Probabilistic Modelling of Strength of Concretes with RCA

Roman Jaskulski , Anna Stępień , Marlena Sobocińska

Abstract

The subject of the work is research and probabilistic modelling of compressive and tensile strength of concrete with recycled concrete aggregate (RCA). Sixteen series of concrete containing natural aggregate and RCA of 50% by mass of coarse aggregate (fraction 4 – 16 mm). Concrete specimens were tested for compressive and tensile splitting strength. In the study also the absorptivity of recycled and natural aggregate was tested, which is the amount of water that both types of aggregates can absorb during concrete mix. Based on the results models were formulated describing the compressive and tensile strength of concrete with RCA. These models are based on the design parameters of the concrete mix. In order to determine the coefficients of the models an estimating of a function of several variables by linear regression was performed. Compliance of the values calculated using the models with the values obtained from the tests was determined by Monte Carlo simulation. The results indicated a possibility of obtaining a high compliance of the test results with results obtained from simulations based on formulated models
Author Roman Jaskulski (FCEMP / ICEn)
Roman Jaskulski,,
- Insitute of Civil Engineering
, Anna Stępień - [Warsaw University of Technology (PW), MNiSW [80]]
Anna Stępień,,
-
- Politechnika Warszawska
, Marlena Sobocińska
Marlena Sobocińska,,
-
Journal seriesKey Engineering Materials, ISSN 1662-9795, [1013-9826], (B 8 pkt)
Issue year2016
Vol722
Pages207-2015
Publication size in sheets90.4
Keywords in Polish-
Keywords in EnglishRecycled concrete aggregate, compressive strength, tensile strength, probabilistic modelling, Monte Carlo simulation
ASJC Classification2210 Mechanical Engineering; 2211 Mechanics of Materials; 2500 General Materials Science
Abstract in Polish-
DOIDOI:10.4028/www.scientific.net/KEM.722.207
Languageen angielski
Score (nominal)8
Score sourcejournalList
ScoreMinisterial score = 0.0, 11-12-2019, ArticleFromJournal
Ministerial score (2013-2016) = 8.0, 11-12-2019, ArticleFromJournal
Publication indicators Scopus Citations = 0; Scopus SNIP (Source Normalised Impact per Paper): 2016 = 0.257
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