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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Equilibrium polymerization on the equivalent-neighbor lattice

The equilibrium polymerization problem is solved exactly on the equivalent-neighbor lattice. The Flory-Huggins (Flory, 1986) entropy of mixing is exact for this lattice. The discrete version of the n-vector model is verified when n approaches 0 is equivalent to the equal reactivity polymerization process in the whole parameter space, including the polymerized phase. The polymerization processes for polymers satisfying the Schulz (1939) distribution exhibit nonuniversal critical behavior. A close analogy is found between the polymerization problem of index the Schulz r and the Bose-Einstein ideal gas in d = -2r dimensions, with the critical polymerization corresponding to the Bose-Einstein condensation.

Kaufman, Miron↗
DOE OSTI2025

Novel Results Visualization for Dynamic PSA and New Modeling Features in EMRALD

The Event Modeling Risk Assessment Linked Diagram (EMRALD) tool, developed at the Idaho National Laboratory (INL), was designed to simplify the creation of dynamic models and support various research projects. One of the primary goals of EMRALD was to provide visual methods for modeling. EMRALD consists of two main components: a web-based user interface for model development and a solve engine for running model simulations. Over time, it has evolved to meet the diverse needs of its users. Initially, EMRALD's results were simple text outputs with final key state percentages and uncertainty bounds. However, because EMRALD utilizes a three-phase discrete event simulation and tracks the paths of each simulation run leading to a key state, there is significant potential to analyze large sets of path results data, including state paths, events, and timing. Visualizing this data meaningfully posed a challenge. To address this, a novel time-based Sankey diagram was developed. EMRALD exports results data in a format that can be opened in this Sankey viewer, allowing users to visualize paths, occurrences, events, and probability data for the entire simulation run in a single diagram. Moreover, when EMRALD was first created, there were limited tools capable of meeting its graphical requirements, many of which are no longer supported. In 2024, a new web-based interface was developed using modern graphing tools, enabling additional modeling features. This paper discusses the new dynamic PSA results visualization capability and the enhanced modeling tools available in EMRALD.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2022

CFD-DEM Modeling of Autothermal Pyrolysis of Corn Stover with a Coupled Particle- and Reactor-Scale Framework

Autothermal operation of fast pyrolysis is an efficient process-intensification technique wherein exothermic oxidation reactions are used to overcome the heat-transfer bottleneck of conventional pyrolysis. The development of accurate, reliable modeling toolsets is imperative to generating a deeper understanding of biomass autothermal pyrolysis systems to support scale-up and industrial deployment. This modeling effort describes the development of single-particle and reactor models which incorporate detailed reaction schemes and simultaneous exothermic oxidation reactions. The particle-scale model was parameterized for corn stover feedstock with particle morphology, density, ash content, and biopolymer composition, all of which impact the emergent conversion characteristics during pyrolysis. Results were then used to parameterize a reactor-scale autothermal pyrolysis model, which was developed using a coarse-grained computational fluid dynamic-discrete element method. The simulation results compared well with experimental results, with the predicted bio-oil, light gas, and biochar yield within 3.0 wt% of the experimental yields. Further analyses were performed to test the influence of equivalence ratio, biomass injection position, and particle size distribution on autothermal pyrolysis. The analysis of the physio-chemical properties of the fluid and solid phase inside the reactor and at the reactor outlet help reveal important process interactions of autothermal pyrolysis.

BIOMASS FUELS,INORGANIC, ORGANIC, PHYSICAL, AND AN↗
NASA NTRS2007

Hybrid Automated Diagnosis of Discrete/Continuous Systems

A recently conceived method of automated diagnosis of a complex electromechanical system affords a complete set of capabilities for hybrid diagnosis in the case in which the state of the electromechanical system is characterized by both continuous and discrete values (as represented by analog and digital signals, respectively). The method is an integration of two complementary diagnostic systems: (1) beacon-based exception analysis for multi-missions (BEAM), which is primarily useful in the continuous domain and easily performs diagnoses in the presence of transients; and (2) Livingstone, which is primarily useful in the discrete domain and is typically restricted to quasi-steady conditions. BEAM has been described in several prior NASA Tech Briefs articles: "Software for Autonomous Diagnosis of Complex Systems" (NPO-20803), Vol. 26, No. 3 (March 2002), page 33; "Beacon-Based Exception Analysis for Multimissions" (NPO-20827), Vol. 26, No. 9 (September 2002), page 32; "Wavelet-Based Real-Time Diagnosis of Complex Systems" (NPO-20830), Vol. 27, No. 1 (January 2003), page 67; and "Integrated Formulation of Beacon-Based Exception Analysis for Multimissions" (NPO-21126), Vol. 27, No. 3 (March 2003), page 74. Briefly, BEAM is a complete data-analysis method, implemented in software, for real-time or off-line detection and characterization of faults. The basic premise of BEAM is to characterize a system from all available observations and train the characterization with respect to normal phases of operation. The observations are primarily continuous in nature. BEAM isolates anomalies by analyzing the deviations from nominal for each phase of operation. Livingstone is a model-based reasoner that uses a model of a system, controller commands, and sensor observations to track the system s state, and detect and diagnose faults. Livingstone models a system within the discrete domain. Therefore, continuous sensor readings, as well as time, must be discretized. To reason about continuous systems, Livingstone uses monitors that discretize the sensor readings using trending and thresholding techniques. In development of the a hybrid method, BEAM results were sent to Livingstone to serve as an independent source of evidence that is in addition to the evidence gathered by Livingstone standard monitors. The figure depicts the flow of data in an early version of a hybrid system dedicated to diagnosing a simulated electromechanical system. In effect, BEAM served as a "smart" monitor for Livingstone. BEAM read the simulation data, processed the data to form observations, and stored the observations in a file. A monitor stub synchronized the events recorded by BEAM with the output of the Livingstone standard monitors according to time tags. This information was fed to a real-time interface, which buffered and fed the information to Livingstone, and requested diagnoses at the appropriate times. In a test, the hybrid system was found to correctly identify a failed component in an electromechanical system for which neither BEAM nor Livingstone alone yielded the correct diagnosis.

Park, Han↗
DOE OSTI2022

An approximate inertial manifold (AIM) based closure for turbulent flows

A closure model for turbulent flows is developed based on a dynamical system theory. An appropriately discretized formulation of the governing equations is considered for this process. The key ingredient is an approximation of the system’s attractor, where all the trajectories in phase space are confined. This approximate inertial manifold based approach provides a path to track trajectories of the system in a lower-dimensional subspace. Unlike conventional coarse-graining approaches, the turbulent field is decomposed into resolved and unresolved dynamics using the properties of the governing equations. The novelty of the approach relies on the reconstruction of the unresolved field constrained by the governing equations. A posteriori tests for homogeneous isotropic turbulence and the Kuramoto–Sivashinsky equation show promising results for considerable dimension reduction with strong convergence properties. The proposed model outperforms the dynamic Smagorinsky model, and the computational overhead is competitive with similar approaches.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Instabilities and phase transitions in architected metamaterials: a gradient-enhanced continuum approach

Architected metamaterials such as foams and lattices exhibit a wide range of properties governed by microstructural instabilities and emerging phase transitions. Their macroscopic response–including energy dissipation during impact, large recoverable deformations, morphing between configurations, and auxetic behavior–remains difficult to capture with conventional continuum models, which often rely on discrete approaches that limit scalability. In this work, we propose a nonlocal continuum formulation that captures both stable and unstable responses of elastic architected metamaterials. The framework extends anisotropic hyperelasticity by introducing nonlocal variables and internal length scales reflective of microstructural features. Local polyconvex free-energy models are systematically augmented with two families of non-(poly)convex energies, enabling both metastable and bistable responses. Implementation in a finite element framework enables solution using a hybrid monolithic–staggered strategy. Simulations capture densification fronts, forward and reverse transitions, hysteresis loops, imperfection sensitivity, and globally coordinated auxetic modes. Overall, this framework provides a robust foundation for accelerated modeling of instability-driven phenomena in architected metamaterials, while enabling extensions to anisotropic, dissipative, and active systems as well as integration with data-driven and machine learning approaches.

42 ENGINEERING↗
NASA NTRS1992

A multi-layer discrete-ordinate method for vector radiative transfer in a vertically-inhomogeneous, emitting and scattering atmosphere. I - Theory. II - Application

A theory is developed for discretizing the vector integro-differential radiative transfer equation including both solar and thermal radiation. A complete solution and boundary equations are obtained using the discrete-ordinate method. An efficient numerical procedure is presented for calculating the phase matrix and achieving computational stability. With natural light used as a beam source, the Stokes parameters from the model proposed here are compared with the analytical solutions of Chandrasekhar (1960) for a Rayleigh scattering atmosphere. The model is then applied to microwave frequencies with a thermal source, and the brightness temperatures are compared with those from Stamnes'(1988) radiative transfer model.

Weng, Fuzhong↗
DOE OSTI2020

Classical discrete time crystals

The spontaneous breaking of time-translation symmetry in periodically driven quantum systems leads to a new phase of matter: the discrete time crystal (DTC). This phase exhibits collective subharmonic oscillations that depend upon an interplay of non-equilibrium driving, many-body interactions and the breakdown of ergodicity. However, subharmonic responses are also a well-known feature of classical dynamical systems ranging from predator–prey models to Faraday waves and a.c.-driven charge density waves. This raises the question of whether these classical phenomena display the same rigidity characteristic of a quantum DTC. In this work, we explore this question in the context of periodically driven Hamiltonian dynamics coupled to a finite-temperature bath, which provides both friction and, crucially, noise. Focusing on one-dimensional chains, where in equilibrium any transition would be forbidden at finite temperature, we provide evidence that the combination of noise and interactions drives a sharp, first-order dynamical phase transition between a discrete time-translation invariant phase and an activated classical discrete time crystal (CDTC) in which time-translation symmetry is broken out to exponentially long timescales. Power-law correlations are present along a first-order line, which terminates at a critical point. We analyse the transition by mapping it to the locked-to-sliding transition of a d.c.-driven charge density wave. To conclude, building upon results from the field of probabilistic cellular automata, we conjecture the existence of classical time crystals with true long-range order, where time-translation symmetry is broken out to infinite times.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Modified Energy Span Analysis Reveals Heterogeneous Catalytic Kinetics

Mechanistic modeling is a cornerstone of catalyst development generally conducted with microkinetic models or density functional theory-based energy profiles. We extend the energy span model of homogeneous catalysis to heterogeneous systems by introducing the modified energy span analysis (MESA) model by implementing collision theory and gas-phase concentration effects. We determine analytically turnover frequencies, coverages, rate-determining steps, apparent activation energies, and reaction orders in agreement with microkinetic and kinetic Monte Carlo simulations. The model applies to discrete catalyst state systems, including single-atom catalysts, homogeneous systems, and microporous materials. A generalizable rate expression is derived for reactor modeling or mechanistic insights from solely experimentally measured reaction orders. Here, we illustrate MESA on three published mechanisms and reveal unexpected phenomena absent in traditional energy span profiles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2012

Adaptive control based on retrospective cost optimization

A discrete-time adaptive control law for stabilization, command following, and disturbance rejection that is effective for systems that are unstable, MIMO, and/or nonminimum phase. The adaptive control algorithm includes guidelines concerning the modeling information needed for implementation. This information includes the relative degree, the first nonzero Markov parameter, and the nonminimum-phase zeros. Except when the plant has nonminimum-phase zeros whose absolute value is less than the plant's spectral radius, the required zero information can be approximated by a sufficient number of Markov parameters. No additional information about the poles or zeros need be known. Numerical examples are presented to illustrate the algorithm's effectiveness in handling systems with errors in the required modeling data, unknown latency, sensor noise, and saturation.

Santillo, Mario A.↗
DOE OSTI2021

Evolution of microstructures in radiation fields using a coupled binary-collision Monte Carlo phase field approach

The simulation of radiation effects in materials broadly falls into two categories. At short time and length scales lies the modeling of primary radiation damage, such as point defect creation, energy deposition, and ballistic mixing. This is followed by the modeling at longer time scales of thermally activated microstructure evolution and defect reactions, such as recombination, clustering, and coarsening. The binary collision Monte Carlo method is an established, numerically efficient method for the computation of primary radiation damage. Conversely, the phase field method is a state of the art method for microstructure evolution on longer time and length scales. Here we present a concurrent coupling of these two methods, overcoming the difference between the discrete object Monte Carlo paradigm for primary radiation damage and the continuum field variable approach for microstructure evolution. The coupling is bidirectional, in which the microstructure evolution in the MOOSE finite element frame- work provides the spatial scattering data set for the charged particle trans- port and receives point defect, mass transport, and heat source terms from the simulated collision cascades that contribute to the field variable evolution. The concurrent coupling scheme is implemented in the code Magpie and demonstrated by investigating patterning for a model irradiated immiscible binary alloy. The results from the coupled binary collision Monte Carlo/phase field simulations reproduce the results of analytical models for phase separation, phase mixing, and patterning, supporting the approach and indicating its utility for modeling real materials systems.

36 MATERIALS SCIENCE↗
NASA NTRS1981

Analytical prediction of aerospace vehicle vibration environments

Considerable attention has been given recently to the formulation and validation of analytical models for the prediction of aerospace vehicle vibration response to acoustic and fluctuating pressures. This paper summarizes the development of such analytical models for two applications, (1) structural vibrations of the Space Shuttle orbiter vehicle due to broadband rocket noise and aerodynamic boundary layer turbulence, and (2) structural vibrations of general aviation aircraft due to discrete frequency propeller and reciprocating engine exhaust noise. In both cases, the spatial exterior excitations are convected pressure fields which are described on the basis of measured cross spectra (coherence and phase) information. Structural modal data are obtained from analytical predictions, and structural responses to appropriate excitation fields are calculated. The results are compared with test data, and the strengths and weaknesses of the analytical models are assessed.

Wilby, J. F.↗
DOE OSTI2020

A higher-order finite element reactive transport model for unstructured and fractured grids

Abstract This work presents a new reactive transport framework that combines a powerful geochemistry engine with advanced numerical methods for flow and transport in subsurface fractured porous media. Specifically, the PhreeqcRM interface (developed by the USGS) is used to take advantage of a large library of equilibrium and kinetic aqueous and fluid-rock reactions, which has been validated by numerous experiments and benchmark studies. Fluid flow is modeled by the Mixed Hybrid Finite Element (FE) method, which provides smooth velocity fields even in highly heterogenous formations with discrete fractures. A multilinear Discontinuous Galerkin FE method is used to solve the multicomponent transport problem. This method is locally mass conserving and its second order convergence significantly reduces numerical dispersion. In terms of thermodynamics, the aqueous phase is considered as a compressible fluid and its properties are derived from a Cubic Plus Association (CPA) equation of state. The new simulator is validated against several benchmark problems (involving, e.g., Fickian and Nernst-Planck diffusion, isotope fractionation, advection-dispersion transport, and rock-fluid reactions) before demonstrating the expanded capabilities offered by the underlying FE foundation, such as high computational efficiency, parallelizability, low numerical dispersion, unstructured 3D gridding, and discrete fraction modeling.

58 GEOSCIENCES↗
DOE OSTI2022

A gradient-based deep neural network model for simulating multiphase flow in porous media

We report simulation of multiphase flow in porous media is crucial for the effective management of subsurface energy and environment-related activities. The numerical simulators used for modeling such processes rely on spatial and temporal discretization of the governing mass and energy balance partial-differential equations (PDEs) into algebraic systems via finite-difference/volume/element methods. These simulators usually require dedicated software development and maintenance, and suffer low efficiency from a runtime and memory standpoint for problems with multi-scale heterogeneity, coupled-physics processes or fluids with complex phase behavior. Therefore, developing cost-effective, data-driven models can become a practical choice, and in this work, we choose deep learning approaches as they can handle high dimensional data and accurately predict state variables with strong nonlinearity. In this paper, we describe a gradient-based deep neural network (GDNN) constrained by the physics related to multiphase flow in porous media. We tackle the nonlinearity of flow in porous media induced by rock heterogeneity, fluid properties, and fluid-rock interactions by decomposing the nonlinear PDEs into a dictionary of elementary differential operators. We use a combination of operators to handle rock spatial heterogeneity and fluid flow by advection. Since the augmented differential operators are inherently related to the physics of fluid flow, we treat them as first principles prior knowledge to regularize the GDNN training. We use the example of pressure management at geologic CO 2 storage sites, where CO 2 is injected in saline aquifers and brine is produced, and apply GDNN to construct a predictive model that is trained with physics-based simulation data and emulates the physics process. We demonstrate that GDNN can effectively predict the nonlinear patterns of subsurface responses, including the temporal and spatial evolution of the pressure and saturation plumes. We also successfully extend the GDNN to convolutional neural network (CNN), namely gradient-based CNN (GCNN), and validate its capability to improve the prediction accuracy. GDNN has great potential to tackle challenging problems that are governed by highly nonlinear physics and enable the development of data-driven models with higher fidelity.

42 ENGINEERING↗
NASA NTRS1990

Space Station Freedom: Dynamic instrumentation for a large space structure

A proposed approach called Modal Identification Experiment (MIE) for obtaining on-orbit dynamic response measurements on Space Station Freedom, the first of a family of large, flexible space structures is discussed. The Phase 2 conceptual design study which provides a conceptual design of a proposed measurement system and an experimental protocol for inobstrusively collecting dynamic response data critical to characterizing important vibration modes of Space Station Freedom were recently concluded. The case for conducting such a measurement program is presented and the specific MIE objectives that were identified, are listed. The sequence of discrete Space Station Freedom assembly configurations is described, and the Phase 2 conceptual design of the experiment and instrumentation system are defined. In addition, a plan to utilize a space station hydrid scale model in laboratory simulations as part of the design process are discussed.

Raney, John P.↗
DOE OSTI2021

Delocalization of a non-Hermitian quantum walk on random media in one dimension

Highlights: • We study the localization-delocalization transition of a non-Hermitian quantum walk. • We find that the phase transition is similar to the one in the Hatano-Nelson model. • All eigenvectors get extended and all eigenvalues become complex at the transition. • This implies that the localization lengths of all eigenvectors are the same. We first review the localization–delocalization transition of a non-Hermitian random tight-binding Anderson model, called the Hatano–Nelson model. We then report a new result for a non-Hermitian extension of a discrete-time quantum walk on a one-dimensional random medium; we numerically find a delocalization transition similar to one of the Hatano–Nelson model. As a common feature to both models, at the transition point, an eigenvector gets delocalized and at the same time the corresponding energy eigenvalue (for the latter quantum-walk model, the imaginary unit times the phase of the eigenvalue of the time-evolution operator) becomes complex. One of the unique properties of the present non-Hermitian quantum walk is that the localization length of all eigenvectors is the same, and thereby all eigenstates simultaneously undergo the delocalization transition and all energy eigenvalues become complex at the same time when we turn up a non-Hermitian parameter.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

The role of cellular structure, non-equilibrium eutectic phases and precipitates on quasi-static strengthening mechanisms of as-built AlSi10Mg parts 3D printed via laser powder bed fusion

The quasi-static loading strengthening mechanism in the as-built state of an AlSi10Mg alloy 3D-printed via Laser Powder Bed Fusion (LPBF) was thoroughly identified and quantified using state-of-the-art electron microscopy and synchrotron X-ray diffraction techniques. The yield strength was comprehensively modelled through an in-depth characterization and quantification of the microstructural features as well as their effective volumes for strengthening. In particular, the non-equilibrium eutectic network was characterized with a two-fold structure: cell boundary particles as well as intracellular lamellar/fibrous networks, each consisting of discrete phases exhibiting a thru-thickness compositional gradient, a semi-coherent interface with the matrix and an abundance of crystal defects such as nano-sized sub-grains, microstrains and stacking faults. Further, these altogether made the eutectic phase the most potent contributor to the yield strength accounting for ~30–40% of the estimated value (i.e., cell boundary and eutectic network strengthening combined). Precipitates strengthening was identified as the second most potent mechanism via a shearing process only. Moreover, the presented methodology was able to capture the effect of LPBF processing variables on the individual strengthening contributions, e.g., the effect of a lower laser scanning speed on increasing the cell size as well as the mean precipitate size, which are shown to exhibit opposing impacts on strengthening.

36 MATERIALS SCIENCE↗