Dynamics of interacting generalized cosmic Chaplygin gas in brane-world scenario

In this work we explore the background dynamics when dark energy is coupled to dark matter with a suitable interaction in the universe described by brane cosmology. Here DGP and the RSII brane models have been considered separately. Dark energy in the form of Generalized Cosmic Chaplygin gas is considered. A suitable interaction between dark energy and dark matter is considered in order to at least alleviate (if not solve) the cosmic coincidence problem. The dynamical system of equations is solved numerically and a stable scaling solution is obtained. A significant attempt towards the solution of the cosmic coincidence problem is taken. The statefinder parameters are also calculated to classify the dark energy models. Graphs and phase diagrams are drawn to study the variations of these parameters. It is also seen that the background dynamics of Generalized Cosmic Chaplygin gas is consistent with the late cosmic acceleration, but not without satisfying certain conditions. It has been shown that the universe in both the models follows the power law form of expansion around the critical point, which is consistent with the known results. Future singularities were studied and our models were declared totally free from any types of such singularities. Finally, some cosmographic parameters were also briefly studied. Our investigation led to the fact that although Generalized cosmic Chaplygin gas with a far lesser negative pressure compared to other dark energy models, can overcome the relatively weaker gravity of RS II brane, with the help of the negative brane tension, yet for the DGP brane model with much higher gravitation, the incompetency of Generalized cosmic Chaplygin gas is exposed, and it cannot produce the accelerating scenario until it reaches the phantom era.     

High-energy afterglow emission from gamma-ray bursts

We calculate the very high-energy (sub-GeV to TeV) inverse Compton emission of GRB afterglows. We argue that this emission provides a powerful test of the currently accepted afterglow model. We focus on two processes: synchrotron self-Compton emission within the afterglow blast wave, and external inverse Compton emission which occurs when flare photons (produced by an internal process) pass through the blast wave. We show that if our current interpretations of the Swift X-ray telescope (XRT) data are correct, there should be a canonical high-energy afterglow emission light curve. Our predictions can be tested with high-energy observatories such as GLAST , Whipple, HESS and MAGIC. Under favourable conditions we expect afterglow detections in all these detectors.     

A novel mathematical morphology based algorithm for shoreline extraction from satellite images

Abstract

Shoreline extraction is fundamental and inevitable for several studies. Ascertaining the precise spatial location of the shoreline is crucial. Recently, the need for using remote sensing data to accomplish the complex task of automatic extraction of features, such as shoreline, has considerably increased. Automated feature extraction can drastically minimize the time and cost of data acquisition and database updating. Effective and fast approaches are essential to monitor coastline retreat and update shoreline maps. Here, we present a flexible mathematical morphology-driven approach for shoreline extraction algorithm from satellite imageries. The salient features of this work are the preservation of actual size and shape of the shorelines, run-time structuring element definition, semi-automation, faster processing, and single band adaptability. The proposed approach is tested with various sensor-driven images with low to high resolutions. Accuracy of the developed methodology has been assessed with manually prepared ground truths of the study area and compared with an existing shoreline classification approach. The proposed approach is found successful in shoreline extraction from the wide variety of satellite images based on the results drawn from visual and quantitative assessments.     

Variability and teleconnections of South and East Asian summer monsoons in present and future projections of CMIP5 climate models

Coupled Model Inter-comparison Project Phase 5 (CMIP5) model outputs of the South and East Asian summer monsoon variability and their tele-connections are investigated using historical simulations (1861-2005) and future projections under the RCP4.5 scenario (2006-2100). Detailed analyses are performed using nine models having better representation of the recent monsoon teleconnections for the interactive Asian monsoon sub-systems. However, these models underestimate rainfall mainly over South Asia and Korea-Japan sector, the regions of heavy rainfall, along with a bias in location of rainfall maxima. Indeed, the simulation biases, underestimations of monsoon variability and teleconnections suggest further improvements for better representation of Asian monsoon in the climate models. Interestingly, the performance of Australian Community Climate and Earth System Simulator version 1.0 (ACCESS1.0) in simulating the annual cycle, spatial pattern of rainfall and multi-decadal variations of summer monsoon rainfall over South and East Asia appears to more realistic. In spite of large spread among the CMIP5 models, historical simulations as well as future projections of summer monsoon rainfall indicate multi-decadal variability. These rainfall variations, displaying certain epochs of more rainfall over South Asia than over East Asia and vice versa, suggest an oscillatory behaviour. Teleconnections between South and East Asian monsoon rainfall also exhibit a multi-decadal variation with alternate epochs of strengthening and weakening relationship. Furthermore, large-scale circulation features such as South Asian monsoon trough and north Pacific subtropical high depict zonal oscillatory behaviour with east-west-east shifts. Periods with eastward or westward extension of the Mascarene High, intensification and expansion of the upper tropospheric South Asian High are also projected by the CMIP5 models.     

Study on clean technology-assisted combustion behavior and NO<Subscript><Emphasis Type="Italic">x</Emphasis></Subscript> emission using thermal imager for alternate fuel blends

The correlation between oxides of nitrogen emission and in-cylinder temperature of diesel engine fueled with various alternative fuels has been investigated in this research paper. Experimentations were performed in engine without any modifications using pure high-speed diesel fuel, used cooking oil biodiesel (UCO20), animal fat residue biodiesel (AFR20) and camphor oil (CMR20) at 20% volume concentration of biodiesel each. From combustion analysis, the heat release rate and peak cylinder pressure of biodiesel blends were about 13.487% lower and 4.819% higher than those of diesel fuel on an average, respectively. Longer combustion duration has been observed for all biodiesel blends at all load conditions. Oxides of nitrogen emission level show 16.405, 10.352 and 7.524% increment for UCO20, AFR20 and CMR20, respectively. Noteworthy NO _x reduction of about 43.8% was recorded for diesel blended with camphor oil when compared to other biodiesel blends. The relationship between in-cylinder temperature and NO _x emission concentration was premeditated through thermal imager. The result depicted that the increase in NO _x concentration depends on augmented in-cylinder temperature for all test fuels.     

Response reduction factor of irregular RC buildings in Kathmandu valley

Most current seismic design includes the nonlinear response of a structure through a response reduction factor(R). This allows the designer to use a linear elastic force-based approach while accounting for nonlinear behavior and deformation limits. In fact, the response reduction factor is used in modern seismic codes to scale down the elastic response of a structure. This study focuses on estimating the actual ‘R' value for engineered design/construction of reinforced concrete(RC) buildings in Kathmandu valley. The ductility and overstrength of representative RC buildings in Kathmandu are investigated. Nonlinear pushover analysis was performed on structural models in order to evaluate the seismic performance of buildings. Twelve representative engineered irregular buildings with a variety of characteristics located in the Kathmandu valley were selected and studied. Furthermore, the effects of overstrength on the ductility factor, beam column capacity ratio on the building ductility, and load path on the response reduction factor, are examined. Finally, the results are further analyzed and compared with different structural parameters of the buildings.     

Vulnerability Assessment at Village Level Due to Tides,Surges and Wave Setup

An assessment of cyclone risk and vulnerability at the village level has evolved, which is an important component of the information system for local level development action plans for preparedness and mitigation. Here, a case study for the Nellore district along the east coast of India is considered. Using maximum probable surges along the coast, total water level (TWL) due to the combined effect of surge, tide, and wind wave is computed for the most vulnerable coastal villages of the Nellore district due to any tropical cyclones. The computations suggest that the TWL along the Nellore coast varies from 2 m in the south to 4 m in the north.     

Spatial interpolation using nonlinear mathematical programming models for estimation of missing precipitation records

Abstract

New mathematical programming models are proposed, developed and evaluated in this study for estimating missing precipitation data. These models use nonlinear and mixed integer nonlinear mathematical programming (MINLP) formulations with binary variables. They overcome the limitations associated with spatial interpolation methods relevant to the arbitrary selection of weighting parameters, the number of control points within a neighbourhood, and the size of the neighbourhood itself. The formulations are solved using genetic algorithms. Daily precipitation data obtained from 15 rain gauging stations in a temperate climatic region are used to test and derive conclusions about the efficacy of these methods. The developed methods are compared with some naïve approaches, multiple linear regression, nonlinear least-square optimization, kriging, and global and local trend surface and thin-plate spline models. The results suggest that the proposed new mathematical programming formulations are superior to those obtained from all the other spatial interpolation methods tested in this study.

Editor D. Koutsoyiannis; Associate editor S. Grimaldi

Citation Teegavarapu, R.S.V., 2012. Spatial interpolation using nonlinear mathematical programming models for estimation of missing precipitation records. Hydrological Sciences Journal, 57 (3), 383–406.     

Missing precipitation data estimation using optimal proximity metric-based imputation,nearest-neighbour classification and cluster-based interpolation methods

Abstract

New optimal proximity-based imputation, K-nearest neighbour (K-NN) classification and K-means clustering methods are proposed and developed for estimation of missing daily precipitation records. Mathematical programming formulations are developed to optimize the weighting, classification and clustering schemes used in these methods. Ten different binary and real-valued distance metrics are used as proximity measures. Two climatic regions, Kentucky and Florida, (temperate and tropical) in the USA, with different gauge density and network structure, are used as case studies to evaluate the new methods. A comprehensive exercise is undertaken to compare the performances of the new methods with those of several deterministic and stochastic spatial interpolation methods. The results from these comparisons indicate that the proposed methods performed better than existing methods. Use of optimal proximity metrics as weights, spatial clustering of observation sites and classification of precipitation data resulted in improvement of missing data estimates.

Editor D. Koutsoyiannis; Associate editor C. Onof     

Near real-time high-resolution airborne camera,AEROCam, for precision agriculture

Precision agriculture often relies on high-resolution imagery to delineate the variability within a field. Airborne Environmental Research Observational Camera (AEROCam) was designed to meet the needs of agriculture producers, ranchers, and researchers, who require high-resolution imagery in a near real-time environment for rapid decision support. AEROCam was developed and operated through a unique collaboration between several departments at the University of North Dakota, including the Upper Midwest Aerospace Consortium (UMAC), the School of Engineering and Mines, and flight operations at the John D. Odegard School of Aerospace Sciences. AEROCam consists of a Redlake MS4100 area-scan multi-spectral digital camera that features a 1920 × 1080 CCD array (7.4-μm detector) with 8-bit quantization. When operated at ～2 km above ground level, multispectral images with four bands in the visible and near infrared have a ground sample distance of 1 m with a horizontal extent of just over 1.6 km. Depending on the applications, flying at different altitudes can adjust the spatial resolution from 0.25 to 2 m. Rigorous spectral and radiometric calibrations allow AEROCam to be used in a variety of applications, qualitative and quantitative. Equipped with an inertial measurement unit (IMU) system, the images acquired can be geo-referenced automatically and delivered to end users near real time through our Digital Northern Great Plains system (DNGP). The images are also available to zone mapping application for precision farming (ZoneMAP), an online decision support tool for creating management zones from remote sensing imagery and data from other sources. Operational since 2004, AEROCam has flown over 250 sorties and delivered over 150,000 images to the users in the Northern Great Plains region, resulting in numerous applications in precision agriculture and resource management.