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All Journal Syntax Literate: Jurnal Ilmiah Indonesia Eduvest - Journal of Universal Studies
Nababan, Nidia Pialina
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Aerospace Engineering Humanities Computer Science & IT Education Environmental Science Health Professions Law, Crime, Criminology & Criminal Justice Neuroscience Social Sciences Other

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New Design of A Micro-Hydro Power Plant (MHPP) System In The 3T Region As Al-ternative Solution Unit Turbine Using Computational Fluid Dynamics (CFD) Simulation Jarrar Pirzada, Syed; Kurniawan, Intan; Nababan, Nidia Pialina; Sahroni, ⁠Taufik Roni
Eduvest - Journal of Universal Studies Vol. 4 No. 5 (2024): Journal Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v4i5.1179

Abstract

This research aims to select the most suitable type of water turbine for the micro-hydro power plant (PLTMH) site in the Anggi District, Pegunungan Arfak Regency, West Papua Province. The study also aims to design the most optimal and effective turbine in terms of technical aspects and generator system reliability. This objective is directed towards providing recommendations for the development of the second unit of PLTMH Anggi in a more comprehensive manner rather than relying solely on expert recommendations without thorough analysis. The data used in this research was obtained from field surveys and secondary data sources. The initial step in selecting the turbine type involves manual turbine design calculations, taking into consideration parameters such as water flow, head height, and hydraulic efficiency. Based on these calculation results, the "Francis" turbine type was chosen as the preferred option, differing from the existing Propeller Tubular Type-S turbine installed in Unit 1. The selected turbine, "Francis," was then modeled using computational fluid dynamics (CFD) simulations with the Ansys Fluent software. These simulations provide computer-generated data on hydrodynamic characteristics, pressure distribution, and flow velocity around the turbine under various operational conditions. This research has significant implications for improving the efficiency and reliability of the micro-hydro power plant system for the optimal power and efficiency development of Unit 2.
Predictive Maintenance Using Linear Regression Prayogo, Rudy Hartono; Kurnianto, Benedict Ariel; Nababan, Nidia Pialina; Suharjito, Suharjito
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36418/syntax-literate.v9i3.15366

Abstract

Problems regarding machine damage often occur in many industries, especially the manufacturing industry, which causes large losses for companies. This is of course influenced by various factors such as engine temperatures that are too high, engine rotation that is too fast, poor engine torque values, and so on. This research aims to provide predictive analysis results regarding engine conditions that have the potential to experience damage. To achieve this goal, this research will carry out predictive maintenance analysis using a linear regression analysis approach in which two linear regression models will be carried out where the first model involves PCA preprocessing and the second model is carried out without PCA. This research will use the predictive maintenance dataset from the conference (Matzka, 2020). It is known that the MSE, RMSE, MAE, and R2 values of the two methods have the same values, namely 0.909, 0.953, 0.806, and 0.772 respectively. Based on this research, it is concluded that whether PCA is performed or not, it does not significantly affect the results of the regression analysis. This outcome can be attributed to the artificial nature of the dataset, rendering it ideal. Moreover, the retained PCA value of 98% is close to the number of attributes in the original dataset.
Co-Authors Intan Kurniawan, Intan Jarrar Pirzada, Syed Kurnianto, Benedict Ariel Prayogo, Rudy Hartono Sahroni, ⁠Taufik Roni Suharjito Suharjito, Suharjito