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Record W1527777322 · doi:10.2172/1044592

Recovery Act: Adaptive Environmentally Contained Power and Cooling IT Infrastructure for the Data Center (Final Technical Report)

2012· report· en· W1527777322 on OpenAlexaff
Р. Манн

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicGreen IT and Sustainability
Canadian institutionsHewlett-Packard (Canada)
Fundersnot available
KeywordsHVACData centerPower (physics)Power managementWater coolingComputer scienceElectric power systemElectrical engineeringAutomotive engineeringEngineeringAir conditioningMechanical engineeringOperating system

Abstract

fetched live from OpenAlex

The objectives of this program were to research and develop a fully enclosed Information Technology (IT) rack system for 100 kilowatts (KW) of IT load that provides its own internal power and cooling with High Voltage Alternating Current (HVAC defined as 480 volt) and chilled water as the primary inputs into the system and accepts alternative energy power sources such as wind and solar. For maximum efficiency, internal power to the IT equipment uses distributed High Voltage Direct Current power (HVDC defined as 360-380 volt) from the power source to the IT loads. The management scheme aggressively controls energy use to insure the best utilization of available power and cooling resources. The solution incorporates internal active management controls that not only optimizes the system environment for the given dynamic IT loads and changing system conditions, but also interfaces with data center Building Management Systems (BMS) to provide a complete end-to-end view of power and cooling chain. This technology achieves the goal of a Power Usage Effectiveness (PUE) of 1.25, resulting in a 38% reduction in the total amount of energy needed to support a 100KW IT load compared to current data center designs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.933
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.040
GPT teacher head0.268
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2012
Admission routes1
Has abstractyes

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