Inferring the dense nuclear matter equation of state with neutron star tides

During the late stages of a neutron star binary inspiral finite-size effects come into play, with the tidal deformability of the supranuclear density matter leaving an imprint on the gravitational-wave signal. As demonstrated in the case of GW170817—the first direct detection of gravitational waves from a neutron star binary—this can lead to strong constraints on the neutron star equation of state. As detectors become more sensitive, effects which may have a smaller influence on the neutron star tidal deformability need to be taken into consideration. Dynamical effects, such as oscillation mode resonances triggered by the orbital motion, have been shown to contribute to the tidal deformability, especially close to the neutron star coalesence, where current detectors are most sensitive. We calculate the contribution of the various stellar oscillation modes to the tidal deformability and demonstrate the (anticipated) dominance of the fundamental mode. We show what the impact of the matter composition is on the tidal deformability, as well as the changes induced by more realistic additions to the problem, e.g. the presence of an elastic crust. Finally, based on this formulation, we develop a simple phenomenological model describing the effective tidal deformability of neutron stars and show that it provides a surprisingly accurate representation of the dynamical tide close to merger.

Explainable Deep Learning for the Analysis of MHD Spectrograms in Nuclear Fusion

In the nuclear fusion community, there are many specialized techniques to analyze the data coming from a variety of diagnostics. One of such techniques is the use of spectrograms to analyze the magnetohydrodynamic (MHD) behavior of fusion plasmas. Physicists look at the spectrogram to identify the oscillation modes of the plasma, and to study instabilities that may lead to plasma disruptions. One of the major causes of disruptions occurs when an oscillation mode interacts with the wall, stops rotating, and becomes a locked mode. In this work, we use deep learning to predict the occurrence of locked modes from MHD spectrograms. In particular, we use a Convolutional Neural Network (CNN) with Class Activation Mapping (CAM) to pinpoint the exact behavior that the model thinks is responsible for the locked mode. Surprisingly, we find that, in general, the model explanation agrees quite well with the physical interpretation of the behavior observed in the spectrogram.

Acoustic microstreaming produced by two interacting gas bubbles undergoing axisymmetric shape oscillations

An analytical theory is developed that describes acoustic microstreaming produced by two interacting bubbles. The bubbles are assumed to undergo axisymmetric oscillation modes, which can include radial oscillations, translation and shape modes. Analytical solutions are derived in terms of complex amplitudes of oscillation modes, which means that the modal amplitudes are assumed to be known and serve as input data when the velocity field of acoustic microstreaming is calculated. No restrictions are imposed on the ratio of the bubble radii to the viscous penetration depth and the distance between the bubbles. The interaction between the bubbles is considered both when the linear velocity field is calculated and when the second-order velocity field of acoustic microstreaming is calculated. Capabilities of the analytical theory are illustrated by computational examples.

Estimation and Separation of Longitudinal Dynamic Stability Derivatives with Forced Oscillation Method Using Computational Fluid Dynamics

This paper focuses on estimating dynamic stability derivatives using a computational fluid dynamics (CFD)-based force oscillation method, and on separating the coupled dynamic derivatives terms obtained from the method. A transient RANS solver is used to calculate the time history of aerodynamic moments for a test model oscillating about the center of gravity, from which the coupled dynamic derivatives are estimated. The separation of the coupled derivatives term is carried out by simulating simple harmonic oscillation motions such as plunging motion and flapping motion which can isolate the pitching moment due to AOA rate (Cmα˙) and the pitching moment due to pitch rate (Cmq), respectively. The periodic motions are implemented using a CFD dynamic mesh technique with user-defined function (UDF). For the validation test, steady and unsteady simulations are performed on the Army-Navy Finner Missile model. The static aerodynamic moments and pressure distribution, as well as the coupled dynamic derivative results from the pitching oscillation mode, show good agreement with the previously published wind tunnel tests and CFD analysis data. In order to separate the coupled derivative terms, two additional harmonic oscillation modes of plunging and flapping motions are tested with the angle of attack variations from 0 to 85 degrees at a supersonic speed to provide real insight on the missile maneuverability. The cross-validation study between the three oscillation modes indicates the summation of the individual plunging and flapping results becoming nearly identical to the coupled derivative results from the pitching motion, which implies the entire set of coupled and separated dynamic derivative terms can be effectively estimated with only two out of three modes. The advantages and disadvantages of each method are discussed to determine the efficient approach of estimating the dynamic stability derivatives using the forced oscillation method.

Inside-wind-farm/Wind-farm-grid sub-synchronous oscillation characteristics analysis in grid-connected system of multiple DFIGs

Aiming at the sub-synchronous oscillation (SSO) problem of the grid-connected system of multiple DFIGs, most of the existing theoretical studies take the entire wind farm as a single-machine model, the stand-alone model cannot reflect the inside-wind-farm oscillation mode produced by the interactions among DFIGs in the wind farm. Therefore, this paper takes the equivalent value of DFIG-based wind farm to three DFIGs, establishes a mathematical model of the grid-connected system of three DFIGs, and studies the sub-synchronous oscillation modes existing in the system through eigenvalue analysis and participation factor analysis. The results show: When the length of transmission line increases, the oscillation frequency of the inside-wind-farm/wind-farm-grid sub-synchronous oscillation mode increases, the damping decreases and the stability weakens; when the number of grid-connected DFIGs increases, the oscillation frequency of the inside-wind-farm/wind-farm-grid sub-synchronous oscillation mode decreases, the damping increases and the stability enhances. Finally, a time-domain simulation model of the grid-connected system of multiple DFIGs was built in PSCAD/EMTDC to verify the correctness of the theoretical analysis results.

String excitation by initial singularity of inflation

We discuss excitation of string oscillation modes by an initial singularity of inflation. The initial singularity of inflation is known to occur with a finite Hubble parameter, which is generally lower than the string scale, and hence it is not clear that stringy effects become significant around it. With the help of Penrose limit, we find that infinitely heavy oscillation modes get excited when a singularity is strong in the sense of Krolak’s classification. We demonstrate that the initial singularities of Starobinsky and hill top inflation, assuming the slow roll inflation to the past infinity, are strong. Hence stringy corrections are inevitable in the very early stage of these inflation models. We also find that the initial singularity of the hill top inflation could be weak for non-slow roll case.