ALKALI-SILICA REACTION MITIGATION USING HIGH VOLUME CLASS C FLY ASH
Published In: 2ND INTERNATIONAL CONFERENCE ON ADVANCES IN CIVIL, STRUCTURAL AND MECHANICAL ENGINEERING
Author(s): RICHARD DESCHENES JR , SYDNEY DICKSON , W. MICAH HALE , WILLIAM PHILLIPS
Abstract: Fly ash is the residue produced from coal combustion in electric generating plants. There are two types of fly ash, Class C and Class F. Approximately 40 percent of fly ash generated from coal combustion can be used as a partial replacement of cement in concrete. Incorporating fly ash improves concrete properties and extends its service life. Alkalisilica reaction (ASR) is an expansive reaction between reactive silica typically found in aggregates (rock and sand) and alkalis in cement. This reaction results in the formation of a gel that absorbs water and swells, which exerts an internal pressure in concrete. This pressure leads to cracking and premature deterioration of the structure. ASR can be prevented by replacing approximately 15 to 25 percent by mass of the cement with Class F fly ash. Class F fly ash is more effective in preventing ASR than Class C fly ash due to its chemical composition. Sources of Class F fly ash are limited in the State of Arkansas, and occurrences of ASR ar
- Publication Date: 17-Nov-2014
- DOI: 10.15224/978-1-63248-054-5-58
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PARAMETER IDENTIFICATION OF MAGNETORHEOLOGICAL DAMPER USING PARTICLE SWARM OPTIMIZATION
Published In: 2ND INTERNATIONAL CONFERENCE ON ADVANCES IN CIVIL, STRUCTURAL AND MECHANICAL ENGINEERING
Author(s): A. ELSAWAF , H. METERED , T. VAMPOLA
Abstract: Particle swarm optimization (PSO) technique has achieved a considerable success in solving nonlinear, nondifferentiable, multi-modal optimization problems. Currently, PSO is broadly applied in several scientific and engineering optimization applications. This paper introduces an identification of magnetorheological (MR) damper’s parameters using the PSO algorithm to introduce a more simple and accurate model. The proposed model predicts the MR damper force as a nonlinear function of the damper velocity, acceleration and command voltage to the damper coil, without using any complex differential equations, which will be very beneficial for complicated systems. PSO algorithm aims to minimize the rootmean- square-error of the damping force between the proposed model and the modified Bouc-Wen model which can estimate the dynamic behavior of the MR damper precisely. The validation of the proposed model is achieved by comparing its behavior against the behavior of the modified Bouc-Wen model.
- Publication Date: 17-Nov-2014
- DOI: 10.15224/978-1-63248-054-5-60
- Views: 0
- Downloads: 0