The DOI matches its Crossref record; 60 of the 60 references it cites were found in a registry or an index.
Evaluation of the splitting tensile strength in plain and steel fiber-reinforced concrete based on the compressive strength
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Citations
Cites
1 retracted
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Support Vector Machines for Classification and Regression
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Mechanical properties of high-strength steel fiber-reinforced concrete
Song, P. S., & Hwang, S. (2004) · Construction and Building Materials · doi:10.1016/j.conbuildmat.2004.04.027 · Cited by 1,004
Crack growth and development of fracture zones in plain concrete and similar materials
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Induction of model trees for predicting continuous classes
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State of the Art Report on High-Strength Concrete
ACI Committee (1984) · ACI Journal Proceedings · doi:10.14359/10692 · Cited by 622
Prediction of compressive strength of recycled aggregate concrete using artificial neural networks
Duan, Z. H., Kou, S. C., & Poon, C. S. (2013) · Construction and Building Materials · doi:10.1016/j.conbuildmat.2012.04.063 · Cited by 509
Machine learning in concrete strength simulations: Multi-nation data analytics
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Prediction of compressive strength of concrete by neural networks
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Research works printed but not linked: 7
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- A. Behnood, J. Olek, M. Glinicki, Prdicting Compressive Strength of Recycled Concrete Aggregate Using M5′ Model, in: 11th International Symposium on BRITTLE MATRIX COMPOSITES, Warsaw, Poland, 2015, pp. 381–391.
- S. Ros, S. Hiroshi, Relationship between splitting tensile strength and compressive strength of concrete at early age with different types of cements and curing temperature histories, in: 13th Annual Convention of Japan Concrete Institute, 2013, pp. 427–432.
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- K. Marar, T. Celik, The Influence of FRI on the Relationship Between Compressive and Tensile Strength of NSFRC and HSFRC, in: The sixth International Conference on Concrete Technology, Amman-Jordan, 2002.
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Cited by
Baduge, S. K., Thilakarathna, S., Perera, J. S., Arashpour, M., Sharafi, P., Teodosio, B., Shringi, A., & Mendis, P. (2022) · Automation in Construction · doi:10.1016/j.autcon.2022.104440 · Cited by 1,007
“In the previous years, a growing interest in ANN and DL applications has been observed in property prediction of Fibre Reinforcement Polymer (FRP) [45], Recycled Concrete Aggregate (RCA) [46], and permeable pavements [47].”
BackgroundMachine Learning for Structural Engineering: A State-of-the-Art Review
Thai, H.-T. (2022) · Structures · doi:10.1016/j.istruc.2022.02.003 · Cited by 748
Ganesan, Y., & Panruti Thangaraj, R. (2026) · Periodica Polytechnica Civil Engineering · doi:10.3311/ppci.41876 · Cited by 2
“Na 2 CO 3 was selected due to its lower alkalinity and reduced environmental and handling haz - ards compared to conventional NaOH, thereby contributing to lower CO 2 emissions [23].”
Metadata
- Authors
- Behnood, A., Verian, K. P., & Modiri Gharehveran, M.
- Affiliations
- Purdue University West Lafayette (US)
- Corresponding author
- Behnood, Ali
- Venue
- Construction and Building Materials
- Publisher
- Elsevier BV
- Published
- 2015-11
- Volume
- 98
- Pages
- 519-529
- ISSN
- 0950-0618 (ISSN-L)
- OpenAlex
- W1752416898
- Cited by
- 183
- References
- 60
- Citations by year
- 2026: 13 · 2025: 21 · 2024: 29 · 2023: 24 · 2022: 24 · 2021: 21 · 2020: 15 · 2019: 11 · 2018: 14 · 2017: 8 · 2016: 3
- FWCI
- 13.78
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- Locations
- Construction and Building Materials (publishedVersion)
- Topics
- Physical Sciences › Engineering › Civil and Structural Engineering › Innovative concrete reinforcement materials
- Physical Sciences › Engineering › Building and Construction › Structural Behavior of Reinforced Concrete
- Physical Sciences › Engineering › Civil and Structural Engineering › Concrete and Cement Materials Research
- Keywords
- splitting tensile strength, steel fiber reinforced concrete, plain concrete, compressive strength, tensile strength prediction, artificial neural networks, support vector machine, M5 model tree, nonlinear regression, machine learning
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- The paper
- Behnood, A., Verian, K. P., & Modiri Gharehveran, M. (2015). Evaluation of the splitting tensile strength in plain and steel fiber-reinforced concrete based on the compressive strength. Construction and Building Materials. https://doi.org/10.1016/j.conbuildmat.2015.08.124
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
