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Machining superalloys through conventional methods is extremely difficult due to their inherent mechanical properties such as improved toughness, lower thermal conductivity, and strength-to-weight ...

In recent days the coating process of the different materials are very important to progress the mechanical properties and also increase the corrosion resistance. For this study aimed to carry out the coating process with Carbon nano tubes (CNT) coating on to the EN8 mild steel and development of mechanical strength. CNT coating with various factor levels are analyzed by the reflection of output values such as tensile and impact strength and also corrosion behavior. Chemical vapour deposition process is involved to coating of CNT on EN8 mild steel and the parameters of holding time with coating temperature are increased it turn to increase the material strength. Mechanical strength evaluation namely yield strength, tensile strength, impact strength and micro hardness of the coated specimens are tested effectively. Mechanical strength is raised by increasing of temperature of coating and holding time of the process. Increasing of both holding time as well as temperature of coating it will be reduced the corrosion rate of the samples.

The Friction stir welding (FSW) process is a strong state joining process and the joining temperature is lower than that utilized in the combination welding forms. In this manner, for different metal welding, FSW is considered to offer a few focal points over combination welding. This study deals with the present examination centers around the impacts on tensile strength due to material position and device rotational speed. Material AA2014 and AA7075 material alloy are chosen for the welding process. The welded aluminum compounds are of a thickness of 6.0 mm in utilizing a traditional processing machine. Three sets of joints were created by fluctuating device rotational velocities and by changing the fixed situation of the material on the progressing and withdrawing sides. The outcomes show that the greatest rigidity of 207 MPa was accomplished for Sample C when AA7075 aluminum amalgams were set on the propelling side at a rotational speed of 1000 rpm with consistent surface appearance and no inward deformity over the weld zone, while the most reduced elasticity of 160 MPa was obtained for sample A when AA7075 was put on the other side with serious passage deserts over the weld region adding to split spread. In this paper we will be analyzing the results using taguchi method.

Human factor is an inevitable element of safety-critical control room operations in nuclear power plants. Identifying human factors influencing operator error occurrence in such critical application is important to mitigate human errors. Conventional methods employed for human factor identification are often static, unable to deal with data and model uncertainty, and to consider independencies among failure modes. This study employs the integration of the soft computing technique, viz. fuzzy analytic hierarchy process (FAHP), into the human factors analysis and classifying system (HFACS) framework to identify the critical human factors that contribute to human errors in the nuclear control room application. Integration of FAHP improves the HFACS framework by providing an analytical foundation and group decision-making ability in order to ensure quantitative assessment of nuclear accidents. The proposed model has two phases. The first phase is study of 18 human performance-related events that occurred in Indian nuclear power plants, utilizing HFACS to analyze and determine the human and organizational factors (HOFs) responsible for such events. Existing HFACS can only be used to detect a wide range of human factors. The proposed model further explores the underlying causes of such a wide range of factors. The hierarchy of HOFs identified as adverse mental states and organizational process factors that contributed most failures causing accident in the first phase provides inputs for the critical human factor identification to the second phase, which is a quantitative analysis using FAHP. In the second phase, more than 40 adverse mental state and organizational process factors are identified from literature survey and ten subfactors are screened and selected by human reliability assessment and control room operation experts. The study was conducted by administering a questionnaire that is comprised of the screened factors. Data have been collected from 88 senior reactor operators in an operating nuclear power plant. The critical factors contributing to human errors identified from FAHP are attention, perception and memory under cognitive factor and decision making, training and communications under organizational factor. The study results reveal that the implementation of HFACS-based FAHP methodology enabled in determining intrinsic human factors that contribute to nuclear power plant control room operator performance.

Recently, several abnormal functioning identifiers in the plants and animals to demolish the agricultural production in the field of the agricultural department. Particularly, in the effect of bacteria, fungi, micro-organisms, and viruses are heavily affect the fruits and their leaf. To achieve fantabulous functioning in leaf disease identification is a vital role in the efficient plant’s disease management and its demonstration to the continuous monitoring of bacteria, fungi and micro-organisms viruses persists a vital work that is undertaken or attempted by the agricultural department. To point out the leaf disease in an efficient manner, this article proposed an Advanced Segmented Dimension Extraction (ASDE) with Heterogeneous Internet of things procedural (HIoT) aspects. IoT procedural aspects identified as a repetitive and persistent space in the leaf image. This is also used to find the impact gesture of a leaf image, that insignificant to the identification time to a feasible extent. This paper suggests a Signs based plant disease identification for real-time resembling of leaf diseases namely bacteria, fungi, micro-organisms, and viruses. Diagnosis and Isolation techniques are maintained by Signs based plant disease identification, namely heterogeneous IoT detection. The relying on experiment show that the aimed framework distinguishes a detection of doing plant disease identification successfully accomplishing of 97.35% with a high-detection quotient. In addition to this proposed paper shows the relevance of algorithms for automatic recognition of fine-tuned disease nodes in the isolated leaf image. On the automatic recognition carried out by parsing, localization, normalization and segmentation procedures.

In the present era, rapid transits are one of the most affordable means of public transport with various useful integrated application systems. The majority of the integrated applications are deployed in concern over safety and precautionary measures against the worst side-effects of unfortunate emergencies. For such cases, high-end reliable and autonomous systems provide possible positive solutions. Wireless Sensor Network is one of the suitable choices for rapid transit applications to gain positive results with inexpensive implementation cost. However, managing few network consequences like fault tolerance, energy balancing and routing critical informative packets are considered to be the challenging task due to their limited resource usage restriction. In this paper, a novel fuzzy logic-based fault tolerance and instant synchronized routing technique have been proposed specifically for the rapid transit system. On utilizing the fuzzy logic concepts, most of the computational complexities and uncertainties of the system is reduced. The central thematic of the proposed design is concerned over the synchronized routing and permanent faults which abruptly depicts the non-functional nature of the sensor nodes during normal operations. Moreover, our proposed simulation outcomes proved to be improvised evidence on obtaining maximum packet delivery ratio which tends to handle an emergency situation in the compartments of rapid transits.

File storing as well as retrieving is the most important security-related research area in cloud. Based on our literature survey, many researchers have developed several searchable encryption protocols. Among the several protocols, only minimum number of protocols satisfies the efficient file retrieval from the cloud. Previous research papers support the file encryption based on the keyword, secret key and random number. But in this research paper, we have proposed attribute-based encryption based on the hierarchical manner. The collections of files are encrypted under one common access layer. Compared to earlier researches, our attribute-based hierarchical file encryption scheme supports very less computation as well as storage complexity. We have constructed a new index model named data vector (DV) tree using crossover genetic algorithm which is a component of the soft computing. The DV tree is built based on the term frequency, inverse document frequency and attributes of the file. We have also developed a new key generation, encryption and decryption function for efficient retrieval of files towards the data users.

This work inspects the effect of methanol inclusion to palm oil Biodiesel (P100) in a diesel engine to view its effect on emission parameters. Three fuel samples were prepared with different concen...

This work examines the impact of butanol addition to Mahua oil Biodiesel (MOBD) in a diesel engine to view its effect on emission characteristics. Two fuel samples were prepared using a novel surfa...

The thermoeconomic analysis comprises three major divisions, namely the estimation of exergy of all internal and external streams of VAR system, the estimation of investment and fuel cost a...

In the recent decades, rapid transit system (RTS) plays a significant key role to form most affordable and comfort travel zone to humans. With increase in population and usage of RTS, safety measures are concerned to be most notable factor in the world. Moreover, during emergency cases internal wired safety setups of any RTS does not prevents drastic disaster and allows negative impact for on-demand reliable changes. As an alternative to other expensive technologies, wireless sensor network (WSN) system provides fast communicative and compact applications to RTS. Inorder to reduce causalities, designing such a network application to RTS always poses challenging problems in terms of fault tolerance and time bounded packet delivery. Integrated fuzzy-logic based synchronized data transmission (IFSDT) algorithm has been designed to optimize those challenges, especially in RTS. IFSDT is a synchronized energy aware algorithm that prevents the occurrence of potential faults during unexpected emergencies in the coaches of RTS and ensures the fast transmission of critical broadcast signal and response in a limited time span. Furthermore, the results of the proposed design performs better than the existing reliable and energy optimized WSN design and exhibits the optimized response time for broadcasting emergency signals which is below 0.02 s.

Human errors contribute a significant portion of risk in safety critical applications and methods for estimation of human error probability have been a topic of research for over a decade. The scarce data available on human errors and large uncertainty involved in the prediction of human error probabilities make the task difficult. This paper presents a Bayesian belief network (BBN) model for human error probability estimation in safety critical functions of a nuclear power plant. BBN is a powerful tool and has been widely used for risk and reliability analysis framework under the conditions of uncertainty. BBNs are joint probability distribution between multiple variables (i.e., performance shaping factors, error modes, error mechanisms, etc.) expressed as directed acyclic graphs consisting of nodes and arcs. Nodes represent system components, and arc represents relationship among them with conditional probability tables. This network functions as an engine for calculation of probability of events given the observation of other events in the same network. BBN can be used to model the uncertainty parameters in a system. Sensitivity analysis can also be performed to study how uncertainty in the model output can be attributed to different sources of uncertainty in the model input. It is frequently applied in real-world situations such as diagnosis, forecasting, and environment, but received less attention in the area of human reliability. In view of its natural architecture, BBN is found to be more appropriate when there is scarce, multi-source data available as in the case of human error data. Further, the probabilistic approach of BBN is best suited for safety assessment to predict system reliability and estimate the probability of consequence of an event. BBN has been adapted to model human factors by taking into account the different parameters and their mutual influences. BBN can also be used to identify the potential human factors leading to significant reduction of accident probability during the operation of NPP. Several researchers have developed advanced HRA models to estimate the error probability but most of the HRA model requires expert judgment at several stages and hence it is subjective. Other models such as HCR and CREAM are not applicable for all scenarios. Limited studies are carried out to eliminate the need of human expert in the human reliability methods. This paper introduces a method that uses the available historical data and provides efficient technique for automated evaluation of human error probability using BBN. In this respect, human cognitive reliability (HCR) has been identified as a suitable model to estimate the mean time required for human intervention and in the selection of human action to estimate HEP in the model. The developed model using BBN would help to estimate HEP with limited human intervention. A step-by-step illustration of the application of the method and subsequent evaluation is provided with a relevant case study and the model is expected to provide useful insights into risk assessment studies.

Joining of ceramics to metals provide timeless challenges in nuclear engineering industries. There is a pressing need for developing a suitable technique for joining silicon carbide (absorber) to copper radio frequency structures in Compact Linear Collider. Transient liquid phase bonding is a promising candidate that could be employed for joining of dissimilar materials with high re-melt temperature. In the present work, experiments were carried out on Transient Liquid phase bonding of silicon carbide and copper using metal interlayer. Lead, which has high wettability, is selected as an interlayer in the Transient Liquid Phase (TLP) bonding process. Experimental results of mechanical testing reveal the strength of the SiC/Cu joints and its integrity. Since, the bonding temperature is the most important parameter to achieve sound joint with good mechanical properties, its influence is studied through experimental trials. From the experimental studies, it is found that the bonding temperature should be 230 °C to obtain the good quality SiC/Copper joints.Favorable temperature distribution is achieved at this bonding temperature and consequently, the joining efficiency of SiC/Copper joints is increased..

We study the generation of single photon perfect W-state. An important aspect of this perfect W-state is that, it can be used for perfect teleportation and superdense coding, which are not achievable with maximally entangled W-state. Our scheme for generation involves entanglement between various path degrees of freedom of a single photon in a compact and weakly coupled integrated waveguide system, which can be fabricated precisely with femtosecond laser direct writing technique. These platforms are interferometrically stable, scalable, less sensitive to decoherence and ensures a very low loss factor of 0.1dB/cm during photon propagation and hence are ideal for generation of perfect W-state. In addition to generation of single photon perfect W-state we study its non local properties using theory of local elements of reality., Comment: 7 pages, 6 figures, Comments are welcome

The high quality and resolution of the time-frequency representation of Bio signals is one of the important area to depict geological structures which are used to reveal the valuable information hidden in them. In this paper, we proposed time-frequency analysis of Bio signal EMG using the empirical wavelet transform (EWT) which is a new approach for analyzing multichannel Bio signals. Comparative results of the EWT, STFT (short time Fourier transform) and CWT (continuous wavelet transform) were analyzed in MATLAB. Overall comparison of the results based on EMT with those obtained from STFT and CWT signals, revealed that PSNR values has been reasonably increased for EWT. In addition, it was observed that presence of EWT-based instantaneous frequency spectra can produce much sparser representation and much higher time frequency resolution than the traditional CWT approach. This emphasizes the feature of empirical wavelet transform.

Adsorption cooling system can be classified into two main types, namely, intermittent adsorption system and continuous adsorption system. In this paper, attention has been focussed on the intermitt...

There are several million species of plants in the world, of which most of the species are not yet identified and recognized.Many species look similar, but they are actually not genetically the same, may belong to different families. It is very important to identify the plant species. Often taxonomist finds it difficult to classify the plants and sometimes may go wrong while grouping them. The key focus of this paper is to identify the variety of species by classifying the plant's leaves. This paper takes leaf image features to classify the species by using Support Vector Machines (SVM). This classification helps to recognize and identify the population of endangered and extint species for preservation.

In this paper, an electromagnetic metamaterial patch antenna is designed and simulated for cognitive radio applications, as cognitive radio communication is anticipated to be a new technology which utilizes all the bands of radio spectrum. This work uses a complementary split ring resonator between the patch and the ground plane for the purpose of size miniaturization. The proposed antenna system is capable of operating in the frequency range of about 2 to 5 GHz. This wide-band design makes it viable for wide spectrum with 80 percentage effective frequency being covered in the designed band. The desired patch antenna has been simulated using Advanced System Design (ADS) simulator. The simulated results are proved to be good in agreement with cognitive radio application.

The secured data transmission is an important application in MANET networks. A primary requirement for the data communication among the nodes security is must. In this, securing the data from malicious nodes that are series threats. In this security is not much enhanced against the jellyfish attacks and also routing protocol does not provide better data transmission with presence of duplicate nodes. So, in this paper we introduce the Ant Colony Optimization based Clustered Base Routing Protocols. This approach, the nodes are clustered using ant code optimization based approach while routing is performed based on the value of nodes. From the value, attacks are determined using the trust table. From the trust table we can calculate the MANET nodes. The data transmission can be secure to introduce the Secured Key Management. The data transmission performance evaluated using Network Simulation-2. The packet delivery ratio, lifetime and overhead show a better performance by using ACO-CBRP approaches.

In Aviation sector, fatigue life and its analysis of each component is one of the prime factors of consideration due to the catastrophic failures that can result from it. Most of the components fail in high cycle fatigue regimes, but the compressor's fatigue life is intermediate between high cycle fatigue and low cycle fatigue. Objective of this paper is to estimate and compare the suitability of a centrifugal compressor in a gas turbine engine with different materials are Titanium alloy 685, Aluminium alloy 2618 and Carpenter Invar 36 alloy by calculating the displacement and fatigue life using analytical method. The reference component of this paper is modeled by using CATIA and simulation is carried through ANSYS with the property of Aluminium alloy 2618, for the purpose of validating the simulation and analytical results.

LaAlO$_{3}$/SrTiO$_{3}$ heterostructure with polar and non-polar constituents has been shown to exhibit interface metallic conductivity due to fractional charge transfer to the interface. The interface reconstruction by electron redistribution along (001) orientation, in which half of an electron is transferred per two dimensional unit cell to the adjacent planes, resulting in a net transfer of half of the charge, to both the interface and top most atomic planes, has been ascribed to a polar discontinuity at the interface in the Polar Catastrophe model. This avoids the divergence of electrostatic potential, as the number of layers are increased, producing an oscillatory electric field and finite potential. Akin to the description of charge fractionalization in quasi one-dimensional polyacetylene by the field theoretic Jackiw-Rebbi model with fermions interacting with topologically non-trivial background field, we show an analogous connection between polar catastrophe model and Bell-Rajaraman model, where the charge fractionalization occurs in the soliton free sector as an end effect., Comment: 4 pages, 3 figures