Laser In-Situ Combinatorial Carbide Coating on Steel

The potential for synthesizing an in-situ grown ultra-fine carbide composite coating on the surface of steel during laser surface engineering was investigated. A 2.5 KW Nd:YAG laser was employed to modify the surface of a AISI 1010 steel deposited with a precursor powder mixture of Fe, Ti, Cr and C. With the help of laser surface engineering, carbide composite coating on the surface of plain C steel was achieved. It is envisioned that such a coating will offer superior tribological properties. Energy Dispersive Spectroscopy in supplement with X-ray Diffractometery indicated the evolution of TiC, Fe-Cr, and M7C3 as major phases in the coating. An oscillatory pattern for evolution of M7C3 was observed with respect to the laser power over the range of 900-2100 watts during processing. Although TiC was present in all the samples, the chromium carbides were absent in samples processed at certain laser powers. Corresponding to this behavior, variation in mechanical properties of the coating was observed. The hardness and wear properties of the samples without chromium carbides was inferior in comparison to samples with both TiC and chromium carbides. The roles of in-situ growth, refractory nature of the carbide particles, the non-equilibrium nature of the process and their contribution in successfully forming a composite coating have been described. Computational techniques were employed with the aim of studying possible reasons for phase evolution, stability of phases and solidification path and thus optimize parameters to tailor properties according to requirement. The temperature range of thermal transitions within the quaternary system (Fe, Ti, Cr and C) and the thermal stability of the evolved phases were studied with the help of differential scanning calorimetry (DSC). DSC studies indicated that the major exothermic reactions (formation of carbides) take place within 850-1150oC. Temperature ranges for individual reactions were investigated. The evolved phases (TiC, M7C3, Fe-Cr and Fe3C) were characterized using X-ray diffraction (XRD). This multicomponent powder mixture, which was used as a precursor for synthesizing a composite coating on the surface of steel via laser surface engineering (LSE), was computationally investigated for thermal stability. The intended wear applications of the coating made thermal stability investigations imperative, as there is a localized heat buildup during wear, because of the contact between rubbing surfaces. Experimental evaluation (DSC) of thermal stability of the phases formed was done to supplement the computational investigations. The degradation of the coating due to prolonged stay at elevated temperatures (in oxidizing environments such as air) could lead to degradation in the properties of the coating. High temperature oxidation studies were done to investigate the oxidation kinetics of the composite coating

Solving Target Coverage Problem in Wireless Sensor Network Using Genetic Algorithm

The past few years have seen tremendous increase of interest in the field of wireless sensor network. These wireless sensor network comprise numerous small sensor nodes distributed in an area and collect specific data from that area. The nodes comprising a network are mostly battery driven and hence have a limited amount of energy. The target coverage deals with the surveillance of the area under consideration taking into account the energy constraint associated with nodes. In nutshell, the lifetime of the network is to be maximized while ensuring that all the targets are monitored. The approach of segregating the nodes into various covers is used such that each cover can monitor all the targets while other nodes in remaining covers are in sleep state. The covers are scheduled to operate in turn thereby ensuring that the targets are monitored all the time and the lifetime of the network is also maximized. The segregation method is based on Maximum Set Cover (MSC) problem which is transformed into Maximum Disjoint Set Cover problem (MDSC). This problem of finding Maximum Disjoint Set Cover falls under the category of NP-Complete problem. Hence, two heuristics based approach are discussed in this work; first Greedy Heuristic is implemented to be used as baseline. Then a Genetic Algorithm based approach is proposed that can solve this problem by evolutionary global search technique. The existing and proposed algorithms are coded and functionality verified using MATLAB R2010b and performance evaluation and comparisons are made in terms of number of sensors and sensing range

Developing Model for Fuel Consumption Optimization in Aviation Industry

The contribution of aviation to society and economy is undisputedly significant. The aviation industry drives economic and social progress by contributing prominently to tourism, commerce and improved quality of life. Identifying the amount of fuel consumed by an aircraft while moving in both airspace and ground networks is critical to air transport economics. Aviation fuel is a major operating cost parameter of the aviation industry and at the same time it is prone to various constraints. This article aims to develop a model for fuel consumption of aviation product. The paper tailors the information for the fuel consumption optimization in terms of information development, information evaluation and information refinement. The information is evaluated and refined using statistical package R and Factor Analysis which is further validated with neural networking. The study explores three primary dimensions which are finally summarized into 23 influencing variables in contrast to 96 variables available in literature. The 23 variables explored in this study should be considered as highly influencing variables for fuel consumption which will contribute significantly towards fuel optimization. Keywords: Fuel Consumption, Civil Aviation Industry, Neural Networking, Optimizatio

Incentive Stackelberg Mean-payoff Games

We introduce and study incentive equilibria for multi-player meanpayoff games. Incentive equilibria generalise well-studied solution concepts such as Nash equilibria and leader equilibria (also known as Stackelberg equilibria). Recall that a strategy profile is a Nash equilibrium if no player can improve his payoff by changing his strategy unilaterally. In the setting of incentive and leader equilibria, there is a distinguished player called the leader who can assign strategies to all other players, referred to as her followers. A strategy profile is a leader strategy profile if no player, except for the leader, can improve his payoff by changing his strategy unilaterally, and a leader equilibrium is a leader strategy profile with a maximal return for the leader. In the proposed case of incentive equilibria, the leader can additionally influence the behaviour of her followers by transferring parts of her payoff to her followers. The ability to incentivise her followers provides the leader with more freedom in selecting strategy profiles, and we show that this can indeed improve the payoff for the leader in such games. The key fundamental result of the paper is the existence of incentive equilibria in mean-payoff games. We further show that the decision problem related to constructing incentive equilibria is NP-complete. On a positive note, we show that, when the number of players is fixed, the complexity of the problem falls in the same class as two-player mean-payoff games. We also present an implementation of the proposed algorithms, and discuss experimental results that demonstrate the feasibility of the analysis of medium sized games.Comment: 15 pages, references, appendix, 5 figure

A basic two-sector new Keynesian DSGE model of the Indian economy

Indian economy is going through underlying changes in post-pandemic recovery process. Effect of policies, monetary or fiscal, on macroeconomy needs a thorough analysis in these recessionary times. In this context, this study develops a closed-economy DSGE model to see the impact of monetary policy on the Indian economy. The model includes price rigidities, and parameters are calibrated using the data on the Indian economy. The model includes two sectors - production and consumption, and an inflation-targeting regime following the Taylor rule. The model is simulated for a positive productivity shock and an expansionary monetary policy shock. Results show that a positive productivity shock improves economic activity, and an expansionary monetary policy shock increases output for the short term only

Development of vacuum compatible, multi-mode operation light source

531-537Light sources are used extensively at various stages of development and characterization of an electro-optical (EO) payload like Cartosat, HySIS, Microsat etc. These sources are required to characterize many critical parameters of EO payload like photo response non uniformity (PRNU), noise performance, saturation radiance etc. Currently integrating sphere with quartz tungsten halogen (QTH) lamp is widely used for payload characterization. These lamp sources generally operate in continuous mode in clean room environment and thermo-vacuum. In case of high resolution payloads, time-delay and integration (TDI) detectors are used to improve signal collection. For characterization and testing of such payloads multi-mode (pulsed and continuous) light source (switching at kHz rate in synchronization with payload electronics) with specific spectral range is required. Pulse mode operation requirement cannot be met using QTH lamps. To cater to such need a LED based indigenous source has been developed. This paper delineates circuit design and implementation of driver and characteristics of the source is also discussed. Proposed source is capable to synchronize and operate in multi-mode with external clock pulse with high achieved linearity (>99%) and high stability (>99%) in vacuum condition

The Humoral Immune Response to Various Domains of Protective Antigen of Bacillus anthracis in Cutaneous Anthrax Cases in India

Anthrax, caused by Bacillus anthracis is known to occur globally since antiquity. Besides being an important biothreat agent, it is an important public health importance pathogen also in countries like India. B. anthracis secretes three distinct toxins, namely protective antigen (PA), lethal factor (LF) and edema factor (EF). PA is the central moiety of the anthrax toxin complex and therefore has been a molecule of choice for vaccine development. PA has four different domains with different functions. In this study, the major domains of PA were cloned and expressed in bacterial system. The purified recombinant proteins were used to determine the humoral immune response by ELISA using 43 human cutaneous anthrax serum samples. The maximum immunoreactivity was observed with the whole PA protein followed by domain 2, 4 and 1. The study corroborated that in addition to full PA, individual domain 2 and 4 can also be good target for vaccine development as well as for serodiagnostic assays for cutaneous anthra

Numerical Simulation and Assessment of Meta Heuristic Optimization Based Multi Objective Dynamic Job Shop Scheduling System

In today's world of manufacturing, cost reduction becomes one of the most important issues. A successful business needs to reduce its cost to be competitive. The programming of the machine is playing an important role in production planning and control as a tool to help manufacturers reduce their costs maximizing   the   use   of   their   resources.   The   programming problem is not only limited to the programming of the machine, but also covers many other areas such such as computer and information technology and communication. From the definition, programming is an art that involves allocating, planning the allocation and utilization of resources to achieve a goal. The aim of the program is complete tasks in a reasonable amount of time. This reasonableness is a performance measure of how well the resources   are   allocated   to   tasks.   Time   or   time-dependent functions are always it used as performance measures. The objectives of this research are to develop Intelligent Search Heuristic algorithms (ISHA) for equal and variable size sub lot for  m  machine  flow  shop  problems,  to  Implement  Particle Swarm Optimization algorithm (PSO) in matlab, to develop PSO based Optimization program for efficient job shop scheduling problem. The work also address solution to observe and verify results of PSO based Job Shop Scheduling with help of graft chart