Бордюженко, О. М. та Дворкін, Л. Й. та Ковальчук, Т. В. та Bordiuzhenko, O. M. та Dvorkin, L. Y. та Kovalchuk, T. V. (2018) РОЗРАХУНОК СКЛАДІВ ФІБРОБЕТОНІВ ЗА КРИТЕРІЄМ МІНІМАЛЬНОЇ ВАРТОСТІ. Ресурсоекономні матеріали, конструкції, будівлі та споруди (36). с. 3-10.

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Анотація

Наведено методику і приклад вирішення задачі знаходження оптимального складу фібробетону із заданими показниками якості при мінімальній сумарній його вартості з використанням експериментально-статистичних моделей.

Title in English

DESIGN OF FIBER REINFORCED CONCRETE COMPOSITION BASED ON THE MINIMAL COST CRITERION

English abstract

When designing concrete structures, the main criterion for their optimization are usually the minimum cost of cement or the minimum possible cost of concrete. For ordinary concrete, these criterion usually coincide. In both cases it is mandatory to provide a complex of normalized properties of concrete. Modern concrete is a multi-component system, the cost of which individual components can approach or exceed the cost of cement. These concrete can include fiber reinforced concrete. They differ in the presence of three components (cement, fibers and plasticizer), whose contents can vary in a wide range and have a major impact on the total cost of fiber reinforced concrete. The problem of finding the optimal composition of concrete with specified indicators of quality at the lowest total cost of it is quite important for the construction industry. This article provides an example method and solve this problem using experimental and statistical models compressive and flexural strength of steel fiber reinforced concrete at different ages and models superplasticizer required to provide specified performance concrete and concrete mixtures. The calculation method of fiber reinforced concrete composition design takes into account the specific characteristics of the studied materials and relatively easy to optimize the composition by specific 4 criterion, such as minimum cost criterion. Also, the advantages of the method include the possibility of setting random limitations, which allows simultaneously to provide a significant number of quality indicators, which may be neither big nor less than the set value.

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