Ghanashyam Hemalata Institute of Technology and Management

Orissa, India

Ghanashyam Hemalata Institute of Technology and Management

Orissa, India
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Sahu L.,Ghanashyam Hemalata Institute of Technology and Management | Mishra A.K.,National Institute of Technology Rourkela | Dutta K.,National Institute of Technology Rourkela
Journal of Materials Engineering and Performance | Year: 2014

Ratcheting fatigue behavior of a non-conventional stainless steel X12CrMnNiN17-7-5 has been investigated with varying combinations of mean stress (σm) and stress amplitude (σa) at room temperature using a servo-hydraulic universal testing machine. X-ray diffraction profile analysis has been carried out for assessing possible martensitic phase transformation in the steel subjected to ratcheting deformation. The results indicate that ratcheting strain as well as volume fraction of martensite increases with increasing σm and/or σa; the phenomenon of strain accumulation is considered to be governed by the associated mechanics of cyclic loading, increased plastic damage as well as martensitic transformation. A correlation between strain produced by ratcheting deformation and martensitic transformation has been established. © 2014, ASM International.


Dutta K.,National Institute of Technology Rourkela | Kishor R.,National Institute of Technology Rourkela | Sahu L.,Ghanashyam Hemalata Institute of Technology and Management | Mondal A.K.,National Institute of Technology Rourkela
Materials Science and Engineering A | Year: 2016

Ratcheting (i.e., asymmetric stress-controlled fatigue) behavior of a non-conventional stainless steel X12CrMnNiN17-7-5 has been investigated with various combinations of stress amplitudes, mean stresses and number of cycles. XRD profile analysis following modified Williamson-Hall method has been carried out to estimate the dislocation characters and their respective densities in the ratcheted specimens. The precise role of these substructural features on the extent of strain produced during the course of ratcheting has been investigated. The increase in strain owing to ratcheting has been explained by the presence of type of dislocations and their respective densities in the constituent phases of the microstructure. The accumulation of cyclic plastic strain during ratcheting deformation is predominantly progressed by the presence of screw dislocations. The significantly increased fraction of edge dislocations in martensite phase resulted higher work hardening in the ratcheted specimens. Accordingly, the extent of strain produced is relatively less during subsequent ratcheting deformation. © 2016.


Tripathy S.C.,Ghanashyam Hemalata Institute of Technology and Management
International Journal of Energy, Environment and Economics | Year: 2011

We have learned that it is possible to supply a given load demand in an infinite number of operating configuration. It is necessary choose one particular configuration; i.e., the systems operator must specify exactly two variables per bus and, in addition, decide on appropriate tap settings on all regulating transformers. For a type 1 bus he must specify PG and QG, for a type 2 bus, PG and {pipe} V {pipe}, and for the slack bus, he must select {pipe} V {pipe}. On what basis are these specifications made? The simplest method is to use an "intelligent guess" Many systems are today operated on that basis. In this paper we discuss more sophisticated methods for selecting a "best" or "optimum" operating strategy. It must be remembered, however, that in the final analysis someone must make the decision as to what shall be understood by best or optimum in each particular instance. The choice of an optimum criterion is therefore always a subjective one. © 2011 Nova Science Publishers, Inc.


Tripathy S.C.,Ghanashyam Hemalata Institute of Technology and Management
International Journal of Energy, Environment and Economics | Year: 2013

Most dc transmission lines use a return path through the ground or seawater or both, either continuously or for short times of emergency. For brevity, such return paths are called ground returns even if the sea constitutes all or part of the path. The ground path has a very low resistance and correspondingly low power loss in comparison with a metallic line conductor of economical size and equal length if the ground electrodes are properly designed. The resistance is low because direct current in the earth in a steady state, unlike transient or alternating current, does not follow closely the route of the metallic conductor but spreads over a very large cross-sectional area in both depth and width. The resistance of this path is essentially independent of the length of the line and may be regarded merely as the sum of the resistances associated with each electrode unless the electrodes are near one another-which certainly would not be true in longdistance transmission. These resistances can be made low. © © Nova Science Publishers, Inc.


Tripathy S.C.,Ghanashyam Hemalata Institute of Technology and Management
International Journal of Energy, Environment and Economics | Year: 2014

There is a continuing tendency to apply many of the powerful results of modern control theory to various industrial processes. Power systems have been indicated as one area where significant progress can be expected. Practically all results of modern control theory require that models of the processes in terms of state equations are available. The need to obtain such models has been a strong motivation for research in the area of modelling and identification. Some progress made in this area is reviewed in this paper. Modelling based on physical equations and on plant experiments is discussed and compared. Particular emphasis is given to parameter estimation techniques like the maximum likelihood method which offer a possibility of combining physical a priori knowledge with experimental investigations. The formulation of identification problems is discussed, including the choice of criteria and model structures. The techniques are illustrated by applications to data obtained from measurements on various components of a power system. The examples include an electric generator, a nuclear reactor and a drum boiler, and serve to illustrate the potentials and limitations of system identification and modelling techniques when they are applied to real data. © Nova Science Publishers, Inc.


Tripathy S.C.,Ghanashyam Hemalata Institute of Technology and Management
International Journal of Energy, Environment and Economics | Year: 2013

These include transmission distribution, Frequency control, and voltage support, as well as generation. The first two deliver the power while the second two maintain power quality. Other services provide reliability. Each service requires a separate market, and some require several markets, this raises many questions about which service should be deregulated and which should not. Even with in a market for a single service, one side-either demand or supply-may need to be regulated to be while the other side of the market can be deregulated. For instance, the supply of transmission rights must be determined by the system operator, but the demand side of this market is competitive. In contrast, the demand for ancillary services is determined by the system operator while the supply sides of these markets can be competitive. The most critical service in a regulated or a deregulated power market is that provided by the system operator. This is a coordination service. For a deregulated market it typically includes operation of the real-time markets and a day-ahead market. These provide scheduling and balancing services, but operating these markets is itself an entirely separate service. While the need for the system operator service is agreed to by all, the proper extent of that service is the subject of the central controversy in power market design. © Nova Science Publishers, Inc.


Tripathy S.C.,Ghanashyam Hemalata Institute of Technology and Management
International Journal of Energy, Environment and Economics | Year: 2010

As noted earlier, the most fundamental task of energy analysis is to define alternative options - for energy pricing, for energy sector investments, and so on - and quantify their impacts on the objectives established for national energy planning. If, say, two policies are to be evaluated, there must also exist some explicit basis for comparing them, preferably on some ordinal scale of measurement. That is, we are interested not only in a ranking of alternatives, but in general one also wishes to know by exactly how much one alternative is better than another. This may well be an obvious point, yet it is particularly important where multiple objectives must be simultaneously evaluated: policy A may be better to policy B in terms of, say, some cost-minimization objective, but worse when evaluated on some environmental criterion. But if we know that B is only slightly less good in economic terms, that is an extremely important piece of additional information for the decision-maker who must ultimately make the trade-off between the two objectives. Examining solutions in the vicinity of the cost-minimizing optimum proves to be very important in such solutions, yet it is rarely done. © 2010 Nova Science Publishers, Inc.


Tripathy S.C.,Ghanashyam Hemalata Institute of Technology and Management
International Journal of Energy, Environment and Economics | Year: 2010

Estimates of future demands are a critical element of energy planning, at both the aggregate sectoral or national level and at the level of some specific fuel, such as electricity. Indeed, one of the most important reasons for making projection of future demand is the lead time required for the supply projects. Since a typical base load electric power plant takes between five and ten years to build, investment decisions must also be made with a five to ten years lead time. Similarly natural gas pipeline, LNG project, and other capital-intensive energy supply project invariably are predicated upon some estimate of future demand. © 2010 Nova Science Publishers, Inc.


Tripathy S.C.,Ghanashyam Hemalata Institute of Technology and Management
International Journal of Energy, Environment and Economics | Year: 2010

Stochastic load flow is a method for calculation of the effects of inaccuracies in input data on all output quantities through the load flow calculations. The method is based on the principles of statistical least squares estimation for linear systems. This gives a range of values for each output quantity to a high degree of probability. These ranges enclose the operating conditions of the system and are used in power system planning and operation. This information is essential for the continuous evaluation of the current performance of a power system and for analyzing the effectiveness of alternative plans for system expansion to meet increased load demand. These analysis require the repetitive calculations for both normal and emergency operating conditions. Thus on-line repetitive load flow should be periodically executed in the digital computer which monitors and controls the power system. Ideally it would be desirable to know the state of the power system, with consideration of input data inaccuracies on instant to instant basis. This is not possible with present technological level. However, we strive to minimize the time taken to get the state of power system. The work in the present chapter aims to achieve this objective through neural nets. © 2010 Nova Science Publishers, Inc.

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