ENG. ANDREW OMWENGA
Chemical & Process Simulation Engineer • Thermodynamic Specialist
Crude Preheat Train Fouling & Furnace Optimization
Section 1.0 — Simulation & Facility Metadata
Section 2.0 — Executive Summary
Quantifying energy penalties, furnace duty increases, and carbon emission surges resulting from severe exchanger fouling in a 100,000 kg/h crude distillation unit (CDU).
Section 3.0 — Problem Statement & Operating Bottlenecks
Crude preheat train fouling reduces recovered heat across E-101/102/103 exchangers and forces the fired heater (furnace) to consume additional fuel to maintain the CDU feed temperature at 350 °C.
Section 4.0 — Objectives & Rigorous Simulation Methodology
Rigorous Aspen HYSYS steady-state simulation coupled with Python via Win32 COM API for automated sensitivity analysis. Exchanger performance degraded progressively from clean U=450 W/m²K to U=180 W/m²K under severe fouling.
Section 5.0 — Simulation Results & Thermodynamic Findings
The +29.2% duty penalty under severe fouling places significant thermal stress on fired heater tubes, driving up bridge wall temperatures and approaching thermal flux limits. Implementing predictive cleaning automation when furnace inlet temperature drops below 195 °C yields a net annual saving of over $500,000 post-cleaning costs.
Section 6.0 — Core Engineering Takeaways
Section 7.0 — Model Assumptions & Future Recommendations
Model assumes constant crude oil composition (32 API gravity) and steady-state thermal operation without temporal tube skin oxidation dynamics.
Integration with Aspen HYSYS Dynamics to capture transient thermal inertia during furnace firing rate ramping.
Section 8.0 — Consultant Conclusion & Verification Sign-off
Crude preheat train fouling is not merely an operational inconvenience; it is a major energy and environmental liability. Dynamic simulation-based monitoring allows refineries to optimize cleaning cycles before severe fuel penalties accumulate.
