Digital Twin, Predictive Analytics & AI

A Smarter, Predictive Approach to Data Center Operations

Modern data centers operate under increasing thermal, electrical, and workload variability, making real-time insight and predictive control essential. GT-SUITE enables the creation of high-fidelity, simulation-driven digital twins that combine multi-physics simulation, operational data, and AI-driven analytics to detect faults early, optimize performance continuously, and support resilient, energy-efficient operation.

GT-Play transforms simulation models into interactive, visual experiences that anyone in your organization can use. It brings your digital twins to life, allowing users to manipulate parameters, test scenarios, and see results instantly. Take it even further, with GT-Play, these digital twins become interactive across the organization, enabling engineers and non-technical stakeholders to experiment, validate decisions, and explore scenarios safely.

Highlights

Up to real-time replication of thermal, power, and airflow behavior
Web application & API-based access through
GT-Play for engineers and non-engineers
Early fault detection and predictive maintenance insights
ML-enhanced optimization for cooling, power, and energy efficiency
Safe, rapid simulation of failure modes and “what-if” scenarios

Impact

Higher Uptime

Proactive Risk Mitigation

ML-enhanced optimization

Better control strategies

Digital Twin, Predictive Analytics & AI Capabilities

Real-Time Monitoring & Virtual Facility Replication

A GT-SUITE digital twin acts as a living, continuously updated replica of your data center. It mirrors real-world thermal, power, and airflow behavior in up to real-time, enabling operators to detect anomalies early, visualize performance trends, and understand system behavior long before issues escalate into downtime events.

GT PLAY

GT-SUITE in Digital Twin Environments

Predictive Fault Detection & Reliability Modeling

GT-SUITE supports early fault detection by providing high-fidelity simulation data and machine learning models that can be integrated into digital twin environments. Through virtual sensors and detailed component modeling, engineers can identify degradation patterns across pumps, valves, chillers, fans, UPS systems, and other electrical components. This enables the detection of fault signatures, prediction of failure timelines, and safe evaluation of worst-case scenarios. By complementing broader monitoring systems, GT-SUITE helps reduce unplanned outages, improve maintainability, and enhance long-term reliability.

ML-Driven Predictive Analytics & Optimization

By providing advanced machine learning workflows, GT-SUITE allows users to train intelligent models using both facility data and physics-based simulation outputs. This fusion dramatically improves prediction accuracy for anomalies, performance deviations, and energy optimization. Engineers can run extensive design explorations, validate system resilience under extreme conditions, and leverage surrogate modeling to accelerate computation without compromising accuracy.

GT-Play: Accessible, Interactive Simulation for Everyone

With GT-Play, digital twins become accessible through an intuitive web interface that requires no installations or specialized engineering expertise. Facility managers, analysts, and non-technical stakeholders can explore models, run simulations, adjust parameters, and visualize results in real time. GT-Play allows both tailored interfaces for user interaction and process integration via APIs.

GT-Play CDU