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Record W4221122579 · doi:10.1002/tal.1933

Seismic reliability evaluation of a tall concrete‐timber hybrid structural system

2022· article· en· W4221122579 on OpenAlex
Jiawei Chen, Haibei Xiong, Carlos E. Ventura

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.

Bibliographic record

VenueThe Structural Design of Tall and Special Buildings · 2022
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsUniversity of British Columbia
FundersFundamental Research Funds for Central Universities of the Central South UniversityChina Scholarship CouncilNational Natural Science Foundation of China
KeywordsReliability (semiconductor)Structural engineeringRange (aeronautics)Structural systemLimit state designEngineeringComputer scienceReliability engineering

Abstract

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Summary Seismic reliability analysis is important for performance evaluation and structure design of novel structural systems since it can consider inherent uncertainties in seismic actions and structural properties. In this paper, seismic reliability analyses were performed on an innovative high‐rise concrete‐timber (FaB) hybrid structural system. The FaB system combines a concrete frame‐tube structure with large story height as the main structure and multi‐story timber structures on each concrete slab as substructures. To better assess the seismic reliability of the FaB system, response surface methods with either the Lasso regression approach or the machine‐learning‐based symbolic regression approach were conducted and compared. Uncertainties, including ground motions, elastic properties and ductility factor of the concrete main structure, mechanical properties of timber substructures and connections (i.e., rubber bearings), mass ratios, and fitting errors, were considered in formulating the limit‐state performance functions. Tens of thousands of non‐linear time‐history analyses were run to establish the response database of the FaB system, and the reliability indexes of both the concrete main structure and timber substructures were calculated. The results show that the symbolic regression approach can formulate simpler response surface functions with similar results compared to the Lasso regression approach. The maximum difference of reliability indexes between the two approaches is less than 8.3%. For the concrete main structure, the seismic reliability indexes are in a range of 1.068 to 4.223 under different performance objectives and hazard levels, while those of timber substructures are in a range of 0.892 to 2.28. The corresponding non‐exceedance probabilities of failure are between 81% and 99%, which reveals the safety and robustness of the FaB system. Meanwhile, the adoption of rubber bearings in the FaB system can enhance the seismic reliability indexes of timber substructures by 9% to 28% but has little influence on those of the concrete main structure. Outcomes of this study can serve as efficient tools to quantify the seismic performance and evaluate the performance‐based seismic design methodology for the proposed tall concrete‐timber hybrid structural system.

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)0.001
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: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.532

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.018
GPT teacher head0.215
Teacher spread0.197 · 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