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Frontiers of Structural and Civil Engineering

ISSN 2095-2430

ISSN 2095-2449(Online)

CN 10-1023/X

邮发代号 80-968

2019 Impact Factor: 1.68

Frontiers of Structural and Civil Engineering  2018, Vol. 12 Issue (4): 474-489   https://doi.org/10.1007/s11709-017-0442-6
  本期目录
The effect of micro-structural uncertainties of recycled aggregate concrete on its global stochastic properties via finite pixel-element Monte Carlo simulation
Qingpeng MENG, Yuching WU(), Jianzhuang XIAO
Department of Structural Engineering, College of Civil Engineering, Tongji University, Shanghai 200092, China
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Abstract

In this paper, the effect of micro-structural uncertainties of recycled aggregate concrete (RAC) on its global stochastic elastic properties is investigated via finite pixel-element Monte Carlo simulation. Representative RAC models are randomly generated with various distribution of aggregates. Based on homogenization theory, effects of recycled aggregate replacement rate, aggregate volume fraction, the unevenness of old mortar, proportion of old mortar, aggregate size and elastic modulus of aggregates on overall variability of equivalent elastic properties are investigated. Results are in a good agreement with experimental data in literature and finite pixel-element method saves the computation cost. It is indicated that the effect of mesoscopic randomness on global variability of elastic properties is considerable.

Key wordsRAC    Monte Carlo analysis    stochastic    finite pixel-element method    homogenization    coefficient of variation
收稿日期: 2017-01-25      出版日期: 2018-11-20
Corresponding Author(s): Yuching WU   
 引用本文:   
. [J]. Frontiers of Structural and Civil Engineering, 2018, 12(4): 474-489.
Qingpeng MENG, Yuching WU, Jianzhuang XIAO. The effect of micro-structural uncertainties of recycled aggregate concrete on its global stochastic properties via finite pixel-element Monte Carlo simulation. Front. Struct. Civ. Eng., 2018, 12(4): 474-489.
 链接本文:  
https://academic.hep.com.cn/fsce/CN/10.1007/s11709-017-0442-6
https://academic.hep.com.cn/fsce/CN/Y2018/V12/I4/474
Fig.1  
Fig.2  
Fig.3  
Fig.4  
Fig.5  
Fig.6  
natural aggregateold mortarnew mortar
elastic modulus (GPa)702530
Poisson’s ratio0.160.220.22
Tab.1  
3024025026027028029021002
time (s)10101945353660929617148462273833614
Tab.2  
Fig.7  
volume fraction of aggregate
(%)
elastic modulus of aggregate
(GPa)
elastic modulus of mortar
(GPa)
experimental value [9]
(GPa)
series model [10]
(GPa/err)
parallel model [10]
(GPa/err)
cube model [10]
(GPa/err)
present study
(GPa/err)
074.513.413.413.4
0.00%
13.4
0.00%
13.4
0.00%
13.4
0.00%
2074.513.415.816.0
1.45%
25.6
62.15%
17.6
11.54%
17.2
8.86%
4074.513.423.219.9
14.04%
37.8
63.10%
24.5
5.64%
23.5
1.29%
6074.513.430.726.4
14.06%
50.1
63.06%
34.8
13.32%
32.7
6.51%
42.55.240.818.610.4
43.89%
25.7
38.01%
21.5
15.53%
16.9
9.14%
42.518.240.830.226.7
11.57%
31.2
3.29%
29.7
1.77%
28.7
4.97%
42.55640.849.546.1
6.83%
47.3
4.53%
46.7
5.63%
46.5
6.06%
42.55440.851.345.5
11.25%
46.4
9.53%
46.0
10.34%
45.8
10.72%
42.57240.852.850.0
5.28%
54.1
2.39%
51.9
1.62%
51.4
2.65%
42.521040.869.962.0
11.24%
112.7
61.24%
76.2
9.07%
73.2
4.72%
Tab.3  
RNA
(mm)
ROM
(mm)
volume fractionENA
(GPa)
EOM
(GPa)
nNAnOMR-rate
(%)
test 11012.540%70250.160.2250
test 21012.540%70250.160.22100
test 31012.540%60250.160.22100
test 410.51550%70250.160.22100
Tab.4  
Fig.8  
Fig.9  
test 1test 2test 3test 4
EnEnEnEn
0.03580.04150.02130.02960.04000.03130.02130.0464
Tab.5  
mean valuestandard deviationCOVR2
test 1E37.761620.168140.0044530.94472
v0.205830.001820.0088420.98195
test 2E35.153490.079110.002250.9909
v0.210170.001160.0055190.98553
test 3E34.13520.050810.0014880.96102
v0.209170.0007710.0036850.99193
test 4E34.102670.050740.0014880.98
v0.211330.000820.0038810.97762
Tab.6  
Fig.10  
Fig.11  
Fig.12  
Fig.13  
Fig.14  
Fig.15  
Fig.16  
Fig.17  
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