So, how do you make the model dependable? How do you calibrate it? Seymour’s paper provides introductory answers to exactly that question, highlighting that it is a fairly simple process, but one that benefits from a systematic approach. Instead, “owner-operators and consultants must exercise due diligence: review and measure the actual installation, then improve the accuracy of the model until it produces dependable results”. “That renders the model useless”, says Seymour. Why? Because low-fidelity models (garbage in) lead to inaccurate results (garbage out) that bear no resemblance to reality (uncalibrated).įor some, the solution to the “garbage in, garbage out” challenge is not to improve the model and calibrate it, but to lazily fix the results of the model to match what is being seen in real life. Summed up colloquially as “garbage in, garbage out”, the most pressing dangers for predictive modelers are that their computer models lack fidelity and are uncalibrated.
“while the overall facility is complex, many of the individual elements can be individually assessed”įor many data center owner-operators, using computational fluid dynamics (CFD) simulations to predictively model the impact that future changes will have on availability, physical capacity and cooling efficiency (ACE), or to help resolve ACE problems in a data center, is second nature.Īnd, despite the historical connotations that CFD brings to mind – a complex and intimidating solution requiring expert knowledge to use – the reality is that predictive modeling has never been simpler or easier for the lay person to take advantage of.īut the success of predictive modeling still lies ultimately in the hands of the user. Aimed at owner-operators, What is a Valid Data Center Model? An Introduction to Calibration for Predictive Modeling brings clarity to an area of data center operations that is increasingly important. What is a Valid Data Center Model? An Introduction to Calibration for Modeling & Simulationįuture Facilities’ CTO Mark Seymour publishes the first in a series of white-papers discussing model refinement and calibration when predictively modeling a data centerįuture Facilities, a leading provider of data center design and operations management software, today announced that Mark Seymour, data center cooling expert and chief technical officer at Future Facilities, has published the first in a series of white papers explaining the importance of model refinement and calibration when predictively modeling the availability, physical capacity and cooling efficiency of a data center.
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