Efficiency of Modular Bridge Configurations: A Study on the Structural Stability and Capacity of Single- and Double-Story Modular Bridges
Bibliographic record
Abstract
This study investigates the structural performance and load-bearing capacity of single- and double-story modular bridge configurations using both experimental testing and finite element analysis. A full-scale field test was conducted on a 45.7 m double-story bridge subjected to truck loading at ten distinct positions along the span. Midspan deflections and axial strains of key members were measured and analyzed at each loading position to assess the bridge’s response under service loads. The experimental data were used to validate three-dimensional finite element (FE) models and refine modeling techniques for the double-story modular bridge. The validated FE models enabled further analysis of the structural performance of double-truss–double-story (DD) and quadruple-truss–single-story (QS) modular bridge configurations, both in single- and double-lane setups. The numerical results demonstrated that the double-story configuration with double truss lines per side provided a notable improvement in stiffness and load-carrying capacity compared to the single-story configuration with quadruple truss lines. Moreover, single-lane bridges exhibited better performance than their double-lane equivalents, emphasizing the impact of bridge width on structural stability. Wider, double-lane bridges were found to be more prone to out-of-plane buckling at midspan, with the top chords experiencing significantly greater deformation. Buckling analyses indicated that, although the DD and QS configurations had comparable critical loads, their failure mechanisms differed. Finally, live load factors predicted through the models were compared with the requirements of the Canadian Highway Bridge Design Code (CHBDC), confirming that the DD configuration in a two-lane setup meets code expectations and demonstrates effective structural performance.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".