{"id":15179,"date":"2019-04-25T11:00:47","date_gmt":"2019-04-25T19:00:47","guid":{"rendered":"http:\/\/www.palada.net\/index.php\/2019\/04\/25\/news-8928\/"},"modified":"2019-04-25T11:00:47","modified_gmt":"2019-04-25T19:00:47","slug":"news-8928","status":"publish","type":"post","link":"http:\/\/www.palada.net\/index.php\/2019\/04\/25\/news-8928\/","title":{"rendered":"Results are in! Our Study Measuring the Different Levels of Data Center Air Containment"},"content":{"rendered":"

Credit to Author: Victor Avelar| Date: Thu, 25 Apr 2019 15:18:07 +0000<\/strong><\/p>\n

In an earlier blog<\/a> I explained the problem with \u201cpercent leakage\u201d in regards to air containment and I proposed some more practical metrics. To quantify these metrics, we set up a test at the Innovation Executive Briefing Center<\/a> in St. Louis. In this blog, I discuss that study we performed in our cooling lab \u2013 with the help of Scott Buell and his awesome team.<\/p>\n

Our Containment Study: the setup<\/h2>\n

We set up a 2-row pod, including four racks in each row with hot aisle containment (HAC) ducted back to the CRAH. \u00a0Although we had a raised floor, we took a hard floor approach where the CRAH supply air flooded the room (no perforated tiles anywhere). This \u201cbowling alley\u201d layout, where the CRAH supply jet crashes against the side of the pod, provided a worst case for our testing. We had 6 temperature sensors attached vertically across each rack. Other sensor arrays were placed in the hot aisle, CRAH return, CRAH supply, and in the cold aisle. We used a power meter for the CRAH and monitored power for all the server simulators. We also used a very sensitive pressure sensor<\/a> in the hot aisle that gave us an indication of the balance between CRAH supply air and IT airflow. This pressure sensor becomes less useful with less containment, but if you have 100% blanking panels, use aisle doors, and duct the hot or cold aisle, I would recommend using a pressure sensor. All this data was collected with two data loggers and fed back to a workstation.<\/p>\n

Removing Variables \u2013 Controlling the Test-environment<\/h2>\n

Our tests started with finding the minimal airflow required to cool the servers in an ideal \u201cairtight\u201d case (yes, with lots of tape). Then we introduced practices that resulted in leakage. In all, we ran 44 cases. The ideal \u201cairtight\u201d case started with a standard HyperPod<\/a> containment solution with brush strips, doors, hot aisle duct to the CRAH return, and 8 racks at kW densities 7, 2, 5, 9.5, 2, 12, 4, and 3.5. (a total of 45kW with an average of 5.7kW\/rack). We used 15 server simulators, 10U each, to simulate the stated densities. Then, to make it airtight, we used cardboard and gaff tape to cover up every single penetration we could see. This took about one week to seal everything, including cable penetrations. Every gap was covered in cardboard and tape except for the server simulators. I don\u2019t recommend this\u2026 super time consuming! Measurement is also time consuming because you have to wait 25-100 minutes for the temperatures to reach steady state, for every change you make.<\/p>\n

Note that when the test called for missing blanking panels, we color-coded the panels to ensure we consistently removed the same panels. We had three cases: 100% panels installed (186 total panels), 87% installed, and 60% installed.<\/p>\n

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Setting the Benchmark with the Ideal \u2018Airtight\u2019 Case<\/h2>\n

By changing the CRAH fan speed we found the airflow at which there was nearly a zero-pressure difference between the hot and cold aisle (this gives us a good indication that the CRAH and IT airflows are about the same). Then we opened the CRAH chilled water valve to bring the average IT supply air temperature at the rack fronts to 21\u00b0C\/70\u00b0F (our target for all cases). Once we measured our ideal \u201cairtight\u201d case, we were able to benchmark the subsequent \u201cleaky\u201d cases to this baseline. What where the metrics for our ideal airtight baseline?<\/p>\n