Elsevier

Computers & Geosciences

Volume 84, November 2015, Pages 54-60
Computers & Geosciences

Case study
soilphysics: An R package to determine soil preconsolidation pressure

https://doi.org/10.1016/j.cageo.2015.08.008Get rights and content

Highlights

  • Preconsolidation pressure is calculated from the soil compression curve.

  • An R package, soilphysics, was developed to determine the preconsolidation pressure.

  • Four basic calculation methods are presented.

  • Examples are used to illustrate the capabilities of the package.

Abstract

Preconsolidation pressure is a parameter obtained from the soil compression curve and has been used as an indicator of load-bearing capacity of soil, as well as to characterize the impacts suffered by the use of machines. Despite its importance in soil physics, there is a few software or computational routines to support its determination. In this paper we present a computational package in R language, the package soilphysics, which contains implementations of the main methods for determining preconsolidation pressure, such as the method of Casagrande, Pacheco Silva, regression methods and the method of the virgin compression line intercept. There is still a consensus that Casagrande is the standard method, although the method of Pacheco Silva has shown similar values. The method of the virgin compression line intercept can be used when trying to be more conservative on the value (smaller) of preconsolidation pressure. Furthermore, Casagrande could be replaced by a regression method when the compression curve is obtained from saturated soils. The theory behind each method is presented and the algorithms are thoroughly described. We also give some support on how to use the R functions. Examples are used to illustrate the capabilities of the package, and the results are briefly discussed. The latter were validated using a recently published VBA. With soilphysics, the user has all the graphical and statistical power of R to determine preconsolidation pressure using different methods. The package is distribution free (under the GPL-2|3) and is currently available from the Comprehensive R Archive Network (http://CRAN.R-project.org/package=soilphysics). The R platform and all the package dependencies are similarly available from CRAN.

Introduction

The emergence of agricultural mechanization provided advances and modernization of agriculture. Today, this is a reflection of technology in the field. With the consolidation of mechanized systems, we started to realize that operations with farm machinery had negative impacts on soil, especially when operated without traffic control (Imhoff et al., 2004, Saffih-Hdadi et al., 2009). The main impact observed in the soil–machine interface is the compression, resulting from a decreased volume of soil mass in response to the imposition of external loads, caused by agricultural traffic (Imhoff et al., 2004, Saffih-Hdadi et al., 2009).

One proposal to determine extent of damage by agricultural traffic in order to avoid compaction is to study the soil compression process. It is characterized by compressibility tests, whose results are analyzed using a compression curve (Keller and Lamandé, 2010, Keller et al., 2011). The latter reflects the history of stresses experienced by the soil and is used as an indicator of load-bearing capacity of soil, as well as to characterize the impacts suffered by the use of the machines (Casagrande, 1936, Baumgartl and Köck, 2004, Imhoff et al., 2004, Saffih-Hdadi et al., 2009).

The preconsolidation pressure is obtained from a compression curve. According to Imhoff et al. (2004), in practice, the agricultural traffic control by use of information on the pre-consolidation pressure can be made when the machine load and the tire inflation pressure applied on soil do not exceed the value of preconsolidation pressure. Thus, the preconsolidation pressure can be seen as the load bearing capacity of soil.

Using a mathematical definition, preconsolidation pressure is the point that divides the compression curve into two segments. The first part is the portion of the curve corresponding to elastic deformations (recoverable). The second part is called virgin compression curve, corresponding to plastic deformations (irreversible) (Casagrande, 1936, Baumgartl and Köck, 2004, Dias Junior and Pierce, 1995). The region of the curve corresponding to elastic deformation can be used to determine the appropriate time at which the soil must be mobilized or trafficked without occurrence of any additional compaction (Dias Junior and Pierce, 1995). This is because it is this component of the compression curve that reflects the soil stress history (Baumgartl and Köck, 2004). Thus, the highest pressure that can be applied on soil to prevent compaction is the preconsolidation pressure (Dias Junior and Pierce, 1995, Baumgartl and Köck, 2004, Imhoff et al., 2004, Saffih-Hdadi et al., 2009). Therefore, it has been widely used for the control of agriculture, based on traffic data for various management classes and ground systems worldwide.

There are several determination methods of preconsolidation pressure, such as the method proposed by Casagrande (1936), Pacheco Silva (ABNT, 1990), the regression methods presented by Dias Junior and Pierce (1995) and the method suggested by Arvidsson and Keller (2004). Some comparison results can be found in the works of Gregory et al. (2006), Cavalieri et al. (2008) and Rosa et al. (2011). Moreover, Cavalieri et al. (2008) analyzed the results obtained with the methods of Casagrande, regression methods based on the first 2 and 3 points of the compression curves and the method proposed by Arvidsson and Keller (2004) on the same compression curve.

The determination of the preconsolidation pressure by any method requires mathematical manipulation of the compression curve, which may be facilitated by means of computer programs. However, there are only a few computational environments that assist the calculations of preconsolidation pressure through the underlying methods. One of them is a Visual Basic Application developed by Gubiani et al. (2014).

The software R (R Core Team, 2014) is a distribution-free computing environment that receives contributions from researchers and experts in various fields of science worldwide. Notwithstanding, packages destined for soil science are scarce (Omuto and Gumbe, 2009) and there is still no package that can deal with preconsolidation pressure.

In this paper we present and illustrate the capabilities of the R package soilphysics, version 2.4, in determining preconsolidation pressure using the methods of Casagrande (1936), Pacheco Silva (ABNT, 1990), the regression methods presented by Dias Junior and Pierce (1995) and the method presented by Arvidsson and Keller (2004). Graphics and simple outputs facilitate the understanding of each method.

Section snippets

Casagrande (1936) method

The Casagrande method is widely accepted and used as a standard method for determining the preconsolidation pressure (σp) in studies of comparison of methods. To obtain the Casagrande method, the compression curve can be modeled by a polynomial of a higher degree (usually four or five) and by the van Genuchten (1980) equation (Cavalieri et al., 2008). After fitting the model, the σp value can be obtained using the following algorithm:

  • i.

    Determine the maximum curvature point of the curve in a log10

Calculation of σp in soilphysics

When loading soilphysics (type library(soilphysics)), the following packages are required: MASS (Venables and Ripley, 2002) and rpanel (Bowman et al., 2007). The first is called by the function simSigmaP(), which has been designed to simulate preconsolidation pressure. Currently, the functionalities of rpanel are used only when fitting soil water models.

In the soilphysics manual (Silva and Lima, 2015), the user will find a list of functions, including the sigmaP() function, which determines the

Examples

Considering the results of a compression test (Table 1), we can observe the values of the void ratio after each stress applied.

In the R console, the data must be entered as two vectors: one containing applied stress and the other containing void ratio. Then, we can use the function sigmaP() to perform the calculations according to the method chosen. For example, for determining σp using the Casagrande method, type:

  • R> pres <- c(1, 12.5, 25, 50, 100, 200, 400, 800, 1600)

  • R> VR <- c(0.846, 0.829,

Results and discussion

The results of the calculations performed using with the examples from Table 1, Table 2 are shown in Table 3, for each method available in sigmaP(). The graphical output illustrating the calculations is shown in Fig. 3.

Note that different methods promote different values of σp. For example, Dias Junior and Pierce (1995) analyzed and compared Casagrande with regression methods and checked that their agreement decreases as the number of points used by the regression method gets increased. The

Conclusions

With soilphysics it is possible to determine the preconsolidation pressure using the methods of Casagrande, Pacheco Silva, four regression methods and the method of the virgin compression line intercept. Casagrande is considered the standard method.

The package produces graphics with high quality that illustrate the process of preconsolidation pressure determination and may be used for subsequent publication in scientific journals and reports. soilphysics is distribution free (under the GPL-2|3)

Acknowledgments

We thank the Coordination for Improvement of Higher Level Personnel (CAPES, Brazil) for granting scholarships, and the Goiano Federal Institute (Brazil) for the financial support.

References (20)

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