33 Transfer Length Probabilistic Model Updating in High Performance Concrete 329 a b Fig. 33.5 Analytical transfer length histograms. (a) Histogram of the Transfer Length obtained from samples using ACI 318-11 [9] model. (b) Histogram of the Transfer Length obtained from samples using Mitchell et al. [10] model Table 33.2 Statistics of transfer length estimation ACI Mitchell Mean 413 432:7 Std 157:4 138:8 Median 389:2 399:3 33.5 Conclusions The goal of this paper was to update two prestress concrete transfer length models in a probabilistic fashion using limited experimental data (one strain gauge). The models updated are the ACI 318-11 code [9] and Mitchell’s model [10]. The transfer length in the ACI 318-11 model is proportional to both the diameter and the stress applied to the strand. Mitchel’s model uses the concrete strength as an additional parameter. Results indicate no dependency between the model parameters in either model. The mean of the Transfer length obtained with the ACI model is shorter than that obtained with Mitchel’s model. The standard deviation of the transfer length was smaller in Mitchel’s model. Future work will focus on comparing these models in a probabilistic sense to determine if one model is more probable when limited experimental data is available. Acknowledgements This material is based upon work supported by Federal Railroad Administration BAA-2014, CSX Transportation, KSAKoppers Concrete Tie Division Inc. under the project entitled “High Strength Reduced Modulus High Performance Concrete for Prestressed Concrete Tie Applications” References 1. Jeong, D.: Concrete ties, fasteners and critical failure modes. In: FRA Research and Development Research Review (2012) 2. Zeman, J.C., Edwards, J.R., Barkan, C.P., Lange, D.A.: Failure mode and effect analysis of concrete ties in north America. In: Proceedings of the 9th International Heavy Haul Conference, pp. 270–278 (2009) 3. Kaewunruen, S., Remennikov, A.M.: Dynamic crack propagations in prestressed concrete sleepers in railway track systems subjected to severe impact loads. J. Struct. Eng. 136(6), 749–754 (2009) 4. Yu, H., Jeong, D.: Finite element bond models for seven-wire prestressing strands in concrete crossties. In: Proceeding of 2015 Joint Rail Conference (JRC) (2015) 5. Beck, J., Katafygiotis, L.S.: Updating models and their uncertainties i: Bayesian statistical framework. J. Eng. Mech. 124, 455–461 (2009) 6. Cheung, S.H., Beck, J.: Bayesian model updating using hybrid monte carlo simulation with application to structural dynamic models with uncertain parameters. J. Eng. Mech. 135, 243–225 (2009) 7. Zárate, B.A., Caicedo, J.M.: Finite element model updating: multiple alternatives. Eng. Struct. 30(12), 3724–3730 (2008) 8. Madarshahian, R., Caicedo, J.M.: Reducing MCMC computational cost with a two layered Bayesian approach. In: Model Validation and Uncertainty Quantification, vol. 3, pp. 291–297. Springer, New York (2015) 9. Committee, A., et al.: Building Code Requirements for Structural Concrete (318-11) and Commentary-(318r-11). American Concrete Institute, Detroit (2011) 10. Mitchell, D., Cook, W.D., Khan, A.A., Tham, T.: Influence of high strength concrete on transfer and development length of pretensioning strand. Precast/prestress. Concr. Inst. J. 38(3), 52–66 (1993)
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