Schumann resonance frequency and conductivity in the nighttime ionosphere of Mars: A source for lightning

We have solved the Maxwellian equations of electromagnetic waves which oscillate within the cavity formed in the lower ionosphere of Mars between 0 and 70?km. The electrical conductivity and Schumann Resonance (SR) frequencies are calculated in the lower ionosphere of Mars, in the presence of a major dust storm that occurred in Martian Year (MY) 25 at low latitude region (25°–35°S). It is found that the atmospheric conductivity reduced by one to two orders of magnitude in the presence of a dust storm. It represents a small dust layer at about 25–30?km altitudes where lightning can occur. We also found that the SR frequencies peak at?～18?km with values 19.9, 34.5 and 48.8?Hz for the modes l?=?1, 2 and 3, respectively, in the non-homogeneous medium. Our results indicate that practical or measurable values of SR are dependent on the altitudes.     

Wake structure and similar behavior of wake profiles downstream of a plunging airfoil

Very limited attention has already been paid to the velocity behavior in the wake region in unsteady aerodynamic problems.A series of tests has been performed on a flapping airfoil in a subsonic wind tunnel to study the wake structure for different sets of mean angle of attack,plunging amplitude and reduced frequency.In this study,the velocity profiles in the wake for various oscillation parameters have been measured using a wide shoulder rake,especially designed for the present experiments.The airfoil under consideration was a critical section of a 660 kW wind turbine.The results show that for a flapping airfoil the wake structure can be of drag producing type,thrust producing or neutral,depending on the mean angle of attack,oscillation amplitude and reduced frequency.In a thrust producing wake,a high-momentum high-velocity jet flow is formed in the core region of the wake instead of the conventional low-momentum flow.As a result,the drag force normally experienced by the body due to the momentum deficit would be replaced by a thrust force.According to the results,the momentum loss in the wake decreases as the reduced frequency increases.The thrust producing wake pattern for the flapping airfoil has been observed for suffi ciently low angles of attack in the absence of the viscous effects.This phenomenon has also been observed for either high oscillation amplitudes or high reduced frequencies.According to the results,for different reduced frequencies and plunging amplitudes,such that the product of them be a constant,the velocity profiles exhibit similar behavior and coalesce on each other.This simi larity parameter works excellently at small angles of attack.However,at near stall boundaries,the similarity is not as evident as before.     

The automated prediction of solar flares from SDO images using deep learning

In the last few years, there has been growing interest in near-real-time solar data processing, especially for space weather applications. This is due to space weather impacts on both space-borne and ground-based systems, and industries, which subsequently impacts our lives. In the current study, the deep learning approach is used to establish an automated hybrid computer system for a short-term forecast; it is achieved by using the complexity level of the sunspot group on SDO/HMI Intensitygram images. Furthermore, this suggested system can generate the forecast for solar flare occurrences within the following 24 h. The input data for the proposed system are SDO/HMI full-disk Intensitygram images and SDO/HMI full-disk magnetogram images. System outputs are the “Flare or Non-Flare” of daily flare occurrences (C, M, and X classes). This system integrates an image processing system to automatically detect sunspot groups on SDO/HMI Intensitygram images using active-region data extracted from SDO/HMI magnetogram images (presented by Colak and Qahwaji, 2008) and deep learning to generate these forecasts. Our deep learning-based system is designed to analyze sunspot groups on the solar disk to predict whether this sunspot group is capable of releasing a significant flare or not. Our system introduced in this work is called ASAP_Deep. The deep learning model used in our system is based on the integration of the Convolutional Neural Network (CNN) and Softmax classifier to extract special features from the sunspot group images detected from SDO/HMI (Intensitygram and magnetogram) images. Furthermore, a CNN training scheme based on the integration of a back-propagation algorithm and a mini-batch AdaGrad optimization method is suggested for weight updates and to modify learning rates, respectively. The images of the sunspot regions are cropped automatically by the imaging system and processed using deep learning rules to provide near real-time predictions. The major results of this study are as follows. Firstly, the ASAP_Deep system builds on the ASAP system introduced in Colak and Qahwaji (2009) but improves the system with an updated deep learning-based prediction capability. Secondly, we successfully apply CNN to the sunspot group image without any pre-processing or feature extraction. Thirdly, our system results are considerably better, especially for the false alarm ratio (FAR); this reduces the losses resulting from the protection measures applied by companies. Also, the proposed system achieves a relatively high scores for True Skill Statistics (TSS) and Heidke Skill Score (HSS).     

The spatio-spectral localization approach to modeling VTEC over the western part of the USA using GPS observations

The precise ionosphere modeling is crucial and remains a challenge for GPS positioning and navigation, as well as many other Earth observation systems. In this research, two approaches have been proposed to model the vertical total electron content (VTEC) of the ionosphere using spherical slepian function. For the two-dimensional case, VTEC has been modeled in a sun-fixed reference frame and the three-dimensional approach based on the system of the three-dimensional base functions has been defined as the tensor product of the spherical slepian function for the longitude and latitude in an Earth-fixed reference frame, and the polynomial B-spline function for time. Rather than the spherical harmonics, the spherical slepian functions can be employed to produce the locally and globally orthogonal bases to optimally represent the data in any arbitrary region up to a given degree. The spherical slepian functions have been applied to the real data obtained from the ground-based GPS observation across the western part of the USA.     

Microbial life in a liquid asphalt desert

Pitch Lake in Trinidad and Tobago is a natural asphalt reservoir nourished by pitch seepage, a form of petroleum that consists of mostly asphaltines, from the surrounding oil-rich region. During upward seepage, pitch mixes with mud and gases under high pressure, and the lighter portion evaporates or is volatilized, which produces a liquid asphalt residue characterized by low water activity, recalcitrant carbon substrates, and noxious chemical compounds. An active microbial community of archaea and bacteria, many of them novel strains (particularly from the new Tar ARC groups), totaling a biomass of up to 10(7) cells per gram, was found to inhabit the liquid hydrocarbon matrix of Pitch Lake. Geochemical and molecular taxonomic approaches revealed diverse, novel, and deeply branching microbial lineages with the potential to mediate anaerobic hydrocarbon degradation processes in different parts of the asphalt column. In addition, we found markers for archaeal methane metabolism and specific gene sequences affiliated with facultative and obligate anaerobic sulfur- and nitrite-oxidizing bacteria. The microbial diversity at Pitch Lake was found to be unique when compared to microbial communities analyzed at other hydrocarbon-rich environments, which included Rancho Le Brea, a natural asphalt environment in California, USA, and an oil well and a mud volcano in Trinidad and Tobago, among other sites. These results open a window into the microbial ecology and biogeochemistry of recalcitrant hydrocarbon matrices and establish the site as a terrestrial analogue for modeling the biotic potential of hydrocarbon lakes such as those found on Saturn's largest moon Titan.     

On the selection of optimal global geopotential model for geoid modeling: A case study in Pakistan

A statistical comparison has been made between gravity field parameters derived from different global geopotential models (GGMs) and observed gravity anomalies, gravimetric geoid and GPS-Leveling data. The motivation behind this study is the selection of best possible global geopotential model that best matches statistically with the local observed data in Pakistan. This will facilitate in decreasing the load on observed data for the development of regional gravimetric geoid in remove-compute-restore technique when used in the Stokes’s integral for computation of the residual part. It is observed that combined geopotential models such as EGM96 and PGM200A, EIGEN-GL04C and EIGEN-CG03C reflect the better match in the total spectral range of gravity and GPS-Leveling data. Results of the precise local geoid model also indicate similar characteristics. A very-high-degree model “EGM2008” (degree/order 2160) exhibits relatively superior statistical fit with observed ground data in Pakistan region. For satellite-only models an increasing trend in the standard deviation can be seen with maximum of about ∼4 m in difference between GPS-Leveling and corresponding GGM’s geoid with increase in the order from 50 to 120 and then it decreases afterwards. However, for the EIGEN-CHAMP03SP, standard deviation saturates to a value of 3.4 m. This is an indication of contamination in the long to medium wavelength part, i.e. 50–100° for the satellite-only models. Moreover, the models DEOS-CHAMP-01C, GGM02C and then ITG-GRACE03 appear to have better fit for medium to long wavelength and can possibly be recommended for use as long wavelength part with the local observed data. While a hybrid geopotential model selection can be achieved through the selection from either of DEOS-CHAMP-01C, GGM02C, GGM02S, EIGEN-GRACE02S or ITG-GRACE03 in the long wavelength (to degree and order 40) and EGM96, PGM200A, EIGEN-GL04C, EIGEN-CG03C or even EGM2008 in medium to short wavelength, i.e. from degree 41 to maximum degree and order.     

Predicting the visibility of LEO satellites

We present a simple algorithm to determine the visibility-time function of a circular low Earth orbit (LEO) satellite at a terminal on the Earth's surface. The simplicity of the algorithm is based on approximating the ground trace of the satellite (which is not a great circle due to Earth's rotation) during a time interval of the order of in-view period, by a great-circle are. This enables us to use spherical geometry to compute the location and time epoch of the observation of the closest approach of the satellite's ground trace to the terminal. This is also the epoch of the observation of the maximum elevation angle from the terminal to the satellite. Applying a result derived relating the maximum elevation angle to the in-view period, we obtain the visibility-time function of the satellite at the terminal. Numerical results illustrate the accuracy of the algorithm for a wide range of LEO orbit altitudes     

A novel autonomous low-cost on-board data handling architecture for a pin-point planetary lander

There has been increased interest in the exploration of the Moon in recent years. Pin-point precision landing is highly desirable for future lunar missions. This paper is concerned with the design of the on-board data handling (OBDH) subsystem for the pin-point lunar lander of the Magnolia-1 project, funded by NASA. Four proposed on-board data handling architectures are outlined and compared in terms of power consumption, performance and reliability. Implementation results are presented, which are obtained from prototyping of the flight computer for the optimal OBDH architecture option on a Xilinx Virtex-5 Field Programmable Gate Array.     

基于仿射变换的机载凝视红外告警器图像配准

提出了一种用于机载凝视红外图像序列的配准算法.分析凝视红外图像的特点,建立二维仿射变换模型描述三维空间.以帧间均方差最小作为评价标准拟合4个最优配准参数,通过参数步长控制配准算法精度.通过实测空中红外小飞机图像序列,证明了该算法配准精度可达到象素级,并可有效屏蔽背景杂波干扰.     

Implications of day temperature variation for an aero-engine's HP turbine-blade's creep life-consumption

Some in-service deterioration in any mechanical device, such as an aero-engine, is inevitable. Also in a country like Pakistan, there is a significant variation of day temperature over the year. As a result of experiencing deterioration (of the engine as a whole or any of its components individually) and/or any alteration in the conditions (such as day temperature) of incoming air stream, an engine will seek a different steady operating point thereby resulting in a variation of the spool speeds and/or turbine-entry temperatures in order to provide the same thrust. Rises in the turbine entry-temperatures and spool speeds result in greater rates of creep and fatigue damage being incurred by the hot-end components and thereby higher engine's life cycle costs.Possessing a better knowledge of the impacts of day temperature variation upon the creep life-consumption of aero-engine's hot-end components, helps the users to take wiser management-decisions. For a military aircraft's mission-profile, using a bespoke computer simulation, the implications of day temperature variation for a turbofan aero-engine's high pressure turbine-blade's creep life-consumption have been predicted.