MétaCan
Menu
Back to cohort
Record W3094928848 · doi:10.2495/hpsm200021

MULTI-PHASE NANOSTRUCTURED 60Si2Mn DISC SPRING BY A NOVEL AUSTEMPERING PROCESS

2020· article· en· W3094928848 on OpenAlexaff
Jiacheng Li, Yun Hang, Shuang Zhou, Xuan Wang, Zhongyang Liang, Wentao Zhou, Derek O. Northwood, Cheng Liu

Bibliographic record

VenueWIT transactions on the built environment · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced Surface Polishing Techniques
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsProcess (computing)Materials scienceSpring (device)Phase (matter)MetallurgyComputer scienceMechanical engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

A disc spring, also known as a Belleville spring, is a conical shell which can be loaded along its axis either statically or dynamically.It can generate a high force in a very short spring length with minimal movement when compressed.A novel multi-step austempering heat treatment process is developed to improve both the hardness and strength of a conventional 60Si2Mn disc spring.In this case, the disc spring is austenitized at 900°C for 0.5 h, control-quenched to a temperature below Ms (the starting temperature of martensite transformation) for a very short time, subsequently heated to the Ms point and holding for a specific time, and finally air cooled to the room temperature.It is found that the resulting multiphase microstructure consists mainly of prior lenticular martensite formed during controlled quenching (PM), needle bainitic ferrite (BF), and high carbon enriched retained austenite (RA).Further observation shows that a nanostructured (BF+RA)nano phase including lath BF and film RA with a width of about 100 nm nucleates around the PM.Such a microstructure results in uniform compression behavior, and significantly higher strength and hardness than for a conventional 60Si2Mn disc spring.This controlled multi-step austempering process is a promising solution for enhancing the disc spring properties for those applications involving higher loading and fatigue conditions.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.024
GPT teacher head0.243
Teacher spread0.220 · 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
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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueWIT transactions on the built environmentSame topicAdvanced Surface Polishing TechniquesFrench-language works237,207