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All Journal Majalah Ilmiah Pengkajian Industri Automotive Experiences
Shalahuddin, Lukman
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Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Transportation

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PROPULSION SYSTEM DESIGN FOR THE INDONESIAN SEMI HIGH SPEED TRAIN Shalahuddin, Lukman; Putranto, Kartiko E.; Eskayudha, Dimas B.
Majalah Ilmiah Pengkajian Industri Vol 13, No 3 (2019): Majalah Ilmiah Pengkajian Industri
Publisher : BPPT

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (420.569 KB) | DOI: 10.29122/mipi.v13i3.3851

Abstract

This paper describes a study on the development of methodology to select the most appropriate technology, and the most optimum design and configuration for the propulsion system of the semi-high speed intercity train that will be operated on the Jakarta-Surabaya corridor. It also describes the method to calculate resistance loads  and tractive forces and hence the power required to propel the train along the specified route within targeted time. Among the output of this study is a recommendation for the most optimum propulsion system with basic/ main parameters for main components such as diesel engine, traction motor and the possibility of Diesel Electric Multiple Unit (DEMU) Hybrid battery system.
PREDICTION OF INTERNAL COMBUSTION ENGINE PERFORMANCE USING ARTIFICIAL INTELLIGENCE Shalahuddin, Lukman; Suksmono, Adityo; Sembiring, Yohanes P
Majalah Ilmiah Pengkajian Industri Vol. 14 No. 2 (2020): Majalah Ilmiah Pengkajian Industri
Publisher : Deputi TIRBR-BPPT

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29122/mipi.v14i2.4164

Abstract

The potential of artificial intelligence (AI) application for prediction of internal combustion engine performance is assessed in this paper. A literature survey on this subject is first reviewed, in which previous researches utilized the advance of artificial neural networks (ANN) as one type of AI. Previous works commonly obtained the data from experimental engine tests. Under the same engines, they varied the fuel compositions or the engine operating conditions. Whereas in this study, an ANN model is developed to calculate the inputs from an engine simulation software package database and to predict the engine performance based on the simulation software outputs as the ANN target outputs. Results from the ANN model in the “learning” step indicates good agreement with the software simulation outputs. Improvement and development of the program are required, including optimation of the ANN model architecture, such as the choice of activation function, the number of neurons in the hidden layer, and the number of iterations, as well as the number and option of input engine parameters. The ANN model seems promising to predict engine performance, with root mean square errors in the range of 0.4-1.8%. Keywords: Artificial Intelligence; Neural Networks; Engine Performance.
Development of an Automatic Coupler for Railway Vehicles: A Topology Optimization Approach with Numerical and Experimental Validation Valentino, Jean Mario; Pramono, Agus Sigit; Syaifudin, Achmad; Shalahuddin, Lukman; Perkasa, Mustasyar; Sasaki, Katsuhiko
Automotive Experiences Vol 7 No 3 (2024)
Publisher : Automotive Laboratory of Universitas Muhammadiyah Magelang in collaboration with Association of Indonesian Vocational Educators (AIVE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/ae.11494

Abstract

Topology optimization has demonstrated its effectiveness in generating lightweight and structurally efficient designs. This study focuses on refining the geometry of an automatic coupler body for trains using solid isotropic material with penalization and a level set method. These optimization methods are applied to the numerical model of the automatic coupler, and their results are compared to select the optimal design. The tensile strength of the automatic coupler is examined through numerical simulations and validated by experimental tensile tests conducted on a 1:1 scale prototype. The optimization outcomes reveal a remarkable 46.41% reduction in the mass of the automatic coupler body compared to the initial model. An evaluation of the tensile strength of the prototype demonstrates the ability of the automatic coupler to withstand the primary load without undergoing plastic deformation. Furthermore, a strong correlation is observed between the numerical and experimental results. This research contributes to advancing the design of next-generation automatic couplers, emphasizing the crucial aspects of lightweight design and structural performance.
Co-Authors Achmad Syaifudin Adityo Suksmono, Adityo Agus Sigit Pramono Eskayudha, Dimas B. Jean Mario Valentino, Jean Mario Perkasa, Mustasyar Putranto, Kartiko E. Sasaki, Katsuhiko Sembiring, Yohanes P