Cylindrical Zakharov–Kuznestov equation for ion-acoustic waves with electrons featuring non-extensive distribution     

Uday Narayan Ghosh  Pankaj Kumar Mandal  Prasanta Chatterjee 《Astrophysics and Space Science》2014,349(2):765-771

Cylindrical Zakharov–Kuznestov equation for ion-acoustic waves comprising of ions and electrons featuring non-extensive distribution are derived from the fluid equations through reductive perturbation technique. System of first order ordinary differential equations is obtained from Zakharov–Kuznestov equation through dynamical system approach and ultimately it is solved using numerical method. It is found that the electron to positron ratio parameter and the non-extensive distributed parameter due to electron play crucial role on the solution.  相似文献   

Zakharov–Kuznestov–Burger Equation for Ion-Acoustic Waves in Cylindrical Geometry     

Pankaj Kumar Mandal  Uday Narayan Ghosh  Prasanta Chaterjee 《Earth, Moon, and Planets》2015,115(1-4):45-58

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Application of Artificial Intelligence to Maximum Dry Density and Unconfined Compressive Strength of Cement Stabilized Soil   总被引：2，自引：1，他引：1  

Sarat Kumar Das  Pijush Samui  Akshaya K. Sabat 《Geotechnical and Geological Engineering》2011,29(3):329-342

This paper describes two artificial intelligence techniques for prediction of maximum dry density (MDD) and unconfined compressive strength (UCS) of cement stabilized soil. The first technique uses various artificial neural network (ANN) models such as Bayesian regularization method (BRNN), Levenberg- Marquardt algorithm (LMNN) and differential evolution algorithm (DENN). The second technique uses the support vector machine (SVM) that is firmly based on the theory of statistical learning theory, uses regression technique by introducing ε-insensitive loss function has been adopted. The inputs of both models are liquid limit (LL), plasticity index (PI), clay fraction (CF)%, sand (S)%, gravel Gr (%), moisture content (MC) and cement content (Ce). The sensitivity analyses of the input parameters have been also done for both models. Based on different statistical criteria the SVM models are found to be better than ANN models for the prediction of MDD and UCS of cement stabilized soil.  相似文献   

Magneto-viscous fluid cosmological models in presence of zero-mass scalar field     

A. R. Roy  Pijush K. Maiti 《Astrophysics and Space Science》1993,205(2):277-282

A viscous fluid cosmological model in presence of magnetic field and zero-mass scalar fields is developed. The non-negativity condition of viscous fluid pressure prescribes a certain minimum value oft vis-a-vis of the scale factorQ(t) and at this epoch the model is found to be singularity free.  相似文献   

Least square support vector machine and relevance vector machine for evaluating seismic liquefaction potential using SPT   总被引：4，自引：1，他引：3  

Pijush Samui 《Natural Hazards》2011,59(2):811-822

The determination of liquefaction potential of soil is an imperative task in earthquake geotechnical engineering. The current research aims at proposing least square support vector machine (LSSVM) and relevance vector machine (RVM) as novel classification techniques for the determination of liquefaction potential of soil from actual standard penetration test (SPT) data. The LSSVM is a statistical learning method that has a self-contained basis of statistical learning theory and excellent learning performance. RVM is based on a Bayesian formulation. It can generalize well and provide inferences at low computational cost. Both models give probabilistic output. A comparative study has been also done between developed two models and artificial neural network model. The study shows that RVM is the best model for the prediction of liquefaction potential of soil is based on SPT data.  相似文献   

Seismogenesis of the uninterrupted occurrence of the aftershock activity in the 2001 Bhuj earthquake zone, Gujarat, India, during 2001�C2010     

Prantik Mandal 《Natural Hazards》2013,65(2):1063-1083

Seismogenesis of aftershocks occurring in the Kachchh seismic zone for more than last 10?years is investigated through modeling of fractal dimensions, b-value, seismic velocities, stress inversion, and Coulomb failure stresses, using aftershock data of the 2001 Bhuj earthquake. Three-dimensional mapping of b-values, fractal dimensions, and seismic velocities clearly delineate an area of high b-, D-, and Vp/Vs ratio values at 15?C35?km depth below the main rupture zone (MRZ) of the 2001 mainshock, which is attributed to higher material heterogeneities in the vicinity of the MRZ or deep fluid enrichment due to the release of aqueous fluid/volatile CO₂ from the eclogitisation of the olivine-rich lower crustal rocks. We notice that several aftershocks are occurred near the contacts between high (mafic brittle rocks) and low velocity regions while many of the aftershocks including the 2001 Bhuj mainshock are occurred in the zones of low velocity (low dVp, low dVs and large Vp/Vs) in the 15?C35?km depth range, which are inferred to be the fractured rock matrixes filled with aqueous fluid or volatiles containing CO₂. Further support for this model comes from the presence of hydrous eclogitic layer at sub-lithospheric depths (34?C42?km). The depth-wise stress inversions using the P- and T-axes data of the focal mechanisms reveal an increase in heterogeneity (i.e., misfit) with an almost N?CS ??₁ orientation up to 30?km depth. Then, the misfit decreases to a minimum value in the 30?C40?km depth range, where a 60^o rotation in the ??₁ orientation is also noticed that can be explained in terms of the fluid enrichment in that particular layer. The modeling of Coulomb failure stress changes (??CFS) considering three tectonic faults [i.e., NWF, GF, and Allah bund fault (ABF)] and the slip distribution of the 2001 mainshock on NWF could successfully explain the occurrences of moderate size events (during 2006?C2008) in terms of increase in positive ??CFS on GF and ABF. In a nutshell, we propose that the fluid-filled mafic intrusives are acting as stress accentuators below the Kachchh seismic zone, which generate crustal earthquakes while the uninterrupted occurrence of aftershocks is triggered by stress transfer and aqueous fluid or volatile CO₂ flow mechanisms. Further, our results on the 3-D crustal seismic velocity structure, focal mechanisms, and b-value mapping will form key inputs for understanding wave propagation and earthquake hazard-related risk associated with the Kachchh basin.  相似文献   

Estimation of Wheat/Rice Residue Burning Areas in Major Districts of Haryana,India, Using Remote Sensing Data     

Manoj Yadav  M. P. Sharma  R. Prawasi  Rajeev Khichi  Pavan Kumar  V. P. Mandal  Abdul Salim  R. S. Hooda 《Journal of the Indian Society of Remote Sensing》2014,42(2):343-352

Haryana has emerged as an important state for Rice & Wheat production in India contributing significantly in the central pool. Mechanized combine harvesting technologies, which have become common in Rice Wheat System (RWS) in India, leave behind large quantities of straw in the field for open burning of residue. Besides causing pollution, the burning kills the useful micro flora of the soil causing soil degradation. There is no field survey (Girdawari) data available with the Government for the areas where stubble burning is taking place. The present paper describes the methodology and results of wheat and rice residue burning areas for three districts of Haryana namely Kaithal, Kurukshetra and Karnal for the year 2010 using complete enumeration approach of multi-date IRS-P6 AWiFS and LISS-III data. In season ground truth was collected using hand held GPS and used to identify area of burnt wheat/rice residues, associated crops and land features. After geo-referencing the satellite images, district images were masked-out and multi-date image data stacks were created. Normalized Difference Vegetation Index (NDVI) of each date was generated and used at the time of classification along with other spectral bands. The non-agricultural classes in the image included: forest, wasteland, water bodies, urban/settlement and permanent vegetation etc. The vector of these non-agriculture classes were extracted from the land use, imported and mask was generated. During the classification non-agriculture area was excluded by using mask of these classes. From this the agricultural area could be separated out. The area was estimated by computing pixels under the classified image mask. In season multi-date AWiFS data along with available single-date LISS-III data between third week of April to last week of May are found to be useful for estimation of wheat residue burning areas estimation. The data between second week of October to last week of November is useful for estimation of rice residue burning areas estimation at district level.  相似文献   

Delineation and characterization of waterlogging and salt affected areas in a canal irrigated semiarid region of north west India     

A. K. Mandal  R. C. Sharma 《国际地球制图》2013,28(3):181-195

Indian Remote Sensing (IRS) Linear Imaging Self Scanning (LISS II) data are interpreted, followed by ground verification facilitated identification of waterlogged areas (ponded water), salt affected soils (salt efflorescence) and high water table zones (potential waterlogging zones) in the Indira Gandhi Nahar Pariyojona (IGNP) command area (India). The false colour composites (bands 4, 3, 2) for February 1996, November 1996 and June 1998 on 1:50 000 scale revealed occurrence and seasonal dynamics of permanent waterlogging in low-lying flats and depressions. The extent of waterlogging was higher in February 1996 due to less evaporation and more agricultural operation during the period. Salt accumulation was higher in November 1996 due to freshly precipitated seasonal salts. Seepage and accumulation of excess irrigation water through coarse sandy mass was primarily responsible for the development of waterlogging in the irrigated zone. The capillary rise of soluble salts with a rising water table and high evaporative demand caused secondary soil salinization. A ground truth study found areas with a high water table (<1.5 m) with patchy crop stands and a potentially sensitive zone with a fluctuating (1.5–6.0 m) water table with poor vegetative growth. The soil characteristics showed moderate to high soil salinity in the control section of soil profiles. These were characterized by medium to coarse texture, weak to moderately strong structure, weak consistency, low organic matter content and the presence of abundant CaCO₃ nodules. The composition of saturated soil paste showed a preponderance of chlorides and sulphates of sodium, calcium and magnesium. The presence of fine texture and calcium carbonate layers at a depth below the surface caused the development of a perched water table indicating unsuitability for traditional irrigated agriculture. The quality of pond water was extremely poor and unfit for reuse. The ground water was saline in some areas but normally lies within the prescribed limit. The quality of drainage water was poor in saline depressions and unsuitable for reuse but moderate in other areas suggesting its safe reuse when mixed with good quality water. Suitable soil and water management practices were necessary for sustainable crop production in the command area.  相似文献   

Application of statistical learning algorithms to ultimate bearing capacity of shallow foundation on cohesionless soil     

Pijush Samui 《国际地质力学数值与分析法杂志》2012,36(1):100-110

This study employs two statistical learning algorithms (Support Vector Machine (SVM) and Relevance Vector Machine (RVM)) for the determination of ultimate bearing capacity (q_u) of shallow foundation on cohesionless soil. SVM is firmly based on the theory of statistical learning, uses regression technique by introducing varepsilon‐insensitive loss function. RVM is based on a Bayesian formulation of a linear model with an appropriate prior that results in a sparse representation. It also gives variance of predicted data. The inputs of models are width of footing (B), depth of footing (D), footing geometry (L/B), unit weight of sand (γ) and angle of shearing resistance (?). Equations have been developed for the determination of q_u of shallow foundation on cohesionless soil based on the SVM and RVM models. Sensitivity analysis has also been carried out to determine the effect of each input parameter. This study shows that the developed SVM and RVM are robust models for the prediction of q_u of shallow foundation on cohesionless soil. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

Applicability of artificial intelligence to reservoir induced earthquakes     

Pijush Samui  Dookie Kim 《Acta Geophysica》2014,62(3):608-619

This paper proposes to use least square support vector machine (LSSVM) and relevance vector machine (RVM) for prediction of the magnitude (M) of induced earthquakes based on reservoir parameters. Comprehensive parameter (E) and maximum reservoir depth (H) are used as input variables of the LSSVM and RVM. The output of the LSSVM and RVM is M. Equations have been presented based on the developed LSSVM and RVM. The developed RVM also gives variance of the predicted M. A comparative study has been carried out between the developed LSSVM, RVM, artificial neural network (ANN), and linear regression models. Finally, the results demonstrate the effectiveness and efficiency of the LSSVM and RVM models.  相似文献