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At least 163 records · Page 9

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DOE OSTI2025

Electrode strain dynamics in layered intercalation battery cathodes

Rechargeable batteries using electrodes based on intercalation chemistry exhibit notable cyclability, yet their performance still suffers from chemomechanical degradation. In this study, by combining a suite of operando microscopy methods, we explored electrode strain evolution and observed intricate particle cluster rearrangement under electrochemical stimuli. We show that early-stage strain accumulation in intercalation cathodes occurs during the period of interparticle charge transfer and redox reactions stemming from asynchronous coupling and decoupling between chemical (de)intercalation and physical grain motion. This interplay drives heterogeneous redox activity, localized charge equilibration, and multiscale strain cascades that propagate through an asynchronous network of chemical-mechanical interactions. Together, these findings reveal how collective particle dynamics and hierarchical strain transmission dictate electrode deformation and degradation in intercalation cathodes.

25 ENERGY STORAGE↗

NASA NTRS2004

Complexity Induced Anisotropic Bimodal Intermittent Turbulence in Space Plasmas

The "physics of complexity" in space plasmas is the central theme of this exposition. It is demonstrated that the sporadic and localized interactions of magnetic coherent structures arising from the plasma resonances can be the source for the coexistence of nonpropagating spatiotemporal fluctuations and propagating modes. Non-Gaussian probability distribution functions of the intermittent fluctuations from direct numerical simulations are obtained and discussed. Power spectra and local intermittency measures using the wavelet analyses are presented to display the spottiness of the small-scale turbulent fluctuations and the non-uniformity of coarse-grained dissipation that can lead to magnetic topological reconfigurations. The technique of the dynamic renormalization group is applied to the study of the scaling properties of such type of multiscale fluctuations. Charged particle interactions with both the propagating and nonpropagating portions of the intermittent turbulence are also described.

Chang, Tom↗

DOE OSTI2025

Prediction of cccDNA dynamics in hepatitis B patients by a combination of serum surrogate markers

Quantification of intrahepatic covalently closed circular DNA (cccDNA) is a key for evaluating an elimination of hepatitis B virus (HBV) in infected patients. However, quantifying cccDNA requires invasive methods such as a liver biopsy, which makes it impractical to access the dynamics of cccDNA in patients. Although HBV RNA and HBV core-related antigens (HBcrAg) have been proposed as surrogate markers for evaluating cccDNA activity, they do not necessarily estimate the amount of cccDNA. Here, we employed a recently developed multiscale mathematical model describing intra- and intercellular viral propagation and applied it in HBV-infected patients under treatment. We developed a model that can predict intracellular HBV dynamics by use of extracellular viral markers, including HBsAg, HBV DNA, and HBcrAg in peripheral blood. Importantly, the model prediction of the amount of cccDNA in patients over time was confirmed to be well correlated with the data for quantified cccDNA by paired liver biopsy. Thus, our method combining classic and emerging surrogate markers enables us to predict the decay dynamics of cccDNA in patients undergoing treatment.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2002

Dynamical Approach Study of Spurious Numerics in Nonlinear Computations

The last two decades have been an era when computation is ahead of analysis and when very large scale practical computations are increasingly used in poorly understood multiscale complex nonlinear physical problems and non-traditional fields. Ensuring a higher level of confidence in the predictability and reliability (PAR) of these numerical simulations could play a major role in furthering the design, understanding, affordability and safety of our next generation air and space transportation systems, and systems for planetary and atmospheric sciences, and in understanding the evolution and origin of life. The need to guarantee PAR becomes acute when computations offer the ONLY way of solving these types of data limited problems. Employing theory from nonlinear dynamical systems, some building blocks to ensure a higher level of confidence in PAR of numerical simulations have been revealed by the author and world expert collaborators in relevant fields. Five building blocks with supporting numerical examples were discussed. The next step is to utilize knowledge gained by including nonlinear dynamics, bifurcation and chaos theories as an integral part of the numerical process. The third step is to design integrated criteria for reliable and accurate algorithms that cater to the different multiscale nonlinear physics. This includes but is not limited to the construction of appropriate adaptive spatial and temporal discretizations that are suitable for the underlying governing equations. In addition, a multiresolution wavelets approach for adaptive numerical dissipation/filter controls for high speed turbulence, acoustics and combustion simulations will be sought. These steps are corner stones for guarding against spurious numerical solutions that are solutions of the discretized counterparts but are not solutions of the underlying governing equations.

Yee, H. C.↗

DOE OSTI2025

A rheological model for loose sands with insights from DEM

A rheological model for loose granular media is developed to capture both solid-like and fluid-like responses during shearing. The proposed model is built by following the mathematical structure of an extended Kelvin–Voigt model, where an elastic spring and plastic slider act in parallel to a viscous damper. This arrangement requires the partition of the total stress into rate-independent and rate-dependent stress components. To model the solid-like behavior, a simple frictional plasticity model is adopted without modifications, thus contributing to the rate-independent stress. Instead, the fluid-like or rate-dependent stress is further decomposed into deviatoric and volumetric parts, by proposing a new formulation based on a combination of the μ(I) relation, originally developed under pressure-controlled shear, with a pressure-shear rate relation derived under volume-controlled shear. The proposed formulation allows the model to capture both the increase in the friction coefficient and the enhanced dilation at high shear rates. High-fidelity simulation data, obtained from discrete element method and multiscale modelling, are used to evaluate the performance of the proposed constitutive model. The model provides accurate results under both drained and undrained simple shear paths across a wide range of shear rates. Furthermore, it successfully reproduces at much lower computational cost the flowslide mobility computed through multiscale simulations, which is primarily regulated by the shear rate dependence of the material properties during the dynamic runout stage.

Elasticity↗

NASA NTRS2005

Image Enhancement, Image Quality, and Noise

The Multiscale Retinex With Color Restoration (MSRCR) is a non-linear image enhancement algorithm that provides simultaneous dynamic range compression, color constancy and rendition. The overall impact is to brighten up areas of poor contrast/lightness but not at the expense of saturating areas of good contrast/brightness. The downside is that with the poor signal-to-noise ratio that most image acquisition devices have in dark regions, noise can also be greatly enhanced thus affecting overall image quality. In this paper, we will discuss the impact of the MSRCR on the overall quality of an enhanced image as a function of the strength of shadows in an image, and as a function of the root-mean-square (RMS) signal-to-noise (SNR) ratio of the image.

Rahman, Zia-ur↗

DOE OSTI2025

Mechanistic Multiscale Uncertainty Propagation in Support of Accelerated Fuel Qualification

Taking a nuclear fuel concept through the research, development, and qualification stages has historically taken on the order of 20 to 25 years because of extensive irradiation tests required for a variety of conditions. The concept of accelerated fuel qualification (AFQ) has been proposed to increase the innovation pace for nuclear fuels. The goal of AFQ is not to replace the traditional qualification approach but rather to reduce the total number of experiments required to ensure approval from the regulatory authority. Of the many AFQ approaches being explored, advanced modeling—and, in particular, mechanistic modeling—is in a uniquely cross-cutting position to reduce the number of required integral tests through the inclusion of separate-effects testing, while helping to extrapolate reactor performance during rare events. We make the case that propagation of uncertainty through various computational length scales helps contextualize mechanistic modeling. We will utilize UO 2 fission gas diffusion predictions from the atomistically informed cluster dynamics code Centipede to inform fuel performance rodlet simulations using the BISON finite element code as the metric for showing how multiscale mechanistic uncertainty quantification can help reduce uncertainty in fuel performance. In conclusion, by quantifying uncertainty and its reduction through multiscale modeling, the qualification process may be accelerated through the reduction of costly irradiation experiments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Adaptive tau-leaping methods for microscopic-lattice kinetic Monte Carlo simulations

Traditional Kinetic Monte Carlo (KMC) approaches, rooted in Gillespie’s stochastic simulation algorithm, become computationally demanding in systems with a large range of timescales. The goal of this work is to propose and study new adaptive lattice-KMC time integration strategies for spatially non-uniform systems. To that end, two novel adaptive tau-leaping methods and their corresponding time integration strategies are developed based on the idea of the “n-fold” direct KMC method. These strategies allow for the simultaneous execution of multiple reactions, advancing time by adaptively selected coarse increments. We present numerical experiments comparing the proposed methods with existing approaches in a catalytic surface kinetics application involving ammonia decomposition.

Bimolecular reactions↗

NASA NTRS2004

Complexity and Intermittent Turbulence in Space Plasmas

Sporadic and localized interactions of coherent structures arising from plasma resonances can be the origin of "complexity" of the coexistence of non- propagating spatiotemporal fluctuations and propagating modes in space plasmas. Numerical simulation results are presented to demonstrate the intermittent character of the non-propagating fluctuations. The technique of the dynamic renormalization-group is introduced and applied to the study of scale invariance of such type of multiscale fluctuations. We also demonstrate that the particle interactions with the intermittent turbulence can lead to the efficient energization of the plasma populations. An example related to the ion acceleration processes in the auroral zone is provided.

Chang, Tom↗

NASA NTRS2007

Maneuver Recovery Analysis for the Magnetospheric Multiscale Mission

The use of spacecraft formations creates new and more demanding requirements for orbit determination accuracy. In addition to absolute navigation requirements, there are typically relative navigation requirements that are based on the size or shape of the formation. The difficulty in meeting these requirements is related to the relative dynamics of the spacecraft orbits and the frequency of the formation maintenance maneuvers. This paper examines the effects of bi-weekly formation maintenance maneuvers on the absolute and relative orbit determination accuracy for the four-spacecraft Magnetospheric Multiscale (MMS) formation. Results are presented from high fidelity simulations that include the effects of realistic orbit determination errors in the maneuver planning process. Solutions are determined using a high accuracy extended Kalman filter designed for onboard navigation. Three different solutions are examined, considering the effects of process noise and measurement rate on the solutions.

Volle, Michael↗

NASA NTRS2007

Maneuver Recovery Analysis for the Magnetospheric Multiscale Mission

Gramling, Cheryl↗

NASA NTRS2016

Multiscale Modeling of Carbon/Phenolic Composite Thermal Protection Materials: Atomistic to Effective Properties

Next generation ablative thermal protection systems are expected to consist of 3D woven composite architectures. It is well known that composites can be tailored to achieve desired mechanical and thermal properties in various directions and thus can be made fit-for-purpose if the proper combination of constituent materials and microstructures can be realized. In the present work, the first, multiscale, atomistically-informed, computational analysis of mechanical and thermal properties of a present day - Carbon/Phenolic composite Thermal Protection System (TPS) material is conducted. Model results are compared to measured in-plane and out-of-plane mechanical and thermal properties to validate the computational approach. Results indicate that given sufficient microstructural fidelity, along with lowerscale, constituent properties derived from molecular dynamics simulations, accurate composite level (effective) thermo-elastic properties can be obtained. This suggests that next generation TPS properties can be accurately estimated via atomistically informed multiscale analysis.

Materials Science↗

NASA NTRSDate not supplied

A Partitioned -Task Parallel Implementation of the NASA Multiscale Analysis Tool for High Performance Computing

The NASA Multiscale Analysis Tool (NASMAT) is a “plug and play” software package that allows users to conduct massively multiscale modeling of hierarchical and nonlinear materials. This work extends the scalability and improves the High Performance Computing friendliness of NASMAT by adopting a Partitioned Task-Parallel approach. Interoperability of NASMAT with external software is enhanced through preCICE, a open source library for multiphysics coupling in a partitioned manner. Enhancement through preCICE allows for easy integration of NASMAT to other macro solvers and dissociates the parallelization strategy adopted within NASMAT from the macro solver. The task-parallel framework based on Master-Worker approach is implemented as the parallelization scheme. The scheme accounts for hierarchy of multiple scales (task-dependence) and heterogeneous nature (dynamic load balancing) of computations. The applicability and scalability of the framework will be evaluated by analyzing large scale engineering problems through massively multiscale methods.

NASMAT↗

NASA NTRS2009

A Multiscale Modeling System: Developments, Applications, and Critical Issues

The foremost challenge in parameterizing convective clouds and cloud systems in large-scale models are the many coupled dynamical and physical processes that interact over a wide range of scales, from microphysical scales to the synoptic and planetary scales. This makes the comprehension and representation of convective clouds and cloud systems one of the most complex scientific problems in Earth science. During the past decade, the Global Energy and Water Cycle Experiment (GEWEX) Cloud System Study (GCSS) has pioneered the use of single-column models (SCMs) and cloud-resolving models (CRMs) for the evaluation of the cloud and radiation parameterizations in general circulation models (GCMs; e.g., GEWEX Cloud System Science Team 1993). These activities have uncovered many systematic biases in the radiation, cloud and convection parameterizations of GCMs and have led to the development of new schemes (e.g., Zhang 2002; Pincus et al, 2003; Zhang and Wu 2003; Wu et al. 2003; Liang and Wu 2005; Wu and Liang 2005, and others). Comparisons between SCMs and CRMs using the same large-scale forcing derived from field campaigns have demonstrated that CRMs are superior to SCMs in the prediction of temperature and moisture tendencies (e.g., Das et al. 1999; Randall et al 2003b; Xie et al. 2005).

Tao, Wei-Kuo↗

DOE OSTI2025

Multiscale Modeling Framework for Lithium Nucleation in 3D Porous Carbon Anodes

Porous carbon scaffolds offer a promising route for mitigating non-uniform lithium (Li) plating to enhance the safety and longevity of Li metal batteries. However, the influence of microstructural morphology on Li nucleation is not well understood. Here, we present a multiscale modeling framework to investigate how the porous microstructure of carbon materials affects Li nucleation behavior. Ab initio molecular dynamics simulations quantify the nucleation energy barriers of Li on graphene as a function of Li content, surface curvature, and applied potential, providing key parameters for a classical nucleation theory (CNT) model. From macroscale half-cell simulations, we obtained Li concentration and electrical potential profiles to define boundary conditions for mesoscopic simulations. At the mesoscale, three distinct synthetic 3D microstructures with different porosities and characteristic feature sizes are generated to resolve local distributions of Li flux, current density, and mechanical stress. These outputs are integrated into the CNT model to map spatial variation in nucleation rates. Our findings reveal trade-offs between suppressing nucleation rates and achieving spatial uniformity, offering design guidelines for optimizing porous carbon anodes to balance nucleation control and mechanical integrity.

Materials science↗

NASA NTRS2000

Fast Particle Methods for Multiscale Phenomena Simulations

We are developing particle methods oriented at improving computational modeling capabilities of multiscale physical phenomena in : (i) high Reynolds number unsteady vortical flows, (ii) particle laden and interfacial flows, (iii)molecular dynamics studies of nanoscale droplets and studies of the structure, functions, and evolution of the earliest living cell. The unifying computational approach involves particle methods implemented in parallel computer architectures. The inherent adaptivity, robustness and efficiency of particle methods makes them a multidisciplinary computational tool capable of bridging the gap of micro-scale and continuum flow simulations. Using efficient tree data structures, multipole expansion algorithms, and improved particle-grid interpolation, particle methods allow for simulations using millions of computational elements, making possible the resolution of a wide range of length and time scales of these important physical phenomena.The current challenges in these simulations are in : [i] the proper formulation of particle methods in the molecular and continuous level for the discretization of the governing equations [ii] the resolution of the wide range of time and length scales governing the phenomena under investigation. [iii] the minimization of numerical artifacts that may interfere with the physics of the systems under consideration. [iv] the parallelization of processes such as tree traversal and grid-particle interpolations We are conducting simulations using vortex methods, molecular dynamics and smooth particle hydrodynamics, exploiting their unifying concepts such as : the solution of the N-body problem in parallel computers, highly accurate particle-particle and grid-particle interpolations, parallel FFT's and the formulation of processes such as diffusion in the context of particle methods. This approach enables us to transcend among seemingly unrelated areas of research.

Koumoutsakos, P.↗

DOE OSTI2026

Neural operator transformers capture bifurcating drift-wave turbulence in fusion plasma simulations

Self-consistent modeling of turbulence-driven transport is critical for optimizing confinement in magnetically confined fusion plasmas, such as tokamaks and stellarators. In particular, capturing the long-term co-evolution of turbulence, flow, and background plasma profiles remains computationally challenging. Direct numerical simulation of these multiscale, highly nonlinear processes is often demanding and impractical for real-time control or design optimization. To address this bottleneck, we investigate transformer-based neural operator partial differential equation surrogates for emulating the dynamics of drift-wave turbulence bifurcation mediated by zonal flows, using the modified Hasegawa–Wakatani (MHW) model as a prototypical system. We find that the finetuned neural operator model has excellent performance in capturing the multi-spatiotemporal-scales of MHW turbulence bifurcation and is robust to testing on rare and out-of-distribution dynamics. Specifically, we demonstrate that a single unified model accurately predicts both quasi-steady-state turbulence and a wide range of dynamical transition processes, such as nonlinear saturation, spontaneous suppression of turbulence, and the emergence of macroscopic zonal flows, over time horizons vastly exceeding the local turbulence correlation time. This computationally efficient approach establishes a strong foundation for fast, AI-based modeling of complex, multiscale phenomena in magnetized fusion plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRSDate not supplied

Detecting Risk and Anomalies in Airplane Dynamics Through Entropic Analysis of Time Series Data

Despite recent efforts to move away from traditional threshold exceedance detection methods for aircraft state monitoring, modern aircraft still rely on safety thresholds to communicate to pilots the identification of an anomaly in the aircraft when a threshold is surpassed. Current anomaly detection methods mainly depend on uninterpretable machine learning models to learn complex patterns and relationships contained in the time series data of aircraft. Although these methods are capable of identifying known anomalies, their deficiency in interpretability presents a challenge when translating them to different aircraft. To overcome this deficiency, entropic analysis of aircraft dynamics seeks to characterize the complexity, or lack thereof, of the aircraft dynamics prior to the development of a risk scenario. This complexity characterization provides a more straightforward summary of state changes in the dynamics of flight variables. To build a foundation for entropic analysis, we analyzed the complexity of unstable approaches, an anomalous event present in many of today’s aviation accidents. The analysis revealed a statistically significant difference in the complexity distribution of flight variables under a stable approach versus an unstable approach. These differences in complexity were especially notable minutes before an approach was identified as unstable. Moreover, the multiscale entropic analysis revealed the presence of signal complexity at multiple time scales across multiple time windows before landing. By capturing state changes and corrections in the aircraft dynamics using entropy, advanced, yet still interpretable, sensor systems based on entropic frameworks from this study can be constructed in the future using classical machine learning approaches.

Risk detection↗