Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userAcceleration Profiles and Processing Methods for Parabolic Flight
66
0
0.0
(
0
)
Authors
Christopher E. Carr
Ask ChatGPT about the research
No Arabic abstract
Parabolic flights provide cost-effective, time-limited access to weightless or reduced gravity conditions experienced in space or on planetary surfaces, e.g. the Moon or Mars. These flights facilitate fundamental research - from materials science to space biology - and testing/validation activities that support and complement infrequent and costly access to space. While parabolic flights have been conducted for decades, reference acceleration profiles and processing methods are not widely available - yet are critical for assessing the results of these activities. Here we present a method for collecting, analyzing, and classifying the altered gravity environments experienced during a parabolic flight. We validated this method using a commercially available accelerometer during a Boeing 727-200F flight with $20$ parabolas. All data and analysis code are freely available. Our solution can be easily integrated with a variety of experimental designs, does not depend upon accelerometer orientation, and allows for unsupervised and repeatable classification of all phases of flight, providing a consistent and open-source approach to quantifying gravito-intertial accelerations (GIA), or $g$ levels. As academic, governmental, and commercial use of space increases, data availability and validated processing methods will enable better planning, execution, and analysis of parabolic flight experiments, and thus, facilitate future space activities.
rate research
Read More
This monograph covers some recent advances on a range of acceleration techniques frequently used in convex optimization. We first use quadratic optimization problems to introduce two key families of methods, momentum and nested optimization schemes, which coincide in the quadratic case to form the Chebyshev method whose complexity is analyzed using Chebyshev polynomials. We discuss momentum methods in detail, starting with the seminal work of Nesterov (1983) and structure convergence proofs using a few master templates, such as that of emph{optimized gradient methods} which have the key benefit of showing how momentum methods maximize convergence rates. We further cover proximal acceleration techniques, at the heart of the emph{Catalyst} and emph{Accelerated Hybrid Proximal Extragradient} frameworks, using similar algorithmic patterns. Common acceleration techniques directly rely on the knowledge of some regularity parameters of the problem at hand, and we conclude by discussing emph{restart} schemes, a set of simple techniques to reach nearly optimal convergence rates while adapting to unobserved regularity parameters.
Modern advances in space technology have enabled the capture and recording of unprecedented volumes of data. In the field of solar physics this is most readily apparent with the advent of the Solar Dynamics Observatory (SDO), which returns in excess of 1 terabyte of data daily. While we now have sufficient capability to capture, transmit and store this information, the solar physics community now faces the new challenge of analysis and mining of high-volume and potentially boundless data sets such as this: a task known to the computer science community as stream mining. In this paper, we survey existing and established stream mining methods in the context of solar physics, with a goal of providing an introductory overview of stream mining algorithms employed by the computer science fields. We consider key concepts surrounding stream mining that are applicable to solar physics, outlining existing algorithms developed to address this problem in other fields of study, and discuss their applicability to massive solar data sets. We also discuss the considerations and trade-offs that may need to be made when applying stream mining methods to solar data. We find that while no one single solution is readily available, many of the methods now employed in other data streaming applications could successfully be modified to apply to solar data and prove invaluable for successful analysis and mining of this new source.
A foundational model has been developed based on trends built from empirical data of space exploration and computing power through the first six plus decades of the Space Age which projects earliest possible launch dates for human-crewed missions from cis-lunar space to selected Solar System and interstellar destinations. The model uses computational power, expressed as transistors per microprocessor, as a key broadly limiting factor for deep space missions reach and complexity. The goal of this analysis is to provide a projected timeframe for humanity to become a multi-world species through off-world colonization, and in so doing all but guarantees the long-term survival of the human race from natural and human-caused calamities that could befall life on Earth. Be-ginning with the development and deployment of the first nuclear weapons near the end of World War II, humanity entered a Window of Peril which will not be safely closed until robust off-world colonies become a reality. Our findings suggest the first human-crewed missions to land on Mars, selected Asteroid Belt objects, and selected moons of Jupiter and Saturn can occur before the end of the 21st century. Launches of human-crewed interstellar missions to exoplanet destinations within roughly 40 lightyears of the Solar System are seen as possible during the 23rd century and launch of intragalactic missions by the end of the 24th century. An aggressive and sustained space exploration program, which includes colonization, is thus seen as critical to the long-term survival of the human race.
Large satellite constellations in low-Earth orbit seek to be the infrastructure for global broadband Internet and other telecommunication needs. We briefly review the impacts of satellite constellations on astronomy and show that the Internet service offered by these satellites will primarily target populations where it is unaffordable, not needed, or both. The harm done by tens to hundreds of thousands of low-Earth orbit satellites to astronomy, stargazers worldwide, and the environment is not acceptable.
Following from the results of the first systematic modern low frequency Search for Extraterrestrial Intelligence (SETI) using the Murchison Widefield Array (MWA), which was directed toward a Galactic Center field, we report a second survey toward a Galactic Anticenter field. Using the MWA in the frequency range of 99 to 122 MHz over a three hour period, a 625 sq. deg. field centered on Orion KL (in the general direction of the Galactic Anticenter) was observed with a frequency resolution of 10 kHz. Within this field, 22 exoplanets are known. At the positions of these exoplanets, we searched for narrow band signals consistent with radio transmissions from intelligent civilisations. No such signals were found with a 5-sigma detection threshold. Our sample is significantly different to the 45 exoplanets previously studied with the MWA toward the Galactic Center Tingay et al.(2016), since the Galactic Center sample is dominated by exoplanets detected using microlensing, hence at much larger distances compared to the exoplants toward the Anticenter, found via radial velocity and transit detection methods. Our average effective sensitivity to extraterrestrial transmiter power is therefore much improved for the Anticenter sample. Added to this, our data processing techniques have improved, reducing our observational errors, leading to our best detection limit being reduced by approximately a factor of four compared to our previously published results.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
