Science & Technology MCQs

Geostationary Orbit (GEO) is typically used for communication satellites because it allows them to remain in a fixed position relative to the Earth's surface, providing continuous coverage over a specific geographical area.

Advanced communication satellites are primarily designed to improve telecommunications, including broadband services, and to provide reliable communication infrastructure for disaster management and emergency response.

The LIGO-India observatory is planned to be established in the Hingoli district of Maharashtra. The site selection process considered factors like seismic stability and low human population density to minimize interference.

The primary scientific objective of LIGO-India is to detect and study gravitational waves originating from cataclysmic astrophysical events such as the merger of black holes and neutron stars. This will open a new window for observing the universe.

LIGO-India is a major scientific project that is a collaboration between the Department of Atomic Energy (DAE) and the Department of Science and Technology (DST) in India, and the LIGO Laboratory in the United States. It aims to establish a gravitational wave detector in India, complementing the existing LIGO detectors in the US.

Semi-cryogenic engines, particularly those using kerosene and LOX, are generally more cost-effective to manufacture and operate compared to fully cryogenic engines. This cost reduction is a significant factor in ISRO's strategy for the NGLV program, aiming for more frequent and affordable access to space.

The semi-cryogenic engine technology is being developed specifically for ISRO's Next Generation Launch Vehicle (NGLV) program. This engine is expected to provide higher thrust and efficiency compared to existing engines, making NGLV a more capable launch platform.

ISRO's semi-cryogenic engine test for the NGLV utilizes a combination of Kerosene (specifically, a refined grade often referred to as 'Refined Petrol' or RP-1) as the fuel and Liquid Oxygen (LOX) as the oxidizer. This is a significant step towards developing more efficient and cost-effective launch vehicles.

AI models offer a significant advantage by providing rapid, localized forecasts at a fraction of the computational cost of traditional supercomputer-based models.

AI models learn from historical weather data to predict future states, whereas NWP models solve physical equations of the atmosphere, which is computationally expensive.