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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 181 records · Page 10

Statistical mechanics of light elements at high pressure. VI - Liquid-state calculations with Thomas-Fermi-Dirac theory

A model free energy is developed for hydrogen-helium mixtures based on solid-state Thomas-Fermi-Dirac calculations at pressures relevant to the interiors of giant planets. Using a model potential similar to that for a two-component plasma, effective charges for the nuclei (which are in general smaller than the actual charges because of screening effects) are parameterized, being constrained by calculations at a number of densities, compositions, and lattice structures. These model potentials are then used to compute the equilibrium properties of H-He fluids using a charged hard-sphere model. The results find critical temperatures of about 0 K, 500 K, and 1500 K, for pressures of 10, 100, and 1000 Mbar, respectively. These phase separation temperatures are considerably lower (approximately 6,000-10,000 K) than those found from calculations using free electron perturbation theory, and suggest that H-He solutions should be stable against phase separation in the metallic zones of Jupiter and Saturn.

Macfarlane, J. J.↗

Probabilistic Failure Criterion of SiC/SiC Composites Under Multiaxial Loading

Owing to its excellent mechanical properties and stability under high temperature and neutron irradiation conditions, SiC/SiC composites have emerged as a promising material for light water reactors (LWRs) in the development of accident-tolerant fuel (ATF) systems. Structural integrity and retention of hermeticity are two crucial requirements for SiC/SiC claddings during normal operations, and both of them are closely related to the proportional limit stress (PLS) of the material. Understanding the behavior of SiC/SiC composites under multiaxial stress states and developing a probabilistic approach for evaluating the structural vulnerability are of paramount importance for reliability-based analysis and design of SiC/SiC composite claddings. So far, there has been very limited effort towards experimental and analytical investigations of probabilistic failure of SiC/SiC claddings. This critical knowledge gap motivates this research. A probabilistic failure criterion for SiC/SiC composites under multi-axial loading is developed, and this criterion is incorporated into reliability analysis of the structural integrity of SiC/SiC fuel cladding. The research consists of two parts: 1) experimental investigation of multiaxial failure behavior of SiC/SiC composites, and 2) theoretical modeling of time-dependent probabilistic failure of SiC/SiC cladding. In the experimental investigation, the PLS is determined through the examination of stress-strain response, the acoustic emission measurement, as well as the X-ray computed tomography. The theoretical framework is derived by combin- ing the finite weakest-link statistical model and the subcritical damage growth model. This theoretical model captures the time-dependent failure mechanism of the material, which has a major consequence for predicting the lifetime distribution of the cladding. Meanwhile, the model also predicts that the failure statistics of the cladding depends strongly on the cladding length. The results of the multiaxial experiments reveal the level of statistical variation of the PLS of SiC/SiC materials under different stress states. The theoretical model provides a robust analytical tool for extrapolation of small-scale laboratory test results to the behavior of full-scale claddings. These findings establish a scientific foundation for the development of reliability-based design of SiC/SiC fuel claddings, which will play an essential role in improving the structural safety and integrity of LWRs.

42 ENGINEERING↗

Exploring the Connection Between Sampling Problems in Bayesian Inference and Statistical Mechanics

The Bayesian and statistical mechanical communities often share the same objective in their work - estimating and integrating probability distribution functions (pdfs) describing stochastic systems, models or processes. Frequently, these pdfs are complex functions of random variables exhibiting multiple, well separated local minima. Conventional strategies for sampling such pdfs are inefficient, sometimes leading to an apparent non-ergodic behavior. Several recently developed techniques for handling this problem have been successfully applied in statistical mechanics. In the multicanonical and Wang-Landau Monte Carlo (MC) methods, the correct pdfs are recovered from uniform sampling of the parameter space by iteratively establishing proper weighting factors connecting these distributions. Trivial generalizations allow for sampling from any chosen pdf. The closely related transition matrix method relies on estimating transition probabilities between different states. All these methods proved to generate estimates of pdfs with high statistical accuracy. In another MC technique, parallel tempering, several random walks, each corresponding to a different value of a parameter (e.g. "temperature"), are generated and occasionally exchanged using the Metropolis criterion. This method can be considered as a statistically correct version of simulated annealing. An alternative approach is to represent the set of independent variables as a Hamiltonian system. Considerab!e progress has been made in understanding how to ensure that the system obeys the equipartition theorem or, equivalently, that coupling between the variables is correctly described. Then a host of techniques developed for dynamical systems can be used. Among them, probably the most powerful is the Adaptive Biasing Force method, in which thermodynamic integration and biased sampling are combined to yield very efficient estimates of pdfs. The third class of methods deals with transitions between states described by rate constants. These problems are isomorphic with chemical kinetics problems. Recently, several efficient techniques for this purpose have been developed based on the approach originally proposed by Gillespie. Although the utility of the techniques mentioned above for Bayesian problems has not been determined, further research along these lines is warranted

Pohorille, Andrew↗

Dynamics of magnetization at infinite temperature in a Heisenberg spin chain

Understanding universal aspects of quantum dynamics is an unresolved problem in statistical mechanics. In particular, the spin dynamics of the one-dimensional Heisenberg model were conjectured as to belong to the Kardar-Parisi-Zhang (KPZ) universality class based on the scaling of the infinite-temperature spin-spin correlation function. In a chain of 46 superconducting qubits, we studied the probability distribution of the magnetization transferred across the chain’s center, P M . The first two moments of P M show superdiffusive behavior, a hallmark of KPZ universality. However, the third and fourth moments ruled out the KPZ conjecture and allow for evaluating other theories. Our results highlight the importance of studying higher moments in determining dynamic universality classes and provide insights into universal behavior in quantum systems.

Science & Technology - Other Topics↗

Error Bounds for Dynamical Spectral Estimation

Dynamical spectral estimation is a well-established numerical approach for estimating eigenvalues and eigenfunctions of the Markov transition operator from trajectory data. Although the approach has been widely applied in biomolecular simulations, its error properties remain poorly understood. Here we analyze the error of a dynamical spectral estimation method called “the variational approach to conformational dynamics" (VAC). We bound the approximation error and estimation error for VAC estimates. Our analysis establishes VAC's convergence properties and suggests new strategies for tuning VAC to improve accuracy.

97 MATHEMATICS AND COMPUTING↗

A Lattice Boltzmann Method for Turbomachinery Simulations

Lattice Boltzmann (LB) Method is a relatively new method for flow simulations. The start point of LB method is statistic mechanics and Boltzmann equation. The LB method tries to set up its model at molecular scale and simulate the flow at macroscopic scale. LBM has been applied to mostly incompressible flows and simple geometry.

Hsu, A. T.↗

Conserved Macromolecular Architecture of Poplar Secondary Cell Walls Revealed by ssNMR and Atomistic Modeling

The macromolecular architecture of plant secondary cell walls governs wood's mechanical and biochemical properties, yet its natural intra-species variability remains poorly characterized. Here, we combined 13C solid-state NMR (ssNMR), multivariate statistical analysis, and molecular modeling to profile nanoscale structure across 13 genetically diverse Populus trichocarpa genotypes grown in 13C-enriched atmospheres. SsNMR-derived phenotypes spanning composition, structure, mobility, and inter-polymer proximities reveal a conserved architecture, with a subtle yet coordinated variation organizing into dominant structural and secondary mobility axes. A representative atomistic model captures these features and reproduces experimental metrics. Molecular dynamics simulations support a weak but consistent positive correlation between cellulose abundance and crystalline-like order, with interior cellulose chains enriched in tg (trans-gauche) conformations without expanding crystalline cores. Together, experiment and simulation reveal a genetically buffered, broadly conserved nanoscale architecture across genotypes, where subtle fine-tuning of cellulose bundling and matrix packing balances mechanical performance with biological function.

09 BIOMASS FUELS↗

An Accident Precursor Analysis Process Tailored for NASA Space Systems

Accident Precursor Analysis (APA) serves as the bridge between existing risk modeling activities, which are often based on historical or generic failure statistics, and system anomalies, which provide crucial information about the failure mechanisms that are actually operative in the system and which may differ in frequency or type from those in the various models. These discrepancies between the models (perceived risk) and the system (actual risk) provide the leading indication of an underappreciated risk. This paper presents an APA process developed specifically for NASA Earth-to-Orbit space systems. The purpose of the process is to identify and characterize potential sources of system risk as evidenced by anomalous events which, although not necessarily presenting an immediate safety impact, may indicate that an unknown or insufficiently understood risk-significant condition exists in the system. Such anomalous events are considered accident precursors because they signal the potential for severe consequences that may occur in the future, due to causes that are discernible from their occurrence today. Their early identification allows them to be integrated into the overall system risk model used to intbrm decisions relating to safety.

Groen, Frank↗

Complex patterns of abnormal heartbeats

Individuals having frequent abnormal heartbeats interspersed with normal heartbeats may be at an increased risk of sudden cardiac death. However, mechanistic understanding of such cardiac arrhythmias is limited. We present a visual and qualitative method to display statistical properties of abnormal heartbeats. We introduce dynamical "heartprints" which reveal characteristic patterns in long clinical records encompassing approximately 10(5) heartbeats and may provide information about underlying mechanisms. We test if these dynamics can be reproduced by model simulations in which abnormal heartbeats are generated (i) randomly, (ii) at a fixed time interval following a preceding normal heartbeat, or (iii) by an independent oscillator that may or may not interact with the normal heartbeat. We compare the results of these three models and test their limitations to comprehensively simulate the statistical features of selected clinical records. This work introduces methods that can be used to test mathematical models of arrhythmogenesis and to develop a new understanding of underlying electrophysiologic mechanisms of cardiac arrhythmia.

Non-NASA Center↗

Extreme value statistics analysis of fracture strengths of a sintered silicon nitride failing from pores

Statistical analysis and correlation between pore-size distribution and fracture strength distribution using the theory of extreme-value statistics is presented for a sintered silicon nitride. The pore-size distribution on a polished surface of this material was characterized, using an automatic optical image analyzer. The distribution measured on the two-dimensional plane surface was transformed to a population (volume) distribution, using the Schwartz-Saltykov diameter method. The population pore-size distribution and the distribution of the pore size at the fracture origin were correllated by extreme-value statistics. Fracture strength distribution was then predicted from the extreme-value pore-size distribution, usin a linear elastic fracture mechanics model of annular crack around pore and the fracture toughness of the ceramic. The predicted strength distribution was in good agreement with strength measurements in bending. In particular, the extreme-value statistics analysis explained the nonlinear trend in the linearized Weibull plot of measured strengths without postulating a lower-bound strength.

Chao, Luen-Yuan↗

Enantioselective Allenoate-Claisen Rearrangement Using Chiral Phosphate Catalysts

Herein we report the first highly enantioselective allenoate-Claisen rearrangement using doubly axially chiral phosphate sodium salts as catalysts. This synthetic method provides access to β-amino acid derivatives with vicinal stereocenters in up to 95% ee. We also investigated the mechanism of enantioinduction by transition state (TS) computations with DFT as well as statistical modeling of the relationship between selectivity and the molecular features of both the catalyst and substrate. The mutual interactions of charge-separated regions in both the zwitterionic intermediate generated by reaction of an amine to the allenoate and the Na + -salt of the chiral phosphate leads to an orientation of the TS in the catalytic pocket that maximizes favorable noncovalent interactions. Crucial arene-arene interactions at the periphery of the catalyst lead to a differentiation of the TS diastereomers. Finally, these interactions were interrogated using DFT calculations and validated through statistical modeling of parameters describing noncovalent interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantum mechanical closure of partial differential equations with symmetries

We develop a statistical framework for the dynamical closure of spatiotemporal dynamics governed by partial differential equations. Employing the mathematical framework of quantum mechanics to embed the original classical dynamics into a quantum mechanical representation, we use the space of quantum density operators to model the unresolved degrees of freedom of the original dynamics in a statistical sense, and the framework of quantum measurement to predict their contributions to the resolved dynamics. The embedded dynamics is discretized by a positivity preserving process, leading to a compressed representation that is invariant under the dynamical symmetries of the resolved dynamics. We present a data based formulation of the closure scheme and apply it to a closure problem for the shallow water equations. The numerical results demonstrate that our closure model can accurately predict the main features of the true dynamics, including for out of sample initial conditions.

Delay embedding↗

Martian crater dark streak lengths - Explanation from wind tunnel experiments

The mechanism determining the length of dark erosional (type-Id) streaks near craters and hills on the surface of Mars is investigated using Mariner-9 images and the results of wind-tunnel studies (Greeley et al., 1974; Iversen et al., 1975 and 1976). An empirical model of time-dependent growth of crater-wake streaks in the downwind direction involving deflation by sand-grain saltation is developed and shown to give relatively good agreement with streak growth rates observed over a 38-day period of Mariner observations and with the streak-length/crater-diameter and streak-length/crater-height ratios analyzed statistically by Lee (1984). This time-dependent mechanism is thus considered a reasonable alternative (for dark streaks) to the blocking model proposed by Lee for both bright and dark streaks. Preliminary analysis of further wind-tunnel experiments (Iversen et al., 1982) supports the blocking model of bright-streak formation.

Iversen, J. D.↗

A Causal Approach to Model Validation and Calibration

This poster presents a novel method for validation and verification that focuses on identifying causal relationships between data elements, moving beyond traditional statistical and machine learning approaches. These methods employ causal discovery techniques to reveal the underlying mechanisms of data generation. The research utilizes structural causal models and directed acyclic graphs to depict causal relationships. This approach assists in achieving alignment between simulation models and reality.

97 MATHEMATICS AND COMPUTING↗

When do short-range atomistic machine-learning models fall short?

In this work, we explore the role of long-range interactions in atomistic machine-learning models by analyzing the effects on fitting accuracy, isolated cluster properties, and bulk thermodynamic properties. Such models have become increasingly popular in molecular simulations given their ability to learn highly complex and multi-dimensional interactions within a local environment; however, many of them fundamentally lack a description of explicit long-range interactions. In order to provide a well-defined benchmark system with precisely known pairwise interactions, we chose as the reference model a flexible version of the Extended Simple Point Charge (SPC/E) water model. Our analysis shows that while local representations are sufficient for predictions of the condensed liquid phase, the short-range nature of machine-learning models falls short in representing cluster and vapor phase properties. These findings provide an improved understanding of the role of long-range interactions in machine learning models and the regimes where they are necessary.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Search for new physics in high-mass diphoton events from proton-proton collisions at $ \sqrt{\textrm{s}} $ = 13 TeV

Results are presented from a search for new physics in high-mass diphoton events from proton-proton collisions at $ \sqrt{s} $ = 13 TeV. The data set was collected in 2016–2018 with the CMS detector at the LHC and corresponds to an integrated luminosity of 138 fb$^{−1}$. Events with a diphoton invariant mass greater than 500 GeV are considered. Two different techniques are used to predict the standard model backgrounds: parametric fits to the smoothly-falling background and a first-principles calculation of the standard model diphoton spectrum at next-to-next-to-leading order in perturbative quantum chromodynamics calculations. The first technique is sensitive to resonant excesses while the second technique can identify broad differences in the invariant mass shape. The data are used to constrain the production of heavy Higgs bosons, Randall-Sundrum gravitons, the large extra dimensions model of Arkani-Hamed, Dimopoulos, and Dvali (ADD), and the continuum clockwork mechanism. No statistically significant excess is observed. The present results are the strongest limits to date on ADD extra dimensions and RS gravitons with a coupling parameter greater than 0.1.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗