EngineeringYouTube (CADFEM APAC)|April 16, 2026
CADFEM APAC’s YouTube video presents a digital twin approach for data center cooling using Ansys simulation tools, demonstrating how it integrates physics, AI, and real-time data for predictive thermal management. Data center engineers should watch to understand how this method enables proactive cooling adjustments and energy savings.
- Digital twin integrates physics-based simulation, AI-driven prediction, and real-time sensor data to forecast temperature behavior.
- CFD model built with Ansys Fluent simulates server heat generation and fan-driven airflow under varying conditions to generate training data.
- Temporal fusion transformer model uses historical data, heat loads, fan speeds, and calibrated states for time series temperature forecasting.
- Moving horizon estimation combines sensor data with model predictions to maintain digital twin accuracy despite noisy or limited inputs.
- System predicts future temperatures and identifies potential hotspots, allowing preventive actions.
- Applications include dynamic fan speed adjustments, energy consumption reduction, anomaly detection, and improved operational planning.







