Compressor Blade Corrosion Prediction Using Environmental Digital Twins
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Turbomachinery compressors face significant corrosion and degradation due to varying environmental conditions, leading to fatigue and pitting, which increases the likelihood of cracking and results in costly downtime and unplanned outages, with current modeling techniques being insufficient in predicting fatigue-based failures under corrosive environments.
Innovation Solution
A control system and method that use processors to determine contaminant loading and corrosion contaminant concentration on compressor blades based on environmental and atmospheric conditions, creating a digital twin to simulate and predict corrosion damage, allowing for real-time operator decisions on maintenance and repair schedules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current modeling techniques are used to predict fatigue failures, then prediction capability is provided, but accuracy in predicting fatigue-based failures under corrosive environments is insufficient
Solution Approach 1:
The patent transforms the prediction approach by changing parameters from generic fatigue modeling to specific corrosive environment parameters. It introduces new parameters including contaminant loading, corrosion contaminant concentration, salt-fouling characteristics, and condensation phenomena to accurately represent the corrosive environment and its impact on fatigue failure prediction
Solution Approach 2:
The patent introduces a digital twin as an intermediary between physical compressor operation and failure prediction. This digital twin model serves as a mediator that integrates environmental data, operational parameters, and corrosion mechanisms to provide accurate fatigue failure predictions without requiring direct intervention in the physical system
2Productivity
If compressor operates longer in corrosive environments, then productivity is maintained, but pitting corrosion increases and fatigue capability reduces
Solution Approach 1:
The patent applies preliminary action by predicting corrosion damage and fatigue risk before actual failures occur. The system continuously monitors environmental conditions and operational parameters to forecast when contaminant loading and corrosion contaminant concentration will reach critical levels, enabling maintenance to be performed proactively before fatigue capability is significantly degraded
Solution Approach 2:
The patent implements feedback through the digital twin system that continuously compares predicted corrosion damage with actual operational conditions. The system uses environmental data, contaminant loading measurements, and fatigue model updates to provide real-time feedback on blade health status, allowing operators to adjust maintenance schedules based on actual corrosion risk rather than fixed intervals
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system effectively predicts aqueous corrosion damage, reducing the probability of fatigue-related failures by accurately modeling salt-fouling and condensation phenomena, enabling proactive maintenance and minimizing downtime and repair costs.
Implementation Method 1
during downtime as the blades of the turbocharger compressor cool down to ambient temperature, condensation phenomenon occurs. The longer the downtime, the higher the probability that condensation will occur, thereby resulting in a thin film of water, dust and salt accumulated during operation.
Implementation Method 2
While during flights and operation the ingestion of salts and dust creates a deposit on the surface of the blades and vanes.
Data Source
AI summary
A control system and method utilizing one or more processors that are configured to determine contaminant loading of blades of a turbomachinery compressor based on one or more environmental conditions to which the turbomachinery compressor is exposed and one or more atmospheric air inlet conditions of the turbomachinery compressor. The one or more processors then determine a corrosion contaminant concentration on the blades of the turbomachinery compressor based on the contaminant loading that is determined and determine an upper limit on or a distribution of potential corrosion of the blades of the turbomachinery based on the corrosion contaminant concentration, at least one of the environmental conditions to which the turbomachinery compressor is exposed, and the corrosion contaminant concentration that is determined.