Incremental Static Analysis for the Seismic Performance Evaluation of a Peruvian R.C. Building
Bibliographic record
Abstract
In the present study, the incremental static or pushover analysis will be used, since it offers more accurate results compared to the linear analysis.Therefore, its application is indispensable for the evaluation of the seismic performance of a reinforced concrete structure composed of beams, columns and walls.This structure is a multi-family building of 6 levels, rectangular in shape with an area of 120 m².The methodology used allows obtaining the capacity of the structure against applied lateral loads, thus determining the performance levels for each level of seismic hazard according to the VISION 2000 guidelines.The study begins with an exhaustive analysis of the geometry, structural elements of the building, the use of standards and guidelines related to seismic resistance.However, two 3D structural models were created in Etabs V.21, called model 1 and model 2. In model 1, the non-linear model of plastic hinges for beams and columns will be taken into account, taking into consideration that the walls are hinged with fiber type hinges.On the other hand, for model 2, the nonlinear model of fiber-type hinges for columns, beams and walls will be taken into account.However, the indispensable resource is the ASCE 41-17/23 standard for the model with plastic hinges.On the other hand, we use the constitutive models of Mander and Park to define the behavior of concrete and steel in each fiber division.Then, the results of the capacity curve in each X and Y direction are compared.Finally, the pushover curve is sectorized to obtain the performance levels for frequent, occasional, rare and very rare earthquakes.Therefore, the findings in this article are useful for professionals engaged in structural engineering who are interested in the performance evaluation of a reinforced concrete structure or in other infrastructures that exist at the international level.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".