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Record W2618826635 · doi:10.5539/mer.v7n1p13

Design of Elastic Screw Fasteners under Tensile Load

2017· article· en· W2618826635 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMechanical Engineering Research · 2017
Typearticle
Languageen
FieldEngineering
TopicEngineering Structural Analysis Methods
Canadian institutionsnot available
Fundersnot available
KeywordsFastenerUltimate tensile strengthStructural engineeringPreloadTension (geology)Ultimate loadYield (engineering)Materials scienceSizingStress (linguistics)Composite materialEngineeringFinite element method

Abstract

fetched live from OpenAlex

This paper presents an equivalent stress approach in the design of screw fasteners under tensile load. Design equations are formulated for sizing and verifying screw fastener selection. It considers axial tensile, direct shear, bending, and torsional stresses and combines them as appropriate into equivalent or effective stresses. The equivalent or effective stresses are compared with screw fastener material strength capabilities such as proof, yield, fatigue, and tensile strengths for failure assessment. Design factors are derived for assessing design adequacy the screw fastener. For elastic screw fasteners, these stresses must each be in the elastic range for the screw material. When the load is removed, elastic screw fasteners regain their original size and shape, behaving like springs. Two illustrative design examples are used to demonstrate both design verification and sizing tasks. Design verification was performed in the first example and the static yield design factors are found to be 0.77 and 0.68 for the preload and service load, respectively. These values are less than unity, representing a case of under-design in static yield failure modes. Without changing the specification of the screw fastener, the preload tension was reduced by 62.76%, and the static yield design factors changed to 1.42 and 1.12 for the preload and service load, respectively. This shows that the under-design condition resulted from high preload tension. When the screw pitch is changed from coarse to fine series, the design factors are worse off in fatigue stress resistance but indicated some improvement in static stress resistance. This suggests that fine pitch threads is not better than coarse pitch threads in fatigue stress capacity when direct shear and bending stresses are considered in Example 1. Both design sizing and verification are performed in Example 2. Design sizing suggests a screw fastener ( ) of slightly larger size than the previous solution ( ). Design verification indicates the previous solution and new solution has a minimum static yield design factor of 0.93 and 1.09, respectively for the service load. This suggests that the screw fastener of the previous solution may yield in service, if implemented. The new solution has a higher design factor in this failure mode and presents less risk of failure. From the illustrative examples presented, it seems that ignoring direct and bending stresses in screw fastener design can lead to under-design in some failure modes.

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.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.885
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
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 science0.0010.000
Research integrity0.0000.001
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 head0.099
GPT teacher head0.358
Teacher spread0.259 · 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