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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Nonequilibrium statistical mechanics and optimal prediction of partially-observed complex systems

Abstract Only a subset of degrees of freedom are typically accessible or measurable in real-world systems. As a consequence, the proper setting for empirical modeling is that of partially-observed systems. Notably, data-driven models consistently outperform physics-based models for systems with few observable degrees of freedom; e.g. hydrological systems. Here, we provide an operator-theoretic explanation for this empirical success. To predict a partially-observed system’s future behavior with physics-based models, the missing degrees of freedom must be explicitly accounted for using data assimilation and model parametrization. Data-driven models, in contrast, employ delay-coordinate embeddings and their evolution under the Koopman operator to implicitly model the effects of the missing degrees of freedom. We describe in detail the statistical physics of partial observations underlying data-driven models using novel maximum entropy and maximum caliber measures. The resulting nonequilibrium Wiener projections applied to the Mori–Zwanzig formalism reveal how data-driven models may converge to the true dynamics of the observable degrees of freedom. Additionally, this framework shows how data-driven models infer the effects of unobserved degrees of freedom implicitly, in much the same way that physics models infer the effects explicitly. This provides a unified implicit-explicit modeling framework for predicting partially-observed systems, with hybrid physics-informed machine learning methods combining both implicit and explicit aspects.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Yield Precursor Dislocation Avalanches in Small Crystals: The Irreversibility Transition

The transition from elastic to plastic deformation in crystalline metals shares history dependence and scale-invariant avalanche signature with other nonequilibrium systems under external loading such as colloidal suspensions. These other systems exhibit transitions with clear analogies to work hardening and yield stress, with many typically undergoing purely elastic behavior only after “training” through repeated cyclic loading; studies in these other systems show a power-law scaling of the hysteresis loop extent and of the training time as the peak load approaches a so-called reversible-to-irreversible transition (RIT). We discover here that deformation of small crystals shares these key characteristics: yielding and hysteresis in uniaxial compression experiments of single-crystalline Cu nano- and micropillars decay under repeated cyclic loading. Here, the amplitude and decay time of the yield precursor avalanches diverge as the peak stress approaches failure stress for each pillar, with a power-law scaling virtually equivalent to RITs in other nonequilibrium systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

The Milky Way Project and ATLASGAL: the distribution and physical properties of cold clumps near infrared bubbles

We present a statistical study of the distribution and physical properties of cold, dense material in and around the inner Galactic Plane near-infrared bubbles as cataloged by the Milky Way Project citizen scientists. Using data from the Atacama Pathfinder Experiment (APEX) Telescope Large Area Survey of the Galaxy 870 μm survey, we show that 48 ± 2% of all cold clumps in the studied survey region (|l|⩽65{sup ∘}, |b|⩽1{sup ∘}) are found in close proximity to a bubble, and 25 ± 2% appear directly projected toward a bubble rim. A two-point correlation analysis confirms the strong correlation of massive cold clumps with expanding bubbles. It shows an overdensity of clumps along bubble rims that grows with increasing bubble size, which shows how interstellar medium material is reordered on large scales by bubble expansion around regions of massive star formation. The highest column density clumps appear to be resistent to the expansion, remaining overdense toward the bubbles’ interior rather than being swept up by the expanding edge. Spectroscopic observations in ammonia show that cold dust clumps near bubbles appear to be denser, hotter, and more turbulent than those in the field, offering circumstantial evidence that bubble-associated clumps are more likely to be forming stars. These observed differences in physical conditions persist beyond the region of the bubble rims.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Nonequilibrium vibrational population and donor-acceptor vibrations affecting rates of radiationless transitions

Here, an analytical theory is developed for radiationless transitions in molecules characterized by nonequilibrium populations of their vibrational modes. Several changes to the standard transition-state framework follow from nonequilibrium conditions: (i) non-Arrhenius kinetics, (ii) the violation of the fluctuation-dissipation theorem (FDT), and (iii) the breakdown of the detailed balance. The violation of the FDT is reflected in the breakdown of relations between the first (Stokes shift) and second (inhomogeneous band-width) spectral moments, and of similar relations between reorganization parameters for radiationless transitions. The detailed balance between the forward and backward rates is not maintained, requiring a lower effective free energy of the reaction relative to the thermodynamic limit. Lastly, the model suggests that strong control of radiationless transitions can be achieved if a nonequilibrium population of vibrations modulating the donor-acceptor distance is produced.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Physics based Reliability Models for Supercritical CO 2 Turbomachinery Components

CSP plants using sCO 2 power cycle can potentially achieve high thermal conversion efficiency at low capital cost due to compact turbo-machinery and other components. An sCO 2 expander and improved heat exchanger is expected to provide a major stepping stone for achieving CSP power at $0.06/kW-hr LCOE, energy conversion efficiency > 50%, and total power block cost < $1,200/kW installed. Hybrid gas bearings (HGB) and Dry gas seals (DGS) are two key components that are critical for robust and efficient operation of future sCO 2 power cycles. From a system perspective, HGBs can provide substantial benefits (~3 to 5%) to the modular CSP operation, while use of DGSs limits the leakage losses as well as the windage losses in the generator and can increase overall generator efficiency by ~ 8%. The life limiting mechanisms of HGBs and DGSs in high pressure, high temperature sCO2 environment were not well understood and hence this program aims at developing physics-based performance prediction and life prediction models for these two components. The output of the performance models serves as input to the life models. The performance models were validated using experimental data and using data from literature. DGS and HGB models have shed light on some risks associated with its operation in sCO2 expander and will guide more robust designs tailored towards sCO 2 cycle applications. A DGS was tested in 1MWe sCO2 turbo expander to study its performance and validate the performance models. To understand the effect of high pressures, high temperatures and sCO 2 environment on crack initiation, crack propagation and LCF/HCF life of these components, a novel experimental setup was developed. The LCF test data was used to calibrate and validate the life prediction models. The effect of sCO 2 corrosion on the life of Ni-based super-alloys is quantified using long duration experiments. Advanced microstructure and spectroscopic analyses conducted shed light on some key differences between IN718 and IN617 in terms of oxidation morphology, chemical species diffusion and trapping, the formation of protective corrosion resistant layers and changes in surface properties. A novel crack initiation model was developed which takes into account strain distribution, temperature, hold times and activation energy at the gas-metal interface and predicts the number of cycles to initiate the crack in the Inconel alloy. An advanced 3D fracture mechanics-based crack propagation model was also developed which takes into account the transient loading mission of the component and predict how fast the crack will grow and what will be its final shape and size. High energy X-Ray tomography measurements were conducted to study and validate 3D morphology of crack growth inside the specimen. These two models along with chemical kinetics models obtained from corrosion tests can be combined to predict the total life of the component under given long term operating conditions. A Bayesian Hybrid Modeling (BHM) probabilistic framework was developed to quantify uncertainty in physics-based performance models and in crack initiation and crack propagation models, to calibrate the models and to validate the models with statistical confidence. Advanced coupled physics multi-phase flow models were developed to study condensation, boiling and phase change behavior of CO 2 under various sCO 2 turbomachinery and heat exchanger conditions. A novel experimental setup was also designed to observe phase change of CO 2 during its transition across liquid-gas-supercritical state lines.

14 SOLAR ENERGY↗
DOE OSTI2019

Physics based Reliability Models for Supercritical CO 2 Turbomachinery Components

CSP plants using sCO 2 power cycle can potentially achieve high thermal conversion efficiency at low capital cost due to compact turbo-machinery and other components. An sCO 2 expander and improved heat exchanger is expected to provide a major stepping stone for achieving CSP power at 0.06/kW-hr LCOE, energy conversion efficiency > 50 % ,and total power block cost< $1,200/kW installed. Hybrid gas bearings (HGB) and Dry gas seals (DGS) are two key components that are critical for robust and efficient operation of future sCO 2 power cycles. From a system perspective, HGBs can provide substantial benefits (~3 to 5%) to the modular CSP operation, while use of DGSs limits the leakage losses as well as the windage losses in the generator and can increase overall generator efficiency by ~ 8%. The life limiting mechanisms of HGBs and DGSs in high pressure, high temperature sCO 2 environment were not well understood and hence this program aims at developing physics-based performance prediction and life prediction models for these two components. The output of the performance models serves as input to the life models. The performance models were validated using experimental data and using data from literature. DGS and HGB models have shed light on some risks associated with its operation in sCO 2 expander and will guide more robust designs tailored towards sCO 2 cycle applications. A DGS was tested in 1MWe sCO 2 turbo expander to study its performance and validate the performance models. To understand the effect of high pressures, high temperatures and sCO 2 environment on crack initiation, crack propagation and LCF/HCF life of these components, a novel experimental setup was developed. The LCF test data was used to calibrate and validate the life prediction models. The effect of sCO 2 corrosion on the life of Ni-based super-alloys is quantified using long duration experiments. Advanced microstructure and spectroscopic analyses conducted shed light on some key differences between IN718 and IN617 in terms of oxidation morphology, chemical species diffusion and trapping, the formation of protective corrosion resistant layers and changes in surface properties. A novel crack initiation model was developed which takes into account strain distribution, temperature, hold times and activation energy at the gas-metal interface and predicts the number of cycles to initiate the crack in the Inconel alloy. An advanced 3D fracture mechanics-based crack propagation model was also developed which takes into account the transient loading mission of the component and predict how fast the crack will grow and what will be its final shape and size. High energy X-Ray tomography measurements were conducted to study and validate 3D morphology of crack growth inside the specimen. These two models along with chemical kinetics models obtained from corrosion tests can be combined to predict the total life of the component under given long term operating conditions. A Bayesian Hybrid Modeling (BHM) probabilistic framework was developed to quantify uncertainty in physics-based performance models and in crack initiation and crack propagation models, to calibrate the models and to validate the models with statistical confidence. Advanced coupled physics multi-phase flow models were developed to study condensation, boiling and phase change behavior of CO 2 under various sCO 2 turbomachinery and heat exchanger conditions. A novel experimental setup was also designed to observe phase change of CO 2 during its transition across liquid-gas-supercritical state lines.

14 SOLAR ENERGY↗
DOE OSTI2024

Explainable AI classification for parton density theory

Quantitatively connecting properties of parton distribution functions (PDFs, or parton densities) to the theoretical assumptions made within the QCD analyses which produce them has been a longstanding problem in HEP phenomenology. To confront this challenge, we introduce an ML-based explainability framework, XAI4PDF, to classify PDFs by parton flavor or underlying theoretical model using ResNet-like neural networks (NNs). By leveraging the differentiable nature of ResNet models, this approach deploys guided backpropagation to dissect relevant features of fitted PDFs, identifying x-dependent signatures of PDFs important to the ML model classifications. By applying our framework, we are able to sort PDFs according to the analysis which produced them while constructing quantitative, human-readable maps locating the x regions most affected by the internal theory assumptions going into each analysis. This technique expands the toolkit available to PDF analysis and adjacent particle phenomenology while pointing to promising generalizations.

Artificial Intelligence↗
DOE OSTI2015

An opinion-driven behavioral dynamics model for addictive behaviors

We present a model of behavioral dynamics that combines a social network-based opinion dynamics model with behavioral mapping. The behavioral component is discrete and history-dependent to represent situations in which an individual’s behavior is initially driven by opinion and later constrained by physiological or psychological conditions that serve to maintain the behavior. Additionally, individuals are modeled as nodes in a social network connected by directed edges. Parameter sweeps illustrate model behavior and the effects of individual parameters and parameter interactions on model results. Mapping a continuous opinion variable into a discrete behavioral space induces clustering on directed networks. Clusters provide targets of opportunity for influencing the network state; however, the smaller the network the greater the stochasticity and potential variability in outcomes. Furthermore, this has implications both for behaviors that are influenced by close relationships verses those influenced by societal norms and for the effectiveness of strategies for influencing those behaviors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Structural relaxation and aging scaling in the Coulomb and Bose glass models

We employ Monte Carlo simulations to study the relaxation properties of the two-dimensional Coulomb glass in disordered semiconductors and the three-dimensional Bose glass in type-II superconductors in the presence of extended linear defects. We investigate the effects of adding non-zero random on-site energies from different distributions on the properties of the correlation-induced Coulomb gap in the density of states (DOS) and on the non-equilibrium aging kinetics highlighted by the density autocorrelation functions. Here, we also probe the sensitivity of the system’s equilibrium and non-equilibrium relaxation properties to instantaneous changes in the density of charge carriers in the Coulomb glass or flux lines in the Bose glass.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Dynamical regimes of vortex flow in type-II superconductors with parallel twin boundaries

We explore the dynamics of driven magnetic flux lines in disordered type-II superconductors in the presence of twin boundaries oriented parallel to the direction of the applied magnetic field, using a three-dimensional elastic line model simulated with Langevin molecular dynamics. The lines are driven perpendicular to the planes to model the effect of an electric current applied parallel to the planes and perpendicular to the magnetic field. A study of the long-time non-equilibrium steady states for varying sample orientation and thickness reveals a rich collection of dynamical regimes spanning the depinning crossover region that separates the pinned and moving-lattice states of vortex matter. We observe the emergence of a preferred direction for the ordering of the Abrikosov lattice in the free- owing vortex regime due to asymmetric pinning by the planar defects. Furthermore, we have performed novel direct measurements of flux line excitations such as half-loops and double kinks to aid the characterization of the topologically rich flux flow profile.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Exactly solvable dynamics of forced polymer loops

Here, we show that a problem of forced polymer loops can be mapped to an asymmetric simple exclusion process with reflecting boundary conditions. The dynamics of the particle system can be solved exactly using the Bethe ansatz. We thus can fully describe the relaxation dynamics of forced polymer loops. In the steady state, the conformation of the loop can be approximated by a combination of Fermi–Dirac and Brownian bridge statistics, while the exact solution is found by using the fermion integer partition theory. With the theoretical framework presented here we establish a link between the physics of polymers and statistics of many-particle systems opening new paths of exploration in both research fields. Our result can be applied to the dynamics of the biopolymers which form closed loops. One such example is the active pulling of chromosomal loops during meiosis in yeast cells which helps to align chromosomes for recombination in the viscous environment of the cell nucleus.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

An implementation of neural simulation-based inference for parameter estimation in ATLAS

Neural simulation-based inference (NSBI) is a powerful class of machine-learning-based methods for statistical inference that naturally handles high-dimensional parameter estimation without the need to bin data into low-dimensional summary histograms. Such methods are promising for a range of measurements, including at the Large Hadron Collider, where no single observable may be optimal to scan over the entire theoretical phase space under consideration, or where binning data into histograms could result in a loss of sensitivity. This work develops a NSBI framework for statistical inference, using neural networks to estimate probability density ratios, which enables the application to a full-scale analysis. It incorporates a large number of systematic uncertainties, quantifies the uncertainty due to the finite number of events in training samples, develops a method to construct confidence intervals, and demonstrates a series of intermediate diagnostic checks that can be performed to validate the robustness of the method. As an example, the power and feasibility of the method are assessed on simulated data for a simplified version of an off-shell Higgs boson couplings measurement in the four-lepton final states. This approach represents an extension to the standard statistical methodology used by the experiments at the Large Hadron Collider, and can benefit many physics analyses.

frequentist statistics↗
DOE OSTI2018

DNA molecules deviate from shortest trajectory when driven through hydrogel

Dynamic fluorescence-based single-molecule imaging of $λ$-DNA molecules driven through agarose hydrogels by DC electric fields reveals that passage through the hydrogel (98.5% water content) induces mobility orthogonal to the external field. Tortuous paths followed by the DNA molecules, which are heavily entangled in the hydrogel mesh as their contour length is nearly 100 times the hydrogel mesh size of 200 nm, cause them to appear to diffuse orthogonal to the driving force. The higher the driving field, from 2 to 16 V/cm, the higher the off-axis dispersion is, over the same time interval. In this work we measure the off-axis displacement distribution over 3 orders of magnitude of probability density and find a master curve after normalizing for time (t) elapsed, but the power of time for normalizing increases with the external field, from t 0.25 to t 0.6 with increasing field. Comparing trajectories over the same distance traveled in the electric field direction, we observe whereas for the highest field strengths DNA molecules come closest to taking the shortest trajectory between two points in space, deviations from the shortest trajectory grow larger and larger (up to 40% larger) as one approaches the case of small yet finite external field strength.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Model reduction methods for nuclear emulators

The field of model order reduction (MOR) is growing in importance due to its ability to extract the key insights from complex simulations while discarding computationally burdensome and superfluous information. We provide an overview of MOR methods for the creation of fast & accurate emulators of memory- and compute-intensive nuclear systems, focusing on eigen-emulators and variational emulators. As an example, we describe how 'eigenvector continuation' is a special case of a much more general and well-studied MOR formalism for parameterized systems. We continue with an introduction to the Ritz and Galerkin projection methods that underpin many such emulators, while pointing to the relevant MOR theory and its successful applications along the way. Here, we believe that this guide will open the door to broader applications in nuclear physics and facilitate communication with practitioners in other fields.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Method of resource-limited device and device class identification using system and function call tracing techniques, performance, and statistical analysis

Methods for cyber physical systems device classification are provided. A method can include receiving system and function calls and parameters and a device performance index from an unknown CPS device and a device performance index of similar class of CPS devices, calculating an autocorrelation value between different realizations of the system and function calls and parameters of the known CPS device, determining whether the autocorrelation value is greater than a threshold amount, and storing the system and function calls and parameters and the device performance characteristics of the known CPS device in the database. A method can also include calculating a correlation between system and function calls and parameters of an unknown CPS device and known CPS devices classes included in the database, as well as determining whether the maximum correlation is also greater than a threshold amount.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗