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Results for “Phenomenological Models”

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 1,045 records · Page 58

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NASA NTRS2012

AGN Winds and Blazar Phenomenology

The launch of {\em Fermi} produced a significant number of AGN detections to allow statistical treatment of their properties. One of the first such systematics was the "Blazar Divide" in FSRQs and BL Lacs according to their gamma-ray spectral index and luminosity. Further data accumulation indicated this separation to be less clear than thought before. An MHD wind model which can model successfully the Seyfert X-ray absorber properties provides the vestiges of an account of the observed blazar classification. We propose to employ this model to model in detail the broad band blazar spectra and their statistical properties in terms of the physical parameters of these MHD winds.

Kazanas, Demos↗

DOE OSTI2025

Overestimated natural biological nitrogen fixation translates to an exaggerated CO 2 fertilization effect in Earth system models

CO 2 fertilization of the terrestrial biosphere is limited by nitrogen. Biological nitrogen fixation (BNF) is the dominant natural nitrogen source to the terrestrial biosphere and can alleviate nitrogen limitation but is poorly constrained in Earth system models (ESMs). Here, in this study, we compare terrestrial BNF from an ensemble of ESMs of the 6th Coupled Model Intercomparison Project to a new global synthesis of observations across natural and agricultural biomes. We find that compared to observations, ESMs underestimate agricultural BNF but overestimate natural BNF in the present day by over 50%. Natural BNF is overestimated in the most productive ecosystems that contribute most to the terrestrial carbon sink (forests and grasslands). ESMs with different BNF representations yield a range of BNF responses to CO 2 enrichment. Some ESMs with phenomenological representations of BNF predict a natural BNF increase in response to a doubling of CO 2 that aligns with a meta-analysis of CO 2 enrichment experiments (31% increase) but fail to account for the substantial carbon cost of BNF. In contrast, ESMs with mechanistic representations of BNF account for its carbon cost as well as its regulation by nitrogen limitation but overestimate the BNF response to a doubling of CO 2 (135% increase). Overall, all current BNF representations in ESMs fall short of fully capturing its response to rising atmospheric CO 2 . Finally, we find a positive correlation between modeled present-day natural BNF and the CO 2 fertilization effect across ESMs, suggesting that overestimated natural BNF translates to an exaggerated CO 2 fertilization effect of approximately 11% in ESMs.

Biological nitrogen fixation↗

NASA NTRS1979

Vortex pattern development on the upper surface of a swept wing at high angle of attack

An experimental study, based on a swept wing, was undertaken in the water tunnel and the wind tunnel at low speeds, with a view to improving the understanding of the intervening phenomena and to make easier their modelling. The vortex flow effects on the wing are first illustrated from global effort measurements and static pressure distributions. The domain of existence of this type of flow is deduced as a function of both sweep angle and angle of attack. By a phenomenological study in the water tunnel, an attempt is made to describe the physical pattern of the vortex flow, from its formation near the apex to its breakdown at the trailing edge. Lastly, by means of a clinometric probe, the flow field over the wing is determined.

Mirande, J.↗

DOE OSTI2020

Dynamical model for social distancing in the U.S. during the COVID-19 epidemic

Social distancing has led to a “flattening of the curve” in many states across the U.S. This is part of a novel, massive, global social experiment which has served to mitigate the COVID-19 pandemic in the absence of a vaccine or effective anti-viral drugs. Hence it is important to be able to forecast hospitalizations reasonably accurately. We propose on phenomenological grounds a random walk/generalized diffusion equation which incorporates the effect of social distancing to describe the temporal evolution of the probability of having a given number of hospitalizations. The probability density function is log-normal in the number of hospitalizations, which is useful in describing pandemics where the number of hospitalizations is very high. We used this insight and data to make forecasts for states using Monte Carlo methods. Back testing validates our approach, which yields good results about a week into the future. States are beginning to reopen at the time of submission of this paper and our forecasts indicate possible precursors of increased hospitalizations. However, the trends we forecast for hospitalizations as well as infections thus far show moderate growth. Additionally we studied the reproducibility in New York (Italian strain) and California (Wuhan strain). We find that even if there is a difference in the transmission of the two strains, social distancing has been able to control the progression of COVID 19.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Tensor force role in β decays analyzed within the Gogny-interaction shell model

The half-life of the famous C 14 β decay is anomalously long, with different mechanisms: the tensor force, cross-shell mixing, and three-body forces, proposed to explain the cancellations that lead to a small transition matrix element. In this study, we revisit and analyze the role of the tensor force for the β decay of C 14 as well as of neighboring isotopes. We add a tensor force to the Gogny interaction, and derive an effective Hamiltonian for shell-model calculations. The calculations were carried out in a p – s d model space to investigate cross-shell effects. Furthermore, we decompose the wave functions according to the total orbital angular momentum L in order to analyze the effects of the tensor force and cross-shell mixing. The inclusion of the tensor force significantly improves the shell-model calculations of the β -decay properties of carbon isotopes. In particular, the anomalously slow β decay of C 14 can be explained by the isospin T = 0 part of the tensor force, which changes the components of N 14 with the orbital angular momentum L = 0 , 1 , and results in a dramatic suppression of the Gamow-Teller transition strength. At the same time, the description of other nearby β decays are improved. Decomposition of wave function into L components illuminates how the tensor force modifies nuclear wave functions, in particular suppression of β -decay matrix elements. Cross-shell mixing also has a visible impact on the β -decay strength. Inclusion of the tensor force does not seem to significantly change, however, binding energies of the nuclei within the phenomenological interaction.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Learning PDFs through interpretable latent representations in Mellin space

Representing the parton distribution functions (PDFs) of the proton and other hadrons through flexible, high-fidelity parametrizations has been a long-standing goal of particle physics phenomenology. This is particularly true since the chosen parametrization methodology can play an influential role in the ultimate PDF uncertainties as extracted in QCD global analyses; these, in turn, are often determinative of the reach of experiments at the LHC and other facilities to nonstandard physics, including at large 𝑥, where parametrization effects can be significant. In this study, we explore a series of encoder-decoder machine-learning (ML) models with various neural-network topologies as efficient means of reconstructing PDFs from meaningful information stored in an interpretable latent space. Given recent effort to pioneer synergies between QCD analyses and lattice-gauge calculations, we formulate a latent representation based on the behavior of PDFs in Mellin space, i.e., their integrated moments, and test the ability of various models to decode PDFs from this information faithfully. We introduce a numerical package, PDFdecoder, which implements several encoder-decoder models to reconstruct PDFs with high fidelity and use this end-to-end tool to explore how such neural-network-based models might connect PDF parametrizations to underlying properties like their Mellin moments. We additionally dissect patterns of learned correlations between encoded Mellin moments and reconstructed PDFs that suggest opportunities for further improvements to ML-based approaches to PDF parametrizations and uncertainty quantification.

Machine learning↗

DOE OSTI2021

$t\bar{t}b\bar{b}$ at the LHC: on the size of corrections and b -jet definitions

We report on the calculation of the next-to-leading order QCD corrections to the production of a $t\bar t$ pair in association with two heavy-flavour jets. We concentrate on the di-lepton $t\bar t$ decay channel at the LHC with $\sqrt{s}$ = 13 TeV. The computation is based on pp → $e^+ν_eμ^-\bar{ν}_μb\bar{b}b\bar{b}$ matrix elements and includes all resonant and non-resonant diagrams, interferences and off-shell effects of the top quark and the W gauge boson. As it is customary for such studies, results are presented in the form of inclusive and differential fiducial cross sections. We extensively investigate the dependence of our results upon variation of renormalisation and factorisation scales and parton distribution functions in the quest for an accurate estimate of the theoretical uncertainties. We additionally study the impact of the contributions induced by the bottom-quark parton density. Results presented here are particularly relevant for measurements of $t\bar{t}H(H → b\bar{b})$ and the determination of the Higgs coupling to the top quark. In addition, they might be used for precise measurements of the top-quark fiducial cross sections and to investigate top-quark decay modelling at the LHC.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Constraints on early dark energy from the axion weak gravity conjecture

A popular proposal for resolving the Hubble tension involves an early phase of dark energy, driven by an axion field with a periodic potential. Here, in this paper, we argue that these models are tightly constrained by the axion weak gravity conjecture: for typical parameter values, the axion decay constant must satisfy f < 0.008,M Pl , which is smaller than the axion decay constants appearing in the vast majority of early dark energy models to date. We discuss possible ways to evade or loosen this constraint, arguing that its loopholes are small and difficult to thread. This suggests that it may prove challenging to realize early dark energy models in a UV complete theory of quantum gravity.

string theory and cosmology↗

DOE OSTI2023

Field-theoretic analysis of hadronization using soft drop jet mass

One of the greatest challenges in quantum chromodynamics is understanding the hadronization mechanism, which is also crucial for carrying out precision physics with jet substructure. In this paper, we bring together recent advancements in our understanding of nonperturbative structure of the soft drop jet mass based on field theory, with precise perturbative calculations at next-to-next-to-leading logarithmic accuracy of its multidifferential variants. This allows for a model-independent analysis of power corrections associated with hadronization in a systematic manner. We test and calibrate hadronization models and their interplay with parton showers by comparing our universality predictions with various event generators for quark and gluon initiated jets in both lepton-lepton and hadron-hadron collisions. Our findings reveal that hadronization models perform better for quark jets relative to gluon jets. Our results provide a valuable toolbox for precision studies with the soft drop jet mass and pave the way for future analyses using real-world collider data. The stringent constraints derived in our framework are useful for improving the modeling of hadronization and its interplay with parton showers in next-generation event generators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1994

Implosive accretion and outbursts of active galactic nuclei

A model and simulation code have been developed for time-dependent axisymmetric disk accretion onto a compact object including for the first time the influence of an ordered magnetic field. The accretion rate and radiative luminosity of the disk are naturally coupled to the rate of outflow of energy and angular momentum in magnetically driven (+/- z) winds. The magnetic field of the wind is treated in a phenomenological way suggested by self-consistent wind solutions. The radial accretion speed u(r, t) of the disk matter is shown to be the sum of the usual viscous contribution and a magnetic contribution proportional to r(exp 3/2)(B(sub p exp 2))/sigma, where B(sub p)(r,t) is the poloidal field threading the disk and sigma(r,t) is the disk's surface mass density. An enhancement or variation in B(sub p) at a large radial distance leads to the formation of a soliton-like structure in the disk density, temperature, and B-field which propagates implosively inward. The implosion gives a burst in the power output in winds or jets and a simultaneous burst in the disk radiation. The model is pertinent to the formation of discrete fast-moving components in jets observed by very long baseline interferometry. These components appear to originate at times of optical outbursts of the active galactic nucleus.

Lovelace, R. V. E.↗

DOE OSTI2023

Aspects of the Domain-Wall Standard Model

Abstract In the “Domain-Wall Standard Model,” all the Standard Model (SM) fields are localized in certain domains in a non-compact 5D space-time. While the SM is realized as a 4D effective theory at low energies, the model involves Kaluza–Klein (KK) modes of the SM particles. In this paper we introduce two simple solvable examples which lead to domain-wall configurations for the SM particles and their KK-modes. Based on the examples, we address a variety of phenomenologies of the Domain-Wall SM, such as the KK-mode gauge boson phenomenology at the Large Hadron Collider (LHC), the effect of the KK-mode SM fermions on Higgs boson phenomenology, and the KK-mode fermion search at the LHC with its decay into a corresponding SM fermion and a Nambu–Goldstone boson associated with a spontaneous breaking of the translational invariance in the 5th dimension. We also propose a simple unified picture of localizing all the SM fields.

Physics↗

NASA NTRS1978

Vertical extent of zonal winds on Venus

A phenomenological study of the Venus winds and atmosphere structure suggests that the region of fast retrograde winds is confined between about 45 and 60 km altitude on the night side and is somewhat broader on the day side. Other aspects of the discussed kinematical model are negligible surface winds, speeds increasing with altitude to approximately 45 km, a wind shear between 60 and 65 km, and slow atmospheric motions above this altitude. Large scale Kelvin-Helmholtz waves associated with the shear at the upper boundary of the highspeed layer may be visible as ultraviolet cloud features, and the possibility of differential heating between light and dark UV features being the cause of the winds is considered.

Crisp, D.↗

NASA NTRS1986

A unified approach to computer analysis and modeling of spacecraft environmental interactions

A new, coordinated, unified approach to the development of spacecraft plasma interaction models is proposed. The objective is to eliminate the unnecessary duplicative work in order to allow researchers to concentrate on the scientific aspects. By streamlining the developmental process, the interchange between theories and experimentalists is enhanced, and the transfer of technology to the spacecraft engineering community is faster. This approach is called the UNIfied Spacecraft Interaction Model (UNISIM). UNISIM is a coordinated system of software, hardware, and specifications. It is a tool for modeling and analyzing spacecraft interactions. It will be used to design experiments, to interpret results of experiments, and to aid in future spacecraft design. It breaks a Spacecraft Ineraction analysis into several modules. Each module will perform an analysis for some physical process, using phenomenology and algorithms which are well documented and have been subject to review. This system and its characteristics are discussed.

Katz, I.↗

DOE OSTI2022

$\mathrm{D}$ark$\mathrm{F}$lux: A new tool to analyze indirect-detection spectra of next-generation dark matter models

Here we present DarkFlux, a software tool designed to analyze indirect-detection signatures for next-generation models of dark matter (DM) with multiple annihilation channels. Version 1.0 of this tool accepts user-generated models with 2→2 tree-level dark matter annihilation to pairs of Standard Model (SM) particles and analyzes DM annihilation to γ rays. The tool consists of three modules, which can be run in a loop in order to scan over DM mass if desired: The annihilation fraction module calls an internal installation of MadDM, a dark matter phenomenology plugin for the Monte Carlo event generator MadGraph5 _ aMC@NLO, to compute the thermally averaged cross section $\langle σv\rangle_i$ for each annihilation channel $χχ$ ($\bar{χ}$,$χ^†$)→ i $\∈{SM, SM}. . The module then computes the fractional annihilation rate (annihilation fraction) into each channel. The flux module combines the flux spectrum from each annihilation channel, weighted by the appropriate annihilation fractions, to compute the total flux at Earth due to DM annihilation. In DarkFlux v1.0, this module specifically computes the γ-ray flux for each channel using the publicly available PPPC4DMID tables. The analysis module compares the total flux to observational data and computes the upper limit at 95% confidence level (CL) on the total thermally averaged DM annihilation cross section. In DarkFlux v1.0, this module compares the total γ-ray flux to a joint-likelihood analysis of fifteen dwarf spheroidal galaxies (dSphs) analyzed by the Fermi-LAT collaboration. DarkFlux v1.0 automatically provides data tables and can plot the output of these three modules. In this manual, we briefly motivate this indirect-detection computer tool and review the essential DM physics. We then describe the several modules of DarkFlux in greater detail. Finally, we show how to install and run DarkFlux and provide two worked examples demonstrating its capabilities.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

MISPR : an open-source package for high-throughput multiscale molecular simulations

Computational tools provide a unique opportunity to study and design optimal materials by enhancing our ability to comprehend the connections between their atomistic structure and functional properties. However, designing materials with tailored functionalities is complicated due to the necessity to integrate various computational-chemistry software (not necessarily compatible with one another), the heterogeneous nature of the generated data, and the need to explore vast chemical and parameter spaces. The latter is especially important to avoid bias in scattered data points-based models and derive statistical trends only accessible by systematic datasets. Here, we introduce a robust high-throughput multi-scale computational infrastructure coined MISPR (Materials Informatics for Structure–Property Relationships) that seamlessly integrates classical molecular dynamics (MD) simulations with density functional theory (DFT). By enabling high-performance data analytics and coupling between different methods and scales, MISPR addresses critical challenges arising from the needs of automated workflow management and data provenance recording. The major features of MISPR include automated DFT and MD simulations, error handling, derivation of molecular and ensemble properties, and creation of output databases that organize results from individual calculations to enable reproducibility and transparency. In this work, we describe fully automated DFT workflows implemented in MISPR to compute various properties such as nuclear magnetic resonance chemical shift, binding energy, bond dissociation energy, and redox potential with support for multiple methods such as electron transfer and proton-coupled electron transfer reactions. The infrastructure also enables the characterization of large-scale ensemble properties by providing MD workflows that calculate a wide range of structural and dynamical properties in liquid solutions. MISPR employs the methodologies of materials informatics to facilitate understanding and prediction of phenomenological structure–property relationships, which are crucial to designing novel optimal materials for numerous scientific applications and engineering technologies.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Spin-dependent interactions and heavy-quark transport in the quark-gluon plasma

We extend a previously constructed T-matrix approach to the quark-gluon plasma (QGP) to include the effects of spin-dependent interactions between partons. Following earlier work within the relativistic quark model, the spin-dependent interactions figure as relativistic corrections to the Cornell potential. When applied to the vacuum spectroscopy of quarkonia, in particular their mass splittings in S- and P-wave states, the issue of the Lorentz structure of the confining potential arises. We confirm that a significant admixture of a vector interaction (to the previously assumed scalar interaction) improves the description of the experimental mass splittings. The temperature corrections to the in-medium potential are constrained by results from thermal lattice-QCD for the equation of state (EoS) and heavy-quark (HQ) free energy in a self-consistent set-up for heavy- and light-parton spectral functions in the QGP. We then deploy the refined in-medium heavy-light T-matrix to compute the charm-quark transport coefficients in the QGP. The vector component of the confining potential, through its relativistic corrections, enhances the friction coefficient for charm quarks in the QGP over previous calculations by tens of percent at low momenta and temperatures, and more at higher momenta. Our results are promising for improving the current phenomenology of open heavy-flavor observables at Relativistic Heavy Ion Collider (RHIC) and the Large Hadron Collider (LHC).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

An analysis of Bayesian estimates for missing higher orders in perturbative calculations

With current high precision collider data, the reliable estimation of theoretical uncertainties due to missing higher orders (MHOs) in perturbation theory has become a pressing issue for collider phenomenology. Traditionally, the size of the MHOs is estimated through scale variation, a simple but ad hoc method without probabilistic interpretation. Bayesian approaches provide a compelling alternative to estimate the size of the MHOs, but it is not clear how to interpret the perturbative scales, like the factorisation and renormalisation scales, in a Bayesian framework. Recently, it was proposed that the scales can be incorporated as hidden parameters into a Bayesian model. In this paper, we thoroughly scrutinise Bayesian approaches to MHO estimation and systematically study the performance of different models on an extensive set of high-order calculations. We extend the framework in two significant ways. First, we define a new model that allows for asymmetric probability distributions. Second, we introduce a prescription to incorporate information on perturbative scales without interpreting them as hidden model parameters. We clarify how the two scale prescriptions bias the result towards specific scale choice, and we discuss and compare different Bayesian MHO estimates among themselves and to the traditional scale variation approach. Finally, we provide a practical prescription of how existing perturbative results at the standard scale variation points can be converted to 68%/95% credibility intervals in the Bayesian approach using the new public code MiHO.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Kinetics-Informed Neural Networks

Chemical kinetics and reaction engineering consists of the phenomenological framework for the disentanglement of reaction mechanisms, optimization of reaction performance and the rational design of chemical processes. Here, we utilize feed-forward artificial neural networks as basis functions to solve ordinary differential equations (ODEs) constrained by differential algebraic equations (DAEs) that describe microkinetic models (MKMs). We present an algebraic framework for the mathematical description and classification of reaction networks, types of elementary reaction, and chemical species. Under this framework, we demonstrate that the simultaneous training of neural nets and kinetic model parameters in a regularized multi-objective optimization setting leads to the solution of the inverse problem through the estimation of kinetic parameters from synthetic experimental data. We analyze a set of scenarios to establish the extent to which kinetic parameters can be retrieved from transient kinetic data, and assess the robustness of the methodology with respect to statistical noise. Furthermore, this approach to inverse kinetic ODEs can assist in the elucidation of reaction mechanisms based on transient data.

36 MATERIALS SCIENCE↗