In the past decade, advances in Machine Learning (ML) techniques have resulted in developing sophisticated models that are capable of modeling extremely complex multi-factorial problems like slope stability analysis. The literature review indicates that considerable works have been done in slope stability using ML, but none of them
Reviewer #2:Comments pertaining to Geological characteristics and Geotechnical study Comment 1: Slope dimensions are not visible in field photos. Authors may add panoramic view illustrating dimensions of slope.Reply: As per recommendation, the slope dimensions were added to the field photograph (Fig. 1).We regret to inform you that we could not add a panoramic view of the slope since no panoramic photograph was taken for the slope during field investigation and now it is not possible to get the panoramic view photograph. Comment 2: Tension cracks were observed during field surveys? If yes, they were considered in simulation studies/ in pre-assumption of slip surfaces? Reply: We would like to inform that out of the four sites (Nainital, Haridwar, Dehradun, and Solan) from where field investigations were carried out, and samples were collected for laboratory tests (Ray et al. 2019), only one site (Haridwar) had few tension cracks. Rest of the sites were free from any tension cracks. Thus, during simulation, no tension cracks were assumed. Comment 3: Kindly provide boundary conditions and model environment/initial conditions. Reply: The following boundary conditions and model environment/initial conditions were used during simulation (Note: This is only to inform the reviewer, and the details are given in Ray et al. (2019). If the reviewer recommends, it can be added in the revised manuscript)"Fixed boundary conditions (zero displacements) have been used at the base of the model, and along the lateral sides, however, the slope face and the rock-soil interface were kept free for showing strain and displacement. Two-dimensional six-noded triangular plane strain elements have been used to discretise across the selected slope profile. In this study, a uniform meshing option has been used for the soil and weathered rock layer and graded meshing for the bedrock layer. The average element size of around 0.5 m,1 m, and 5 m is kept for the residual soil layer, the weathered rock layer, and the bedrock layer, respectively. It was assumed that no tension cracks are present on the crown of the slope.All the models evaluated under dry condition."
Thermal conductivity and viscosity analysis of Al2O
3/CuO (50/50) hybrid nanofluid in various mass fractions of ethylene glycol (EG) and propylene glycol (PG) binary base fluid have been investigated in the present work. Hybrid nanofluid with vol. fraction range limited to 1.5% and within the higher temperature range of 50°C to 70°C is considered for thermal conductivity and viscosity analysis. Impact on viscosity and conductivity models with various shape nanoparticles, i.e, spherical, cylindrical, brick, platelets, and blades have been discussed and were compared in EG and PG binary base fluids. Also, the analysis extends to the prediction for the stability with zeta potential and synthesis of spherical shape Al2O3/CuO hybrid nanofluid with X‐ray diffraction (XRD) and scanning electron microscope (SEM). The theoretical analysis revealed that thermal conductivity of Al2O3/CuO hybrid nanofluid in EG binary base fluid is lower compared to in PG binary base fluid. The thermal conductivity is observed to be higher in spherical and cylindrical shape nanoparticle compared to bricks, blades, and platelets shape nanoparticles. Optimum viscosity of Al2O3/CuO hybrid nanofluid is observed at 50%EG and 30%PG of the binary base fluid. Hybrid nanofluid in 30% of PG as binary base fluid results 16.2% higher dynamic viscosity compared to pure PG base fluid for a volume concentration of 2%. Zeta potential measurement results in the stability of spherical Al2O3‐CuO/ (50/50) EG/W hybrid nanofluid, and it may be considered as a heat transfer fluid.
In this research, heat transfer along with entropy of an unsteady non-Newtonian Casson nanofluid flow is studied. The fluid is positioned over a stretched flat surface moving non-uniformly. The nanofluid is analyzed for its flow and heat transport properties by subjecting it to a slippery surface, which is convectively heated. The governing mathematical equations describing the physical characteristics of Casson nanofluid flow as well as heat transfer models are abridged under boundary layer flow assumptions and Roseland approximations. Governing equations of flow problem are formulated in partial differential equations. A computative technique, Keller box accustomed to find the self-similar solution of equations that converted into ordinary differential equations (ODEs) by using proper transformations. Two different classes of nanofluids, copper-methanol (Cu-MeOH) and titanium-methanol (TiO 2 -MeOH) are considered for our analysis. Significant results of various parameters in flow, heat, skin friction, Nusselt number and entropy analysis are elaborate graphically. The remarkable finding of this work is that the Cu-MeOH nanofluid is better transfer source as compared to TiO 2 -MeOH nanofluid.
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