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NASA NTRS2016

Analysis and Characterization of Damage Utilizing an Orthotropic Generalized Composite Material Model Suitable for Use in Impact Problems

The need for accurate material models to simulate the deformation, damage and failure of polymer matrix composites under impact conditions is becoming critical as these materials are gaining increased usage in the aerospace and automotive communities. In order to address a series of issues identified by the aerospace community as being desirable to include in a next generation composite impact model, an orthotropic, macroscopic constitutive model incorporating both plasticity and damage suitable for implementation within the commercial LS-DYNA computer code is being developed. The plasticity model is based on extending the Tsai-Wu composite failure model into a strain hardening-based orthotropic plasticity model with a non-associative flow rule. The evolution of the yield surface is determined based on tabulated stress-strain curves in the various normal and shear directions and is tracked using the effective plastic strain. To compute the evolution of damage, a strain equivalent semi-coupled formulation is used in which a load in one direction results in a stiffness reduction in multiple material coordinate directions. A detailed analysis is carried out to ensure that the strain equivalence assumption is appropriate for the derived plasticity and damage formulations that are employed in the current model. Procedures to develop the appropriate input curves for the damage model are presented and the process required to develop an appropriate characterization test matrix is discussed.

Impact↗

NASA NTRS2016

Analysis and Characterization of Damage Utilizing an Orthotropic Generalized Composite Material Model Suitable for Use in Impact Problems

Impact↗

NASA NTRS2012

The Performance of Current Atmospheric Radiation Codes in Phase I of CIRC

The Continual Intercomparison of Radiation Codes (CIRC) is intended as an evolving and regularly updated reference source for evaluation of radiative transfer (RT) codes used in Global Climate Models and other atmospheric applications. In our presentation we will discuss our evaluation of the performance of 13 shortwave and 11 longwave RT codes that participated in Phase I of CIRC. CIRC differs from previous intercomparisons in that it relies on an observationally validated catalogue of cases. The seven CIRC Phase I baseline cases, five cloud-free, and two with overcast liquid clouds, are built around observations by the Atmospheric Radiation Measurements (ARM) program that satisfy the goals .of Phase I, namely to examine RT model performance in realistic, yet not overly complex, atmospheric conditions. Besides the seven baseline cases, additional idealized "subcases" are also examined to facilitate interpretation of model errors. We will quantify individual model performance with respect to reference line-by-line calculations, and will also highlight RT code behavior for conditions of doubled CO2 , aspects of utilizing a spectral specification of surface albedo, and the impact of the inclusion of scattering in the thermal infrared. Our analysis suggests that RT codes should work towards improving their calculation of diffuse shortwave flux, shortwave absorption, treatment of spectral surface albedo, and shortwave CO2 forcing. Despite practical difficulties in comparing our results to previous results by the Intercomparison of Radiation Codes in Climate Models (ICRCCM) conducted about 20 years ago, it appears that the current generation of RT codes do indeed perform better than the codes of the ICRCCM era. By enhancing the range of conditions under which participating codes are tested, future CIRC phases will hopefully allow even more rigorous examination of RT code performance.

Oreopoulos, L.↗

NASA NTRS2010

Concerning the Motion of FTEs and Attendant Signatures

We employ the Cooling et al. [2001] model to predict the location, orientation, and motion of flux transfer events (FTEs) generated along finite length component and anti parallel reconnection lines for typical solar wind plasma conditions and various interplanetary magnetic field (IMF) orientations in the plane perpendicular to the SunEarth line at the solstices and equinoxes. For duskward and northward or southward IMF orientations, events formed by component reconnection originate along reconnection curves passing through the sub solar point that tilt from southern dawn to northern dusk. They maintain this orientation as they move either northward into the northern dawn quadrant or southward into the southern dusk quadrant. By contrast, events formed by antiparallel reconnection originate along reconnection curves running from northern dawn to southern dusk in the southern dawn and northern dusk quadrants and maintain these orientations as they move anti sunward into both these quadrants. Although both the component and antiparallel reconnection models can explain previously reported event orientations on the southern dusk magnetopause during intervals of northward and dawn ward IMF orientation, only the component model explains event occurrence near the subsolar magnetopause during intervals when the IMF does not point due southward.

Sibeck, David G.↗

NASA NTRS2016

Ice-Accretion Test Results for Three Large-Scale Swept-Wing Models in the NASA Icing Research Tunnel

Icing simulation tools and computational fluid dynamics codes are reaching levels of maturity such that they are being proposed by manufacturers for use in certification of aircraft for flight in icing conditions with increasingly less reliance on natural-icing flight testing and icing-wind-tunnel testing. Sufficient high-quality data to evaluate the performance of these tools is not currently available. The objective of this work was to generate a database of ice-accretion geometry that can be used for development and validation of icing simulation tools as well as for aerodynamic testing. Three large-scale swept wing models were built and tested at the NASA Glenn Icing Research Tunnel (IRT). The models represented the Inboard (20% semispan), Midspan (64% semispan) and Outboard stations (83% semispan) of a wing based upon a 65% scale version of the Common Research Model (CRM). The IRT models utilized a hybrid design that maintained the full-scale leading-edge geometry with a truncated afterbody and flap. The models were instrumented with surface pressure taps in order to acquire sufficient aerodynamic data to verify the hybrid model design capability to simulate the full-scale wing section. A series of ice-accretion tests were conducted over a range of total temperatures from -23.8 deg C to -1.4 deg C with all other conditions held constant. The results showed the changing ice-accretion morphology from rime ice at the colder temperatures to highly 3-D scallop ice in the range of -11.2 deg C to -6.3 deg C. Warmer temperatures generated highly 3-D ice accretion with glaze ice characteristics. The results indicated that the general scallop ice morphology was similar for all three models. Icing results were documented for limited parametric variations in angle of attack, drop size and cloud liquid-water content (LWC). The effect of velocity on ice accretion was documented for the Midspan and Outboard models for a limited number of test cases. The data suggest that there are morphological characteristics of glaze and scallop ice accretion on these swept-wing models that are dependent upon the velocity. This work has resulted in a large database of ice-accretion geometry on large-scale, swept-wing models.

Wind-Tunnel Tests↗

NASA NTRS1989

Rotation of Halley's comet

Numerical simulations supported by analytical calculations are used to model the suspected condition of Comet Halley's nucleus, which has been suggested to not be in a state of principal-axis rotation. It is found easy to numerically generate lightcurves from modulated jets of material which exhibit both of the observed periodicities of 2.2 and 7.4 days, after choosing initial conditions for a representative nucleus such that the shorter period is the rotation period, and the longer period is that of precession of the spin vector in the body frame-of-reference. The improbability of exciting a spin precession about the axis of minimum moment-of-inertia, the relative instability of this state to the jet-induced torques, and the smaller probability of observing significant seasonal changes in the lightcurve in this state, all favor the model in which Halley's nucleus precesses about the axis of maximum moment-of-inertia.

Peale, S. J.↗

NASA NTRS1978

Primordial metamorphism of asteroids via electrical induction in a T Tauri-like solar wind

Possible heating mechanisms for an intense thermal cycle in the early solar system are considered, and inductive asteroid heating in a T Tauri environment is examined. Calculations of thermal models based on recent measurements of the electrical conductivity of carbonaceous meteorites are reported which are presumably more representative of actual conditions in the early solar nebula. Asteroidal thermal evolution is computed using a highly simplified code that restricts induction to the dc limit of the TM mode, approximates the complete unipolar-generation differential equation by a simple series-resistance model, and restricts the modeling of thermal conduction to a calculation of heat transfer across a thin planar shell of given thickness increasing with time, which blankets a body assumed to have an isothermal core. A grid of results is obtained for 20 combinations of asteroid radius and solar distance representing the populaton of asteroids. It is found that there is a relative heating maximum with respect to body radius, that this effect is due to the operation of two distinct heating-rate restrictions which have opposite radius dependences, and that the maximum current density is roughly proportional to the inverse of interior radius.

Herbert, F.↗

DOE OSTI2025

A Numerical Modeling Framework for Flocculation and Cohesive Sediment Transport in the Wave Bottom Boundary Layer

Flocculation, a critical process in coastal and estuarine systems, plays a significant role in sediment transport, nutrient cycling, and ecological health. This study develops a cohesive sediment transport modeling framework tailored to the wave bottom boundary layer under dilute and equilibrium conditions, explicitly incorporating flocculation effects via a Population Balance Equation (PBE). Using Direct Numerical Simulation, six baseline cases, each with a distinct sediment concentration profile resulting from a constant settling velocity and critical erosion shear stress, are generated to drive the PBE flocculation model for given floc yield strength and stickiness. Results reveal that flocculation significantly influences sediment concentration profiles promoting three distinct stages, well‐mixed, transition to lutocline, and well‐developed lutocline. At low concentrations with well‐mixed profiles, cohesive floc properties are less significant, and turbulence is a main flocculation driver. In contrast, as concentration increases, cohesive floc properties become crucial, facilitating lutocline formation. Here, the analysis also highlights limitations of depth‐averaged settling velocity as a parameterization. It is suitable for well‐mixed and transitional profiles but fails in well‐developed lutoclines, where empirical formulations that explicitly incorporate turbulent shear rate and sediment concentration better capture variability. This study underscores the necessity of incorporating flocculation effects into sediment transport models to enhance predictions of sediment dynamics in wave bottom boundary layers.

Penaloza‐Giraldo, Jorge A. [Oak Ridge National Lab↗

NASA NTRS2014

Synthesis of 3-D Coronal-Solar Wind Energetic Particle Acceleration Modules

Acute space radiation hazards pose one of the most serious risks to future human and robotic exploration. Large solar energetic particle (SEP) events are dangerous to astronauts and equipment. The ability to predict when and where large SEPs will occur is necessary in order to mitigate their hazards. The Coronal-Solar Wind Energetic Particle Acceleration (C-SWEPA) modeling effort in the NASANSF Space Weather Modeling Collaborative [Schunk, 2014] combines two successful Living With a Star (LWS) (http:lws.gsfc.nasa.gov) strategic capabilities: the Earth-Moon-Mars Radiation Environment Modules (EMMREM)[Schwadron et al., 2010] that describe energetic particles and their effects, with the Next Generation Model forthe Corona and Solar Wind developed by the Predictive Science, Inc. (PSI) group. The goal of the C-WEPA effort is to develop a coupled model that describes the conditions of the corona, solar wind, coronal mass ejections (CMEs) and associated shocks, particle acceleration, and propagation via physics-based modules. Assessing the threat of SEPs is a difficult problem. The largest SEPs typically arise in conjunction with X classflares and very fast (1000 kms) CMEs. These events are usually associated with complex sunspot groups(also known as active regions) that harbor strong, stressed magnetic fields. Highly energetic protonsgenerated in these events travel near the speed of light and can arrive at Earth minutes after the eruptiveevent. The generation of these particles is, in turn, believed to be primarily associated with the shock waveformed very low in the corona by the passage of the CME (injection of particles fromthe flare sitemay also playa role). Whether these particles actually reach Earth (or any other point) depends on their transport in theinterplanetary magnetic field and their magnetic connection to the shock.

exploration↗

NASA NTRS2015

LEWICE3D/GlennHT Particle Analysis of the Honeywell Al502 Low Pressure Compressor

A flow and ice particle trajectory analysis was performed for the booster of the Honeywell AL502 engine. The analysis focused on two closely related conditions one of which produced a rollback and another which did not rollback during testing in the Propulsion Systems Lab at NASA Glenn Research Center. The flow analysis was generated using the NASA Glenn GlennHT flow solver and the particle analysis was generated using the NASA Glenn LEWICE3D v3.56 ice accretion software. The flow and particle analysis used a 3D steady flow, mixing plane approach to model the transport of flow and particles through the engine. The inflow conditions for the rollback case were: airspeed, 145 ms; static pressure, 33,373 Pa; static temperature, 253.3 K. The inflow conditions for the non-roll-back case were: airspeed, 153 ms; static pressure, 34,252 Pa; static temperature, 260.1 K. Both cases were subjected to an ice particle cloud with a median volume diameter of 24 microns, an ice water content of 2.0 gm3 and a relative humidity of 100 percent. The most significant difference between the rollback and non-rollback conditions was the inflow static temperature which was 6.8 K higher for the non-rollback case.

Ice Accretion Codes↗

NASA NTRS1987

Dynamic testing of a two-dimensional box truss beam

Testing to determine the effects of joint freeplay and pretensioning of diagonal members on the dynamic characteristics of a two-dimensional box truss beam was conducted. The test article was ten bays of planar truss suspended by long wires at each joint. Each bay measured 2 meters per side. Pins of varying size were used to simulate various joint freeplay conditions. Single-point random excitation was the primary method of test. The rational fraction polynomial method was used to extract modal characteristics from test data. A finite element model of the test article was generated from which modal characteristics were predicted. These were compared with those obtained from tests. With the exception of the fundamental mode, correlation of theoretical and experimental results was poor, caused by the resonant coupling of local truss member bending modes with global truss beam modes. This coupling introduced many modes in the frequency range of interest whose frequencies were sensitive to joint boundary conditions. It was concluded that local/global coupling must be avoided in the frequency range where accurate modal characteristics are required.

White, Charles W.↗

NASA NTRS1990

Bearingless rotor aeromechanical stability measurements and correlations using nonlinear aerodynamics

The aeromechanical stability of a 1/8th Froude scaled bearingless rotor model was investigated experimentally in a wind tunnel. Both shaft-fixed and shaft-free conditions were examined to study the aeroelastic stability of a bearingless rotor without the incorporation of auxiliary dampers. This wind tunnel investigation generated a set of stability data for four different advance ratios, and a wide range of collective pitch settings. Theoretical analysis was performed using the newly developed University of Maryland Advanced Rotorcraft Code (UMARC). For analysis, the blade is modeled as an elastic beam undergoing flap bending, lag bending, elastic twist, and axial deformation. Blade response is calculated using a finite element method in time. Nonlinear aerodynamic effects are included by using a semiempirical stall modeling. The linearized periodic rotor perturbation equations in the nonrotating frame are solved for stability roots using Floquet transition matrix theory, as well as constant coefficient approximation. The predicted results are compared with the experimental data.

Wang, James M.↗

DOE OSTI2024

SDYN-GANs: Adversarial learning methods for multistep generative models for general order stochastic dynamics

We introduce adversarial learning methods for data-driven generative modeling of dynamics of nth-order stochastic systems. Our approach builds on Generative Adversarial Networks (GANs) with generative model classes based on stable m-step stochastic numerical integrators. From observations of trajectory samples, we introduce methods for learning long-time predictors and stable representations of the dynamics. Our approaches use discriminators based on Maximum Mean Discrepancy (MMD), training protocols using both conditional and marginal distributions, and methods for learning dynamic responses over different time-scales. We show how our approaches can be used for modeling physical systems to learn force-laws, damping coefficients, and noise-related parameters. Our adversarial learning approaches provide methods for obtaining stable generative models for dynamic tasks including long-time prediction and developing simulations for stochastic systems.

• Artificial intelligence (AI) / machine learning ↗

NASA NTRS1988

On the origin of the Orion and Monoceros molecular cloud complexes

A detailed model for the origin of the Orion and Monoceros cloud complexes is presented, showing that a single high-velocity H I cloud-galaxy collision can explain their main observed features. The collision generates massive shocked layers, and self-gravity can then provide the conditions for the transformation of these layers into molecular clouds. The clouds formed by the collision maintain the motion of their parental shocked gas and reach positions located far away from the plane. According to this model, both the Orion and Monoceros complexes were formed some 60 million yr ago, when the original shocked layer was fragmented by Galactic tidal forces.

Franco, J.↗

DOE OSTI2025

Deep learning model for fast, science-based forecasting of fluid migration along faults in geologic carbon storage scenarios

Effective long-term geologic storage depends on robust site selection and credible, science-based forecasting of subsurface behavior to ensure storage integrity. For this work, we develop a deep learning–based reduced-order model (ROM) to quantify potential carbon dioxide (CO₂) and brine migration through geological faults. The ROM combines a Transformer model for binary classification and a Stacked Ensemble for regression, trained on a comprehensive dataset generated from 1400 physics-based reservoir simulations. Key geologic and operational parameters—including fault geometry, reservoir structure, and injection conditions—were systematically varied to capture a wide range of fluid migration scenarios. The ROM accurately predicts the onset of migration, cumulative migration volumes of both CO₂ and brine, and associated migration rates, as compared to an independent set of validation simulations, while significantly reducing computational cost compared to traditional simulation methods. Model performance was evaluated across diverse fault configurations, revealing that shallow reservoir geometry and fault angle are among the most influential factors governing migration behavior. Sensitivity analysis using SHapley Additive exPlanations (SHAP) provided interpretability, revealing distinct patterns in how geological and operational features drive transient versus cumulative migration outcomes. The ROM’s ability to rapidly simulate fault migration scenarios enables efficient sensitivity analyses, scenario evaluations, and decision support for site selection and monitoring design. This approach enhances the safety, scalability, and long-term operational performance of geologic carbon storage (GCS) systems by providing a robust, interpretable tool for predicting subsurface fluid migration and assessing fault-related migration potential.

42 ENGINEERING↗

DOE OSTI2026

Hierarchical transfer learning: an agile and equitable strategy for machine-learning interatomic models

Machine-learned interatomic models are growing in popularity due to their ability to afford near quantum-accurate predictions for complex phenomena with orders-of-magnitude greater computational efficiency. However, these models struggle when applied to systems of many element types due to the approximately exponential increase in number of parameters that must be determined. To mitigate this challenge, we present a new hierarchical transfer learning approach that allows the fitting problem to be decomposed into smaller independent and reusable parameter blocks that enable development of explicitly chemically extensible ML-IAM. Application of this strategy is demonstrated for C and N mixtures under conditions ranging from nominally ambient to ~10,000 K and 200 GPa for compositions from 0 to 100% N. Ultimately, this strategy makes model generation for chemically complex systems more tractable and efficient, facilitates comprehensive model validation, and makes ML-IAM development for problems of this nature more accessible to users with limited access to extreme computing infrastructure.

Lindsey, Rebecca K. [Univ. of Michigan, Ann Arbor,↗

DOE OSTI2025

Data-Driven Method for Groundwater-Level Mapping and Monitoring-Well Network Optimization at Hanford

This report summarizes the initial results and outcomes of a physics-informed, data-driven groundwater level (GWL) mapping capability for the Hanford Site. GWL mapping at Hanford is typically conducted annually and requires a significant amount of computational and expert resources, and it does not allow assessment of the informational value of specific monitoring wells. The proposed method produces spatially and temporally resolved fields consistent with sparse, irregularly sampled, and nonuniformly distributed well measurements. Implemented successfully, this capability will allow rapid mapping of groundwater levels and provide an opportunity to optimize monitoring activities (both location and sampling frequency) based on data information value evaluation. The approach integrates a diffusion-based generative model – trained on MODFLOW simulation data from the Plateau-to-River (P2R) model – with score-based data assimilation (SDA), allowing observation-conditioned mapping without retraining for each monitoring-network layout.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1993

An analytic modeling and system identification study of rotor/fuselage dynamics at hover

A combination of analytic modeling and system identification methods have been used to develop an improved dynamic model describing the response of articulated rotor helicopters to control inputs. A high-order linearized model of coupled rotor/body dynamics including flap and lag degrees of freedom and inflow dynamics with literal coefficients is compared to flight test data from single rotor helicopters in the near hover trim condition. The identification problem was formulated using the maximum likelihood function in the time domain. The dynamic model with literal coefficients was used to generate the model states, and the model was parametrized in terms of physical constants of the aircraft rather than the stability derivatives resulting in a significant reduction in the number of quantities to be identified. The likelihood function was optimized using the genetic algorithm approach. This method proved highly effective in producing an estimated model from flight test data which included coupled fuselage/rotor dynamics. Using this approach it has been shown that blade flexibility is a significant contributing factor to the discrepancies between theory and experiment shown in previous studies. Addition of flexible modes, properly incorporating the constraint due to the lag dampers, results in excellent agreement between flight test and theory, especially in the high frequency range.

Hong, Steven W.↗