A model on the basis of analytics for computing maximum heat transfer in porous fins

This study presents an analytical work on the performance and optimum design analysis of porous fin of various profiles operating in convection environment. Straight fins of four different profiles, namely, rectangular, convex parabolic and two exponential types are considered for the present investigation. An analytical technique based on the Adomian decomposition method is proposed for the solution methodology as the governing energy equations of porous fins for all the profiles are non-linear. A comparative study has been carried out among the results obtained from the porous and solid fins, and an appreciable difference has been noticed for a range of design conditions. Finally, the result shows that the heat transfer rate in an exponential profile with negative power factor is much higher than the rectangular profile but slightly higher than the convex profile. On the other hand, the fin performance is observed to be better for exponential profiles with positive power factor than other three profiles. A significant increase in heat transfer through porous fins occurs for any geometric fin compared to that of solid fins for a low porosity and high flow parameter.     

A hybrid neuro-fuzzy prediction system with butterfly optimization algorithm for PM2.5 forecasting

Microsystem Technologies - With the rapid increase of urbanization and industrialization, particulate matter (PM2.5) concentration has increased significantly. PM2.5 profile forecasting has become...     

Mapping the research landscape of Covid-19 from social sciences perspective: a bibliometric analysis

Scientometrics - COVID-19 has emerged as a widely researched topic and the academia has taken interest in the effects of COVID-19 in various sectors of human life and society. Most of the...     

An analytical prediction for performance and optimum design analysis of porous fins

Enhancement of heat transfer rate through porous fins is one of the common choices nowadays. As the energy equation is highly nonlinear, researchers never concentrated on analyzing porous fins analytically. In the present study, an effort has been devoted to develop an analytical model for determination of the performance and optimum dimensions of porous fins with consideration of different models of predictions. Every result has been presented in a comparative way so that the merit of the models adopting in the present work can easily be understood. The optimum design analysis of porous fins has also been carried out. The influences of all the dependent parameters on the performances and optimization conditions have been studied for the selection of a design criterion of porous fins in such applications where the requirement of heat dissipation is essentially high.     

Switching activity estimation of VLSI circuits using Bayesian networks

Switching activity estimation is an important aspect of power estimation at circuit level. Switching activity in a node is temporally correlated with its previous value and is spatially correlated with other nodes in the circuit. It is important to capture the effects of such correlations while estimating the switching activity of a circuit. In this paper, we propose a new switching probability model for combinational circuits that uses a logic-induced directed-acyclic graph (LIDAG) and prove that such a graph corresponds to a Bayesian network (BN), which is guaranteed to map all the dependencies inherent in the circuit. BNs can be used to effectively model complex conditional dependencies over a set of random variables. The BN inference schemes serve as a computational mechanism that transforms the LIDAG into a junction tree of cliques to allow for probability propagation by local message passing. The proposed approach is accurate and fast. Switching activity estimation of ISCAS and MCNC circuits with random and biased input streams yield high accuracy (average mean error=0.002) and low computational time (average elapsed time including CPU, memory access and I/O time for the benchmark circuits=3.93 s).     

Studies on the kinetics of catalytic combustion of deuterium using 0.5% platinum loaded on Dixon ring catalyst

When hydrogen isotopes are present in stoichiometric ratio of 2:1 with oxygen in inert gas such as helium, catalytic combustion is the most promising option to reduce the concentration of hydrogen isotopes and to minimize the associated safety hazards. This is the case, when deuterium and oxygen is formed during radiolysis of heavy water in moderator circuit of Pressurized Heavy Water Reactors (PHWR) and mixed with helium in the cover gas system. In order to design the catalytic reactor for recombination of deuterium and oxygen, the data on catalytic combustion kinetics under the similar process conditions are essential. However, the catalytic combustion data is generally reported for combustion of hydrogen in air, where oxygen is available in excess. The studies on the kinetics of catalytic combustion of deuterium where oxygen is present in stoichiometric ratio of 2:1 in an inert gas medium such as helium, is very scarce. In the present study, the multi-step reaction mechanism of catalytic combustion of hydrogen in presence of platinum catalyst is analyzed for the present process conditions. Based on the analysis, a simple rate expression is proposed for the present process conditions of catalytic combustion of deuterium. Further, 0.5% platinum catalyst is prepared on a stainless steel Dixon ring support with an objective to achieve better heat transfer characteristics and lesser reduction in the catalytic activity due to water adsorption. The kinetic data is generated using a differential packed bed reactor operating in a closed loop. The experiments were conducted at different temperatures using a stoichiometric mixture of deuterium and oxygen in helium. The rate constant for the above proposed model is estimated based on the experimental data at different temperatures. Further, the activation energy and frequency factor are determined and the activation energy for the present catalyst is found to be on the lower side in comparison to literature data.     

Cascade convolutional neural network-long short-term memory recurrent neural networks for automatic tonal and nontonal preclassification-based Indian language identification

This work presents an automatic tonal/nontonal preclassification-based Indian language identification (LID) system. Languages are firstly classified into tonal and nontonal categories, and then, individual languages are identified from the languages of the respective categories. This work proposes the use of pitch Chroma and formant features for this task, and also investigates how Mel-frequency Cepstral Coefficients (MFCCs) complement these features. It further explores block processing (BP), pitch synchronous analysis (PSA)- and glottal closure regions (GCRs)-based approaches for feature extraction, using syllables as basic units. Cascade convolutional neural network (CNN)-long short-term memory (LSTM) model using syllable-level features has been developed. National Institute of Technology Silchar language database (NITS-LD) and OGI-Multilingual Telephone Speech Corpus (OGI-MLTS) have been used for experimental validation. The proposed system based on the score combination of Cascade CNN-LSTM models of Chroma (extracted from BP method), first two formants and MFCCs (both extracted from GCR method) reports the highest accuracies. In the preclassification stage, the observed accuracies are 91%, 87.3%, and 85.1% for NITS-LD, for 30 s, 10 s, and 3 s test data respectively. For OGI-MLTS database, the respective accuracies are 86.7%, 83.1%, and 80.6%. That amounts to absolute improvements of 11.6%, 12.3%, and 13.9% for NITS-LD, and 12.5%, 11.9%, and 12.6% for OGI-MLTS database with respect to that of the baseline system. The proposed preclassification-based LID system shows improvements of 7.3%, 6.4%, and 7.4% for NITS-LD and 6.1%, 6.7%, and 7.2% for OGI-MLTS database over the baseline system for the three respective test data conditions.     

Influence of silica fume on the tensile strength of concrete

The present paper is directed towards developing a better understanding on the isolated contribution of silica fume on the tensile strengths of high-performance concrete (HPC). Extensive experimentation was carried out over water-binder ratios ranging from 0.26 to 0.42 and silica fume-binder ratios from 0.0 to 0.3. For all the mixes, compressive, flexural and split tensile strengths were determined at 28 days. The compressive, as well as the tensile, strengths increased with silica fume incorporation, and the results indicate that the optimum replacement percentage is not a constant one but depends on the water-cementitious material (w/cm) ratio of the mix. Compared with split tensile strengths, flexural strengths have exhibited greater improvements. Based on the test results, relationships between the 28-day flexural and split tensile strengths with the compressive strength of silica fume concrete have been developed using statistical methods.     

Investigations on the compressive strength of silica fume concrete using statistical methods

The present paper deals with a mathematical model developed using statistical methods to predict the 28-day compressive strength of silica fume concrete with water-to-cementitious material (w/cm) ratios ranging from 0.3 to 0.42 and silica fume replacement percentages from 5 to 30. Strength results of 26 concrete mixes, on more than 300 test specimens, have been analyzed for statistical modeling. The ratios of compressive strengths between silica fume and control concrete have been related to silica fume replacement percentage. The expression, being derived with strength ratios and not with absolute values of strength, is independent of the specimen parameters and is applicable to all types of specimens. On examining the validity of the model with the results of previous researchers, it was observed that for results on both cubes and cylinders, predictions were obtained within 7.5% of the experimentally obtained values.     

Prospects of in ovo feeding and nutrient supplementation for poultry: the science and commercial applications—a review

In ovo supplementation of poultry embryos was first reported several decades ago, but it is only recently that concerted research has been directed at developing the technology for this process to be routinely used by the poultry industry. Although the technology of in ovo feeding was patented more than 10 years ago, it has not been widely adopted by the poultry industry. This review examines the early development of the enteric system of the poultry embryo; defines and distinguishes between in ovo feeding and in ovo nutrient administration; highlights the importance of early feeding of the chick; and discusses the development of in ovo feeding technology and its effects on hatchability, growth, gut health and immune response of chicks. The range of possible nutrients that can be administered is also explored. The limitations associated with embryo development and nutrient metabolism are highlighted, leading to the prediction of the future role of in ovo feeding in the poultry industry. © 2013 Society of Chemical Industry