Validation of Compressor Surge Rundown Trajectories: Comparative Analysis of Transient Model Predictions and Test Rig Measurements

Abstract Dynamic simulation tools are crucial in the process industry for analysing transient operating scenarios. Accurate models are vital for developing digital twin and adaptive monitoring technologies for turbomachinery applications, particularly compressor systems. Such tools have traditionally been confined to the normal operating area, while specialised models have been required for instability analysis. Recent advances integrate surge models with general-purpose modelling tools, thereby extending their application to severe off-design operation in the surge area. This study documents the transient behaviour of an industrial-sized centrifugal compressor test rig during emergency shutdown. The test cases encompass driver trips and protection system responses, with a focus on the system stability and surge behaviour. The dynamic model, tuned with performance data and incorporating a revised surge model, demonstrates significant improvements over conventional models. Representative surge behaviour is obtained by shifting negatively sloped model curves with a head offset and time lag to match the positive-slope and second-quadrant compressor performance characteristics. The results highlight the accuracy and reproducibility attainable when using well-developed dynamic models and emphasise the importance of accounting for surge behaviour when simulating shutdown. System stability is quantified using the time to surge metric, and its sensitivity to head rise to surge and plenum volume variations is documented. The model’s ability to predict shifts in time to surge is validated.

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Publication Details

Published
2025-06-16
DOI
https://doi.org/10.1115/gt2025-151663
Primary Topic
Turbomachinery Performance and Optimization
Type
article
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article

Validation of Compressor Surge Rundown Trajectories: Comparative Analysis of Transient Model Predictions and Test Rig Measurements

Lars E. Bakken, Alberto Serena, Ola Ilseth Pronk
Turbomachinery Performance and Optimization
article

Validation of Compressor Surge Rundown Trajectories: Comparative Analysis of Transient Model Predictions and Test Rig Measurements

Lars E. Bakken, Alberto Serena, Ola Ilseth Pronk
article en

Abstract

Abstract Dynamic simulation tools are crucial in the process industry for analysing transient operating scenarios. Accurate models are vital for developing digital twin and adaptive monitoring technologies for turbomachinery applications, particularly compressor systems. Such tools have traditionally been confined to the normal operating area, while specialised models have been required for instability analysis. Recent advances integrate surge models with general-purpose modelling tools, thereby extending their application to severe off-design operation in the surge area. This study documents the transient behaviour of an industrial-sized centrifugal compressor test rig during emergency shutdown. The test cases encompass driver trips and protection system responses, with a focus on the system stability and surge behaviour. The dynamic model, tuned with performance data and incorporating a revised surge model, demonstrates significant improvements over conventional models. Representative surge behaviour is obtained by shifting negatively sloped model curves with a head offset and time lag to match the positive-slope and second-quadrant compressor performance characteristics. The results highlight the accuracy and reproducibility attainable when using well-developed dynamic models and emphasise the importance of accounting for surge behaviour when simulating shutdown. System stability is quantified using the time to surge metric, and its sensitivity to head rise to surge and plenum volume variations is documented. The model’s ability to predict shifts in time to surge is validated.

Norwegian University of Science and Technology (NO)
Industry, innovation and infrastructure
Openalex Percentile: Top 71%
Turbomachinery Performance and Optimization
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