Effect of transverse reinforcement on the shear behavior of reinforced concrete deep beams
Open accessAbstract
Reinforced concrete deep beams are safety critical members that carry heavy loads over short spans (ACI Committee 318, 2008). Design provisions in many codes can under or overestimate their shear strength, which introduces reliability concerns in practice (Kong & Evans, 1987). This study investigates how transverse reinforcement and concrete type influence the shear behavior of deep beams. Four simply supported deep beams were tested under four point loading, two made with self-compacting concrete and two with conventionally vibrated concrete, with a shear span to depth ratio of 0.75 for all beams (EFNARC, 2002; JSCE, 2005). Web reinforcement patterns were either congested, with vertical stirrups at 50 mm, or normal, with vertical stirrups at 100 mm. Key responses recorded include load deflection, diagonal cracking load, crack patterns, and ultimate load. Results show that self-compacting concrete with normal web reinforcement produced slightly higher diagonal cracking at ultimate capacities, while both concretes reached similar capacities under congested web reinforcement (Okamura & Ouchi, 2003; Choi, Kim, & Kang, 2012; Akinpelu & Adedeji, 2018). All beams failed by sudden shear compression after diagonal crack band formation. Findings endorse self-compacting concrete for deep beams where congestion and compaction challenges exist.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In infringement or ownership disputes, the burden of proof generally falls upon the claimant, requiring demonstrable attribution to human actors whose creative intent can be documented.
“In infringement or ownership disputes, the burden of proof generally falls upon the claimant, requiring demonstrable attribution to human actors whose creative intent can be documented [8].”
From Designing automated audit mechanisms to evaluate compliance of generative AI platforms with federal authorship and ownership disclosure requirements. (2023) · cites this paper as [8]
The Introduction and Background and Related Work discuss self-compacting concrete and reinforced-concrete deep beams, not legal disputes. Searches for burden of proof, infringement, ownership, human creative intent, and copyright found no passage addressing the claim in our copy. (LLM, conf=0.78)
Experimental — accuracy not yet measuredDisclosure is necessary for enforceability because legal systems require verifiable evidence of creative contribution to adjudicate infringement, ownership disputes, and licensing claims.
“disclosure is necessary for enforceability: legal systems require verifiable evidence of creative contribution to adjudicate infringement, ownership disputes, and licensing claims [8].”
From Designing automated audit mechanisms to evaluate compliance of generative AI platforms with federal authorship and ownership disclosure requirements. (2023) · cites this paper as [8]
The Introduction discusses self-compacting concrete and reinforced-concrete deep beams; the Conflict section’s disclosure concerns conflicts of interest. Neither addresses legal enforceability or evidence of creative contribution. Searches for infringement, ownership, licensing, and related intellectual-property terms found no relevant passage in our copy. Page numbers were unavailable. (LLM, conf=0.78)
Experimental — accuracy not yet measuredCompliance with authorship and ownership disclosure requirements functions as a foundation for maintaining trust in information, cultural production, and economic exchange.
“Compliance with authorship and ownership disclosure requirements functions as a foundation for maintaining trust in information, cultural production, and economic exchange [8].”
From Designing automated audit mechanisms to evaluate compliance of generative AI platforms with federal authorship and ownership disclosure requirements. (2023) · cites this paper as [8]
The Introduction discusses self-compacting concrete and reinforced deep beams, while the Conflict section says only that no conflict of interest is disclosed. Searches for authorship and ownership disclosure, and for their proposed connection to trust, found no passage addressing the claim; page numbers were not available in our copy. (LLM, conf=0.75)
Experimental — accuracy not yet measuredOwnership attaches either to the creator or, in work-for-hire arrangements, to the commissioning or employing entity, with derivative rights conditioned on the provenance of underlying inputs.
“Ownership, in turn, attaches either to the creator or, in work-for-hire arrangements, to the commissioning or employing entity, with derivative rights conditioned on the provenance of underlying inputs [8].”
From Designing automated audit mechanisms to evaluate compliance of generative AI platforms with federal authorship and ownership disclosure requirements. (2023) · cites this paper as [8]
The Introduction and Background discuss reinforced-concrete deep beams, not legal ownership. Searches for work-for-hire, creator ownership, derivative rights, copyright, and employment found no passage addressing the attributed claim. (LLM, conf=0.78)
Experimental — accuracy not yet measuredCompliance requires documentation specific enough to demonstrate who contributed what and under which conditions, not merely acknowledgment that AI contributed to the creation of a work.
“Compliance does not merely require acknowledgment that AI contributed to the creation of a work; it requires documentation specific enough to demonstrate who contributed what and under which conditions [8].”
From Designing automated audit mechanisms to evaluate compliance of generative AI platforms with federal authorship and ownership disclosure requirements. (2023) · cites this paper as [8]
The paper’s ‘Compliance with ethical standards’ section discusses concrete materials and testing, while its ‘Conflict’ section only states that there is no conflict of interest; neither has a page number in our copy. Searches for documentation of who contributed what and for AI-contribution disclosure found no passage addressing the claimed compliance requirement. (LLM, conf=0.77)
Experimental — accuracy not yet measured
Disclosure is necessary for enforceability: legal systems require verifiable evidence of creative contribution to adjudicate infringement, ownership disputes, and licensing claims.
“Moreover, disclosure is necessary for enforceability: legal systems require verifiable evidence of creative contribution to adjudicate infringement, ownership disputes, and licensing claims [8].”
From Designing automated audit mechanisms to evaluate compliance of generative AI platforms with federal authorship and ownership disclosure requirements. (2023) · cites this paper as [8]
The Introduction and Practical Implications sections discuss concrete deep beams and transverse reinforcement, not legal enforceability. Searches for creative contribution, infringement, ownership, licensing, and related legal terms found no passage addressing the claim. Page numbers were unavailable in our copy. (LLM, conf=0.78)
Experimental — accuracy not yet measuredCompliance requires documentation specific enough to demonstrate who contributed what and under which conditions, not merely acknowledgment that AI contributed.
“Compliance does not merely require acknowledgment that AI contributed to the creation of a work; it requires documentation specific enough to demonstrate who contributed what and under which conditions [8].”
From Designing automated audit mechanisms to evaluate compliance of generative AI platforms with federal authorship and ownership disclosure requirements. (2023) · cites this paper as [8]
The paper’s Introduction discusses reinforced-concrete deep beams, and its ‘Compliance with ethical standards’ passage describes concrete materials and testing; neither addresses documentation of AI contributions. Searches for contributor documentation and AI-disclosure requirements found no relevant passage. Page numbers are unavailable in our copy. (LLM, conf=0.78)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
The publisher hasn’t deposited this paper’s reference list.
Research works printed but not linked: 8
- Akinpelu, M. A., & Adedeji, A. A. (2018). Structural response of reinforced self-compacting concrete deep beam using finite element method. Journal of Soft Computing in Civil Engineering, 2(1), 33-58. https://www.jsoftcivil.com/article_50115.html
- Choi, Y. W., Kim, Y. J., & Kang, H. J. (2008). Flowability properties of high-flowing self-compacting concrete for precast bridge members]. Journal of the Korean Society of Civil Engineers, 28, 155-163. https://koreascience.or.kr/article/JAKO200830265651399.page
- Choi, Y. W., Kim, Y. J., & Kang, H. J. (2012). Shear behavior and performance of deep beams made with self- compacting concrete. International Journal of Concrete Structures and Materials, 6(2), 79-88. https://doi.org/10.1007/s40069-012-0007-y · DOI
- Kong, F. K., & Evans, R. H. (1987). Reinforced and prestressed concrete (3rd ed.). Van Nostrand Reinhold. https://www.routledge.com/Reinforced-and-Prestressed-Concrete/Kong-Evans/p/book/9780419245605
- Kong, F. K., Robins, P. J., & Cole, D. F. (1970). Web reinforcement effects on deep beams. ACI Journal, 67(12), 1010- 1017. https://trid.trb.org/View/105760
- Ritter, W. (1899). Die Bauweise Hennebique. Schweizerische Bauzeitung, 33(7), 59-61. https://www.e- periodica.ch/digbib/view?pid=sbz-002%3A1899%3A33%3A%3A2288
- Tan, K. H., Tong, K., & Tang, C. Y. (2003). Consistent strut-and-tie modelling of deep beams with web openings. Magazine of Concrete Research, 55(1), 65-75. https://doi.org/10.1680/macr.2003.55.1.65 · DOI
- Yang, K. H., Chung, H. S., & Ashour, A. F. (2007). Influence of shear reinforcement on reinforced concrete continuous deep beams. ACI Structural Journal, 104(4), 420-429. https://www.concrete.org/publications/internationalconcreteabstractsportal.aspx?ID=18772&m=details.
Cited by
Sorted by citations
Omogiate, P. M. (2023) · International Journal of Science and Research Archive · doi:10.30574/ijsra.2023.10.2.1099 · Cited by 3 · see citing works
Merdas, H. S., Shallal, M. A., & Al-Rekabi, A. H. (2026) · Journal of Building Pathology and Rehabilitation · doi:10.1007/s41024-026-00824-8 · Cited by 2 · see citing works
- Authors
- Afolabi, O. S., Femi, A., & Toyyib, O.
- Corresponding author
- Afolabi, Oluwafemi Samson
- Venue
- World Journal of Advanced Research and Reviews
- Publisher
- GSC Online Press
- Published
- 2022-11-30
- Volume
- 16
- Issue
- 2
- Pages
- 1294-1303
- ISSN
- 2581-9615 (ISSN-L)
- OpenAlex
- W4413750036
- Cited by
- 1
- References
- 0
- Citations by year
- 2026: 1
- FWCI
- 0.00
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc-sa
- Locations
- World Journal of Advanced Research and Reviews (publishedVersion, cc-by-nc-sa)
- Topics
- Physical Sciences › Engineering › Building and Construction › Structural Behavior of Reinforced Concrete
- Physical Sciences › Engineering › Civil and Structural Engineering › Innovative concrete reinforcement materials
- Physical Sciences › Engineering › Civil and Structural Engineering › Structural Load-Bearing Analysis
- Keywords
- reinforced concrete deep beams, shear behavior, transverse reinforcement, web reinforcement, self-compacting concrete, diagonal cracking, shear span-to-depth ratio, ultimate load capacity, four-point loading, concrete types
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
