activity atmospheric control subsystem is described. This subsystem includes the astronaut, temperature control, moisture control, CO2 removal, and oxygen make-up components. Trade studies evaluating competing components and subsystems to guide the selection and development of hardware for lunar and Martian missions will use this modeling tool. The integrated modeling tool uses the Advanced System for Process Engineering (ASPEN) to accomplish pseudosteady-state simulations, and the general environmental thermal control and life support program (G189A) to manage overall control of the run and transient input output, as well as transient modeling computations and database functions. Flow charts and flow diagrams are included.

Kolodney, Matthew↗

NASA NTRS1994

X-ray color analysis of the spectra of active galactic nuclei

The identification and detection of X-ray absorption and emission features depends on the resolution and the signal-to-noise ratio (S/N) of the observation, the understanding of the instrument response, and the Galactic line-of-sight absorption. Since many of the active galactic nucleus (AGN) data sets are limited in their S/N and full modeling of the physical conditions is rather complicated, we suggest a new analysis method based on 'X-ray colors.' The two sets of X-ray colors, defined for low (ROSAT Position Sensitive Proportional Counter (PSPC)) and medium (Broad Band X-Ray Telescope (BBXRT)) and ASCA Solid-State Imaging Spectrometers (SIS) resolution experiments, are used to separate regions of different physical conditions in a two-dimensional color-color plane. They are similar but superior to previous methods using the X-ray 'hardness ratio' in being able to reveal more of the physical properties of the source. We illustrate the use of such diagrams by studying a number of AGNs suspected of showing absorption features. A sample of 14 AGNs observed by the ROSAT PSPC is presented which includes several objects with suspected 'warm absorbers' along the line-of-sight to the nucleus, several others exhibiting intrinsic continuum variations, and a number of control objects thought to be featureless. Our new observations show, for the first time, the color variation as a function of time for three of the Seyfert 1 sources: NGC 4051, Mrk 335, and Mrk 766. The variations suggest that in two sources we are witnessing real changes in continuum shape, while one (NGC 4051) is consistent with having a warm absorber. Four of the objects observed by BBXRT are reanalyzed using our X-ray colors. Out of these, we discuss in detail the case of NGC 4151 and show that the color-color analysis agrees very well with previous, detailed spectral fitting methods. In particular, we confirm that the observed BBXRT observation of this source is not consistent with the warm absorber explanation and must be interpreted as a combination of a variable hard component and another component. We explain the limitations in measuring low-energy emission features in ASCA SIS observations and present color-color diagrams which can be used as a powerful diagnostic tool in the analysis of data collected by this experiment.

Netzer, Hagai↗

NASA NTRS2008

Hydrogen Research for Spaceport and Space-Based Applications: Fuel Cell Projects

The activities presented are a broad based approach to advancing key hydrogen related technologies in areas such as fuel cells, hydrogen production, and distributed sensors for hydrogen-leak detection, laser instrumentation for hydrogen-leak detection, and cryogenic transport and storage. Presented are the results from research projects, education and outreach activities, system and trade studies. The work will aid in advancing the state-of-the-art for several critical technologies related to the implementation of a hydrogen infrastructure. Activities conducted are relevant to a number of propulsion and power systems for terrestrial, aeronautics and aerospace applications. Fuel cell research focused on proton exchange membranes (PEM), solid oxide fuel cells (SOFC). Specific technologies included aircraft fuel cell reformers, new and improved electrodes, electrolytes, interconnect, and seals, modeling of fuel cells including CFD coupled with impedance spectroscopy. Research was conducted on new materials and designs for fuel cells, along with using embedded sensors with power management electronics to improve the power density delivered by fuel cells. Fuel cell applications considered were in-space operations, aviation, and ground-based fuel cells such as; powering auxiliary power units (APUs) in aircraft; high power density, long duration power supplies for interplanetary missions (space science probes and planetary rovers); regenerative capabilities for high altitude aircraft; and power supplies for reusable launch vehicles.

Anderson, Tim↗

NASA NTRS2016

A Model for Straight and Helical Solar Jets: II. Parametric Study of the Plasma Beta

Context. Jets are dynamic, impulsive, well-collimated plasma events that develop at many different scales and in different layers of the solar atmosphere. Aims. Jets are believed to be induced by magnetic reconnection, a process central to many astrophysical phenomena. Within the solar atmosphere, jet-like events develop in many different environments, e.g. in the vicinity of active regions as well as in coronal holes, and at various scales, from small photospheric spicules to large coronal jets. In all these events, signatures of helical structure and/or twisting/rotating motions are regularly observed. The present study aims to establish that a single model can generally reproduce the observed properties of these jet-like events. Methods. In this study, using our state-of-the-art numerical solver ARMS, we present a parametric study of a numerical tridimensional magnetohydrodynamic (MHD) model of solar jet-like events. Within the MHD paradigm, we study the impact of varying the atmospheric plasma beta on the generation and properties of solar-like jets. Results. The parametric study validates our model of jets for plasma beta ranging from 10(sup 3) to 1, typical of the different layers and magnetic environments of the solar atmosphere. Our model of jets can robustly explain the generation of helical solar jet-like events at various beta less than or equal to 1. We show that the plasma beta modifies the morphology of the helical jet, explaining the different observed shapes of jets at different scales and in different layers of the solar atmosphere. Conclusions. Our results allow us to understand the energisation, triggering, and driving processes of jet-like events. Our model allows us to make predictions of the impulsiveness and energetics of jets as determined by the surrounding environment, as well as the morphological properties of the resulting jets.

Magnetic Field↗

NASA NTRS2018

Predictive Thermal Control (PTC) Technology to Enable Thermally Stable Telescopes

The Predictive Thermal Control (PTC) technology development project is a multiyear effort initiated in Fiscal Year (FY) 2017, to mature the Technology Readiness Level (TRL) of critical technologies required to enable ultra-thermally-stable telescopes for exoplanet science. During 2017/18 PTC has successfully progressed its three defined objectives: 1. Validate thermal optical performance models. 2. Derive thermal system stability specifications. 3. Demonstrate Predictive Thermal Control. by accomplishing or advancing three of its five quantifiable milestones: Milestone #1 (Complete): Created a high-fidelity STOP (Structural-Thermal-Optical-Performance) model of the1.5 meter ULE® AMTD (Advanced Mirror Technology Development)-2 mirror, including 3D CTE (Coefficient of Thermal Expansion) distribution and reflective coating, that predicts its optical performance response to steady-state and dynamic thermal gradients. Structural model was created using 3D X-Ray Computed Tomography; Milestone #2 (Complete): Derived specifications for thermal control system as a function of wavefront stability for a Vector Vortex Coronagraph; Milestone #3 (In-Process): Designed and started fabricating a predictive Thermal Control System for the AMTD-2 1.5 meter ULE® mirror that senses temperature changes and actively controls the mirror's thermal environment; Milestone #4 (In-Process): Performed preliminary STOP model validation tests of the 1.5-m ULE® mirror in a relevant thermal vacuum environment at the MSFC X-ray and Cryogenic Facility (XRCF) test facility; Milestone #5: Use validated model to perform trade studies to determine how thermo-optical performance can be optimized as a function of mirror design, material selection, mass, etc.

Stahl, H. Philip↗

NASA NTRSDate not supplied

NASA's New Wildland Fire Earth Observation Science & Applications Programmatic Developments

In 2021, the U.S. National Aeronautics & Space Administration (NASA) initiated new programmatic elements within the Science Mission Directorate (SMD) and the Aeronautics Research Mission Directorate (ARMD) focused on supporting wildland fire science and applications improvements, employing the vast array of NASA scientific knowledge, airborne and space-borne Earth Observations (EO) capabilities, technology development (sensor systems, etc.), and large framework modeling efforts. Within the Science Mission Directorate, the NASA Earth Science Division (ESD) will focus on improving our understanding of wildland fire through EO tools and applying rigorous-tested modeling and results of that research into operational use. The ESD Wildfire strategy is to invest in new technology and to better integrate NASA’s satellite, airborne, and ground-based observations with wildfire models to provide the wildfire stakeholders with the information they need to make informed decisions about the pre-, active-, and post-fire conditions. The Applied Science Program has restarted the Wildland Fire Applications Program with a focus on engaging wildland fire management and the fire science community in transitioning EO science efforts into routine use by land management entities at the local, state, national and international level. The NASA Aeronautics Research Mission Directorate will focus on arenas where their aeronautics science and engineering outcomes can benefit the fire management community as well, specifically in the innovative development of Uncrewed Aircraft systems, congested mixed-use platform airspace management issues, new platform configurations supporting wildland fire missions, and other aeronautics-related science / engineering capabilities which may benefit the fire management community. In total, these developments represent a major thrust forward, supporting the goals of utilizing NASA science to benefit humankind. This presentation will highlight the various wildland fire science focus areas identified through collaborations with the wildland fire science and management community and highlight the plans of this new NASA focus area.

NASA↗

DOE OSTI2021

Modeling and Analysis of the Transport and Disposal of Beryllium Moderator Blocks and Greater than Class C (GTCC) Waste

Radioactive waste in the United states is categorized based on its source, radioactivity, and security risk. The categorization method employed by the Nuclear Regulatory Committee (NRC) for low-level radioactive waste is not currently applied to any waste generated by the Department of Energy (DOE) or disposed of in DOE facilities. As a result, there is a large volume of DOE-generated waste with characteristics similar to the NRC’s “Greater than Class C” (GTCC) waste category which presently do not have a path for long-term disposal. Much of this waste cannot undergo the standard commercial disposition process due to it being categorized as Transuranic (TRU) waste under DOE guidelines, due to elevated concentrations of key fission products. Possible solutions to this dilemma are explored in the Environmental Impact Statement for the “Disposal of Greater-Than-Class-C Low Level Radioactive Wave” (EIS-0375). This paper analyzes several EIS possible paths for disposal for this “orphaned” waste. One example that highlights this categorization issue is the spent beryllium cladding that has been extracted from the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL) throughout its operational lifetime. These beryllium blocks surround the reactor’s main chambers and components and serve as neutron moderators. This paper will use this particular waste form to analyze the economic and technological viability of transporting and storing this material under the storage and transportation criteria of the Waste isolation Pilot Plant (WIPP), which was deemed the most feasible disposition path according to the EIS. The example of this waste form used in this paper that highlights this categorization issue is the spent beryllium cladding extracted from Idaho National Laboratory’s (INL) Advanced Test Reactor (ATR). These beryllium blocks surround the reactor’s components and serve as neutron moderators, and thus have accumulated high concentration of high-activity transuranic isotopes. This paper analyzed the viability of transporting and storing this material under the storage and transportation criteria of the five primary disposition paths covered in EIS-0375. An array of calculations was carried out to assess the viability of the various disposition paths for the beryllium shipments as well as other waste shipments that fall within the GTCC category. Modeling with MCNP 6.2 was conducted to determine whether the beryllium blocks could be safely stored and transported within a 72-B cask; the standard shipping container for remote-handled, transuranic waste, while also meeting regulatory limits at various disposition paths. A cost analysis of the transportation and long-term disposal paths mentioned in the EIS was also carried out using available data and information from similar waste shipments. Lastly, a geochemical analysis of the various geological repository discussed in the EIS was also carried out using the Geochemists Workbench Release 14. Long-term disposal of the beryllium blocks at the Waste Isolation Pilot Plant (WIPP) proved to be the most cost-effective long-term disposition option of the ones considered in the EIS. A dose rate calculation at both contact and remote-handling distances indicate that the analyzed beryllium shipments should not exceed the exposure limits at any of the considered locations. Greater-than-class-C waste has been left in a regulatory state of limbo for years, resulting in backlogs of inventory across several research sites in the United States. Due to its high activity and presence of transuranic isotopes, it is imperative to ensure that it remains inaccessible and sequestered both in its short-term interim as well as a long-term geologic time scale. The information and assessments done in the paper could potentially serve as a reference for any future shipments of this waste form at the WIPP facility as well as other disposition paths that may be considered in the future.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS2017

Using Data Assimilation Methods of Prediction of Solar Activity

The variable solar magnetic activity known as the 11-year solar cycle has the longest history of solar observations. These cycles dramatically affect conditions in the heliosphere and the Earth's space environment. Our current understanding of the physical processes that make up global solar dynamics and the dynamo that generates the magnetic fields is sketchy, resulting in unrealistic descriptions in theoretical and numerical models of the solar cycles. The absence of long-term observations of solar interior dynamics and photospheric magnetic fields hinders development of accurate dynamo models and their calibration. In such situations, mathematical data assimilation methods provide an optimal approach for combining the available observational data and their uncertainties with theoretical models in order to estimate the state of the solar dynamo and predict future cycles. In this presentation, we will discuss the implementation and performance of an Ensemble Kalman Filter data assimilation method based on the Parker migratory dynamo model, complemented by the equation of magnetic helicity conservation and long-term sunspot data series. This approach has allowed us to reproduce the general properties of solar cycles and has already demonstrated a good predictive capability for the current cycle, 24. We will discuss further development of this approach, which includes a more sophisticated dynamo model, synoptic magnetogram data, and employs the DART Data Assimilation Research Testbed.

Prediction↗

NASA NTRS2017

How the Emitted Size Distribution and Mixing State of Feldspar Affect Ice Nucleating Particles in a Global Model

The effect of aerosol particles on ice nucleation and, in turn, the formation of ice and mixed phase clouds is recognized as one of the largest sources of uncertainty in climate prediction. We apply an improved dust mineral specific aerosol module in the NASA GISS Earth System ModelE, which takes into account soil aggregates and their fragmentation at emission as well as the emission of large particles. We calculate ice nucleating particle concentrations from K-feldspar abundance for an active site parameterization for a range of activation temperatures and external and internal mixing assumption. We find that the globally averaged INP concentration is reduced by a factor of two to three, compared to a simple assumption on the size distribution of emitted dust minerals. The decrease can amount to a factor of five in some geographical regions. The results vary little between external and internal mixing and different activation temperatures, except for the coldest temperatures. In the sectional size distribution, the size range 24 micrometer contributes the largest INP number.

Perlwitz, Jan P.↗

DOE OSTI2025

Antiviral discovery using sparse datasets by integrating experiments, molecular simulations, and machine learning

Computational methods have demonstrated success in identifying virucidal agents, effectively contributing to the discovery of novel virucidal molecules. In this study, we developed a machine learning (ML) model, trained on a small dataset, to predict inhibitors of human enterovirus 71 (EV71), a pathological agent that causes severe disease in children and immunocompromised adults. Despite the dataset’s limitation, comprising of only 36 compounds tested, our ML framework demonstrated significant predictive capability. Notably, experimental validation revealed that five out of the eight compounds predicted by our model from the Chinese cosmetic material list exhibited virucidal activity. The inhibitor effects displayed by the main active compounds were further confirmed by molecular dynamics simulation. This underscores the potential of our AI-driven approach to bypass data constraints in identifying active molecules against viral pathogens.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Ion Size Effects on the Thermodynamic, Kinetic, and Mechanical Properties during Ion Exchange in Solid-State Electrolytes

Ion exchange offers a pathway to impose residual compressive stresses to mitigate the electro-chemo-mechanical cracking of solid-state electrolytes such as lithium lanthanum zirconium oxide. This study uses a coupled multiscale framework (integrating density functional theory (DFT), molecular dynamics (MD), and continuum modeling) to examine how exchange ion size influences stress, diffusion, fracture toughness, and electronic properties. Larger isovalent ions (Na + , Ag + , K + ) were exchanged with Li + , with DFT confirming their preference for octahedral 96h sites and a linear relationship between ion size and chemical free expansion coefficient. MD simulations reveal stress and concentration effects on exchange ion diffusivity at elevated temperatures, with Na + and Ag + maintaining favorable mobility while K + showing concentration-dependent clustering. Continuum modeling predicts the range of fracture strength improvements and the required ion exchange concentration profile. It was shown that a 5% surface exchange concentration can induce ∼0.6 GPa of surface compressive stress using Na + and ∼1.0 GPa of surface compressive stress using Ag + . On the other hand, larger ion exchange species may penalize Li + diffusivity by increasing the activation volume and activation energy. Interestingly, Na + has a negligible penalty on Li-ion diffusivity. The room temperature Li + ion diffusivity is reduced by ∼40% with Ag + ion exchange. Electronic band structure analysis shows no size-dependent change in the bandgap, though Ag + introduces localized defect states near the valence band maximum. This study highlights ion size as a key factor in optimizing LLZO properties, offering a framework to improve the solid-state battery performance.

Jagad, Harsh D. [Brown Univ., Providence, RI (Unit↗

DOE OSTI2026

Neural Posterior Estimation for Scalable and Accurate Inverse Parameter Inference in Li-Ion Batteries

Diagnosing the internal state of Li-ion batteries is critical for battery research, operation of real-world systems, and prognostic evaluation of remaining lifetime. By using physics-based models to perform probabilistic parameter estimation via Bayesian calibration, diagnostics can account for the uncertainty due to model fitness, data noise, and the observability of any given parameter. However, Bayesian calibration in Li-ion batteries using electrochemical data is computationally intensive even when using a fast surrogate in place of physics-based models, requiring many thousands of model evaluations. A fully amortized alternative is neural posterior estimation (NPE). NPE shifts the computational burden from the parameter estimation step to data generation and model training, reducing the parameter estimation time from minutes to milliseconds, enabling real-time applications. The present work shows that NPE can infer parameters equally or more accurately than Bayesian calibration, even if it leads to higher voltage reconstruction errors. We also demonstrate that the higher computational costs for data generation are tractable even in high-dimensional cases (ranging from 6 to 27 estimated parameters). The NPE method also offers several interpretability advantages over Bayesian calibration, such as local parameter sensitivity to specific regions of the voltage curve. The NPE method is demonstrated using an experimental fast charge dataset, with parameter estimates validated against measurements of loss of lithium inventory and loss of active material. The implementation is made available in a companion repository (https://github.com/NatLabRockies/BatFIT).

25 ENERGY STORAGE↗