MétaCan
Menu
Back to cohort
Record W4412722915 · doi:10.1016/j.soildyn.2025.109638

A methodology for scaling non-linear force-displacement behavior of elastomeric isolators for design

2025· article· en· W4412722915 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSoil Dynamics and Earthquake Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsUniversity of Windsor
FundersUniversity of Windsor
KeywordsElastomerScalingDisplacement (psychology)Structural engineeringMaterials scienceEngineeringMathematicsComposite materialGeometryPsychology

Abstract

fetched live from OpenAlex

Base isolation systems may perform differently in practice than in theoretical predictions due to factors such as environmental conditions, aging, temperature fluctuations, scragging, and the natural variability of rubber materials and the manufacturing processes. These factors significantly influence the mechanical behavior of base isolators, affecting their characteristic strength, damping, and stiffness, which consequently impacts the performance of both the isolation system and the superstructure. Most standards emphasize that isolator design should not rely solely on nominal values, leading to the introduction of property modification factors, commonly referred to as λ -factors, to account for the variability in the mechanical behavior of base isolators. These factors were originally defined for bilinear or trilinear force-displacement behaviors. Their application to more complex models has been theorized without clear guidance on how they should be implemented. This study presents a method for scaling the effective stiffness, K eff , and enclosed hysteresis area, W , in the force-displacement behavior of isolators for complex numerical models such as the Bouc-Wen model, modified Bouc-Wen model, and the algebraic model, which are commonly used for modeling elastomeric isolators. Unlike characteristic strength, Q d , and post-yield stiffness, K d , which are typically employed in bilinear and trilinear models, the K eff and W were chosen because they offer a more general and practical representation of highly nonlinear devices, which often lack well-defined Q d and K d values. The proposed approach can independently scale the K eff and W within the ranges specified by AASHTO, ASCE 7–22, and ASCE 7–41. This approach can be extended to other isolator mechanical properties and numerical models. • Proposes a method for scaling effective stiffness, K eff , and hysteresis area, W , in advanced isolator models. • Extends application of the λ -factors concept beyond bi- and trilinear models to Bouc-Wen, modified Bouc-Wen, and algebraic models. • Provides a scalable framework to independently adjust K eff and W while ensuring compatibility with relevant guidelines. • Demonstrates the method's effectiveness across a wide range of λ -factors and its generalizability to numerical models.

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)0.000
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 score0.632
Threshold uncertainty score0.909

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 head0.016
GPT teacher head0.260
Teacher spread0.244 · 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