Prediction and optimization of unsteady forced convection around a rounded cornered square cylinder in the range of Re

An unsteady two-dimensional laminar forced convection heat transfer around a square cylinder with the rounded corner edge is numerically investigated for Re = 80–180 and non-dimensional corner radius, r = 0.50–0.71 at Pr = 0.71 (Air). A structured non-uniform mesh is used for the computational domain discretization, and the finite-volume-method-based commercial code FLUENT is used for numerical simulation. The heat transfer characteristics over the rounded corner square cylinder are analyzed with average Nusselt number (Nu _avg) at various Re and various corner radii. The heat transfer characteristic is predicted by gene expression programming (GEP), and the GEP-generated explicit equation of Nu _avg is utilized in particle swarm optimization to optimize the corner radii for maximum heat transfer rate. The data required for the training the GEP model have been collected from the authors’ recent published article (Neural Comput Appl, 2015. doi:10.1007/s00521-015-2023-8). It is found that the heat transfer rate of a circular cylinder can be enhanced 12 % by introducing a new cylinder geometry of corner radius r = 0.51.

     

Morphological Changes During Annealing of Electrodeposited Ni-Cr Coating on Steel and Their Effect on Corrosion in 3% of NaCl Solution

 Steel containing carbon of 02% was coated with Ni and Cr through electrodeposition, and subsequently annealed at 400 and 600 ℃ for 5 min, 30 min, 1 h and 2 h. During annealing at 400 ℃, the formation and growth of oxides occurred in the form of petals along with voids, cracks and porosities. However, at 600 ℃, the nucleation and growth of chromium oxide whiskers produced a surface almost free from crack, porosity and void for 1 h and 2 h of holding. In accordance with the surface morphology, the bare steel, as-deposited steel, all specimens deposited and annealed at 400 ℃, and specimens deposited and annealed at 600 ℃ for 5 and 30 min exhibited continuous corrosion in 3% of NaCl solution. However, the specimens deposited and annealed at 600 ℃ for 1 and 2 h exhibited an improved corrosion resistance in 3% of NaCl solution with high pitting potential due to presence of a dense passive oxide film almost free from voids at the surface.     

Aflatoxin contamination in mustard (Brassica juncea) in relation to agronomic practices

Aflatoxin contamination in two varieties of mustard (Brassica juncea L), Varuna and BR-40, sown on three planting dates (1, 15 and 30 November) under two different cropping patterns, viz monocropping and mixed cropping (along with the UP-262 variety of wheat), was examined in rabi (winter) crops of 1987–1988 and 1988–1989. Analysis of variance showed a significant effect of planting date and cropping pattern as well as a combined effect of planting date × cropping pattern. Delayed planting (30 November) resulted in a very high level of aflatoxin contamination. The level of aflatoxin was low when mustard was cultivated along with wheat (mixed cropping). Varuna was more susceptible to aflatoxin than BR-40. The maximum number of fungi was recorded in mixed cropping samples.     

Effect of Fe and Cr Addition on the Sintering Behavior of ZrB2 Produced by Self-Propagating High-Temperature Synthesis

An investigation of the sintering behavior of ZrB₂ powder with Fe and Cr (0 to 20 wt%) addition was conducted. It was observed that Fe addition helps to enhance the density of ZrB₂ only up to 10 wt%. Further addition of Fe degrades the sintering by segregation of Fe-rich phases. Formation of a eutectic phase containing a Fe:Zr ratio of 92.57:7.43 was also found in Fe-added samples. The addition of Cr to a ZrB₂ matrix was found to result in swelling of the samples, leading to several cracks.     

Abrasive wear behavior of thermally sprayed diamond reinforced composite coating deposited with both oxy-acetylene and HVOF techniques

Diamond and diamond-based coatings have long been studied for their exceptional properties. Although a great deal of research has been carried out in this field, little is known about their tribological wear behavior. In the present work, diamond reinforced composite (DRC) coatings of varying diamond content was deposited on mild steel substrates using both oxy-acetylene (OA) and high velocity oxy fuel (HVOF) thermal spraying techniques. The high stress abrasive wear behavior of these coatings is studied by performing two body abrasion tests for varying experimental parameters. It is observed that the HVOF-sprayed coatings suffered abrasion at a relatively low wear rate. The reasons for variations observed in the wear rate as a function of displacement during abrasion and grit size could be attributed to the deterioration of abrasive particles and the particle size effect respectively. While the disparity in the wear rates with respect to composition of the coatings was primarily controlled by the diamond content in the coating. The abrasive wear mechanism was found to be the same in both the coatings except that the coating deposited by HVOF spray technique, offered better abrasion resistance and therefore abraded at a slower rate. This is possibly due to lower porosity in the coating and higher bond strength between reinforced diamond particulates and the bronze matrix in HVOF-sprayed specimens.     

Self-stabilizing multi-token rings

Summary A distributed system consists of a set of loosely connected machines that do not share a global memory. The system isself-stabilizing if it can be started in any global state and achieves consistency all by itself. This also means that the system can deal withinfrequent errors. This paper presents self-stabilizing multi-token rings. A multitoken ring is a generalization of a (one-)token ring. The algorithms presented are generalizations of a self-stabilizing mutual exclusion algorithm by Dijkstra [5] which can also be viewed as a token ring. We develop the algorithms in a stepwise manner, to show how and why we arrived at the final multi-token rings. The final parameterized algorithm represents a set of algorithms, one for each choice of the parameter. This enables one to select the algorithm with an optimal trade-off in desired flexibility versus memory requirements and stabilization time. Mitchell Flatebo received the B.S. degree in Mathematics (1990), the B.S. degree in Computer Science (1990), the M.S. degree in Mathematics (1992), and the M.S. degree in Computer Science (1993) from the University of Nevada, Las Vegas. He is currently a software engineer for Loral Space and Range Systems. His research interests include distributed systems, fault-tolerant computing, and self-stabilization. Ajoy Kumar Datta received the Ph.D. degree in Computer Science from the Jadavpur University, Calcutta, India in 1983. He is currently an Associate Professor of Computer Science at the University of Nevada, Las Vegas. His area of research is distributed and fault-tolerant computing —algorithms and self-stabilization. Anneke Schoone received an M.Sc. degree in Biology in 1978, an M.Sc. degree in Mathematics in 1981, and a Ph.D. degree in Computer Science in 1991 from Utrecht University (The Netherlands). Currently she is a senior research associate at the Department of Computer Science of Utrecht University, supported by ESPRIT Basic Research Action No. 7141 (project ALCOM II:Algorithms and Complexity) of the EC. Her research interests include assertional verification of distributed algorithms and the concept of self-stabilization.The research of this author was supported partially by the ESPRIT Basic Research Action No. 7141 (project ALCOM II:Algorithms and Complexity), and partially by the Netherlands Organization for Scientific Research (NWO) under contract NF 62-376 (NFI project ALADDIN:Algorithmic Aspects of Parallel and Distributed Systems)     

Synthetic D(-)penicillamine in rheumatoid arthritis. Double-blind controlled study of a high and low dosage regimen

Doses of 600 mg and 1200 mg of D(-)penicillamine daily were superior to a standard regimen of therapy in rheumatoid arthritis. The higher dose did not produce significantly greater therapeutic benefit in the group of patients so treated, although individual patients sometimes improved more. The frequency of rashes, blood dyscrasias, and withdrawals from the trial increased withe dosage. It is concluded that D(-)penicillamine is a useful treatment that the daily dose should be as low as possible, and that it should be increased at infrequent intervals only, with due regard to the likelihood of further improvement in relation to an increased risk of adverse reactions.     

Performance of quantum cloning and deleting machines over coherence

Coherence, being at the heart of interference phenomena, is found to be an useful resource in quantum information theory. Here we want to understand quantum coherence under the combination of two fundamentally dual processes, viz., cloning and deleting. We found the role of quantum cloning and deletion machines with the consumption and generation of quantum coherence. We establish cloning as a cohering process and deletion as a decohering process. Fidelity of the process will be shown to have connection with coherence generation and consumption of the processes.     

A two-stage mechanism for registration and classification of ECG using Gaussian mixture model

An automatic classifier for electrocardiogram (ECG) based cardiac abnormality detection using Gaussian mixture model (GMM) is presented here. In first stage, pre-processing that includes re-sampling, QRS detection, linear prediction (LP) model estimation, residual error signal computation and principal component analysis (PCA) has been used for registration of linearly independent ECG features. GMM is here used for classification based on the registered features in a two-class pattern classification problem using 730 ECG segments from MIT-BIH Arrhythmia and European ST-T Ischemia datasets. A set of 12 features explaining 99.7% of the data variability is obtained using PCA from residual error signals for GMM based classification. Sixty percent of the data is used for training the classifier and 40% for validating. It is observed that the overall accuracy of the proposed strategy is 94.29%. As an advantage, it is also verified that Chernoff bound and Bhattacharya bounds lead to minimum error for GMM based classifier. In addition, a comparative study is done with the standard classification techniques with respect to its overall accuracy.