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Current Methods and Technologies for Storage Tank Condition Assessment: A Comprehensive Review.

Alexandru-Adrian Stoicescu1, Razvan George Ripeanu1, Maria Tănase1

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Summary
This summary is machine-generated.

This study explores advanced non-destructive testing (NDT) methods and technologies for storage tank assessment. Implementing robotics, AI, and standardized software can significantly enhance inspection efficiency and accuracy.

Keywords:
condition assessmentequipment lifetimelifetime extensionnon-destructive testingoil storagestorage tank

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Area of Science:

  • Materials Science and Engineering
  • Mechanical Engineering
  • Asset Integrity Management

Background:

  • Current storage tank assessment relies on established non-destructive testing (NDT) methods.
  • There is a continuous need to improve the efficiency, economy, and accuracy of these inspections.
  • Technological advancements offer new possibilities for enhancing tank integrity assessment.

Purpose of the Study:

  • To investigate current industry practices for storage tank assessment.
  • To explore the potential of modern technologies for improving inspection methods.
  • To present advanced analysis techniques for determining tank lifetime expectancy.

Main Methods:

  • Review of current non-destructive testing (NDT) technologies and their advancements.
  • Exploration of robotic/drone and autonomous device applications in NDT.
  • Integration of automated inspection procedures, including remote video inspection, thickness measurement, and 3D scanning.
  • Application of advanced analysis methods: analytical calculations, Finite Element Analysis (FEA), and AI-driven data processing.
  • Utilizing digitalized equipment models (Digital Twin) for comprehensive analysis.

Main Results:

  • Robotics, drones, and autonomous devices can significantly improve NDT efficiency.
  • Automated inspection procedures like remote video and 3D scanning offer enhanced data collection.
  • Advanced analysis methods, including FEA and AI, improve the accuracy of lifetime expectancy predictions.
  • Digital Twins combined with AI provide powerful tools for data processing and condition assessment.
  • Standardized software is crucial for efficient and consistent tank condition assessment.

Conclusions:

  • The integration of advanced technologies like AI, robotics, and Digital Twins revolutionizes storage tank assessment.
  • Automated and data-driven approaches enhance the efficiency, accuracy, and economic viability of inspections.
  • Development and adoption of dedicated standardized software are key to optimizing the tank condition assessment process.