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Record W2930677328 · doi:10.1002/9781119097921.ch8

Maximising Impact Through Performance Simulation: The Work of Transsolar Klimaengineering

2018· other· en· W2930677328 on OpenAlexaboutno aff
Terri Peters

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAbu dhabiArchitectural engineeringWork (physics)Scale (ratio)Civil engineeringEngineeringEnergy performanceComputer scienceEfficient energy useConstruction engineeringMechanical engineeringGeographyCartography

Abstract

fetched live from OpenAlex

This chapter discusses how Transsolar KlimaEngineering's approach to sustainable buildings is informed by its deep expertise in engineering principles, building physics, and thermodynamics. The office uses building performance simulation and computation to maximize locally specific site conditions and to enable the adoption of passive strategies, therefore minimizing required energy use. Transsolar has experience in simulating extreme environments at a range of scales. Recent projects include calculating and predicting outdoor comfort and performance at the urban scale, in the Masdar City masterplan and the Al Fayah Park, both in Abu Dhabi. Transsolar worked on the Manitoba Hydro building, designed by architects Kuwabara Payne McKenna Blumberg, and located in Winnipeg. Transsolar has collaborated on a number of naturally ventilated school projects that have little or no mechanical systems.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.666
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0200.000

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 head0.013
GPT teacher head0.239
Teacher spread0.226 · 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
GenreOther

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

Citations2
Published2018
Admission routes1
Has abstractyes

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