Please note that a complete list of my publications can be found on my Google Scholar, Scopus, and ResearchGate profiles.

Total number of documents: 25
Number of peer-reviewed journal articles: 14
Number of peer-reviewed conference papers: 7
Number of books/thesis: 3
Number of book chapters: 0
Number of standards/design manuals: 0

Refereed Journal Articles

  1. M. M. Madirisha, L. Simwanda, and R. P. Mtei, "Predicting the hydrogen storage capacity of alumina pillared interlayer clays using interpretable ensemble machine learning," Int. J. Hydrogen Energy, vol. 120, pp. 354-364, 2025. doi: 10.1016/j.ijhydene.2025.03.216.

  2. Amika, A.U., Haas, T.N., Simwanda, L. Reliability-based assessment of a multilinear regression model for estimating the ultimate load of eccentrically loaded slender circular CFDST columns. Structural Concrete, 2025. doi: 10.1002/suco.202400418

  3. Simwanda, L., Ikotun, B.D., Ilunga, F.M., Onyari, E.K. “Epistemic uncertainties in torque capacity prediction models for circular CFDST members”, Journal of Construction Steel Research, 2025, volume 226, pages 109299, doi: 10.1016/j.jcsr.2024.109299

  4. Gatheeshgar, P., Ranasinghe, R. S. S., Mohotti, D., Meddage, D. P. P., & Simwanda, L. (2024). Machine learning prediction of web crippling strength in cold-formed steel beams with staggered slotted perforations. Structures,71:108079, doi.org/10.1016/j.istruc.2024.108079

  5. David, A.B.; Olalusi, O.B.; Awoyera, P.O.; Simwanda, L. Suitability of Mechanics-Based and Optimized Machine Learning-Based Models in the Shear Strength Prediction of Slender Beams Without Stirrups. Buildings 2024, 14, 3946. https://doi.org/10.3390/buildings14123946

  6. Amika AU, Haas TN, Simwanda L. Multilinear regression model for predicting the ultimate load of slender circular CFDST columns subjected to concentric and eccentric loading. Structural Concrete. 2024. https://doi.org/10.1002/suco.202400417

  7. Simwanda, L., Gatheeshgar, P., Ilunga, F. M., Ikotun, B. D., Mojtabaei, S. M., & Onyari, E. K. (2024). Explainable machine learning models for predicting the ultimate bending capacity of slotted perforated cold-formed steel beams under distortional buckling. Thin-Walled Structures, 112, 112587. https://doi.org/10.1016/j.tws.2024.112587

  8. Chandrasiri D, Gatheeshgar P, Ahmadi HM, Simwanda L. Numerical Study of Thermal Efficiency in Light-Gauge Steel Panels Designed with Varying Insulation Ratios. Buildings. 2024; 14(1):300. https://doi.org/10.3390/buildings14010300

  9. L. Simwanda, P. Gatheeshgar, BD. Ikotun, M. Bock, FM Ilunga, EK. Onyari, “Reliability analysis of shear design provisions for cold formed steel sections”, Journal of Construction Steel Research, 217 (2024): 108656, doi.org/10.1016/j.jcsr.2024.108656.

  10. Simwanda L, Ikotun BD. Prediction of Torque Capacity in Circular Concrete-Filled Double-Skin Tubular Members under Pure Torsion via Machine Learning and Shapley Additive Explanations Interpretation. Buildings. 2024; 14(4):1040. https://doi.org/10.3390/buildings14041040

  11.  L. Simwanda, N. De Koker, C. Viljoen, and AJ. Babafemi, “Structural reliability of ultra-high-performance fiber reinforced concrete beams in shear” Structural Concrete, 2023; 24(2): 2862– 2878. https://doi.org/10.1002/suco.202200342

  12. L. Simwanda, C. Kahanji, and F. Ali, “Numerical simulation, parametric analysis and design of UHPFRC Beams exposed to fire”, Structures 52,1-16 (2023), doi.org/10.1016/j.istruc.2023.03.155.

  13. L. Simwanda, N. De Koker, C. Viljoen, and AJ. Babafemi, “Bayesian calibration and reliability of UHPFRC beams in fire”, Structural Safety 103, 102352 (2023) https://doi.org/10.1016/j.strusafe.2023.102352

  14. L. Simwanda, N. De Koker, and C. Viljoen, “Structural reliability of ultra-high-performance fibre reinforced concrete beam in flexure”, Engineering Structures 244, 112767 (2021), https://doi.org/10.1016/j.engstruct.2021.112767

Refereed Journal Articles (under review)

  1. L. Simwanda, A.B Davida,O.B. Olalusi, I.B Muhit. Shear capacity prediction and reliability analysis of CRC beams via generative modeling and ensemble learning, Engineering Applications of Artificial Intelligenc, Elsevier, (under review).

  2.  L. Simwanda, M. Sykora, and R. Lenner. (2024). Full and semi-probabilistic analysis of ultra-high-performance concrete beams in bending via machine learning. Structural Engineering International, Taylor and Francis, (under review), X3741.24.05.R1.

Refereed Conference Proceedings

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  1. Simwanda, L., Ikotuna, B. D., Ilunga, M., Onyari, E., & Perampalam, G. (2024). Prediction of the torsional capacity of CFDST steel columns using extreme gradient boosting tree-based machine learning technique. In Proceedings of the 15th Nordic Steel Construction Conference (paper No. 99). Luleå, Sweden, June 26–28. https://doi.org/10.5281/zenodo.12522918

  2. Perampalam, G., Idongesit, U., Bock, M., Dimopoulos, C., & Simwanda, L. (2024). Shear behaviour of cold-formed stainless steel lipped channel sections with web holes. In Proceedings of the 15th Nordic Steel Construction Conference (Paper No. 100). Luleå, Sweden, June 26–28. https://doi.org/10.5281/zenodo.12123993

  3. Simwanda, L., & Sykora, M. (2024). Prediction of moment capacity of ultra-high-performance concrete beams using explainable extreme gradient boosting machine learning model. In Proceedings of the CEACM S4ML 2024 Conference, June 19-21, Prague, Czech Republic.

  4. Simwanda, L., Sykora, M., & Markova, J. (2024). Model uncertainty in European UHPC standards: Insights from SIA-2052 and NF P18-710 flexure models. In Proceedings of the 4th Central European Congress on Concrete Structures, September 22-24, Mikulov, Czech Republic.

  5. Simwanda, L., & Sykora, M. (2024). Resistance model uncertainty in non-linear finite element analyses of ultra-high-performance reinforced concrete beams in flexure. In Proceedings of the Fifteenth International Conference on Computational Structures Technology, special session: Advances in Safety Assessment through Numerical Analyses, September 4-6, Prague, Czech Republic. http://dx.doi.org/10.4203/ccc.9.9.3

  6. L. Simwanda, N. De Koker, C. Viljoen, and AJ. Babafemi, “Structural reliability of existing RC beams strengthened with UHPFRC tensile layers”, Proceedings of the 19th International Probabilistic Workshop 2022 26:191, 197 (2022). 2022, https://ojs.cvut.cz/ojs/index.php/APP/article/view/8409

Refereed Conference Proceedings  [under review]

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