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Contact Name
Marzuki Naibaho
Contact Email
vertexeditorial@gmail.com
Phone
+6281381251442
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vertexeditorial@gmail.com
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INDONESIA
Vertex
ISSN : 2089385X     EISSN : 28296761     DOI : https://doi.org/10.35335/Vertex
Articles published in Vertex include original scientific research results (top priority), new scientific review articles (non-priority), or comments or criticisms on scientific papers published by Vertex. The journal accepts manuscripts or articles in the field of engineering from various academics and researchers both nationally and internationally. The journal is published every June and December (2 times a year). Articles published in Vertex are those that have been reviewed by Peer-Reviewers. The decision to accept a scientific article in this journal is the right of the Board of Editors based on recommendations from the Peer-Reviewers. Since 2011, Vertex only accepts articles derived from original research (top priority), and new scientific review articles (non-priority).
Articles 5 Documents
Search results for , issue "Vol. 13 No. 1 (2023): December: Engineering" : 5 Documents clear
Enhancing Hydrogen Production Efficiency in Water Electrolysis through Polycarbonate Integration from CD-R Waste Matthews Romagnoli; Boiral Lymberopoulos Sevastya; Vanechka Valery
Vertex Vol. 13 No. 1 (2023): December: Engineering
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/7ds16z37

Abstract

This research explores the integration of polycarbonate derived from CD-R (Compact Disc-Recordable) waste into water electrolysis for hydrogen production, aiming to assess its catalytic potential and influence on electrolysis efficiency. The study investigates the effects of waste-derived polycarbonate on hydrogen evolution rates, electrolysis kinetics, and operational parameters. Experimental trials reveal a notable enhancement in hydrogen production rates with the incorporation of waste-derived polycarbonate, suggesting its potential catalytic influence within the electrolysis process. However, observed variations and nonlinear concentration-efficiency relationships underscore the complexities and challenges in achieving consistent performance. Limitations related to material dispersion and compatibility highlight critical areas requiring optimization for practical implementation. The findings offer insights into the nuances of waste-derived material integration in electrochemical systems, emphasizing the need for further research to address challenges and optimize the utilization of waste-derived materials in advancing clean energy technologies.
Advancing Fault Diagnosis in BLDC Motors: Surge Test-Based Diagnostic Equipment for Phase to Ground Faults Stephen Larigaduelle; Jeseph Patrick William
Vertex Vol. 13 No. 1 (2023): December: Engineering
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/p5j7yp39

Abstract

This research introduces a groundbreaking approach to fault diagnosis in Brushless DC (BLDC) motors through the design and validation of specialized diagnostic equipment utilizing surge tests for phase to ground faults. The study focuses on identifying, localizing, and classifying various fault types, including insulation breakdowns, erosion, penetration, and partial grounding within BLDC motors. The research methodology encompasses theoretical frameworks, experimental validations, and comparative analyses with existing diagnostic methods. Surge tests conducted on BLDC motors with induced faults revealed distinct fault signatures, providing precise fault localization and aiding in the establishment of diagnostic criteria and thresholds. The findings showcased the developed equipment's precision, reliability, and automated fault classification capabilities, surpassing the limitations of traditional diagnostic methods. Comparisons with conventional techniques highlighted the advantages of the developed approach, emphasizing its heightened sensitivity, objectivity, and potential for predictive maintenance strategies. The equipment's ability to offer quantifiable fault parameters and establish diagnostic thresholds presents a transformative potential for proactive maintenance, minimizing downtime, and enhancing operational efficiency in BLDC motor-driven systems. The research findings underline the significance of surge tests and specialized diagnostic equipment in revolutionizing fault diagnosis practices for BLDC motors. The implications extend to industry-wide adoption, offering a pathway for enhanced reliability, safety, and operational continuity in various industrial applications.
Analyzing the Impact of Occupational Safety Programs on Work Productivity Using Fault Tree Analysis Alex Christhoper; Dareen Dominic
Vertex Vol. 13 No. 1 (2023): December: Engineering
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/c10g3861

Abstract

This research delves into the intricate relationship between the implementation of an occupational safety program and its influence on work productivity within organizational settings. Employing fault tree analysis as a primary methodology, the study aims to scrutinize the efficacy of safety initiatives and delineate their direct correlation with productivity outcomes. Through a mixed-method approach integrating qualitative and quantitative analyses, the research examines the effectiveness of safety programs in mitigating workplace hazards and fostering a culture of safety. The fault tree analysis dissects causal factors, identifying critical pathways and root causes impacting work productivity. Findings reveal a symbiotic relationship between safety measures and productivity metrics. A well-executed safety program emerges as a catalyst for improved operational efficiency, employee engagement, and quality of work. The implications drawn from this study advocate for a paradigm shift, where safety initiatives are integrated strategically, nurturing an environment where safety and productivity coalesce seamlessly. This research contributes actionable insights for organizations to optimize safety measures, bolster productivity, and foster a culture where safety isn't just a priority but a fundamental value. Ultimately, the findings offer a compass guiding organizations towards a future where safety and productivity converge synergistically, shaping a landscape of sustained success and employee well-being.
Optimizing Anthurium Cultivation: Advancements in Greenhouse Design for Enhanced Plant Quality in Controlled Environments Albertus Bahri; Chairi Kamoga; Kinza Adiguna Pallawarukka
Vertex Vol. 13 No. 1 (2023): December: Engineering
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/sm80xp89

Abstract

Anthuriums, renowned for their captivating blooms and lush foliage, thrive in controlled environments. This research delves into the nuanced intricacies of greenhouse design, aiming to optimize growth conditions and enhance the quality of anthurium plants. Through meticulous experimentation and comparative analysis of various greenhouse configurations, the study explores the impact of structural elements, environmental variables, lighting strategies, and soil management on anthurium growth and flowering patterns. Distinct greenhouse structures, including glass, polycarbonate, and advanced plastics, were scrutinized for their effects on anthurium health and quality. Findings reveal the significance of elements such as insulation, humidity regulation, ventilation, and balanced lighting strategies in fostering superior plant vitality. Polycarbonate or advanced plastic structures emerged as optimal environments, ensuring stable conditions conducive to vibrant foliage, prolific blooms, and overall plant vigor. The research extends beyond plant quality, emphasizing economic viability and sustainability. While aesthetics traditionally favored glass structures, the evidence supporting energy efficiency and reduced maintenance costs of alternative materials underscores their practicality in commercial anthurium cultivation. These insights not only redefine greenhouse design paradigms but also serve as a guiding beacon for future research and industry practices. They pave the way for innovative approaches and sustainable cultivation methods, heralding a new era of precision and excellence in anthurium cultivation within controlled greenhouse environments.
Optimizing Wind Energy Generation: Wind Speed Forecasting Using Elman Recurrent Neural Networks for Enhanced Power Generation in Turbines Anthony Brandon; Richrad Xavier; Cley Valentine Ludwig
Vertex Vol. 13 No. 1 (2023): December: Engineering
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/zgnvvy88

Abstract

This research delves into the realm of wind energy by exploring the accuracy of wind speed forecasting using the Elman Recurrent Neural Network (RNN) and its direct influence on the power generation of wind turbines. Leveraging historical wind speed data and employing the Elman RNN, this study demonstrates the model's precision in forecasting wind speeds, capturing temporal dependencies, and elucidating their impact on electricity output. Correlating these forecasts with actual power generation records, the research establishes a profound relationship, showcasing how even minor variations in predicted wind speeds significantly influence the amount of electricity produced by wind turbines. The study's findings underscore the critical role of accurate wind speed predictions in optimizing wind farm operations, enhancing energy capture efficiency, and contributing to grid stability. Furthermore, the research sets the stage for practical applications in renewable energy planning and policy-making, offering insights that shape the future trajectory of wind energy utilization. The research concludes by proposing avenues for further refinement in predictive models, real-time integration strategies, and long-term forecasting, guiding the path towards a sustainable and resilient energy landscape.

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