CASE STUDIES » STAGE STACKING MODELS

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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PERFORMANCE TECHNICAL ADVISORY

GAS TURBINES

AMBIENT AIR QUALITY DATA ANALYSIS CALIBRATION TO FIELD DATA COMBINED CYCLE ANALYSIS COMPRESSOR EFFICIENCY DEGRADATION TRACKING COMPRESSOR FOULING PREDICTION COST COMPARISON ANALYSIS DATA PROCESSING AND ANALYSIS DATA VISUALIZATION DISCOUNT RATE APPLICATIONS ECONOMIC ANALYSIS EMPIRICAL CORRELATIONS ENERGY OUTPUT CALCULATIONS

Gas Turbine Filtration Life Cycle Cost Analysis Tool Development

A client needed a way to evaluate the economic impact of different air filtration strategies for their gas turbine operations. The challenge involved balancing multiple competing factors: filter efficiency, pressure drop effects on turbine performance, maintenance costs, water wash scheduling, and long-term operational expenses.

Other Studies

Sensor Health Monitoring for Gas Turbine Operations

Gas turbine monitoring and diagnostics centers frequently encounter false alarms that consume valuable time and resources. Many of these false alarms stem from issues within the instrumentation chain: sensors that have drifted, failed, or produced corrupted data during transmission or storage.

Combustion Dynamics Monitoring Implementation

A power generation company sought to enhance their gas turbine fleet monitoring capabilities, particularly around combustion dynamics. They needed a solution that could provide early detection of anomalous behavior related to instrumentation issues, tuning problems, and potential hardware damage before these issues led to costly unplanned outages or equipment damage.

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.

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.

Digital Twin Framework Development for the Power Generation Industry

A client in the power generation sector recognized that digital twin technologies were being developed inconsistently across their organization, leading to duplicated efforts and challenges in deploying these tools effectively. Without a standardized approach, teams struggled to leverage real-world operational data, create adaptable models, and integrate emerging technologies like AI and machine learning into their workflows.

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