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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The radiation valley and exotic resonances in $Wγ$ production at the LHC

The tree-level partonic angular distribution of Standard Model $Wγ$ production possesses a feature known as the Radiation Amplitude Zero (RAZ) where destructive interference causes the cross section to vanish. At the proton level the exact cancellation disappears, however, one can find a dip in the central region of the angular distributions, here called the Radiation Valley (RV). In this paper, we show how the sensitivity for $W(ℓv)γ$ resonances can be significantly improved if one focuses on events in the RV region. Using this technique, we find that the LHC could probe a larger range of resonance masses, equivalent to increasing the luminosity by a factor of 2–3 over conventional searches. The exact increase depends on the spin of the $Wγ$ resonance and exactly how it couples to electroweak gauge bosons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1978

On the propagation of cosmic rays in the Galaxy

Cosmic ray propagation in the Galaxy is examined within the framework of the leaky-box model, whereby phenomenological aspects of diffusion and propagation are related to the physical properties of the interstellar medium. The model is parameterized by data on composition, spectra, spectral change as a function of energy, and cosmic ray particle lifetime. It is assumed that electrons and nucleons have a common source within the Galaxy (probably associated with supernova remnants). Lifetime data and leakage length are compared with radio synchrotron and gamma-ray data to establish a place of origin for cosmic rays observed at earth, i.e., at a radius of 0.5-1.0 kpc from earth. It is noted that if the escape length becomes energy independent, all nuclear spectra will flatten, while the electron spectrum remains unchanged.

Ormes, J.↗
NASA NTRS1999

RXTE Observation of Cygnus X-1: III. Implications for Compton Corona and ADAF Models: Implications for Compton Corona and ADAF Models - Report 3

We have recently shown that a 'sphere + disk' geometry Compton corona model provides a good description of Rossi X-ray Timing Explorer (RXTE) observations of the hard/low state of Cygnus X-1. Separately, we have analyzed the temporal data provided by RXTE. In this paper we consider the implications of this timing analysis for our best-fit 'sphere + disk' Comptonization models. We focus our attention on the observed Fourier frequency-dependent time delays between hard and soft photons. We consider whether the observed time delays are: created in the disk but are merely reprocessed by the corona; created by differences between the hard and soft photon diffusion times in coronae with extremely large radii; or are due to 'propagation' of disturbances through the corona. We find that the time delays are most likely created directly within the corona; however, it is currently uncertain which specific model is the most likely explanation. Models that posit a large coronal radius [or equivalently, a large Advection Dominated Accretion Flow (ADAF) region] do not fully address all the details of the observed spectrum. The Compton corona models that do address the full spectrum do not contain dynamical information. We show, however, that simple phenomenological propagation models for the observed time delays for these latter models imply extremely slow characteristic propagation speeds within the coronal region.

Nowak, Michael A.↗
DOE OSTI2024

A Road Map to Determine Chemical Phenomenology Required for Molten Salt Reactor Accident Modeling

The differences between molten salt reactors (MSRs) and light water reactors (LWRs) has required modification of previous approaches to model reactor accident progression. Part of this is related to the different chemical phenomenology of these reactors as their fuel is not as contained and can react with their surroundings. MELCOR is a reactor simulation tool that has implemented methods and models to model MSRs. However, additional development of MELCOR for modeling MSRs is required. Although understanding the chemistry surrounding MSRs is important to general MSR licensing and operation, only a subset of reactions and phenomenology are required to model beyond design basis incidents and therefore to be captured by MELCOR. This report is intended to guide the chemical phenomenology to improve MELCOR MSR accident modeling and discusses phenomenology models that are in development.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

An asynchronous parallel high-throughput model calibration framework for crystal plasticity finite element constitutive models

Crystal plasticity finite element model (CPFEM) is a powerful numerical simulation in the integrated computational materials engineering toolboxes that relates microstructures to homogenized materials properties and establishes the structure–property linkages in computational materials science. However, to establish the predictive capability, one needs to calibrate the underlying constitutive model, verify the solution and validate the model prediction against experimental data. Bayesian optimization (BO) has stood out as a gradient-free efficient global optimization algorithm that is capable of calibrating constitutive models for CPFEM. Here in this paper, we apply a recently developed asynchronous parallel constrained BO algorithm to calibrate phenomenological constitutive models for stainless steel 304 L, Tantalum, and Cantor high-entropy alloy.

304L stainless steel↗
DOE OSTI2025

Computational materials reliability assessment of hydrogen fueled gas turbine power generation engines

The use of blended fuel sources in land based gas turbine engines drives variations in the resulting operational profile (temperatures and pressures) which can impact engine reliability. Furthermore, variability in the manufacture of components affects the resulting microstructure which directly impacts material performance and reliability. Currently, data-driven models are typically used for maintaining and inspecting fleets of engines. Without explicitly capturing material and operational sources of variability conservatism must be used in developing component-level reliability models. Therefore, there exists an opportunity to use information from materials-scale physics models to better inform reliability modeling and reduce conservatism; the impact is more cost-efficient operation and maintenance of current and future fleets. Specifically, this work establishes a computational framework for evaluating the probabilistic high temperature creep performance of hot-section Ni-based superalloys where uncertainty comes from both microstructural and operational variability. A novel high-fidelity physics model which phenomenologically captures grain-boundary sensitive phenomena has been established. A probabilistic calibration procedure was used to calibrate the model and capture uncertainty in the parameterized model coefficients. A design of experiments methodology was established for identifying informative microstructural digital representations for suitable for forward model evaluation. Results show that training a machine-learning surrogate using this design criteria outperforms random selection of microstructural representations. Finally, two surrogate models were developed: (1) a deterministic surrogate model which predicts the local field response given microstructure, constitutive model parameters, and operating conditions (stress, temperature) and (2) a probabilistic model, where uncertainty comes from constitutive law uncertainty, built using denoising diffusion probabilistic models which samples responses given (1) microstructure and (2) operating conditions. These surrogate models enable partner Siemens Energy to rapidly perform UQ analysis specific to creep deformation across a range of microstructures and operating conditions. The impact is that these ML and physics codes can be used to establish more advanced reliability models for the inspection, servicing, and maintenance of land based gas turbine engines.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Micro–macro finite element modeling method for rub response in abradable coating materials

Gas turbine engines experience “rub” when the rotating blades come in contact with a static abradable coating. This results in extreme strain rates and dynamics inside a high-temperature/high-pressure environment. Current rub models are phenomenological and do not reflect the underlying microstructures, thus limiting their prediction accuracy. In this work, a microstructure-informed, reduced order modeling framework is introduced for simulating abradable coating “rub" behavior. This framework comprises a microscale model constructed based on digitized abradable microstructure and explicitly simulates the mechanical behavior of each constituent phases and their interactions. After calibration and validation with experiment data, the calibrated microscale model is used to generate data across a vast range of applied strain rates and temperature with various load paths. Then, the virtually generated data are used to fit the macroscopic-reduced order model, which enables fast component scale rub simulation without compromising the integrity of the complex material behavior. In conclusion, the proposed effort will address the technical challenge of predicting abradable material behavior during rub through the application of multiscale modeling from microstructure to engines behavior, effectively reducing the development costs and time of new abradable material for better “rub” properties.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Data-Driven Discovery of Active Nematic Hydrodynamics

Active nematics can be modeled using phenomenological continuum theories that account for the dynamics of the nematic director and fluid velocity through partial differential equations (PDEs). While these models provide a statistical description of the experiments, the relevant terms in the PDEs and their parameters are usually identified indirectly. We adapt a recently developed method to automatically identify optimal continuum models for active nematics directly from spatio-temporal data, via sparse regression of the coarse-grained fields onto generic low order PDEs. After extensive benchmarking, we apply the method to experiments with microtubule-based active nematics, finding a surprisingly minimal description of the system. Furthermore, our approach can be generalized to gain insights into active gels, microswimmers, and diverse other experimental active matter systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Towards Z-Next: The Integration of Theory, Experiments, and Computational Simulation in a Bayesian Data Assimilation Framework

Making reliable predictions in the presence of uncertainty is critical to high-consequence modeling and simulation activities, such as those encountered at Sandia National Laboratories. Surrogate or reduced-order models are often used to mitigate the expense of performing quality uncertainty analyses with high-fidelity, physics-based codes. However, phenomenological surrogate models do not always adhere to important physics and system properties. This project develops surrogate models that integrate physical theory with experimental data through a maximally-informative framework that accounts for the many uncertainties present in computational modeling problems. Correlations between relevant outputs are preserved through the use of multi-output or co-predictive surrogate models; known physical properties (specifically monotoncity) are also preserved; and unknown physics and phenomena are detected using a causal analysis. By endowing surrogate models with key properties of the physical system being studied, their predictive power is arguably enhanced, allowing for reliable simulations and analyses at a reduced computational cost.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Microstructure based modeling of friction stir welded joint of dissimilar metals using crystal plasticity

We report the friction stir welding (FSW) process shows promising results in joining dissimilar metals which are otherwise almost impossible to join using traditional welding techniques. Being a new technique, the deformation and the failure mechanism of the joints made by the FSW process needs to be investigated. In this work, a joint between AZ31 Mg alloy and DP590 steel is modeled using phenomenological crystal plasticity formulation on the mesoscale in the form of a representative volume element (RVE). The interface of the two materials is modeled using a cohesive zone model. A parametric study has been performed to understand the effect of grain size and interface fracture toughness as well as strength on the mechanical performance of the joint. It was found that the grain size of AZ31 Mg alloy, as well as DP590 steel, has little effect on the overall joint performance. On the other hand, interface fracture toughness and strength have a significant impact on the mechanical properties of the joint

36 MATERIALS SCIENCE↗
NASA NTRS1992

A differential CDM model for fatigue of unidirectional metal matrix composites

A multiaxial, isothermal, continuum damage mechanics (CDM) model for fatigue of a unidirectional metal matrix composite volume element is presented. The model is phenomenological, stress based, and assumes a single scalar internal damage variable, the evolution of which is anisotropic. The development of the fatigue damage model, (i.e., evolutionary law) is based on the definition of an initially transversely isotropic fatigue limit surface, a static fracture surface, and a normalized stress amplitude function. The anisotropy of these surfaces and function, and therefore the model, is defined through physically meaningful invariants reflecting the local stress and material orientation. This transversely isotropic model is shown, when taken to it's isotropic limit, to directly simplify to a previously developed and validated isotropic fatigue continuum damage model. Results of a nondimensional parametric study illustrate (1) the flexibility of the present formulation in attempting to characterize a class of composite materials, and (2) the capability of the formulation in predicting anticipated qualitative trends in the fatigue behavior of unidirectional metal matrix composites. Also, specific material parameters representing an initial characterization of the composite system SiC/Ti 15-3 and the matrix material (Ti 15-3) are reported.

Arnold, S. M.↗
DOE OSTI2026

Quantifying uncertainty in physics-based predictions of rare-isotope production cross sections via Bayesian-inspired model averaging across nuclear mass tables

Accurate prediction of fragmentation cross sections is essential for rare-isotope beam production, planning new-isotope searches, and designing experiments to study the most exotic regions of the nuclear chart. However, existing reaction models and phenomenological cross-section parametrizations often exhibit significant deviations over broad regions of mass and charge. In this work, a Bayesian-inspired model-averaging framework is developed to combine abrasion-ablation (AA) calculations based on multiple nuclear mass tables into a single statistically weighted estimate. For the calibrated systems, the model weights are assigned empirically according to the relative quality of fit to measured cross sections, thereby reducing systematic model bias while preserving the underlying physics content of the AA description. The weights are constrained using proton-rich fragmentation data for the 78 Kr and 124 Xe projectiles. The resulting parameter trends are then propagated to the 92 Mo and 144 Sm systems through a controlled scaling procedure. In the present implementation, the excitation-energy prescription is fixed, while the averaging is performed across nuclear-mass inputs; the framework provides both weighted cross sections and associated uncertainty estimates. Applied to proton-rich fragmentation, the present approach provides a practical basis for interpolation and limited extrapolation in regions relevant to rare-isotope production. The resulting predictions are used to assess the production of very proton-rich nuclei, and candidate new isotopes are discussed.

Bayesian methods↗
DOE OSTI2025

The impact of $γN$ and $γ^∗N$ interactions on our understanding of nucleon excitations

We review recent progress in our understanding of the nucleon excitation spectrum. Thanks to dedicated efforts at facilities such as ELSA, MAMI and Jefferson Lab, several new nucleon resonances have been discovered, and evidence for previously elusive states has been significantly improved. Numerous decay channels have been observed for the first time, and resonance properties are being extracted from these data by several groups through coupled-channel analyses of varying complexity. Electroproduction experiments have provided further insights into the internal structure of light baryon resonances – for example, the long-debated Roper resonance N (1440) is observed as a three-quark state with a significant meson-cloud component. While the non-relativistic quark model remains a valuable tool for organizing the spectrum of nucleon and Δ resonances, a variety of theoretical frameworks have emerged to offer deeper understanding, including phenomenological quark models, holographic QCD, functional methods, effective field theories, and lattice QCD. We examine the interplay between these approaches, highlight their respective strengths and explore how they complement each other in shaping our knowledge of light baryon resonances. We address several open questions in baryon spectroscopy, including the nature of the enigmatic Λ (1405), ongoing searches for exotic states such as hybrid baryons and pentaquarks, and the dichotomy between microscopic descriptions of baryons in terms of quarks and gluons versus effective hadronic descriptions based on meson-baryon dynamics.

Baryon resonances↗
NASA NTRS1981

Multi-parameter yield zone model for predicting spectrum crack growth

A phenomenological load interaction model referred to as the Multi-Parameter Yield Zone model is presented which accounts for crack growth retardation caused by previous overloads, acceleration due to current overloads, and underload effects. In the present model, load interaction effects are calculated utilizing a residual stress intensity concept. Crack growth retardation and acceleration are accounted for by decreasing or increasing, respectively, the effective stress ratio used in a modified Forman's (1967) crack growth equation. Results of spectrum crack growth predictions for 2219-T851 aluminum are presented.

Johnson, W. S.↗
DOE OSTI2025

3 𝑃 0 model revisited

We revisit the phenomenological 3 𝑃 0 model for the decay of quarkonium ($Q\bar{Q}$) into two open flavor mesons ($\bar{𝔐}⁢𝔐$). We take the heavy-quark limit and derive a transition rate between $Q\bar{Q}$ and $\bar{𝔐}⁢𝔐$ to be compared with the one calculated in studies of string breaking using lattice QCD. This comparison allows us to fit the creation amplitude of a light quark-antiquark pair in the 3 𝑃 0 model to the string-breaking transition rate in QCD.

lifetimes & widths↗
NASA NTRS1991

Differential continuum damage mechanics models for creep and fatigue of unidirectional metal matrix composites

Three multiaxial isothermal continuum damage mechanics models for creep, fatigue, and creep/fatigue interaction of a unidirectional metal matrix composite volume element are presented, only one of which will be discussed in depth. Each model is phenomenological and stress based, with varying degrees of complexity to accurately predict the initiation and propagation of intergranular and transgranular defects over a wide range of loading conditions. The development of these models is founded on the definition of an initially transversely isotropic fatigue limit surface, static fracture surface, normalized stress amplitude function and isochronous creep damage failure surface, from which both fatigue and creep damage evolutionary laws can be obtained. The anisotropy of each model is defined through physically meaningful invariants reflecting the local stress and material orientation. All three transversely isotropic models have been shown, when taken to their isotropic limit, to directly simplify to previously developed and validated creep and fatigue continuum damage theories. Results of a nondimensional parametric study illustrate (1) the flexibility of the present formulation when attempting to characterize a large class of composite materials, and (2) its ability to predict anticipated qualitative trends in the fatigue behavior of unidirectional metal matrix composites. Additionally, the potential for the inclusion of various micromechanical effects (e.g., fiber/matrix bond strength, fiber volume fraction, etc.), into the phenomenological anisotropic parameters is noted, as well as a detailed discussion regarding the necessary exploratory and characterization experiments needed to utilize the featured damage theories.

Arnold, S. M.↗
DOE OSTI2023

Modular machine learning-based elastoplasticity: Generalization in the context of limited data

The development of highly accurate constitutive models for materials that undergo path-dependent processes continues to be a complex challenge in computational solid mechanics. Challenges arise both in considering the appropriate model assumptions and from the viewpoint of data availability, verification, and validation. Recently, data-driven modeling approaches have been proposed that aim to establish stress-evolution laws that avoid user-chosen functional forms by relying on machine learning representations and algorithms. However, these approaches not only require a significant amount of data but also need data that probes the full stress space with a variety of complex loading paths. Furthermore, they rarely enforce all necessary thermodynamic principles as hard constraints. Hence, they are in particular not suitable for low-data or limited-data regimes, where the first arises from the cost of obtaining the data and the latter from the experimental limitations of obtaining labeled data, which is commonly the case in engineering applications. In this work, we discuss a hybrid framework that can work on a variable amount of data by relying on the modularity of the elastoplasticity formulation where each component of the model can be chosen to be either a classical phenomenological or a data-driven model depending on the amount of available information and the complexity of the response. The method is tested on synthetic uniaxial data coming from simulations as well as cyclic experimental data for structural materials. The discovered material models are found to not only interpolate well but also allow for accurate extrapolation in a thermodynamically consistent manner far outside the domain of the training data. This ability to extrapolate from limited data was the main reason for the early and continued success of phenomenological models and the main shortcoming in machine learning-enabled constitutive modeling approaches. Training aspects and details of the implementation of these models into Finite Element simulations are discussed and analyzed.

42 ENGINEERING↗
NASA NTRS1978

The relation of open magnetic structures to solar wind flow

A study has been made of solar wind observations and models of the low-coronal magnetic field of the sun during the Skylab mission. Potential sources of solar wind plasma have been identified and in most cases systematically associated with observed solar wind flow features. The study pinpoints the problems of associating significant portions of the observed solar wind with sources outside coronal holes, although such associations are strongly suggested by the models. The phenomenological relationship between observed high solar wind speed at 1 AU and small coronal field divergence near the sun is examined and found to be well established but causally inconclusive in light of models of the outer heliosphere.

Levine, R. H.↗