The optimum cutting parameters such as cutting depth, feed rate, cutting speed and magnitude of the cutting force for A356 T6 was determined concerning the microstructural detail of the material. Novel test analyses were carried out, which include mechanical evaluation of the materials for density, glass transition temperature, tensile and compression stress, frequency analysis and optimisation as well as the functional analytic behaviour of the samples. The further analytical structure of the particle was performed, evaluating the surface luminance structure and the profile structure. The cross-sectional filter profile of the sample was extracted, and analyses of Firestone curve for the Gaussian filter checking the roughness and waviness profile of the structure on aluminium alloy A356T6 is proposed. A load cell dynamometer was used to measure different parameters with the combination of a conditioning signal system, a data acquisition system and a computer with visualised software. This allowed recording the variations of the main cutting force throughout the mechanised pieces under different cutting parameters. A carbide inserted tool with triangular geometry was used. The result shows that the lowest optimum cutting force is 71.123N at 75m/min cutting speed, 0.08mm/rev feed rate and a 1.0mm depth of cut. The maximum optimum cutting force for good surface finishing is 274.87N which must be at a cutting speed of 40m/min, 0.325mm/rev feed rate and the same 1.0mm depth of cut.

Cutting metals have been the subject of many studies since the 1850s when the industrial revolution was ruined by the development of machining tools such as lathe, drill, milling, brushing and profiling tools. The development of these machines necessitates the investigation of the phenomenon of metal cutting for the manufacture of pieces with different geometries [1,2]. However, it was until the early 1900s that the first studies [3,4] about the behaviour of cutting forces in machining were carried out. The development of new or improved materials to obtain the optimal parameters in the turning process requires the study of the behaviour of the materials when being machined by conventional or automated methods. Turning is a chip-making process widely used for obtaining parts with complex geometry and excellent surface finish required. Materials have now been developed or improved to increase the efficiency of the manufacturing processes to result in a decrease in their weight, desirable aesthetic and mechanical strength [5,6]. This explains why plain steel has been replaced in manufacturing parts in the automotive sector by aluminium alloys such as A356, A357, and A356.2. These have great acceptance in the development of parts for components in the suspension, transmission, body, wheels and engine of vehicles [6,7]. During the turning operation of a piece, three force components are acting on the cutting tool. A force component act in the direction of the longitudinal advancement of the machine (F), the second act in the course of the radial advancement of the device (Fd), and the third act in a tangential direction to the surface of the part (Fc) of the components.

The tangential force has a greater magnitude which denominates the main cutting force in the process of turning. It is the force that creates a greater consumption of power due to the high speed of cut in the same direction and its impact on the workpiece [8,9]. Takashi and Shoichi [8] analysed the model to evaluate the effect of the cutter run-out on the cutting force of three-dimensional chip flow in milling as a piling up of the orthogonal cuttings in the planes having the cutting velocities and the chip flow velocities. Paulo and Monteiro [9] presented a study of the correlation between cutting forces and tool wear of polycrystalline diamond (PCD) which is measured when machining a composite A356/20/SiCp-T6. Hu et al. [10] based their research on the analysis of process technology and tool kinematics of high cutting honeycomb composites using a triangular blade, it was designed to be performed by analysing cutting force with ultrasonic and non-ultrasonic assistance. Min et al. [11] researched on the correction of cutting force measurement and impact tests using the dynamometer to measure the cutting forces and transfer function between the measured cutting forces and applied forces, respectively. Guicai and Changsheng [12] and Yuan et al. [13] investigated on tool wear model based on the prediction of the cutting force and the energy consumption on the turning process. Also, it is based on the cutting force estimate using an authenticated force model of the residual surface stress of end milling relating cutting force and temperature. Recently Aezhisai et al. [14] presented their work on the study of the cutting conditions that affect the surface roughness and cutting force relative to the spindle speed, axial, radial depth of cut, feed rate and weight percentage of silicon carbide particle SiCp but not cutting force control of A356 T6 alloy in turning operations. The focal emphasis of this research work is to optimise and determine the influence of various cutting parameters such as the speed of tool feed rate, cutting depth and cutting speed over the tangential cutting force which is the primary cutting force. To validate the efficiency of this approach, the research reports on:

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An in-depth study of the cutting force control conditions that affect the surface finishing and cutting force relative to the spindle speed, axial, radial depth of cut and feed rate which change the cutting force control of aluminium alloy A356 T6 in turning operations.

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An evaluation of the turning operations of the aluminium alloy A356 T6 using experimental tests performed with a load cell-based dynamometer, a data acquisition module, a signal conditioning system, a personal computer and a conventional lathe commonly found in the Industry.

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To create the mathematical model for cutting force considering the process parameter of spindle speed, feed rate, axial depth of cut, the radial thickness of cut and control force for turning operations of the aluminium alloy A356 T6

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To implement the factor level Design of Experiments (DoE) technique in the measurement of axial and radial cutting force and affect surface finishing in control force for turning operations of the aluminium alloy A356 T6. Although the aluminium alloy A356 is not easily found in the local market which makes the research on the mechanical behaviour of alloy A356 T6 limited in many countries. However, due to the extensive use and acceptance of this alloy in machine parts in the automotive sector, enhanced information on the behaviour of this alloy in machining operations and especially in turning is required.

The parameter in the Daimler Lead Twist Analysis includes a diameter of 40.0mm, an evaluation length of 2.00mm and a maximum wavelength of 0.400mm. Other settings include period length DP (mm), theoretical supply cross-section DF (μm2), academic supply cross-section per turn DFu (μm2/U), number of threads DG, contact length in per cent DLu (%), lead depth Dt (μm) and lead angle Dy (°).

2Mathematical model of machining toolAccording to Refs. [14,15] who developed a model where the cutting force is proportional to the shear strength of the material, the cutting area and the geometry of the tool. These variables were related to a mathematical model. Another simplified model is the specific shear pressure model [14] which proposes to simplify the area of the cutting plane depending on cutting depth, the cutting thickness and the chip. The simplification that is made is that the cutting area is the product of the feed rate (f) of the tool and the depth of cut (d). According to this model, the cutting force is then obtained by multiplying this simplified cutting area by a factor called the specific shear pressure (Ks), which considers the cutting shears strength of the material:

Since the earliest experimental studies on shear forces, many investigations have been carried out presenting equations of the type shown in Eq. (2):

Several empirical formulas have been proposed but maintaining the original form of Eq. (2). These equations are the product of conditions and parameters such as material characteristics, tool geometry, lubrication, etc. which does not make them applicable to another experiment; although they provide results that serve as a reference for different conditions. In the investigation of Refs. [10–12], an analytical method was developed to leave aside the “particularities” of each test generating an expression that depends only on the ultimate strength of the material and the cutting area. Kexuan et al. [6] developed a mathematical model for the determination of shear force in machining operations which unlike the theory of specific shear pressure considers the characteristics of the material. The empirical expression is defined as:

3MethodologyThe material used is a cast aluminium, silicon and magnesium alloy whose designation according to the Aluminum Association (AA) is A356. Four bars were modelled using a model parameter 50.84mm in diameter and 610mm long; making a direct casting of the alloy already deduced and balanced in the model conditioned for that purpose. The chemical composition of the model bars was obtained by sampling the rods, and an optical spectrometer was used to obtain the weight per cent of the components. The model bars were subjected to a T6 heat treatment which involves a solubilisation treatment at 540°C for 4h followed by rapid cooling in a tub with water at 75°C for 10min. After this, an artificial ageing treatment was applied at a temperature of 155°C for 5h using a THERMOLYNE model 4800 electric oven. The temperature was controlled by a K-type thermocouple from the oven and a J-type thermocouple connected to an EXTECH model EX470 digital display [15–17]. The specimens were machined from the heat-treated rods according to ASTM [17,18]. The samples were subjected to a uniaxial tensile test in a Universal GALDABINI Model CTM 20 material test machine with a capacity of 20 metric tonnes, calibrated the length of 50mm and a test speed of 2mm/min. This was used to obtain the mechanical properties shown in Table 1[19]. The hardness measurement of a sample of one of the model bars was taken after the heat treatment (T6) was applied and the surface was prepared according to the recommendations of the ASTM E18 standard [20,21] for measuring Rockwell hardness in metallic materials.

Mechanical properties of the samples tested.

Samples | The module of elasticity (MPa) | Yield strength (0.2% offset of the length calibrated) (MPa) | Ultimate strength (MPa) | Elongation (% by 50mm) |
---|---|---|---|---|

1 | 4739.87 | 128.90 | 162.16 | 2.59 |

2 | 4855.53 | 111.67 | 144.02 | 1.20 |

3 | 4718.44 | 107.67 | 164.98 | 2.25 |

4 | 4886.12 | 112.81 | 152.93 | 2.35 |

Average | 4799.99 | 115.2625 | 156.0225 | 2.0975 |

For preparing the sample, the recommendations of ASTM E3 [11] were followed. The recommendations of ASTM E407 [12] were used to develop example by chemical etching, a solution of Tucker 15HF concentration, 45cc HCL concentration, 15cc HNO3 concentration and 70cc H3O concentration was used. The prepared sample was observed under a microscope with different magnification scale to obtain the microstructures that are sampled in Fig. 1.

Nanostructures of reactive analysis (A) enhance the increase of 100×, (B) surface characterisation of KL transformed in nanometer of the A356 T6 alloy of a Gaussian filter of the materials of the threshold of −60.8nm to 39.1nm, (C) surface roughness wavelet filter of the Daubechies 2, and (D) graphical profile of upper enhance KL transformed.

This consists of an enhanced KL converted 2/5 profile with a T-axis and Y-axis of 13.2mm. The parameters include a length of 76.0mm, a Pt of 99.9mm, a scale of 133mm and a shown scale of 133nm. The equipment used a signal conditioning system strain gage-based load cell filter with fixed gain. A data acquisition system multifunction data acquisition module connected via USB to a computer system of a power source to power the filter Amplifier which in turn feeds to the load cell with an excitation voltage of 10V. A personal computer with real-time data visualisation and monitoring software to record the variations of the cutting force along the workpiece. The dynamometer was rectified by applying a known force to the load cell using a universal test machine model CTM 20, then with a digital multimeter. The output voltage the load cell is conditioned by the filter – amplifier. From this, the calibration curve which relates the load applied to the cell, and the already conditioned output voltage by the dynamometer is obtained (Table 2).

Parameter of KL transformed of A356 T6 in ISO 25178.

Parameters of Karhunen–Loève theorem (KL) transformed ISO 25178 | ||||
---|---|---|---|---|

Height parameters | Feature parameters | |||

Root square height (Sq) | 29.2nm | Density of peaks (Spd) | 0.123mm−2 | pruning=5% |

Skewness (Ssk) | −0.0315 | Arith. peak curvature (Spc) | 0.000183mm−1 | pruning=5% |

Kurtosis (Sku) | 1.85 | Ten point height (S10z) | 83.9nm | pruning=5% |

Peak height (Sp) | 49.3nm | Five peak height (S5p) | 42.0nm | pruning=5% |

Pit height (Sv) | 50.7nm | Five pit height (S5v) | 41.9nm | pruning=5% |

Height (Sz) | 100nm | Mean dale area (SDA) | 6.49mm2 | pruning=5% |

Arithmetic height (Sa) | 25.1nm | Mean hill area (Sha) | 6.75mm2 | pruning=5% |

Functional parameters | 3D parameters | |||
---|---|---|---|---|

Areal material ratio (Smr) | 100% | c=1000nm of peak | Mean height absolute (Smean) | 129,387,514nm |

Inverse areal ratio (Smc) | 40.5nm | p=10% | Developed area (Sdar) | 4609mm2 |

Extreme peak height (Sxp) | 49.6nm | p=50% and q=97.5% | Projected area (Spar) | 4609mm2 |

Spatial parameters | Hybrid parameters | |||
---|---|---|---|---|

Autocorrelation (Sal) | 3.31mm | s=0.2 | Root square gradient (Sdq) | 5.52e−05 |

Texture ratio (Str) | 0.728 | s=0.2 | Developed interfacial area ratio (Sdr) | 1.52e−07% |

Texture direction (Std) | 69.7° | Ref. angle=0° |

Functional parameters volume (mm3/mm2) | Functional parameters of stratified surfaces | ||||
---|---|---|---|---|---|

Material volume (Vm) | 4.78e−07 | p=10% | Core roughness depth (Sk) | 4.76nm | Gaussian filter, 0.8mm |

Void volume (Vv) | 4.1e−05 | p=10% | Reduced summit height (Spk) | 2.83nm | Gaussian filter, 0.8mm |

Peak material vol. (Vmp) | 4.78e−07 | p=10% | Reduced valley depth (Svk) | 3.20nm | Gaussian filter, 0.8mm |

Core material vol. (Vmc) | 3.13e−05 | p=10% and q=80% | Root square roughness (Spq) | 2.08 | Gaussian filter, 0.8mm |

Core void volume (Vvc) | 3.87e−05 | p=10% and q=80% | Root square roughness (Svq) | 11.8 | Gaussian filter, 0.8mm |

Pit void volume (Vvv) | 2.31e−06 | p=80% | Material ratio valley (Smq) | 99.0 | Gaussian filter, 0.8mm |

The extracted profile of the parameter of the surface characterisation of KL of the A356 T6 alloy was set according to ISO 4287 standard of spacing parameters roughness profile that sooth the experiment. The Gaussian filter was configured to 0.8mm of a mean width of the roughness profile elements (RSm) of 1.63mm at root-mean-square slope of the roughness profile (Rdq) 0.000265°. The peak parameters of roughness profile at Gaussian filter of 0.8mm is of peak count on the roughness profile (RPC) 0.503L/mm at ±0.5nm. The material ratio parameters of a primary profile with a relative material ratio of the raw profile (Pmr) of 100% has the highest peak at 1000nm and a raw profile section height difference (PDC) at 63.7nm as p=20%, q=80%. A relative material ratio of the raw profile (Pmr) of 100% has the highest peak at 3000nm and raw profile section height difference (Pdc) at 98.1nm as p=2%, q=98%.

The waviness profile information of the analysis includes an appropriate setting of a Gaussian filter with 2.50nm cut-off, a diameter of 40.0mm, an evaluation length of 2.00mm and a maximum wavelength of 0.400mm. Other parameters include period length DP (mm), theoretical supply cross-section DF (μm2), theoretical supply cross-section per turn DFu (μm2/U), number of threads DG, contact length in per cent DLC (%), first depth Dt (μm) and lead angle Dy (°).

In the determination of the experimental cutting force, an experimental methodology of machining was designed by combining the cutting parameters and relating them to a 4×4×4 factorial model. The parameters selected for the machining tests were: 0.06mm/rev, 0.12mm/rev, 0.24mm/rev and 0.38mm/rev of feed rate, cut depths of 0.25mm, 0.5mm, 1.0mm and 1.5mm and cutting speeds of 22.97m/min, 44.07m/min, 81.40m/min and 133.0m/min. The combination of these cutting parameters according to the methodology developed in Section 3 of the research work was used to obtain the shearing force that is generated when turning the alloy A356 T6. The tool position angle was 91°. The machining tests involve external cylindrical specimens made for this purpose using a conventional parallel lathe, a model with bench length of 3m, turning 40cm, spindle turning speeds of 50–1200rpm and positioning accuracy of 0.05mm. The dimensions of the specimen are 48mm in diameter and 250mm in length. The selected turning operation is an external displacement holding the probe with the lathe mandrel on the left side of the bar and placing a counterpoint on the right side of the bar to minimise the effects of buckling and vibrations on the measurements of the cutting force. The cutting depth was constant throughout the machining, and the feed rate was varied in each of the delimited sectors with a constant cutting speed which was also taken as cutting speed average speed considering the diameter of the bar and the speed of rotation of the selected spindle. The machining was done without the use of cutting lubricants. The dynamometer was used for the measurement and recording of the main cutting force for each combination of parameters used in the test. To obtain the average shear force value for each combination of parameters, the data obtained with the use was first analysed. The curve was smoothed using a data post-processing technique called a digital smoothing polynomial filter which smooth the curve by attenuating noise from data acquisition instruments and other sources used. Then the average arithmetic means of the cutting force for the combination of cut parameters tested in the stable zone of the curve was calculated from the data obtained from the smoothed curve (Fig. 2).

4Discussion of resultsThe graphs of the cutting force as a function of the experimentally measured cutoff time have a large amplitude due to the characteristics of the load cell used in the dynamometer. The features of the data acquisition module, as well as the variables which occur in the turning process such as the microstructure of the material [21–23] vibrations among other parameters, also have a large amplitude. Smooth experimental curves for each combination of parameters were analysed, determining the average arithmetic mean of the shear force in the stable zone of the curve. In examining the behaviour of the cutting force, it is observed that as the cutting speed increases for a given cut depth, the cutting force decreases slightly. This behaviour of shear strength by increasing the cutting rate was evidenced for almost all combinations of feed rate and sheer depth used in operation as shown in Figs. 4 and 5.

The alloy A356 T6 waviness filters of Daubechies 10 characterisation of fractal analysis of KL transformation in relative length scale sensitive of surface fractal analysis of KL transformation is represented in Fig. 3A–C. The complexity of scale sensitivity of fractal analysis of KL transformation with the averaged power spectrum density of KL transformed and control chart compactness of volumetric parameters of KL transformed is shown in Fig. 3D–H which has its parameters for Fig. 3D and E and Fig. 3F–H in pairs as follows: projected area 23.6%, 50.8%, volume of void 12.5%, 49.0%, volume of material 87.5%, 51.0%, volume of void 3.116788654e+12nm3/mm2, 2.452386954e+13nm3/mm2, volume of material 2.188321078e+13nm3/mm2, 2.54761316e+13nm3/mm2, mean thickness of void 3.12nm, 24.5nm, mean thickness of material 21.9nm, 25.5nm. The information in Fig. 3 is obtained using morphological envelopes method. The parameters include fractal dimension 2.60, slope (1) 0.397, R2 (1) 0.989, slope (2) 0.0625 and R2 (2) 0.937. The information in Fig. 4 is obtained by the length-scale (rows) method with the parameters as follows: number of points 200, Y (Max) 1.00, SRC threshold 1.00, domain max scale 76.0mm, SRC 2.89mm, Reg. line slope −2.65e−10, Reg. line Y-intercept 1.32e−10, R2 0.988, Lsfc 2.65e−07, Dls 1.00, Smfc 0.569mm and epLsar (1.8mm, 5°).

Microstructural illustration of the alloy A356 T6: (A) waviness filters of Daubechies 10 characterisation of relative length scale sensitive of surface fractal analysis of KL transformation, (D) complexity of scale sensitivity of fractal analysis of KL transformation, (C and D) averaged power spectrum density of KL transformed, and (E and F) control chart compactness of volumetric parameters of KL transformed.

The information in Fig. 4 is also obtained by the length-scale method with the following parameters of number of points 200, Y (Max) 1.00, SRC threshold 1.00, domain max scale 76.0mm, SRC 2.89mm, Reg. line slope −2.65e−10, Reg. line Y-intercept 1.32e−10, R2 0.988, Lsfc 2.65e−07, Dls 1.00, Smfc 0.569mm and epLsar (1.8mm, 5°). The zoom factor information of Fig. 4 is ×4 of a smoothing parameter value with a spatial frequency value of 0.0785nm−1, an amplitude of 75.2nm2, a dominant spatial frequency of 0.0132nm−1 and the maximum amplitude of 114nm2. The information represented in Fig. 4 is the zoom factor of ×4 of a smoothing parameter profile with a wavelength of 7.61mm, an amplitude of 4.79nm, a dominant wavelength of 11.3mm and a maximum amplitude of 8.40nm. It is also and has its parameters as follows as peak material volume (Vmp) 0.000478ml/m2, core material volume (Vmc) 0.0313ml/m2, core void volume (Vvc) 0.0387ml/m2 and pit void volume (Vvv) 0.00231ml/m2. It has unfiltered settings with parameters of core roughness depth (Sk) of 97.9nm, reduce submit height (Spk) of 0.0316nm, reduce valley depth (Svk) of 2.67nm, area material ratio (Smr(1)) of 0.0316%, areal material ratio (Smr(2)) of 96.6%, arithmetic mean height (Sa(1)) of 4,991,926nm3/mm2 and arithmetic mean height (Sa(2)) of 4.584235538e+10nm3/mm2. The parameter's value of Fig. 4 which shows the control chart includes a variance 0.07742, yield 0.00%, Cp 24.5, Cpk −5.41, Cpkl −5.41, Cpku 54.4, NT 1.672 and ET 40.92. Fig. 4 contains information about nanostructure which its parameters include a variance 1678(nm/mm2)2, yield 40.2%, Cp 0.166, Cpk −0.0367, Cpkl 0.369, Cpku −0.0367, NT 246(nm/mm2)2 and ET 40.9(nm/mm2)2. It is the control area of the motif analysis. The parameters are: a variance 229mm4, yield 87.7%, Cp 0.450, Cpk 0.257, Cpkl 0.257, Cpku 0.643, NT 90.8(mm2)2 and ET 40.9(mm2)2.

Fig. 4 represents the control chart of Sq height parameter of the system modification in ISO 25178 standard. The parameters include a variance 27.6nm2, yield 80%, Cp 0.524, Cpk 0.461, Cpkl 0.588, Cpku 0.461, NT 31.5nm2 and ET 16.5nm2. For great tool advancement values, as the cutting speed is increased, the decrease in shear force as compared to low feed rates becomes more noticeable. As the cutting speed is increased for an advance and the cutting depth is increased for a given tool advance, the cutting force required to perform the machining increased. Also, for high cut depth values and grow in the cutting speed, the cutting strength decreases in comparison to low cut depth values as shown in Figs. 5 and 6. For a feed rate used, the behaviour is like the rest of the feed rate.

As the cutting depth is increased for constant cutting speed, the required cutting force is linearly increased because the cutting area increased, and more material is removed per unit time. This behaviour was evidenced by the full range of feed rate used in the graph as shown in Fig. 4. As the feed rate of the tool increased to a constant depth of cut, the required cutting force is linearly increased because the cutting area also improved and more material is removed per unit time. This behaviour was evidenced by the full range of shear rates used in the tests as shown in Fig. 5. As the cutting depth is increased for constant cutting speed, the required cutting force is linearly increased because the cutting area also improved and more material is removed per unit time. This behaviour was evidenced by the entire range of tool advances used in the tests as shown in Fig. 6.

As the depth of cut for a constant tool advance increases, the cutting force required is linearly increased. This is because the cutting area also improved and more materials are removed per unit time. This behaviour was evidenced by the full range of feed rate used in the tests as shown in Fig. 6. The optimal levels for the turning of aluminium alloy A356 T6 in centre lathe to obtain minimum surface roughness and cutting force of 71.123N at 75m/min cutting speed are at a feed rate of 0.08mm/rev and 1.0mm depth of cut. The maximum optimum cutting force for good surface finishing is 274.8762N which must be at a cutting speed of 40m/min of 0.325mm/rev feed rate and the same 1.0mm depth of cut which are the measured optimal parameters for the turning operations of aluminium alloy A356 T6.

5ConclusionsThe main cutting force was measured and recorded experimentally in turning operation of the aluminium alloy A356 T6. It was discovered that as the cutting speed in the turning of A356 T6 alloy increases, the cutting force required to perform the turning operation to maximum satisfaction is slightly reduced. As the feed rate or cutting depth of the tool increases, the cutting area in the turning of A356 T6 alloy increases, it also increases the cutting force required to perform the machining operation to optimal satisfaction. This research proposes a novel evaluation for the possible turning of A356 T6 alloy of different sample and examine it nanoparticles and microstructural behaviour to enhance productivities. According to the results obtained in the tensile and compression tests, the resistance of the A356 T6 alloy was low when compared to the other commercial alloy, but they presented fair values if the desired application was treated according to the results obtained in differential scanning calorimetry and the analysis of the microstructure. The resins showed different behaviour from the low-temperature state to the high-temperature state, which is typical of crystalline and semi-crystalline alloy, with characteristics like the industrial plastics. The maximum shear force measured in the experimental tests was 45.50kg for the following combination of parameters: cutting speed of 22.97m/min, a feed rate of 0.35mm/rev and cutting depth of 1.50mm. The alloy presented different thermoplastic behaviour, and the values concerning the contraction and expansion of these materials were evaluated, as well as its compatibility and emissions of compounds when subjected to heating processes. Also, such as those occurring in the cast-deposition this study opens the way for other researches regarding the identification of the characteristics of another alloy available for application in cutting operation.

FundingThis project is funded by the Higher Education Innovation Fund (HEIF) of De Montfort University 2017-2018, UK: Research Project No.0043.06

Conflicts of interestThe authors declare no conflicts of interest.