A dataset on void ratio limits and their range for cohesionless soils
A database, which consists of maximum and minimum void ratio limits and their range, particle size, distribution and shape characteristics, is compiled. More specifically, minimum and maximum void ratios (emin and emax) along with their range (emax-emin), particle roundness (R) and spherecity (S), f...
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doaj-4da106b9de8d425295087736c860fb832020-11-25T00:44:43ZengElsevierData in Brief2352-34092019-12-0127A dataset on void ratio limits and their range for cohesionless soilsMakbule Ilgac0Gizem Can1Kemal Onder Cetin2Dept. of Civil Engineering, Middle East Technical University, Ankara, TurkeyDept. of Civil Engineering, Middle East Technical University, Ankara, TurkeyCorresponding author.; Dept. of Civil Engineering, Middle East Technical University, Ankara, TurkeyA database, which consists of maximum and minimum void ratio limits and their range, particle size, distribution and shape characteristics, is compiled. More specifically, minimum and maximum void ratios (emin and emax) along with their range (emax-emin), particle roundness (R) and spherecity (S), fines content (FC), coefficient of uniformity (Cu), mean grain size (D50) data are compiled from natural cohesionless soils and reconstituted grained material (e.g.: rice, glass beads, mica) mixtures. The final dataset is composed of 636, mostly soil samples. Out of 636 samples, 496, 474 and 603 of them have emax, emin or emax-emin data, respectively. Similarly, for 593, 419, 171, 126 and 93 soils, D50, Cu, R, S and FC data exists, respectively. Not for every sample, USCS based soil classification designation is available, hence for the missing ones, soil classification is performed based on mean particle diameter-based classification as suggested by ASTM D2487 – 17: Standard Practice for Classification of Soils for Engineering Purposes (Unified Soil Classification System) [1]. The dataset consists of 19 silts and clays, 527 sands (357 fine sands, 153 medium sands, 17 coarse sands) and 47 gravels (44 fine gravels, 3 coarse gravels). A spreadsheet summary of the dataset is provided. This dataset is later used for the development of probability-based void ratio predictive models. Keywords: Void ratio, Mean grain size, Coefficient of uniformityhttp://www.sciencedirect.com/science/article/pii/S2352340919310510 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Makbule Ilgac Gizem Can Kemal Onder Cetin |
spellingShingle |
Makbule Ilgac Gizem Can Kemal Onder Cetin A dataset on void ratio limits and their range for cohesionless soils Data in Brief |
author_facet |
Makbule Ilgac Gizem Can Kemal Onder Cetin |
author_sort |
Makbule Ilgac |
title |
A dataset on void ratio limits and their range for cohesionless soils |
title_short |
A dataset on void ratio limits and their range for cohesionless soils |
title_full |
A dataset on void ratio limits and their range for cohesionless soils |
title_fullStr |
A dataset on void ratio limits and their range for cohesionless soils |
title_full_unstemmed |
A dataset on void ratio limits and their range for cohesionless soils |
title_sort |
dataset on void ratio limits and their range for cohesionless soils |
publisher |
Elsevier |
series |
Data in Brief |
issn |
2352-3409 |
publishDate |
2019-12-01 |
description |
A database, which consists of maximum and minimum void ratio limits and their range, particle size, distribution and shape characteristics, is compiled. More specifically, minimum and maximum void ratios (emin and emax) along with their range (emax-emin), particle roundness (R) and spherecity (S), fines content (FC), coefficient of uniformity (Cu), mean grain size (D50) data are compiled from natural cohesionless soils and reconstituted grained material (e.g.: rice, glass beads, mica) mixtures. The final dataset is composed of 636, mostly soil samples. Out of 636 samples, 496, 474 and 603 of them have emax, emin or emax-emin data, respectively. Similarly, for 593, 419, 171, 126 and 93 soils, D50, Cu, R, S and FC data exists, respectively. Not for every sample, USCS based soil classification designation is available, hence for the missing ones, soil classification is performed based on mean particle diameter-based classification as suggested by ASTM D2487 – 17: Standard Practice for Classification of Soils for Engineering Purposes (Unified Soil Classification System) [1]. The dataset consists of 19 silts and clays, 527 sands (357 fine sands, 153 medium sands, 17 coarse sands) and 47 gravels (44 fine gravels, 3 coarse gravels). A spreadsheet summary of the dataset is provided. This dataset is later used for the development of probability-based void ratio predictive models. Keywords: Void ratio, Mean grain size, Coefficient of uniformity |
url |
http://www.sciencedirect.com/science/article/pii/S2352340919310510 |
work_keys_str_mv |
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1725273730677997568 |