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Record W2769184283 · doi:10.1556/1848.2017.8.2.7

A sustainable design for an off-grid passive container house

2017· article· en· W2769184283 on OpenAlexaff
Wesley Bowley, Phalguni Mukhopadhyaya

Bibliographic record

VenueInternational Review of Applied Sciences and Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicSmart Grid Energy Management
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsRainwater harvestingLow-energy housePassive houseElectricityGridPassive solar building designPhotovoltaic systemCivil engineeringEnvironmental scienceContainer (type theory)Architectural engineeringSustainable designZero-energy buildingEfficient energy useEnvironmental economicsSolar energyEngineeringSustainabilityElectrical engineeringMechanical engineeringGeography

Abstract

fetched live from OpenAlex

Buildings are the largest consumers of energy, accounting for nearly 40% of all energy used. Therefore, an effective method of reducing energy consumption is to create and design more efficient buildings. In this paper details of a sustainable and green building design for a small residential home are presented. This design is unique in that it is built to Passive house standards, and using shipping containers. The structure will use four 20 ft. (6.1 m) high and one 40 ft. (12.2 m) high cube containers, with the four 20 ft. (6.1 m) making up the main floor and the 40 ft. (12.2 m) forming the second floor. The size is a modest 820 sq. ft. (76.2 m 2 ) designed for a family with one or two children. The goal for the building is to be as self-sufficient as possible which makes it ideally suited to an ‘off-grid’ rural setting. However, it can be adapted to be ‘on-grid’ as well. Solar energy will provide all the electricity needs through a photovoltaic battery system, and warm water with a solar water heater. The site will be water neutral by utilising rainwater harvesting and on site waste water treatment. The results from energy modelling, using HOT2000, are presented, as well as an in-depth analysis on different insulation types and strategies. Finally, a cost estimate exercise is conducted and results compared to other passive houses and traditional code compliance buildings.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.863
Threshold uncertainty score0.365

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)0.0000.000

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 head0.021
GPT teacher head0.260
Teacher spread0.239 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations18
Published2017
Admission routes1
Has abstractyes

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