Spectral properties of shocked accretion flows— a self-consistent study     

Sandip K. Chakrabarti  Samir Mandal 《Astrophysics and Space Science》2007,309(1-4):163-166

Magnetized accretion flows around black holes which include standing or oscillating shock waves can produce very realistic spectrum till a few MeV. These shocks accelerate hot electrons which produce power-law spectrum. The post-shock region intercepts soft-photons from an external source, namely, a Keplerian disk and also from distributed sources such as the synchrotron photons emitted from thermal and non-thermal electrons originated in the pre-shock and post-shock flow. These photons are inverse Comptonized by the thermal and the non-thermal electrons present in the CENBOL region. Computations show that the emitted radiation is extended till a few MeV. We include the bulk motion Comptonization as well and discuss its importance vis-a-vis the power-law spectrum produced by non-thermal electrons.   相似文献   

Comments on ‘Temporal significant wave height estimation from wind speed by perceptron Kalman filtering’: by A. Altunkaynak and M. Ozger, Ocean Engineering, 31 (2004), 1245–1255     

S. Mandal   《Ocean Engineering》2007,34(8-9):1355-1356

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Viscous fluid cosmological models in the presence of the zero-mass scalar field     

A. R. Roy  Pijush K. Maiti 《Astrophysics and Space Science》1992,191(1):161-166

The curvature-free (k=0) FRW expanding cosmological model is developed corresponding to interacting viscous fluids and zero-mass scalar fields. In the absence of non-static scalar fields the model exhibits the existence of the initial singularity (Q=0). However, with non-negative coefficient of shear viscosity, in the presence of non-static scalar fields we find thatQ has a minimum value (0). If this epoch is treated as the initial one, it may be said that the presence of scalar fields avoids the initial singularity. Other physical behaviour that the model exhibit has been discussed.  相似文献   

Ocean wave forecasting using recurrent neural networks     

S. Mandal  N. Prabaharan 《Ocean Engineering》2006,33(10):1401-1410

The tremendous increase in offshore operational activities demands improved wave forecasting techniques. With the knowledge of accurate wave conditions, it is possible to carry out the marine activities such as offshore drilling, naval operations, merchant vessel routing, nearshore construction, etc. more efficiently and safely. This paper describes an artificial neural network, namely recurrent neural network with rprop update algorithm and is applied for wave forecasting. Measured ocean waves off Marmugao, west coast of India are used for this study. Here, the recurrent neural network of 3, 6 and 12 hourly wave forecasting yields the correlation coefficients of 0.95, 0.90 and 0.87, respectively. This shows that the wave forecasting using recurrent neural network yields better results than the previous neural network application.  相似文献   

Rainfall-runoff simulations using the CARIWIG Simple Model for Advection of Storms and Hurricanes and HEC-HMS: Implications of Hurricane Ivan over the Jamaica Hope River watershed     

Arpita Mandal  Tannecia S. Stephenson  Alrick A. Brown  Jayaka D. Campbell  Michael A. Taylor  Theron L. Lumsden 《Natural Hazards》2016,83(3):1635-1659

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Skills of different mesoscale models over Indian region during monsoon season: Forecast errors     

Someshwar Das  Raghavendra Ashrit  Gopal Raman Iyengar  Saji Mohandas  M. Das Gupta  John P. George  E. N. Rajagopal  Surya Kanti Dutta 《Journal of Earth System Science》2008,117(5):603-620

Performance of four mesoscale models namely, the MM5, ETA, RSM and WRF, run at NCMRWF for short range weather forecasting has been examined during monsoon-2006. Evaluation is carried out based upon comparisons between observations and day-1 and day-3 forecasts of wind, temperature, specific humidity, geopotential height, rainfall, systematic errors, root mean square errors and specific events like the monsoon depressions.It is very difficult to address the question of which model performs best over the Indian region? An honest answer is ‘none’. Perhaps an ensemble approach would be the best. However, if we must make a final verdict, it can be stated that in general, (i) the WRF is able to produce best All India rainfall prediction compared to observations in the day-1 forecast and, the MM5 is able to produce best All India rainfall forecasts in day-3, but ETA and RSM are able to depict the best distribution of rainfall maxima along the west coast of India, (ii) the MM5 is able to produce least RMSE of wind and geopotential fields at most of the time, and (iii) the RSM is able to produce least errors in the day-1 forecasts of the tracks, while the ETA model produces least errors in the day-3 forecasts.  相似文献   

Optimal Underground Extraction of Coal at Shallow Cover Beneath Surface/Subsurface Objects: Indian Practices     

Rajendra Singh  P. K. Mandal  A. K. Singh  R. Kumar  A. Sinha 《Rock Mechanics and Rock Engineering》2008,41(3):421-444

Summary  Considering ground instability problems of underground coal mines at shallow covers, this paper reviews and describes problems of optimal extraction of coal stuck below surface/subsurface constraints at Indian coal fields. Importance of thickness and quality of inter-burden between the working horizon and surface/subsurface constraints is discussed from a ground movement point of view during optimisation of coal recovery by underground mining beneath the constraints. A CIMFR, formerly CMRI idea, known as Wide Stall Method, was found suitable to overcome the limitations of non-effective-width based optimisation of recovery of coal, trapped in pillars below surface/subsurface objects, at shallow cover. The involved rock mechanics concept and three successful field trials of the Wide Stall Method under three different geo-mining conditions of the country are also briefly given in this paper. Author’s address: Rajendra Singh, Central Institute of Mining and Fuel Research (CIMFR, formerly CMRI), Barwa Road, Dhanbad, 826001 Jharkhand, India  相似文献   

Theoretical Concept to Understand Plan and Design Smooth Blasting Pattern   总被引：1，自引：0，他引：1  

S. K. Mandal  M. M. Singh  S. Dasgupta 《Geotechnical and Geological Engineering》2008,26(4):399-416

Considering different mechanical cutting tools for excavation of rock, drilling and blasting is said to be inexpensive and at the same time most acceptable and compatible to any geo-excavation condition. Depending upon strength properties of in-situ rock mass, characteristics of joint pattern and required quality of blasting, control blasting techniques viz., pre-split and smooth blasting are commonly implemented to achieve an undamaged periphery rock-wall. To minimize magnitude of damage or overbreak, the paper emphasized that in-situ stresses and re-distribution of stresses during the process of excavation should be considered prior to selection of explosive parameters and implementation of any suitable blast pattern. Rock structure being not massive in nature, the paper firstly explains the influence of discontinuities and design parameters on smooth-wall blasting. Considering the empirical equations for estimation of stress wave’s magnitude and its attenuation characteristics through transmitting medium, the paper has put forward a mathematical model for smooth blasting pattern. The model firstly illustrates that rock burden for each hole should be sub-divided into thin micro strips/slabs to understand the characteristics of wave transmission through the medium and lastly with the help of beam theory of structural dynamics have put forward a mathematical model to analyze and design an effective smooth blasting pattern to achieve an undamaged periphery rock-wall.  相似文献   

Slope stability analysis: a support vector machine approach   总被引：5，自引：0，他引：5  

Pijush Samui 《Environmental Geology》2008,56(2):255-267

Artificial Neural Network (ANN) such as backpropagation learning algorithm has been successfully used in slope stability problem. However, generalization ability of conventional ANN has some limitations. For this reason, Support Vector Machine (SVM) which is firmly based on the theory of statistical learning has been used in slope stability problem. An interesting property of this approach is that it is an approximate implementation of a structural risk minimization (SRM) induction principle that aims at minimizing a bound on the generalization error of a model, rather than minimizing only the mean square error over the data set. In this study, SVM predicts the factor of safety that has been modeled as a regression problem and stability status that has been modeled as a classification problem. For factor of safety prediction, SVM model gives better result than previously published result of ANN model. In case of stability status, SVM gives an accuracy of 85.71%.  相似文献   

Climate change vulnerability to agrarian ecosystem of small Island: evidence from Sagar Island,India     

Mandal  S.  Satpati  L. N.  Choudhury  B. U.  Sadhu  S. 《Theoretical and Applied Climatology》2018,132(1-2):451-464

Theoretical and Applied Climatology - The present study assessed climate change vulnerability in agricultural sector of low-lying Sagar Island of Bay of Bengal. Vulnerability indices were estimated...  相似文献