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SCHLIEREN VISUALIZATION OF WATER NATURAL CONVECTION IN A VERTICAL RIBBED CHANNEL

Published In: 4TH INTERNATIONAL CONFERENCE ON ADVANCES IN CIVIL, STRUCTURAL AND MECHANICAL ENGINEERING
Author(s): MARIO MISALE , GIOVANNI TANDA , MARCO FOSSA

Abstract: Schlieren techniques are valuable tools for the qualitative and quantitative visualizations of flows in a wide range of scientific and engineering disciplines. In this work, a schlieren technique is applied to visualize the buoyancy-induced flow inside vertical ribbed channels using water as convective fluid. The test section consists of a vertical plate made of two thin sheets of chrome-plated copper with a foil heater sandwiched between them; the external sides of the plate are roughened with transverse, square-cross-sectioned ribs. Results include flow schlieren visualizations and reconstruction of the local heat transfer coefficient distribution along the ribbed surface

  • Publication Date: 08-May-2016
  • DOI: 10.15224/978-1-63248-096-5-08
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DEVELOPMENT OF ARTIFICIAL NEURAL NETWORK MODEL FOR PERMEABILITY OF HIGH PERFORMANCE CONCRETE

Published In: 4TH INTERNATIONAL CONFERENCE ON ADVANCES IN CIVIL, STRUCTURAL AND MECHANICAL ENGINEERING
Author(s): VAISHALI. G. GHORPADE , BEULAH. M , H. SUDARSANA RAO

Abstract: High performance concrete (HPC) is an engineered concrete possessing the most desirable properties during fresh as well as hardened concrete stages. Permeability is one of the most important parameters to quantify the durability of high-performance concrete. This research was to study the chloride ion permeability of high performance concrete with different mineral admixtures like Fly ash, Silicafume and Metakaolin of different percentages, with varying aggregate-binder ratios (2, 2.5). In addition, on the basis of the experimental data an artificial neural network (ANN) technique is executed to demonstrate the possibilities of artificial neural network formulation for the prediction of chloride permeability as a function of four input parameters : water-cement ratio (0.3, 0.325, 0.35, 0.375, 0.4, 0.425, 0.45, 0.475, 0.5), aggregate binder ratio (2,2.5), type of mineral admixtures, percentage replacement of mineral admixtures i.e Fly ash, Silicafume and Metakaolin(0,10,20,30%) as input

  • Publication Date: 08-May-2016
  • DOI: 10.15224/978-1-63248-096-5-09
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