This paper investigates the physical and mechanical properties of bighorns of Deccani breed sheep native from Karnataka, India. The exhaustive work comprises two cases. First, rehydrated (wet) and ambient (dry) conditions, and second, the horn coupons were selected for longitudinal and lateral (transverse) directions. More than seventy-two samples were subjected to a test for physical and mechanical property extraction. Further, twenty-four samples were subjected to physical property testing, which included density and moisture absorption tests. At the same time, mechanical testing included analysis of the stress state dependence with the horn keratin tested under tension, compression, and flexural loading. The mechanical properties include the elastic modulus, yield strength, ultimate strength, failure strain, compressive strength, flexural strength, flexural modulus, and hardness. The results showed anisotropy and depended highly on the presence of water content more than coupon orientation. Wet conditioned specimens had a significant loss in mechanical properties compared with dry specimens. The observed outcomes were shown at par with results for yield strength of 53.5 ± 6.5 MPa (which is better than its peers) and a maximum compressive stress of 557.7 ± 5 MPa (highest among peers). Young’s modulus 6.5 ± 0.5 GPa and a density equivalent to a biopolymer of 1.2 g/cc are expected to be the lightest among its peers; flexural strength 168.75 MPa, with lowest failure strain percentage of 6.5 ± 0.5 and Rockwell hardness value of 60 HRB, seem best in the class of this category. Simulation study identified a suitable application area based on impact and fatigue analysis. Overall, the exhaustive experimental work provided many opportunities to use this new material in various diversified applications in the future.

Investigation of Mechanical and Physical Properties of Big Sheep Horn as an Alternative Biomaterial for Structural Applications

Genetic algorithm is widely used in multi-objective mechanical structure optimization. In this paper, a genetic algorithm-based optimization method for ladle refractory lining structure is proposed. First, the parametric finite element model of the new ladle refractory lining is established by using ANSYS Workbench software. The refractory lining is mainly composed of insulating layer, permanent layer and working layer. Secondly, a mathematical model for multi-objective optimization is established to reveal the functional relationship between the maximum equivalent force on the ladle lining, the maximum temperature on the ladle shell, the total mass of the ladle and the structural parameters of the ladle refractory lining. Genetic algorithm translates the optimization process of ladle refractory lining into natural evolution and selection. The optimization results show that, compared with the unoptimized ladle refractory lining structure (insulation layer thickness of 0 mm, permanent layer thickness of 81 mm, and working layer thickness of 152 mm), the refractory lining with insulation layer thickness of 8.02 mm, permanent layer thickness of 76.20 mm, and working layer thickness of 148.61 mm has the best thermal insulation performance and longer service life within the variation of ladle refractory lining structure parameters. Finally, the results of the optimization are verified and analyzed in this paper. The study found that by optimizing the design of the ladle refractory lining, the maximum equivalent force on the ladle lining, the maximum temperature on the ladle shell and the ladle mass were reduced. The thermal insulation performance and the lightweight performance of the ladle are improved, which is very important for improving the service life of the ladle.

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Multi-Objective Optimization Design of Ladle Refractory Lining Based on Genetic Algorithm

Since today, most of the manufacturing companies have the operated CAD model, so CAD-based object autonomous bin picking which using 6DOF Manipulator may be a good option that can save time and increases productivity for an assembly line. This research aims to present an effectively autonomous method that can increases productivity as well as respond quickly of changing items based on customer demand for an assembly line which using 6DOF Manipulator by combining CAD data and computer vision system. Firstly, The 3D CAD model of grasped object is projected onto six different 2D planes, then combining six views to form the final pointcloud. Secondly, a voting scheme is used to estimated the 3D pose of object which is obtained by a 3D camera. For tuning a precision of an estimation such as surface normal, angle and location of an object, Iterative closest point (ICP) algorithm is applied. Before doing experiments, the recognition algorithm is verified through the simulation program. Through implement experiments, the system proved that it is stable, good precision and applicable in production line where mass product is produced. Moreover, the developed system allows non-expert users with basic knowledge about CAD drawing and image processing can generate a pose of an object from CAD model and transmit data to a manipulator for the bin picking task.

3D matching by combining CAD model and computer vision for autonomous bin picking

In today’s world, efficiency and margin of safety are prime considerations for any applications. To address such parameters in aerospace or high-tech consumer products, there are still limitations in terms of capabilities from a material perspective. Aluminium 7075 is predominantly used as a combination material in these applications, but it has many drawbacks such as early wear/friction, low fatigue life cycle, high weight ratios, high deformation and stresses. To overcome these key issues, many reinforcements have been used to date. However, the results are not so convincing with respect to tribological applications, and the aforementioned issues still persist. In the current work, a novel hybrid composite comprising Aluminium 7075 as substrate and the reinforcement of silicon carbide and aluminium oxide at varying combinations of 3 to 9% in steps of 3% and a constant percentage of 5% were added, respectively. The exhaustive work focuses on extracting the mechanical, tribological and physical properties of a hybrid composite. Furthermore, a microcharacterisation study of these combinations was carried out using FE-SEM and EDX. In a continuation to this simulation, a study was performed using ANSYS Workbench to identify a suitable gear application with real-time loading conditions. The observed results show a tensile strength of 366 MPa for 6%SiC, hardness of 93 VHN and wear rate of 0.00025 mm3/Nm for the 9%SiC combination.

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A Tribological Study on the Effect of Reinforcing SiC and Al2O3 in Al7075: Applications for Spur Gears

Pressure exertion and heat dissipation analysis on uncoated and ceramic (Al2O3, TiO2 and ZrO2) coated braking pads

This study discusses the acoustic property variations by introducing new absorption materials. An experimental set up established to simulate virtually as well as experimentally with various biodegradable, biocompatible and naturally absorbable materials for a truck cabin of carrier capacity 3.5Tonnes. The materials were embedded on the sidewall and base of the cabin covering the entire cabin not leaving any air pockets. Experimental and simulation study was carried out for six materials and in the later part a combination of these materials also carried out to see through the possible optimal cases providing due Weightage to cost and weight. A sound quality index study being made to see with each case of material how the sound pressure level affects the rider and the subordinates seating in a cabin. A detailed simulation study carried out to understand the material behavioral characteristics along with convergence study using ANSYS Workbench. The exhaustive work emphasis on percentage error study with simulation and experimental work and proposes an optimal material from sound pressure level and rider comfort aspects.

Vishalagoud S. Patil

Papers

A study of sound pressure level (SPL) inside the truck cabin for new acoustic materials: An experimental and FEA approach

Non-Linear structural and thermal analysis of automotive brake disc