4 research outputs found
Finite Element Modelling and Validation of Thermomechanical Behaviour for Layered Aluminium Parts Made by Composite Metal Foil Manufacturing
The paper presents finite element modelling and thermomechanical analysis on the tensile properties of layered aluminium 1050 metal foil parts made by composite metal foil manufacturing. In this paper, a three-dimensional finite element model was developed and validated through experiments to analyse thermal effects on the tensile properties of 200-μm-thick aluminium 1050 metal foils. The effects of thermal stress and strain were studied by carrying out transient thermal analysis on the heated plates used to join the 200-μm-thick metal foils together using a special brazing paste. A standard tensile test at ambient temperature was carried out on the resulting layered dog bone specimens to analyse the thermal effects on the individual layers of metal. The investigations were precisely designed to assess the effect of heat provided amid the brazing operation to join the metal thwarts together as a layered structure and whether it assumed a part in affecting the tensile properties of the final products when contrasted to a solid aluminium 1050 dog bone specimen of the same dimensions. Corrosion testing was also carried out on dog bone specimens made from varying thickness foils (50 μm, 100 μm, and 200 μm) of aluminium 1050 to assess the effect of corrosion on the tensile strength and elongation. The results showed that the specimens did not face the problem of galvanic corrosion of the foil–bond interface. Microstructural analysis was also carried out to analyse the fracture modes of the tested specimens after corrosion testing
Finite Element Modeling and Mechanical Testing of Metal Composites Made by Composite Metal Foil Manufacturing
Foils of aluminum 1050 H14 ½ hard temper and 99.9% copper with 500-micron thickness have been used to manufacture similar and dissimilar composites by composite metal foil manufacturing (CMFM). The metal foils are bonded to each other using a special 80% zinc and 20% aluminum by weight brazing paste. A 3D finite element model has been developed to numerically analyze the time required to heat the metal foils so that a strong bond can be developed by the paste. The numerical simulations run in ANSYS 19.1 have been validated through experiments and rectangular layered composite products have been developed for flexural testing. The flexural test results for layered Al and Al/Cu composites are compared with solid samples of Al 1050 and 99.9% pure copper made by subtractive method. The results show that the layered Al composite is 5.2% stronger whereas the Al/Cu sample is 11.5% stronger in resisting bending loads compared to a solid Al 1050 sample. A higher bend load indicates the presence of a strong intermetallic bond created by the brazing paste between the metal foils. Corrosion testing was also carried out on the composite samples to assess the effect of corrosion on flexural strength. The tests revealed that the composites made by CMFM are not affected by galvanic corrosion after 7 days of testing and the flexural loads remained consistent with composites that were not immersed in a solution of distilled water and NaCl
The Deep Convolutional Neural Network Role in the Autonomous Navigation of Mobile Robots (SROBO)
The ability to navigate unstructured environments is an essential task for intelligent systems. Autonomous navigation by ground vehicles requires developing an internal representation of space, trained by recognizable landmarks, robust visual processing, computer vision and image
processing. A mobile robot needs a platform enabling it to operate in an environment autonomously, recognize the objects, and avoid obstacles in its path. In this study, an open-source ground robot called SROBO was designed to accurately identify its position and navigate certain areas using a deep convolutional neural network and transfer learning. The framework uses an RGB-D MYNTEYE camera, a 2D laser scanner and inertial measurement units (IMU) operating through an embedded system capable of deep learning. The real-time decision-making process and experiments were conducted while the onboard signal processing and image capturing system enabled continuous information analysis. State-of-the-art Real-Time Graph-Based SLAM (RTAB-Map) was adopted to create a map of indoor environments while benefiting from deep convolutional neural network
(Deep-CNN) capability. Enforcing Deep-CNN improved the performance quality of the RTAB-Map SLAM. The proposed setting equipped the robot with more insight into its surroundings. The robustness of the SROBO increased by 35% using the proposed system compared to the conventional
RTAB-Map SLAM
Hybrid Manufacturing and Mechanical Characterization of Cu/PLA Composites
Fused Deposition Modelling (FDM) is a widely used additive manufacturing process. It utilizes a variety of homogeneous and heterogeneous materials for product development. A new manufacturing process termed as Hybrid Fused Deposition Modelling (HFDM) has been used for the manufacture of various copper metal mesh (99.99% pure)/PLA (polylactic acid or polylactide) plastic composites. These products have been subjected to standardized experimental testing for evaluating properties such as tear resistance, tensile strength, water absorption, hardness, and flexural strength. The tests have been conducted to analyse the effectiveness of the HFDM process in manufacturing stronger composites compared to commercially available PLA and copper-infused PLA. Microstructural characterization has also been carried out to analyse the bond between the plastic and metal mesh layers. The results have been promising and demonstrate the effectiveness of HFDM to produce Cu/PLA composites with superior mechanical properties compared to parent FDM-printed PLA plastic as well as copper-infused FDM-printed PLA. Multiple copper mesh layers have been placed strategically within the test specimens to study their effect on the composites made by HFDM. The experimental results show that the process is capable of manufacturing high-quality composites (Cu/PLA) with tailored properties for various engineering applications