Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Mechatronics, Electrical Power, and Vehicular Technology

Analyzing the growth and trends of vertical axis wind turbine research: Insight from a bibliometric study Elysa Nensy Irawan; Nuur Wachid Abdul Majid; Liptia Venica; Fahrur Aslami; Goro Fujita
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 14, No 1 (2023)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.mev.2023.v14.55-61

Abstract

Bibliometric analysis research has been done for vertical axis wind turbine (VAWT). This study aims to determine the growth of VAWT research, the number of VAWT studies in various countries and the most influential authors to find opportunities for research collaboration, and the challenges of future VAWT research. Research data was taken from Scopus in 1801 articles from 1970-2021. The software used for data interpretation was VosViewer 1.6.19 and Tableau Public 2022.2. Based on the analysis, VAWT research has tended to increase from 1970-2021, although there was a decrease from 1987-2006. The country that has conducted the most VAWT research is China, while the author with the highest number of citations is from Italy. The most dominant research topic related to VAWT research is computational fluid dynamics (CFD), which is 50.14 % of the total. A future challenge related to VAWT research is finding a suitable turbulence model for each type of VAWT or finding an airfoil optimization method so that a model with betterperformance is obtained. Opportunities for research collaboration can be carried out with China or an author with the highest number of citations who has expertise in the field of CFD.
An evaluation of stereo vision for distance estimation using the SGBM algorithm in the CARLA simulator Rizky Hamdani Sakti; Liptia Venica; Dewi Indriati Hadi Putri; Shinta Rohmatika Kosmaga; Estiko Rijanto
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 16, No 2 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2025.1284

Abstract

This paper presents an evaluation of stereo vision based on the semi-global block matching (SGBM) algorithm for distance estimation in an autonomous parking scenario using the CARLA simulator. Distance-disparity regression functions are explored to enhance distance estimation accuracy. The proposed distance estimation model was evaluated using the design science research methodology (DSRM) framework, with experimental validation conducted in CARLA’s promenade environment. The evaluation employed root mean square error (RMSE) and relative error metrics to assess performance. Experiments were performed within a range of 40-350 cm, which is relevant for autonomous parking applications. The experimental results show that the algorithm achieves an overall RMSE of 1.69 cm and an average relative error of 1.1 %. The findings contribute to the advancement of perception systems for autonomous vehicles, particularly in challenging environments.