Electromagnetic Formation Flying with Eccentric Reference Orbits

Over the last decade, a considerable amount of research work has been done in the area of spacecraft formation flight, with particular emphasis on control techniques using thruster-based systems. Nevertheless, thrusters require propellant to work and this limit the lifetime of the mission. Electromagnetic Formation Flight (EMFF) is presented in this paper as a fuel-less strategy to control spacecraft formations by means of electromagnets. In EMFF, spacecraft can be equipped with one or more coils and reactions wheels which could be arranged in several combinations according to mission requirements. An electric current flows through the coils in order to produce a magnetic dipole in a specific direction. The magnetic field of a spacecraft reacts against the magnetic dipoles of the others, generating forces and torques which in turn could be used as control inputs. The main objective of this paper is to provide a formulation for EMFF when a formation is moving in eccentric reference orbits and for this purpose, the Tschauner and Hempel model will be used. Results are presented after analysing different formation scenarios providing the necessary magnetic requirements for station keeping and resolving which cases are suitable to be controlled by this technology. High-Temperature Semiconductor (HTS) plays an important role in EMFF and for that reason the paper also investigates the correlation of the magnetic force and the coil mass, which in turn affects the total mass of the spacecraft

The pole-sitter mission concept : an overview of recent developments and possible future applications

The paper provides a survey of novel mission concepts for continuous, hemispheric polar observation and direct-link polar telecommunications. It is well known that these services cannot be provided by traditional platforms: geostationary satellites do not cover high-latitude regions, while low- and medium-orbit Sun-synchronous spacecraft only cover a narrow swath of the Earth at each passage. Concepts that are proposed in the literature are described, including the pole-sitter concept (in which a spacecraft is stationary above the pole), spacecraft in artificial equilibrium points in the Sun-Earth system and non-Keplerian polar Molniya orbits. Additionally, novel displaced eight-shaped orbits at Lagrangian points are presented. For many of these concepts, a continuous acceleration is required and propulsion systems include solar electric propulsion, solar sail and a hybridisation of the two. Advantages and drawbacks of each mission concept are assessed, and a comparison in terms of high-latitude coverage and distance, spacecraft mass, payload and lifetime is presented. Finally, the paper will describe a number of potential applications enabled by these concepts, focusing on polar Earth observation and telecommunications

Novel mission concepts for polar coverage : An overview of recent developments and possible future applications

The paper provides a survey of novel mission concepts for continuous, hemispheric polar observation and direct-link polar telecommunications. It is well known that these services cannot be provided by traditional platforms: geostationary satellites do not cover high-latitude regions, while low- and medium-orbit Sun-synchronous spacecraft only cover a narrow swath of the Earth at each passage. Concepts that are proposed in the literature are described, including the pole-sitter concept (in which a spacecraft is stationary above the pole), spacecraft in artificial equilibrium points in the Sun-Earth system and non-Keplerian polar Molniya orbits. Additionally, novel displaced eight-shaped orbits at Lagrangian points are presented. For many of these concepts, a continuous acceleration is required and propulsion systems include solar electric propulsion, solar sail and a hybridisation of the two. Advantages and drawbacks of each mission concept are assessed, and a comparison in terms of high-latitude coverage and distance, spacecraft mass, payload and lifetime is presented. Finally, the paper will describe a number of potential applications enabled by these concepts, focusing on polar Earth observation and telecommunications

Electromagnetic Formation Flying with Eccentric Reference Orbits

Over the last decade, a considerable amount of research work has been done in the area of spacecraft formation flight, with particular emphasis on control techniques using thruster-based systems. Nevertheless, thrusters require propellant to work and this limit the lifetime of the mission. Electromagnetic Formation Flight (EMFF) is presented in this paper as a fuel-less strategy to control spacecraft formations by means of electromagnets. In EMFF, spacecraft can be equipped with one or more coils and reactions wheels which could be arranged in several combinations according to mission requirements. An electric current flows through the coils in order to produce a magnetic dipole in a specific direction. The magnetic field of a spacecraft reacts against the magnetic dipoles of the others, generating forces and torques which in turn could be used as control inputs. The main objective of this paper is to provide a formulation for EMFF when a formation is moving in eccentric reference orbits and for this purpose, the Tschauner and Hempel model will be used. Results are presented after analysing different formation scenarios providing the necessary magnetic requirements for station keeping and resolving which cases are suitable to be controlled by this technology. High-Temperature Semiconductor (HTS) plays an important role in EMFF and for that reason the paper also investigates the correlation of the magnetic force and the coil mass, which in turn affects the total mass of the spacecraft

Autonomous distributed LQR/APF control algorithms for CubeSat swarms manoeuvring in eccentric orbits

Spacecraft formation flying has shown to be promising approach to enhance mission capabilities. Nevertheless, formation flying presents several control challenges which escalate as the numbers of elements in the formation is increased. The objective of this paper is to develop decentralised control algorithms to regulate the station-keeping, reconfiguration and collision avoidance of spacecraft in formation around eccentric reference orbits using the combination of a Linear Quadratic Regulator (LQR) and an Artificial Potential Function (APF). Within this control scheme, the LQR will provide station-keeping and reconfiguration capabilities toward desired positions, while optimizing fuel consumption and the APF will ensure collision free manoeuvres between the elements of the formation during manoeuvres. The controller is designed under the assumption of continuous thrust as a standard LQR problem using the Pontryagin minimum principle, an APF based in normalized Gaussian functions and the Tschauner and Hempel (TH) equations as the relative dynamics model

Accelerating the convergence of path integral dynamics with a generalized Langevin equation

The quantum nature of nuclei plays an important role in the accurate modelling of light atoms such as hydrogen, but it is often neglected in simulations due to the high computational overhead involved. It has recently been shown that zero-point energy effects can be included comparatively cheaply in simulations of harmonic and quasi-harmonic systems by augmenting classical molecular dynamics with a generalized Langevin equation (GLE). Here we describe how a similar approach can be used to accelerate the convergence of path integral (PI) molecular dynamics to the exact quantum mechanical result in more strongly anharmonic systems exhibiting both zero point energy and tunnelling effects. The resulting PI-GLE method is illustrated with applications to a double-well tunnelling problem and to liquid water

Efficient stochastic thermostatting of path integral molecular dynamics

The path integral molecular dynamics (PIMD) method provides a convenient way to compute the quantum mechanical structural and thermodynamic properties of condensed phase systems at the expense of introducing an additional set of high-frequency normal modes on top of the physical vibrations of the system. Efficiently sampling such a wide range of frequencies provides a considerable thermostatting challenge. Here we introduce a simple stochastic path integral Langevin equation (PILE) thermostat which exploits an analytic knowledge of the free path integral normal mode frequencies. We also apply a recently-developed colored-noise thermostat based on a generalized Langevin equation (GLE), which automatically achieves a similar, frequency-optimized sampling. The sampling efficiencies of these thermostats are compared with that of the more conventional Nos\'e-Hoover chain (NHC) thermostat for a number of physically relevant properties of the liquid water and hydrogen-in-palladium systems. In nearly every case, the new PILE thermostat is found to perform just as well as the NHC thermostat while allowing for a computationally more efficient implementation. The GLE thermostat also proves to be very robust delivering a near-optimum sampling efficiency in all of the cases considered. We suspect that these simple stochastic thermostats will therefore find useful application in many future PIMD simulations.Comment: Accepted for publication on JC

The ghrelin paradox in the control of equine chondrocyte function: The good and the bad

Increasing evidence suggests a role for ghrelin in the control of articular inflammatory diseases like osteoarthritis (OA). In the present study we examined the ability of ghrelin to counteract LPS-induced necrosis and apoptosis of chondrocytes and the involvement of GH secretagogue receptor (GHS-R)1a in the protective action of ghrelin. The effects of ghrelin (10-7-10-11\u202fmol/L) on equine primary cultured chondrocytes viability and necrosis in basal conditions and under LPS treatment (100\u202fng/ml) were detected by using both acridine orange/propidium iodide staining and annexin-5/propidium iodide staining. The presence of GHS-R1a on chondrocytes was detected by Western Blot. The involvement of the GHS-R1a in the ghrelin effect against LPS-induced cytotoxicity was examined by pretreating chondrocytes with D-Lys3-GHRP-6, a specific GHS-R1a antagonist, and by using des-acyl ghrelin (DAG, 10-7and 10-9\u202fmol/L) which did not recognize the GHS-R 1a. Low ghrelin concentrations reduced chondrocyte viability whereas 10-7\u202fmol/L ghrelin protects against LPS-induced cellular damage. The protective effect of ghrelin depends on the interaction with the GHS-R1a since it is significantly reduced by D-Lys3-GHRP-6. The negative action of ghrelin involves caspase activation and could be due to an interaction with a GHS-R type different from the GHS-R1a recognized by both low ghrelin concentrations and DAG. DAG, in fact, induces a dose-dependent decrease in chondrocyte viability and exacerbates LPS-induced damage. These data indicate that ghrelin protects chondrocytes against LPS-induced damage via interaction with GHS-R1a and suggest the potential utility of local GHS-R1a agonist administration to treat articular inflammatory diseases such as OA

Robustness of Local Predictions in Atomistic Machine Learning Models

Machine learning (ML) models for molecules and materials commonly rely on a decomposition of the global target quantity into local, atom-centered contributions. This approach is convenient from a computational perspective, enabling large-scale ML-driven simulations with a linear-scaling cost, and also allow for the identification and post-hoc interpretation of contributions from individual chemical environments and motifs to complicated macroscopic properties. However, even though there exist practical justifications for these decompositions, only the global quantity is rigorously defined, and thus it is unclear to what extent the atomistic terms predicted by the model can be trusted. Here, we introduce a quantitative metric, which we call the local prediction rigidity (LPR), that allows one to assess how robust the locally decomposed predictions of ML models are. We investigate the dependence of LPR on the aspects of model training, particularly the composition of training dataset, for a range of different problems from simple toy models to real chemical systems. We present strategies to systematically enhance the LPR, which can be used to improve the robustness, interpretability, and transferability of atomistic ML models

Robustness of Local Predictions in Atomistic Machine Learning Models

Machine learning (ML) models for molecules and materials commonly rely on a decomposition of the global target quantity into local, atom-centered contributions. This approach is convenient from a computational perspective, enabling large-scale ML-driven simulations with a linear-scaling cost and also allows for the identification and posthoc interpretation of contributions from individual chemical environments and motifs to complicated macroscopic properties. However, even though practical justifications exist for the local decomposition, only the global quantity is rigorously defined. Thus, when the atom-centered contributions are used, their sensitivity to the training strategy or the model architecture should be carefully considered. To this end, we introduce a quantitative metric, which we call the local prediction rigidity (LPR), that allows one to assess how robust the locally decomposed predictions of ML models are. We investigate the dependence of the LPR on the aspects of model training, particularly the composition of training data set, for a range of different problems from simple toy models to real chemical systems. We present strategies to systematically enhance the LPR, which can be used to improve the robustness, interpretability, and transferability of atomistic ML models