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All Journal International Journal of Innovation in Mechanical Engineering and Advanced Materials
Sri Pudjiwati
Universitas Mercu Buana
Automotive Engineering Energy Engineering Materials Science & Nanotechnology Mechanical Engineering

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Heat Distribution Simulation in a Square Aluminum 7075 Plate Using Laplace Equation and MATLAB Sri Pudjiwati; Andi Firdaus Sudarma; Kontan Tarigan; Deni Shidqi Khaerudini; Eldwin Djajadiwinata
International Journal of Innovation in Mechanical Engineering and Advanced Materials Vol. 6 No. 2 (2024)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/ijimeam.v6i2.25356

Abstract

The efficient management of heat transfer from aircraft engines to the wings is vital for maintaining thermal efficiency and structural integrity in modern aircraft design. Excessive heating of the wings, caused by engine-generated heat, can negatively impact aerodynamic performance and safety. This study focuses on analyzing heat distribution in a square aluminum 7075 plate to better understand heat transfer mechanisms. Using the Laplace equation, implemented through MATLAB (2023 Online Version), we aim to simulate and analyze heat distribution on the plate. The numerical method employed in this research involves solving the Laplace equation with Neumann boundary conditions, which represent insulated edges. The Liebmann method is used to iteratively reduce error to less than 1%. Simulations are conducted on an aluminum 7075 plate of dimensions 4x10⁻² m x 4x10⁻² m under various temperature conditions at the edges. Numerical results show that at the 9th iteration, the error reaches 0.71%, while MATLAB simulations yield an error of 0.4681% at the same iteration. The heat distribution across the plate is clearly visualized, and the analysis indicates that increasing the number of grids improves both the clarity and accuracy of the simulation results. In conclusion, this study demonstrates that applying the Laplace equation via MATLAB is an effective approach for analyzing heat distribution in aluminum 7075 plates. The results show that a finer grid resolution enhances accuracy, with a 101-grid system providing particularly clear and precise heat distribution patterns. These findings contribute to the optimization of thermal system designs, especially in aviation-related applications.
Correlation Analysis of Battery Capacity, Range, and Charging Time in Electric Vehicles Using Pearson Correlation and MATLAB Regression Yasa Sanusi; Sri Pudjiwati; Kontan Tarigan; Dianta Ginting; Farrah Anis Fazliatun Adnan; Gerald Ensang Timuda; Nono Darsono; Nuwong Chollacoop; Deni Shidqi Khaerudini
International Journal of Innovation in Mechanical Engineering and Advanced Materials Vol. 7 No. 3 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/ijimeam.v7i3.31800

Abstract

The increasing adoption of electric vehicles (EVs) reflects growing global awareness of climate change and air pollution challenges. As a sustainable alternative to conventional internal combustion vehicles, EVs produce zero tailpipe emissions and can significantly reduce carbon emissions—particularly when powered by renewable energy sources. However, one of the primary barriers to widespread EV adoption remains the high cost of battery components, which are essential to vehicle performance and energy storage. In Indonesia, two dominant battery types used in EVs are Lithium Ferro Phosphate (LFP) and Nickel Manganese Cobalt (NMC), each offering distinct advantages. LFP batteries are recognized for their thermal stability and longer life cycles, making them suitable for everyday use, while NMC batteries offer higher energy density and are preferred for performance-focused and long-distance applications. This study aims to evaluate the correlation between battery capacity, driving range, and charging time for LFP and NMC batteries using Pearson correlation and regression analysis through MATLAB simulation. The results indicate a strong and statistically significant correlation among the key parameters, with a Pearson coefficient of 0.576 for battery capacity and range, and an R-square value of 0.99 for the regression model, demonstrating high predictive accuracy. Furthermore, the analysis reveals that LFP batteries have a higher average energy efficiency of 7.53 km/kWh compared to 6.84 km/kWh for NMC batteries, indicating more consistent performance in energy usage. These findings offer valuable insights for optimizing battery selection in EV applications and contribute to strategic planning for the development of more efficient electric vehicle systems. The combination of statistical and simulation-based analysis provides a robust foundation for future research and policy-making in the field of electric mobility.
Co-Authors Andi Firdaus Sudarma Deni Shidqi Khaerudini Dianta Ginting Eldwin Djajadiwinata Farrah Anis Fazliatun Adnan Gerald Ensang Timuda Kontan Tarigan Nono Darsono Nuwong Chollacoop Yasa Sanusi