L&T Achieves 2–10X Faster Data Center Design with Reality Digital Twin Platform

Every data center design starts with a deceptively simple question: will the facility keep critical systems within safe thermal limits when conditions change? For hyperscale data centers and AI factories, the answer now carries much higher stakes. Higher rack densities, accelerated compute loads, and tighter reliability expectations leave less margin for thermal uncertainty. Airflow, chilled water, equipment heat, controls, leakage, redundancy, and outdoor exhaust behavior do not operate in isolation—and during backup or failure conditions, small thermal assumptions can quickly become reliability risks.

At CadenceLIVE India 2026, Larsen & Toubro (L&T) presented a technical study on data center thermal management using the Cadence Reality Digital Twin Platform. The study reported 2X–10X productivity gains across preprocessing, simulation, and postprocessing while examining data hall airflow, chilled-water backup, electrical-room ventilation, diesel-generator heat rejection, and site-level exhaust recirculation.

3D external view of a data center

Why Early CFD Simulation Is Important in Data Center Design

Data center performance is often measured through uptime, power capacity, rack density, and redundancy. Inside the facility, those goals become practical thermal and airflow requirements: stable rack inlet temperatures, effective separation of hot and cold streams, resilient backup operation during utility events, and exterior equipment layouts that limit chiller or generator exhaust recirculation.

Computational fluid dynamics (CFD) gives engineers a three-dimensional view of these interactions before construction and commissioning. In the study presented by L&T, CFD served as a design decision tool: it was used to evaluate airflow distribution, temperature fields, pressure behavior, chilled-water response, leakage sensitivity, and failure scenarios rather than treating simulation as a final visualization step.

Inside the Data Hall: Cooling Control and ASHRAE Compliance

With the role of CFD established, L&T first applied the method to the area where thermal performance is most critical: the data hall. The team modeled an air-cooling unit (ACU) control strategy that adjusted fan speed based on temperature difference and differential pressure, while chilled-water flow through the heat exchanger was regulated using off-coil temperature sensing. This approach was designed to keep cabinet inlet temperatures within allowable limits while matching cooling output to the actual operating condition.

Data hall CFD analysis for cooling control and ASHRAE compliance

Using Cadence Reality DC Design within the Cadence Reality Digital Twin Platform, the team evaluated temperature and pressure distribution, cabinet mean inlet air temperature, cooling utilization, chilled-water flow, and compliance to American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) guidelines. Under normal operating conditions, the ACU control strategy reduced cooling power consumption by approximately 9.89%. The result showed that control logic could be tested quantitatively within the data hall model, instead of being assessed only after installation.

Building on the data hall model, the analysis next isolated the effect of leakage. In a failure-mode case where available cooling capacity was roughly equal to cooling demand, leakage pushed several cabinets outside ASHRAE limits. When the same constrained case was evaluated without leakage, the design met compliance requirements. This comparison showed that leakage was a measurable design variable that could influence thermal reliability.

Failure-mode CFD analysis showing leakage impact on ASHRAE compliance

Utility Power Failure: Tracking Thermal Response Over Time

The failure-mode analysis also required a time-based view of thermal response. In the utility power failure scenario, air-cooling unit fans and pumps operate outside an uninterruptible power supply (UPS) backup, leaving the data hall dependent on the system's fault-response strategy.

L&T measured how long server inlet temperatures stayed above 27°C following the event. In the initial controlled case with leakage, the breach time was approximately 295 seconds, which exceeded the customer requirement of 120 seconds.

The simulation helped define a targeted control response. During the transient event, the standard energy-optimized mode was overridden so fans and pumps could ramp to full rated capacity. That adjustment reduced breach time to about 90 seconds and clarified the distinction between two control priorities: efficient steady-state operation and rapid thermal recovery after a fault.

Transient CFD analysis for scenarios with control and without control, resulting in 295s and 90s breach time, respectively

Validating Chilled-Water Backup with 1D Flow Network Analysis

In the chilled-water analysis, L&T used a 1D flow network model in Cadence Reality DC Design to size the chilled-water system and verify the backup duration required before the facility could transition from diesel-generator power back to utility power. The model considered three operating modes: normal, discharge, and recharge. In normal and discharge modes, chilled water from the chillers is supplied to the data hall through the chilled-water system, and return water is routed back to the chillers.

In recharge mode, chilled water bypasses the main chilled-water system and is supplied directly to individual floors, while additional chillers recharge the thermal energy storage (TES) tank.

1D chilled-water flow network analysis for data center backup cooling

In discharge mode, the results show how long the chiller takes to resume supplying chilled water at the design temperature. In the simulation, the chiller returned to the design supply temperature in about 200 seconds, while the TES tank supplied chilled water for nearly 400 seconds during the transition.

1D chilled-water flow network analysis: TES tank sizing in discharge mode

The minimum requirement was 420 seconds of chilled-water availability at each fan wall unit (FWU). The 1D analysis showed at least 480 seconds of availability at each FWU, meeting the requirement with additional margin. Differences in backup time were driven by piping length; for example, floors with longer piping runs experienced a longer delay before chilled water reached the FWUs.

Airflow Redistribution in Raised-Floor Data Halls

Air delivery inside the room introduced another design lever. In a separate raised-floor data hall with cold aisle containment, mechanically controlled floor grilles were evaluated for their ability to redirect cooling air where it was needed most.

Under uniform grille flow, rack inlet temperatures remained outside compliance. CFD results were then used to set damper openings that redirected airflow toward the racks that needed it most. The design reached compliance by redistributing available air rather than increasing total cooling capacity.

Raised-floor data hall airflow redistribution using damper control

Extending CFD Beyond the White Space

The same modeling discipline also applies beyond the IT white space. In electrical rooms, CFD was used to evaluate uninterruptible power supply (UPS) and power distribution unit (PDU) supply temperatures under normal and failure conditions. The maximum temperature was about 29°C, which remained below the 40°C OEM derating threshold. This showed that electrical-room ventilation could be assessed with the same thermal rigor used for server cooling.

Electrical room CFD analysis for UPS and PDU supply-air temperature

At the campus scale, external CFD supported a preliminary 270 MW data center master plan. The study examined chiller exhaust recirculation, the impact of diesel generator exhaust on chillers, and generator exhaust recirculation to understand how outdoor equipment behavior could affect thermal performance.

These effects depend on building geometry, equipment placement, exhaust direction, and wind conditions. The model helped evaluate mitigation options such as exhaust ducting, radiator discharge orientation, chiller containment, increased fan casing height, adiabatic pre-cooling, and alternative water-cooled configurations.

External data center CFD analysis for site-level exhaust recirculation

Workflow Productivity in Data Center CFD

Running these analyses repeatedly depends as much on workflow productivity as on modeling capability. L&T compared Cadence Reality DC Design with other commercial and open-source CFD tools to evaluate how efficiently teams could set up, solve, and report data center CFD studies.

The comparison focused on practical engineering workflow factors: ease of use, data center specialization, data extraction, failure-scenario setup, and overall productivity. As summarized below, L&T reported 2x–10x productivity gains with Reality DC Design Pro across preprocessing, simulation, and postprocessing.

Evaluation Parameter	Cadence Reality DC Design	Other Commercial Software	Open-Source Software
Ease of Use	Easy	Easy-Moderate	Moderate-Difficult
Domain Specialization	Data Center Specific (Vendor Libraries)	General Purpose: Heavy customization required	Require heavy script development
Data Extraction	In Excel format	Time Consuming	Manual
Failure Scenario	Built-in Workflow	Require an advanced user defined function	Complex Setup
Productivity Gain (Including Preprocessing, Simulation, and Postprocessing)	2X – 10X	1.5X - 2X	X

For engineering teams, this productivity gain matters because data center CFD requires repeated scenario evaluation. A single project may include normal-mode studies, failure-mode cases, transient power-event simulations, 1D chilled-water analysis, electrical-room ventilation checks, and site-level recirculation studies. A shorter setup and reporting cycle gives teams more opportunity to iterate before design decisions are locked in.

Connecting Simulation Results with Commissioning Evidence

Simulation becomes more valuable when it carries through to commissioning. In the L&T workflow, CFD results were used alongside system-level checks from the building management system (BMS), supervisory control and data acquisition (SCADA), electrical power management system (EPMS), and functional and integrated system testing.

Comparing simulation results with commissioning data showed satisfactory agreement, giving teams a stronger basis for interpreting thermal behavior before handover. This connection helps validate design assumptions, identify potential failure risks, and confirm that mitigation strategies are supported by both analysis and field evidence.

What This Means for Data Center Thermal Design

The L&T work points to a broader role for CFD in data center thermal design. Beyond individual airflow checks, simulation can connect decisions across the data hall, chilled-water network, electrical rooms, and outdoor equipment layout. By modeling leakage sensitivity, utility-failure response, backup cooling availability, derating risk, and exhaust recirculation together, engineering teams gain a clearer view of how each system contributes to overall facility performance.

This system-level view is especially valuable for hyperscale data centers and AI factories, where higher power density calls for earlier thermal insight, tighter design coordination, and greater confidence before commissioning.

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Ready to evaluate your own data center design before it reaches the commissioning stage? Explore the Cadence Reality Digital Twin Platform to test airflow behavior, chilled-water response, containment strategy, leakage sensitivity, and failure scenarios in a physics-based CFD workflow tailored for data center engineering.

Want to know how L&T used Cadence Reality Digital Twin Platform in an earlier case study? Read the blog