Schneider Electric It Corporation

Other

Healey, Christopher, M.

Vangilder, James, W.

Johansen, Martin

Dalgas, Mikkel

Christopher M Healey

James William VanGilder

Xuanhang Zhang

Zachary Pardey

Anna Lake

James S Spitaels

Mikkel Dalgas

Claude Le Pape-Gardeux

Martin Johansen

Laurent Billet

Jean-Louis Bergerand

James William Vangilder

Zack Pardey

Zachary M Pardey

James W Vangilder

According to at least one aspect of the present invention, a system for automatically generating a data-center network mapping for automated alarm consolidation is provided comprising a plurality of devices, and at least one computing device communicatively coupled to each of the devices, the at least one computing device being configured to receive operational data from each of the devices, the operational data being indicative of at least one of a power path, cooling or temperature zones, or communications paths, determine, based on the operational data, device relationships between each of the devices, receive, from each of the devices, a respective alarm of a plurality of alarms, determine alarm relationships between at least two of the plurality of alarms, consolidate, based on the determined device relationships and based on the determined alarm relationships, the plurality of alarms into a consolidated alert, and provide the consolidated alert to a user.

Systems and methods for automatically generating a data center network mapping for automated alarm consolidation

Systems and methods for a compact wall model are provided. According to one aspect, embodiments herein provide a method that comprises receiving input data related to an enclosure, the input data including solar intensity data on an exterior of a wall of the enclosure, generating, by a processor, a thermal model of a wall of the enclosure based at least in part on the input data, the wall modeled as having a plurality of layers and the thermal model including a plurality of nodes such that each layer of the plurality of layers is associated with at least one node of the plurality of nodes and each node of the plurality of nodes is thermally coupled to an adjacent node by a thermal resistance, solving, by the processor, an energy balance equation for the at least one node to determine a predicted temperature for the at least one node, and output the predicted temperature to a display device.

Systems and methods for constructing a compact wall model

A system and method for predicting the effect of a transient event on a data center. A method comprises receiving input data related to a data center that includes at least one equipment rack and at least one cooling provider, the input data including data center architecture information, building data, and operating data, generating, a model based at least in part on the input data and on a set of energy balance and heat exchange equations for the data center that account for removed and added heat and a thermal mass of the at least one equipment rack and a thermal mass of the at least one cooling provider, the model configured to predict at least one temperature in the data center during a transient event, and controlling a display device to display the at least one predicted temperature.

Method and system for predicting effect of a transient event on a data center

According to one aspect, embodiments described herein provide a system and a method for modeling airflow. In one example, the system comprises a memory and a controller coupled to the memory, the controller configured to receive data related to equipment including at least two of a group comprising a cooling consumer and a cooling provider, compute at least one quantity of airflow between an inlet and an outlet associated with the equipment, generate a representation of at least one airflow path between the outlet and the inlet having a cross-sectional area proportional to the at least one quantity of airflow, and display the representation of the at least one airflow path in a cooling model.

Systems and methods of visualizing airflow

A system and method for modeling airflow and temperature are disclosed. In one example, the method includes receiving input data related to a physical layout of a facility, dividing, by a computer, a representation of the facility into a plurality of grid cells, identifying where effects of at least one of jet airflow, thermal plumes and buoyancy forces are present in the facility based on the physical layout, specifying a velocity value, using a velocity correction method, for a first set of the plurality of grid cells if the effects of at least one of jet airflow and thermal plumes are present within the first set of the plurality of grid cells, calculating, by the computer, an airflow velocity value for each of a second set of the plurality of grid cells, the second set being different from the first set, modifying the determined airflow velocity value for any of the second set of the plurality of grid cells where the effects of buoyancy forces are present, and storing, on a storage device, the modified airflow values.

System and method for fluid dynamics prediction with an enhanced potential flow model

Aspects of this disclosure are directed to a simulation-based cooling optimization method that provides real-time cooling set points in a data center. The method combines airflow and temperature simulation, energy modeling, and an optimization solver to determine optimal cooling set point values for a data center. Other aspects are also directed to estimating power consumption and cost and energy savings.

System and methods for simulation-based optimization of data center cooling equipment

A system and method for evaluating equipment in a data center is disclosed, hi one aspect, a method includes receiving parameters for equipment in the data center, the parameters including information descriptive of mass of the equipment, calculating an idealized thermal mass of the equipment based on the received parameters, calculating a temperature associated with the equipment at a first time period of a plurality of time periods based on the idealized thermal mass, and calculating a temperature for each subsequent time period of the plurality of time periods based on the idealized thermal mass and the temperature at a previous time period of the plurality of time periods.

Method and apparatus for characterizing thermal transient performance

A computer-implemented method for evaluating cooling performance of equipment in a data center. In one aspect, the method comprises receiving data related to equipment in the data center, determining first parameters related to airflow and temperature in the data center at a first period in time, receiving a description of a transient event affecting one of airflow and temperature in the data center at a second time, breaking a second time period subsequent to the second time into a plurality of time intervals, determining second parameters related to airflow in the data center during one of the time intervals, determining the parameters related to temperature in the data center at each of the time intervals based on the second parameters related to airflow, and storing, on a storage device, a representation of the parameters related to temperature in the data center during the second time period.

Analysis of effect of transient events on temperature in a data center

A system and method for designing aspects of a cooling system for a data center is provided. A method is provided including computing cooling redundancy at each rack position in a data center, in real time. The redundancy can be reported using the traditional N+1, N+2, etc. notation, where N is the number of coolers required to meet the primary cooling load type specification. The redundancy can also be reported in terms of a Cooling Reliability Index (CRI) which also takes into account the inherent availability of the specific cooling units in the design.

Method for computing cooling redundancy at the rack level

A system and method for predicting airflow within a data center using a potential flow technique is provided. In one aspect, a method includes automatically generating an unstructured grid, the unstructured grid comprising a plurality of unstructured grid cells, each unstructured grid cell having a size, dividing a representation of the data center into the plurality of unstructured grid cells, determining airflow velocity values for each of the plurality of unstructured grid cells using airflow velocity potentials, determining a temperature value for each one of the plurality of the unstructured grid cells using the airflow velocity values, determining a concentration value for each of the plurality of the unstructured grid cells using the airflow velocity values, and calculating a comparison result indicating whether the concentration values, the airflow velocity values and the temperature values for the plurality of the unstructured grid cells satisfy convergence criteria.

Systems and methods for predicting fluid dynamics in a data center

A system and method for evaluating equipment in a data center, the equipment including a plurality of equipment racks, and at least one cooling provider. In one aspect, a method includes receiving data regarding each of the plurality of equipment racks and the at least one cooling provider, the data including a layout of the equipment racks and the at least one cooling provider, and a power draw value for each of the equipment racks, storing the received data, determining air flow between the at least one cooling provider and each of the equipment racks, determining inlet and exit air temperature for the at least one cooling provider based on the layout, the power draw and the airflow, and for each equipment rack, determining inlet and exit air temperature based on the layout, the power draw and the airflow.

System and method for predicting temperature values in a data center

A system and method for designing aspects of a cooling system for a data center is provided. A method is provided including computing cooling redundancy at each rack position in a data center, in real time. The redundancy can be reported using the traditional N+1, N+2, etc. notation, where N is the number of coolers required to meet the primary cooling load type specification. The method substantially reduces the computational complexity of computing cooling redundancy.

A system and method for evaluating cooling performance of equipment in a data center, the equipment including a plurality of equipment racks and at least one cooling provider. In one aspect, a method includes receiving a plurality of measured inlet and exhaust air temperature values for the at least one cooling provider and a subset of the plurality of equipment racks, implementing a cooling model, the model including an ambient air temperature value, a plurality of inlet and exhaust air temperature values for the plurality of equipment racks and the at least one cooling provider, and a plurality of airflow values for the plurality of equipment racks and the at least one cooling provider, adjusting at least one of the ambient air temperature value and each of the plurality of airflow values in the cooling model, adjusting the cooling model to compensate for the adjusted at least one of the ambient air temperature value and each of the plurality of airflow values in the cooling model, substituting a first subset of the plurality of inlet and exhaust air temperature values in the cooling model with the plurality of measured inlet and exhaust air temperature values, and predicting a second subset of the plurality of inlet and exhaust air temperature values for the plurality of equipment racks and the at least one cooling provider in the cooling model.

System and method for measurement aided prediction of temperature and airflow values in a data center

A computer-implemented method for sequential placement of cooling resources in a data center comprises: defining a weighted, higher-order cooling metric,, representing an overall performance of the cooling resources in the data center; enumerating all possible locations in the data center for placing an additional c cooling resources; and placing the c cooling resources in locations in the data center for whichis closest to an optimum value. For a performance metric M, the weighted, higher-order cooling performance metric can be defined as where R represents a number of racks in the data center, C represents a total number of cooling resources placed in the data center, i represents one of the R racks in the data center, Mrepresents a value of metric Mwhen k cooling resources are shut down, and a(i,k) is a weighting function for rack i with the k cooling resources shut down. A system performing the method and computer-readable media having stored thereon instructions causing a processor to perform the method are also provided.

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Chelmsford, MA, United States of America

Christopher M Healey