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All Journal Journal of Mechanical Engineering Science and Technology Buletin Ilmiah Sarjana Teknik Elektro Journal of Mechanical Engineering, Science, and Innovation
Muhdi, Krisna Dwipa
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Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering

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Heuristic Approach to Comparing the Environmental Impacts of Carbon Nanotube Production Methods Fikri, Ahmad Atif; Fadlika, Irham; Saeful, Albarrobi Nabila; Muhdi, Krisna Dwipa; Pratama, Daniel Febrian; Bello, Nasir Garba
Journal of Mechanical Engineering Science and Technology (JMEST) Vol 8, No 1 (2024)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um016v8i12024p199

Abstract

Carbon Nanotubes (CNTs) production so far has its own advantages and disadvantages. Some methods that can be used in producing CNTs are chemical vapor deposition (CVD), laser ablation, and arc discharge. The three methods have their own requirements, this causes different environmental impacts on each method. Studies into the environmental impact of the CNTs production process found that during thermal pretreatment of the reactant gas, more than 45 by-products were formed, including methane, volatile organic compounds, and polycyclic aromatic hydrocarbons. Calculating the environmental impact of CNTs production method often has challenges in implementation, because each production process has different systems and needs. One way to overcome this problem is by using the heuristic method for forecasting environmental impact, which can be done with the Multi-Criteria Decision Analysis algorithm. The method can calculate uncertainty in each scenario, by normalizing the given load value. In this study, the CVD method has the best solution and objective value results compared to laser ablation and arc discharge. The best solution and objective values that show the value of scenario quality and environmental impact in each method, in CVD the solution obtained in the 34th generation has an epsilon value of 0.00251. The generation shows the performance of the scenario, while the epsilon value shows the value of the environmental impact, the smaller the generation, the better the scenario, while the smaller the epsilon value, the smaller the environmental impact.
Quantum Mechanics Approach for Metal-Organic Frameworks Deformation Effect on Carbon Capture Performance: A Density Functional Theory Study Muhdi, Krisna Dwipa; Fikri, Ahmad Atif
Journal of Mechanical Engineering, Science, and Innovation Vol 5, No 1 (2025): (April)
Publisher : Mechanical Engineering Department - Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.jmesi.2025.v5i1.7415

Abstract

Increasing carbon dioxide (CO₂) emissions from fossil fuel combustion demand the development of effective and efficient carbon capture technologies. Metal-Organic Frameworks (MOFs) are excellent candidates as adsorbent materials because they have uniform pores, specific surface area, and can modified according to purpose. However, performance of MOFs may decrease due to structural deformation during  adsorption-desorption process, especially under extreme conditions. This study uses a quantum mechanical approach, namely Density Functional Theory (DFT), to analyze effect of deformation, specifically hMOF-13, on its performance in CO₂ adsorption. Through modeling the atomic structure of hMOF-13, an understanding of the quantum interactions between atoms, changes in position of atoms and cells due to deformation is obtained. Simulation results show that mechanical deformation of hMOF-13 decreases CO₂ adsorption performance through pore narrowing and electrostatic charge redistribution. In addition, excessive deformation can trigger structural failures that reduce regeneration cycles and lower carbon capture efficiency. Insights from this study can guide the subsequent development of MOFs with enhanced mechanical resistance, contributing to the optimization of industrial-scale carbon capture processes. By improving the structural stability of MOFs, industries can achieve higher adsorption efficiency, longer material life, and reduced operational costs, making carbon capture technology more feasible and sustainable.
Sensor Fusion of Laser and Inertial Units with Kalman-KMeans-Fuzzy Framework for Real-Time Railway Geometry Monitoring Fikri, Ahmad Atif; Subhan, Muhammad Ferindin Nuha; Suryanto, Heru; Muhdi, Krisna Dwipa; Pratama, Daniel Febrian; Iqbal, Ahmad
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 3 (2025): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i3.13780

Abstract

Maintaining railway track geometry integrity is essential to ensuring transportation safety and predictive maintenance. Conventional manual inspection methods are limited by low sampling frequency, subjective interpretation, and delayed anomaly detection. This study introduces a real-time, embedded monitoring system using VL53L0X infrared laser sensors and an MPU6050 IMU to measure gauge, cross-level height, and inclination. Sensors are mounted on a lightweight aluminum trolley and sampled every 0.5 seconds using an Arduino-based platform. A Kalman Filter reduces measurement noise, with tuned covariance matrices based on field calibration. Filtered outputs are clustered via K-Means (K = 2), validated by the Elbow Method and Silhouette Score (>0.6). Maintenance categories are assigned through a fuzzy logic system, with a ±1 mm sensitivity analysis confirming >85% decision stability. Field results demonstrate a measurement noise, achieving RMSE and MAE values of 0.8165 mm and 0.3175 mm for gauge and height, and 0.3086° and 0.0952° for inclination, respectively and a SNR gain from 0.5 dB to 21.7 dB. The low-cost, modular setup supports scalable, condition-based maintenance and demonstrates robustness in noisy environments. This approach offers a practical foundation for future integration with predictive analytics and digital twin technologies in smart rail infrastructure.
Co-Authors Ahmad Atif Fikri Bello, Nasir Garba Heru Suryanto Iqbal, Ahmad Irham Fadlika Pratama, Daniel Febrian Saeful, Albarrobi Nabila Subhan, Muhammad Ferindin Nuha