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JMES: The International Journal of Mechanical Engineering and Sciences Editorial Office Departemen Teknik Mesin, ITS Kampus ITS Sukolilo Surabaya 60111 Building C, Floor 2 Indonesia
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JMES: The International Journal of Mechanical Engineering and Sciences
Published by Institut Teknologi Sepuluh Nopember Surabaya
ISSN : -     EISSN : 25807471     DOI : https://dx.doi.org/10.12962/j25807471
Core Subject : Science, Engineering,
Energy Materials Science & Nanotechnology Mechanical Engineering
JMES publishes high-quality original research articles, review articles, and letters to the editor that advance mechanical engineering and related disciplines. The journal provides an international platform for researchers, academics, and industry practitioners to disseminate scientifically rigorous, innovative, and application-oriented research, bridging fundamental science with real-world engineering solutions. JMES welcomes high-quality original research and review articles covering theoretical, experimental, and numerical aspects in the following areas: Thermal and Fluid Engineering, including heat transfer, fluid flow, and energy conversion. Manufacturing and Mechanical Design, focusing on manufacturing processes, product development, and mechanical systems. Materials and Structural Engineering, covering engineering materials, structural performance, reliability, and failure analysis. Computational Engineering, emphasizing modeling, simulation, optimization, and data-driven engineering methods. Sustainable Energy Systems, addressing renewable energy, energy efficiency, energy storage, and low-carbon engineering technologies.
Arjuna Subject : Teknik (semua kategori) - Teknik Mesin
Articles 5 Documents
 1 
Search results for , issue "vol 5 no 2 (2021)" : 5 Documents clear
Determination of Injection Molding Process Parameters using Combination of Backpropagation Neural Network and Genetic Algorithm Optimization Method Arif Wahjudi; Thenny Daus Salamoni; I Made Londen Batan; Dinny Harnany
JMES: The International Journal of Mechanical Engineering and Sciences Vol 5 No 2 (2021)
Publisher : LPPM, Institut Teknologi Sepuluh Nopember, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25807471.v5i2.8592

Abstract

Comparative Study of Hydro-Magneto-Electric Regenerative Shock Absorber (HMERSA) with Two Outputs Hydraulic Generator Installed Series And Parallels Taufik Kurniawan; Harus Laksana Guntur
JMES: The International Journal of Mechanical Engineering and Sciences Vol 5 No 2 (2021)
Publisher : LPPM, Institut Teknologi Sepuluh Nopember, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25807471.v5i2.8934

Abstract

Through the Regenerative Shock Absorber (RSA) mechanism, wasted energy will be utilized into electrical energy. Hydro-Magneto-Electric Regenerative Shock Absorber (HMERSA) was designed and analyzed with 2 generator outputs installed in series and parallel. The twin-tube shock absorber was modified, so that fluid flow in the chamber is only unidirectional flow. It is passed to four check valves that keep the fluid flow in one direction and towards the 2 hydro-generators installed on the system in series and parallel positions. The hydro-generator converts the linear fluid flow into a rotational motion which causes the generator to rotate and generate energy. HMERSA was tested on minibus with speed bumps types of roads. In the bump test, the harvested energy were 8.2 Volts and 5.97 Volts for HMERSA with 2 generator outputs installed in series, and 5.169 Volts and 4.33 Volts for HMERSA with 2 parallel output generators. From the result, we can conclude that HMERSA with 2 generator outputs installed in series is better than HMERSA with 2 parallel output generators.
Design and Analysis of ECVT on Electric Powered Vehicles for Determining the Speed Ratio Himmawan Sabda Maulana; I Nyoman Sutantra
JMES: The International Journal of Mechanical Engineering and Sciences Vol 5 No 2 (2021)
Publisher : LPPM, Institut Teknologi Sepuluh Nopember, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25807471.v5i2.8923

Abstract

Electronics Continuous Variable Transmission (ECVT) is a smart transmission that has unlimited gear ratios. By analyzing vehicle conditions, ECVT can choose the most efficient gear ratio. ECVT mode requires a Planetary Gear Set (PGS) as a power splitter. This research will use PGS and double electric motor to combine the ECVT mode with electric vehicles to determine the desired speed ratio. The PGS was designed by an analytical model and simulated using CAD software. The simulation will provide several input variations to get the right speed ratio, such as speed variations and rotational direction. The analytical model obtained a PGS ratio of 1:6 with 19 sun gear teeth, 95 ring gear teeth, 38 planet gear teeth, and a motor power of 47 kW. Simulation results will be applied to build the prototype that will be made with a 3D printer. This study shows that ECVT can be a transmission system for electric vehicles with 2 to 5 levels of transmission, and using double electric motors with small power can replace an electric motor with large power. To obtain maximum efficiency, a good control strategy is needed. The control strategy will be discussed in further research.
Quasi-Static Cyclic Response of Unidirectional Thin-Ply Hybrid Composites Putu Suwarta; Gergely Czel; Mohamad Fotouhi; Marco L. Longana; Sutikno Sutikno; Michael R. Wisnom
JMES: The International Journal of Mechanical Engineering and Sciences Vol 5 No 2 (2021)
Publisher : LPPM, Institut Teknologi Sepuluh Nopember, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25807471.v5i2.8614

Abstract

Multi-objective Optimization Using Neural Network, Differential Evolution, and Teaching Learning Based Optimization in Drilling Process of Glass Fiber Reinforced Polymer Kirana Alif Fatika; Mohammad Khoirul Effendi
JMES: The International Journal of Mechanical Engineering and Sciences Vol 5 No 2 (2021)
Publisher : LPPM, Institut Teknologi Sepuluh Nopember, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25807471.v5i2.10382

Abstract

This experiment focused on the drilling process of Glass Fiber Reinforced Polymer (GFRP) composites. The data was obtained from an experiment carried out by Production Engineering Laboratory, Mechanical Engineering Department, Faculty of Industrial Technology and Systems Engineering, Institut Sepuluh Nopember Surabaya in 2019. The experiment was done with an artificial intelligence method called Backpropagation Neural Network (BPNN) as an approach to predict the response parameters (thrust force, torque, hole roundness, and hole surface roughness). The parameter inputs are drill point geometry, drill point angle, feed rate, and spindle speed. Hence the prediction would be used to gain the minimum input parameters by applying metaheuristic methods called Differential Evolution (DE) and Teaching Learning Based Optimization (TLBO). Then the result from both methods was compared to determine which method gained the better optimization values. Since BPNN-DE and BPNN-TLBO with type X drill point geometry was considerably better than type S drill point geometry, type X drill point geometry could be used to optimize the drilling process of GFRP.

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