Recent in Engineering Science and Technology

Measuring Thermal Conductivity and Magnetic Strength Using Low-Cost Sensors Based on an Open-Source Platform Arduino

Sat, 25 Apr 2026 00:00:00 +0000

The use of low-cost sensors controlled by open-source microcontrollers (Arduino, ESP32) is investigated in this study not only to measure electrical, thermal, and magnetic values but also to investigate intrinsic material properties such as thermal conductivity and magnetic strength. Four sensors are used in this study such as SS49E, MAX6675, ACS712, and HMC5883L. Their performance is evaluated in monitoring a carbon rod subjected to 29.9 V DC current and the measurement results are displayed on a 20x4 I2C LCD and stored in CSV format on an SD Card. The MAX6675 thermocouple sensor shows the most stable and reliable results for surface temperature measurement, which is supported by reference multimeter readings. However, the use of multiple sensors simultaneously reveals interference issues, indicating the need for electrical isolation or signal multiplexing in future designs. This study contributes to the advancement of affordable open-source instrumentation as a viable alternative to commercial measurement tools, emphasizing the shift from raw signal acquisition to meaningful property computation.

Applying Structural Reliability to Risk-Based Inspections of Underwater Crude Oil Pipelines

Muhammad Iqbal, Johny Wahyuadi Soedarsono, Gusti Verhan Pratama — Tue, 28 Apr 2026 00:00:00 +0000

This study investigates the application of structural reliability methods in risk-based inspections (RBIs) for subsea crude oil pipelines. Given the increasing reliance on submarine pipeline infrastructure in offshore oil and gas operations, maintaining its integrity is critical to operational safety and environmental protection. This study uses inspection data from smart pigging operations carried out in 2020 and 2024 on 28.7 km of 12-inch underwater pipes. Using API RP 581 (2020) and First-Order Second-Moment (FOSM) structural reliability theory, this study quantitatively assesses the probability of failure (PoF) and the consequence of failure (CoF). Results showed active internal corrosion, with pitting corrosion identified as the dominant degradation mechanism. Risk projections from 2024 to 2030 reveal unacceptable levels of risk in 2030 if mitigation strategies are not implemented. Based on the financial impact and business risk thresholds, a tailored inspection and maintenance strategy is proposed. These findings support the optimization of inspection intervals and highlight the importance of corrosion control measures such as routine pigging and inhibitor injections.

A Simple Insight into Convolutional Neural Network Research Using VOSviewer, Python, and Gen-AI

Thu, 30 Apr 2026 00:00:00 +0000

This study presents a bibliometric analysis of research trends in Convolutional Neural Networks (CNN) published in 2023. Using the Scopus database, metadata for 2,185 journal articles was extracted based on criteria including open access status, English language, and classification under Computer Science. The research employed a systematic methodology involving data extraction, preprocessing, and network visualization. VOSviewer was used to map co-authorship networks, keyword co-occurrence, and citation patterns, while Python supported advanced data processing, topic modeling, and trend analysis. Keyword analysis highlighted the prominence of terms such as "deep learning," "learning systems," "image classification," and "object detection," indicating the diverse and interdisciplinary applications of CNN technology. The co-authorship network revealed China, India, and the United States as key centers of international research collaboration, demonstrating global engagement in advancing CNN studies. Citation analysis showed a skewed distribution where most publications received between zero and two citations, though some articles garnered significantly higher attention, with citations reaching up to 57 within the same year of publication. This suggests that a few studies have rapidly influenced the field despite the overall low citation count typical of recent papers. By integrating quantitative bibliometric techniques with AI-assisted qualitative insights, this study offers a comprehensive overview of the dynamic and rapidly evolving landscape of CNN research in 2023, guiding future academic and practical endeavors.

Cost and Reliability Optimization of SME-Scale Knock-Down Biomass Pyrolyzers via Value Engineering and Fault Tree Analysis

Mohamad Ramadani Rudiatama, Muhammad Athala Zakwan, Fauzi Khair, Ahmad Maksum — Thu, 30 Apr 2026 00:00:00 +0000

Small and medium enterprises in rural Indonesia are central to local growth yet often lack efficient rice husk waste management, with open burning still prevalent. This study designs an accessible knock-down biomass pyrolyzer for rural and home-scale SMEs by integrating Value Engineering and Fault Tree Analysis. The method combines functional analysis, cost breakdown, targeted simulations, and risk mapping to prioritize high-leverage improvements. The selected design includes load-indicator washers, modular knock-down joints, high-efficiency insulation, and stiffener rings in the condenser. Results indicate a structural failure risk reduction of up to 30 percent, a thermal efficiency gain of 10 to 15 percent, and only a 5.5 percent increase in production cost. Fault Tree Analysis attributes 50 percent of failures to design, 33.3 percent to assembly, and 16.7 percent to materials, while simulations show markedly lower bulging deformation, enhancing operational reliability. The final configuration is robust, quick to assemble, and well suited to rural constraints, enabling safer and more productive valorization of rice husk. The integrated approach offers a practical pathway to strengthen SME competitiveness, improve equipment reliability, and advance circular economy practices in Indonesia.

Development of IoT-based Monitoring of the Lithium-Ion Battery Pack for a Two-Wheeled Vehicle Ecosystem

Sonki Prasetya, Muhammad Todaro, Hasvienda M Ridlwan — Thu, 30 Apr 2026 00:00:00 +0000

Electric bicycles with two wheels are increasingly popular as a convenient mode of short-distance transportation. To enhance mobility and promote the use of eco-friendly energy around campus areas, conventional bicycles can be transformed into electric ones using a conversion kit. The main challenge lies in creating a design that is easy to install (plug-and-play) and compatible with various bicycle models. Moreover, monitorized battery condition is an advantage to inform the user. A key advantage of this concept is the inclusion of a universal battery pack equipped with an IoT-based monitoring system. This study aims to design an IOT based battery pack conversion kit powered by a 576 Wh of LiFePO₄ lithium-ion battery type. Experiment results indicate that battery pack of 50 cm × 16 cm × 14 cm dimension with the total weight of 4.5 kg can perform as the energy storage for a converted two-wheeled electric vehicle. The test achieves the speed of 500rpm with 1A current.

Table of Content Vol 04 No 02 2026

Thu, 30 Apr 2026 00:00:00 +0000

Front Cover Vol 04 No 02 2026

Thu, 30 Apr 2026 00:00:00 +0000