Uncertainty quantification in the strain response of prestressed reinforced concrete structures using fractile based sampling

Uncertainty quantification in the strain response of prestressed reinforced concrete structures using fractile based sampling

Článek WoS

The probabilistic evaluation of the capacity and response of structural systems is often done by probabilistic simulation. This approach relies on a considerable number of deterministic analyses to obtain an accurate estimation of the desired statistical characteristics. However, the need of performing a large number of analyses hinders the application of probabilistic simulation in practice, especially when the deterministic calculation of the structural response is computationally expensive in itself (e.g. nonlinear finite element analysis). To increase the appeal of probabilistic simulation, the number of analyses should be very small (i.e. ten or less). This study shows how different sampling techniques can be adopted to select a very small sample subset of analyses to be run, and how they can yield accurate results in estimating the shear capacity of prestressed reinforced concrete beams. Based on the results of the study, the Fractile Based Sampling (FBS) method emerges as a more promising sampling strategy than other sampling techniques, like Latin Hypercube Sampling (LHS). For the same small number of samples, the results show that FBS is preferable over LHS and other sampling techniques for capturing both the general distribution of the response and the tails of the distribution, which shows its usefulness in assessing probability of failure and reliability.

The probabilistic evaluation of the capacity and response of structural systems is often done by probabilistic simulation. This approach relies on a considerable number of deterministic analyses to obtain an accurate estimation of the desired statistical characteristics. However, the need of performing a large number of analyses hinders the application of probabilistic simulation in practice, especially when the deterministic calculation of the structural response is computationally expensive in itself (e.g. nonlinear finite element analysis). To increase the appeal of probabilistic simulation, the number of analyses should be very small (i.e. ten or less). This study shows how different sampling techniques can be adopted to select a very small sample subset of analyses to be run, and how they can yield accurate results in estimating the shear capacity of prestressed reinforced concrete beams. Based on the results of the study, the Fractile Based Sampling (FBS) method emerges as a more promising sampling strategy than other sampling techniques, like Latin Hypercube Sampling (LHS). For the same small number of samples, the results show that FBS is preferable over LHS and other sampling techniques for capturing both the general distribution of the response and the tails of the distribution, which shows its usefulness in assessing probability of failure and reliability.

Fractile based sampling; Latin hypercube sampling; nonlinear deterministic modelling; prestressed concrete beams; probability assessment; sampling strategy; shear capacity; structural reliability

Fractile based sampling; Latin hypercube sampling; nonlinear deterministic modelling; prestressed concrete beams; probability assessment; sampling strategy; shear capacity; structural reliability

WANG, X.; STRAUSS, A.; RANDL, N.; BOCCHINI, P.

2025

09.01.2024

TAYLOR & FRANCIS LTD

ABINGDON

1744-8980

Structure and Infrastructure Engineering

20

5

Spojené království Velké Británie a Severního Irska

771

789

19

https://www.tandfonline.com/doi/full/10.1080/15732479.2023.2300072