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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Dark QCD: the Next Frontier in Dark Matter

There has been a surge of interest in hidden valley models with new, strong forces, sometimes called "dark QCD". These models propose asymmetric, composite dark matter in the form of "dark hadrons" that would evade direct and indirect bounds as well as typical collider DM searches for large missing transverse momentum accompanied by radiation. However, evidence of these models can still be found in collider datasets by targeting their unique phenomenological signatures, which include semivisible jets, emerging jets, and soft unclustered energy patterns. We will present the latest experimental results for these signatures and discuss the significant strides in exploring the vast space of dark QCD models. We will further discuss the prospects for dramatic expansions in sensitivity via machine learning.

Pedro, Kevin [Fermilab]↗
NASA NTRS1988

Wave particle interactions in the foot of the Saturnian bow shock

Voyager 1 plasma wave data show that the quasi-perpendicular, supercritical bow shock of Saturn exhibits the same plasma wave phenomenology observed near Jupiter. Using a quasi-linear model developed for the Jovian bow shock, it is shown that plasma waves at Saturn can generate a significant portion of the totalelectron temperature jump measured across the shock. In this respect, Saturn's bow shock more closely resembles Jupiter's than the earth's, where plasma waves contribute negligibly to the total electron temperature jump.

Moses, S. L.↗
NASA NTRS1992

Research activity at the shock tube facility at NASA Ames

The real gas phenomena dominate the relaxation process occurring in the flow around hypersonic vehicles. The air flow around these vehicles undergoes vibrational excitation, chemical dissociation, and ionization. These chemical and kinetic phenomena absorb energy, change compressibility, cause temperature to fall, and density to rise. In high-altitude, low density environments, the characteristic thicknesses of the shock layers can be smaller than the relaxation distances required for the gas to attain chemical and thermodynamic equilibrium. To determine the effects of chemical nonequilibrium over a realistic hypersonic vehicle, it would be desirable to conduct an experiment in which all aspects of fluid flow are simulated. Such an experiment is extremely difficult to setup. The only practical alternative is to develop a theoretical model of the phenomena and to compute the flow around the vehicle including the chemical nonequilibrium, and compare the results with the experiments conducted in the facilities under conditions where only a portion of the flow phenomena is simulated. Three types of experimental data are needed to assist the aerospace community in this model development process: (1) data which will enhance our phenomenological understanding of the relaxation process, (2) data on rate reactions for the relevant reactions, and (3) data on bulk properties, such as spectral radiation emitted by the gas, for a given set of aerodynamic conditions. NASA Ames is in a process of collecting such data by simulating the required aerothermochemical conditions in an electric arc driven shock tube.

Sharma, Surendra P.↗
NASA NTRS2006

Quantity Distance for the Kennedy Space Center Vehicle Assembly Building for Solid Propellant Fueled Launchers

The NASA KSC VAB was built to process Apollo launchers in the 1960's, and later adapted to process Space Shuttles. The VAB has served as a place to assemble solid rocket motors (5RM) and mate them to the vehicle's external fuel tank and Orbiter before rollout to the launch pad. As Space Shuttle is phased out, and new launchers are developed, the VAB may again be adapted to process these new launchers. Current launch vehicle designs call for continued and perhaps increased use of SRM segments; hence, the safe separation distances are in the process of being re-calculated. Cognizant NASA personnel and the solid rocket contractor have revisited the above VAB QD considerations and suggest that it may be revised to allow a greater number of motor segments within the VAB. This revision assumes that an inadvertent ignition of one SRM stack in its High Bay need not cause immediate and complete involvement of boosters that are part of a vehicle in adjacent High Bay. To support this assumption, NASA and contractor personnel proposed a strawman test approach for obtaining subscale data that may be used to develop phenomenological insight and to develop confidence in an analysis model for later use on full-scale situations. A team of subject matter experts in safety and siting of propellants and explosives were assembled to review the subscale test approach and provide options to NASA. Upon deliberations regarding the various options, the team arrived at some preliminary recommendations for NASA.

Stover, Steven↗
NASA NTRS2021

The X-Ray Pulsar XTE J1858+034 Observed with NuSTAR and Fermi/GBM: Spectral and Timing Characterization plus a Cyclotron Line

Accreting X-ray pulsars (XRPs) undergo luminous X-ray outbursts during which the spectral and timing behavior of the neutron star can be studied in detail. We analyze a NuSTAR observation of the XRP XTE J1858+034 during its outburst in 2019. The spectrum is fit with a phenomenological, a semi-empirical and a physical spectral model. A candidate cyclotron line is found at 48 keV, implying a magnetic field of 5.4×1012G at the site of emission. This is also supported by the physical best-fit model. A nominal Gaia distance of 1.55 kpc is available for a star that is close to – although not coincident with – the previously proposed optical counterpart but, based on Fermi Gamma-ray Burst Monitor data, the standard disk accretion-torque theory allowed us to infer a distance of 10.9±1.0 kpc. Pulse profiles are single-peaked and show a pulsed fraction that is strongly energy-dependent at least up to 40keV.

C Malacaria↗
DOE OSTI2022

A view on the current and future impact of research reactors

Full text of publication follows. The current fleet of nuclear research reactors worldwide is nearly 70 years old. These reactors have proven to be extremely valuable tools of nuclear science and engineering with a broad and interdisciplinary impact. To date, research reactors are utilized as tools for understanding the physics, operations, and safety of nuclear fission systems. In addition, they are used as intense sources of radiation in support of irradiation testing and nondestructive examination of materials. As this fleet of reactors ages, an urgent need exists to establish new facilities that can propel the benefit of these reactors into the 21. century. In fact, an opportunity exists to build research reactors based on technology concepts that are being considered for nuclear energy reactors. This may include high temperature gas cooled and/or molten salt based advanced and micro reactor concepts. Such future reactors should be designed to maintain the broad utility of current reactors in research and education. However, modern research reactors can be purposefully designed and instrumented to access neutronic and thermal hydraulic information that would support the development and validation of reactor multi-physics modeling and simulation techniques. In this case, the entire phenomenological paradigm of the reactor may be captured to understand the neutronic multiscale and its impact on operations and safety. Moreover, the generated data can be channeled to drive anticipatory examination of the state of the reactor. In general, a symbiotic relation may be envisioned between the modern research reactor and power reactor fleets, which could facilitate the safe and efficient implementation of clean nuclear energy. (author)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Numerical relativity simulations of prompt collapse mergers: Threshold mass and phenomenological constraints on neutron star properties after GW170817

We determine the threshold mass for prompt (no bounce) black hole formation in equal-mass neutron star (NS) mergers using a new set of 227 numerical relativity simulations. We consider 23 phenomenological and microphysical finite-temperature equations of state (EOS), including models with hyperons and first-order phase transitions to deconfined quarks. We confirm the existence of EOS-insensitive relations between the threshold mass, binary tidal parameter at the threshold (Λth), maximum mass of nonrotating NSs, and radii of reference mass NSs. We combine the EOS-insensitive relations, phenomenological constraints on NS properties, and observational data from GW170817 to derive an improved lower limit on radii of maximum mass and a 1.6 M ⊙ NS of 9.81 and 10.90 km, respectively. We also constrain the radius and quadrupolar tidal deformability (Λ) of a 1.4 M ⊙ NS to be larger than 10.74 km and 172, respectively. We consider uncertainties in all independent parameters—fitting coefficients as well as GW170817 masses while reporting the range of radii constraints. We discuss an approach to constrain the upper as well as lower limit of NS maximum mass using future binary NS detections and their identification as prompt or delayed collapse. With future observations, it will be possible to derive even tighter constraints on the properties of matter at and above nuclear density using the method proposed in this work.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

FolpsD: combining EFT and phenomenological approaches for joint power spectrum and bispectrum analyses

We present a theoretical model for the power spectrum and bispectrum of galaxy clustering that exploits the complementarity between small-scale power spectrum information and large-scale bispectrum measurements. We extend the FOLPS code by combining its one-loop EFT galaxy power spectrum with a tree-level galaxy bispectrum projected onto the tripolar spherical harmonics (Sugiyama) basis. To access additional small-scale information, we also consider a line-of-sight damping factor in both statistics, mirroring approaches commonly used in studies of redshift-space distortions. We test the model using DESI DR2 galaxy mocks. Even without damping, the joint analysis of the EFT power spectrum and bispectrum significantly improves constraints and reduces parameter degeneracies relative to power spectrum analyses alone. For LRG-like samples, including the damping further extends the range beyond $k\sim 0.3 \,h \text{Mpc}^{-1}$ in the power spectrum and $k \sim 0.24 \,h \text{Mpc}^{-1}$ in the bispectrum without introducing statistically significant parameter biases. This leads to up to $\sim 30\%$ tighter constraints on $A_s$ and $ω_{cdm}$. For low signal-to-noise tracers such as QSOs, however, the damping parameters are weakly constrained and can absorb noise fluctuations, leading to shifts in inferred parameters. Similar limitations may arise in models where cosmological information is encoded in power-spectrum shape features degenerate with the damping, such as scenarios with massive neutrinos. In contrast, for $w_0w_a$CDM we obtain $15\%$ and $21\%$ tighter constraints on $w_0$ and $w_a$, respectively, yielding a deviation from constant dark energy at slightly more than the $1σ$ level using full-shape information alone. The code is publicly available at https://github.com/cosmodesi/FolpsD

Bansal, P. [Michigan U., MCTP; Michigan U.] (ORCID↗
DOE OSTI2024

Dark QCD: the Next Frontier in Dark Matter

There has been a surge of interest in hidden valley models with new, strong forces, sometimes called "dark QCD". These models propose asymmetric, composite dark matter in the form of "dark hadrons" that would evade direct and indirect bounds as well as typical collider DM searches for large missing transverse momentum accompanied by radiation. However, evidence of these models can still be found in collider datasets by targeting their unique phenomenological signatures, which include semi visible jets, emerging jets, and soft unclustered energy patterns. We will present the first experimental results for all of these signatures, which have made significant strides in exploring the vast space of dark QCD models. We will further discuss the prospects for dramatic improvements in sensitivity using machine learning.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1973

Modelling a particular class of stochastic systems

In this paper a method is given for obtaining a mathematical model of a class of black boxes having multiple inputs and multiple outputs in terms of Ito stochastic integral equations. This method is applicable to the class of black boxes having ergodic correlation functions when there is zero applied input. The point of view adopted in this paper is phenomenological in that it is desired that calculations made using the mathematical model should be 'close' to what is actually observed at the output of the black box.

Eyman, E. D.↗
NASA NTRS1973

Modeling a particular class of multiple-input/multiple-output black boxes with stochastic integral equations and identifying the required parameters

A method is given for obtaining a mathematical model of a class of black boxes having multiple inputs and multiple outputs in terms of Ito stochastic integral equations. This method is applicable to the class of black boxes having ergodic correlation functions when there is zero applied input. The point of view adopted in this paper is phenomenological in that it is desired that calculations made using the mathematical model should be close to what is actually observed at the output of the black box. How close is defined in the problem statement.

Eyman, E. D.↗
DOE OSTI2022

FY22 Progress on Multicontinuum Methods in Containment

Estimation of two-phase fluid flow properties is important to understand and predict water and gas movement through the vadose zone for agricultural, hydrogeological, and engineering applications, such as containment transport and/or containment of gases in the subsurface. To estimate rock fluid flow properties and subsequently predict physically realistic processes such as patterns and timing of water, gas, and energy (e.g., heat) movement in the subsurface, laboratory spontaneous water imbibition with simultaneous temperature measurement and numerical modeling methods are presented in the FY22 progress report. A multiple-overlapping-continua conceptual model is used to explain and predict observed complex multi-phenomenological laboratory test behavior during spontaneous imbibition experiments. This report primarily addresses two complexities that arise during the experiments: 1) capturing the late-time behavior of spontaneous imbibition tests with dual porosity; and 2) understanding the thermal perturbation observed at or ahead of the imbibing wetting front, which are associated with adsorption of water in initially dry samples. We use numerical approaches to explore some of these issues, but also lay out a plan for further laboratory experimentation and modeling to best understand and leverage these unique observations.

58 GEOSCIENCES↗
DOE OSTI2023

Spin alignment of vector mesons by glasma fields

We explain how spin alignment of vector mesons can be induced by background fields, such as electromagnetic fields or soft gluon fields. Our study is based on the quantum kinetic theory of spinning quarks and antiquarks and incorporates the relaxation of the dynamically generated spin polarization. The spin density matrix of vector mesons is obtained by quark coalescence via the Wigner function and kinetic equation. Our approach predicts a local spin correlation that is distinct from the nonlocal expressions previously obtained in phenomenological derivations. We estimate the magnitude of such local correlations in the glasma model of the preequilibrium phase of relativistic heavy ion collisions. It is found that the resulting spin alignment could be greatly enhanced and may be comparable to the experimental measurement in order of magnitude. We further propose new phenomenological scenarios to qualitatively explain the transverse-momentum and centrality dependence of spin alignment in a self-consistent framework.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Computational investigation of water glasses using machine-learning potentials

The molecular origins of water’s anomalous properties have long been a subject of scientific inquiry. The liquid–liquid phase transition hypothesis, which posits the existence of distinct low-density and high-density liquid states separated by a first-order phase transition terminating at a critical point, has gained increasing experimental and computational support and offers a thermodynamically consistent framework for many of water’s anomalies. However, experimental challenges in avoiding crystallization near the postulated liquid–liquid critical point have focused attention to water’s canonical glassy states: low-density and high-density amorphous ice. Here, we use two Deep Potential machine-learning models, trained on the Strongly Constrained and Appropriately Normed density functional and the highly accurate Many-Body Polarizable potential, to conduct an investigation of water’s glassy phenomenology based on quantum mechanical calculations. Despite not being explicitly trained on amorphous ices, both models accurately capture the structure and transformation of the water glasses, including their interconversion along different thermodynamic paths. Isobaric quenching of liquid water at various pressures generates a continuum of intermediate amorphous ices and density fluctuations increase near the liquid–liquid critical pressure. The glass transition temperatures of the amorphous ices produced at different pressures exhibit two distinct branches, corresponding to low-density and high-density amorphous ice behaviors, consistent with experiment and the liquid–liquid transition hypothesis. Extrapolating transformation pressures from isothermal compressions to experimental compression rates brings our simulations into excellent agreement with data. Our findings demonstrate that machine-learning potentials trained on equilibrium phases can effectively model nonequilibrium glassy behavior and pave the way for studying long-timescale, out-of-equilibrium processes with quantum mechanical accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2010

Relating Cohesive Zone Model to Linear Elastic Fracture Mechanics

The conditions required for a cohesive zone model (CZM) to predict a failure load of a cracked structure similar to that obtained by a linear elastic fracture mechanics (LEFM) analysis are investigated in this paper. This study clarifies why many different phenomenological cohesive laws can produce similar fracture predictions. Analytical results for five cohesive zone models are obtained, using five different cohesive laws that have the same cohesive work rate (CWR-area under the traction-separation curve) but different maximum tractions. The effect of the maximum traction on the predicted cohesive zone length and the remote applied load at fracture is presented. Similar to the small scale yielding condition for an LEFM analysis to be valid. the cohesive zone length also needs to be much smaller than the crack length. This is a necessary condition for a CZM to obtain a fracture prediction equivalent to an LEFM result.

Wang, John T.↗
DOE OSTI2025

Phenomenology of electroweak portal dark showers: high energy direct probes and low energy complementarity

We investigate the phenomenology of a dark QCD sector interacting with the Standard Model (SM) via the electroweak (EW) portals. The portal interactions allow SM bosons, such as Z and h, or additional bosons that mix with them, to decay into dark quarks, producing dark showers. The light dark mesons are expected to be long-lived particles (LLPs), as their decays back to the SM states through the EW-portal interactions typically have macroscopic decay lengths. We focus on dark shower events initiated by various bosons at the Large Hadron Collider (LHC). The most prominent signal is the displaced decay of GeV-scale dark pions as LLPs. Current limits on dark shower signals at LHC detectors are recast from public data to provide simplified limits insensitive to UV physics details. Future limits in the high-luminosity phase and proposed auxiliary detectors are also projected. Additionally, we study the flavor-changing neutral current (FCNC) B decays into dark pions, obtaining both current and projected constraints at the LHC and other facilities. These constraints can be combined for specific models, which are illustrated in two EW-portal benchmarks: one with the heavy doublet fermion mediation and another with the Z′ mediator including a mass mixing. The collider reach shows significant potential to probe the parameter space unconstrained by EW precision tests, highlighting the necessity of dedicated LLP search strategies and facilities.

Dark Matter at Colliders↗
DOE OSTI2020

Computationally efficient CFD prediction of bubbly flow using physics-guided deep learning

To realize efficient computational fluid dynamics (CFD) prediction of two-phase flow, a multi-scale framework was proposed in this paper by applying a physics-guided data-driven approach. Instrumental to this framework, Feature Similarity Measurement (FSM) technique was developed for error estimation in two-phase flow simulation using coarse-mesh CFD, to achieve a comparable accuracy as fine-mesh simulations with fast-running feature. In this work, by defining physics-guided parameters and variable gradients as physical features, FSM has the capability to capture the underlying local patterns in the coarse-mesh CFD simulation. Massive low-fidelity data and respective high-fidelity data are used to explore the underlying information relevant to the main simulation errors and the effects of phenomenological scaling. By learning from previous simulation data, a surrogate model using deep feedforward neural network (DFNN) can be developed and trained to estimate the simulation error of coarse-mesh CFD. In a demonstration case of two-phase bubbly flow, the DFNN model well captured and corrected the unphysical “peaks” in the velocity and void fraction profiles near the wall in the coarse-mesh configuration, even for extrapolative predictions. The research documented supports the feasibility of the physics-guided deep learning methods for coarse mesh CFD simulations which has a potential for the efficient industrial design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗