Background

Distillation is a fundamental separation process in chemical and petrochemical industries, but its efficiency and stability depend strongly on the control of reflux and boilup rates, instrumentation reliability, and energy utilization. The primary objective was to evaluate the feasibility of automatic control strategies for this pilot-scale unit, identify sources of measurement error, and recommend improvements for more stable and energy-efficient operation.

Action

Our approach integrated experimental testing, data reconciliation, and simulation modeling to evaluate control performance and system reliability:

System Setup and Instrumentation:

Operated the LSU Packed Distillation Unit, consisting of 4.9 meters of structured packing, a thermosyphon reboiler, and a water-cooled condenser. Measurements were taken for flows, temperatures, and compositions using orifice flow meters, RTDs, and gas chromatography (GC). Calibration of flow meters and GC instruments was performed to improve measurement accuracy.

Experimental Design:

Conducted four steady-state runs at two pressures (100 and 120 mmHg) with a nominal reflux ratio of 1.0, collecting comprehensive data on flowrates, temperature profiles, and compositions of feed, distillate, and bottoms streams.

Mass and Energy Balances:

Applied conservation equations to assess process consistency.

Observed small mass residuals (7.7–10.2 kg/h) and energy deficits (~15 W), primarily attributed to valve instability and unsteady reflux flow.

Implemented data reconciliation to refine measurements and identify gross errors, confirming that deviations were random and instrumentation was generally reliable.

GC Calibration and Regression Analysis:

Prepared four calibration standards of known water/PG compositions to quantify analytical precision (standard deviation ≈ 3%).

Improved GC accuracy using regression-derived response factors, increasing the correlation coefficient (R²) from 0.9512 to 0.9778—a significant enhancement in measurement reliability.

Aspen Plus Simulation and Benchmarking:

Simulated the water/PG system in Aspen Plus to establish benchmarks for minimum reflux ratio and number of theoretical stages.

The model predicted four ideal stages and a minimum reflux ratio of 0.019 for 99.5% water purity.

Experimental temperature profiles aligned with the simulated trend but were 6–8°C lower due to non-adiabatic heat losses, confirming realistic operation despite energy inefficiencies.

Control Performance Evaluation:

Analyzed control-valve performance for both steam and reflux loops.

Found steam flow deviations of 5–60% and reflux flow deviations up to 300% at low valve openings (<20% travel), demonstrating oversized valves and poor controllability near closed positions.

Verified that while steam control remained manageable with manual supervision, reflux control was unstable, requiring constant operator intervention.

Control Strategy Recommendations:

Proposed an improved cascade control architecture with a reflux-ratio controller (outer loop) and a reflux-flow controller (inner loop), supplemented by steam-flow feedforward and constraint overrides for reboiler level and column pressure. This structure enhances automatic control, reduces operator workload, and stabilizes product purity during operation.

Result

The experimental and simulation results validated that the distillation column operated stably at vacuum conditions, achieving predictable temperature gradients and steady separation performance. However, control analysis revealed significant limitations in the current reflux-valve configuration, making precise ratio control infeasible without intervention.

The reconciled dataset and regression-enhanced GC calibration improved data consistency and mass-balance closure, enabling more confident evaluation of process performance.

The final recommendations—valve resizing, cascade reflux control, and steam feedforward coordination—provide a clear pathway to automate operation, reduce energy consumption, and enhance process reliability.

This project strengthened my skills in process control analysis, mass and energy balancing, data reconciliation, and process simulation (Aspen Plus), as well as my ability to connect theoretical control concepts with practical engineering implementation.