Design complete, not yet tendered
Validation coverage is at its widest: space, thermal, hydraulics, and network can all still be changed on the drawings.
Data Center Digital Twin
Catch design errors before construction and avoid costly rework
KONST uses NVIDIA Omniverse to turn design drawings into a one-to-one 3D model and validates space, thermal, hydraulic, power redundancy, and network architecture before construction, delivering a construction-ready design and a list of issues resolved in advance. The model serves as the single source of truth, and every design change is validated against it.
PROBLEM｜ Customer challenges
High-density facility mistakes only surface after power-on
Most data center design experience comes from low-density loads. Applied to racks drawing tens of kilowatts, hotspots, airflow short-circuits, and power distribution issues often appear only after power-on, when fixes cost far more than adjustments before construction.
Tendered, equipment not yet on site
Re-run the simulation with the equipment models actually ordered, correcting rack layout and piping before arrival.
Equipment on site, not yet powered
Compare the model against the physical installation to find gaps between simulation and site, and resolve them before power-on.
Retrofitting an existing facility
Load capacity, ceiling height, power capacity, and existing piping are fixed constraints; a first run in the model shows the retrofit's upper limit.
SOLUTION｜ The KONST approach
Design, delivery, and operations in one complete process
The model is not a one-off acceptance document. It validates the design before construction, is calibrated to match the site at delivery, and keeps answering capacity questions with live data after go-live.
Design validation
Resolve spatial clashes, hotspots, hydraulic imbalance, and power redundancy issues at the drawing stage, delivering construction-ready validation results.
Delivery calibration
After power-on, the model's behavior is tuned to match the actual facility, and it becomes the site's reference baseline from then on.
Operations optimization
Connected to live operating data, the model stays current so capacity and layout decisions follow actual conditions rather than design assumptions.
DESIGN VERIFICATION
Validation dimensions and primary deliverables
| Dimension | Validation scope | Primary deliverable |
|---|---|---|
| Space | Physical clashes between piping, power paths, cable trays, and structure | Clash detection report |
| Thermal | CFD analysis of full-load airflow and cooling efficiency | Thermal simulation results and redundancy margin |
| Hydraulics | Liquid-cooling pipe pressure drop, flow velocity, and branch distribution | Hydraulic balance simulation results |
| Failure drill | Temperature rise and response window after CDU or CRAC shutdown | Basis for judging whether redundancy is sufficient |
| Power | Verification of N+1 or 2N power distribution redundancy | Architecture review comments |
| Network | Leaf-Spine topology, non-blocking switching, and oversubscription ratio | Logical topology diagram and port mapping matrix |
| Cabling | Cable routing planned in the 3D environment | Actual length list for every cable |
BENEFIT｜ Benefits
After go-live, the model turns from a validation tool into an operations tool
Once the model stays in sync with the actual facility, it is calibrated with live digital data; subsequent expansion planning, asset audits, and failure assessments all happen on the same calibrated model.
Shorter time from equipment to usable capacity
The model stays in sync with telemetry, assets, and existing tools, so pre-deployment validation needs no remodeling.
Surface gaps and errors in asset data
With data consolidated into one model, unmaintained, duplicated, or mismatched records surface immediately, raising asset accuracy.
Consolidate data scattered across systems
MEP monitoring, power management, and asset data are read on one platform, and cross-team changes and reviews happen on the same model.
FAQ
We already have design drawings. Do we still need digital twin validation?
Drawings answer "what will be built"; simulation answers "will it work once built." Thermal behavior, hydraulic balance, and clashes in high-density facilities cannot be read from 2D plans and require a 3D model with physics simulation. The more complete the drawings, the more specific the validation feedback.
What information do we need to provide for a digital twin?
Architectural and MEP drawings, equipment lists with power and heat parameters, rack layout and power planning, and the network topology. The more complete the data, the closer the model matches reality; missing items can be estimated with assumptions, and the applicable scope of conclusions is noted accordingly.
If the design changes midway, does validation need to be re-run?
Every design change is validated on the same model, with traceable versions and change history.
Our facility is already in operation. Can we still build a digital twin?
Yes. An operating facility is modeled and connected to live power and environmental data, used for capacity audits, simulations before new equipment is racked, and failure-scenario analysis. This is a different use case from pre-construction design validation.
Want to validate the design before breaking ground?
Send us your drawings and equipment list, and we will reply with the validation scope and timeline.