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<p>Stress–strain behaviour of construction materials under axial compression is important for their design and analysis under various stress states. This study is focused on assessing the compressive strength and stress–strain behaviour of un-grouted dry-stack concrete masonries (UDCM) under axial compression. A database was developed by collecting the experimental results of UDCM to predict their compressive strength and stress–strain behaviour. Existing formulations for evaluating the compressive strength and stress–strain behaviour of dry-stack masonry have been appraised and optimised using Bayesian Optimisation technique integrated with a lightweight machine learning approach. An updated formulation is proposed to predict the compressive strength of UDCM incorporating block strength and contact area, i.e. the shape of the blocks. The proposed analytical stress–strain model is composed of three components (1) initial joint settlement, (2) hardening and (3) softening portions. The optimised analytical models are accurate in predicting the compressive strength and stress–strain behaviour of diverse experimental datasets. These formulations can be rationally applied in assessing and designing of UDCM walls under different stress-states.</p>

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Compressive strength and stress–strain characteristics of un-grouted dry-stack concrete block masonry

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月10日

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  • Mathavanayakam Sathurshan,
  • Hossein Derakhshan,
  • Julian Thamboo,
  • Jack Gill,
  • Cathy Inglis,
  • Tatheer Zahra

摘要

Stress–strain behaviour of construction materials under axial compression is important for their design and analysis under various stress states. This study is focused on assessing the compressive strength and stress–strain behaviour of un-grouted dry-stack concrete masonries (UDCM) under axial compression. A database was developed by collecting the experimental results of UDCM to predict their compressive strength and stress–strain behaviour. Existing formulations for evaluating the compressive strength and stress–strain behaviour of dry-stack masonry have been appraised and optimised using Bayesian Optimisation technique integrated with a lightweight machine learning approach. An updated formulation is proposed to predict the compressive strength of UDCM incorporating block strength and contact area, i.e. the shape of the blocks. The proposed analytical stress–strain model is composed of three components (1) initial joint settlement, (2) hardening and (3) softening portions. The optimised analytical models are accurate in predicting the compressive strength and stress–strain behaviour of diverse experimental datasets. These formulations can be rationally applied in assessing and designing of UDCM walls under different stress-states.