CASE STUDIES » DIGITAL TWIN

Case Studies

Explore how Turbine Logic helps companies like yours optimize the performance of your assets through advanced analytics, diagnostics, and engineering expertise.

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AI TECHNIQUES AI/ML TECHNOLOGIES ALGORITHM DEVELOPMENT ANALYSIS TECHNIQUES ANALYTICAL SIMULATION ANALYTICS ANOMALY DETECTION APR DIAGNOSTICS AUTO-CALIBRATION AUTOMATED CALIBRATION AUTOMATED RECONCILIATION BAYESIAN NETWORKS
AI-Powered Dispatch Optimization for Power Generation Assets

Power generation operators managing multiple assets often struggle to balance competing priorities: responding quickly to grid demands, maintaining optimal efficiency, and minimizing maintenance impacts across their fleet. Traditional dispatch approaches rely on static models that fail to account for real-time equipment health, leading to suboptimal bidding strategies and reduced profitability.

Aeroderivative Gas Turbine Digital Twin Development

A power generation operator sought to expand their monitoring and diagnostic capabilities for aeroderivative gas turbines. While digital twin technology had proven valuable for frame-type units, the client needed similar capabilities extended to a different class of equipment, along with support for implementing advanced combustion monitoring techniques.

Cycle Model Development for Gas Turbine Fault Diagnostics

A client sought to improve their ability to detect and diagnose equipment faults in their gas turbine fleet before they led to costly unplanned outages. Traditional monitoring approaches were reactive, often identifying problems only after performance had already degraded significantly.

Digital Twin Model Development for Industrial Gas Turbines

A client needed to expand their gas turbine monitoring and diagnostic capabilities to cover additional equipment types within their fleet. Existing digital twin models were limited to certain turbine configurations, creating gaps in their ability to perform comprehensive performance analysis across all assets.

Firing Temperature Assessment for Heavy-Duty Gas Turbines

A power generation client needed to understand whether maintenance activities had impacted the firing temperature of their heavy-duty gas turbine fleet. Changes in firing temperature can significantly affect both performance and component life, making accurate assessment critical for operational decision-making and long-term asset management.

Gas Turbine Digital Twin Development and Deployment

A client in the power generation industry sought to enhance their operational capabilities through advanced digital modeling of gas turbine assets. The goal was to create a sophisticated monitoring solution that could provide deeper insights into turbine performance and support data-driven decision making.

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