---
title: Flexural Crack Width in Concrete Beams
url: https://www.ml-quant.com/papers/ssrn/4909625/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: SSRN 4909625
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4909625
featured: 2024-07-31
citations: unknown
topic: ML & AI Methods
---


# Flexural Crack Width in Concrete Beams

The research uses machine learning algorithms to predict the flexural crack width in reinforced concrete beams, identifying the Extra Gradient Boosting Regressor as the most accurate, and highlights the stress in reinforcing steel as a key influencing factor.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4909625
- Identifier: SSRN 4909625
- Released: 2024-07-29
- First featured: Quant Letter No. 59 (2024-07-31): https://www.ml-quant.com/issues/2024-07-31/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: ML & AI Methods

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