Sensitivity Assessment of Macroscopic Mechanical Responses of Cemented Sand and Gravel to Mesoscopic Parameters Using an Improved MULTIMOORA Method

The macroscopic mechanical responses of cemented sand and gravel (CSG) are jointly affected by the mesoscopic properties of the aggregate, mortar matrix, and interfacial transition zone, while different parameters exhibit distinct magnitudes and directions of influence on strength, stiffness, and failure deformation. To establish a unified parameter priority across multiple macroscopic responses, a two-dimensional random aggregate finite element model was developed, and the elastic moduli and tensile strengths of the aggregate, mortar matrix, and interface were selected as six mesoscopic parameters. Bidirectional perturbations of ±5% and ±10% were introduced around the baseline state, and dimensionless local sensitivity coefficients were calculated using a central finite-difference formulation. Five statistically independent random aggregate realizations were further considered to evaluate the influence of mesostructural variability. The Ordered Weighted Averaging (OWA) operator and entropy weighting method were used to determine subjective and objective criterion weights, respectively, and a MULTIMOORA-based multi-response parameter-prioritization framework was established using the ratio system, reference point method, and modified multiplicative form. Across the five random realizations, the mean sensitivities of the mortar elastic modulus to the macroscopic elastic modulus and failure displacement are 0.5158 and 0.2664, respectively, while those of the interfacial tensile strength to compressive strength and failure displacement are 0.1550 and 0.4512, respectively. The ±5% and ±10% perturbations yield consistent parameter hierarchies, indicating stable local sensitivity results within the investigated neighborhood of the baseline state. Under the combined OWA–entropy weighting scheme, the multi-response parameter priority is ranked as mortar elastic modulus, interfacial tensile strength, aggregate elastic modulus, interfacial elastic modulus, mortar tensile strength, and aggregate tensile strength. The ratio system and modified multiplicative form yield identical rankings, and both show a Spearman rank correlation coefficient of 0.9429 with the reference point method. Weight-scenario analysis further shows that the mortar elastic modulus and interfacial tensile strength consistently remain the two highest-priority parameters, although their internal order varies with the criterion weights. The resulting ranking therefore represents a model- and evaluation-objective-dependent multi-response parameter priority and provides a quantitative basis for mesoscopic parameter screening and subsequent calibration of CSG numerical models.

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Publication Details

Journal
Materials
Published
2026-09-15
DOI
https://doi.org/10.3390/ma19183917
Primary Topic
Geotechnical Engineering and Soil Mechanics
Type
article
Field-Weighted Citation Impact
0.00

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article

Sensitivity Assessment of Macroscopic Mechanical Responses of Cemented Sand and Gravel to Mesoscopic Parameters Using an Improved MULTIMOORA Method

Fan Li, Zhangyu Shi, Yanan Zhang
Materials
Geotechnical Engineering and Soil Mechanics
article

Sensitivity Assessment of Macroscopic Mechanical Responses of Cemented Sand and Gravel to Mesoscopic Parameters Using an Improved MULTIMOORA Method

Fan Li, Zhangyu Shi, Yanan Zhang
article en

Abstract

The macroscopic mechanical responses of cemented sand and gravel (CSG) are jointly affected by the mesoscopic properties of the aggregate, mortar matrix, and interfacial transition zone, while different parameters exhibit distinct magnitudes and directions of influence on strength, stiffness, and failure deformation. To establish a unified parameter priority across multiple macroscopic responses, a two-dimensional random aggregate finite element model was developed, and the elastic moduli and tensile strengths of the aggregate, mortar matrix, and interface were selected as six mesoscopic parameters. Bidirectional perturbations of ±5% and ±10% were introduced around the baseline state, and dimensionless local sensitivity coefficients were calculated using a central finite-difference formulation. Five statistically independent random aggregate realizations were further considered to evaluate the influence of mesostructural variability. The Ordered Weighted Averaging (OWA) operator and entropy weighting method were used to determine subjective and objective criterion weights, respectively, and a MULTIMOORA-based multi-response parameter-prioritization framework was established using the ratio system, reference point method, and modified multiplicative form. Across the five random realizations, the mean sensitivities of the mortar elastic modulus to the macroscopic elastic modulus and failure displacement are 0.5158 and 0.2664, respectively, while those of the interfacial tensile strength to compressive strength and failure displacement are 0.1550 and 0.4512, respectively. The ±5% and ±10% perturbations yield consistent parameter hierarchies, indicating stable local sensitivity results within the investigated neighborhood of the baseline state. Under the combined OWA–entropy weighting scheme, the multi-response parameter priority is ranked as mortar elastic modulus, interfacial tensile strength, aggregate elastic modulus, interfacial elastic modulus, mortar tensile strength, and aggregate tensile strength. The ratio system and modified multiplicative form yield identical rankings, and both show a Spearman rank correlation coefficient of 0.9429 with the reference point method. Weight-scenario analysis further shows that the mortar elastic modulus and interfacial tensile strength consistently remain the two highest-priority parameters, although their internal order varies with the criterion weights. The resulting ranking therefore represents a model- and evaluation-objective-dependent multi-response parameter priority and provides a quantitative basis for mesoscopic parameter screening and subsequent calibration of CSG numerical models.

MaterialsVol. 19(18)
China Three Gorges Corporation (China) (CN), Hohai University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 17%
Geotechnical Engineering and Soil Mechanics
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