Modeling, Analysis, and Optimization Issues for Large Space Structures

Topics concerning the modeling, analysis, and optimization of large space structures are discussed including structure-control interaction, structural and structural dynamics modeling, thermal analysis, testing, and design

Heterogeneity of the Attractor of the Lorenz '96 Model: Lyapunov Analysis, Unstable Periodic Orbits, and Shadowing Properties

The predictability of weather and climate is strongly state-dependent: special and extremely relevant atmospheric states like blockings are associated with anomalous instability. Indeed, typically, the instability of a chaotic dynamical system can vary considerably across its attractor. Such an attractor is in general densely populated by unstable periodic orbits that can be used to approximate any forward trajectory through the so-called shadowing. Dynamical heterogeneity can lead to the presence of unstable periodic orbits with different number of unstable dimensions. This phenomenon - unstable dimensions variability - implies a serious breakdown of hyperbolicity and has considerable implications in terms of the structural stability of the system and of the possibility to describe accurately its behaviour through numerical models. As a step in the direction of better understanding the properties of high-dimensional chaotic systems, we provide here an extensive numerical study of the dynamical heterogeneity of the Lorenz '96 model in a parametric configuration leading to chaotic dynamics. We show that the detected variability in the number of unstable dimensions is associated with the presence of many finite-time Lyapunov exponents that fluctuate about zero also when very long averaging times are considered. The transition between regions of the attractor with different degrees of instability comes with a significant drop of the quality of the shadowing. By performing a coarse graining based on the shadowing unstable periodic orbits, we can characterize the slow fluctuations of the system between regions featuring, on the average, anomalously high and anomalously low instability. In turn, such regions are associated, respectively, with states of anomalously high and low energy, thus providing a clear link between the microscopic and thermodynamical properties of the system.Comment: 28 pages, 11 figures, final accepted versio

Long-term variability of CO2 and O in the Mars upper atmosphere from MRO radio science data

We estimate the annual variability of CO2 and O partial density using approximately 6years of Mars Reconnaissance Orbiter (MRO) radio science data from August 2006 to January 2012, which cover three full Martian years (from the northern hemisphere summer of 28 to the northern hemisphere summer of 31). These two elements are the dominant species at the MRO periapsis altitude, constituting about 70-80% of the total density. We report the recovered annual cycle of CO2 and the annual and seasonal cycle of O in the upper atmosphere. Although no other observations are available at those altitudes, our results are in good agreement with the density measurements of the Mars Express Spectroscopy for Investigation of Characteristics of the Atmosphere of Mars, which uses stellar occultations between 60 and 130km to determine the CO2 variability, and with the Mars Global Reference Atmospheric Model 2010 for the O annual and seasonal variabilities. Furthermore, the updated model provides more reasonable MRO drag coefficients (CD), which are estimated to absorb mismodeling in the atmospheric density prediction. The higher content of dust in the atmosphere due to dust storms increases the density, so the CDs should compensate for this effect. The correlation between the drag coefficient and the dust optical depth, measured by the Mars Odyssey Thermal Emission Imaging System (THEMIS) instrument, increases from 0.4 to 0.8 with the a priori and adjusted models, respectively. The trend of CDs not only confirms a substantial improvement in the prediction of the atmospheric density with the updated model but also provides useful information for local dust storms, near MRO periapsis, that cannot be measured by the opacity level since THEMIS does not always sample the southern hemisphere evenly

New measurements of total ionizing dose in the lunar environment

[1] We report new measurements of solar minimum ionizing radiation dose at the Moon onboard the Lunar Reconnaissance Orbiter (LRO) from June 2009 through May 2010. The Cosmic Ray Telescope for the Effects of Radiation (CRaTER) instrument on LRO houses a compact and highly precise microdosimeter whose design allows measurements of dose rates below 1 micro-Rad per second in silicon achieved with minimal resources (20 g, ∼250 milliwatts, and ∼3 bits/second). We envision the use of such a small yet accurate dosimeter in many future spaceflight applications where volume, mass, and power are highly constrained. As this was the first operation of the microdosimeter in a space environment, the goal of this study is to verify its response by using simultaneous measurements of the galactic cosmic ray ionizing environment at LRO, at L1, and with other concurrent dosimeter measurements and model predictions. The microdosimeter measured the same short timescale modulations in the galactic cosmic rays as the other independent measurements, thus verifying its response to a known source of minimum-ionizing particles. The total dose for the LRO mission over the first 333 days was only 12.2 Rads behind ∼130 mils of aluminum because of the delayed rise of solar activity in solar cycle 24 and the corresponding lack of intense solar energetic particle events. The dose rate in a 50 km lunar orbit was about 30 percent lower than the interplanetary rate, as one would expect from lunar obstruction of the visible sky

Satellite Communications

This study is motivated by the need to give the reader a broad view of the developments, key concepts, and technologies related to information society evolution, with a focus on the wireless communications and geoinformation technologies and their role in the environment. Giving perspective, it aims at assisting people active in the industry, the public sector, and Earth science fields as well, by providing a base for their continued work and thinking

Prediction of Satellite Shadowing in Smart Cities with Application to IoT

The combination of satellite direct reception and terrestrial 5G infrastructure is essential to guarantee coverage in satellite based-Internet of Things, mainly in smart cities where buildings can cause high power losses. In this paper, we propose an accurate and fast graphical method for predicting the satellite coverage in urban areas and SatCom on-the-move scenarios. The aim is to provide information that could be useful in the IoT network planning process, e.g., in the decision of how many terrestrial repeaters are really needed and where they should be placed. Experiments show that the shadowed areas predicted by the method correspond almost perfectly with experimental data measured from an Eutelsat satellite in the urban area of Barcelona.Ministerio de Industria, Turismo y Comercio de España TSI-020301-2009-3

Proceedings of the Second International Mobile Satellite Conference (IMSC 1990)

Presented here are the proceedings of the Second International Mobile Satellite Conference (IMSC), held June 17-20, 1990 in Ottawa, Canada. Topics covered include future mobile satellite communications concepts, aeronautical applications, modulation and coding, propagation and experimental systems, mobile terminal equipment, network architecture and control, regulatory and policy considerations, vehicle antennas, and speech compression

Climate Model Sensitivity with Respect to Parameters and External Forcing

Mathematical modelling is one of the most powerful methods for the study and understanding of the Earth’s climate system and its components. Modern climate models used in variety of applications are derived from a set of multi-dimensional non-linear differential equations in partial derivatives, which describe dynamical, physical and chemical processes and cycles in the climate system. Climate models are mostly deterministic with a large-phase space dimension containing a vast number of parameters that have various meanings. Most of them are not well-known a priori and, hence, are not well defined. Parameter errors and their time and space variabilities generate parametric uncertainty. Some model parameters describe external forcing that can strongly influence the climate model behaviour. It is, therefore, very important to estimate the influence of variations in parameters on the model behaviour and results of simulations. Questions like these can be answered by performing sensitivity analysis. This chapter considers various methods of sensitivity analysis that can be used: first, to estimate the influence of model parameter variations on its behaviour; second, to identify parameters of climate models and third, to study the model response to external forcing