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Failure Analysis and Forensic Engineering Views: 563 Downloads: 289 Vol. 20, No. 76 (2026) January 6, 2026 pp. 49-66

Hybrid feedforward neural network for pressure vessel internal corrosion prediction: integrating chemical models with inspection data for structural integrity assessment

Mina Pascal

This study presents a hybrid framework integrating a physics-based corrosion model with a feedforward neural network (FNN) to predict corrosion rates and estimate the remaining useful life (RUL) of industrial pressure vessels for…

10.3221/IGF-ESIS.76.04

Details: Hybrid feedforward neural network for pressure vessel internal corrosion prediction: integrating chemical models with inspection data for structural integrity assessment Graphical Abstract PDF HTML

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Analytical, Numerical and Physical Models Views: 1,040 Downloads: 1,659 Vol. 16, No. 60 (2022) March 25, 2022 pp. 187-212

FFS Master Software For Fitness-For-Service Assessment of Hydrogen Induced Cracking Equipment Based on API 579-1/ASME FFS-1

Razieh Karimihaghighi, Masoumeh Naghizadeh, Sirus Javadpour

Over time, industrial equipment, particularly in the oil, gas, and petrochemical industries, is subjected to various forms of degradation and damage that can affect its structural integrity. Most of the Codes and Standards pertaining to…

10.3221/IGF-ESIS.60.14

Details: FFS Master Software For Fitness-For-Service Assessment of Hydrogen Induced Cracking Equipment Based on API 579-1/ASME FFS-1 PDF Visual Abstract

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Hybrid feedforward neural network for pressure vessel internal corrosion prediction: integrating chemical models with inspection data for structural integrity assessment

FFS Master Software For Fitness-For-Service Assessment of Hydrogen Induced Cracking Equipment Based on API 579-1/ASME FFS-1