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PREDICTION EQUATIONS FOR CREEP AND DRYING SHRINKAGE IN CONCRETE OF WIDE-RANGING STRENGTH (Translation from Proceedings of JSCE, No.690/V-53, November 2001) Kenji SAKATA Tatsuya TSUBAKI Shoichi INOUE Toshiki AYANO As the performance of concrete is enhanced and high-strength concrete comes into common use, the model code for concrete is being improved to cope with the changes. Today, prediction equations for creep and shrinkage in high-strength concrete are an essential part of the model code. In this study, the precision of current prediction equations is examined using a number of databases, from which data providing reliable knowledge of the effect of concrete strength on creep and shrinkage is extracted. New prediction equations are proposed, and this paper shows that they are very simple and applicable to a wide range of concrete strengths. Keywords: prediction equation, creep, drying shrinkage, high-strength concrete, data base K. Sakata, a professor in Environmental and Civil Engineering at Okayama University, Okayama, Japan, received his Doctor of Engineering degree from Kyoto University, Japan in 1976. His research interests include the prediction of concrete shrinkage, creep, and fatigue properties. He is a fellow of the JSCE. T. Tsubaki is a Professor in the Department of Civil Engineering at Yokohama National University, Japan. He obtained his Ph.D. from Northwestern University in 1980. His research interests include the time-dependent mechanical behavior of concrete and the analysis of concrete structures. He is a member of the JSCE and the JCI. S. Inoue is a Professor in the Department of Civil Engineering at Tottori university, Tottori, Japan. He received his Doctor of Engineering Degree from Kyoto University in 1985. His research interests include the fatigue properties, time-dependence deformation of concrete structures, and properties of fresh concrete. He is a member of the ACI, JSMS, JCI, LPC and JSCE. T. Ayano, an associate professor in Environmental and Civil Engineering at Okayama University, Okayama, Japan, received his Doctor of Engineering degree from Okayama University in 1993. His research interests include the prediction of concrete shrinkage and creep. He is a member of the JSCE. - 145 - 1. INTRODUCTION Every increment in concrete creep and shrinkage strain increases the deflection of a concrete member, affects cracking progress, and causes loss of prestress. Thus, to check the safety, durability and serviceability of concrete structures, it is very important to have a means of predicting creep and shrinkage over the long term. Higher strength concrete has now been used extensively, and research into high-performance concrete and its applications has been very active. The wide acceptability of high-performance concrete can be attributed to the establishment of a technique for producing high-performance concrete using silica fume and high-range water-reducing admixtures. Its use has led to the construction of slender, lightweight concrete members. Increasing the strength of concrete may also improve the durability and extend the service life of concrete structures. In this sense, many hope that high-performance concrete may decrease environmental loading. On the other hand, others point out that high-strength concrete is prone to cracking. Whatever one's perspective, however, it is very important to precisely predict both creep and shrinkage at the design stage in order to discuss the durability and service life of concrete structures. Most model codes are based on prediction equations that consist of several factors relating to concrete creep and shrinkage [1][2]. Some existing codes are applicable to high-performance concrete. The Japan Society of Civil Engineers (JSCE) has its own prediction equations [3], but the model is proven only for normal-strength concrete up to 60 N/mm2. It has not been clarified whether the model is available for high-strength concrete as well. High-strength concrete with strength at 28 days exceeding 70 N/mm2 is not unusual. Indeed, the 2002 edition of the Standard Specifications for Design and Construction of Concrete Structures cover concrete whose 28-day strength is up to 80 N/mm2. Thus the requirement for creep and shrinkage prediction equations suitable for a wide range of concrete strengths is increasing. Both RILEM and JSCE are establishing databases of creep and shrinkage. In this paper, new prediction equations that are simple and available for a wide range of strengths are proposed on the basis of data extracted from the RILEM and JSCE databases as well as other minor sources. 2. REPRESENTATIVE PREDITION EQUATIONS 2.1 Outline of data used The main source of data used in establishing the new prediction equations was the creep and shrinkage data collected by RILEM and JSCE. The RILEM database holds data consisting of 512 creep records and 419 shrinkage records [4], while the JSCE database contains 259 creep records and 219 shrinkage records [5]. The RILEM database consists mainly of data from the western countries, while the JSCE has collected data from papers published by Japanese organizations. Every data set was subjected to regression using the hyperbola expressed by Equation (1). The standard divisions of the optimal value of C0 and C1 were checked. If each of them was beyond 10, the data was judged to be unreliable and was excluded from use in the study. Creep or shrinkage = C0 ⋅ t C1 + t (1) In total, 295 creep records and 200 shrinkage records from the RILEM and JSCE database were selected for use in the study. Not all sets of shrinkage and creep data include all information. However, the selected data sets were obtained for concrete specimens with a wide range of strength and dimensions. Summaries of the selected drying shrinkage and creep data are shown - 146 - in Figures 1 and 2, respectively. All data was measured at 20°C. Drying shrinkage was obtained from unloaded specimens. The drying shrinkage strain of high-strength concrete was obtained by subtracting the strain of a sealed specimen from that of an unsealed specimen. In cases where the start of drying was more than one week after casting, the effect of autogenous shrinkage on the strain of unsealed specimens was regarded to be negligible. Creep strain was obtained by subtracting the strain of an unloaded specimen from that of a loaded specimen. The size and shape of specimens under loading and unloading were the same. 100 200 Total = 318 Number of data records Number of data records Total = 497 147 150 111 100 62 61 50 31 26 17 6 15 16 5 79 75 75 60 50 30 20 25 17 12 10 0 20 40 60 80 100 120 0 2 Strength at 28 days - N/mm 20 40 60 80 100 120 2 Strength at start of drying - N/mm (a) Compressive strength at 28 days (b) Compressive strength at start of drying 200 500 Total = 497 Number of data records Total = 497 Number of data records 3 2 0 0 380 400 300 200 100 71 39 7 146 150 151 100 67 78 50 27 21 5 2 0 0 40 50 60 70 80 90 100 80 100 120 140 160 180 200 220 240 Relaitve humidity - % Water content - kg/m 3 (c) Relative humidity at atmosphere (d) Water content of Concrete 400 Total = 318 75 75 79 60 50 30 20 25 17 10 12 2 8 2 3 Number of data records 100 Number of data records 8 2 Total = 482 282 300 200 97 100 39 0 0 0 20 40 60 80 100 Strength at start of drying - N/mm 120 0 200 27 11 5 6 0 0 9 0 0 0 0 6 400 600 800 1,000 1,200 1,400 1,600 V / S - mm 2 (e) Age at start of drying (f) Specimen size Figure 1 Summaries of data used for drying shrinkage - 147 - 200 Total = 476 Total = 483 151 150 129 100 65 50 35 15 13 23 22 13 9 1 Number of data records Number of data records 200 0 150 20 40 60 80 100 Strength at 28 days - N/mm 50 37 30 9 1 120 0 2 19 19 7 6 1 20 40 60 80 100 120 2 Strength at applicaton of load - N/mm (a) Compressive strength at 28 days (b) Compressive strength at initial load application 250 300 266 Total = 485 Number of data records Total = 350 250 200 150 100 35 50 34 6 5 4 188 200 150 122 100 80 50 35 33 16 9 2 0 0 30 40 50 60 70 80 90 100 80 120 (c) Relative humidity of atmosphere 250 224 239 200 100 56 37 29 7 Number of data records Total = 485 58 3~7 240 Total = 474 200 150 126 100 86 50 31 5 1 0 0 0 0 600 800 1,000 1,200 1,400 0 0 0~3 200 (d) Water content of concrete 300 59 160 Water content - kg/m 3 Relative humidity - % Number of data records 105 97 100 0 0 Number of data records 152 7~14 14~28 28~56 56~90 90~ 0 200 400 V / S - mm Age at application of load - days (e) Age at initial load application of load (f) Specimen size Figure 2 Summaries of data used for creep - 148 - 0 1 2.2 Applicable range of representative prediction equations Table 1 shows the applicable range of the representative prediction equations for creep and shrinkage. Table 2 shows the factors needed to predict creep and shrinkage using each prediction equation, since the factors differ according to the equation selected. Model B3 [6] requires more factors than any of the other prediction equations listed in Table 1. As for creep, model B3 predicts the creep function J (t,t') ; models CEB [7] and GZ [8] predict the creep coefficient; and the JSCE model [9] predicts specific creep C (t,t') . Furthermore, the creep coefficient φ 28 (t,t') predicted by model CEB is the product of specific creep and Young’s modulus at 28 days. The creep coefficient φ (t,t') predicted by model BZ is the product of specific creep and Young’s modulus at the application of loading. When Young’s modulus at the age of t’ is represented by E (t') , the relationship between J (t,t') , C (t,t') , J (t,t') = φ 28 (t,t') and φ (t,t') is represented as follows: 1 + C (t,t') E (t') (2) φ (t,t') φ (t,t') 1 1 = + 28 = + E (t') E (28) E (t') E (t') Where, t: current age (days), t’: age at first application of loading (days) The accuracy of creep models CEB, BZ, and the JSCE model was examined by using the specific creep strain. The accuracy of model B3 was examined by using the creep function. In cases where Young’s modulus was also available in the database, it was used to calculate specific creep strain. Otherwise, Young’s modulus was calculated using the proposed equation in each model code including the creep and shrinkage model. The factors used as the basis for prediction are listed in Table 3; these are values for ordinary concrete. Table 4 gives the predicted shrinkage strain and specific creep for each model based on these factors. The values predicted by the JSCE model are a little bigger than the others. Table 1 Applicable range of each prediction equation. Model B3 17.2~68.95 2.5~13.5 160~721 0.35~0.85 40~100 Normal Low heat Rapid Normal hardening Type of Cement High strength Volume-surface ratio (mm) 100~300 t’≧ t0 t’ and t0 Autoclave Water curing Curing method Sealed curing t’: Age at initial load application (days), t0: Age at start of drying (days) Strength at 28 days(N/mm2) Aggregate/cement ratio in weight Unit cement content (kg/m3) Water-cement ratio Relative humidity (%) JSCE Model Less than 70 260~500 0.40~0.65 45~80 - 149 - Model CEB 20~90 40~100 Normal Low heat Rapid hardening High strength - Model GZ 20~68.95 0~0.6 40~100 Normal Low heat Rapid hardening High strength ≧2days - Table 2 Necessary factors for each prediction equation JSCE Model Creep Shrinkage Strength at 28 days Strength at t’ or t0 Aggregate/cement ○ Unit cement content ○ ○ Unit water content ○ Water-cement ratio ○ ○ Relative humidity Type of cement ○ Start of drying ○ t’ ○ ○ Size of specimen Shape of specimen Curing method t’: age at initial load application (days) Model CEB Creep ○ ○ Shrinkage Model B3 Creep ○ ○ Shrinkage ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ Model GZ Creep ○ ○ ○ Shrinkage ○ ○ ○ ○ ○ ○ ○ Table 3 Set values for prediction Item Start of drying Age at initial load application Relative humidity Strength at 28 days Strength at initial load application Cement type Aggregate-cement ratio Unit cement ratio Unit water content Water-cement ratio Size and shape of specimen Input data 7 days 7 days 60 % 30 N/mm2 20 N/mm2 Normal 6 300 kg/m3 180 kg/m3 60 % 100×100×400 mm Table 4 Predicted values Drying shrinkage (μ) Specific creep (μ/(N/mm2)) JSCE Model Model CEB 790 557 214 130 Model B3 441 107 Model GZ 817 134 2.3 Accuracy of shrinkage prediction equations Figure 3 presents a comparison between experimental shrinkage data extracted from the databases and the JSCE model predictions. Here, however, the 28-day concrete compressive strength is less than 80 N/mm2. On the other hand, the comparison in Figure 4 is for concrete with - 150 - a 28-day compressive strength greater than 80 N/mm2. The start of drying is indicated by ● and ○, representing 28 days and 1 day, respectively. As is clear from these figures, the JSCE model tends to predict larger values than the experimental data when the start of drying is late. Figure 5 is a comparison between experimental shrinkage data and predictions by model CEB. Here, only data within the applicable range of model CEB was used for comparison. Model CEB is able to closely predict the experimental shrinkage data from the western database well. However, the predicted values are smaller than the data from the JSCE database. Figure 6 compares data outside the applicable range of model CEB. The 28-day strength expressed by ● is greater than 90 N/mm2. Model CEB underestimates the shrinkage strain of this high-strength concrete. Figure 7 is a comparison between experimental shrinkage data and predictions by model B3. Here, only data within the applicable range of model B3 was used for comparison. Model B3 tends to underestimate experimental shrinkage data, even within its applicable range. As is clear from Figure 8, which is a comparison with data outside its applicable range, model B3 underestimates concrete shrinkage especially significantly when the 28-day strength is greater than 70 N/mm2. In this figure, data for concrete in this strength range is indicated by ●. Figure 9 compares experimental shrinkage data and predictions by model GZ. Here again, only data within the applicable range of model GZ was used for comparison. The GZ model can predict experimental shrinkage strain to an accuracy of ±40% when the data is within its applicable range. On the other hand, Figure 10 is a comparison between predictions by model GZ and experimental shrinkage data beyond the applicable range of the model. Symbols ○ represent shrinkage data for concrete whose strength at 28 days is greater than 70 N/mm2. Symbols □ represent concrete whose strength at 28 days is less than 20 N/mm2. Shrinkage data for concrete whose start of drying is earlier than 2 days is shown by ●. Model GZ is able to predict the shrinkage strain of high-strength concrete. However, in the case of concrete whose start of drying is earlier than 2 days, the values predicted by model GZ are larger than the experimental values. 800 0 -4 % 400 Outside limits (f'c(28) > 80MPa) 600 ○ : t0=1day ● : t0=28days 500 +4 0% ○ : JSCE data □ : RILEM data Experimental shrinkage strain - µ 700 Within limits +4 0% Experimental shrinkage strain - µ 1,200 400 0% -4 300 200 100 Number of data sets = 8 0 0 0 400 800 Calculated shrinkage strain - 0 1,200 µ 100 200 300 400 500 600 Calculated shrinkage strain - Figure 3 Precision of the JSCE Model 700 µ Figure 4 Precision of the JSCE Model - 151 - 1,000 750 - 40 % 500 250 ○ : JSCE data □ : RILEM data 750 500 % - 40 250 ●: f'c(28) > 90MPa Number of data sets = 17 0 0 0 250 500 750 1,000 Calculated shrinkage strain - 0 1,250 500 750 1,000 µ Figure 6 Precision of Model CEB Experimental shrinkage strain - 1,000 750 % - 40 500 ○ : RILEM data □ : CEB data ◇ : JSCE data Number of data sets = 129 250 0 0 250 500 750 1,000 750 500 % - 40 250 ●: f'c(28) > 70MPa Number of data sets = 58 0 0 1,250 250 500 750 1,000 µ Calculated shrinkage strain - µ Calculated shrinkage strain - +4 0 Outside limits µ +4 0% µ Within limits % 1,000 1,250 Figure 7 Precision of Model B3 Figure 8 Precision of Model B3 1,250 +4 0 µ Within limits 1,000 750 - 40 500 % ○ : RILEM data □ : CEB data ◇ : JSCE data Number of data sets = 104 250 Experimental shrinkage strain - µ % 1,250 250 500 750 1,000 Calculated shrinkage strain - 1,000 750 - 40 % 500 250 ●: t0 < 2days Number of data sets = 92 0 0 0 Outside limits ○: f'c(28) > 70MPa □: f'c(28) < 20MPa +4 0% Experimental shrinkage strain - 250 Calculated shrinkage strain - µ Figure 5 Precision of Model CEB Experimental shrinkage strain - 0% Outside limits +4 +4 1,000 Experimental shrinkage strain - µ Within limits µ Experimental shrinkage strain - 0% 1,250 0 1,250 250 500 750 1,000 Calculated shrinkage strain - µ Figure 9 Precision of Model GZ Figure 10 Precision of Model GZ - 152 - 1,250 µ Each of the models described above is able to predict shrinkage strain reasonably well when the data is within its applicable range. However, out of this range, the capabilities of the models vary. The JSCE model overestimates shrinkage for high-strength concrete when the age at the start of drying is 28 days. On the other hand, predictions by the other models are smaller than the experimental values in the case of high-strength concrete. Thus, prediction equations used for normal-strength concrete cannot be applied as is to high-strength concrete. 2.4 Accuracy of creep prediction equations Figure 11 is a comparison of experimental values of specific creep extracted from the databases and predictions by the JSCE model. The figure includes data for concrete whose 28-day strength is greater than 100 N/mm2. Figure 12 shows a case where the predictions by the JSCE model are extremely unreasonable. The JSCE model takes account of factors representing the concrete mixture, specimen size, and environmental conditions. It does not include a strength factor. Even where other creep models that include a strength factor are able to predict creep well, the JSCE model sometimes gives unreasonable results. Figure 13 compares the experimental specific creep strain with predictions by model CEB. Data within the applicable range of model CEB was used for the comparison. Figure 14 is a similar comparison but for data outside the applicable range of model CEB. As is clear from these figures, model CEB is able to predict creep well even outside the usual range. ○ : RILEM data □ : CEB data ◇ : JSCE data 200 150 0% -4 100 50 Number of data sets = 250 0 0 50 100 150 Calculated specific creep strain - 200 250 µ/(N/mm 2 ) Figure 11 Precision of the JSCE Model 500 ○ : RILEM data □ : CEB data +4 0% µ/(N/mm 2 ) +4 0% 250 Experimental specific creep strain - Experimental specific creep strain - µ/( N/mm 2 ) Figure 15 compares experimental creep data with predictions data by model B3. Data within the applicable range of model B3 was used for comparison. The difference between experimental values and predictions appears large even within the applicable range. Figure 16 shows a similar comparison for data outside the applicable range of model B3. Here, data for concrete whose 28day strength is greater than 70 N/mm2 is indicated by ●. It is clear that model B3 is able to predict the creep of high-strength concrete with accuracy. 400 300 0% -4 200 100 Number of data sets = 17 0 0 100 200 300 Calculated specific creep strain - 400 500 µ/(N/mm 2 ) Figure 12 Precision of the JSCE Model - 153 - 150 100 50 % ○ : RILEM data □ : CEB data ◇ : JSCE data Number of data sets = 255 0 0 50 100 150 Calculated specific creep strain - 200 µ/(N/mm 2 ) Outside limits 150 100 % - 40 50 ●: f'c(28) > 90MPa Number of data sets = 31 0 0 µ/(N/mm 2 ) % +4 0 Experimental creep compliance - µ/(N/mm 2 ) Experimental creep compliance - 200 150 % - 40 100 ○ : RILEM data □ : CEB data ◇ : JSCE data Number of data sets = 217 0 0 50 100 150 200 150 200 µ/(N/mm 2 ) Figure 14 Precision of Model CEB 250 50 100 Calculated specific creep strain - Figure 13 Precision of Model CEB Within limits 50 250 Calculated creep compliance - µ/(N/mm 2 ) Figure 15 Precision of Model B3 250 Outside limits +4 0% - 40 200 +4 0% µ/(N/mm 2 ) Within limits Experimental specific creep strain - +4 0% µ/(N/mm 2 ) Experimental specific creep strain - 200 200 150 - 40 % 100 50 ●: f'c(28) > 70MPa Number of data sets= 52 0 0 50 100 150 200 250 Calculated creep compliance - µ/(N/mm 2 ) Figure 16 Precision of Model B3 Figure 17 compares experimental creep data with predictions by model GZ for data within the applicable range of model GZ. Model GZ tends to underestimate creep even for data within the applicable range. On the other hand, Figure 18 shows a similar comparison for data that is out of model GZ's applicable range. Symbol ● represents creep data for concrete whose strength at 28 days is above 70 N/mm2. Symbol □ represents creep data for concrete for which drying began within 2 days. From this figure, it is clear that model GZ tends to overestimate creep strain when the concrete strength is high or the first application of loading is early. Despite that, the accuracy of model GZ is as good as any of the others. All the models are able to predict creep to an accuracy of ±40%, and it is clear that each prediction equation offers reasonable predictions of creep from the range of concrete strength from normal to high. However, in general, the prediction equations for creep are more complicated than those for shrinkage strain. - 154 - 150 - 40 % 100 ○ : RILEM data □ : CEB data ◇ : JSCE data 50 Number of data sets = 135 0 0 50 100 150 200 Calculated specific creep strain - 250 µ/(N/mm 2 ) 250 +4 0% µ/(N/mm 2 ) 200 Experimental specific creep strain - Within limits +4 0% µ/(N/mm 2 ) Experimental specific creep strain - 250 Outside limits 200 150 % - 40 100 50 ●: f'c(28) > 70MPa □: t' < 2days Number of data = 135 0 0 50 100 150 200 Calculated specific creep strain - Figure 17 Precision of Model GZ 250 µ/(N/mm 2 ) Figure 18 Precision of Model GZ 3. PROPOSED NEW SHRINKAGE PREDITION EQUATION 3.1 Effect of concrete strength on ultimate shrinkage strain Figure 19 shows the relationship between ultimate shrinkage strain and compressive strength at the start of drying. By regression, the development of shrinkage strain with time fits the hyperbola expressed by equation (3). εsh (t,t 0 ) = εsh∞ ⋅ (t − t 0 ) β + (t − t 0 ) (3) µ 1,000 900 Ultimate shrinkage strain - µ Where, εsh∞ : ultimate shrinkage strain ( µ ), β : the term representing development of shrinkage strain, t: current age of concrete (days), t0: the start of drying (days). 800 0% +4 750 500 0% -4 Ultimate shrinkage strain - Number of data sets = 92 250 R.H.=60~68% 100 ×100 ×400mm prism 0 0 30 60 90 120 Strength at start of drying - N/mm Figure 19 Relationship between shrinkage and concrete strength Gravel Type-A (water absorption: 1.12%) Gravel Type-B 700 (water absorption: 1.07%) 600 500 Gravel Type-C (water absorption: 0.52%) 400 300 200 10 2 20 30 40 50 60 70 Water-cement ratio - % ultimate Figure 20 Relationship shrinkage and W/C - 155 - between ultimate µ Ultimate shrinkage strain - Ultimate s hrinkage strain - µ 1,400 1,200 1,000 558 800 613 390 600 445 334 400 279 500 200 100 223 125 150 175 200 Cement content (kg/m 3 ) 225 250 1,000 W=220kg/・ 750 W=200kg/・ W=180kg/・ 500 250 275 Unit water content - kg /m 3 70N/mm 2 50N/mm 2 0 0.00 0.01 0.02 0.03 20N/mm2 0.04 0.05 (Strength at start of drying) Figure 21 Effect of cement and water content on ultimate shrinkage Figure 22 Relationship between shrinkage and concrete strength 0.06 0.07 -1 ultimate As this makes clear, the greater the concrete strength at start of drying, the lower the ultimate shrinkage strain. When the relationship between ultimate shrinkage strain εsh∞ and the concrete strength at the start of drying is fitted to the hyperbola, every data point εsh∞ is within ±40% of the value on the curve. Many conventional prediction equations make use of this fitting [10][11]. However, as is clear from the results shown in Figure 20, the effect of concrete strength on ultimate shrinkage strain is small when the range of water-cement ratio is between 50% and 60%, that is, when the concrete strength is low. This result is independent of the type of gravel used. Other investigations have also found the same result. Figure 21 shows the effect of water content on the ultimate shrinkage strain of normal-strength concrete [12]. It is clear from this figure that the effect of water content on ultimate shrinkage strain is much higher than that of water-cement ratio. The horizontal axis of Figure 22 is the inverse of concrete strength at the start of drying. When concrete strength is less than 50 N/mm2, the effect of strength is very small and the effect of water content is much greater. The results given in both Figures 21 and 22 were collected from not only normal concrete, but also concrete containing a wide range of water contents in order to investigate the effect of concrete mix proportion. We can conclude that the effect of water content on ultimate shrinkage strain depends on concrete strength, and that the effect of concrete strength on ultimate shrinkage strain is much higher than that of water content when the concrete strength is high. This situation makes it very difficult to establish a shrinkage prediction equation that takes full account of all these dependencies, since neither of the databases stores information on concrete strength at the start of drying, though the 28-day strength was collected. For this reason, a prediction equation for ultimate shrinkage strain εsh∞ based on 28-day strength was established. The relationship between ultimate shrinkage strain εsh∞ and age at the start of drying is expressed by equation (4). εsh∞ = Where, εshρ 1 + ϕ ⋅ t0 (4) εshρ , ϕ : the optimal values obtained by regression, t0: start of drying (days); however, t0=98 when t0>98. - 156 - 1,000 ε shρ ε sh∞ = 1+ ϕ ⋅ t 0 1000 W=200kg/・ 800 Oita Univ. Okayama Univ. 600 W=220kg/・ 750 εsh ρ µ Ultimate shrinakge strain - 1200 500 W=180kg/・ 250 70N/mm2 400 0 28 56 84 0 0.000 112 Age at start of drying - days 0.005 0.010 50N/mm2 0.015 0.020 0.025 0.030 (C ompressive strength at 28days) Figure 23 Effect of start of drying -1 εshρ and concrete strength Figure 24 1,000 700 W=220kg/m 3 R.H.=68% 200 kg/m 3 750 εsh ρ εsh ρ 650 500 W=180 kg/m 3 600 250 550 170 180 190 200 210 220 0 0.0 230 0.1 Water content - kg/ m3 Figure 25 0.2 0.3 0.4 0.5 1-R.H./100 εshρ and water content Figure 26 εshρ and relative humidity Figure 23 shows a regression example for the relationship between ultimate shrinkage strain and age at the start of drying. It is clear that equation (4) expresses the relation well. Figure 24 shows the relationship between strength. This demonstrates that εsh∞ εshρ in equation (4) and the 28-day compressive εshρ can be expressed by a single curve as long as the water content of the concrete is constant. The curves in Figure 24 were drawn using equation (5). εshρ = Cρ 3 Cρ 2 1+ Cρ1 exp− f ' c (28) (5) Where, Cρ1 , Cρ 2 , Cρ 3 : the optimal value decided by regression. Figure 25 shows the relationship between εshρ in equation (4) and water content in the case of normal-strength concrete whose 28-day strength is less than 40 N/mm2. Further, Figure 26 shows the relationship between εshρ and relative humidity of the atmosphere. Both relationships can be regarded as linear. Equation (6) is derived from this finding. The coefficients in this equation were obtained by regression from experimental data. - 157 - 0.14 0.011 Data: RILEM 0.12 0.010 0.009 0.08 0.008 ϕ ϕ 0.10 0.06 0.007 0.04 0.006 0.02 0.005 0.00 75 Strength at 28 days - Figure 27 100 0.004 170 125 N/mm 2 Figure 28 1,000 +4 0 % Data : RILEM 750 % - 40 250 d ata=52 = 52 NumberNumber of dataofsets 0 0 250 500 750 1,000 Calculated ultimate shrinkage strain - µ Figure 29 Precision of new model for ultimate shrinkage strain εshρ = 190 200 210 220 230 Water content - kg/m 3 ϕ and concrete strength 500 180 1,500 ϕ and water content Data : JSCE Mesured in Japan OKADAI ('80s) +4 0% 50 Experimental ultimate shrinkage strain - µ 25 Experimental ultimate shrinkage strain - µ Data: RILEM 1,000 % - 40 500 NumberNumber of dataofsets d ata=310 = 310 0 0 500 1,000 1,500 Calculated ultimate shrinkage strain - µ Figure 30 Precision of new model for ultimate shrinkage strain α (1− h)W 500 1+ 150exp− f ' c (28) (6) Where, α : coefficient depending on the type of cement, h: relative humidity as a decimal, W: water content (kg/m3), f 'c (28) : 28-day concrete strength in compressive mode. When Japanese normal Portland cement is used, α is equal to 11. Figure 27 shows the relationship between factor ϕ in equation (4) and 28-day concrete strength. As is clear from this figure, the greater the concrete strength at 28 days, the higher the factor ϕ . Factor ϕ is also affected by the water content of concrete, as shown in Figure 28, with the relationship between the two being linear. This understanding leads to the following equation (where the coefficients were obtained by regression from experimental data): ϕ = 10−4 {15exp(0.007 f 'c (28)) + 0.25W } Where, f 'c (28) : concrete compressive strength at 28 days, W: water content (kg/m3). - 158 - (7) β V/S=25mm 45 t0=14days 40 t0=28days 35 30 t0=56days 25 20 170 180 190 200 210 220 230 70 Shrinkage development term - β Shrinkage development term - 50 Data: RILEM 50 30 10 0 Water content - kg/m 3 40 80 120 160 Volume-surface ratio - mm Figure 31 β and water content Figure 32 β and volume surface ratio The vertical axes of both Figure 29 and Figure 30 are the experimental values of ultimate shrinkage strain. The horizontal axes are the calculated ultimate shrinkage strain using equations (4), (5), (6), and (7). The data in Figure 29 are from the European database, while those in Figure 30 are from the Japanese one. In equation (6), the coefficient α for the type of cement is set as follows: Japanese normal Portland cement and slow-hardening Portland cement: α =11, Japanese rapid-hardening cement: α =15, European early hardening and high-strength cement: α =11, European normal and rapid-hardening cement: α =10, European slow-hardening cement: α =8. These values of coefficient α were obtained by regression from the experimental data. In fact, coefficient α also includes the effect of aggregate types used in different countries and other factors in addition to the concrete type. It is clear from the figures presented here that the difference between experimental ultimate shrinkage strains and shrinkage strains calculated using equations (4), (5), (6), and (7) is mostly within ±40%, and that the proposed prediction equation for ultimate shrinkage strain is very accurate. 3.2 Development of shrinkage strain Figure 31 plots coefficient β for the development of shrinkage strain against concrete water content. The relationship is linear, and the effect of water content on β is small when the start of drying is late; that is, at 56 days. On the other hand, Figure 32 plots the volume surface ratio of the specimen against coefficient β The greater the volume surface ratio of specimen, the bigger β These findings are expressed by the following equation: C ⋅ W + Cβ 3 ⋅ (V /S ) β 4 1+ Cβ 2 ⋅ t 0 β = Cβ 1 (8) Where, W: water content (kg/m3), V/S: volume surface ratio of the specimen (mm), Cβ 1 , Cβ 2 , Cβ 3 , and Cβ 4 : coefficients obtained by regression. Using regression to obtain coefficient Cβ 3 yields zero. The following equation was obtained. β= 4W V / S 100 + 0.7t 0 - 159 - (9) 1,000 Experimental shrinkage strain - % -20 500 -40 % 250 0 250 500 750 +4 0% +2 0 750 0 750 500 - 40 Number of data sets= 52 0 0 250 500 750 1,000 Calculated shrinkage strain - µ Figure 33 Precision of new prediction equation for shrinkage % 250 1,000 Calculated shrinkage strain - µ Figure 34 Precision of new prediction equation for shrinkage 1,500 +4 0% Data : CEB 1,000 % - 40 500 Number of data sets= 106 Data : JSCE +4 0% Experimental shrinkage strain - µ 1,250 µ Experimental shrinkage strain - Data : RILEM µ % Number of data sets= 92 +4 0% Experimental shrinkage strain - µ 1,000 1,000 0 750 - 40 500 % 250 Number of data sets= 43 0 0 500 1,000 Calculated shrinkage strain - 1,500 0 µ 250 500 750 1,000 Calculated shrinkage strain - Figure 35 Precision of new prediction equation for shrinkage 1,250 µ Figure 36 Precision of new prediction equation for shrinkage 3.3 Accuracy of proposed new prediction equation for shrinkage strain Figures 33 to 36 compare the experimental shrinkage strain with values calculated using the new prediction equation proposed in this study, as discussed above. Overall, the discrepancy between measured and calculated values is within approximately ± 40%, so the proposed prediction equation is very accurate and applicable to a wide range of concrete strengths from normal to high-strength concrete. 4. PROPOSED NEW CREEP PREDITION EQUATION 4.1 Effect of concrete strength on ultimate creep Figure 37 shows the relationship between ultimate specific creep and compressive strength at initial load application. By regression, the development of specific creep with time fits the hyperbola expressed by equation (10). - 160 - µ/(N/mm 2 ) Data : RILEM ○ : R.H.=48~50% □ : R.H.=65~75% ● : R.H.=99~100% 100 50 0 0 25 50 75 100 Compressive strength at loading - 125 N/mm 2 µ/(N/mm 2 ) 200 +2 0% Data : CEB ■ : Gravel Type-A (water absorption: 1.12%) ▲ : Gravel Type-B (water absorption: 1.07%) ● : Gravel Type-C (water absorption: 0.52%) 80 60 40 20 W=140kg/m 3 0 1.0 2.0 3.0 4.0 5.0 Cement-water ratio Figure 38 Relationship between ultimate creep and cement water ratio 150 200 Data : CEB 150 0% -2 100 50 Number of data sets = 118 0 0 50 100 150 Calculated specific creep strain - 200 µ/(N/mm 2 ) Figure 39 Accuracy when fitted to hyperbola Experimental specific creep strain - Experimental specific creep strain - µ/(N/mm 2 ) Figure 37 Relationship between ultimate creep and compressive strength 100 +2 0% 150 Ultimate specific creep - µ/( N/mm 2 ) Ultimate specific creep - 200 0 -2 % 100 50 Number of data sets = 118 0 0 50 100 150 Calculated specific creep strain - 200 µ/(N/mm 2 ) Figure 40 Accuracy when fitted to logarithmic curve Cr(t,t') = Cr∞ ⋅ (t − t') β cr + (t − t') (10) Where, Cr∞ : ultimate specific creep ( µ /N/mm2), β cr : term representing the development of specific creep, t: current age of concrete (days), t’: time at initial load application (days). This figure clearly shows that the greater the concrete strength, the smaller the ultimate specific creep. The variance from average is also small at high concrete strengths. The same result was obtained from an experiment with a different type of gravel. Figure 38 shows that the ultimate specific creep becomes small when the water-cement ratio is small and concrete strength is high. 4.2 Development of creep Figure 39 shows the results of fitting the specific creep to the hyperbola in equation (10). Similarly, Figure 40 shows the results of fitting specific creep to the logarithmic equation (11). - 161 - 20 R.H. = 60~65% Coefficient A - µ/(N/mm 2 ) Coefficient A - µ/(N/mm 2 ) 40 30 +40% 20 10 -40% 0 0 20 40 60 80 R.H. = 99~100% 15 10 100 120 Strength at application of load - N/mm 2 +40% 5 -40% 0 0 25 50 75 Strength at application of load - Figure 41 Relationship between coefficient A and compressive strength 100 125 N/mm 2 Figure 42 Relationship between coefficient A and compressive strength Cr(t,t') = Alog e (t − t' +1) (11) Where, A: coefficient obtained by regression, t: age of concrete (days), t’: age at initial load application (days). The discrepancy between experimental values of specific creep and the hyperbolic and logarithmic curves fitted to specific creep by regression is basically within ± 20%. However, dispersion increases as time passes when the hyperbola is used for regression. On the other hand, when the logarithmic curve is used, the discrepancy with experimental data is large at an early stage. However, at later times, the regressed value fits the experimental data more closely. More importantly, just one coefficient is required to express the development of specific creep when the logarithmic curve is. It is thus very simple and convenient to establish a creep prediction equation. Figures 41 and 42 show the relationship between coefficient A in equation (11) and concrete strength at initial load application. Figure 41 is for data measured at relative humidity levels between 60% and 65%. In Figure 42, on the other hand, the data were measured at relative humidity levels over 99%. It is clear from these figures that the relationship between coefficient A and concrete strength can be expressed by hyperbola. The lines fitted to the data in these figures are based on equation (12). A= Cα Cβ + f 'c (t) (12) Where, Cα , Cβ : coefficients obtained by regression, f 'c (t ): concrete compressive strength at initial load application (N/mm2). Figure 43 is a plot of coefficient A in equation (11) against the relative humidity of the atmosphere. The relationship is clearly linear. The relationship between coefficient A and water content is also linear, as seen in Figure 44. Equation (13) expresses this situation; when the relative humidity is 100%, then h=1 and the equation becomes that for basic creep. Thus, equation (13) separates the development of drying creep from the phenomenon of basic creep. A= Cdrying ⋅ W (1− h ) ϕ drying + f 'c (t) + - 162 - Cbasic ϕ basic + f 'c (t) (13) 25 Coefficient A - µ/(N/mm 2 ) Coefficient A - µ/(N/mm 2 ) 25 20 f'c(t)=30~40 N/mm2 15 f'c(t)=50~60 N/mm2 10 f'c(t)=70~80 N/mm2 5 0 0.0 f'c(t)=100~110 N/mm2 0.1 0.2 0.3 0.4 0.5 R.H. = 60~65% 20 R.H. = 45~50% 15 10 R.H. = 70~80% 5 0 100 0.6 120 140 160 180 200 220 240 Unit water content - kg/m 3 1-R.H./100 Figure 43 Relationship between coefficient A and relative humidity Figure 44 Relationship between coefficient A and water content of concrete Where, Cbasic , Cdrying , ϕ basic , ϕ drying : coefficients obtained by regression, h: relative humidity as a decimal, W: water content (kg/m3), f 'c (t ): compressive concrete strength (N/mm2). Obtaining every coefficient in equation (13) by regression shows that ϕ drying . The following equation can be derived as a consequence: Equation (14) is obtained by regression using the many data given in Figure 2. Factors with little influence were eliminated. For example, the last JSCE model includes the effect of specimen size and shape. However, the new creep prediction equation proposed in this study does not include this influence because regression showed it to be small. Figure 45 shows the effect of volume surface ratio of the specimen on the predicted ultimate specific creep by model CEB and the JSCE model. The predicted value at a volume surface ratio of 100 mm is just 1.2 times bigger than that for a ratio of 1,000 mm, even when model CEB is used. This difference is even smaller when the last JSCE model is used. Models B3 and GZ include the effect of specimen size in the factor for creep development. This factor was excluded from the new creep prediction equation for the purpose of simplification. µ/(N/mm 2 ) 4W (1 − h ) + 350 12 + f 'c (t) Ultimate specific creep - A= ϕ basic is almost the same as (14) 80.0 f'c(28)=50MPa, R.H.=80% W=180kg/m 3 , W/C=40.0% t'=3days 75.0 70.0 CEB model 65.0 JSCE model 60.0 0 250 500 750 1,000 1,250 V/S - mm Figure 45 Relation between ultimate creep and volume surface ratio 4.3 Accuracy of proposed new prediction equation for specific creep Figures 46 to 49 compare experimental measurements of specific creep with calculated values obtained by the new prediction equation proposed in this study. The discrepancy between measured values and predictions is generally within ±40%, so the proposed prediction equation is very accurate and applicable to a wide range of concrete strengths from normal to high. The new - 163 - equation is extremely simple, yet its accuracy is as good as that of the major conventional equations. 5. NEW PREDICTION EQUATIONS PROPOSED IN THIS STUDY To summarize, the newly proposed prediction equations for drying shrinkage are as follows: 100 % - 40 50 Number of data sets = 146 0 (16) 100 Calculated specific creep strain - 150 µ/(N/mm 2 ) µ/(N/mm 2 ) 250 +4 0% Data : CEB 200 150 - 40 100 % 50 Number of data sets= 118 0 0 50 100 150 Calculated specific creep strain - 200 Data : RILEM 200 150 % - 40 100 50 Number of data sets= 140 0 0 50 100 150 200 Calculated specific creep strain - 250 µ/(N/mm 2 ) Figure 47 Precision of proposed model 250 µ/(N/mm 2 ) Experimental specific creep strain - Experimental specific creep strain - µ/(N/mm 2 ) Figure 46 Precision of proposed model 250 Figure 48 Precision of proposed model 150 Data : JSCE +4 0% 50 εshρ 1 + η ⋅ t0 µ/(N/mm 2 ) +4 0% 150 0 (15) Experimental specific creep strain - Experimental specific creep strain - µ/(N/mm 2 ) εsh∞ = εsh∞ ⋅ (t − t0 ) β + (t − t0 ) +4 0% εsh (t,t0 ) = 100 % - 40 50 Number of data sets= 37 0 0 50 100 Calculated specific creep strain - 150 µ/(N/mm 2 ) Figure 49 Precision of proposed model - 164 - εshρ = α (1− h)W 500 1+ 150exp− f ' c (28) η = 10−4 {15exp(0.007 f 'c (28)) + 0.25W } β= Where 4W V / S 100 + 0.7t 0 (17) (18) (19) εsh (t,t 0 ): drying shrinkage strain ( µ ), t, t0: current age and age at drying (days), when age at drying > 98 days, t0=98. f 'c (28) : compressive strength at 28 days (N/mm2) ( f 'c (28) <120 N/mm2), h: relative humidity of atmosphere (0.4<h<0.9), W: unit water content (130<W<230 kg/m3), V/S: volume surface ratio of specimen (100<V/S<1,000mm), α : factor accounting for cement type (Japanese data: α = 11 for normal cement and α = 15 for rapid-hardening cement; Western data: α = 10 for normal Portland cement and α = 8 for slow-hardening cement). The newly proposed prediction equation for creep is as follows: Cr(t,t') = 4W (1− h ) + 350 ⋅ log e (t − t'+1) 12 + f ' c (t') (20) Where, Cr(t,t'): specific creep ( µ /N/mm2), h: relative humidity of the atmosphere (0.4<h<0.9), W: unit water content (130<W<230 kg/m3), t’: time at initial load application (days) (t’>1), f 'c (t ) : compressive strength at age t (N/mm2) ( f 'c (t )<120N/mm2). 6. CONCLUSION New prediction equations for creep and shrinkage have been proposed and their accuracy investigated. The equations are based on a model established by statistical methods. The investigation results demonstrate that the proposed equations are able to predict concrete creep and shrinkage strain to a certain degree of accuracy. The new shrinkage equation takes into account a number of influences. In particular, it takes account of the finding that the effect of water content on ultimate shrinkage strain depends on concrete strength, and that the effect of concrete strength on ultimate shrinkage strain is much higher than that of water content when the concrete strength is high. The proposed creep equation is very simple, and specific creep can be predicted on the basis of just three items of data: compressive strength, relative humidity of the atmosphere, and water content. Despite this simplicity, it is able to predict the specific creep of concrete from normal strength to high strength with accuracy equivalent to that of typical conventional prediction equations. The proposed prediction equations offer a simple design procedure for calculating creep and shrinkage using information available at the design stage. References [1] abc, edf: dog cat pen abc, abifdasd fdsafda fdsadas. Fdsafdsa fdassdf ise, dfasdfa fdasfda, fdsafd fdsaf fdsafa fda, 2002 - 165 - [2] ACI Committee 209: Prediction of creep and shrinkage, and temperature effects on concrete structures, American Concrete Institute Special Publication No.76, 1982. [3] JSCE: Standard specification for design and construction of concrete and structures, 1996. [4] RILEM TC 107 Subcommittee 5: Database on creep and shrinkage tests - 3.0, 1999. [5] Dilger, W. H.: Private communication. [6] JSCE committee 308: Concrete shrinkage and creep, Concrete Engineering Series, N0.24, pp.56~93, 1997 (in Japanese). [7] Comite Euro-International du Beton: CEB-FIP MODEL CODE 1990 (DESIGN CODE), Thomas Telford, pp.52~65, 1998. [8] Bazant, Z. P. and Baweja, S.: Creep and shrinkage prediction model for analysis and design of concrete structures - Model B3, Materials and Structures, RILEM, Paris, France, Vol. 28, pp.357~365, 1995. [9] Gardner, N. J.: Design Provisions for Shrinkage and Creep of Concrete, Proceedings of International Conference on Engineering Material, Ottawa, Canada, Vol.1, pp.647~657, 1997. [10] CEB-FIP: International Recommendations for the Design and Construction of Concrete Structures - Principles and Recommendations, Comite Europeen du Beton - Federation Internationale de la Precontrainte, FIP Sixth Congress, Prague, June 1970; published by Cement and Concrete Association: London, 1970. [11] Bazant, Z. P. and Panula, L.: Simplified prediction of concrete creep and shrinkage from strength and mix, Structural Engineering Reports No.78-10/6405, Department of Civil Engineering, Northwestern University, Evanston, Illinois, pp.24, Oct. 1978. [12] Kiyoshi Okada, Toyoki Akashi, and Wataru Koyanagi, Construction Materials for Civil Engineering, Kokumin Kagaku-sya, p.193, 1998 (in Japanese). - 166 -