An evolutionary computational framework for capacity-safety trade-off in an air transportation network

Airspace safety and airport capacity are two key challenges to sustain the growth in Air Transportation. In this paper, we model the Air Transportation Network as two sub-networks of airspace and airports, such that the safety and capacity of the overall Air Transportation network emerge from the interaction between the two. We propose a safety-capacity trade-off approach,using a computational framework, where the two networks can inter-act and the trade-off between capacity and safety in an Air Transport Network can be established. The framework comprise of an evolutionary computation based air traffic scenario generation using a flow capacity estimation module(for capacity), Collision risk estimation module(for safety) and an air traffic simulation module(for evaluation). The proposed methodology to evolve air traffic scenarios such that it minimizes collision risk for given capacity estimation was tested on two different air transport network topologies(random and small-world) with the same number of airports. Experimental results indicate that though airspace collision risk increases almost linearly with the increasing flow(flow intensity) in the corresponding airport network, the critical flow depend on the underlying network configuration. It was also found that, in general, the capacity upper bound depends not only on the connectivity among airports and their individual performances but also the configuration of waypoints and mid-air interactions among conflicts. Results also show that airport network can accommodate more traffic in terms of capacity but the corresponding airspace network cannot accommodate the resulting traffic flow due to the bounds on collision risk.     

Numerical investigation of transitions in flow states and variation in aerodynamic forces for flow around square cylinders arranged inline

This study focuses on the transitions in flow states around two-, three- and four-inline square cylinders under the effect of Reynolds numbers at two different gap spacing values using the lattice Boltzmann method. For this purpose, Reynolds number is varied in the range 1–130 while two different values of spacing taken into account are gap spacing?=?2 and 5. Before going to actual problem, the code is tested for flow around a single square cylinder by comparing the results with experimental and numerical results of other researchers, and good agreement is found. The current numerical computations yield that for both spacing values and all combinations of cylinders there exist three different sates of flow depending on Reynolds numbers: steady state, transitional state and unsteady state. It is found that the range of Reynolds numbers for these flow states is different for both spacing values. At gap spacing?=?2 the range of Reynolds numbers for each flow state decreases by increasing the number of cylinders while at gap spacing?=?5 opposite trend is observed. The results also show that at gap spacing?=?2 the reduction in drag force is greater than the corresponding reduction at gap spacing?=?5. The maximum reduction in drag force is observed at Reynolds numbers?=?1 at both spacing values. Similarly, at both spacing values and all Reynolds numbers, the maximum reduction in drag force is observed for the case of four-inline square cylinders.     

Sea level trend over Malaysian seas from multi-mission satellite altimetry and vertical land motion corrected tidal data

Rise in sea levels is one of the disastrous effects of climate change. A relatively small increase in sea level could affect natural coastal systems. In a study of long-term changes in sea level and measurements of postglacial rebound, monitoring vertical land motion (VLM) is of crucial interest. This study presents an approach to estimate precise sea level trends based on a combination of multi-sensor techniques in the Malaysian region over 19?years. In this study, satellite altimeters (SALT) were used to derive absolute sea levels (ASLs). Tide gauge (TG) stations along the coast of Malaysia were utilised to derive the rate of relative sea levels using sea level changes and VLMs. To obtain ASL at TGs, VLM at these stations were computed using Global Positioning System (GPS), Persistent Scatterer Interferometric Synthetic Aperture Radar (PS InSAR), and SALT minus TG. The computed VLMs mostly show similarities in signs rather than magnitude. The findings from the multi-sensor techniques showed that regional sea level trends ranged from 2.65?±?0.86?mm/yr to 6.03?±?0.79?mm/yr for chosen sub-areas, with an overall mean of 4.47?±?0.71?mm/yr and overall subsidence. This information is expected to be valuable for a wide variety of climatic applications and for studying environmental issues related to flooding and global warming in Malaysia.     

Automatic lineament extraction in a heavily vegetated region using Landsat Enhanced Thematic Mapper (ETM+) imagery

Lineament extraction from satellite remotely sensed data has been one of the widely used applications of remote sensing in geology. In fact, recent advances in digital image processing allow such lineament extraction to be accomplished in semi-automatic to fully automatic approaches. However, satellite remotely sensed data acquired in heavily vegetated regions such as tropical rainforest, are vulnerable to higher inherent noise levels attributed to the resultant effects of scattering by clouds and adjacency effects of highly inhomogeneous vegetation cover within the pixel dimension. In this study, we examined the effects of noise levels to lineament extraction using a fully automatic approach, consisting of a combination of edge-line detection algorithms. Ancillary information from a digitized topographic map and image classification was used to discriminate between cultural and natural lineaments from the extracted lineaments. Adapting the combination of edge detection and a line-linking algorithm, we have found the optimal parameters for automatic lineament extraction of such complex areas using Enhanced Thematic Mapper (ETM+) data. A noise level of 30% is the maximum threshold before artifacts are generated. It is therefore concluded that the combination of edge-based and line-linking digital image processing operations with the priori local optimal parameters is crucial in lineament feature extraction in heavily vegetated regions.     

Statistical ionospheric E layer properties measured with the Cyprus Digisonde and comparisons with IRI predictions

This paper reports the diurnal, seasonal, and long term variability of the E layer critical frequency (foE) and peak height (hmE) derived from Digisonde measurements from 2009 to 2016 at the low-middle latitude European station of Nicosia, Cyprus (geographical coordinates: 35°N, 33°E, geomagnetic lat. 29.38°N, I = 51.7°). Manually scaled monthly median values of foE and hmE are compared with IRI-2012 predictions with a view to assess the predictability of IRI. Results show that in general, IRI slightly overestimates foE values both at low and high solar activity. At low solar activity, overestimations are mostly limited to 0.25?MHz (equivalent electron density, 0.775?×?10³?el/m^?3) but can go as high as 0.5?MHz (equivalent electron density, 3.1?×?10³?el/m^?3, during noon) around equinox. In some months, underestimations, though sporadic in nature, up to 0.25?MHz are noted (mostly during sunrise and sunset). At high solar activity, a similar pattern of over-/underestimation is evident. During the entire period of study, over-/under estimations are mostly limited to 0.25?MHz. In very few cases, these exceed 0.25?MHz but are limited to 0.5?MHz. Analysis of hmE reveals that: (1) hmE remains almost constant during ±2 to ±4?h around local noon, (2) hmE values are higher in winter than in spring, summer and autumn, (3) there are two maxima near sunrise and sunset with a noontime minimum in between. During the entire period of study, significant differences between observed hmE and the IRI predictions have been noted. IRI fails to predict hmE and outputs a constant value of 110?km, which is higher than most of the observed values. Over- and under estimations range from 3 to 13?km and from 0 to 3?km respectively.