A multi-station satellite radio beacon study of ionospheric variations during total solar eclipses

Faraday rotation data obtained at Delhi, Kurukshetra, Hyderabad, Bangalore, Waltair, Nagpur and Calcutta during the total solar eclipse of 16 February 1980 and at Delhi during the total solar eclipse of 31 July 1981 have been analysed to detect the gravity waves generated by a total solar eclipse as hypothesized by Chimonas and Hines (1970, J. geophys. Res. 75, 875). It has been found that gravity waves can be generated by a total solar eclipse but their detection at ionospheric heights is critically dependent on the location of the observing station in relation to the eclipse path geometry. The distance of the observing station from the eclipse path should be more than 500 km in order to detect such gravity waves.

Inverse Polynomial Based Explicit Guidance for Lunar Soft Landing During Powered Braking

In this paper an explicit guidance law for the powered descent phase of the soft lunar landing is presented. The descent trajectory, expressed in polynomial form is fixed based on the boundary conditions imposed by the precise soft landing mission. Adapting an inverse model based approach, the guidance command is computed from the known spacecraft trajectory. The guidance formulation ensures the vertical orientation of the spacecraft during touchdown. Also a closed form relation for the final flight time is proposed. The final time is expressed as a function of initial position and velocity of the spacecraft ( at the start of descent) and also depends on the desired landing site. To ensure the fuel minimum descent the proposed explicit method is extended to optimal guidance formulation. The effectiveness of the proposed guidance laws are demonstrated with simulation results.

Fuel-optimal G-MPSP Guidance for Powered Descent Phase of Soft Lunar Landing

A fuel optimal nonlinear sub-optimal guidance scheme is presented in this paper for soft landing of a lunar craft during the powered descent phase. The recently developed Generalized Model Predictive Static Programming (G-MPSP) is used to compute the required magnitude and angle of the thrust vector. Both terminal position and velocity vector are imposed as hard constraints, which ensures high position accuracy and facilitates initiation of vertical descent at the end of the powered descent phase. A key feature of the G-MPSP algorithm is that it converts the nonlinear dynamic programming problem into a low-dimensional static optimization problem (of the same dimension as the output vector). The control history update is done in closed form after computing a time-varying weighting matrix through a backward integration process. This feature makes the algorithm computationally efficient, which makes it suitable for on-board applications. The effectiveness of the proposed guidance algorithm is demonstrated through promising simulation results.

Optimal Guidance for Accurate Lunar Soft Landing with Minimum Fuel Consumption using Model Predictive Static Programming

In this paper the soft lunar landing with minimum fuel expenditure is formulated as a nonlinear optimal guidance problem. The realization of pinpoint soft landing with terminal velocity and position constraints is achieved using Model Predictive Static Programming (MPSP). The high accuracy of the terminal conditions is ensured as the formulation of the MPSP inherently poses final conditions as a set of hard constraints. The computational efficiency and fast convergence make the MPSP preferable for fixed final time onboard optimal guidance algorithm. It has also been observed that the minimum fuel requirement strongly depends on the choice of the final time (a critical point that is not given due importance in many literature). Hence, to optimally select the final time, a neural network is used to learn the mapping between various initial conditions in the domain of interest and the corresponding optimal flight time. To generate the training data set, the optimal final time is computed offline using a gradient based optimization technique. The effectiveness of the proposed method is demonstrated with rigorous simulation results.

Silicon isotopes: from cosmos to benthos

Silicon is the second most abundant element on the Earth and one of the more abundant elements in our Solar System. Variations in the relative abundance of the stable isotopes of Si (Si isotope fractionation) in different natural reservoirs, both terrestrial (surface and deep Earth) as well as extra-terrestrial (e.g. meteorites, lunar samples), are a powerful tracer of present and past processes involving abiotic as well as biotic systems. The versatility of the Si isotope tracer is reflected in its wide-ranging applications from understanding the origin of early Solar System objects, planetary differentiation, Moon formation, mantle melting and magma differentiation on the Earth, ancient sea-water composition, to modern-day weathering, clay formation and biological fractionation on land as well as in the oceans. The application of Si isotopes as tracers of natural processes started over six decades ago and its usage has seen a sudden increase over the last decade due to improvements in mass spectrometry, particularly the advent of multi-collector inductively coupled plasma mass spectrometers, which has made Si isotope measurements safe and relatively easy while simultaneously improving the accuracy and precision of measurements.