Comparative experimental study on the serviceability and flexural strength of cold-formed steel I-joists with and without stiffened web holes
Bibliographic record
Abstract
a bstract Cold-Formed Steel (CFS) has emerged as a preferred material for low-rise building construction, as well as for roof and floor systems, due to its favorable performance, cost efficiency, safety, and sustainability attributes. However, the structural and economic advantages of CFS floor systems can be undermined by vibration serviceability challenges if not appropriately addressed in the design phase. Furthermore, utility holes, such as slotted or circular openings in the web of CFS joists, are commonly introduced to accommodate piping, plumbing, or electrical wiring. These holes, while functional, may also affect the serviceability of the floor system by altering its dynamic response and structural integrity. Existing design methodologies for calculating the dynamic properties of floor systems have been primarily developed for light-frame CFS, structural steel, and concrete floor systems. The applicability of these methods to I-shaped CFS joists, particularly those with utility holes, remains unexplored. Furthermore, the North American Standard for Cold-Formed Steel Structural Members (CSA-S136–16) provides design specifications for C-shaped joists at ultimate limit states but lacks provisions for I-shaped joists or edge-stiffened (lipped) holes. As such, an experimental study on CFS I-shape joists is needed to obtain experimental data to evaluate the available ultimate strength equations and serviceability design procedure when applied to such joist type with utility holes. This paper presents the experimental investigation of CFS I-shape members with web holes with edge stiffening to study the effect of stiffened holes on the serviceability and flexural strength of the member when subjected to flexural loading. Additionally, the study assessed the accuracy and applicability of existing design methods in predicting key dynamic and static performance metrics, including fundamental frequency, static deflection, and acceleration responses to walking-induced excitation. The findings contribute to the advancement of design practices for CFS floor systems, particularly those employing I-shaped members with utility holes.
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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".