Flexural Behavior and Design of Prestressed Ultrahigh-Performance Concrete Beams: Failure Mode and Ductility
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Bibliographic record
Abstract
Ultra-high performance concrete (UHPC) is well-known for its ultra-high compressive strength and sustained postcracking tensile ductility, making it an attractive choice for the construction of modern structures. However, prestressed UHPC members often fail quickly after crack localization accompanied by reinforcement rupture, which shows limited failure warnings (i.e., relatively small ductility, nearly invisible cracking, and negligible compressive damage). In contrast, UHPC members can also be designed to allow the gradual strain hardening of reinforcement to compensate for the load loss due to crack localization, and the final failure is attributed to the gradual crushing of UHPC prior to reinforcement rupture. Failure after gradual strain hardening is desirable since it brings warning signs through high ductility, visible cracks, and controlled spalling. To achieve a resilient structural design of UHPC members, this study aims to develop design methods to avoid early failure after crack localization and promote failure after gradual strain hardening. This study first establishes a three-dimensional finite-element analysis (FEA) model to simulate the flexural behavior of prestressed UHPC beams, which is validated against seven existing experimental beams. Then, parametric analyses are conducted to assess the influence of five key aspects, including the steel rebar-to-prestressing strand ratio, the postyield hardening of mild steel rebars, the pretensioned stress of prestressing strands, the tensile behavior of UHPC, and the web width to bottom flange ratio. Additionally, the authors propose a design method to predict the failure mode of prestressed UHPC beams, which can be used to guide the design of reinforcement configuration and promote ductile structural behavior. In particular, a threshold reinforcing ratio for mild-steel rebar is proposed to design for failure after gradual strain hardening.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it