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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A Multiscale Inelastic Internal State Variable Corrosion Model

We present a corrosion internal state variable (ISV) damage model based upon the integrated computational materials engineering (ICME) hierarchical multiscale paradigm. Structure–property experiments for magnesium alloys were used where the only inputs were the volume fractions of each element of the periodic table. This macroscale ISV corrosion model finds its basis in Horstemeyer’s mechanical damage model, which includes three separate ISVs for damage nucleation, growth, and coalescence, as well as Walton’s inclusion of corrosion, which introduces five new ISVs for pit nucleation, growth, and coalescence, along with general corrosion and intergranular corrosion. While Walton’s corrosion ISVs are phenomenological in nature, herein we develop a multiscale physical basis for the corrosion ISVs. The parameters for the macroscale corrosion ISVs were garnered from the mesoscale Butler–Volmer equations. Pure magnesium with differing amounts of aluminum were used in corrosion tests to exemplify the different pitting, general corrosion, and intergranular corrosion rates, and the macroscale ISV model was calibrated with said data, in which the only inputs to the model are the volume percentages of the elements magnesium and aluminum. Although magnesium alloys were used to motivate and calibrate the model, the model is abstract enough to possibly capture other material systems as well.

Chemistry↗
DOE OSTI2024

A Multiphysics Thermoelastoviscoplastic Damage Internal State Variable Constitutive Model including Magnetism

We present a macroscale constitutive model that couples magnetism with thermal, elastic, plastic, and damage effects in an Internal State Variable (ISV) theory. Previous constitutive models did not include an interdependence between the internal magnetic (magnetostriction and magnetic flux) and mechanical fields. Although constitutive models explaining the mechanisms behind mechanical deformations caused by magnetization changes have been presented in the literature, they mainly focus on nanoscale structure–property relations. A fully coupled multiphysics macroscale ISV model presented herein admits lower length scale information from the nanoscale and microscale descriptions of the multiphysics behavior, thus capturing the effects of magnetic field forces with isotropic and anisotropic magnetization terms and moments under thermomechanical deformations. For the first time, this ISV modeling framework internally coheres to the kinematic, thermodynamic, and kinetic relationships of deformation using the evolving ISV histories. For the kinematics, a multiplicative decomposition of deformation gradient is employed including a magnetization term; hence, the Jacobian represents the conservation of mass and conservation of momentum including magnetism. The first and second laws of thermodynamics are used to constrain the appropriate constitutive relations through the Clausius–Duhem inequality. The kinetic framework employs a stress–strain relationship with a flow rule that couples the thermal, mechanical, and magnetic terms. Experimental data from the literature for three different materials (iron, nickel, and cobalt) are used to compare with the model’s results showing good correlations.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Multiphysics Thermoelastoviscoplastic Damage Internal State Variable Constitutive Model including Magnetism

We present a macroscale constitutive model that couples magnetism with thermal, elastic, plastic, and damage effects in an Internal State Variable (ISV) theory. Previous constitutive models did not include an interdependence between the internal magnetic (magnetostriction and magnetic flux) and mechanical fields. Although constitutive models explaining the mechanisms behind mechanical deformations caused by magnetization changes have been presented in the literature, they mainly focus on nanoscale structure–property relations. A fully coupled multiphysics macroscale ISV model presented herein admits lower length scale information from the nanoscale and microscale descriptions of the multiphysics behavior, thus capturing the effects of magnetic field forces with isotropic and anisotropic magnetization terms and moments under thermomechanical deformations. For the first time, this ISV modeling framework internally coheres to the kinematic, thermodynamic, and kinetic relationships of deformation using the evolving ISV histories. For the kinematics, a multiplicative decomposition of deformation gradient is employed including a magnetization term; hence, the Jacobian represents the conservation of mass and conservation of momentum including magnetism. The first and second laws of thermodynamics are used to constrain the appropriate constitutive relations through the Clausius–Duhem inequality. The kinetic framework employs a stress–strain relationship with a flow rule that couples the thermal, mechanical, and magnetic terms. Experimental data from the literature for three different materials (iron, nickel, and cobalt) are used to compare with the model’s results showing good correlations.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Electrically-driven IMT and volatile memristor behavior in NdNiO 3 films

Abstract Transition metal oxides with insulator-metal transitions (IMTs) are uniquely suited for volatile memristor devices that mimic the spiking of biological neurons. Unlike most non-volatile memristors, which often operate via ion migration into filaments, volatile devices utilize a reversible phase change that returns to a ground state in the absence of applied stimulus. In these devices, Joule heating triggers the IMT and changes the bulk resistivity rather than influencing conduction through defects, as in previous studies. This volatile resistive switching behavior has previous been leveraged in niobium and vanadium oxides, but not in rare-earth nickelates, despite their tunable transition temperatures. This study demonstrates an electrically driven IMT in the prototypical rare-earth nickelate, NdNiO 3 , in large area devices. While previous work examining the electrically-driven IMT in NdNiO 3 suggests defect-dominated conduction, this study shows clear s-type negative differential resistance (NDR) consistent with temperature-dependent resistivity measurements. The NDR peak-to-valley voltage scales linearly with temperature as expected for conductivity pathways dominated by bulk IMT behavior. Unlike other transition metal oxides, which are modeled using the insulator-metal phase fraction as the internal state variable, a thermoelectric model with temperature as the internal state variable is found to more accurately describe the current–voltage characteristic of NdNiO 3 volatile memristors. Overall, we report the synthesis, fabrication, and characterization of NdNiO 3 volatile memristors with resistivity dominated by bulk-like IMT behavior which is scalable and not dependent upon oxygen vacancy migration or defect mediated conduction pathways.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Phase-field modeling and experiments of dynamic fracture in single crystal quartz

Predicting the onset and characteristics of brittle fracture is important for a wide range of engineering and geological material applications. In this paper, we study important aspects of brittle fracture in α-quartz by phase-field modeling and experiments using a top-down approach. In the modeling framework, the work term in the Griffith energy balance is replaced with internal energy contributions that represent surface energy, thermal energy, and elastic strain energy stored in defects. This allows parametrization of individual energy contributions in terms of internal state variables and keeps track of energy partitioning after the onset of fracture. The path and history dependence of fracture is included in evolution laws for internal state variables, e.g., entropy evolution, while the energy remains a true potential. In the experimental part, dynamic compression experiments coupled with X-ray phase contrast imaging are performed on cube-like samples with a hole. In the top-down analysis, dynamic compression and three point bending experiments from the literature are simulated with the developed phase-field damage model. In conclusion, the fitted model highlights the strain rate, size, and stress state dependence of damage nucleation and evolution in single crystal α-quartz.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A non-isothermal breakage-damage model for plastic-bonded granular materials incorporating temperature, pressure, and rate dependencies

Plastic-bonded granular materials (PBM) are widely used in industrial sectors, including building construction, abrasive applications, and defense applications such as plastic-bonded explosives. The mechanical behavior of PBM is highly nonlinear, irreversible, rate dependent, and temperature sensitive governed by various micromechanical attributions such as grain crushing and binder damage. This paper presents a thermodynamically consistent, microstructure-informed constitutive model to capture these characteristic behaviors of PBM. Key features of the model include a breakage internal variable to upscale the grain-scale information to the continuum level and to predict grain size evolution under mechanical loading. In addition, a damage internal state variable is introduced to account for the damage, deterioration, and debonding of the binder matrix upon loading. Temperature is taken as a fundamental external state variable to handle non-isothermal loading paths. The proposed model is able to capture with good accuracy several important aspects of the mechanical properties of PBM, such as pressure-dependent elasticity, pressure-dependent yield strength, brittle-to-ductile transition, temperature dependency, and rate dependency in the post-yielding regime. Furthermore, the model is validated against multiple published datasets obtained from confined and unconfined compression tests, covering various PBM compositions, confining pressures, temperatures, and strain rates.

Breakage↗
DOE OSTI2022

A smeared crack modeling framework accommodating multi-directional fracture at finite strains

A generic smeared crack modeling framework predicated on the deformation gradient decomposition (DGD) approach is proposed for use in dynamic fracture problems at finite strains, accommodating failure along multiple mutually orthogonal fracture planes embedded within an independently defined bulk material model. Within this constitutive framework, the traction equilibrium conditions imposed at each failure surface are used to determine the associated crack displacements stored as internal state variables. In general, the enforcement of interfacial equilibrium entails the implicit solution of a non-linear system of equations within the constitutive update procedure. However, if inertial effects arising due to the relative motion of the fractured material are incorporated within the model, the traction equilibrium conditions are shown to give rise to corresponding dynamic equations of motion governing the time-evolution of the crack opening displacements. For dynamic problems, an explicit time-integration procedure is devised to efficiently update the material state, subject to a set of internal frictionless contact constraints to prevent material inversion. Finally, the efficacy of the proposed modeling framework is investigated through several benchmark dynamic fracture problems run within the explicit finite element code DYNA3D.

42 ENGINEERING↗
DOE OSTI2024

Electromechanical memcapacitor model offering biologically plausible spiking.

In this article, we introduce a new nanoscale electromechanical device - a leaky memcapacitor - and show that it may be useful for the hardware implementation of spiking neurons. The leaky memcapacitor is a movableplate capacitor that becomes quite conductive when the plates come close to each other. The equivalent circuit of the leaky memcapacitor involves a memcapacitive and memristive system connected in parallel. In the leaky memcapacitor, resistance and capacitance depend on the same internal state variable, which is the displacement of the movable plate. We have performed a comprehensive analysis showing that several types of spiking observed in biological neurons can be implemented with the leaky memcapacitor. Significant attention is paid to the dynamic properties of the model. As in leaky memcapacitors the capacitive, leaking resistive, and reset functionalities are implemented naturally within the same device structure, their use will simplify the creation of spiking neural networks.

Zhang, Zixi↗
DOE OSTI2025

An attention-based neural ordinary differential equation framework for modeling inelastic processes

To preserve strictly conservative behavior as well as model the variety of dissipative behavior displayed by solid materials, we propose a significant enhancement to the internal state variable-neural ordinary differential equation (ISV-NODE) framework. In this data-driven, physics-constrained modeling framework internal states are inferred rather than prescribed. The ISV-NODE consists of: (a) a stress model dependent on observable deformation and inferred internal state, and (b) a model of the evolution of the internal states. The enhancements to ISV-NODE proposed in this work are multifold: (a) a partially input convex neural network stress potential provides polyconvexity in terms of observed strain while leaving the inferred state unconstrained, and (b) an internal state flow model uses common latent features to inform novel attention-based gating and drives the flow of internal state only in dissipative regimes. We demonstrated that this architecture can accurately model dissipative and conservative behavior across an isotropic, isothermal elastic-viscoelastic-elastoplastic spectrum with three exemplars, while maintaining fundamental principles by design.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

AMOC Variability in Climate Models and Its Dependence on the Mean State

Abstract Understanding internal variability of the climate system is critical when isolating internal and anthropogenically forced signals. Here, we investigate the modes of Atlantic Meridional Overturning Circulation ( AMOC ) variability using perturbation experiments with the Institut Pierre‐Simon Laplace's (IPSL) coupled model and compare them to Coupled Model Intercomparison Project Phase 6 (CMIP6) pre‐industrial control simulations. We identify two characteristic modes of variability—decadal‐to‐multidecadal ( DMD var ) and centennial ( CEN var ). The former is driven largely by temperature anomalies in the subpolar North Atlantic, while the latter is driven by salinity in the western subpolar North Atlantic. The amplitude of each mode scales linearly with the mean AMOC strength in the IPSL experiments. The DMD var amplitude correlates well with the AMOC mean strength across CMIP6 models, while the CEN var mode does not. These findings suggest that the strength of DMD var depends robustly on the North Atlantic mean state, while the CEN var mode may be model‐dependent.

Ferster, Brady S. [LOCEAN‐IPSL Sorbonne Université↗
DOE OSTI2025

Recent Accelerated Decadal Shift in Winter North American Temperature Patterns Under Pacific‐Atlantic Decadal Variability

Global warming and internal climate variability have changed winter temperature extreme regimes in North America, affecting droughts and wildfires in the western United States. However, how internal climate variability influences North American winter temperature extreme patterns remains poorly understood. Here, we demonstrate that the recent winter North American surface air temperature (SAT) exhibits an accelerated decadal alternation between Warm West-Cold East (WWCE) and Cold West-Warm East (CWWE) dipoles because their variations show shorter decadal periods during 1990–2022 than during 1950–1989 and are regulated by the Pacific Decadal Oscillation (PDO) variability. While the winter WWCE dipole mainly linked to North Pacific blocking events exhibited a smaller mean amplitude during 1990–2022 than 1950–1989 due to the weakened positive PDO phase during 1990–2022 under the positive phase of the Atlantic Multidecadal Oscillation (AMO), the winter CWWE showed a larger mean amplitude during 1990–2022 due to the stronger negative PDO phase than during 1950–1989. Our results further suggest that the recent rapid decadal shift of North American winter temperatures is primarily attributed to the PDO variability likely due to anthropogenic warming under the positive AMO.

Atlantic Multidecadal Oscillation↗
DOE OSTI2022

A directional microcrack damage theory for brittle solids based on continuous hyperplasticity

We present a novel microcrack-damage theory for brittle solids under compression. Instead of using internal variables like zeroth, second or fourth rank damage tensors, the state of material damage is represented by an internal function that encapsulates the information of direction, density and size of microcracks. Just like other internal variables, the evolution of this state function must obey the second law of thermodynamics for arbitrary loading paths. This is done by casting the model in the framework of continuous hyperplasticity and enforcing a non-negative dissipation rate functional. The proposed framework offers predictions on the continuous evolution of microcrack density and the induced material anisotropy along with the macroscopic stress-strain curves. The use of continuous damage function grants the model significantly enhanced resolution in characterizing the direction-dependent response of cracked solids compared to classical models that are based on damage tensors. Two scenarios are considered in developing the theory, one assumes frictionless cracks and the other incorporates friction between crack surfaces. The results highlight that inelasticity, pressure dependence, and loading-unloading hysteresis exhibited by brittle solids are natural consequences of frictional microcracks. The proposed theory offers a generic and versatile framework to upscale micromechanical processes operating at individual crack scale to explain the macroscopic behavior of cracked solids.

Materials Science↗
DOE OSTI2025

Evaluation of historical precipitation interannual variability in CMIP6 over the United States

Interannual precipitation variability profoundly influences society via its effects on agriculture, water resources, infrastructure, and disaster risks. In this study, we use daily in situ precipitation observations from the global historical climatology network-daily (GHCN-D) to assess the ability of 21 Coupled Model Intercomparison Project Phase 6 (CMIP6) models, including the 50-member fifth-generation Canadian Earth System Model single model initial-condition large ensemble (CanESM5_SMILE), to realistically simulate historical interannual precipitation variability trends within 17 regions of the contiguous United States (CONUS). We assess how accurately the CMIP6 simulations align with observational data across annual, summer, and winter periods, focusing on four key hydrometeorological metrics, including interannual precipitation variability, relative interannual precipitation variability (coefficient of variation), annual mean precipitation, and annual wet day frequency. Our findings reveal that CMIP6 ensemble members generally reproduce the spatial patterns of observed trends in annual mean precipitation. In most regions, models agree well with the signs of observed changes in annual mean precipitation, though discrepancies in trend magnitude are evident. Further, observed trends in winter mean precipitation broadly exhibit a spatial pattern similar to that of the observed annual mean. However, analysis of the CanESM5_SMILE shows that trends in precipitation variability may primarily be the result of model-simulated internal variability, suggesting caution in interpreting multi-model single-realization ensemble results. Challenges in accurately simulating interannual precipitation variability underscore the need for ongoing model refinement and validation to enhance climate projections, especially in regions vulnerable to extreme precipitation events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Approximation of refrigerant thermophysical properties using neural networks to speed up transient thermofluid simulations

Accurate and efficient evaluations of refrigerant thermophysical properties and their partial derivatives are essential for transient simulations of thermofluid systems, where several computations need to be executed at each integration time step. Since the utilization of an Equation of State for retrieving properties based on a pair of independent inputs typically involves numerical iterations in solution procedures, when the input variables differ from the refrigerant state variables employed in dynamic models, a variety of approaches including lookup table interpolation and curve fitting have been developed to explicitly approximate these properties based on the state variables, and consequently eliminate internal iterations. This paper presents an alternative method that exploits derivative-informed neural networks to model refrigerant properties explicitly from inputs of pressure and enthalpy, while ensuring consistent partial derivatives generated by differentiating the neural networks. Computational speed and accuracy of the proposed approach are demonstrated via transient simulations of a discretized heat exchanger model in Modelica, and comparisons against other property evaluation routines. Simulation results indicate that the proposed approach can realize a significant speedup with negligible discrepancies in predicted transients. The method is implemented in an open-source Modelica library.

Ma, Jiacheng↗
DOE OSTI2025

Detecting tropospheric composition and climate responses to US air pollution controls in the context of internally-arising variability

Since the 1970s, air pollutant emissions controls in the United States (US) have lowered concentrations of ozone (O 3 ) and aerosols, which have opposing radiative effects on surface temperature. Using a pair of initial-condition ensembles generated by a fully-coupled chemistry-climate model, we simulate the “world avoided” by US air pollution controls. In this counterfactual world, we find tropospheric column O 3 increases, robust to natural internal variability, extending across the Northern Hemisphere. Robust aerosol increases, dominated by sulfate, remain localized near the US. Wintertime Northwest Atlantic cloud droplet number concentration is particularly sensitive to US aerosol. While an ensemble mean US surface cooling signal (−0.4 °C) implies that aerosol-driven cooling prevails over any O 3 -induced warming, we find that large regional internal variability will confound its detection in any single transient realization. Larger signal-to-noise ratios for composition versus climate variables underscore the greater detectability of emissions-driven changes in tropospheric composition compared to their associated climate impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Internal Climate Variability Obscures Future Freezing Rain Changes Despite Global Warming Trend

Abstract Although numerous studies have projected changes in freezing rain under future climate conditions, the internal variability of freezing rain remains poorly quantified. Here, we introduce a framework utilizing a novel machine‐learning algorithm to diagnose freezing rain in reanalysis and climate model simulations. By employing multivariate quantile mapping, we decompose the projected freezing rain trend into contributions from changes in temperature, relative humidity, and precipitation, which helps separate the forced response from internal climate variability. Our finding reveals a notable decrease in freezing rain occurrence in most areas. Despite a substantial temperature increase, internal variability overshadows climate forcing across a large portion of the eastern United States until about 2050. This insight has implications for practitioners, suggesting that the observed freezing rain frequency climatology continues to provide a relevant baseline for decision‐making in the near term. However, longer‐term design and adaptation plans should consider the projected changes in these regions.

Zhuang, Haoyu (Richard) [Department of Atmospheric↗
DOE OSTI2023

Anthropogenic Aerosols Contribute to the Recent Decline in Precipitation Over the U.S. Southwest

Abstract The winter‐spring precipitation over the Southwestern United States (SWUS) decreased since 1980. It is frequently attributed to Pacific internal decadal variability, but recent studies found anthropogenic aerosols (AA) can also induce a transition to a negative Pacific Decadal Variability (PDV) phase. We revisit the attribution of SWUS drying by quantifying the contributions of anthropogenically forced decadal Pacific Sea Surface Temperatures (SSTs). Applying a low‐frequency component analysis to observations, Community Earth System Model version 2 (CESM2) all‐forcings and single‐forcing large ensembles, we find up to 42% of the observed precipitation trend to be related to the AA‐induced negative PDV‐like pattern, which is driven by the emission shift from the Western to the Eastern Hemisphere. In CESM2, other radiative forcings counteract the influence of AA, but it remains unclear whether the model correctly simulates this balance. This implies that the near‐future trajectories of these forcings, in particular Asian aerosols, are important for projections of SWUS precipitation.

Geology↗