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Harness AI Opinions with Sensor Facts - sensorCFD AI.pdf

2026-05-16
文档编号:1240937
文档页数:35
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1、Harness AI Opinions with Sensor FactsQuicklime AI Enabled Thermal Optimization2 Established in the USA in 1981 Worlds oldest and largest manufacturer of sensors for the data center Over 250,000 installations worldwide 250 page catalog of sensor solutions3Quicklime DCIM Digital Twin AI Toolkit for Da

2、ta Center Optimization Sensor Backed Computational Fluid Dynamics(sensorCFD)Power Train Management Capacity AI Video AI Easy Configuration AI4Data Center Thermal Optimization AI Generated CFD and Data Center Analysis Identify Hotspots Identify Coldspots Identify Stranded Capacity Report that details

3、 underlying causes and solutions5No Containment6Hot Aisle Containment7Hot Aisle Containment8Cold Aisle Containment9Cold Aisle Containment10Cold Aisle Containment1112Cold Aisle sensorCFD AI Report1)What do I see in the slices?Temperature slices:Temperature is not uniform across rack rows.Local warm r

4、egions appear near room boundaries and around the containment perimeter(localized risk).Partial mixing between cold and warm streams.Streamlines:Flow is dominated by a few high-momentum paths(jet-like features)rather than an even sweep across all aisles.Several regions show weak vectors/low circulat

5、ion,consistent with dead zones where heat removal can degrade.Recirculation loops are visible near corners and near the containment boundary,indicating local flow reversals.2)What are the physical causes?Supply short-circuiting:a portion of supply air travels on a preferential path toward return wit

6、hout washing all rack faces.Containment mixing interface:imperfect separation between cold and warm regions allows local mixing,reducing containment effectiveness.Recommended Actions Inspect and reduce containment leakage paths(doors/curtains/gaps)to limit cold-to-warm and warm-to-cold mixing.Review

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