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Application of Bayesian Regularization Artificial Neural Network in explosion risk analysis of fixed offshore platform

机译:贝叶斯正规化人工神经网络在固定海上平台爆炸风险分析中的应用

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Computational Fluid Dynamics (CFD) is routinely used in Explosion Risk Analysis (ERA), as CFD-based ERA offers a good understanding of underlying physics accidental loads. Generally, simplifications were incorporated into CFD-based ERA to limit the number of simulations. Frozen Cloud Approach (FCA) is a frequently used simplification in the dispersion part of the CFD-based ERA procedure. However, its accuracy is questionable in the complex and congested environment such as offshore facility. Furthermore, in explosion part, some specific techniques, e.g. linear/double bin-interpolated techniques have been proposed while the corresponding accuracy is still unknown since the developers did not yet check their accuracy by considering the explosion computational data as the benchmark.
机译:计算流体动力学(CFD)经常用于爆炸风险分析(时代),因为基于CFD的ERA对潜在的物理意外载荷提供了良好的理解。 通常,将简化纳入基于CFD的时代,以限制模拟的数量。 冻结云方法(FCA)是基于CFD的ERA程序的分散部分的常用简化。 然而,它的准确性在诸如海上设施之类的复杂和拥挤的环境中是值得怀疑的。 此外,在爆炸部分中,一些特定的技术,例如一些特定的技术。 已经提出了线性/双箱内插技术,而相应的准确性仍然未知,因为通过将爆炸计算数据视为基准,开发人员尚未检查其准确性。

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