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Record W7001970284

Milling sticks : Evolving methodologies to fabricate complex traditional Japanese timber joints for use in light timber structures

2021· dissertation· en· W7001970284 on OpenAlexaboutno aff

Bibliographic record

VenueResearchSpace (University of Auckland) · 2021
Typedissertation
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsPavilionInterlockingCraftTrussArchitectureShadow (psychology)Prefabrication
DOInot available

Abstract

fetched live from OpenAlex

The role of a carpenter in traditional Japanese architecture is as much an architect as a craftsman. Japanese joinery created by miyadaiku carpenters (carpentry techniques using interlocking wood without nails) allows timber connections to be resolved by sophisticated joints without relying on mechanical fastenings. This approach to timber design has been largely lost with the adoption of mechanical fastenings such as nail or screw connections, especially in the construction of structures with many small timber members. Essentially, this is the result of the expensive labour cost associated with making timber joinery, leaving this craft to be the reserve of high-end furniture; it is no longer seen in the realm of 21st-century building. Sophisticated timber joints are still used in structures with large timber members, costing thousands of dollars. Using a CNC (computer numerical control) to mill the joints accurately with timber of this scale, the time and set up of the CNC milling is justified by the cost of the member being cut. However, a gap in the application of this technology exists regarding small timber members, costing a fraction of what larger members do. As a result of this, the cost to set up the CNC cannot be justified, and screws are used. The question focusing the research is ‘How can simple three-axis CNC milling be utilised to fabricate traditional Japanese timber joints, creating viable timber-to-timber connections on small members?’ and secondly ‘How might this methodology be applied to a live project?’ Research into this field has been undertaken by previous timber structures thesis supervised by Andrew Barrie, such as Dylan Waddell’s Shadow Pavilion (2019), which devised a jig to hold and consistently cut many small pieces of timber by locating sticks on the CNC. This massively reduced the set-up time associated with milling each stick. Kanade Konoshi’s Watari-Ago Shelter (2020) evolved this jig using toggles to make moving the stick within the jig even faster and more accurate. Both projects successfully milled one face of the timber to create lapped and cog joints; the issue is the limitation of what type of joints can be fabricated when only one face of the timber is cut. In this thesis, a new jig methodology is devised to cut multiple face of the timber so that more sophisticated and complex joints can be fabricated. To interrogate and test the methodology, a 12m2 forest classroom constructed from a lattice of small timber members, connected by Kashigi-orie joints, has been built for a client in Papamoa. This serves as a built example of how the technology can be applied to live projects, dispelling the notion that structures of this scale and budget must rely on mechanical fastenings.

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)0.002
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.195
GPT teacher head0.360
Teacher spread0.165 · 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 designBench or experimental
Domainnot available
GenreMethods

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
Published2021
Admission routes1
Has abstractyes

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