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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Remotely sensed physical property estimation from powder contaminated surfaces

It is the intent of this paper to demonstrate the veracity of a method to estimate the total solid contaminant mass present on a sparsely coated surface encompassing a pixel from longwave infrared spectra. Sparsely coated surfaces create complex radiometry due to the interactions of electromagnetic energy between intimate materials. Current algorithms can be used on intimate mixtures to identify the abundances of materials in a pixel, but they cannot provide additional property information. Radiative transfer models can create mixture signatures, but only with a set of well-characterized physical parameters that are typically not known or are difficult to retrieve. Finally, the approach described here creates a parameter inversion model from a radiative transfer model and uses empirically measured mixture data to retrieve physical characteristics of the contaminated surface and derive a total contaminant mass present.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations

We developed a new class of physics-informed generative adversarial networks (PI-GANs) to solve forward, inverse, and mixed stochastic problems in a unified manner based on a limited number of scattered measurements. Unlike standard GANs relying solely on data for training, here we encoded into the architecture of GANs the governing physical laws in the form of stochastic differential equations (SDEs) using automatic differentiation. In particular, we applied Wasserstein GANs with gradient penalty (WGAN-GP) for its enhanced stability compared to vanilla GANs. We first tested WGAN-GP in approximating Gaussian processes of different correlation lengths based on data realizations collected from simultaneous reads at sparsely placed sensors. We obtained good approximation of the generated stochastic processes to the target ones even if there is a mismatch between the input noise dimensionality and the effective dimensionality of the target stochastic processes. We also studied the overfitting issue for both the discriminator and the generator, and we found that overfitting occurs also in the generator in addition to the discriminator as previously reported. Subsequently, we considered the solution of elliptic SDEs requiring approximations of three stochastic processes, namely the solution, the forcing, and the diffusion coefficient. Here again, we assumed data collected from simultaneous reads at a limited number of sensors for the multiple stochastic processes. Furthermore, three generators were used for the PI-GANs: two of them were feed forward deep neural networks (DNNs), while the other one was the neural network induced by the SDE. For the case where we have one group of data, we employed one feed forward DNN as the discriminator, while for the case of multiple groups of data we employed multiple discriminators in PI-GANs. We solved forward, inverse, and mixed problems without changing the framework of PI-GANs, obtaining both the means and the standard deviations of the stochastic solution and the diffusion coefficient in good agreement with benchmarks. In this work, we have demonstrated the effectiveness of PI-GANs in solving SDEs for about 120 dimensions. In principle, PI-GANs could tackle very high dimensional problems given more sensor data with low-polynomial growth in computational cost.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

On-Sensor Data Filtering using Neuromorphic Computing for High Energy Physics Experiments

This work describes the investigation of neuromorphic computing-based spiking neural network (SNN) models used to filter data from sensor electronics in high energy physics experiments conducted at the High Luminosity Large Hadron Collider. We present our approach for developing a compact neuromorphic model that filters out the sensor data based on the particle's transverse momentum with the goal of reducing the amount of data being sent to the downstream electronics. The incoming charge waveforms are converted to streams of binary-valued events, which are then processed by the SNN. We present our insights on the various system design choices - from data encoding to optimal hyperparameters of the training algorithm - for an accurate and compact SNN optimized for hardware deployment. Our results show that an SNN trained with an evolutionary algorithm and an optimized set of hyperparameters obtains a signal efficiency of about 91% with nearly half as many parameters as a deep neural network.

R. Kulkarni, Shruti↗
DOE OSTI2020

High-power few-cycle Cr:ZnSe mid-infrared source for attosecond soft x-ray physics

The development of mid-infrared, high-energy pulses of extremely short pulse duration is of great importance to the strong-field physics community, as it enables extension of the high-harmonic cutoff towards the keV range of photon energies. Here we demonstrate a C r 2 + : Z n S e laser amplifier delivering 7 mJ, 100 fs pulses at 1 kHz repetition rate and 2.4 µm central wavelength with excellent energy stability and beam quality. These pulses are post-compressed to 39 fs, 6.2 mJ, and 115 GW peak power in a novel nonlinear compression scheme. The laser system was used to generate coherent soft x-ray radiation up to 0.6 keV covering the entire water window, which is of high importance for bio-relevant applications. The obtained results open a wide range of applications in nonlinear optics, attosecond and strong-field physics, and remote sensing.

Leshchenko, Vyacheslav E. (ORCID:0000000199708559)↗
DOE OSTI2024

Role of physics in physics-informed machine learning

Physical systems are characterized by inherent symmetries, one of which is encapsulated in the units of their parameters and system states. These symmetries enable a lossless order-reduction, e.g., via dimensional analysis based on the Buckingham theorem. Despite the latter's benefits, machine learning (ML) strategies for the discovery of constitutive laws seldom subject experimental and/or numerical data to dimensional analysis. We demonstrate the potential of dimensional analysis to significantly enhance the interpretability and generalizability of ML-discovered secondary laws. Our numerical experiments with creeping fluid flow past solid ellipsoids show how dimensional analysis enable both deep neural networks and sparse regression reproduce old results, e.g., Stokes law for a sphere, and generate new ones, e.g., an expression for an ellipsoid misaligned with the flow direction. Furthermore, our results suggest the need to incorporate other physics-based symmetries and invariances into ML-based techniques for equation discovery.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Big data health physics: a case study in operational health physics

This paper, written as a two part project as required by Illinois Institute of Technology’s Phys597 Reading & Special Problems class and health physics professional master’s program, focuses on the results of a prototype data collection process implemented at a Los Alamos National Laboratory facility. In particular, this paper examines the data in a statistical context in an effort to optimize operational health physics processes at the Los Alamos National Laboratory.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Late-time Cooling of Neutron Star Transients and the Physics of the Inner Crust

An accretion outburst onto a neutron star transient heats the neutron star’s crust out of thermal equilibrium with the core. After the outburst, the crust thermally relaxes toward equilibrium with the neutron star core, and the surface thermal emission powers the quiescent X-ray light curve. Crust cooling models predict that thermal equilibrium of the crust will be established ≈1000 days into quiescence. Recent observations of the cooling neutron star transient MXB 1659-29, however, suggest that the crust did not reach thermal equilibrium with the core on the predicted timescale and continued to cool after ≈2500 days into quiescence. Because the quiescent light curve reveals successively deeper layers of the crust, the observed late-time cooling of MXB 1659-29 depends on the thermal transport in the inner crust. In particular, the observed late-time cooling is consistent with a low thermal conductivity layer near the depth predicted for nuclear pasta that maintains a temperature gradient between the neutron star’s inner crust and core for thousands of days into quiescence. As a result, the temperature near the crust–core boundary remains above the critical temperature for neutron superfluidity, and a layer of normal neutrons forms in the inner crust. We find that the late-time cooling of MXB 1659-29 is consistent with heat release from a normal neutron layer near the crust–core boundary with a long thermal time. We also investigate the effect of inner crust physics on the predicted cooling curves of the accreting transient KS 1731-260 and the magnetar SGR 1627-41.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1967

Physical electronics and surface physics

Physical electronics and surface physics - contact potential measurements of adsorption of oxygen on Ta and steady-state analysis of desorption of molecules from nonuniform surfaces

CONTACT POTENTIAL↗
NASA NTRS1974

Solar Physics - Plasma Physics Workshop

A summary of the proceedings of a conference whose purpose was to explore plasma physics problems which arise in the study of solar physics is provided. Sessions were concerned with specific questions including the following: (1) whether the solar plasma is thermal or non-themal; (2) what spectroscopic data is required; (3) what types of magnetic field structures exist; (4) whether magnetohydrodynamic instabilities occur; (5) whether resistive or non-magnetohydrodynamic instabilities occur; (6) what mechanisms of particle acceleration have been proposed; and (7) what information is available concerning shock waves. Very few questions were answered categorically but, for each question, there was discussion concerning the observational evidence, theoretical analyses, and existing or potential laboratory and numerical experiments.

Baum, P. J.↗
NASA NTRS1987

Backscatter analysis of dihedral corner reflectors using physical optics and the physical theory of diffraction

The backscatter cross-sections of dihedral corner reflectors in the azimuthal plane are presently determined by both physical optics (PO) and the physical theory of diffraction (PTD), yielding results for the vertical and horizontal polarizations. In the first analysis method used, geometrical optics is used in place of PO at initial reflections in order to maintain the planar character of the reflected wave and reduce the complexity of the analysis. In the second method, PO is used at almost every reflection in order to maximize the accuracy of the PTD solution at the expense of a rapid increase in complexity. Induced surface current densities and resulting cross section patterns are illustrated for the two methods.

Griesser, Timothy↗
NASA NTRS1991

Nuclear winter - Physics and physical mechanisms

The basic physics of the environmental perturbations caused by multiple nuclear detonations is explored, summarizing current knowledge of the possible physical, chemical, and biological impacts of nuclear war. Emphasis is given to the impact of the bomb-generated smoke (soot) particles. General classes of models that have been used to simulate nuclear winter are examined, using specific models as examples.

Turco, R. P.↗
NASA NTRS2004

Ultrahigh Energy Cosmic Rays: Old Physics or New Physics?

We consider the advantages of and the problems associated with hypotheses to explain the origin of ultrahigh energy cosmic rays (UHECR: E greater than 10 EeV) and the "trans-GZK" cosmic rays (TGZK: E greater than 100 EeV) both through "old physics" (acceleration in cosmic sources) and "new physics" (new particles, topological defects, fat neutrino cross sections, Lorentz invariance violation).

Stecker, F. W.↗
NASA NTRS2020

2019 NASA Division of Space Life and Physical Sciences Research and Applications Fluid Physics Workshop Report

On October 16 and 17, 2019, NASA’s Space Life and Physical Sciences Research and Applications (SLPSRA) Division held the 2019 NASA SLPSRA Fluid Physics Workshop at the Glenn Research Center in Cleveland, Ohio. Researchers from academia, industry, and Government agencies gathered to provide recommendations to NASA on exploration-related microgravity challenges in multiphase systems and thermal transport processes. The goal of the workshop was to identify overarching future research themes relevant to NASA’s exploration goals in three key areas: (1) boiling and condensation; (2) water recovery; and (3) heat pipes.

microgravity↗
DOE OSTI2022

Report of the Topical Group on Higgs Physics for Snowmass 2021: The Case for Precision Higgs Physics

A future Higgs Factory will provide improved precision on measurements of Higgs couplings beyond those obtained by the LHC, and will enable a broad range of investigations across the fields of fundamental physics, including the mechanism of electroweak symmetry breaking, the origin of the masses and mixing of fundamental particles, the predominance of matter over antimatter, and the nature of dark matter. Future colliders will measure Higgs couplings to a few per cent, giving a window to beyond the Standard Model (BSM) physics in the 1-10 TeV range. In addition, they will make precise measurements of the Higgs width, and characterize the Higgs self-coupling. Here, this report details the work of the EF01 and EF02 working groups for the Snowmass 2021 study.

Dawson, Sally↗
DOE OSTI2017

White paper on nuclear astrophysics and low-energy nuclear physics, Part 2: Low-energy nuclear physics

In preparation for the 2015 NSAC Long Range Plan (LRP), the DNP town meetings on Nuclear Astrophysics and Low-Energy Nuclear Physics were held at the Mitchell Center on the campus of Texas A&M University August 21–23, 2014. Participants met in a number of topic-oriented working groups to discuss progress since the 2007 LRP, compelling science opportunities, and the resources needed to advance them. These considerations were used to determine priorities for the next five to ten years. In addition, approximately 270 participants attended the meetings, coming from US national laboratories, a wide range of US universities and other research institutions and universities abroad.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Solving kinetic equations with adaptive mesh in phase space for rarefied gas dynamics and plasma physics (Invited)

The paper describes an Adaptive Mesh in Phase Space (AMPS) technique for solving kinetic equations with deterministic mesh-based methods. The AMPS technique allows automatic generation of adaptive Cartesian mesh in both physical and velocity spaces using a Tree-of-Trees data structure. We illustrate advantages of AMPS for simulations of rarefied gas dynamics and electron kinetics on low temperature plasmas. In particular, we consider formation of the velocity distribution functions in hypersonic flows, particle kinetics near oscillating boundaries, and electron kinetics in a radio-frequency sheath. AMPS provide substantial savings in computational cost and increased efficiency of the mesh-based kinetic solvers.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Kaon physics without new physics in $$ \varepsilon _K$$

Abstract Despite the observation of significant suppressions of $$b\rightarrow s\mu ^+\mu ^-$$ b → s μ + μ - branching ratios no clear sign of New Physics (NP) has been identified in $$\Delta F=2$$ Δ F = 2 observables $$\Delta M_{d,s}$$ Δ M d , s , $$\varepsilon _K$$ ε K and the mixing induced CP asymmetries $$S_{\psi K_S}$$ S ψ K S and $$S_{\psi \phi }$$ S ψ ϕ . Assuming negligible NP contributions to these observables allows to determine CKM parameters without being involved in the tensions between inclusive and exclusive determinations of $$|V_{cb}|$$ | V cb | and $$|V_{ub}|$$ | V ub | . Furthermore this method avoids the impact of NP on the determination of these parameters present likely in global fits. Simultaneously it provides SM predictions for numerous rare K and B branching ratios that are most accurate to date. Analyzing this scenario within $$Z^\prime $$ Z ′ models we point out, following the 2009 observations of Monika Blanke and ours of 2020, that despite the absence of NP contributions to $$\varepsilon _K$$ ε K , significant NP contributions to $$K^+\rightarrow \pi ^+\nu {\bar{\nu }}$$ K + → π + ν ν ¯ , $$K_{L}\rightarrow \pi ^0\nu {\bar{\nu }}$$ K L → π 0 ν ν ¯ , $$K_S\rightarrow \mu ^+\mu ^-$$ K S → μ + μ - , $$K_L\rightarrow \pi ^0\ell ^+\ell ^-$$ K L → π 0 ℓ + ℓ - , $$\varepsilon '/\varepsilon $$ ε ′ / ε and $$\Delta M_K$$ Δ M K can be present. In the simplest scenario, this is guaranteed, as far as flavour changes are concerned, by a single non-vanishing imaginary left-handed $$Z^\prime $$ Z ′ coupling $$g^L_{sd}$$ g sd L . This scenario implies very stringent correlations between the Kaon observables considered by us. In particular, the identification of NP in any of these observables implies automatically NP contributions to the remaining ones under the assumption of non-vanishing flavour conserving $$Z^\prime $$ Z ′ couplings to $$q{\bar{q}}$$ q q ¯ , $$\nu {\bar{\nu }}$$ ν ν ¯ , and $$\mu ^+\mu ^-$$ μ + μ - . A characteristic feature of this scenario is a strict correlation between $$K^+\rightarrow \pi ^+\nu {\bar{\nu }}$$ K + → π + ν ν ¯ and $$K_{L}\rightarrow \pi ^0\nu {\bar{\nu }}$$ K L → π 0 ν ν ¯ branching ratios on a branch parallel to the Grossman-Nir bound. Moreover, $$\Delta M_K$$ Δ M K is automatically suppressed as seems to be required by the results of the RBC-UKQCD lattice QCD collaboration. Furthermore, there is no NP contribution to $$K_L\rightarrow \mu ^+\mu ^-$$ K L → μ + μ - which otherwise would bound NP effects in $$K^+\rightarrow \pi ^+\nu {\bar{\nu }}$$ K + → π + ν ν ¯ . Of particular interest are the correlations of $$K^+\rightarrow \pi ^+\nu {\bar{\nu }}$$ K + → π + ν ν ¯ and $$K_{L}\rightarrow \pi ^0\nu {\bar{\nu }}$$ K L → π 0 ν ν ¯ branching ratios and of $$\Delta M_K$$ Δ M K with the ratio $$\varepsilon '/\varepsilon $$ ε ′ / ε . We investigate the impact of renormalization group effects in the context of the SMEFT on this simple scenario.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗