Due to its numerous properties, iron is one of the most useful materials on the planet. The mechanical and physical properties of iron and its alloys are suitable and manageable. These alloys have significant issues l...
Due to its numerous properties, iron is one of the most useful materials on the planet. The mechanical and physical properties of iron and its alloys are suitable and manageable. These alloys have significant issues like heavyweight, low corrosion resistivity and some other limitations. The researchers and companies for solving problems look out for other alternative materials. Titanium and its alloys, according to the researchers, have a huge variety of engineering applications. Titanium and titanium alloys have high strength and corrosion resistance, and they perform well at high temperatures up to nearly 600 °C. Titanium and its alloys have a density of about 60 % that of steel and its alloys, and about 50 % that of nickel alloys. Even though titanium and its alloys have cost and supply problems, they're utilized in numerous industries, which includes aerospace, automotive, and navy projects. Titanium and its alloys have unique properties, indicating that they are cost-effective components that require special manufacturing techniques. This study aims to explore the potential of titanium and its alloys to replace iron in various engineering applications. Addressing the critical need for materials with superior performance characteristics is essential for advancing technological development.
The mechatronic device has been designed and implemented based on the comprehensive rehabilitation of the paretic upper limb. This system has been prepared for an individual approach to the recovery process including ...
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This article describes the device which provides comfort and safety for the elderly and disabled people. The system can be installed in any room, particularly in a flat or a house. The device is dedicated for the elde...
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Magnetorheological elastomers (MRE) have gained popularity due to their ability to control viscoelastic properties by varying the strength of the magnetic field. Due to the obvious nonlinear and complex behavior of MR...
Magnetorheological elastomers (MRE) have gained popularity due to their ability to control viscoelastic properties by varying the strength of the magnetic field. Due to the obvious nonlinear and complex behavior of MRE, machine learning approaches were used to predict the MRE viscoelastic properties, which are storage and loss modulus. In comparison to the traditional viscoelastic model, which is complex in mathematical derivation, machine learning method easily identifies trends and patterns by mapping the input-output relationship. It can also handle nonlinear problems by training on data. Support vector regression (SVR), Gaussian process regression (GPR), Backpropagation neural network (BP-ANN), and Extreme learning machine (ELM) were introduced and compared to simulate the field-dependent viscoelastic behavior of MRE with frequency and magnetic field strength as model input. As a result, the ELM model produced the highest accuracy, with more than 98 percent accuracy on model generalization capability. Therefore, this demonstrates that machine learning can replace traditional modelling approaches and serve as a basis for material and device development.
The copper-tin alloy in the Heat Exchanger system plays an important role in maintaining physical properties due to direct contact with the working fluid. In addition to having a melting point of up to 10830C and a bo...
The copper-tin alloy in the Heat Exchanger system plays an important role in maintaining physical properties due to direct contact with the working fluid. In addition to having a melting point of up to 10830C and a boiling point of up to 23100C, Tin alloy copper is also a group IB transition metal having properties that are resistant to corrosive. The heat exchanger here is a heat exchanger in an ocean thermal energy conversion (OTEC) power plant where fluid use ammonia and seawater as the working medium. As a result of the long-term effect of a working fluid, ammonia and seawater can cause erosion of the copper-tin alloy (Cu-Sn) material. The focus of this research discussion is on the shell and tube model of heat exchanger material. The heat exchanger material used is a copper-tin alloy. To determine the mechanical characteristics of the heat exchanger material, the material was tested using a furnace test, microstructure test and hardness test. Heating room temperature in the furnace machine on 4 test samples set at 500°C, 600°C, 700°C and the ambient temperature is 25°C. The test samples were surface polished on a polisher machine using sandpaper 400, 600, 800, 1000, 1200, 1500 and 2000. Furthermore, microstructural metallographic testing was carried out on 4 test samples with 200x, 500x and 800x magnifications with the test samples previously immersed in chemical Nitric Acid 69.0%-70.0% and alcohol. The Brinell hardness test with a load of 500 kg and a steel ball diameter of 5 mm was carried out on 4 test samples, A, B, C and D. In test sample A the ambient temperature were 25°C by pressing the steel ball 5 mm at three pressure points with a distance of 15 mm each, against a force load of 500 kg over a period of 15 seconds resulted in an average hardness value of 50.05 BHN. The B test sample with a temperature of 500°C produced an average hardness value of 56.37 BHN. The C test sample with a temperature of 600°C produced an average hardness value of 50.25 BHN.
Low values of critical-current-densities are a significant shortcoming in the performance of Li6.25La3Zr2A10.25O12, a ceramic electrolyte. X-ray Computed Tomography (CT) images obtained from pristine and "exhaust...
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This article was published online on 2 December 2022 with errors throughout the paper. All the derivative terms had the wrong denominator; the denominators were
This article was published online on 2 December 2022 with errors throughout the paper. All the derivative terms had the wrong denominator; the denominators were
The design and numerical analysis of a 3D open-circuit, low-speed, with a maximum velocity of 20 m/s in the test section, wind tunnel is presented. Two diffusers' angels are numerically tested in order to reduce t...
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We present DeepClaw as a reconfigurable benchmark of robotic hardware and task hierarchy for robot learning. The DeepClaw benchmark aims at a mechatronics perspective of the robot learning problem, which features a mi...
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ISBN:
(数字)9781728167947
ISBN:
(纸本)9781728167954
We present DeepClaw as a reconfigurable benchmark of robotic hardware and task hierarchy for robot learning. The DeepClaw benchmark aims at a mechatronics perspective of the robot learning problem, which features a minimum design of robot cell that can be easily reconfigured to host robot hardware from various vendors, including manipulators, grippers, cameras, desks, and objects, aiming at a streamlined collection of physical manipulation data and evaluation of the learned skills for hardware benchmarking. We provide a detailed design of the robot cell with readily available parts to build the experiment environment that can host a wide range of robotic hardware commonly adopted for robot learning. We propose a hierarchical pipeline of software integration, including localization, recognition, grasp planning, and motion planning, to streamline learning-based robot control, data collection, and experiment validation towards shareability and reproducibility. We present benchmarking results of the DeepClaw system for a baseline Tic-Tac-Toe task, a bin-clearing task, and a jigsaw puzzle task using three sets of standard robotic hardware. Our results show that tasks defined in DeepClaw can be easily reproduced on three robot cells. Under the same task setup, the differences in robotic hardware used will present a non-negligible impact on the performance metrics of robot learning. All design layouts and codes are hosted on Github for open access (https://***/bionicdl-sustech/DeepClaw).
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