Abstract
Crack distribution and widths were experimentally examined in a series of reinforced concrete (RC) beams. Concretes of different strengths were used, and beams were reinforced with 600 MPa yield strength steel bars. The features of cracks, which need to be considered in the design, were determined by using statistical analysis of different crack patterns observed in RC beams. The methods for determining the depth of effective influence zone of 600 MPa steel bars in RC beams were experimentally obtained. Based on the experimental data obtained in this study and from the data on RC beams with 335–600 MPa yield strength steel bars from other studies, the applicability of different formulas for the determination of the maximum widths (provided in codes and by scholars) was analyzed. Methods for the calculation of average crack spacing and maximum crack widths in RC beams with steel bars of various yield strengths were proposed. A unified formula for the calculation of maximum crack width in such beams was also established.
Highlights
Checking and controlling of cracks in reinforced concrete (RC) components or structures are the key issues in the engineering design, construction, and serviceability of concrete structures
The details of RC beams with 600 and 400 MPa steel bars are listed in Table 5, where ρ denotes the reinforcement ratio determined as ρ = As/(bh0), and As is the area of steel bars
The results indicate that the proposed method leads to a good estimation of maximum crack widths in the case of RC beams with 335 MPa steel bars
Summary
Checking and controlling of cracks in reinforced concrete (RC) components or structures are the key issues in the engineering design, construction, and serviceability of concrete structures. An accurate crack width checking is known as a crucial and complicated problem in the design and testing of RC. The second type is formulas based on mathematical statistics, which involves conducting a regression analysis of the impacts of different parameters on the crack width development and requires a large number of measured data. After selecting the most important parameters, an appropriate mathematical statistics methodology is used to directly establish an appropriate formula. Such examples are formulas provided in the US codes ACI318-71 (ACI Committee, 1971) and ACI318-95 (ACI Committee, 1995), and Chinese codes JTG (JTGD62-2012, 2012), JTJ (JTJ267-98, 1998) and TB (TB10002.3-2005, 2005)
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