This Topic introduces a series of papers that address the impact of uncertainty during the sequence of scientific discovery, which is found across multiple disciplines working with different types, scales, and applications of geomaterials, including i) experimentation, ii) data analysis, and iii) the formulation of corresponding forward models, either based on physical and/or life sciences, statistics, artificial intelligence, or a combination of them, when geomaterial properties and responses are defined in space and time. This Topic has a special focus on cases wherein a series of geomaterial experiments were collected in a laboratory setting or in the field and these were repeated under similar conditions to capture the space, time, or spatio-temporal variability of the geomaterial properties and response when subjected to varying control variables such as boundary conditions, initial and loading conditions, sensing technology, and even the operator’s experience. By capturing the effect of the experimental variability and the associated material properties and response, it is hypothesized that a better understanding of geomaterial performance can be achieved, including its likely failure mechanisms. Consequently, it is anticipated that a more realistic definition of a geomaterial behavior will lead to improved risk assessment and management for physical and/or life processes that depend on it. The original effort to define the scope of this multi-journal MDPI Topic started with the integration of a series of papers produced by the lead and associate guest editors, including the development of a comprehensive experimental database and the mechanical and stochastic modeling of sand specimens, built and tested under similar experimental conditions, which captured 3D displacement fields from their undeformed to their critical states. This allowed for the geomechanical kinematic analysis of localization effects, as well the computation of spatio-temporal statistics of both the displacement fields and of the kinematic effects. This set the basis for the use of other forward modeling methods, including the use of emerging artificial intelligence methods, in multiple geoscientific and geoengineering applications. We also welcome submissions in this field from Applied Sciences, Geosciences, Materials, Minerals, and Modelling. Dr. Zenon Medina-Cetina Dr. Yichuan Zhu Topic Editors Deadline for abstract submissions: 31 March 2022. Deadline for manuscript submissions: 30 June 2022.
Featured Dataverses

In order to use this feature you must have at least one published dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

Advanced Search

1 to 1 of 1 Result
Feb 19, 2022
Medina-Cetina, Zenon, 2022, "Global and Local Deformation Effects of Dry Vacuum-Consolidated Triaxial Compression Tests on Sand Specimens: Making a Database Available for the Calibration and Development of Forward Models",, Texas Data Repository, V1, UNF:6:MN2NAx1SMTczTkcP6ME+Jg== [fileUNF]
A comprehensive experimental database containing results of a series of dry vacuum-consolidated triaxial compression tests was populated. The tests were performed on sand specimens and conducted under similar experimental conditions, in which specimens’ boundary deformation was c...
Add Data

Log in to create a dataverse or add a dataset.

Share Dataverse

Share this dataverse on your favorite social media networks.

Link Dataverse
Reset Modifications

Are you sure you want to reset the selected metadata fields? If you do this, any customizations (hidden, required, optional) you have done will no longer appear.