Meshfree method for fluctuating hydrodynamics

In the current study a meshfree Lagrangian particle method for the Landau–Lifshitz Navier–Stokes (LLNS) equations is developed. The LLNS equations incorporate thermal fluctuation into macroscopic hydrodynamics by the addition of white noise fluxes whose magnitudes are set by a fluctuation–dissipation theorem. The study focuses on capturing the correct variance and correlations computed at equilibrium flows, which are compared with available theoretical values. Moreover, a numerical test for the random walk of standing shock wave has been considered for capturing the shock location.     

Application of variational methods to a rectangular clamped plate problem

The present paper deals with the variational approach for solving a clamped rectangular plate under a uniform load. The increasing use of composite materials for plate-type structures intensified the need for solutions of rectangular plates. The variational approach has a broad range of applications in solid mechanics. The methods used to solve the problem consider the minimum total potential energy approach. The maximum deflection is obtained for a square plate by the Ritz, Galerkin and Kantorovich methods. The aim of this paper is to find an approximate solution of higher accuracy. Numerical results for various components of stresses are found and plotted in the form of curves. The results obtained by various methods are compared with those reported earlier. The results show reasonable agreement with the known results, but with a simple and practical approach. The physical aspect of the concept is the immediate use of these results in solid and structural mechanics.     

A framework for joint community detection across multiple related networks

Community detection in networks is an active area of research with many practical applications. However, most of the early work in this area has focused on partitioning a single network or a bipartite graph into clusters/communities. With the rapid proliferation of online social media, it has become increasingly common for web users to have noticeable presence across multiple web sites. This raises the question whether it is possible to combine information from several networks to improve community detection. In this paper, we present a framework that identifies communities simultaneously across different networks and learns the correspondences between them. The framework is applicable to networks generated from multiple web sites as well as to those derived from heterogeneous nodes of the same web site. It also allows the incorporation of prior information about the potential relationships between the communities in different networks. Extensive experiments have been performed on both synthetic and real-life data sets to evaluate the effectiveness of our framework. Our results show superior performance of simultaneous community detection over three alternative methods, including normalized cut and matrix factorization on a single network or a bipartite graph.     

Co-evolutionary immuno-particle swarm optimization with penetrated hyper-mutation for distributed inventory replenishment

This article is betrothed to serve as a continuation of the emerging swarm techniques to solve supply chain problems. Our aim is to map some of the pressing research challenges contributed by the artificial intelligence community and to develop an improved algorithm: Co-evolutionary immuno-particle swarm optimisation with penetrated hyper-mutation (COIPSO-PHM). In this paper, we proposed a new algorithm which uses clonal selection approach in particle swarm optimisation by embedding co-evolutionary theory to solve the problem of inventory replenishment in distributed plant–warehouse–retailer system. Constraint handling is explicitly taken care by implanting augmented lagrangian concept. To demonstrate the efficiency of the algorithm, its performance are evaluated and compared on 10 benchmarked problems (made constrained problem via random initialisation in the infeasible zone) including functions with uni-modalities as well as multi-modalities. The result follows shows superior performance of the algorithm in every respect.     

Evaluation of hot corrosion resistance of HVOF coatings on a Ni-based superalloy in molten salt environment

High-velocity oxy-fuel (HVOF) has the advantage of being a continuous and most convenient process for applying coatings to industrial installations at site. In this study, Cr₃C₂–NiCr, NiCrBSi, Stellite-6 and Ni–20Cr coatings were deposited on a Ni-based superalloy (19.5Cr–3Fe–0.3Ti–0.1C–balance Ni) using an HVOF process. Hot corrosion studies were performed on bare as well as coated superalloy specimens after exposure to a molten salt environment at 900 °C under cyclic conditions. The thermogravimetric technique was used to establish the kinetics of corrosion. XRD, SEM/EDAX and EPMA techniques were used to analyse the corrosion products. The hot corrosion resistance of all the coatings were superior to bare superalloy. Among the coatings studied, the Ni–20Cr coated superalloy imparted maximum hot corrosion resistance, whereas the Stellite-6 coated indicated minimum resistance. The hot corrosion resistance of all coatings may be attributed to the formation of oxides and spinels of nickel, chromium or cobalt.     

A study on fitness-for-service assessment for crack-like defects and corrosion in nuclear reactor pressure tubes

This paper looks forward to thoroughly assess zirconium alloy (Zr-2) pressure tubes used in nuclear power reactors for crack like and corrosion type defects. It emphasizes on the use of reliability concept for determining the probability of failure of zirconium alloy pressure tubes based on deuterium ingress. The in depth analysis carried out to calculate the reliability index for the above two problems is based on FORM approach. A steady state corrosion rate is assumed to estimate the growth in the dimensions of corrosion defects. The methodology suggested in this paper is useful for designers and plant engineers in timely detection of the cracks and leaks in the pressure tubes used in nuclear reactors and initiate suitable corrective actions based on their criticality.     

Influence of Liquid Phase Additives on Structural and Sintering Behaviour of Samarium Modified Lead Titanate Ceramics

The combination of metal oxides Bi₂O₃:Li₂O in a ratio 89:11 gives a eutectic with a melting point of ～680°C. Such a low melting point oxide combination creates a working liquid phase at a highly favorable temperature for use as a densification aid. A liquid—phase sintering aid incorporating Bi₂O₃ and Li₂O is presented which demonstrates not only a reduction in the required sintering temperature but also shows relatively higher ‘c/a’ ratio (tetragonality) of PbTiO₃ ceramics with no fragility of the samples. Detailed dilatometric investigations have been performed in order to study the dominant shrinkage mechanism in the present system. Besides acting as a liquid phase fluxing agent, Bi₂O₃/Li₂O also behave as Curie shifter, which decreases Curie temperature in lead titanate system. The Curie temperature has also been verified from the thermal expansion behavior of sintered specimens. The value of dielectric constant increases after poling which may be due to the dominance of 180° domain wall over 90°.     

Designing communication strategies for heterogeneous parallel systems

This paper explores the suitability of the emerging passive star-coupled optical interconnection using wavelength division multiplexing as the system interconnect to provide high bandwidth (Gbits/sec) communication demanded by heterogeneous systems. Several different communication strategies (combinations of communication topologies and protocols) are investigated under a representative master-slave computational model. The interplay between system speed, network speed, task granularity, and degree of parallelism is studied using both analytical modeling and simulations. It is shown that a hierarchical ALOHA-based communication strategy between the master and the slaves, implemented on top of the passive star-coupled network, leads to a considerable reduction in channel contention and provides 50–80% reduction in task completion time for applications with medium to high degrees of coarse grain parallelism. Comparable reduction in channel contention is also shown to be achieved by using tunable acoustooptic filters at master nodes.     

Parametric Feature Detection

Most visual features are parametric in nature, including, edges, lines, corners, and junctions. We propose an algorithm to automatically construct detectors for arbitrary parametric features. To maximize robustness we use realistic multi-parameter feature models and incorporate optical and sensing effects. Each feature is represented as a densely sampled parametric manifold in a low dimensional subspace of a Hilbert space. During detection, the vector of intensity values in a window about each pixel in the image is projected into the subspace. If the projection lies sufficiently close to the feature manifold, the feature is detected and the location of the closest manifold point yields the feature parameters. The concepts of parameter reduction by normalization, dimension reduction, pattern rejection, and heuristic search are all employed to achieve the required efficiency. Detectors have been constructed for five features, namely, step edge (five parameters), roof edge (five parameters), line (six parameters), corner (five parameters), and circular disc (six parameters). The results of detailed experiments are presented which demonstrate the robustness of feature detection and the accuracy of parameter estimation.     

Stereo and Specular Reflection

The problem of accurate depth estimation using stereo in the presence of specular reflection is addressed. Specular reflection, a fundamental and ubiquitous reflection mechanism, is viewpoint dependent and can cause large intensity differences at corresponding points, resulting in significant depth errors. We analyze the physics of specular reflection and the geometry of stereopsis which lead to a relationship between stereo vergence, surface roughness, and the likelihood of a correct match. Given a lower bound on surface roughness, an optimal binocular stereo configuration can be determined which maximizes precision in depth estimation despite specular reflection. However, surface roughness is difficult to estimate in unstructured environments. Therefore, trinocular configurations, independent of surface roughness are determined such that at each scene point visible to all sensors, at least one stereo pair can produce correct depth. We have developed a simple algorithm to reconstruct depth from the multiple stereo pairs.