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Record W2786699793 · doi:10.22215/etd/2017-11993

Passive Solar Architecture: Case Study on Strategies Used in Jacobs House Designed by Frank Lloyd Wright

2017· dissertation· en· W2786699793 on OpenAlexaff
David Gikaru

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldArts and Humanities
TopicArchitecture and Cultural Influences
Canadian institutionsCarleton University
Fundersnot available
KeywordsWrightPassive houseArchitectural engineeringPassive solar building designZero-energy buildingArchitectureLow-energy houseEnergy (signal processing)EngineeringEfficient energy useSolar energyArtElectrical engineeringVisual artsSystems engineering

Abstract

fetched live from OpenAlex

Over the ages major breakthroughs made in passive solar architecture stem from technical innovations, understanding of material properties and energy flows.The emergence of net zero energy buildings represents a crucial moment in terms of energy performance of passive solar designs.Despite the technical feasibility, NZE proposals have proved to be unaffordable owing to complex technical innovations and overreliance on mechanical systems.The purpose of this study is to examine Jacobs's house designed by Frank Lloyd Wright, to rediscover ideas of the past that would be integrated to contemporary passive solar architecture.This began with a literature review, an overview of Wright's background and visit of Jacobs's house.Then, a study of five passive strategies namely: orientation, thermal mass, insulation, ventilation, and natural lighting was done.The thesis will also prove that ideas behind net zero are not new.There is need to re-examine net zero in a wider context of sustainability not to be limited to just energy calculation.Net zero energy building should not be viewed as just a passive building but rather an active social, political, and economical project as the Jacobs House demonstrates.In search for interconnectivity between our built environment and natural world, adopting Wright's principles of organic architecture will make NZE more sustainable.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.004
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.032
GPT teacher head0.285
Teacher spread0.253 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations0
Published2017
Admission routes1
Has abstractyes

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