The Lunar Terrestrial Observatory: Observing the Earth using photometers on the Moon’s surface

The Earth’s albedo is one of the least studied fundamental climate parameters. The albedo is a bi-directional variable, and there is a high degree of anisotropy in the light reflected from a given terrestrial surface. However, simultaneously observing from all points on Earth at all reflecting angles is a practical impossibility. Therefore, all measurements from which albedo can be inferred require assumptions and/or modeling to derive a good estimate. Nowadays, albedo measurements are taken regularly either from low Earth orbit satellite platforms or from ground-based measurements of the earthshine from the dark side of the Moon. But the results from these different measurements are not in satisfactory agreement. Clearly, the availability of different albedo databases and their inter-comparisons can help to constrain the assumptions necessary to reduce the uncertainty of the albedo estimates. In recent years, there has been a renewed interest in the development of robotic and manned exploration missions to the Moon. Returning to the Moon will enable diverse exploration and scientific opportunities. Here we discuss the possibility of a lunar-based Earth radiation budget monitoring experiment, the Lunar Terrestrial Observatory, and evaluate its scientific and practical advantages compared to the other, more standard, observing platforms. We conclude that a lunar-based terrestrial observatory can enable advances in Earth sciences, complementary to the present efforts, and to our understanding of the Earth’s climate.     

Solar flare forecasting model supported with artificial neural network techniques

Nowadays operational models for solar activity forecasting are still based on the statistical relationship between solar activity and solar magnetic field evolution. In order to set up this relationship, many parameters have been proposed to be the measures. Conventional measures are based on the sunspot group classification which provides limited information from sunspots. For this reason, new measures based on solar magnetic field observations are proposed and a solar flare forecasting model supported with an artificial neural network is introduced. This model is equivalent to a person with a long period of solar flare forecasting experience.     

Modes of uncontrolled rotational motion of the <Emphasis Type="Italic">Progress M-29M</Emphasis> spacecraft

We have reconstructed the uncontrolled rotational motion of the Progress M-29M transport cargo spacecraft in the single-axis solar orientation mode (the so-called sunward spin) and in the mode of the gravitational orientation of a rotating satellite. The modes were implemented on April 3–7, 2016 as a part of preparation for experiments with the DAKON convection sensor onboard the Progress spacecraft. The reconstruction was performed by integral statistical techniques using the measurements of the spacecraft’s angular velocity and electric current from its solar arrays. The measurement data obtained in a certain time interval have been jointly processed using the least-squares method by integrating the equations of the spacecraft’s motion relative to the center of mass. As a result of processing, the initial conditions of motion and parameters of the mathematical model have been estimated. The motion in the sunward spin mode is the rotation of the spacecraft with an angular velocity of 2.2 deg/s about the normal to the plane of solar arrays; the normal is oriented toward the Sun or forms a small angle with this direction. The duration of the mode is several orbit passes. The reconstruction has been performed over time intervals of up to 1 h. As a result, the actual rotational motion of the spacecraft relative to the Earth–Sun direction was obtained. In the gravitational orientation mode, the spacecraft was rotated about its longitudinal axis with an angular velocity of 0.1–0.2 deg/s; the longitudinal axis executed small oscillated relative to the local vertical. The reconstruction of motion relative to the orbital coordinate system was performed in time intervals of up to 7 h using only the angularvelocity measurements. The measurements of the electric current from solar arrays were used for verification.     

Functional analysis: a system conceptual design tool [andapplication to ATC system]

Functional analysis is a methodology for analyzing the mission and performance requirements of a system, and translating them into discrete activities or tasks which must be performed by the system. Determination of the system's functionality is the first step in obtaining a conceptual view of a system that is to be designed. The methodology for conducting functional analysis is developed, some of the tools used to support the activity are described, including examples to help solidify the concepts presented     

Detection of ultrahigh-energy cosmic rays and neutrinos by radio method using artificial lunar satellites

An estimate of the feasibility of the ultrahigh-energy cosmic ray and neutrino detection using a lunar satellite-borne radio receiver is presented. The data obtained in the proposed experiment will make resolving the current contradictions in the ultrahigh-energy cosmic ray spectra measured with the major ground-based instruments possible. Moreover, they will enable us to considerably extend the accessible energy range and to check predictions of various models of the origin of the highest-energy particles in the Universe. At the same time the lunar radio detector provides a means of searching for ultrahigh-energy neutrinos with a high sensitivity combined with a very large target effective mass.     

Temperature Cycling Effects on Solar Panels

Temperature cycling for more than 300 cycles and for temperatures down to - 175°C performed on soldered silicon cell assemblies with copper, Kovar, and molybdenum interconnectors showed a wide range in failures depending both upon the materials used and on interconnector thickness and substrate material. The solder fatigue failure rate is strongly dependent on stress level in agreement with analytical predictions.