Abstract

The evaluation of the failure pressure of the containment building of a large dry PWR-W three loops nuclear power plant, based on computer numerical simulation, is described in this paper. The proposed method considers fully three-dimensional finite element models in order to take into account the effect of the most significant structural characteristics (presence of three buttresses, penetrations, additional reinforcement around the penetrations, etc.), the lack of symmetry of the forces generated by the prestressing system, as well as the nonlinear behaviour of the materials and the sensitivity of the results to uncertainties associated with several parameters. The computational model is completely described, including the constitutive equations for the concrete, the reinforcing steel and prestressing tendons, the spatial discretization—isoparametric elements including the reinforcement are used. The structural models and the analyses performed for their calibration are also described. The influence on the failure pressure of incorporating the foundation slab in the structural model, and the influence of the thermal effects, are discussed. One of the conclusions of the numerical study is that the failure process can be appropriately simulated by means of a structural model which does not include either the foundation slab or the thermal effects. Finally, results of a probabilistic simulation of the failure pressure are given.

Abstract

The assessment of corroded pipelines is considered a very important task in the oil and gas industry. The present work aims to develop an efficient system to accurately predict the burst pressure of corroded pipelines with complex corrosion profiles through hybrid models using multiresolution analysis, numerical analysis, and metamodels. The corrosion profile is obtained from ultrasonic inspections and the data is provided as a river bottom profile. The real corrosion shapes are parametrized considering a discrete wavelet transform to reduce the amount of data that describes the defect. The coefficients obtained from the wavelet transform are used as inputs to feed a deep neural network system for quickly and accurately predict the burst pipeline pressure. Eight different steel materials are considered in the NN build process. Synthetic models that have similar statistics to real corrosion profiles are created and submitted to non-linear FEM analysis, for the different materials. The failure pressures obtained from the synthetic defects are used to train a neural network to predict the burst pressure of the pipelines. The results obtained with the deep neural networks are very accurate for all cases presented in this work.

Abstract

Aiming at the safety problem of the pipeline containing corrosion defects caused by ground overload, a novel method is developed to assess the safety of buried pipelines with corrosion defects and predict the failure pressure. The effects of parameters including internal pressure, ground overload, length of the loading area, corrosion defect depth, buried depth and soil Young’s modulus, are discussed. Ground overload greatly increases the von Mises stress and strain at the corrosion defect location and decreases the internal pressure threshold. The von Mises stress and strain are an obvious nonlinear relationship with internal pressure. The high stress and strain area expand along the diagonal direction of the defect area. The local stress and strain concentration at the corrosion defect increases with the increase of ground overload, length of the loading area and corrosion defect depth, which reduces the failure pressure of the pipeline. Increasing the buried depth and soil Young’s modulus would effectively reduce local stress and strain concentration, and increase the failure pressure of the pipeline. The pipeline settlement displacement increases with the increase of internal pressure, ground overload, length of the loading area, and decreases with the increase of pipeline buried depth and soil Young’s modulus.