**4. Experimental study**

where *n* can be represented with *n* = 3/ψ, ψ is the sphericity of the particle. Generally, n = 3 is

Unlike Maxwell model, Bruggeman model is applicable for two binary mixtures with no particle concentration limitations. However, Bruggeman model tends to deviate from Maxwell model at higher concentrations. The Bruggeman model is similar to that of Maxwell model as both models use the same assumption basis that the shape of particles are spherical. The

(

where φ is the volume fraction of nanoparticles dispersed, kbf is the thermal conductivity of base fluid, kp as the thermal conductivity of nanoparticles and keff as the effective thermal

Rheological models are used to determine the relationships between shear stress and shear rate as different applications possess different characteristics. Non-Newtonian models such as Bingham Plastic model [39] and Power Law model [40] are commonly used to predict rheo-

Bingham Plastic fluids are unique as it has "infinite" viscosity until adequate stress is applied

*σ* = *σ*<sup>0</sup> + (4)

rate. The limiting shear stress is often referred to as Bingham Yield Stress of the material. This model is suitable for concentrated mixtures and colloidal systems possessing Bingham

Generally known as Ostwald model, non-Newtonian materials behave with respect to shear rate to produce two effects, namely shear thinning and shear thickening. Shear thinning yield lower viscosity when subjected to higher shear rate while shear thickening contradicts. The thickening is normally associated with the increase in sample volume and is known as dilat-

is the limiting shear stress, μ is the viscosity and γ is the shear

*kp* <sup>−</sup> *<sup>k</sup>* \_\_\_\_\_\_*eff*

*kp* <sup>+</sup> <sup>2</sup> *<sup>k</sup>eff*) <sup>=</sup> <sup>0</sup> (3)

taken for spherical particles while n = 6 is considered for cylindrical shape particles.

*3.1.3. Bruggeman model*

70 Drilling

conductivity of nanofluid.

**3.2. Rheological models**

*3.2.1. Bingham Plastic model*

where σ is the shear stress, σ<sup>o</sup>

ancy. The Power Law model is as follows:

behaviours.

*3.2.2. Power Law model*

Bruggeman model is written as follows:

ϕ(

logical behaviours and are considered in this study.

to initiate flow process. The Bingham Plastic model is as follows:

*kp* <sup>−</sup> *<sup>k</sup>* \_\_\_\_\_\_*eff*

*kp* <sup>+</sup> <sup>2</sup> *<sup>k</sup>eff*) <sup>+</sup> (<sup>1</sup> <sup>−</sup> *<sup>ϕ</sup>*)

#### **4.1. Homogenization process**

In this study, hydrogenated base oil (HBO) as base fluid and graphene oxide paste are supplied by a local company supplier. HBO is derived from vegetable oil through catalytic hydrotreating process and contains alkane chain branch between C15-C18. For the characterization of nanoparticles, graphene oxide paste was subjected to FTIR (Perkin Elmer) with wavenumber ranging from 500 to 4000 cm−1 and TEM (Zeiss Libra 200FE) analysis at magnification range at 20,000x to 800,000x values. The HBO and graphene oxide paste were homogenized through a hydrodynamic cavitation unit at a constant flow rate of 1.5 L/min for 3 hours duration with an average of 10 bars pressure. The orifice diameter and length are 1 mm and 30 mm respectively. The schematic diagram is as shown in **Figure 3**. The hydrogenated oil-based nanofluids were transferred to an ultrasonic bath (Bath Ultrasonic Branson 8510E – DTH) for further homogenization.

#### **4.2. Thermal conductivity properties analysis**

Thermal conductivity analysis of hydrogenated oil-based nanofluids are carried out with KD2 Pro Thermal Properties Analyser equipped with KS-1 sensor with dimension

**Figure 3.** Schematic diagram of hydrodynamic cavitation unit (HDV: hydrodynamic vessel, MV: mixer vessel, PG: pressure gauge, RP: rotary pump, HDP: hydrodynamic pump).

1.3 mm diameter × 60 mm length) which complies with ASTM D5334-14 standards. The parametric studies in thermal conductivity analysis are divided into three categories, mainly the effect of temperature, the effect of nanoparticle concentrations and the effect of nanoparticle types. The temperature parameter in this study is set within the ranges of 30–50°C with a 5°C increase at each interval step. The presence of nanoparticles suspended within each sample move freely under elevated temperature, prompting fluctuations in thermal conductivity results. Therefore, each sample was repeated three times to ensure mean thermal conductivity is obtained. Further detailed explanation on the method can be found in our earlier work [48].

Two characterizations were used to characterize graphene oxide paste, namely FTIR analysis and TEM analysis. **Figures 4** and **5** show FTIR spectra analysis and TEM imaging of graphene

Bio-Based Oil Drilling Fluid Improvements through Carbon-Based Nanoparticle Additives

http://dx.doi.org/10.5772/intechopen.74674

73

At 3500 cm−1 range, O-H group is present in graphene oxide as shown in **Figure 4** and is further supported by the findings of Farbod et al. [17]. Absorption peak between 1630 and

oxide paste respectively.

**Figure 4.** FTIR spectra analysis of graphene oxide.

**Figure 5.** TEM image of graphene oxide at 31,500× (left) and 80,000× (right) magnifications.

## **4.3. Rheological properties analysis**

The parametric studies considered for the rheological properties analysis are viscosity values and shear stress values of hydrogenated base oil nanofluid with respect to shear rate and temperature. Rheological properties were measured using Malvern Bohlin Gemini II Rheometer following the method discussed in our earlier work [56].
