In the present work, the power model adopted to predict compressive strength of masonry as a function of brick and mortar strengths was studied by means of Dimensional Analysis, identifying the main dimensionless groups ruling the problem. The approach was applied on a dataset of solid-clay-brick masonry tests collected from the literature. Data were represented in a novel way that permitted to display the importance of the main dimensionless parameters. The dataset was filtered distinguishing these parameters and used to propose a new calibration of the power model considering mortar type and geometry of the specimens. Results show an interesting improvement in terms of indicators of regression quality with respect to the power models proposed in the literature. Both Dimensional Analysis and regressions confirm that the power models are specific for the type of specimens, i.e. dimensionless parameters, used for their calibration and direct comparisons among them should be done with great caution.
Dimensional analysis and calibration of a power model for compressive strength of solid-clay-brick masonry / Ferretti, D.. - In: ENGINEERING STRUCTURES. - ISSN 0141-0296. - 205:(2020), p. 110064. [10.1016/j.engstruct.2019.110064]
Dimensional analysis and calibration of a power model for compressive strength of solid-clay-brick masonry
Ferretti D.
2020-01-01
Abstract
In the present work, the power model adopted to predict compressive strength of masonry as a function of brick and mortar strengths was studied by means of Dimensional Analysis, identifying the main dimensionless groups ruling the problem. The approach was applied on a dataset of solid-clay-brick masonry tests collected from the literature. Data were represented in a novel way that permitted to display the importance of the main dimensionless parameters. The dataset was filtered distinguishing these parameters and used to propose a new calibration of the power model considering mortar type and geometry of the specimens. Results show an interesting improvement in terms of indicators of regression quality with respect to the power models proposed in the literature. Both Dimensional Analysis and regressions confirm that the power models are specific for the type of specimens, i.e. dimensionless parameters, used for their calibration and direct comparisons among them should be done with great caution.File | Dimensione | Formato | |
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