The PoliTO–UniRoma1 database of cyclic and dynamic laboratory tests: assessment of empirical predictive models

• Published in: Bulletin of earthquake engineering Vol. 21; no. 5; pp. 2569 - 2601
• Main Authors: Ciancimino, Andrea, Cosentini, Renato Maria, Foti, Sebastiano, Lanzo, Giuseppe, Pagliaroli, Alessandro, Pallara, Oronzo
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01-03-2023; Springer Nature B.V
• Subjects: Civil Engineering; Damping; Damping ratio; Datasets; Earth and Environmental Science; Earth Sciences; Empirical analysis; Empirical models; Environmental Engineering/Biotechnology; Fine-grained soils; Geophysics/Geodesy; Geotechnical Engineering & Applied Earth Sciences; Hydrogeology; Laboratories; Laboratory tests; Modelling; Original Article; Performance assessment; Physical properties; Prediction models; Regression analysis; Regression models; Shear modulus; Soil; Soil dynamics; Soils; Statistical analysis; Statistical methods; Structural Geology; Tests; Database; Dynamic properties; Shear modulus; Cyclic and dynamic tests; Empirical models; Damping ratio
• ISSN: 1570-761X; 1573-1456
• DOI: 10.1007/s10518-022-01573-y

The soil nonlinear hysteretic behaviour is usually described, in the moderate strain range, through the shear modulus reduction and material damping ratio (MRD) curves. In common practice, in absence of specific laboratory tests, the curves are estimated by employing empirical regression models. Such predictive models, typically calibrated on large experimental datasets, correlate the soil response to its physical properties. This research fits within this context, presenting a comprehensive database of cyclic and dynamic laboratory tests conducted on natural Italian soils. The database, publicly available as supplementary data of the paper, contains the results of the tests conducted by the geotechnical laboratories of the Politecnico di Torino (Turin, Italy) and the
Sapienza
Università di Roma (Rome, Italy) over the past 30 years. The experimental data are employed to assess the performance of some widely used empirical models in predicting the MRD curves of natural uncemented fine-grained soils, emphasizing the importance of using an independent dataset for conducting a reliable statistical analysis. The results show that the use of many soil parameters as proxies for predicting the soil response does not necessarily lead to an improvement in the performance of the model. Therefore, according to Occam’s razor principle, simple models are to be preferred.