Abstract

The durability of road infrastructure in Sub-Saharan Africa represents a major challenge, exacerbated by growing climate hazards and the depletion of conventional materials. Road construction projects consume non-renewable natural resources such as lateritic gravels, as well as locally scarce resources such as water. In response to the need to preserve these resources, the valorization of local excavated materials—previously considered unsuitable for reuse—appears promising. This manuscript presents a comprehensive characterization of an excavated fine lateritic soil from a road construction site in Bassinko (Burkina Faso), with a view toward its reuse in earthworks. The objective is to evaluate its thermo-hydraulic and mechanical properties to provide a sustainable alternative to the exploitation of traditional lateritic borrow pits, which are becoming increasingly scarce. Experimental investigations on the material focused on determining its physical and morphological properties (particle density, Atterberg limits, methylene blue value, particle size distribution, Proctor characteristics), thermal conductivity (in dry and saturated states), the soil-water characteristic curve (SWCC), and mechanical bearing capacity (CBR/IPI). The results show that thermal conductivity is highly dependent on the degree of saturation, increasing from 0.458 W∙m⁻¹∙K⁻¹ in the dry state to 1.826 W∙m⁻¹∙K⁻¹ at saturation, illustrating the formation of aqueous thermal bridges. The analysis of the SWCC, modeled using the Van Genuchten equation, reveals high Van Genuchten modeling parameters $P_{\text{dry}}$ and $P_{\text{sat}}$ (1.85 MPa and 1.03 MPa, respectively), confirming a fine microporous structure. Although soaking causes a drop in the CBR index—decreasing from 50% to 20% for modified energy and from 25% to 17% for standard energy due to the dissipation of matric suction—the material maintains a stable S4 bearing class. Despite an initial classification often deemed “mediocre,” this soil exhibits sufficient immediate bearing capacity and low swelling potential (G < 1%). Its reuse will limit the opening of new borrow sites, thereby reducing the ecological footprint and costs of road infrastructure projects.

Keywords

Excavated Materials, Experimental Characterization, Sandy-Clay Soil, Road Earthworks, Sustainable Development

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1. Introduction

Road projects require the mobilization of large quantities of soil. In tropical Africa, lateritic gravels remain the benchmark materials. Particularly in Burkina Faso, where the paved network is still very limited—with only 26.7% of the classified network being paved [1]—the demand for lateritic gravel is increasing due to numerous road projects currently underway or in the planning stages [1]-[3]. Given this situation, the management of natural resources constitutes one of the primary challenges in road development [4] [5]. Indeed, standard road construction practice involves supplying large volumes of lateritic gravel from borrow pits, which are becoming increasingly scarce and are often located far from construction sites [6]. In addition to the depletion of this resource, which is advantageous for use in base and sub-base layers [4], extraction and transport methods cause negative environmental impacts (such as gas emissions from machinery and high aerosol loading in surrounding areas) and social consequences, notably the loss of potentially arable land for local populations [7] [8].

To address one of the primary challenges—namely the overexploitation of lateritic gravels—the use of local materials located near construction sites proves to be a relevant solution. Indeed, in Burkina Faso specifically, and in tropical and Sahelian countries more generally, significant proportions of swelling or low-swelling sandy-clay soils are encountered at road construction sites [9]-[12]. However, when these soils are used in road embankments, they are subjected to mechanical stresses (road traffic) [13], thermal stresses (due to excessive solar radiation), and hydraulic stresses caused by capillary rise, climatic hazards (flooding, drought), or nearby human activities (excessive irrigation, water pipe leaks, etc.) [14] [15]. These stresses can lead to significant changes in soil properties, potentially compromising the stability and durability of the structures. Consequently, the reuse of these local soils in road embankments is only feasible when they are treated following an exhaustive characterization of their thermo-hydro-mechanical properties. Such treatment enables them to achieve sufficient performance levels to withstand the various mechanical and environmental stresses to which they will be subjected (road traffic, climate, etc.) [12] [16] [17].

A growing body of literature has explored the potential of these local materials in tropical Africa [10] [17]-[25]. As highlighted by Reiffsteck et al. [23], this approach significantly reduces construction costs, notably by limiting the transport of borrow materials and the disposal of excavated soil, while contributing to the sustainable management of natural resources. This practice also aligns with the current context of sustainable development and environmental protection [26].

Although numerous studies have established the potential of low-swelling fine-grained soils as earthwork materials, their behavior in tropical climates is not yet fully understood, as it is complex and depends on several factors. This uncertainty limits their reuse. Furthermore, current specifications for their use in road infrastructure are essentially based on simple identification parameters. In light of these findings, this manuscript proposes an in-depth experimental characterization of a fine-grained soil excavated from a road construction site. It successively addresses the physical and morphological properties of the material, its thermal and hydro-dynamic characteristics, and finally its identification for potential use in road infrastructure.

2. Location of the Road Construction Site

Within the framework of the development and paving of urban roads in the cities of Ouagadougou and Bobo-Dioulasso, the Burkinabe government has initiated the paving of the main access road to the Bassinko district (located on the map in Figure 1). This locality is situated on the northwestern outskirts of Ouagadougou (Burkina Faso). The soil sample used in the present study was collected from this road construction site: a 6.17 km section connecting the locality to National Road RN02. The sample was collected from one of four (4) disposal sites (shown in Figure A1 in Appendix A). A quantity of approximately 500 kg of soil was sampled from the non-organic excavated layer at depths ranging from 0.3 m to over 1 m in some places.

3. Experimental Characterization of Physical and Morphological Properties

3.1. Physical Properties of the Soil

The physical characterization of the soil includes the determination of the specific gravity of solid grains, bulk density, in-situ void ratio, saturated water content, Atterberg limits, and optimal compaction parameters.

3.1.1. Particle Density and Specific Weight

The specific weight or unit weight (${\gamma }_s$ ) of a soil is used in civil engineering to determine the weight of a structure designed to support specific loads while remaining intact and within its deformation limits. Its laboratory determination is based on the measurement of the particle density (or real density) ${\rho }_s$ of the

Figure 1. Location of the sampling site.

soil’s solid grains (NF-EN-ISO-17892-3, 2015). The experimental setup and key laboratory procedure steps are illustrated in Appendix A (Figure A2).

The test was conducted on a single specimen. The values obtained for the particle density (${\rho }_s$ ) and specific gravity (${\gamma }_s$ ) are recorded in Table 1. The determined value of ${\rho }_s$ is close to the standard particle density value typically used for soils when measurements are unavailable, namely 2650 kg∙m⁻³.

Table 1. Particle density and specific weight.

3.1.2. Atterberg Limits

Atterberg limits, or soil consistency limits, are used to identify and classify the soil. They also allow for the prediction of its behavior during earthwork phases and/or when subjected to mechanical stress (allowable stress, modulus of elasticity). Standard NF-EN-ISO-17892-12 (2018) specifies the methods for their determination, namely the liquid limit ($w_L$ ) and the plastic limit ($w_P$ ). These are determined on the fine fraction of the material passing through a 0.4 mm sieve. The plasticity index $I_P$ of the soil corresponds to the difference between $w_L$ and $w_P$ . It indicates the extent of the plastic range and is commonly used to characterize soil clayiness. Table 2 summarizes these three soil parameters. Based on the obtained values, the studied soil, with an $I_P$ between 12 and 22, is classified as moderately clayey [27].

Table 2. Atterberg limits of the soil.

3.1.3. Methylene Blue Value of the Soil

The methylene blue value (MBV), which characterizes the clayiness of a soil, is determined according to standard NF-EN-933-9 (1999). The test data and the resulting VBS are recorded in Table 3. According to the GTR classification system [27], which uses the VBS for soil identification, the studied material is classified as a low-plasticity clayey sand.

Table 3. Methylene blue value of the soil.

3.1.4. Proctor Characteristics

The Proctor characteristics of the soil are presented below. Figure 2 shows the Proctor curves obtained according to standard NF-P94-093 (2014). The 80% and 100% saturation curves (zero air voids curves) are also illustrated. Table 4 summarizes the optimal compaction characteristics of the studied soil.

Figure 2. Proctor curves.

The curves, which are relatively flat, reveal a wide range of compaction water contents that allow the material to achieve optimal mechanical performance. The optimal characteristics of this soil (Table 4) are virtually identical to those reported by Savadogo et al. [24]. Furthermore, the Modified Proctor dry density (${\rho }_{\text{OPM}}$ ) is in the same range as those measured by Mbengue et al. [21]. In contrast, the optimal water content ($w_{\text{OPM}}$ ) obtained for this soil is slightly lower, indicating a higher clay particle content in the studied soil.

Table 4. Proctor characteristics of the soil.

3.2. Morphological Characterization—Particle Size Distribution

The particle size distribution (PSD) of the soil is determined according to standard NF-EN-ISO-17892-4 (2018). The described methodology employs both sieve analysis (for particles larger than 80 μm) and hydrometer analysis (for those smaller than 80 μm). The soil’s grading curve is presented in Figure 3. Table 5 summarizes the results of the particle size analysis of the studied soil.

Table 5. Morphological characteristics of the soil.

a. United States Department of Agriculture.

Figure 3. Granulometric curve of soil.

The grain size classification of the soil was performed in accordance with the USDA classification system. The coefficient of uniformity $C_u$ provides an indication of grain size homogeneity: $C_u>2$ corresponds to a well-graded (extended) distribution, while $C_u<2$ indicates a uniform distribution. The grading is considered well-graded if $1<C_c<3$ , and poorly graded otherwise. Based on the values in Table 5, the studied material has an extended but poorly graded particle size distribution. The proportion of material passing through the 63 μm sieve is essential for classification according to GTR [27]. This proportion is 39.50%. Being higher than the 35% threshold established by GTR [27], this indicates that the material’s behavior is governed by its fine fraction (i.e., particles smaller than 63 μm).

4. Characterization of Thermo-Hydrodynamic Properties

4.1. Thermal Properties—Measurement of Thermal Conductivity

Thermal conductivity is used to describe the thermal behavior of the soil. This parameter is essential for modeling heat transfer within the soil to optimize the design and durability of structures subjected to thermal stresses. The thermal conductivities of the soil in dry (${\lambda }_{\text{dry}}$ ) and saturated (${\lambda }_{\text{sat}}$ ) states were measured in the laboratory following standard ASTM-D5334-22 (2022). The specimens used were compacted at optimal conditions: $w=w_{\text{OMC}}=9.4\%$ and ${\rho }_d={\rho }_{d\text{OMC}}=1.98\text{g}\cdot {\text{cm}}^{-3}$ . The dry specimen was prepared in a Proctor mold (Height H = 116.5 mm and Diameter D = 101.5 mm) and subsequently demolded. To ensure uniform and complete drying, it was exposed to ambient air at an average daily temperature of approximately 35˚C for 30 days. It was carefully drilled using a power drill to accommodate the sensor. As for the saturated specimen, it was prepared in an oedometer ring (Height H = 20 mm and Diameter D = 70 mm) and then submerged for 96 hours to achieve full saturation. The KD2 Pro measurement system equipped with the RK-1 sensor, along with the dry and saturated specimens, are shown in Figure A3 of Appendix A. The RK-1 sensor, with a diameter of 3.9 mm and a length of 6 cm, measures thermal conductivities ranging from 0.10 W∙m⁻¹∙K⁻¹ to 6.00 W∙m⁻¹∙K⁻¹ with an accuracy of ±10%. In accordance with the user manual¹, the sensor was inserted into a hole carefully drilled in each specimen. A reading time of 15 min was set for each of the three (03) measurements performed. The measurement results and the average values are summarized in Table 6.

Table 6. Thermal conductivity (W∙m⁻¹∙K⁻¹) of the soil in dry and saturated states.

The results show a ratio of approximately 4 (i.e., 1.826/0.458). This discrepancy between ${\lambda }_{\text{dry}}$ and ${\lambda }_{\text{sat}}$ is due to the replacement of air (an insulator, ${\lambda }_{\text{air}}\approx 0.024$ W∙m⁻¹∙K⁻¹) with water (a conductor, ${\lambda }_{\text{water}}\approx 0.6$ W∙m⁻¹∙K⁻¹) within the pores during saturation, thereby creating “thermal bridges” between the solid grains. Furthermore, the saturated value of 1.826 for ${\lambda }_{\text{sat}}$ is consistent with soils having a dominant sandy fraction ">">">[28].

4.2. Saturated Permeability

The intrinsic permeability $k$ of a soil depends on its geometry as well as the distribution and size of its constituent pores. It is related to the saturated hydraulic conductivity $K_{\text{sat}}$ by Equation (1).

$K_{\text{sat}}=k\cdot \frac{\rho \times g}{\mu }$ (1)

where:

• $K_{\text{sat}}\left[\text{m}\cdot {\text{s}}^{-1}\right]$ is the saturated hydraulic conductivity of the soil;

• $k\left[{\text{m}}^2\right]$ is the intrinsic permeability of the soil;

• $\rho \left[\text{kg}\cdot {\text{m}}^{-3}\right]$ is the fluid density;

• $g=9.81\text{m}\cdot {\text{s}}^{-2}$ is the acceleration due to gravity;

• $\mu \left[\text{kg}\cdot {\text{m}}^{-1}\cdot {\text{s}}^{-1}\right]$ is the dynamic viscosity of the fluid.

Direct measurement of intrinsic permeability is complex [29]. Therefore, saturated hydraulic conductivity $K_{\text{sat}}$ , which is directly linked to k (Equation (1)), is generally used instead. Experimental laboratory or in-situ measurement methods are proposed in the literature for estimating $K_{\text{sat}}$ . In this study, $K_{\text{sat}}$ is determined using a falling-head permeameter and through a consolidated undrained (CU) triaxial test.

4.2.1. Falling-Head Permeameter Method

Standard NF-X30-441 (2008) specifies the laboratory experimental procedure. The hydraulic conductivity is obtained using Equation (2):

$K_{sat}=\frac{s}{S}\frac{L}{\Delta t}\ln \left(\frac{h_0}{h_1}\right)$ (2)

where:

• $\Delta t\left[\text{s}\right]$ is the time taken by the water to cover the distance $h_0-h_1\left[\text{m}\right]$ ($h_0$ and $h_1$ being the initial and final hydraulic heads, respectively);

• $s$ and $S$ are the cross-sectional areas of the standpipe and the specimen, respectively [in m²];

• $L\left[\text{m}\right]$ is the height of the specimen.

4.2.2. Triaxial Test

The triaxial procedure [30] utilizes Darcy’s law (Equation (3)), which expresses the volumetric flow rate $Q$ [m³∙s⁻¹] (or the filtration velocity of water through the soil column) as a function of the cross-sectional area $A$ [m²] of the specimen and the hydraulic gradient $i=\Delta h/L$ :

$Q=K_{\text{sat}}\cdot A\cdot i$ (3)

where $\Delta h$ [m] is the head loss. Figure 4 shows the evolution of the volume of water injected into the soil specimen during the test at a pressure of 79 kPa. The volumetric flow rate $Q$ corresponds to the slope of the resulting linear trend line. The measurement characteristics for $K_{\text{sat}}$ are presented in Table 7.

Table 7. Permeability measurement characteristics.

Figure 4. Variation of water volume as a function of time.

4.2.3. Results

The measurement results for the soil’s hydraulic conductivity are presented in Table 8. The obtained experimental values of $K_{\text{sat}}$ are relatively close, with a mean relative difference of 2.09%. These values, on the order of 10⁻⁸ m∙s⁻¹, are typical of a clayey to silty clay soil.

Table 8. Hydraulic conductivity and intrinsic permeability of the soil.

4.3. Soil-Water Characteristic Curve

The ability of a soil to retain or release its pore water is characterized by the determination of the soil-water characteristic curve (SWCC). It is typically represented in an ($S_r,s$ ) or ($w,s$ ) plane for a given void ratio $e_0$ . The experimental setup for measuring suction at a given water content differs for low and high suction ranges. A synthesis of the challenges regarding the experimental and numerical (modeling) determination of the characteristic curve is presented in [29], with an emphasis on determination across the entire water content range: from the saturated state to the near-dry state. The WP4C chilled-mirror dewpoint potentiometer (Figure A4 of Appendix A) was used in our study. Unlike other methods such as the pressure plate apparatus (Richards pressure chamber), this device measures total soil suction over a range from 100 kPa to 3∙10⁵ kPa. The experimental procedure complies with the standard ASTM-D6836-16 (2016). Its operating principle is based on measuring the relative humidity of air at the dew point inside a sealed chamber containing the soil specimen at equilibrium García Fernández et al. [31]. Kelvin’s law (Equation (4)) is then applied to estimate the total soil suction $\Psi$ (the sum of a matric component ${\Psi }_m$ due to the porous matrix and capillary forces, and an osmotic component ${\Psi }_O$ due to solute concentration in the pore fluid). In this study, osmotic effects were neglected because at low water contents, the measured suction is dominated by capillary and matric effects; furthermore, demineralized water was used in specimen preparation, thereby limiting the presence of soluble salts [32] [33]. Consequently, the suction measured by the WP4C is assumed to be the matric suction (${\Psi }_m\approx \Psi =-s$ ).

$s=-\frac{RT{\rho }_w}{M_w}\ln \left(RH\right)$ (4)

where:

• $s\left[\text{MPa}\right]$ is the matric suction;

• $R=8.3143\text{J}\cdot {\text{K}}^{-1}\cdot {\text{mol}}^{-1}$ is the ideal gas constant;

• $T\left[\text{K}\right]$ is the absolute temperature;

• $M_w=0.01801\text{kg}\cdot {\text{mol}}^{-1}$ is the molar mass of water;

• ${\rho }_w=998\text{kg}\cdot {\text{m}}^{-3}$ is the density of pure water at 293 K; and;

• RH [/] is the relative humidity.

Figure 5 presents the experimental retention curves alongside those estimated by the numerical model (Equation (5)) of Van Genuchten [34] (the most widely used in the literature). Discrepancies between the experimental and simulated curves are observed for water contents exceeding 50%. These gaps are explained by the inaccuracy of suction measurements in this range, as the WP4C is particularly suited for high suctions. The model calibration parameters (Equation (5)) and the associated statistical test results (R² and Root Mean Square Error: RMSE) are presented in Table 9.

$S_e=\frac{S_l-S_{\min }}{S_{\max }-S_{\min }}={\left[1+{\left(\frac{s}{P}\right)}^{\frac{1}{1-\lambda }}\right]}^{-\lambda }$ (5)

where:

• $S_e[/]$ is the effective degree of saturation of the soil;

• $S_l[/]$ is the liquid (water) saturation;

• $S_{\max }[/]$ is the maximum saturation;

• $S_{\min }[/]$ is the minimum (or residual) saturation;

• $s\left[\text{MPa}\right]$ is the matric suction;

• $P\left[\text{MPa}\right]$ and $\lambda [/]$ are constant parameters to be determined from the experimental curve.

Figure 5. Soil-water characteristic curve.

Table 9. Van Genuchten model parameters [34] for the characteristic curve.

The discrepancy between $P_{\text{dry}}=1.85\text{MPa}$ and $P_{\text{wet}}=1.03\text{MPa}$ indicates that the soil releases its water more with more difficulty than it reabsorbs it. This behavior is conventionally attributed to changes in the contact angle during the drying-wetting cycle. The higher value of $P_{\text{dry}}$ suggests a degree of hydraulic inertia during desiccation episodes.

From a practical standpoint, this property could be a potentially favorable factor for embankment stability under alternating dry and wet seasons. Indeed, since desaturating the material is more difficult ($P_{\text{dry}}>P_{\text{wet}}$ ), the suction variations induced by climatic cycles could be limited—and consequently, variations in effective stress—thereby reducing the risk of shrink-swell behavior. However, it should be emphasized that in situ stability cannot be captured by the retention curve alone, as it depends on several other parameters (geometry, drainage conditions, cohesion, friction angle, and dynamic loading). The work of Kocaman et al. [35] and Luo et al. [36] indicates that pores associated with higher values of P or suction (several hundred kPa) fall within the range of micropores and ultramicropores, which are typical of fine-grained structures. A parameter P of 1.85 MPa thus indicates fine pores, confirming the presence of the clay fraction identified earlier.

5. Soil Bearing Indices

The bearing capacity of a soil is a measure of its ability to support mechanical loads applied to its surface. It is evaluated using the California Bearing Ratio (CBR) and the Immediate Bearing Index (IBI). These bearing indices are used to establish soil utilization criteria in road engineering, as well as to evaluate the trafficability of earthmoving equipment and the thickness of pavement layers based on the underlying soil, expected traffic, anticipated loads, and future hydraulic conditions [22]. In the present study, the soaked CBR and IBI indices were determined for compaction energies corresponding to 25 blows/layer and 56 blows/layer. The tests were conducted on a single soil sample. The characteristics of the IPI and soaked CBR specimens, as well as the test results, are recorded in Table 10.

Table 10. Results of soaked CBR and IBI tests.

The values of the bearing indices $I_{\text{CBR}}$ and $I_{\text{IBI}}$ indicate a soil of medium bearing capacity. According to the $I_{\text{CBR}}$ index, the studied soil belongs to bearing class S4 [37]. The same class was obtained by Mbengue et al. [21] for a borrow pit in Saaba (located on the map in Figure 1). The linear swell index G, being less than 1%, falls within the allowable range for pavement layers ">">">[37]. The soil bearing capacity drops significantly after soaking, decreasing from $I_{\text{IBI}}=50\%$ to $I_{\text{CBR}}=20\%$ (a 30% reduction) for 56-blow compaction, and from $I_{\text{IBI}}=25\%$ to $I_{\text{CBR}}=17\%$ (an 8% reduction) for 25-blow compaction. This drop indicates that at saturation (immersion), the matric suction vanishes. The apparent cohesion provided by suction disappears, leaving the soil to rely solely on its internal friction (sandy fraction) and its intrinsic cohesion (clay fraction). However, this reduction is low compared to bearing capacity losses of 77% and 82% reported by Bâ et al. [38] for lateritic soil samples in Senegal. This difference may be explained by the low activity of the clay fraction in the soil under study. This activity is assessed by Skempton’s activity index ($A_c$ ), which evaluates the soil’s reactivity to changes in hydraulic states: $A_C=I_P/C_{2\mu \text{m}}=0.95$ . This result corresponds to a moderately active clay [39]. Figure 6 shows the evolution of the $I_{\text{CBR}}$ and $I_{\text{IBI}}$ bearing indices according to the compaction level. The evolution of the IBI index in Figure 6(a) demonstrates that the soil requires intense compaction (Modified Proctor energy) to achieve its maximum density. According to the evolution of the $I_{\text{CBR}}$ index (Figure 6(b)), such compaction could enable the soil to maintain its bearing capacity in the event of significant changes in hydraulic conditions. Nevertheless, the risk of swelling or a decrease in bearing capacity should not be entirely ruled out.

Figure 6. Variations in bearing indices as a function of compaction energy: (a) IBI index and (b) CBR index.

6. Classification of the Studied Material

The soil characterization tests presented in the preceding sections provided the parameters necessary for its classification. Thus, the soil classes according to the [27], LCPC (Laboratoire Central des Ponts et Chaussées), and lateritic classification [23] are presented in Tables 11-13, respectively.

Table 11. GTR soil class [27].

Table 12. LCPC soil class.

Table 13. Lateritic soil class [23].

Based on the classification criteria used by the different systems, the soil in this study is identified as a clayey sandy silt. This classification is consistent with the particle size proportions (Table 5). The USDA triangular diagram places it within the aforementioned class. The behavior of this material, while dominated by the sandy fraction, shows a significant influence from the clay content. According to the [27] guide, this soil is suitable for use in road earthworks. However, its implementation is subject to either prior treatment or strict compliance with the recommendations of “Fascicule 2” [27].

7. Conclusions

This study contributes to the valorization of road cut materials in Sub-Saharan Africa through a detailed characterization of an excavated soil from a road construction site in Ouagadougou (Burkina Faso). The work carried out enabled an integrated assessment of the physical, morphological, thermal, and hydrodynamic properties of the soil. Through this characterization, the parameters necessary for classifying the material within established systems were identified. The systems selected for soil identification were: the Guide for Earthworks (GTR), the classification system of the Laboratoire Central des Ponts et Chaussées (LCPC), and the classification system for lateritic materials in tropical regions proposed by Reiffsteck et al. [23]. The material was classified as follows:

• According to the GTR: a fine, moderately sandy clay with extended grading;

• According to the LCPC classification: a low-plasticity sandy clay;

• According to the lateritic soil classification by Reiffsteck et al. [23]: a fine silty lateritic soil (SLF_L1).

Despite being traditionally classified as “mediocre”, the F2 material provides sufficient immediate bearing capacity for earthwork applications. Its reuse helps limit the opening of new lateritic borrow pits, significantly reducing the project’s ecological footprint. However, achieving efficient implementation requires prior treatment or strict adherence to the GTR guidelines [27].

Acknowledgements

This work is part of Burkina Faso’s Higher Education Support Project (PAES), funded by the World Bank, and is the result of a collaboration between Joseph KI-ZERBO University, the 2iE institute, and the Polytechnic University of Catalonia (UPC).

Author Contributions

Conceptualization, Soumaïla Gandema and François Dabilgou; methodology, Soumaïla Gandema and Marcel Bawindsom Kébré; validation, Marcel Bawindsom Kébré; formal analysis, Marcel Bawindsom Kébré and Adamah Messan; investigation, Soumaïla Gandema; resources, Soumaïla Gandema and Marcel Bawindsom Kébré; data curation, Soumaïla Gandema; writing—original draft preparation, Soumaïla Gandema; writing—review and editing, Soumaïla Gandema, Marcel Bawindsom Kébré, Guillaume Zamantakonè Ki and Marie Therese Marame Mbengue; visualization, Soumaïla Gandema; supervision, Marcel Bawindsom Kébré and Marie Therese Marame Mbengue; project administration, Marcel Bawindsom Kébré, Marie Therese Marame Mbengue, Rimyalegdo Kiébré and Adamah Messan; funding acquisition, Marcel Bawindsom Kébré and Adamah Messan. All authors have read and agreed to the published version of the manuscript.

Appendix A. Illustrations of Select Experimental Equipment and Procedures

Figure A1. One of four (4) disposal sites for materials excavated from the road construction site.

Figure A2. Water pycnometer for determining particle density: (a) water bath and temperature control unit set to maintain a constant temperature (20 ˚C in this test), (b) mass and volume of liquid (pure ethanol), and (c) mass and volume of liquid plus material.

Figure A3. Thermal conductivity measurement in dry and saturated states: KD2 Pro testing system with dry and saturated specimens.

Figure A4. Experimental setup for the characteristic curve (WP4C & precision electronic balance containing the soil sample).

NOTES

¹https://aratajhiz.co/wp-content/uploads/2019/03/13351_KD2-Pro_Web.pdf

Conflicts of Interest

The authors declare no conflicts of interest regarding the publication of this paper.

References