Management and predictions of operational changes and growth in mission critical facilities
The main challenge in understanding the cooling performance in a legacy data center is the invisible transport medium (air). This emphasizes the need for smart and meticulous measurement techniques. However, the nature of measurements is finite (e.g. top, middle and bottom) and the variation between often non-linear, therefore to capture the gradients between measured points a validated CFD simulation is needed. In this paper a brief description of an experimental characterization of a new data center lab is discussed. Airflow and temperature measurements are utilized to understand the facility's performance at different operational stages, until reaching the designed capacity. Since the facility houses a wide range of different IT equipment (servers, switches, storage and blades), it is important to understand the airflow demand of each. To do that, each type of IT was tested separately and flow characteristics were obtained (i.e. free delivery, critical pressure and flow curves). In the second part, all the characterization data is integrated via compact models into a full CFD simulation. The measured points are used for validation and the full field of air temperature and flow is resolved. Both the measurements and simulation data will now be used to answer important design, deployment and operational change questions.
The Impact of Cold Aisle Containment Pressure Relief on IT Availability
During the lifespan of a data center, power outages and blower cooling failures are common occurrences. Given that data centers have a vital role in modern life, it is especially important to understand these failures and their effects. A previous study [16] showed that cold aisle containment might have a negative impact on IT equipment uptime during a blower failure. This new study further analyzed the impact of containment on IT equipment uptime during a CRAH blower failure. It also compared the IT equipment performance both with and without a pressure relief mechanism implemented in the containment system. The results show that the effect of implementing pressure relief in containment solution on the IT equipment performance and response could vary and depend on the server’s airflow, generation and hence types of servers deployed in cold aisle enclosure. The results also showed that when compared to the discrete sensors, the IPMI inlet temperature sensors underestimate the Ride Through Time (RTT) by 32%. This means that the RTT calculations based on the IPMI inlet sensors may be inaccurate due to variations in the sensor readings; as they exist today; in these servers. as discussed in a previous study [26]. Additionally, it was shown that all Dell PowerEdge 2950 servers have a similar IPMI inlet temperature reading, regardless of mounting location. As external system resistance increases during cooling failure, the servers exhibit internal recirculation through their weaker power supply fans, which is reflected in the high IPMI inlet temperature readings. For this server specifically, a pressure relief mechanism reduces the external resistance, thereby eliminating internal recirculation and resulting in lower IPMI inlet temperature readings. This in turn translates to a lower RTT. However, pressure relief showed conflicting results where the discrete sensors showed an increase in inlet temperature when pressure relief was introduced, thereby reducing the RTT. The CPU temperatures conformed with the discrete sensor data, indicating that containment helped increase the RTT of the servers during failure.
Cooling performance of ceiling-plenum-ducted containment systems in data centers
In an effort to improve the reliability and efficiency of data centers, racks and sometimes entire hot aisles are ducted to a dropped ceiling. The cooling performance of such systems strongly depends on IT and cooler airflow, the number and configuration of ducted objects and perforated ceiling tiles, the leakiness of the ceiling system, ceiling plenum depth, and other factors. Recently, a compact model has been proposed in which a Flow Network Model (FNM) representing the ducted equipment is embedded into a parent CFD model. By eliminating the need to explicitly model difficult-to-characterize leakage paths in CFD, this approach allows for realistic solutions while greatly improving the solutions speed and robustness of the CFD simulation. This paper employs the FNM (without CFD) to characterize and compare the cooling effectiveness of individually-ducted racks and ducted hot aisles subject to a given ceiling plenum pressure. Example resistance values needed in the FNM are provided. Additionally, an example data center layout is studied with the coupled FNM-CFD model to explore cooling performance as a function of ceiling leakiness, plenum depth, ratio of cooling to IT airflow, and rack density (IT airflow). Best-practice type recommendations for ducted equipment are provided.