CASE STUDIES » MODEL ORDER REDUCTION

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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Other Studies

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.

Legacy Software Modernization for Continued Platform Compatibility

A client faced a growing compatibility challenge with a critical performance monitoring tool that had been in use for years. The software relied on older architecture that was becoming increasingly incompatible with modern computing environments as industry standards evolved.

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.

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.

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.

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