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Record W4412983468 · doi:10.1016/j.jobe.2025.113495

Energy-based framework for designing pinned rocking systems with dissipative devices

2025· article· en· W4412983468 on OpenAlexaff
Michela De Angelis, Giulia Angelucci, Giuseppe Quaranta, Fabrizio Mollaioli, Solomon Tesfamariam

Bibliographic record

VenueJournal of Building Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsUniversity of Waterloo
FundersSapienza Università di Roma
KeywordsDissipative systemEnergy (signal processing)Computer scienceMechanical engineeringMaterials scienceEngineering physicsEngineeringPhysicsThermodynamics

Abstract

fetched live from OpenAlex

Traditional seismic design has primarily aimed to prevent structural collapse, often accepting significant damage that compromises building functionality and necessitates extensive repairs. In response, a low-damage design philosophy has emerged, prioritizing structural safety, minimizing residual damage, preserving operational continuity, and reducing post-earthquake costs. Among the various strategies, rocking systems – such as pinned rocking configurations – offer an effective balance between high performance and ease of post-event restoration. However, the comparative evaluation of dissipation mechanisms and layout configurations within these systems remains limited, and a systematic methodology for optimizing their design while minimizing material usage has yet to be developed. This study presents a comprehensive iterative energy-based design methodology for pinned rocking systems, potentially enhanced with supplementary dissipative devices. The investigated designs include rocking systems equipped with either viscous dampers or self-centering mechanisms at the base, as well as configurations incorporating diagonal dampers that link the rocking system to the primary structural frame. A multi-stripe analysis is conducted to evaluate the benefits and limitations of the proposed rocking system configurations and to assess the effectiveness of the energy-based design approach.

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 score0.815
Threshold uncertainty score0.609

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 head0.007
GPT teacher head0.227
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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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