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Dr. Paul Chuo
Stantec Consulting Services Inc.
Building Performance
Professor
Education
Ph.D. in Civil Engineering, University of New South Wales, Sydney, New South Wales
Experience
1. Over 28 years of infrastructure engineering planning and design experiences across Asia
2. PhD in civil engineering from University of New South Wales in Australia
3. Associate Professor Adjunct in Environmental Engineering, NYCU, Taiwan
Speech Title and Abstract
Digital Twins for Energy-Intensive High-Tech Facilities: Realizing Sustainability Through A
Lifecycle AI-Enabled Framework from Early Design to Closed-Loop Operation.
AI-scale data centers and advanced manufacturing facilities are pushing building-services engineering into a new operating regime. Global data-center electricity consumption is projected to reach roughly 945 TWh by 2030, while in semiconductor facilities the HVAC and utility infrastructure alone can account for a major share of total facility energy use. Under these conditions, energy performance is no longer determined primarily by component efficiency in isolation; it is governed by the dynamic interaction of thermal loads, utility generation and distribution, control sequences, redundancy logic, and process-driven operating states. Conventional digital practice such as static BIM during design and point-based BMS/FMCS during operations do not preserve sufficient continuity of system logic, metadata, and performance context to support rigorous lifecycle optimization.
This presentation introduces a lifecycle digital-twin (DT) framework developed for data centers and other high-tech facilities in which the operational twin is not created after handover, but instantiated in early design and matured continuously through design development, commissioning, and operations. The framework consists of three tightly coupled layers: (1) a high-fidelity physics-based Building Energy Model (BEM) representing cleanroom or white-space HVAC, chilled-water plants, condenser-water systems, process cooling, exhaust, power distribution, lighting, and other critical environmental utilities; (2) a live data-exchange layer based on OPC UA, allowing telemetry, equipment states, alarms, and setpoints to be synchronized between the physical facility and the virtual model; and (3) a semantic layer based on the Brick ontology, extended where required through IFC-to-Brick mapping and facility-specific ontology augmentation, so that spaces, assets, sensors, control points, and system relationships remain machine-readable and queryable across all project phases for various Large Language Models (LLMs) and trained agents.
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