Physics

Renewed interest in Very Low Earth Orbits (VLEO) - i.e. altitudes below 450 km - has led to an increased demand for accurate environment characterisation and aerodynamic force prediction. While the former requires knowledge of the mechanisms that drive density variations in the thermosphere, the latter also depends on the interactions between the gas-particles in the residual atmosphere and the surfaces exposed to the flow. The determination of the aerodynamic coefficients is hindered by the numerous uncertainties that characterise the physical processes occurring at the exposed surfaces. Several models have been produced over the last 60 years with the intent of combining accuracy with relatively simple implementations. In this paper the most popular models have been selected and reviewed using as discriminating factors relevance with regards to orbital aerodynamics applications and theoretical agreement with gas-beam experimental data. More sophisticated models were neglected, since their increased accuracy is generally accompanied by a substantial increase in computation times which is likely to be unsuitable for most space engineering applications. For the sake of clarity, a distinction was introduced between physical and scattering kernel theory based gas-surface interaction models. The physical model category comprises the Hard Cube model, the Soft Cube model and the Washboard model, while the scattering kernel family consists of the Maxwell model, the Nocilla-Hurlbut-Sherman model and the Cercignani-Lampis-Lord model. Limits and assets of each model have been discussed with regards to the context of this paper. Wherever possible, comments have been provided to help the reader to identify possible future challenges for gas-surface interaction science with regards to orbital aerodynamic applications.

Solar wind stream interaction regions (SIRs) are often characterized by energetic ion enhancements. The mechanisms accelerating these particles, as well as the locations where the acceleration occurs, remain debated. Here, we report the findings of a simulation of a SIR event observed by Parker Solar Probe at ~0.56 au and the Solar Terrestrial Relations Observatory-Ahead at ~0.95 au in 2019 September when both spacecraft were approximately radially aligned with the Sun. The simulation reproduces the solar wind configuration and the energetic particle enhancements observed by both spacecraft. Our results show that the energetic particles are produced at the compression waves associated with the SIR and that the suprathermal tail of the solar wind is a good candidate to provide the seed population for particle acceleration. The simulation confirms that the acceleration process does not require shock waves and can already commence within Earth's orbit, with an energy dependence on the precise location where particles are accelerated. The three-dimensional configuration of the solar wind streams strongly modulates the energetic particle distributions, illustrating the necessity of advanced models to understand these particle events.

This paper presents a new algorithm for detecting high-speed flow channels in the polar cap. The algorithm was applied to Super Dual Auroral Radar Network data, specifically to data from the new Longyearbyen radar. This radar is located at 78.2 ∘ N, 16.0 ∘ E geographical coordinates looking north-east, and is therefore at an ideal location to measure flow channels in the high-latitude polar cap. The algorithm detected > 500 events over 1 year of observations, and within this paper two case studies are considered in more detail. A flow channel on "old-open field lines" located on the dawn flank was directly driven under quiet conditions over 13 min. This flow channel contributed to a significant fraction (60%) of the cross polar cap potential and was located on the edge of a polar cap arc. Another case study follows the development of a flow channel on newly opened field lines within the cusp. This flow channel is a spontaneously driven event forming under strong solar wind driving and is intermittently excited over the course of almost an hour. As they provide a high fraction of the cross polar cap potential, these small-scale structures are vital for understanding the transport of magnetic flux over the polar cap.

The main purpose of this work is to perform an analysis of realistic new trajectories for a robotic mission to Saturn's largest moon, Titan, in order to demonstrate the great advantages related to the Direct Fusion Drive (DFD). The DFD is a D - 3 He fuelled, aneutronic, thermonuclear fusion propulsion system. This fusion propulsion concept is based on a magnetically confined field reversed configuration plasma, where the deuterium propellant is heated by fusion products, and then expanded into a magnetic nozzle, providing both thrust and electrical energy to the spacecraft [1]. The trajectories calculations and analysis for the Titan mission are obtained based on the characteristics provided by the PPPL [1]. Two different profile missions are considered: the first one is a thrust-coast-thrust profile with constant thrust and specific impulse; the second scenario is a continuous and constant thrust profile mission. Each mission study is divided into four different phases, starting from the initial low Earth orbit departure, the interplanetary trajectory, Saturn orbit insertion and the Titan orbit insertion. For all mission phases, maneuver time and propellant consumption are calculated. The results of calculations and mission analysis offer a complete overview of the advantages in term of payload mass and travel time. It is important to emphasize that the deceleration capability is one of the DFD game changer: in fact, the DFD performance allows to rapidly reach high velocities and decelerate in even shorter time period. This capability results in a total trip duration of 2.6 years for the thrust-coast-thrust profile and less than 2 years considering the continuous thrust profile. The high payload enabling capability, combined with the huge electrical power available from the fusion reactor, leads to a tremendous advantage compared to present technology.

Context. The electrostatic potential of a spacecraft, VS, is important for the capabilities of in situ plasma measurements. Rosetta has been found to be negatively charged during most of the comet mission and even more so in denser plasmas. Aims. Our goal is to investigate how the negative VS correlates with electron density and temperature and to understand the physics of the observed correlation. Methods. We applied full mission comparative statistics of VS, electron temperature, and electron density to establish VS dependence on cold and warm plasma density and electron temperature. We also used Spacecraft-Plasma Interaction System (SPIS) simulations and an analytical vacuum model to investigate if positively biased elements covering a fraction of the solar array surface can explain the observed correlations. Results. Here, the VS was found to depend more on electron density, particularly with regard to the cold part of the electrons, and less on electron temperature than was expected for the high flux of thermal (cometary) ionospheric electrons. This behaviour was reproduced by an analytical model which is consistent with numerical simulations. Conclusions. Rosetta is negatively driven mainly by positively biased elements on the borders of the front side of the solar panels as these can efficiently collect cold plasma electrons. Biased elements distributed elsewhere on the front side of the panels are less efficient at collecting electrons apart from locally produced electrons (photoelectrons). To avoid significant charging, future spacecraft may minimise the area of exposed bias conductors or use a positive ground power system.

Magnetic nulls are ubiquitous in space plasmas, and are of interest as sites of localized energy dissipation or magnetic reconnection. As such, a number of methods have been proposed for detecting nulls in both simulation data and in situ spacecraft data from Earth's magnetosphere. The same methods can be applied to detect stagnation points in flow fields. In this paper we describe a systematic comparison of different methods for finding magnetic nulls. The Poincare index method, the first-order Taylor expansion (FOTE) method, and the trilinear method are considered. We define a magnetic field containing fourteen magnetic nulls whose positions and types are known to arbitrary precision. Furthermore, we applied the selected techniques in order to find and classify those nulls. Two situations are considered: one in which the magnetic field is discretized on a rectangular grid, and the second in which the magnetic field is discretized along synthetic `spacecraft trajectories' within the domain. At present, FOTE and trilinear are the most reliable methods for finding nulls in the spacecraft data and in numerical simulations on Cartesian grids, respectively. The Poincare index method is suitable for simulations on both tetrahedral and hexahedral meshes. The proposed magnetic field configuration can be used for grading and benchmarking the new and existing tools for finding magnetic nulls and flow stagnation points.

Moving objects leave extended tracks in optical images acquired with a telescope that is tracking stars or other targets. By searching images for these tracks, one can obtain statistics on populations of space debris in Earth orbit. The algorithm described here combines matched filtering with a Fourier implementation of the discrete Radon transform and can detect long linear tracks with high sensitivity and speed. Monte-Carlo simulations show that such tracks, in a background of Poisson random noise, can be reliably detected even if they are invisible to the eye. On a 2.2 GHz computer the algorithm can process a 4096 x 4096-pixel image in less than a minute.

In this work we deepen and complement the analysis on the dynamics of Low Earth Orbits (LEO), carried out by the authors within the H2020 ReDSHIFT project, by characterising the evolution of the eccentricity of a large set of orbits in terms of the main frequency components. Decomposing the quasi-periodic time series of eccentricity of a given orbit by means of a numerical computation of Fourier transform, we link each frequency signature to the dynamical perturbation which originated it in order to build a frequency chart of the LEO region. We analyse and compare the effects on the eccentricity due to solar radiation pressure, lunisolar perturbations and high degree zonal harmonics of the geopotential both in the time and frequency domains. In particular, we identify the frequency signatures due to the dynamical resonances found in LEO and we discuss the opportunity to exploit the corresponding growth of eccentricity in order to outline decommissioning strategies.

Hot flow anomalies (HFAs) are studied using observations of the magnetometer and the plasma instrument aboard the four Cluster spacecraft. We study several specific features of tangential discontinuities on the basis of Cluster measurements from the time periods of February-April 2003, December 2005-April 2006 and January-April 2007, when the separation distance of spacecraft was large. The previously discovered condition (Facsko et al., 2008) for forming HFAs is confirmed, i.e. that the solar wind speed and fast magnetosonic Mach number values are higher than average. Furthermore, this constraint is independent of the Schwartz et al. (2000)s condition for HFA formation. The existence of this new condition is confirmed by simultaneous ACE magnetic field and solar wind plasma observations at the L1 point, at 1.4 million km distance from the Earth. The temperature, particle density and pressure parameters observed at the time of HFA formation are also studied and compared to average values of the solar wind plasma. The size of the region affected by the HFA was estimated by using two different methods. We found that the size is mainly influenced by the magnetic shear and the angle between the discontinuity normal and the Sun-Earth direction. The size grows with the shear and (up to a certain point) with the angle as well. After that point it starts decreasing. The results are compared with the outcome of recent hybrid simulations.

We present a novel algorithm that predicts the probability that the time derivative of the horizontal component of the ground magnetic field dB/dt exceeds a specified threshold at a given location. This quantity provides important information that is physically relevant to Geomagnetically Induced Currents (GIC), which are electric currents { associated to} sudden changes in the Earth's magnetic field due to Space Weather events. The model follows a 'gray-box' approach by combining the output of a physics-based model with machine learning. Specifically, we combine the University of Michigan's Geospace model that is operational at the NOAA Space Weather Prediction Center, with a boosted ensemble of classification trees. We discuss the problem of re-calibrating the output of the decision tree to obtain reliable probabilities. The performance of the model is assessed by typical metrics for probabilistic forecasts: Probability of Detection and False Detection, True Skill Statistic, Heidke Skill Score, and Receiver Operating Characteristic curve. We show that the ML enhanced algorithm consistently improves all the metrics considered.