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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 829 records · Page 46

Statistical Analysis of Hubble /WFC3 Transit Spectroscopy of Extrasolar Planets

Transmission spectroscopy provides a window to study exoplanetary atmospheres, but that window is fogged by clouds and hazes. Clouds and haze introduce a degeneracy between the strength of gaseous absorption features and planetary physical parameters such as abundances. One way to break that degeneracy is via statistical studies. We collect all published HST /WFC3 transit spectra for 1.1–1.65 μ m water vapor absorption and perform a statistical study on potential correlations between the water absorption feature and planetary parameters. We fit the observed spectra with a template calculated for each planet using the Exo-transmit code. We express the magnitude of the water absorption in scale heights, thereby removing the known dependence on temperature, surface gravity, and mean molecular weight. We find that the absorption in scale heights has a positive baseline correlation with planetary equilibrium temperature; our hypothesis is that decreasing cloud condensation with increasing temperature is responsible for this baseline slope. However, the observed sample is also intrinsically degenerate in the sense that equilibrium temperature correlates with planetary mass. We compile the distribution of absorption in scale heights, and we find that this distribution is closer to log-normal than Gaussian. However, we also find that the distribution of equilibrium temperatures for the observed planets is similarly log-normal. This indicates that the absorption values are affected by observational bias, whereby observers have not yet targeted a sufficient sample of the hottest planets.

79 ASTRONOMY AND ASTROPHYSICS↗

Review of Particle Physics

The Review summarizes much of particle physics and cosmology. Using data from previous editions, plus 2,873 new measurements from 758 papers, we list, evaluate, and average measured properties of gauge bosons and the recently discovered Higgs boson, leptons, quarks, mesons, and baryons. We summarize searches for hypothetical particles such as supersymmetric particles, heavy bosons, axions, dark photons, etc. Particle properties and search limits are listed in Summary Tables. We give numerous tables, figures, formulae, and reviews of topics such as Higgs Boson Physics, Supersymmetry, Grand Unified Theories, Neutrino Mixing, Dark Energy, Dark Matter, Cosmology, Particle Detectors, Colliders, Probability and Statistics. Here, among the 118 reviews are many that are new or heavily revised, including a new review on Neutrinos in Cosmology.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Implications of first neutrino-induced nuclear recoil measurements in direct detection experiments: Probing nonstandard interaction via CE ν NS

PandaX-4T and XENONnT have recently reported the first measurement of nuclear recoils induced by the B 8 solar neutrino flux, through the coherent elastic neutrino-nucleus scattering ( CE ν NS ) channel. As long anticipated, this is an important milestone for dark matter searches as well as for neutrino physics. This measurement means that these detectors have reached exposures such that searches for low mass, ≲ 10 GeV dark matter cannot be analyzed using the background-free paradigm going forward. It also opens a new era for these detectors to be used as neutrino observatories. In this paper we assess the sensitivity of these new measurements to new physics in the neutrino sector. We focus on neutrino nonstandard interactions (NSI) and show that—despite the still moderately low statistical significance of the signals—these data already provide valuable information. We find that limits on NSI from PandaX-4T and XENONnT measurements are comparable to those derived using combined COHERENT CsI and LAr data. Furthermore, they provide sensitivity to pure τ flavor parameters that are not accessible using stopped-pion or reactor sources. With larger exposures and consequently improvements of statistical uncertainties, forthcoming data from these experiments will provide important, novel results for CE ν NS -related physics. Published by the American Physical Society 2025

Sierra, D. Aristizabal↗

Challenging Practices of Algebraic Battery Life Models through Statistical Validation and Model Identification via Machine-Learning

Various modeling techniques are used to predict the capacity fade of Li-ion batteries. Algebraic reduced-order models, which are inherently interpretable and computationally fast, are ideal for use in battery controllers, technoeconomic models, and multi-objective optimizations. For Li-ion batteries with graphite anodes, solid-electrolyte-interphase (SEI) growth on the graphite surface dominates fade. This fade is often modeled using physically informed equations, such as square-root of time for predicting solvent-diffusion limited SEI growth, and Arrhenius and Tafel-like equations predicting the temperature and state-of-charge rate dependencies. In some cases, completely empirical relationships are proposed. However, statistical validation is rarely conducted to evaluate model optimality, and only a handful of possible models are usually investigated. This article demonstrates a novel procedure for automatically identifying reduced-order degradation models from millions of algorithmically generated equations via bi-level optimization and symbolic regression. Identified models are statistically validated using cross-validation, sensitivity analysis, and uncertainty quantification via bootstrapping. On a LiFePO 4 /Graphite cell calendar aging data set, automatically identified models utilizing square-root, power law, stretched exponential, and sigmoidal functions result in greater accuracy and lower uncertainty than models identified by human experts, and demonstrate that previously known physical relationships can be empirically "rediscovered" using machine learning.

25 ENERGY STORAGE↗

An Applied Strategy for Using Empirical and Hybrid Models in Online Monitoring

The monitoring of plant equipment for failure prediction is one of the key contributors to operation and maintenance (O&M) costs for a nuclear power plant (NPP) because O&M monitoring depends on labor-intensive activities that are required to meet high equipment reliability standards. These activities rely primarily on humans for information gathering, condition diagnosis, and predictive analysis. Online monitoring aims to automate these activities by relying on sensors to replace human information gathering and machine learning to replace human analysis and decision making. To facilitate automated monitoring, a systematic strategy for anomaly detection is needed to optimally use the available sensor data, empirical models, and physics-supported models. This strategy is essential to provide credible reasoning on why and when an empirical (i.e., purely data-driven) versus hybrid (i.e., physics-supported) approach should be used and to determine the ideal mix of these two approaches for a defined anomaly detection scope. The extant methods usually adopt an ad hoc trial-and-error approach that, in addition to being time-consuming and costly, is also highly subjective; it is impacted by the background and the skill set of the personnel making the decisions. Thus, such an approach cannot guarantee an optimum outcome. This represents the motivation of the current research effort, which is focused on devising a scientifically supported strategy for the optimum selection of anomaly detection methods. This report presents a detailed assessment of the main anomaly detection techniques within the empirical or hybrid method streams. Empirical methods include pattern, statistical, and causal inference. Hybrid methods include the use of physics models to train and test data methods, reduce data dimensionality, reduce data-model complexity, augment data, and reduce empirical uncertainty; hybrid methods also include the use of data to tune physics models. The listed techniques within these two streams represent the vast majority of techniques performed for anomaly detection. Using the techniques as outcomes, a strategy was developed to enable a systematic decision-making process to lead to one of these techniques. The strategy is driven by key decision points related to data relevance, simple modeling feasibility, data inference, physics-modeling value, data dimensionality, physics knowledge, method of validation, performance, data availability and suitability for training and testing, cause-effect, entropy inference, and model fitting. Each of these decision points in the strategy is explained in detail in this report with examples, along with the scientific basis behind the decisions and outcomes in common and simplified terminology. The strategy is developed for use by any NPP staff with basic engineering or science knowledge. A user-friendly graphical state flow diagram was also developed as a visual presentation of the strategy. The strategy was tested and demonstrated through two pilot projects for the application of anomaly detection at an NPP. Each pilot had two use cases: an initial case in which certain decisions were made that resulted in one or more empirical techniques and a revised use case where one or more key decisions were modified resulting in using a set of hybrid methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A global significance evaluation method using simulated events

In High-Energy Physics experiments it is often necessary to evaluate the global statistical significance of apparent resonances observed in invariant mass spectra. One approach to determining significance is to use simulated events to find the probability of a random fluctuation in the background mimicking a real signal. As a high school summer project, we demonstrate a method with Monte Carlo simulated events to evaluate the global significance of a potential resonance with some assumptions. This method for determining significance is general and can be applied, with appropriate modification, to other resonances.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Ten years of CR physics with PAMELA

The satellite borne Pamela instrument is dedicated to the precise and high statistics study of CR fluxes on a four decades energy range. Pamela experiment is the last step of the “Russian-Italian Mission” (RIM) program established in 1992 between several Italian and Russian institutes and with the participation of Sweden and Germany. Designed as a cosmic ray observatory at 1 AU, it extensive program is made possible thanks to the outstanding performance of the instrument, the low energy threshold, the quasi-polar orbit and the 10 years duration of the observation. The physics program pays particular attention to the study of particles and antiparticles fluxes and includes search for dark matter, primordial antimatter, new matter in the Universe, study of cosmic-ray propagation, solar physics and solar modulation, and terrestrial magnetosphere. Very important is the discovery of the anomalous increase of the positron flux at energies higher that 50 GeV (the so called “Pamela anomaly”), and the abrupt spectral hardening of H and He, challenging the current paradigm of cosmic-ray acceleration and propagation in the Galaxy.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Revisiting ENSO and IOD Contributions to Australian Precipitation

Tropical modes of variability, such as El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD), exert a strong influence on the interannual variability of Australian precipitation. Nevertheless, commonly used indices of ENSO and IOD variability display significant co-variability that prevents a robust quantification of the independent contribution of each mode to precipitation anomalies. This co-variability issue is often addressed by statistically removing ENSO or IOD variability from the precipitation field before calculating teleconnection patterns. However, by performing a suite of coupled and uncoupled modeling experiments in which either ENSO or IOD variability is physically removed, we show that ENSO-only-driven precipitation patterns computed by statistically removing the IOD influence significantly underestimate the impact of ENSO on Australian precipitation variability. Here, inspired by this, we propose a conceptual model that allows one to effectively separate the contribution of each mode to Australian precipitation variability.

54 ENVIRONMENTAL SCIENCES↗

Parametrizing the detector response with neural networks

In high energy physics, characterizing the response of a detector to radiation is one of the most important and fundamental experimental tasks. In many cases, this task is accomplished by parameterizing summary statistics of the full detector response probability density. The parameterized detector response can then be used for calibration as well as for directly improving physics analysis sensitivity. This paper reports on how to parameterize summary statistics of the detector response using neural networks. Specifically, neural networks are powerful tools for incorporating multidimensional data and the loss function used during training determines which summary statistic is learned. One common summary statistic that has not been combined with deep learning (as far as the authors are aware) is the mode. A neural network-based approach to mode learning is proposed and empirically demonstrated in the context of high energy jet calibrations. Altogether, the neural network-based toolkit for detector response parameterization can enhance the utility of data collected at high energy physics experiments and beyond.

47 OTHER INSTRUMENTATION↗

Augmentation of blood circulation to the fingers by warming distant body areas

Future activities in space will require greater periods of time in extreme environments in which the body periphery will be vulnerable to chilling. Maintaining the hands and fingers in comfortable conditions enhances finger flexibility and dexterity, and thus effects better work performance. We have evaluated the efficacy of promoting heat transfer and release by the extremities by increasing the blood flow to the periphery from more distant parts of the body. The experimental garment paradigm developed by the investigators was used to manipulate the temperature of different body areas. Six subjects, two females and four males, were evaluated in a stage-1 baseline condition, with the inlet temperature of the circulating water in the liquid cooling/warming garment (LCWG) at 33 degrees C. At stage 2 the total LCWG water inlet temperature was cooled to 8 degrees C, and at stage 3 the inlet water temperature in specific segments of the LCWG was warmed (according to protocol) to 45 degrees C, while the inlet temperature in the rest of the LCWG was maintained at 8 degrees C. The following four body-area-warming conditions were studied in separate sessions: (1) head, (2) upper torso/arm, (3) upper torso/arm/head, and (4) legs/feet. Skin temperature, heat flux and blood perfusion of the fingers, and subjective perception of thermal sensations and overall physical comfort were assessed. Finger temperature (T(fing)) analyses showed a statistically significant condition x stage interaction. Post-hoc comparisons (T(fing)) indicated that at stage 3, the upper torso/arm/head warming condition was significantly different from the head, upper torso/arm and legs/feet conditions, showing an increase in T(fing). There was a significant increase in blood perfusion in the fingers at stage 3 in all conditions. Subjective perception of hand warmth, and overall physical comfort level significantly increased in the stage 3 upper torso/arm/head condition. The findings indicate that physiological methods to enhance heat transfer by the blood to the periphery within protective clothing provide an additional tool for increasing total and local human comfort in extreme environments.

NASA Discipline Life Sciences Technologies↗

Proton production in relativistic heavy ion collisions; comparison with a thermodynamical model

Experimental results concerning proton production in nuclear collisions, obtained at Saturne with the Diogene 4 pi facility, are compared with the predictions of a thermodynamical model, using collective velocity distributions combined with a statistical thermodynamics in local rest frames. Experimental differential cross sections for alpha + nucleus and Neon + nucleus central collisions at incident energies between 200 and 800 MeV per nucleon are well reproduced by the model, for an angular range 30-110 degrees in the laboratory system. Extracted values of the temperatures are compared with those given by other authors.

NASA Program Biomedical Research↗

Exploring the Use of Radar for Physically-Based Nowcasting of Lightning Cessation

NASA's Marshall Space Flight Center and the University of Alabama in Huntsville (UAHuntsville) are collaborating with the 45th Weather Squadron (45WS) at Cape Canaveral Air Force Station (CCAFS) to enable improved nowcasting of lightning cessation. This project centers on use of dual-polarimetric radar capabilities, and in particular, the new C-band dual polarimetric weather radar acquired by the 45WS. Special emphasis is placed on the development of a physically-based operational algorithm to predict lightning cessation. While previous studies have developed statistically based lightning cessation algorithms driven primarily by trending in the actual total lightning flash rate, we believe that dual polarimetric radar variables offer the possibility to improve existing algorithms through the inclusion of physically meaningful trends reflecting interactions between in-cloud electric fields and ice-microphysics. Specifically, decades of polarimetric radar research using propagation differential phase has demonstrated the presence of distinct phase and ice crystal alignment signatures in the presence of strong electric fields associated with lightning. One question yet to be addressed is: To what extent can propagation phase-based ice-crystal alignment signatures be used to nowcast the cessation of lightning activity in a given storm? Accordingly, data from the UAHuntsville Advanced Radar for Meteorological and Operational Research (ARMOR) along with the NASA-MSFC North Alabama Lightning Mapping Array are used in this study to investigate the radar signatures present before and after lightning cessation. Thus far our case study results suggest that the negative differential phase shift signature weakens and disappears after the analyzed storms ceased lightning production (i.e., after the last lightning flash occurred). This is a key observation because it suggests that while strong electric fields may still have been present, the lightning cessation signature was encompassed in the period of the polarimetric negative phase shift signature. To the extent this behavior is repeatable in other cases, even if only in a substantial fraction of those cases, the analysis suggests that differential propagation phase may prove to be a useful parameter for future lightning cessation algorithms. Indeed, a preliminary analysis of 15+ cases has shown additional indications of the weakening and disappearance of this ice alignment signature with lightning cessation. A summary of these case-study results is presented.

Schultz, Elise V.↗

Separation of conditions as a prerequisite for quantum theory

We introduce the notion of “separation of conditions” meaning that a description of statistical data obtained from experiments, performed under a set of different conditions, allows for a decomposition such that each partial description depends on mutually exclusive subsets of these conditions. Descriptions that allow a separation of conditions are shown to entail the basic mathematical framework of quantum theory. The Stern–Gerlach and the Einstein–Podolsky–Rosen–Bohm experiment with three, respectively nine possible outcomes are used to illustrate how the separation of conditions can be used to construct their quantum theoretical descriptions. It is shown that the mathematical structure of separated descriptions implies that, under certain restrictions, the time evolution of the data can be described by the von Neumann/Schrödinger equation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Nonequilibrium statistical thermodynamics of multicomponent interfaces

Nonequilibrium interfacial thermodynamics has important implications for crucial biological, physical, and industrial-scale transport processes. Here, we discuss a theory of local equilibrium for multiphase multicomponent interfaces that builds upon the “sharp” interface concept first introduced by Gibbs, allowing for a description of nonequilibrium interfacial processes such as those arising in evaporation, condensation, adsorption, etc. By requiring that the thermodynamics be insensitive to the precise location of the dividing surface, one can identify conditions for local equilibrium and develop methods for measuring the values of intensive variables at the interface. We then use extensive, high-precision nonequilibrium molecular dynamics (NEMD) simulations to verify the theory and establish the validity of the local equilibrium hypothesis. In particular, we demonstrate that equilibrium equations of state are also valid out of equilibrium, and can be used to determine interfacial temperature and chemical potential(s) that are consistent with nonequilibrium generalizations of the Clapeyron and Gibbs adsorption equations. We also show, for example, that, far from equilibrium, temperature or chemical potential differences need not be uniform across an interface and may instead exhibit pronounced discontinuities. However, even in these circumstances, we demonstrate that the local equilibrium hypothesis and its implications remain valid. These results provide a thermodynamic foundation and computational tools for studying or revisiting a wide variety of interfacial transport phenomena.

36 MATERIALS SCIENCE↗

The CosmoVerse White Paper: Addressing observational tensions in cosmology with systematics and fundamental physics.

The standard model of cosmology has provided a good phenomenological description of a wide range of observations both at astrophysical and cosmological scales for several decades. This concordance model is constructed by a universal cosmological constant and supported by a matter sector described by the standard model of particle physics and a cold dark matter contribution, as well as very early-time inflationary physics, and underpinned by gravitation through general relativity. There have always been open questions about the soundness of the foundations of the standard model. However, recent years have shown that there may also be questions from the observational sector with the emergence of differences between certain cosmological probes. In this White Paper, we identify the key objectives that need to be addressed over the coming decade together with the core science projects that aim to meet these challenges. These discordances primarily rest on the divergence in the measurement of core cosmological parameters with varying levels of statistical confidence. These possible statistical tensions may be partially accounted for by systematics in various measurements or cosmological probes but there is also a growing indication of potential new physics beyond the standard model. After reviewing the principal probes used in the measurement of cosmological parameters, as well as potential systematics, we discuss the most promising array of potential new physics that may be observable in upcoming surveys. We also discuss the growing set of novel data analysis approaches that go beyond traditional methods to test physical models. These new methods will become increasingly important in the coming years as the volume of survey data continues to increase, and as the degeneracy between predictions of different physical models grows. There are several perspectives on the divergences between the values of cosmological parameters, such as the model-independent probes in the late Universe and model-dependent measurements in the early Universe, which we cover at length. The White Paper closes with a number of recommendations for the community to focus on for the upcoming decade of observational cosmology, statistical data analysis, and fundamental physics developments.

Dienes, Keith [Univ. of Arizona, Tucson, AZ (Unite↗

A Framework for Imperfectly Observed Networks

Model a network as an edge-weighted graph, where the (unknown) weight w{sub e} of edge e indicates the frequency of observed interactions, and over time t we observe a Poisson (tw{sub e}) number of interactions across edges e. How should we estimate some given statistic of the underlying network? This leads to wide-ranging and challenging problems, on which this article makes only partial progress.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗