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A yield curvature model considering axial compression ratio
Advances in Bridge Engineering volume 4, Article number: 19 (2023)
Abstract
This study proposed a yield curvature prediction model considering axial compression ratio with exponential function which is improved on the basis of the specification effective yield curvature prediction model. Parametric moment–curvature curves approach was used to verify that the yield curvature is greatly affected by the section size, the yield strength of longitudinal steel bar and the axial compression ratio. On the basis, the yield curvature under different levels was obtained by Xtract and parametric moment–curvature curves approach, the result shows that with the increase of axial compression ratio, the yield curvature also increases, which is roughly a linear relationship. Subsequently, combined with the specification and considering the influence of axial compression ratio, a new yield curvature prediction model is proposed based on a massive sample space obtained by parametric moment–curvature curves approach. Moreover, by comparing with the experimental database of PEER, the accuracy of new prediction model is verified, and the result shows that the new prediction model is suitable for estimating yield curvature of square section columns.
1 Introduction
Bridge columns are structural elements that support the weight of the bridge. These columns are subject to various types of loads, including horizontal and vertical loads, and moments caused by bridge displacement. The design of the column is crucial to the safety and reliability of the structure, and the failure of the column will lead to catastrophic consequences (Cornell et al. 2002). Axial compression ratio is an important design parameter that significantly affects the seismic performance of columns. This is demonstrated in prediction models proposed by researchers. Ho (Ho and Pam 2010) proposed a prediction model of curvature in collapse damage state, in which the axial compression ratio is an important parameter. Moreover, in the specification, the axial compression ratio plays a crucial role in collapse damage state (Ministry 2020). However, for the effective yield curvature, the influence of axial compression ratio has not been considered by some researchers and specifications (Ministry 2020; Olivia and Mandal 2005; En 2005; ATC-40. 1996). The effective yield curvature is obtained from the actual moment–curvature curve equivalent to the ideal elastic–plastic moment–curvature curve, and the ideal elastic–plastic moment–curvature curve must pass through the point corresponding to the yield curvature, but it is different from the definition of yield curvature, moreover, some scholars have considered the influence of axial compression ratio in the yield curvature prediction model (Hernández-Montes and Aschleim 2003; Zhong et al. 2022a). In the prediction model proposed by Hernández (2003), the yield curvature increases with the increase of axial compression ratio. The yield curvature prediction model proposed by Zhong (Zhong et al. 2022a) also considers the influence of axial compression ratio, the yield and effective yield curvature prediction model proposed by scholars and specifications is shown in Table 1. Although the yield curvature prediction models proposed by Hernández (2003) and Zhong (2022a) have been verified, there are still the following problems: (1) it is inconvenient to remember; (2) prediction model is not applicable when the axial compression ratio is 0.
Finite element analysis has become a popular choice among researchers for studying bridge columns due to its advantages in terms of resource efficiency and convenience, as compared to experimental methods. With the aid of finite element analysis software, scholars extensively investigate and optimize the design of bridge columns. Su (2019) obtained the yield curvature of bridge columns using Xtract and implemented it into a formula to calculate the displacement of steel reinforcement slip. Zhang (2020) studied the factors affecting the top displacement of high-strength column through ABAQUS. Aldabagh (2022) deduced the prediction model of drift ratio of different damage states by establishing samples with OpenSees. Therefore, Xtract was employed as a tool to validate the yield curvature in this study.
In this study, the yield curvature is first defined, and the section information of the columns is replaced by the expression by using the parametric moment–curvature (M-φ) curves approach (PMCA), and the M-φ curves can be obtained based on the plane hypothesis model and the stress–strain models of longitudinal reinforcement and concrete. On this basis, PMCA was employed to discuss the influence of section size (L), axial compression ratio (Rac), longitudinal reinforcement ratio (ρl), stirrup reinforcement ratio (ρs), concrete compressive strength (fco) and yield strength of longitudinal steel bar (fy) on yield curvature, and then remove the parameters that have little effect on yield curvature. On this basis, some levels under different L, fy and Rac were set, and the yield curvature was obtained by Xtract and PMCA and compared. Moreover, some columns whose failure form is flexural failure are selected and the experimental yield curvature is obtained. The yield curvature prediction model considering the influence of Rac was proposed based on a massive sample space obtained by PMCA and compared it with experiments.
2 Definition of yield curvature
The order of failure of the bridge column is as follows: the cracks first occur, then the first yielding of longitudinal steel bars is observed, followed by the spalling of the cover concrete, the crushing of the core concrete, and the fracture of the stirrup in the final stage. The section curvature corresponding to the first yielding of longitudinal steel bars is taken as the yield curvature (φy) of column in this study, as shown in Fig. 1. Strain can be used as an index to judge the damage state (Calvi and Kingsley 1995; Priestley et al. 1996). When the strain of the longitudinal steel bars reaches, it can be considered that the longitudinal steel bars has yielded for the first time, and the corresponding curvature is φy.
Definition of yield curvature
3 Parametric M-φ curves approach
Zhong (2022a) proposed a parametric moment–curvature (M-φ) curves approach (PMCA), which transformed discrete longitudinal steel bars into ‘steel loop’, the thickness of the ‘steel loop’ can be approximately represented to d0 = (ρlLW) / (2L + 2W-4C0), where L and W are the size of the bridge column section, C0 is cover concrete thickness, and so that three important parts (cover concrete, core concrete and longitudinal steel bars) are continuous sections. Each part can be represented by thickness information: Tuc, Tcc, and Ts, as shown in Fig. 2. Then, based on the plane hypothesis model and the stress–strain model of concrete (proposed by Mander et al. (1988)) and steel (steel01), the balance between the axial force and the reaction force of the column is established and moment is obtained. The stress–strain model is shown in Fig. 3, where εco, εcc and εcu are peak strain of cover concrete, peak strain of core concrete and ultimate strain of core concrete, fco and fcc are the compressive strength of cover and core concrete, b is strain-hardening ratio.
Parametric M-φ curves approach
a Concrete04; and b Steel01 model
The φy prediction model proposed by Zhong (2020) does not consider the influence of fy, and the φy cannot be calculated when the Rac is 0. Therefore, this study attempts to establish a φy prediction model of six parameters, and then remove the parameters that have little influence on the yield curvature. 96(531,441) levels are established to fit the prediction model through PMCA, and the parameters information is shown in the Table 2.
The exponential function is used for fitting to directly obtain the influence of each parameter on φy. The form of the expression is as follows:
where a, a1, a2, a3, a4, a5, a6 are coefficients of exponential function. The greater the absolute value of a1 to a6, the greater the influence of parameters on φy. The fitted expression is shown in Eq. 2.
By comparing the fitted expression and PMCA in Fig. 4, the effect is not bad. From the fitted expression, φy is significantly influenced by L and fy, and as fy increases or L decreases, the φy increase accordingly, as reported in previous studies. Priestley ( 1998) reported that L and fy have a great influence on the curvature of the slight limit state, which is inversely proportional to L and proportional to fy. The coefficient of (1-Rac) is also high, therefore, based on the effective yield curvature prediction model combined with the specification, this study proposes a yield curvature prediction model considering Rac. Hernández ( 2003) studied that as Rac increases, the curvature of the slight limit state also increases, which is consistent with Eq. 2.
Comparison of fitted expression with PMCA
4 Comparison between numerical simulation and PMCA
4.1 Finite element model
Xtract was used in this study to verify the accuracy of PMCA and provide a control group for subsequent studies. According to the main influence parameters obtained by PMCA, some levels of different L, fy and Rac are set, as shown in Table 3.
Xtract is an effective software for obtaining φy, which can calculate the moment–curvature curve of column section and output φy directly. Therefore, a square section column was established by Xtract, and the parameters of cover concrete, core concrete and longitudinal steel bars are defined. The cover and core concrete material model proposed by Mander et al. (Mander et al. 1988) are adopted in Xtract. In this study, the concrete grade is C50, the cover concrete strength is 32.4 MPa. The core concrete strength is 42.1 MPa in Test 1 and 42.8 MPa in Test 3. The yield strain of core concrete is 0.0035 in Test 1 and 0.00365 in Test 3. The elastic modulus of cover and core concrete is 3.45 × 104 MPa. The longitudinal reinforcement ratio is 1.13%, the yield strength of stirrup is 360 MPa, the stirrup ratio is 1%, and the thickness of cover concrete is 0.04 m, the other parameters are shown in Table 3, the units are divided according to the default length.
4.2 Comparison
By applying Xtract and PMCA, the yield curvature of all conditions in Table 3 is calculated and compared. On the one hand, the trend of yield curvature with the change of Rac can be seen. On the other hand, Xtract can be set as the control group to verify the accuracy of PMCA. The comparison results are shown in Fig. 5. The error rate = 100% × (PMCA—Xtract) / Xtract.
Comparison between specification and numerical simulation: a Test 1; b Test 2; and c Test 3
From the comparison of the two, the above two problems can be easily solved: (1) With the increase of Rac, the yield curvature also increases, which is roughly a linear relationship; (2) The calculation results of PMCA and Xtract are very close, the error between the two is about 3%, and the maximum is only 5%. Therefore, PMCA can replace Xtract as the main tool to obtain yield curvature in the follow study. In addition, considering that the influence of longitudinal steel bars into ‘steel loop’, the yield curvature of PMCA is always smaller than Xtract. However, this is beneficial to engineering design and can leave a certain safety space for the project.
5 Experimental data
The experiment of PEER database is integrated here (Nagasaka 1982; Imai and Yamamoto 1986; Zhou et al. 1987; Arakawa et al. 1989; Umehara 1983; Bett et al. 1985; Aboutaha et al. 1999; Iwasaki et al. 1985; Priestley et al. 1994; Pandey and Mutsuyoshi 2005; Yoshimura et al. 1991; Hassane 2002; Nakamura and Yoshimura 2002; Moehle 2000; Wight 1973; Lynn et al. 1996; Pandey and Mutsuyoshi 2005; Nagasaka 1982; Ohue et al. 1985; Ono and Shimizu 1985; Ono 1989; Amitsu et al. 1991; Wight 1973; Lynn et al. 1996; Xiao and Martirossyan 1998; Sezen and Moehle 2002; Iwasaki et al. 1985; Ikeda 1968; Umemura and Endo 1970; Hirosawa 1973; Yalcin 1997; Elwood and Moehle 2008; Saatcioglu and Ozcebe 1989; Esaki 1996; Lynn et al. 1996; Yoshimura et al. 2003; Yarandi 2007; Pandey and Mutsuyoshi 2005; Yoshimura and Yamanaka 2000; Gill 1979; Ang 1981; Soesianawati 1986; Zahn 1985; Watson 1989; Tanaka 1990; Park and Paulay 1990; Arakawa et al. 1982; Ohno and Nishioka 1984; Zhou et al. 1987; Kanda 1988; Muguruma et al. 1989; Sakai 1990; Atalay and Penzien 1975; Azizinamini et al. 1988; Saatcioglu and Ozcebe 1989; Galeota et al. 1996; Wehbe 1998; Xiao and Martirossyan 1998; Sugano 1996; Nosho et al. 1996; Bayrak and Sheikh 1996; Saatcioglu and Grira 1999; Matamoros 1999; Mo and Wang 2000; Aboutaha and Machado 1999; Thomson and Wallace 1994; Legeron and Paultre 2000; Paultre et al. 2001; Pujol 2002; Kono and Watanabe 2000; Harries et al. 2006; Melek and Wallace 2004). The distribution of L, Rac and fy are represented by the histogram and the cumulative probability, as shown in Fig. 6. It can be seen that L and Rac are roughly logarithmic normal distribution, with mean values of 0.317m and 0.242, respectively, while fy is roughly uniform distribution, with mean value of 429MPa.
The experimental columns parameter distribution of PEER database: a L; b Rac; c fy
The research object of this paper is mainly the bridge column with flexural failure. In order to ensure that the bridge column is flexural failure, only the shear span ratio not less than 2.5 (H/L ≥ 2.5) and the square section bridge column of ordinary reinforced concrete are retained. Therefore, the stacked bar charts for the column physical parameters are shown in Fig. 7, fyh is the yield strength of stirrups; H/L is the column aspect ratio.
Stacked bar chart of column physical parameters
According to the yield displacement method proposed by Priestley and Park (Eq. 3), the yield displacement of these experiments is marked in the hysteresis curve, and the results are shown in Fig. 8.
Yield displacement and yield curvature of experiment
6 Prediction model combined with Chinese specification
6.1 New prediction model
Considering that the effective yield curvature is close to the yield curvature, so the prediction model of yield curvature is derived based on the effective yield curvature prediction model of Chinese specification. Based on the accuracy of PMCA, and this study removes some less influential parameters to use easily, a new prediction model is proposed which combines the exponential function considering the influence of Rac with the Chinese specification. A large number of levels are obtained by PMCA, the parameters information is shown in Table 2. The new prediction model is not complex and is more suitable for researchers to use directly. The prediction model is as follows:
where the first part is the Chinese specification effective yield curvature prediction model, b1 and b2 are the coefficients. The values of b1 and b2 are fitted by the least square method. Finally, the prediction model of φy combined with Chinese specification is Eq. 5. The experimental axial compression ratios of the retained PEER database are all brought into the new prediction model, and the average value of the coefficients is calculated, the coefficient is 1.82, it shows that the yield curvature is about 0.1 times smaller than the coefficient of effective yield curvature (1.957).
6.2 Application of the prediction model
In order to verify the accuracy of the new prediction model, the yield curvature obtained from the experiment is compared with the predicted, and the results are shown in the Table 4 and Fig. 9.
Comparison between experiment and new model
From the comparison in Fig. 9 and Table 4, it can be seen that the results of the experiment and the prediction are very close, and the error rate is kept within -20% ~ 20%, and most of them are less than 0%. This shows that the predicted yield curvature is often smaller than the experiment, which also provides a certain safety space for practical projects. In addition, the reason why some errors are relatively large may be that the data source of the new prediction model is determined according to the set condition range. There will be some errors outside the range, but the error is still guaranteed to be within a relatively small range. Therefore, the prediction model can be used to predict the yield curvature of practical engineering.
7 Conclusions
The main purpose of this paper is to study the influence of axial compression ratio on yield curvature, and propose a prediction model considering the axial compression ratio based on the effective yield curvature prediction model of Chinese specification. To achieve this goal, parametric moment–curvature curves approach (PMCA) is adopted to verify that section size, the yield strength of longitudinal steel bar and the axial compression ratio have great influence on yield curvature. Then, some levels under different section size, the yield strength of longitudinal steel bar and the axial compression ratio were set, and the yield curvature was obtained by Xtract and PMCA and compared, the result shows that the yield curvature increases with the increase of the axial compression ratio. Besides, a new prediction model is proposed by combining the exponential function with effective yield curvature prediction model of Chinese specification, the yield curvature of the database of PEER is compared with the new prediction model. Through the above research, the following conclusions can be obtained:
-
(1)
The numerical simulation result shows that yield curvature increases with the increase of the axial compression ratio, and the growth trend is obvious, which is different from the specifications effective yield curvature prediction model.
-
(2)
The yield curvature prediction model proposed in this study can well predict the yield curvature of the experiment, and the error is between -20% and 20%, and most of them are concentrated near -10%. The negative error indicates that the prediction is smaller than the experiment, indicating that retaining a certain safety space and it is beneficial to the actual project.
In this paper, a simplified prediction model of yield curvature is proposed, which provides a convenient tool for the design of bridge columns in practical engineering. However, this paper only studies the square cross-section column and cannot predict the curvature of the limit state after the column yield. In the future research, we will make up for these deficiencies.
8 Appendix
# | Reference | ID | f c (MPa) | f y (MPa) | f yh (MPa) | L (m) | W (m) | R ac | ρ l (%) | ρ s (%) |
|---|---|---|---|---|---|---|---|---|---|---|
1 | Nagasaka 1982) | HPRC10-63 | 21.6 | 371 | 344 | 0.20 | 0.20 | 0.17 | 1.27 | 0.80 |
2 | Imai and Yamamoto 1986) | UNIT_1 | 27.1 | 318 | 336 | 0.50 | 0.40 | 0.07 | 2.66 | 0.40 |
3 | Zhou et al. 1987) | No.104–08 | 19.8 | 341 | 559 | 0.16 | 0.16 | 0.80 | 2.22 | 0.70 |
4 | Zhou et al. 1987) | No.114–08 | 19.8 | 341 | 559 | 0.16 | 0.16 | 0.80 | 2.22 | 0.70 |
5 | Zhou et al. 1987) | No.124–08 | 19.8 | 341 | 559 | 0.16 | 0.16 | 0.80 | 2.22 | 1.80 |
6 | Arakawa et al. 1989) | OA2 | 31.8 | 340 | 249 | 0.18 | 0.18 | 0.18 | 3.13 | 0.20 |
7 | Arakawa et al. 1989) | OA5 | 33.0 | 340 | 249 | 0.18 | 0.18 | 0.45 | 3.13 | 0.20 |
8 | Umehara 1983) | CUS | 34.9 | 441 | 414 | 0.41 | 0.23 | 0.16 | 3.01 | 0.30 |
9 | Umehara 1983) | CUW | 34.9 | 441 | 414 | 0.23 | 0.41 | 0.16 | 3.01 | 0.30 |
10 | Bett et al. 1985) | UNIT_1_1 | 29.9 | 462 | 414 | 0.31 | 0.31 | 0.10 | 2.44 | 0.30 |
11 | Aboutaha et al. 1999) | SC3 | 21.9 | 434 | 400 | 0.46 | 0.91 | 0.00 | 1.88 | 0.27 |
12 | Aboutaha et al. 1999) | SC9 | 16.0 | 434 | 400 | 0.91 | 0.46 | 0.00 | 1.88 | 0.20 |
13 | Iwasaki et al. 1985) | I18 | 33.1 | 323 | 258 | 0.50 | 0.50 | 0.00 | 2.12 | 0.47 |
14 | Iwasaki et al. 1985) | I21 | 31.7 | 323 | 258 | 0.50 | 0.50 | 0.00 | 2.12 | 0.47 |
15 | Priestley et al. 1994) | UnitR3A | 34.5 | 469 | 324 | 0.41 | 0.61 | 0.06 | 2.53 | 0.23 |
16 | Priestley et al. 1994) | UnitR5A | 32.4 | 469 | 324 | 0.41 | 0.61 | 0.06 | 2.53 | 0.23 |
17 | Priestley et al. 1994) | Specimen_B1 | 32.5 | 380 | 396 | 0.30 | 0.30 | 0.03 | 2.68 | 0.18 |
18 | Pandey and Mutsuyoshi 2005) | Specimen_CE | 26.0 | 388 | 312 | 0.18 | 0.18 | 0.10 | 3.08 | 0.70 |
19 | Yoshimura et al. 1991) | Specimen_BE | 32.7 | 344 | 312 | 0.18 | 0.18 | 0.10 | 3.08 | 0.70 |
20 | Yoshimura et al. 1991) | Specimen_LE | 41.5 | 344 | 322 | 0.18 | 0.18 | 0.10 | 6.94 | 3.78 |
21 | Yoshimura et al. 1991) | No.1 | 30.7 | 402 | 392 | 0.30 | 0.30 | 0.20 | 2.68 | 0.47 |
22 | Yoshimura et al. 1991) | No.3 | 30.7 | 402 | 392 | 0.30 | 0.30 | 0.20 | 2.68 | 0.24 |
23 | Yoshimura et al. 1991) | No.4 | 30.7 | 402 | 392 | 0.30 | 0.30 | 0.30 | 2.68 | 0.47 |
24 | Yoshimura et al. 1991) | C1 | 13.5 | 340 | 587 | 0.30 | 0.30 | 0.30 | 1.69 | 0.20 |
25 | Hassane 2002) | C4 | 13.5 | 340 | 587 | 0.30 | 0.30 | 0.30 | 1.69 | 0.69 |
26 | Hassane 2002) | C8 | 18.0 | 340 | 384 | 0.30 | 0.30 | 0.30 | 1.69 | 0.69 |
27 | Hassane 2002) | C12 | 18.0 | 340 | 384 | 0.30 | 0.30 | 0.20 | 1.69 | 0.69 |
28 | Hassane 2002) | D1 | 27.7 | 447 | 398 | 0.30 | 0.30 | 0.22 | 1.69 | 1.03 |
29 | Hassane 2002) | D11 | 28.1 | 447 | 398 | 0.30 | 0.30 | 0.21 | 2.25 | 0.34 |
30 | Hassane 2002) | D12 | 28.1 | 447 | 398 | 0.30 | 0.30 | 0.21 | 2.25 | 0.34 |
31 | Hassane 2002) | D13 | 26.1 | 447 | 398 | 0.30 | 0.30 | 0.23 | 2.25 | 1.03 |
32 | Hassane 2002) | D14 | 26.1 | 447 | 398 | 0.30 | 0.30 | 0.23 | 2.25 | 1.03 |
33 | Hassane 2002) | D16 | 26.1 | 447 | 398 | 0.30 | 0.30 | 0.23 | 1.69 | 1.03 |
34 | Hassane 2002) | N-18 M | 26.5 | 380 | 380 | 0.30 | 0.30 | 0.18 | 2.68 | 0.53 |
35 | Nakamura and Yoshimura 2002) | N-27C | 26.5 | 380 | 380 | 0.30 | 0.30 | 0.27 | 2.68 | 0.53 |
36 | Nakamura and Yoshimura 2002) | N-27 M | 26.5 | 380 | 380 | 0.30 | 0.30 | 0.27 | 2.68 | 0.53 |
37 | Nakamura and Yoshimura 2002) | S-1 | 25.1 | 547 | 355 | 0.40 | 0.40 | 0.20 | 3.87 | 0.45 |
38 | Moehle 2000) | WI_0_033E | 32.0 | 496 | 345 | 0.31 | 0.15 | 0.00 | 2.45 | 0.33 |
39 | Wight 1973) | 3CLH18 | 26.9 | 331 | 400 | 0.46 | 0.46 | 0.09 | 3.03 | 0.16 |
40 | Lynn et al. 1996) | A1 | 28.8 | 380 | 396 | 0.30 | 0.30 | 0.03 | 2.68 | 0.30 |
41 | Pandey and Mutsuyoshi 2005) | HPRC19-32 | 21.0 | 371 | 344 | 0.20 | 0.20 | 0.35 | 1.27 | 1.40 |
42 | Nagasaka 1982) | 2D16RS | 32.0 | 369 | 316 | 0.20 | 0.20 | 0.14 | 2.01 | 0.60 |
43 | Ohue et al. 1985) | 4D13RS | 29.9 | 370 | 316 | 0.20 | 0.20 | 0.15 | 2.65 | 0.60 |
44 | Ohue et al. 1985) | No.1007 | 34.0 | 336 | 341 | 0.08 | 0.08 | 0.70 | 1.77 | 0.50 |
45 | Ono and Shimizu 1985) | No.204–08 | 21.1 | 341 | 559 | 0.16 | 0.16 | 0.80 | 2.22 | 0.70 |
46 | Ono and Shimizu 1985) | No.223–09 | 21.1 | 341 | 559 | 0.16 | 0.16 | 0.90 | 2.22 | 1.80 |
47 | Ono and Shimizu 1985) | No.302–07 | 28.8 | 341 | 559 | 0.16 | 0.16 | 0.70 | 2.22 | 0.70 |
48 | Ono and Shimizu 1985) | No.312–07 | 28.8 | 341 | 559 | 0.16 | 0.16 | 0.70 | 2.22 | 0.70 |
49 | Ono and Shimizu 1985) | CA025C | 25.8 | 361 | 426 | 0.20 | 0.20 | 0.26 | 2.13 | 0.90 |
50 | Ono 1989) | CA060C | 25.8 | 361 | 426 | 0.20 | 0.20 | 0.62 | 2.13 | 0.90 |
51 | Ono 1989) | CB060C | 46.3 | 441 | 414 | 0.28 | 0.28 | 0.74 | 2.75 | 0.90 |
52 | Amitsu et al. 1991) | WI_40_033aE | 34.7 | 496 | 345 | 0.31 | 0.15 | 0.12 | 2.45 | 0.33 |
53 | Wight 1973) | WI_40_033aW | 34.7 | 496 | 345 | 0.31 | 0.15 | 0.12 | 2.45 | 0.33 |
54 | Wight 1973) | WI_40_048E | 26.1 | 496 | 345 | 0.31 | 0.15 | 0.15 | 2.45 | 0.48 |
55 | Wight 1973) | WI_40_048W | 26.1 | 496 | 345 | 0.31 | 0.15 | 0.15 | 2.45 | 0.48 |
56 | Wight 1973) | WI_40_033_E | 33.6 | 496 | 345 | 0.31 | 0.15 | 0.11 | 2.45 | 0.33 |
57 | Wight 1973) | WI_40_033_W | 33.6 | 496 | 345 | 0.31 | 0.15 | 0.11 | 2.45 | 0.33 |
58 | Wight 1973) | WI_25_033_E | 33.6 | 496 | 345 | 0.31 | 0.15 | 0.07 | 2.45 | 0.33 |
59 | Wight 1973) | WI_25_033_W | 33.6 | 496 | 345 | 0.31 | 0.15 | 0.07 | 2.45 | 0.33 |
60 | Wight 1973) | WI_0_048W | 25.9 | 496 | 345 | 0.31 | 0.15 | 0.00 | 2.45 | 0.48 |
61 | Wight 1973) | WI_40_067_E | 33.4 | 496 | 345 | 0.31 | 0.15 | 0.11 | 2.45 | 0.70 |
62 | Wight 1973) | WI_40_067_W | 33.4 | 496 | 345 | 0.31 | 0.15 | 0.11 | 2.45 | 0.70 |
63 | Wight 1973) | WI_40_147_E | 33.5 | 496 | 317 | 0.31 | 0.15 | 0.11 | 2.45 | 1.50 |
64 | Wight 1973) | WI_40_147_W | 33.5 | 496 | 317 | 0.31 | 0.15 | 0.11 | 2.45 | 1.50 |
65 | Wight 1973) | WI_40_092_E | 33.5 | 496 | 317 | 0.31 | 0.15 | 0.11 | 2.45 | 0.90 |
66 | Wight 1973) | WI_40_092_W | 33.5 | 496 | 317 | 0.31 | 0.15 | 0.11 | 2.45 | 0.90 |
67 | Wight 1973) | 2CLH18 | 33.1 | 331 | 400 | 0.46 | 0.46 | 0.07 | 1.94 | 0.16 |
68 | Lynn et al. 1996) | 2CMH18 | 25.5 | 331 | 400 | 0.46 | 0.46 | 0.28 | 1.94 | 0.16 |
69 | Lynn et al. 1996) | 2SLH18 | 33.1 | 331 | 400 | 0.46 | 0.46 | 0.07 | 1.94 | 0.16 |
70 | Lynn et al. 1996) | 3SMD12 | 25.5 | 331 | 400 | 0.46 | 0.46 | 0.28 | 3.03 | 0.41 |
71 | Lynn et al. 1996) | HC4-0.1P | 86.0 | 510 | 449 | 0.25 | 0.25 | 0.10 | 2.46 | 1.60 |
72 | Xiao and Martirossyan 1998a) | HC4-0.2P | 86.0 | 510 | 449 | 0.25 | 0.25 | 0.19 | 2.46 | 1.60 |
73 | Xiao and Martirossyan 1998a) | Specimen_1 | 21.1 | 434 | 476 | 0.46 | 0.46 | 0.15 | 2.48 | 0.20 |
74 | Sezen and Moehle 2002) | Specimen_2 | 21.1 | 434 | 476 | 0.46 | 0.46 | 0.61 | 2.48 | 0.20 |
75 | Sezen and Moehle 2002) | Specimen_4 | 21.8 | 434 | 476 | 0.46 | 0.46 | 0.15 | 2.48 | 0.20 |
76 | Sezen and Moehle 2002) | I_03 | 30.7 | 323 | 258 | 0.40 | 0.80 | 0.00 | 1.42 | 0.61 |
77 | Iwasaki et al. 1985) | I_04 | 28.4 | 323 | 258 | 0.40 | 0.80 | 0.00 | 1.77 | 0.61 |
78 | Iwasaki et al. 1985) | I_10 | 31.2 | 323 | 258 | 0.50 | 0.50 | 0.00 | 2.12 | 0.47 |
79 | Iwasaki et al. 1985) | I_14 | 32.0 | 323 | 258 | 0.50 | 0.50 | 0.00 | 2.12 | 0.47 |
80 | Iwasaki et al. 1985) | I_16 | 31.8 | 323 | 258 | 0.50 | 0.50 | 0.00 | 2.12 | 0.47 |
81 | Iwasaki et al. 1985) | I_17 | 31.8 | 323 | 258 | 0.50 | 0.50 | 0.00 | 2.12 | 0.47 |
82 | Iwasaki et al. 1985) | I_20 | 33.3 | 323 | 258 | 0.50 | 0.50 | 0.00 | 2.12 | 0.47 |
83 | Iwasaki et al. 1985) | I_25 | 33.0 | 323 | 258 | 0.50 | 0.50 | 0.00 | 2.12 | 2.37 |
84 | Iwasaki et al. 1985) | IK_43 | 19.6 | 434 | 559 | 0.20 | 0.20 | 0.10 | 1.99 | 0.66 |
85 | Ikeda 1968) | IK_44 | 19.6 | 434 | 559 | 0.20 | 0.20 | 0.10 | 1.99 | 0.66 |
86 | Ikeda 1968) | IK_45 | 19.6 | 434 | 559 | 0.20 | 0.20 | 0.20 | 1.99 | 0.66 |
87 | Ikeda 1968) | IK_46 | 19.6 | 434 | 559 | 0.20 | 0.20 | 0.20 | 2.66 | 0.66 |
88 | Ikeda 1968) | IK_62 | 19.6 | 345 | 476 | 0.20 | 0.20 | 0.10 | 1.97 | 0.67 |
89 | Ikeda 1968) | IK_63 | 19.6 | 345 | 476 | 0.20 | 0.20 | 0.20 | 1.97 | 0.67 |
90 | Ikeda 1968) | IK_64 | 19.6 | 345 | 476 | 0.20 | 0.20 | 0.20 | 1.97 | 0.67 |
91 | Ikeda 1968) | UM_205 | 17.6 | 462 | 324 | 0.20 | 0.20 | 0.22 | 1.99 | 0.61 |
92 | Umemura and Endo 1970) | UM_207 | 17.6 | 462 | 324 | 0.20 | 0.20 | 0.22 | 1.99 | 0.61 |
93 | Umemura and Endo 1970) | UM_214 | 17.6 | 462 | 324 | 0.20 | 0.20 | 0.56 | 1.99 | 0.31 |
94 | Umemura and Endo 1970) | UM_220 | 32.9 | 379 | 648 | 0.20 | 0.20 | 0.12 | 1.18 | 0.24 |
95 | Umemura and Endo 1970) | UM_231 | 14.8 | 324 | 524 | 0.20 | 0.20 | 0.27 | 0.95 | 0.28 |
96 | Umemura and Endo 1970) | UM_232 | 13.1 | 324 | 524 | 0.20 | 0.20 | 0.30 | 0.95 | 0.28 |
97 | Umemura and Endo 1970) | UM_233 | 13.9 | 372 | 524 | 0.20 | 0.20 | 0.28 | 1.18 | 0.28 |
98 | Umemura and Endo 1970) | UM_234 | 13.1 | 372 | 524 | 0.20 | 0.20 | 0.30 | 1.18 | 0.28 |
99 | Umemura and Endo 1970) | KO_372 | 19.9 | 524 | 352 | 0.20 | 0.20 | 0.20 | 1.33 | 0.80 |
100 | Hirosawa 1973) | KO_373 | 20.4 | 524 | 352 | 0.20 | 0.20 | 0.19 | 1.98 | 0.79 |
101 | Hirosawa 1973) | KO_452 | 21.9 | 359 | 316 | 0.20 | 0.20 | 0.45 | 2.84 | 0.77 |
102 | Hirosawa 1973) | KO_454 | 21.9 | 359 | 316 | 0.20 | 0.20 | 0.45 | 3.80 | 0.76 |
103 | Hirosawa 1973) | BR-S1 | 45.0 | 445 | 425 | 0.55 | 0.55 | 0.13 | 1.98 | 0.30 |
104 | Yalcin 1997) | Specimen1 | 24.5 | 479 | 718 | 0.23 | 0.23 | 0.10 | 1.94 | 0.45 |
105 | Elwood and Moehle 2008) | Specimen2 | 23.9 | 479 | 718 | 0.23 | 0.23 | 0.24 | 1.94 | 0.45 |
106 | Elwood and Moehle 2008) | UnitR1A | 37.9 | 324 | 359 | 0.61 | 0.41 | 0.05 | 2.53 | 0.23 |
107 | Saatcioglu and Ozcebe 1989) | U2 | 30.2 | 453 | 470 | 0.35 | 0.35 | 0.16 | 3.21 | 0.69 |
108 | Esaki 1996) | H-2-1_3 | 23.0 | 362 | 364 | 0.20 | 0.20 | 0.35 | 2.65 | 1.62 |
109 | Esaki 1996) | H-2-1_5 | 23.0 | 362 | 364 | 0.20 | 0.20 | 0.21 | 2.65 | 1.29 |
110 | Esaki 1996) | HT-2-1_3 | 20.2 | 362 | 364 | 0.20 | 0.20 | 0.35 | 2.65 | 1.62 |
111 | Esaki 1996) | HT-2-1_5 | 20.2 | 362 | 364 | 0.20 | 0.20 | 0.21 | 2.65 | 1.29 |
112 | Lynn et al. 1996) | 3CMH18 | 27.6 | 331 | 400 | 0.46 | 0.46 | 0.26 | 3.04 | 0.16 |
113 | Lynn et al. 1996) | 3CMD12 | 27.6 | 331 | 400 | 0.46 | 0.46 | 0.26 | 3.04 | 0.42 |
114 | Lynn et al. 1996) | 3SLH18 | 26.9 | 331 | 400 | 0.46 | 0.46 | 0.09 | 3.03 | 0.16 |
115 | Yoshimura et al. 2003) | Unit_6 | 30.7 | 409 | 392 | 0.30 | 0.30 | 0.20 | 1.77 | 0.48 |
116 | Yoshimura et al. 2003) | Unit_7 | 30.7 | 409 | 392 | 0.30 | 0.30 | 0.20 | 1.77 | 0.32 |
117 | Yarandi 2007) | RRC | 35.0 | 400 | 400 | 0.70 | 0.35 | 0.15 | 1.46 | 0.11 |
118 | Yarandi 2007) | SRC | 42.0 | 400 | 400 | 0.70 | 0.35 | 0.15 | 1.46 | 0.37 |
119 | Pandey and Mutsuyoshi 2005) | A4 | 33.1 | 380 | 396 | 0.30 | 0.30 | 0.03 | 2.68 | 0.65 |
120 | Pandey and Mutsuyoshi 2005) | C1 | 36.4 | 396 | 427 | 0.30 | 0.30 | 0.03 | 2.68 | 0.30 |
121 | Yoshimura and Yamanaka 2000) | FS0 | 27.0 | 387 | 355 | 0.30 | 0.30 | 0.26 | 3.82 | 1.48 |
122 | Yoshimura and Yamanaka 2000) | FS1 | 27.0 | 387 | 355 | 0.30 | 0.30 | 0.26 | 3.82 | 1.48 |
123 | Gill 1979) | No.1 | 23.1 | 375 | 297 | 0.55 | 0.55 | 0.26 | 1.79 | 1.50 |
124 | Gill 1979) | No.2 | 41.4 | 375 | 316 | 0.55 | 0.55 | 0.21 | 1.79 | 2.30 |
125 | Gill 1979) | No.3 | 21.4 | 375 | 297 | 0.55 | 0.55 | 0.42 | 1.79 | 2.00 |
126 | Gill 1979) | No.4 | 23.5 | 375 | 294 | 0.55 | 0.55 | 0.60 | 1.79 | 3.50 |
127 | Ang 1981) | No.3 | 23.6 | 427 | 320 | 0.40 | 0.40 | 0.38 | 1.51 | 2.80 |
128 | Ang 1981) | No.4 | 25.0 | 427 | 280 | 0.40 | 0.40 | 0.21 | 1.51 | 2.20 |
129 | Soesianawati 1986) | No.1 | 46.5 | 446 | 364 | 0.40 | 0.40 | 0.10 | 1.51 | 0.90 |
130 | Soesianawati 1986) | No.2 | 44.0 | 446 | 360 | 0.40 | 0.40 | 0.30 | 1.51 | 1.20 |
131 | Soesianawati 1986) | No.3 | 44.0 | 446 | 364 | 0.40 | 0.40 | 0.30 | 1.51 | 0.80 |
132 | Soesianawati 1986) | No.4 | 40.0 | 446 | 255 | 0.40 | 0.40 | 0.30 | 1.51 | 0.60 |
133 | Zahn 1985) | No.7 | 28.3 | 440 | 466 | 0.40 | 0.40 | 0.22 | 1.51 | 1.60 |
134 | Zahn 1985) | No.8 | 40.1 | 440 | 466 | 0.40 | 0.40 | 0.39 | 1.51 | 2.00 |
135 | Watson 1989) | No.5 | 41.0 | 474 | 372 | 0.40 | 0.40 | 0.50 | 1.51 | 0.70 |
136 | Watson 1989) | No.6 | 40.0 | 474 | 388 | 0.40 | 0.40 | 0.50 | 1.51 | 0.30 |
137 | Watson 1989) | No.7 | 42.0 | 474 | 308 | 0.40 | 0.40 | 0.70 | 1.51 | 1.30 |
138 | Watson 1989) | No.8 | 39.0 | 474 | 372 | 0.40 | 0.40 | 0.70 | 1.51 | 0.70 |
139 | Watson 1989) | No.9 | 40.0 | 474 | 308 | 0.40 | 0.40 | 0.70 | 1.51 | 2.50 |
140 | Tanaka 1990) | No1 | 25.6 | 474 | 333 | 0.40 | 0.40 | 0.20 | 1.57 | 2.50 |
141 | Tanaka 1990) | No2 | 25.6 | 474 | 333 | 0.40 | 0.40 | 0.20 | 1.57 | 2.50 |
142 | Tanaka 1990) | No3 | 25.6 | 474 | 333 | 0.40 | 0.40 | 0.20 | 1.57 | 2.50 |
143 | Tanaka 1990) | No4 | 25.6 | 474 | 333 | 0.40 | 0.40 | 0.20 | 1.57 | 2.50 |
144 | Tanaka 1990) | No5 | 32.0 | 511 | 325 | 0.55 | 0.55 | 0.10 | 1.25 | 1.70 |
145 | Tanaka 1990) | No6 | 32.0 | 511 | 325 | 0.55 | 0.55 | 0.10 | 1.25 | 1.70 |
146 | Tanaka 1990) | No7 | 32.0 | 511 | 325 | 0.55 | 0.55 | 0.30 | 1.25 | 2.10 |
147 | Tanaka 1990) | No8 | 32.1 | 511 | 325 | 0.55 | 0.55 | 0.30 | 1.25 | 2.10 |
148 | Park and Paulay 1990) | No9 | 26.9 | 432 | 305 | 0.60 | 0.40 | 0.10 | 1.89 | 1.88 |
149 | Arakawa et al. 1982) | No.102 | 20.6 | 393 | 323 | 0.25 | 0.25 | 0.33 | 0.68 | 1.20 |
150 | Ohno and Nishioka 1984) | L1 | 24.8 | 362 | 325 | 0.40 | 0.40 | 0.03 | 1.42 | 0.30 |
151 | Ohno and Nishioka 1984) | L2 | 24.8 | 362 | 325 | 0.40 | 0.40 | 0.03 | 1.42 | 0.30 |
152 | Ohno and Nishioka 1984) | L3 | 24.8 | 362 | 325 | 0.40 | 0.40 | 0.03 | 1.42 | 0.30 |
153 | Zhou et al. 1987) | 214–08 | 21.1 | 341 | 559 | 0.16 | 0.16 | 0.80 | 2.22 | 0.70 |
154 | Kanda 1988) | 85STC-1 | 27.9 | 374 | 506 | 0.25 | 0.25 | 0.11 | 1.62 | 0.40 |
155 | Kanda 1988) | 85STC-2 | 27.9 | 374 | 506 | 0.25 | 0.25 | 0.11 | 1.62 | 0.40 |
156 | Kanda 1988) | 85STC-3 | 27.9 | 374 | 506 | 0.25 | 0.25 | 0.11 | 1.62 | 0.40 |
157 | Kanda 1988) | 85PDC-1 | 24.8 | 374 | 352 | 0.25 | 0.25 | 0.12 | 1.62 | 0.40 |
158 | Kanda 1988) | 85PDC-2 | 27.9 | 374 | 506 | 0.25 | 0.25 | 0.11 | 1.62 | 0.40 |
159 | Kanda 1988) | 85PDC-3 | 27.9 | 374 | 506 | 0.25 | 0.25 | 0.11 | 1.62 | 0.40 |
160 | Muguruma et al. 1989) | AL-1 | 85.7 | 399 | 328 | 0.20 | 0.20 | 0.40 | 3.17 | 1.60 |
161 | Muguruma et al. 1989) | AH-1 | 85.7 | 399 | 792 | 0.20 | 0.20 | 0.40 | 3.80 | 1.60 |
162 | Muguruma et al. 1989) | AL-2 | 85.7 | 399 | 328 | 0.20 | 0.20 | 0.63 | 3.80 | 1.60 |
163 | Muguruma et al. 1989) | AH-2 | 85.7 | 399 | 792 | 0.20 | 0.20 | 0.63 | 3.80 | 1.60 |
164 | Muguruma et al. 1989) | BL-1 | 115.8 | 399 | 328 | 0.20 | 0.20 | 0.25 | 3.80 | 1.60 |
165 | Muguruma et al. 1989) | BH-1 | 115.8 | 399 | 792 | 0.20 | 0.20 | 0.25 | 3.80 | 1.60 |
166 | Muguruma et al. 1989) | BL-2 | 115.8 | 399 | 328 | 0.20 | 0.20 | 0.42 | 3.80 | 1.60 |
167 | Muguruma et al. 1989) | BH-2 | 115.8 | 399 | 792 | 0.20 | 0.20 | 0.42 | 3.80 | 1.60 |
168 | Sakai 1990) | B1 | 99.5 | 379 | 774 | 0.25 | 0.25 | 0.35 | 2.43 | 0.50 |
169 | Sakai 1990) | B2 | 99.5 | 379 | 774 | 0.25 | 0.25 | 0.35 | 2.43 | 0.70 |
170 | Sakai 1990) | B3 | 99.5 | 379 | 344 | 0.25 | 0.25 | 0.35 | 2.43 | 0.60 |
171 | Sakai 1990) | B4 | 99.5 | 379 | 1126 | 0.25 | 0.25 | 0.35 | 2.43 | 0.50 |
172 | Sakai 1990) | B5 | 99.5 | 379 | 774 | 0.25 | 0.25 | 0.35 | 2.43 | 0.50 |
173 | Sakai 1990) | B6 | 99.5 | 379 | 857 | 0.25 | 0.25 | 0.35 | 2.43 | 0.50 |
174 | Sakai 1990) | B7 | 99.5 | 339 | 774 | 0.25 | 0.25 | 0.35 | 1.81 | 0.50 |
175 | Atalay and Penzien 1975) | No.1S1 | 29.1 | 367 | 363 | 0.31 | 0.31 | 0.10 | 1.63 | 1.50 |
176 | Atalay and Penzien 1975) | No.2S1 | 30.7 | 367 | 363 | 0.31 | 0.31 | 0.09 | 1.63 | 0.90 |
177 | Atalay and Penzien 1975) | No.3S1 | 29.2 | 367 | 363 | 0.31 | 0.31 | 0.10 | 1.63 | 1.50 |
178 | Atalay and Penzien 1975) | No.4S1 | 27.6 | 429 | 363 | 0.31 | 0.31 | 0.10 | 1.63 | 0.90 |
179 | Atalay and Penzien 1975) | No.5S1 | 29.4 | 429 | 392 | 0.31 | 0.31 | 0.20 | 1.63 | 1.50 |
180 | Atalay and Penzien 1975) | No.6S1 | 31.8 | 429 | 392 | 0.31 | 0.31 | 0.18 | 1.63 | 0.90 |
181 | Atalay and Penzien 1975) | No.9 | 33.3 | 363 | 392 | 0.31 | 0.31 | 0.26 | 1.63 | 1.50 |
182 | Atalay and Penzien 1975) | No.10 | 32.4 | 363 | 392 | 0.31 | 0.31 | 0.27 | 1.63 | 0.90 |
183 | Atalay and Penzien 1975) | No.11 | 31.0 | 363 | 373 | 0.31 | 0.31 | 0.28 | 1.63 | 1.50 |
184 | Atalay and Penzien 1975) | No.12 | 31.8 | 363 | 373 | 0.31 | 0.31 | 0.27 | 1.63 | 0.90 |
185 | Azizinamini et al. 1988) | NC | 39.3 | 439 | 454 | 0.46 | 0.46 | 0.21 | 1.94 | 2.20 |
186 | Azizinamini et al. 1988) | NC | 39.8 | 439 | 616 | 0.46 | 0.46 | 0.31 | 1.94 | 1.30 |
187 | Saatcioglu and Ozcebe 1989) | U1 | 43.6 | 430 | 470 | 0.35 | 0.35 | 0.00 | 3.31 | 0.90 |
188 | Saatcioglu and Ozcebe 1989) | U3 | 34.8 | 430 | 470 | 0.35 | 0.35 | 0.14 | 3.31 | 2.50 |
189 | Saatcioglu and Ozcebe 1989) | U4 | 32.0 | 438 | 470 | 0.35 | 0.35 | 0.15 | 3.31 | 2.50 |
190 | Saatcioglu and Ozcebe 1989) | U6 | 37.3 | 437 | 425 | 0.35 | 0.35 | 0.13 | 3.31 | 3.21 |
191 | Saatcioglu and Ozcebe 1989) | U7 | 39.0 | 437 | 425 | 0.35 | 0.35 | 0.13 | 3.31 | 2.00 |
192 | Galeota et al. 1996) | AA1 | 80.0 | 430 | 430 | 0.25 | 0.25 | 0.30 | 1.51 | 1.20 |
193 | Galeota et al. 1996) | AA2 | 80.0 | 430 | 430 | 0.25 | 0.25 | 0.30 | 1.51 | 1.20 |
194 | Galeota et al. 1996) | AA3 | 80.0 | 430 | 430 | 0.25 | 0.25 | 0.20 | 1.51 | 1.20 |
195 | Galeota et al. 1996) | AA4 | 80.0 | 430 | 430 | 0.25 | 0.25 | 0.20 | 1.51 | 1.20 |
196 | Galeota et al. 1996) | BA1 | 80.0 | 430 | 430 | 0.25 | 0.25 | 0.20 | 1.51 | 1.80 |
197 | Galeota et al. 1996) | BA2 | 80.0 | 430 | 430 | 0.25 | 0.25 | 0.30 | 1.51 | 1.80 |
198 | Galeota et al. 1996) | BA3 | 80.0 | 430 | 430 | 0.25 | 0.25 | 0.30 | 1.51 | 1.80 |
199 | Galeota et al. 1996) | BA4 | 80.0 | 430 | 430 | 0.25 | 0.25 | 0.20 | 1.51 | 1.80 |
200 | Galeota et al. 1996) | CA1 | 80.0 | 430 | 430 | 0.25 | 0.25 | 0.20 | 1.51 | 3.70 |
201 | Galeota et al. 1996) | CA2 | 80.0 | 430 | 430 | 0.25 | 0.25 | 0.30 | 1.51 | 3.70 |
202 | Galeota et al. 1996) | CA3 | 80.0 | 430 | 430 | 0.25 | 0.25 | 0.20 | 1.51 | 3.70 |
203 | Galeota et al. 1996) | CA4 | 80.0 | 430 | 430 | 0.25 | 0.25 | 0.30 | 1.51 | 3.70 |
204 | Galeota et al. 1996) | AB1 | 80.0 | 430 | 430 | 0.25 | 0.25 | 0.20 | 6.03 | 1.20 |
205 | Galeota et al. 1996) | AB2 | 80.0 | 430 | 430 | 0.25 | 0.25 | 0.30 | 6.03 | 1.20 |
206 | Galeota et al. 1996) | AB3 | 80.0 | 430 | 430 | 0.25 | 0.25 | 0.30 | 6.03 | 1.20 |
207 | Galeota et al. 1996) | AB4 | 80.0 | 430 | 430 | 0.25 | 0.25 | 0.20 | 6.03 | 1.20 |
208 | Galeota et al. 1996) | BB | 80.0 | 430 | 430 | 0.25 | 0.25 | 0.20 | 6.03 | 1.80 |
209 | Galeota et al. 1996) | BB1 | 80.0 | 430 | 430 | 0.25 | 0.25 | 0.20 | 6.03 | 1.80 |
210 | Galeota et al. 1996) | BB4 | 80.0 | 430 | 430 | 0.25 | 0.25 | 0.30 | 6.03 | 1.80 |
211 | Galeota et al. 1996) | BB4B | 80.0 | 430 | 430 | 0.25 | 0.25 | 0.30 | 6.03 | 1.80 |
212 | Galeota et al. 1996) | CB1 | 80.0 | 430 | 430 | 0.25 | 0.25 | 0.20 | 6.03 | 3.70 |
213 | Galeota et al. 1996) | CB2 | 80.0 | 430 | 430 | 0.25 | 0.25 | 0.20 | 6.03 | 3.70 |
214 | Galeota et al. 1996) | CB3 | 80.0 | 430 | 430 | 0.25 | 0.25 | 0.30 | 6.03 | 3.70 |
215 | Galeota et al. 1996) | CB4 | 80.0 | 430 | 430 | 0.25 | 0.25 | 0.30 | 6.03 | 3.70 |
216 | Wehbe 1998) | A1 | 27.2 | 448 | 428 | 0.61 | 0.38 | 0.10 | 2.22 | 0.40 |
217 | Wehbe 1998) | A2 | 27.2 | 448 | 428 | 0.61 | 0.38 | 0.24 | 2.22 | 0.40 |
218 | Wehbe 1998) | B1 | 28.1 | 448 | 428 | 0.61 | 0.38 | 0.09 | 2.22 | 0.50 |
219 | Wehbe 1998) | B2 | 28.1 | 448 | 428 | 0.61 | 0.38 | 0.23 | 2.22 | 0.50 |
220 | Xiao and Martirossyan 1998b) | HC4-0.1P | 76.0 | 510 | 510 | 0.25 | 0.25 | 0.10 | 3.55 | 3.70 |
221 | Xiao and Martirossyan 1998b) | HC4-0.2P | 76.0 | 510 | 510 | 0.25 | 0.25 | 0.20 | 3.55 | 3.70 |
222 | Xiao and Martirossyan 1998b) | HC4-0.1P | 86.0 | 510 | 510 | 0.25 | 0.25 | 0.10 | 2.46 | 3.70 |
223 | Xiao and Martirossyan 1998b) | HC4-0.2P | 86.0 | 510 | 510 | 0.25 | 0.25 | 0.19 | 2.46 | 3.70 |
224 | Sugano 1996) | UC10H | 118.0 | 393 | 1415 | 0.23 | 0.23 | 0.60 | 1.86 | 3.18 |
225 | Sugano 1996) | UC15H | 118.0 | 393 | 1424 | 0.23 | 0.23 | 0.60 | 1.86 | 5.00 |
226 | Sugano 1996) | UC20H | 118.0 | 393 | 1424 | 0.23 | 0.23 | 0.60 | 1.86 | 5.00 |
227 | Sugano 1996) | UC15L | 118.0 | 393 | 1424 | 0.23 | 0.23 | 0.35 | 1.86 | 5.00 |
228 | Sugano 1996) | UC20L | 118.0 | 393 | 1424 | 0.23 | 0.23 | 0.35 | 1.86 | 5.00 |
229 | Nosho et al. 1996) | No.1 | 40.6 | 407 | 351 | 0.28 | 0.28 | 0.34 | 1.01 | 2.18 |
230 | Bayrak and Sheikh 1996) | ES-1HT | 72.1 | 454 | 463 | 0.31 | 0.31 | 0.50 | 2.58 | 3.20 |
231 | Bayrak and Sheikh 1996) | AS-2HT | 71.7 | 454 | 542 | 0.31 | 0.31 | 0.36 | 2.58 | 2.80 |
232 | Bayrak and Sheikh 1996) | AS-3HT | 71.8 | 454 | 542 | 0.31 | 0.31 | 0.50 | 2.58 | 2.80 |
233 | Bayrak and Sheikh 1996) | AS-4HT | 71.9 | 454 | 463 | 0.31 | 0.31 | 0.50 | 2.58 | 5.10 |
234 | Bayrak and Sheikh 1996) | AS-5HT | 101.8 | 454 | 463 | 0.31 | 0.31 | 0.45 | 2.58 | 4.00 |
235 | Bayrak and Sheikh 1996) | AS-6HT | 101.9 | 454 | 463 | 0.31 | 0.31 | 0.46 | 2.58 | 6.70 |
236 | Bayrak and Sheikh 1996) | AS-7HT | 102.0 | 454 | 542 | 0.31 | 0.31 | 0.45 | 2.58 | 2.70 |
237 | Bayrak and Sheikh 1996) | ES-8HT | 102.2 | 454 | 463 | 0.31 | 0.31 | 0.47 | 2.58 | 4.30 |
238 | Saatcioglu and Grira 1999) | BG-1 | 34.0 | 455 | 570 | 0.35 | 0.35 | 0.43 | 1.95 | 1.00 |
239 | Saatcioglu and Grira 1999) | BG-2 | 34.0 | 455 | 570 | 0.35 | 0.35 | 0.43 | 1.95 | 2.00 |
240 | Saatcioglu and Grira 1999) | BG-3 | 34.0 | 455 | 570 | 0.35 | 0.35 | 0.20 | 1.95 | 2.00 |
241 | Saatcioglu and Grira 1999) | BG-4 | 34.0 | 455 | 570 | 0.35 | 0.35 | 0.46 | 2.93 | 1.30 |
242 | Saatcioglu and Grira 1999) | BG-5 | 34.0 | 455 | 570 | 0.35 | 0.35 | 0.46 | 2.93 | 2.70 |
243 | Saatcioglu and Grira 1999) | BG-6 | 34.0 | 478 | 570 | 0.35 | 0.35 | 0.46 | 2.29 | 2.70 |
244 | Saatcioglu and Grira 1999) | BG-7 | 34.0 | 455 | 580 | 0.35 | 0.35 | 0.46 | 2.93 | 1.30 |
245 | Saatcioglu and Grira 1999) | BG-8 | 34.0 | 455 | 580 | 0.35 | 0.35 | 0.23 | 2.93 | 1.30 |
246 | Saatcioglu and Grira 1999) | BG-9 | 34.0 | 428 | 580 | 0.35 | 0.35 | 0.46 | 3.28 | 1.30 |
247 | Saatcioglu and Grira 1999) | BG-10 | 34.0 | 428 | 570 | 0.35 | 0.35 | 0.46 | 3.28 | 2.70 |
248 | Matamoros 1999) | C10-05N | 69.6 | 586 | 407 | 0.20 | 0.20 | 0.05 | 1.93 | 1.00 |
249 | Matamoros 1999) | C10-05S | 69.6 | 586 | 407 | 0.20 | 0.20 | 0.05 | 1.93 | 1.00 |
250 | Matamoros 1999) | C10-10N | 67.8 | 572 | 514 | 0.20 | 0.20 | 0.10 | 1.93 | 1.00 |
251 | Matamoros 1999) | C10-10S | 67.8 | 573 | 515 | 0.20 | 0.20 | 0.10 | 1.93 | 1.00 |
252 | Matamoros 1999) | C10-20N | 65.5 | 572 | 514 | 0.20 | 0.20 | 0.21 | 1.93 | 1.00 |
253 | Matamoros 1999) | C10-20S | 65.5 | 573 | 515 | 0.20 | 0.20 | 0.21 | 1.93 | 1.00 |
254 | Matamoros 1999) | C5-00N | 37.9 | 572 | 514 | 0.20 | 0.20 | 0.00 | 1.93 | 1.00 |
255 | Matamoros 1999) | C5-00S | 37.9 | 573 | 515 | 0.20 | 0.20 | 0.00 | 1.93 | 1.00 |
256 | Matamoros 1999) | C5-20N | 48.3 | 586 | 407 | 0.20 | 0.20 | 0.14 | 1.93 | 1.00 |
257 | Matamoros 1999) | C5-20S | 48.3 | 587 | 408 | 0.20 | 0.20 | 0.14 | 1.93 | 1.00 |
258 | Matamoros 1999) | C5-40N | 38.0 | 572 | 514 | 0.20 | 0.20 | 0.36 | 1.93 | 1.00 |
259 | Matamoros 1999) | C5-40S | 38.0 | 573 | 515 | 0.20 | 0.20 | 0.36 | 1.93 | 1.00 |
260 | Mo and Wang 2000) | C1-1 | 24.9 | 497 | 459 | 0.40 | 0.40 | 0.11 | 2.14 | 3.00 |
261 | Mo and Wang 2000) | C1-2 | 26.7 | 497 | 459 | 0.40 | 0.40 | 0.16 | 2.14 | 3.00 |
262 | Mo and Wang 2000) | C1-3 | 26.1 | 497 | 459 | 0.40 | 0.40 | 0.22 | 2.14 | 3.00 |
263 | Mo and Wang 2000) | C2-1 | 25.3 | 497 | 459 | 0.40 | 0.40 | 0.11 | 2.14 | 3.00 |
264 | Mo and Wang 2000) | C2-2 | 27.1 | 497 | 459 | 0.40 | 0.40 | 0.16 | 2.14 | 3.00 |
265 | Mo and Wang 2000) | C2-3 | 26.8 | 497 | 459 | 0.40 | 0.40 | 0.21 | 2.14 | 3.00 |
266 | Mo and Wang 2000) | C3-1 | 26.4 | 497 | 459 | 0.40 | 0.40 | 0.11 | 2.14 | 3.00 |
267 | Mo and Wang 2000) | C3-2 | 27.5 | 497 | 459 | 0.40 | 0.40 | 0.15 | 2.14 | 3.00 |
268 | Mo and Wang 2000) | C3-3 | 26.9 | 497 | 459 | 0.40 | 0.40 | 0.21 | 2.14 | 3.00 |
269 | Aboutaha and Machado 1999) | ORC1 | 83.0 | 414 | 414 | 0.51 | 0.31 | 0.00 | 2.53 | 5.19 |
270 | Aboutaha and Machado 1999) | ORC2 | 83.0 | 414 | 414 | 0.51 | 0.31 | 0.12 | 2.53 | 5.19 |
271 | Aboutaha and Machado 1999) | ORC3 | 83.0 | 414 | 414 | 0.51 | 0.31 | 0.16 | 2.53 | 5.20 |
272 | Thomson and Wallace 1994) | A1 | 102.7 | 517 | 793 | 0.15 | 0.15 | 0.00 | 2.45 | 1.44 |
273 | Thomson and Wallace 1994) | A3 | 86.3 | 517 | 793 | 0.15 | 0.15 | 0.20 | 2.45 | 1.44 |
274 | Thomson and Wallace 1994) | B1 | 87.5 | 455 | 793 | 0.15 | 0.15 | 0.00 | 2.45 | 1.63 |
275 | Thomson and Wallace 1994) | B2 | 83.4 | 455 | 793 | 0.15 | 0.15 | 0.10 | 2.45 | 1.63 |
276 | Thomson and Wallace 1994) | B3 | 90.0 | 455 | 793 | 0.15 | 0.15 | 0.20 | 2.45 | 1.63 |
277 | Thomson and Wallace 1994) | C1 | 67.5 | 476 | 1262 | 0.15 | 0.15 | 0.00 | 2.45 | 1.63 |
278 | Thomson and Wallace 1994) | C2 | 74.6 | 476 | 1262 | 0.15 | 0.15 | 0.10 | 2.45 | 1.63 |
279 | Thomson and Wallace 1994) | C3 | 81.8 | 476 | 1262 | 0.15 | 0.15 | 0.20 | 2.45 | 1.63 |
280 | Thomson and Wallace 1994) | D1 | 75.8 | 476 | 1262 | 0.15 | 0.15 | 0.20 | 2.45 | 1.63 |
281 | Thomson and Wallace 1994) | D2 | 87.0 | 476 | 1262 | 0.15 | 0.15 | 0.20 | 2.45 | 1.63 |
282 | Thomson and Wallace 1994) | D3 | 71.2 | 476 | 1262 | 0.15 | 0.15 | 0.20 | 2.45 | 1.63 |
283 | Legeron and Paultre 2000) | 1,006,015 | 92.4 | 451 | 391 | 0.31 | 0.31 | 0.14 | 2.57 | 9.97 |
284 | Legeron and Paultre 2000) | 1,006,025 | 93.3 | 430 | 391 | 0.31 | 0.31 | 0.28 | 2.57 | 9.97 |
285 | Legeron and Paultre 2000) | 1,006,040 | 98.2 | 451 | 418 | 0.31 | 0.31 | 0.39 | 2.57 | 9.97 |
286 | Legeron and Paultre 2000) | 10,013,015 | 94.8 | 451 | 391 | 0.31 | 0.31 | 0.14 | 2.57 | 9.97 |
287 | Legeron and Paultre 2000) | 10,013,025 | 97.7 | 430 | 391 | 0.31 | 0.31 | 0.26 | 2.57 | 9.97 |
288 | Legeron and Paultre 2000) | 10,013,040 | 104.3 | 451 | 418 | 0.31 | 0.31 | 0.37 | 2.57 | 9.97 |
289 | Paultre et al. 2001) | 806,040 | 78.7 | 446 | 438 | 0.31 | 0.31 | 0.40 | 2.57 | 9.97 |
290 | Paultre et al. 2001) | 1,206,040 | 109.2 | 446 | 438 | 0.31 | 0.31 | 0.41 | 2.57 | 9.97 |
291 | Paultre et al. 2001) | 1,005,540 | 109.5 | 446 | 825 | 0.31 | 0.31 | 0.35 | 2.57 | 7.04 |
292 | Paultre et al. 2001) | 1,008,040 | 104.2 | 446 | 825 | 0.31 | 0.31 | 0.37 | 2.57 | 7.04 |
293 | Paultre et al. 2001) | 1,005,552 | 104.5 | 446 | 744 | 0.31 | 0.31 | 0.53 | 2.57 | 9.84 |
294 | Paultre et al. 2001) | 1,006,052 | 109.4 | 446 | 492 | 0.31 | 0.31 | 0.51 | 2.57 | 9.97 |
295 | Pujol 2002) | 10–2-3N | 33.7 | 453 | 411 | 0.30 | 0.15 | 0.09 | 2.45 | 0.60 |
296 | Pujol 2002) | 10–2-3S | 33.7 | 453 | 411 | 0.30 | 0.15 | 0.09 | 2.45 | 0.60 |
297 | Pujol 2002) | 10–3-1.5N | 32.1 | 453 | 411 | 0.30 | 0.15 | 0.09 | 2.45 | 1.96 |
298 | Pujol 2002) | 10–3-1.5S | 32.1 | 453 | 411 | 0.30 | 0.15 | 0.09 | 2.45 | 1.96 |
299 | Pujol 2002) | 10–3-3N | 29.9 | 453 | 411 | 0.30 | 0.15 | 0.10 | 2.45 | 1.96 |
300 | Pujol 2002) | 10–3-3S | 29.9 | 453 | 411 | 0.30 | 0.15 | 0.10 | 2.45 | 1.96 |
301 | Pujol 2002) | 10–3-2.25N | 27.4 | 453 | 411 | 0.30 | 0.15 | 0.10 | 2.45 | 1.96 |
302 | Pujol 2002) | 10–3-2.25S | 27.4 | 453 | 411 | 0.30 | 0.15 | 0.10 | 2.45 | 1.96 |
303 | Pujol 2002) | 20–3-3N | 36.4 | 453 | 411 | 0.30 | 0.15 | 0.16 | 2.45 | 1.96 |
304 | Pujol 2002) | 20–3-3S | 36.4 | 453 | 411 | 0.30 | 0.15 | 0.16 | 2.45 | 1.96 |
305 | Pujol 2002) | 10–2-2.25N | 34.9 | 453 | 411 | 0.30 | 0.15 | 0.08 | 2.45 | 1.96 |
306 | Pujol 2002) | 10–2-2.25S | 34.9 | 453 | 411 | 0.30 | 0.15 | 0.08 | 2.45 | 1.96 |
307 | Pujol 2002) | 10–1-2.25N | 36.5 | 453 | 411 | 0.30 | 0.15 | 0.08 | 2.45 | 1.96 |
308 | Pujol 2002) | 10–1-2.25S | 36.5 | 453 | 411 | 0.30 | 0.15 | 0.08 | 2.45 | 1.96 |
309 | Kono and Watanabe 2000) | D1N30 | 37.6 | 461 | 485 | 0.25 | 0.25 | 0.30 | 2.43 | 1.91 |
310 | Kono and Watanabe 2000) | D1N60 | 37.6 | 461 | 485 | 0.25 | 0.25 | 0.60 | 2.43 | 1.91 |
311 | Kono and Watanabe 2000) | L1D60 | 39.2 | 388 | 524 | 0.60 | 0.60 | 0.57 | 1.69 | 7.81 |
312 | Kono and Watanabe 2000) | L1N60 | 39.2 | 388 | 524 | 0.60 | 0.60 | 0.57 | 1.69 | 7.55 |
313 | Kono and Watanabe 2000) | L1N6B | 32.2 | 388 | 524 | 0.56 | 0.56 | 0.59 | 1.94 | 7.55 |
314 | Harries et al. 2006) | L0 | 24.6 | 460 | 438 | 0.46 | 0.46 | 0.25 | 1.48 | 0.20 |
315 | Melek and Wallace 2004) | S10MI | 36.2 | 510 | 481 | 0.46 | 0.46 | 0.07 | 1.94 | 0.16 |
316 | Melek and Wallace 2004) | S20MI | 36.2 | 510 | 481 | 0.46 | 0.46 | 0.14 | 1.94 | 0.16 |
317 | Melek and Wallace 2004) | S30MI | 36.2 | 510 | 481 | 0.46 | 0.46 | 0.21 | 1.94 | 0.16 |
318 | Melek and Wallace 2004) | S20HI | 35.3 | 510 | 481 | 0.46 | 0.46 | 0.14 | 1.94 | 0.16 |
319 | Melek and Wallace 2004) | S20HIN | 35.3 | 510 | 481 | 0.46 | 0.46 | 0.14 | 1.94 | 0.16 |
320 | Melek and Wallace 2004) | S30XI | 35.3 | 510 | 481 | 0.46 | 0.46 | 0.22 | 1.94 | 0.16 |
Availability of data and materials
The data and materials in the current study are available from the corresponding author on reasonable request.
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This research was supported by the National Natural Science Foundation of China (52178135).
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This research was funded by the National Natural Science Foundation of China (52178135).
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Zhu, Y., Zhong, J. A yield curvature model considering axial compression ratio. ABEN 4, 19 (2023). https://doi.org/10.1186/s43251-023-00099-w
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DOI: https://doi.org/10.1186/s43251-023-00099-w
Keywords
- Yield curvature
- Axial compression ratio
- Prediction model