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Experimental datasets on engineering properties of expansive soil treated with common salt.

ABSTRACT: Construction of highway pavements or high rise structures over the expansive soils are always problematic due to failures of volume change or swelling characteristic experienced in the water permeability of the soil. The data in this article represented summary of (Durotoye et al., 2016; Durotoye, 2016) [1], [2]. The data explored different percentages of sodium chloride as additive in stabilizing the engineering properties of expansive soil compared with other available stabilizer previously worked on. Experimental procedures carried out on expansive soil include: (Liquid limit, Plastic limit, Plasticity index, Shrinkage limit, Specific gravity Free swell index and Optimum water content) to determine the swelling parameters and (maximum dry density, California bearing ratio and unconfined compressive strength) to determine the strength parameters. The results of the experiment were presented in pie charts.

SUBMITTER: Durotoye TO

PROVIDER: S-EPMC5997960 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Experimental datasets on engineering properties of expansive soil treated with common salt.

Durotoye Taiwo O TO Akinmusuru Joseph O JO Ogundipe Kunle E KE

Data in brief 20180414

Construction of highway pavements or high rise structures over the expansive soils are always problematic due to failures of volume change or swelling characteristic experienced in the water permeability of the soil. The data in this article represented summary of (Durotoye et al., 2016; Durotoye, 2016) [1], [2]. The data explored different percentages of sodium chloride as additive in stabilizing the engineering properties of expansive soil compared with other available stabilizer previously wo ...[more]

PMID: 29900305

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Project description:Grassroots have received more attention than the traditional method as soil reinforcement materials, especially the use of vetiver and other vegetation protection methods to treat expansive soil slope, have been tried and applied. To study the influence of grassroots on the strength properties of expansive soil, the laws of vetiver root growth over time and its vertical distribution of root content(δ) were firstly investigated by the experiment of planting vetiver. Then different δ and depth of planted soil were obtained. Simultaneously different δ and water content(ω) of grafted soil were made. With the direct shear test, the shear strength parameters of root-soil with different δ were analyzed. The shear test on root-soil composites with different δ was carried out to compare the strength characteristics of planted and grafted soil. The results showed that the δ of vetiver decreased with the increase of depth, and the δ of each layer increased with the growth period. The δ of 180d was 70.5% higher than that of 90d. The cohesion(c) of root-soil can be increased by more than 97%, and internal friction angle(φ) can be increased by more than 15.4% after 180 days. The c of 90 d vetiver root system can be increased by more than 18%, and the φ can be increased by more than 1.5%. At each depth, the c and φ of composite soil increases with the increase of δ, and the increment of cohesion (Δc) and the increment of internal friction angle (Δφ) increase with the increment of δ. But the increase in the ω will weaken the shear strength parameters of root-soil. Under the condition of the planted root system and grafted root system, the influence degree of δ on strength parameter of root-soil is different, and the law of strength parameters versus δ of grafted soil of 365d is similar to that of planted soil of 90d. And the root reinforcement of grafted soil is weaker than planted soil. Hence the grafted soil can´t accurately reflect the root-soil interaction of the existing root system.

Project description:This research suggests a robust integration of artificial neural networks (ANN) for predicting swell pressure and the unconfined compression strength of expansive soils (PsUCS-ES). Four novel ANN-based models, namely ANN-PSO (i.e., particle swarm optimization), ANN-GWO (i.e., grey wolf optimization), ANN-SMA (i.e., slime mould algorithm) alongside ANN-MPA (i.e., marine predators' algorithm) were deployed to assess the PsUCS-ES. The models were trained using the nine most influential parameters affecting PsUCS-ES, collected from a broader range of 145 published papers. The observed results were compared with the predictions made by the ANN-based metaheuristics models. The efficacy of all these formulated models was evaluated by utilizing mean absolute error (MAE), Nash-Sutcliffe (NS) efficiency, performance index ρ, regression coefficient (R2), root mean square error (RMSE), ratio of RMSE to standard deviation of actual observations (RSR), variance account for (VAF), Willmott's index of agreement (WI), and weighted mean absolute percentage error (WMAPE). All the developed models for Ps-ES had an R significantly > 0.8 for the overall dataset. However, ANN-MPA excelled in yielding high R values for training dataset (TrD), testing dataset (TsD), and validation dataset (VdD). This model also exhibited the lowest MAE of 5.63%, 5.68%, and 5.48% for TrD, TsD, and VdD, respectively. The results of the UCS model's performance revealed that R exceeded 0.9 in the TrD. However, R decreased for TsD and VdD. Also, the ANN-MPA model yielded higher R values (0.89, 0.93, and 0.94) and comparatively low MAE values (5.11%, 5.67, and 3.61%) in the case of PSO, GWO, and SMA, respectively. The UCS models witnessed an overfitting problem because the aforementioned R values of the metaheuristics were 0.62, 0.56, and 0.58 (TsD), respectively. On the contrary, no significant observation was recorded in the VdD of UCS models. All the ANN-base models were also tested using the a-20 index. For all the formulated models, maximum points were recorded to lie within ± 20% error. The results of sensitivity as well as monotonicity analyses depicted trending results that corroborate the existing literature. Therefore, it can be inferred that the recently built swarm-based ANN models, particularly ANN-MPA, can solve the complexities of tuning the hyperparameters of the ANN-predicted PsUCS-ES that can be replicated in practical scenarios of geoenvironmental engineering.

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Experimental datasets on engineering properties of expansive soil treated with common salt.

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Experimental datasets on engineering properties of expansive soil treated with common salt.

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