Ravinder Kumar

Bio: Ravinder Kumar is an academic researcher from Lovely Professional University. The author has contributed to research in topics: Exergy & Materials science. The author has an hindex of 23, co-authored 160 publications receiving 1770 citations. Previous affiliations of Ravinder Kumar include Deenbandhu Chhotu Ram University of Science and Technology & Maharishi Markandeshwar University, Mullana.

Recent progress of reinforcement materials: a comprehensive overview of composite materials

Abstract: Emerged in the middle of 20th century, composite materials are now one of the hotspot research topics in the modern technology. Their promising characteristics make them suitable for enormous applications in industrial field such as aerospace, automotive, construction, sports, bio-medical and many others. These materials reveal remarkable structural and mechanical properties such as high strength to weight ratio, resistance to chemicals, fire, corrosion and wear; being economical to manufacture. Herein, an overview of composite materials, their characterization, classification and main advantages linked to physical and mechanical properties based on the recent studies are presented. There, were presented the conventional manufacturing techniques of composite and their applications. It was highlighted the tremendous need to discovery new generation of composites that should incorporate the synthetic or natural materials by implementing new efficient manufacturing processes. In the combination of matrix and reinforcement materials, the use of natural materials as constituent are compulsory in order to obtain a complete material degradable as environmentally friendly.

Comparing various machine learning approaches in modeling the dynamic viscosity of CuO/water nanofluid

Abstract: Nanofluids are broadly employed in heat transfer mediums to enhance their efficiency and heat transfer capacity. Thermophysical properties of nanofluids play a crucial role in their thermal behavior. Among various properties, the dynamic viscosity is one of the most crucial ones due to its impact on fluid motion and friction. Applying appropriate models can facilitate the design of nanofluidics thermal devices. In the present study, various machine learning methods including MPR, MARS, ANN-MLP, GMDH, and M5-tree are used for modeling the dynamic viscosity of CuO/water nanofluid based on the temperature, concentration, and size of nanostructures. The input data are extracted from various experimental studies to propose a comprehensive model, applicable in wide ranges of input variables. Moreover, the relative importance of each variable is evaluated to figure out the priority of the variables and their influences on the dynamic viscosity. Finally, the accuracy of the models is compared by employing the statistical criteria such as R-squared value. The models’ outputs disclosed that employing ANN-MLP approach leads to the most precise model. R-square value and average absolute percent relative error (AAPR) value of the model by using ANN-MLP model are 0.9997 and 1.312%, respectively. According to these values, ANN-MLP is a reliable approach for predicting the dynamic viscosity of the studied nanofluid. Additionally, based on the relative importance of the input variables, it is concluded that concentration has the highest relative importance; while the influence of size is the lowest one.

Artificial neural networks

Abstract: Artificial neural networks (ANNs) constitute a class of flexible nonlinear models designed to mimic biological neural systems. In this entry, we introduce ANN using familiar econometric terminology and provide an overview of ANN modeling approach and its implementation methods. † Correspondence: Chung-Ming Kuan, Institute of Economics, Academia Sinica, 128 Academia Road, Sec. 2, Taipei 115, Taiwan; ckuan@econ.sinica.edu.tw. †† I would like to express my sincere gratitude to the editor, Professor Steven Durlauf, for his patience and constructive comments on early drafts of this entry. I also thank Shih-Hsun Hsu and Yu-Lieh Huang for very helpful suggestions. The remaining errors are all mine.

Numerical Heat Transfer And Fluid Flow

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Fiber-Reinforced Polymer Composites: Manufacturing, Properties, and Applications.

Abstract: Composites have been found to be the most promising and discerning material available in this century. Presently, composites reinforced with fibers of synthetic or natural materials are gaining more importance as demands for lightweight materials with high strength for specific applications are growing in the market. Fiber-reinforced polymer composite offers not only high strength to weight ratio, but also reveals exceptional properties such as high durability; stiffness; damping property; flexural strength; and resistance to corrosion, wear, impact, and fire. These wide ranges of diverse features have led composite materials to find applications in mechanical, construction, aerospace, automobile, biomedical, marine, and many other manufacturing industries. Performance of composite materials predominantly depends on their constituent elements and manufacturing techniques, therefore, functional properties of various fibers available worldwide, their classifications, and the manufacturing techniques used to fabricate the composite materials need to be studied in order to figure out the optimized characteristic of the material for the desired application. An overview of a diverse range of fibers, their properties, functionality, classification, and various fiber composite manufacturing techniques is presented to discover the optimized fiber-reinforced composite material for significant applications. Their exceptional performance in the numerous fields of applications have made fiber-reinforced composite materials a promising alternative over solitary metals or alloys.

Biology of mosquitoes.

Abstract: 日本には約110種の蚊が産する。その中で医学的に重要なのは, 幼虫(ボウフラ)が人里近くの水域に発生し, 雌成虫がヒトから好んで吸血する種である。西日本ではアカイエカ(南西諸島ではネッタイイエカにおきかわる), チカイエカ, コガタアカイエカ, ヒトスジシマカなどが最も重要である。これらの種は生態がことなるので, その被害に対する効果的対策もことなる。雌成虫が吸血源となる動物を発見して完了するまでの過程は複雑で, わかつていない点もある。

Smart Textiles for Electricity Generation.

Abstract: Textiles have been concomitant of human civilization for thousands of years. With the advances in chemistry and materials, integrating textiles with energy harvesters will provide a sustainable, environmentally friendly, pervasive, and wearable energy solution for distributed on-body electronics in the era of Internet of Things. This article comprehensively and thoughtfully reviews research activities regarding the utilization of smart textiles for harvesting energy from renewable energy sources on the human body and its surroundings. Specifically, we start with a brief introduction to contextualize the significance of smart textiles in light of the emerging energy crisis, environmental pollution, and public health. Next, we systematically review smart textiles according to their abilities to harvest biomechanical energy, body heat energy, biochemical energy, solar energy as well as hybrid forms of energy. Finally, we provide a critical analysis of smart textiles and insights into remaining challenges and future directions. With worldwide efforts, innovations in chemistry and materials elaborated in this review will push forward the frontiers of smart textiles, which will soon revolutionize our lives in the era of Internet of Things.