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<p>Multiple industries depend on heat exchangers because they provide essential thermal energy transfer functions which power generation, oil refining, chemical processing and HVAC systems require. The system fails because tube materials which comprise carbon steel, stainless steels, copper, brass, nickel alloys, Inconel and titanium materials cannot withstand extreme thermal, chemical and mechanical damage. Corrosion mechanisms (pitting, crevice, galvanic, erosion-corrosion, MIC, dealloying) exhibit material-specific behaviours like stainless steels suffer localized attack and sensitization, carbon steel undergoes rapid thinning, copper/brass experience dezincification, while nickel alloys/Inconel offer superior resistance. The combined effect of mechanical failures and metallurgical defects induces an accelerated process that leads to tube deterioration. The review conducts a systematic assessment of failure modes which show material-specific performance characteristics while using the causative factors, diagnostic techniques and mitigation strategies to create a complete body of knowledge. The implementation of artificial intelligence (AI) and machine learning (ML) technologies enables organizations to conduct predictive maintenance while analyzing real-time sensor data which includes temperature and vibration and corrosion rates to enhance their ability to forecast equipment failures and implement strategies based on equipment condition. The study found that AI/ML-driven monitoring, advanced materials optimization, precise fabrication controls and intelligent design methods help engineers create heat exchanger systems which exhibit decreased failure rates, unplanned outages and reduced lifecycle costs.</p> Graphical Abstract <p></p>

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Comprehensive Review on Failure Mechanisms in Heat Exchanger Tubes: Insights into Material Degradation, Corrosion, and Design Flaws

  • 期刊论文

  • 发表日期：

    2026年4月29日

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  • Mohamed Fayas Saffiudeen,
  • Vasanth Swaminathan,
  • Abdullah Wahid Fathi

摘要

Multiple industries depend on heat exchangers because they provide essential thermal energy transfer functions which power generation, oil refining, chemical processing and HVAC systems require. The system fails because tube materials which comprise carbon steel, stainless steels, copper, brass, nickel alloys, Inconel and titanium materials cannot withstand extreme thermal, chemical and mechanical damage. Corrosion mechanisms (pitting, crevice, galvanic, erosion-corrosion, MIC, dealloying) exhibit material-specific behaviours like stainless steels suffer localized attack and sensitization, carbon steel undergoes rapid thinning, copper/brass experience dezincification, while nickel alloys/Inconel offer superior resistance. The combined effect of mechanical failures and metallurgical defects induces an accelerated process that leads to tube deterioration. The review conducts a systematic assessment of failure modes which show material-specific performance characteristics while using the causative factors, diagnostic techniques and mitigation strategies to create a complete body of knowledge. The implementation of artificial intelligence (AI) and machine learning (ML) technologies enables organizations to conduct predictive maintenance while analyzing real-time sensor data which includes temperature and vibration and corrosion rates to enhance their ability to forecast equipment failures and implement strategies based on equipment condition. The study found that AI/ML-driven monitoring, advanced materials optimization, precise fabrication controls and intelligent design methods help engineers create heat exchanger systems which exhibit decreased failure rates, unplanned outages and reduced lifecycle costs.

Graphical Abstract