Bibliographic record
Abstract
The chapter provides an overview of the advances made in the field of structural integrity and failure with a specific focus on reinforced concrete structures. It begins with a brief history of reinforced concrete and covers its structural properties and characteristics. It then delves into the mechanics of reinforced concrete structures, including the various forces that act on them, and the design and construction of these structures. It delves into the basic mechanics, stressing the concrete’s performance under loading and its inherent material properties. The focus then shifts to the design principles applied to reinforced concrete structures, and the consideration of critical structural elements like beams, slabs, columns, and foundations. Various advances in reinforced concrete technology, including High-Performance Concrete, Fiber-Reinforced Concrete, Self-Compacting Concrete, and the use of nanomaterials, are explored. The chapter provides insights into methods for the analysis and assessment of reinforced concrete structures, discussing non-destructive testing methods, structural health monitoring, and finite element analysis. It examines the causes of failure, including material quality, overloading, design flaws, environmental factors, and construction errors. Several case studies of notable building failures are highlighted, emphasizing lessons learned and the importance of safe construction practices. The chapter concludes by looking at future directions in reinforced concrete, encompassing advanced materials, digital technology, sustainable construction practices, and resilience-based design.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".