Sensitivity Analysis of a Calibrated Data Center Model to Minimize the Site Survey Effort

To reproduce a Digital Twin (DT) of a data center (DC), input data is required which is collected through site surveys. Data collection is an important step since accurate representation of a DC depends on capturing the necessary detail for various model fidelity levels of each DC component. However, guidance is lacking in this regard as to which components within the DC are crucial to achieve the level of accuracy desired for the computational model. And determining the input values of the component object parameters is an exercise in engineering judgement during site survey. Sensitivity analysis can be an effective methodology to determine how the level of simplification in component models can affect the model accuracy.In this study, a calibrated raised-floor DC model is used to study the sensitivity of a DC component’s representation to the DC model accuracy. Commercial CFD tool, 6SigmaDC Room is used for modeling and simulation. A total of 8 DC components are considered and eventually ranked on the basis of time and effort required to collect model input data. For parametrized component object, the object’s full range of input parameter values are considered, and simulations run. The results are compared with the baseline calibrated model to understand the trade-off between survey effort/cost and model accuracy. For the calibrated DC model and of the 8 components considered, it was observed that the chilled water piping branches, data cables and the cable penetration seal (found within cabinets) have considerable influence on the tile flow rate prediction accuracy.