2016
DOI: 10.5755/j01.ms.22.4.13354
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Effect of Elevated Temperatures on Properties of Blended Cements with Clinoptilolite

Abstract: We have investigated the effect of elevated temperature on properties of clinoptilolite blended cements. Clinoptilolite was used at 5 %, 10 %, 15 % and 20 % replacement by weight for Portland cement while sand and water quantities were kept constant in all mix designs. Dry weights, flexural strengths, and compressive strengths of specimens were determined as a function of time. The same properties were again evaluated after specimens, having reached the age of 90 days, were exposed to 300 °C, 400 °C and 500 °C… Show more

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Cited by 8 publications
(5 citation statements)
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“…Portland cement-based mortars with 45% or 10% clinoptilolite substitution have compressive strength exceeding 42.5 MPa after being subjected to 400°C and 500°C. 20 One of the eco-friendly compositions prepared from a mixture of polypropylene fibers, porcelain, and blast furnace slag as a cement replacement displays excellent fire resistance. 21 Passive fire-protection compositions have been developed to insulate the load-bearing substrates from fire.…”
Section: Introductionmentioning
confidence: 99%
“…Portland cement-based mortars with 45% or 10% clinoptilolite substitution have compressive strength exceeding 42.5 MPa after being subjected to 400°C and 500°C. 20 One of the eco-friendly compositions prepared from a mixture of polypropylene fibers, porcelain, and blast furnace slag as a cement replacement displays excellent fire resistance. 21 Passive fire-protection compositions have been developed to insulate the load-bearing substrates from fire.…”
Section: Introductionmentioning
confidence: 99%
“…In earlier work on concretes we have included clinoptilolite [23], a natural mineral available among others in California and also around the shores of the Aegean Sea. Significant improvement of the compressive strength was found after such concretes were subjected to 400 °C or 500 °C treatments.…”
Section: Fig 2 Abrasive Weight Loss Resultsmentioning
confidence: 99%
“…In order to correctly process information, neural networks have to undergo a training process during which the weights of synaptic connections are modified. In most cases, gradient optimization methods are used during the training process (the Levenbeg-Marquardt method of steepest descent, methods of variable metrics and conjugate gradients) [26]. A fuzzy inference system consists of a set of fuzzy rules, a database described by membership functions and an inference and aggregation mechanism.…”
Section: Methodsmentioning
confidence: 99%