Development of nomogram for torsional strength of reinforced concrete using hybrid machine learning algorithm

Nolan Concha; Cindelyn Acuyado; Ayke Bernal; Zordic Grey Dumag; John Eazer Francisco; Kenneth Carl Prado

doi:10.1007/s42107-025-01630-2

February 5, 2026Asian Journal of Civil Engineering

Development of nomogram for torsional strength of reinforced concrete using hybrid machine learning algorithm

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Key Points

Torsional strength predictions are essential for structural integrity in engineering designs, ensuring safety and performance.
The hybrid machine learning algorithm achieved significant accuracy in torsional strength predictions across various concrete compositions.
Observational analysis implemented a nomogram to simplify the predicted torsional strength based on key input parameters.
The findings could enhance design standards for reinforced concrete, highlighting the need for integration into industry practices.

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Implication

This research develops a nomogram predicting torsional strength in reinforced concrete using a hybrid machine learning algorithm, suggesting improved design methods.

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Concha et al. (2026) studied this question.

synapsesocial.com/papers/69a766dabadf0bb9e87deb06 https://doi.org/10.1007/s42107-025-01630-2

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Development of nomogram for torsional strength of reinforced concrete using hybrid machine learning algorithm

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Development of nomogram for torsional strength of reinforced concrete using hybrid machine learning algorithm

Key Points

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