Výsledky vyhledávání - "Tayfun Uyanık"

Akademický článek

Prediction of Ship Main Particulars for Harbor Tugboats Using a Bayesian Network Model and Non-Linear Regression

Autor: Ömer Emre Karaçay, Çağlar Karatuğ, Tayfun Uyanık, Yasin Arslanoğlu, Abderezak Lashab

Publikováno v: Applied Sciences, Vol 14, Iss 7, p 2891 (2024)

Determining the key characteristics of a ship during the concept and preliminary design phases is a critical and intricate process. In this study, we propose an alternative to traditional empirical methods by introducing a model to estimate the main

Externí odkaz: https://doaj.org/article/f1d3e100ff7e4b38833fc538a11126e8

Zobrazit plný text záznamu

Akademický článek

A Data-Driven Approach for Generator Load Prediction in Shipboard Microgrid: The Chemical Tanker Case Study

Autor: Tayfun Uyanık, Nur Najihah Abu Bakar, Özcan Kalenderli, Yasin Arslanoğlu, Josep M. Guerrero, Abderezak Lashab

Publikováno v: Energies, Vol 16, Iss 13, p 5092 (2023)

Energy efficiency and operational safety practices on ships have gained more importance due to the rules set by the International Maritime Organization in recent years. While approximately 70% of the fuel consumed on a commercial ship is utilized for

Externí odkaz: https://doaj.org/article/e0e1e3f1a54540e48e4bb727a4642ac1

Zobrazit plný text záznamu

Plný text ve formátu HTML

Akademický článek

Data-Driven Approach for Estimating Power and Fuel Consumption of Ship: A Case of Container Vessel

Autor: Tayfun Uyanık, Yunus Yalman, Özcan Kalenderli, Yasin Arslanoğlu, Yacine Terriche, Chun-Lien Su, Josep M. Guerrero

Publikováno v: Mathematics, Vol 10, Iss 22, p 4167 (2022)

In recent years, shipborne emissions have become a growing environmental threat. The International Maritime Organization has implemented various rules and regulations to resolve this concern. The Ship Energy Efficiency Management Plan, Energy Efficie

Externí odkaz: https://doaj.org/article/a04070da9d8a426f8b17c80da17811a3

Zobrazit plný text záznamu

Plný text ve formátu HTML

Akademický článek

Prediction of Voltage Sag Relative Location with Data-Driven Algorithms in Distribution Grid

Autor: Yunus Yalman, Tayfun Uyanık, İbrahim Atlı, Adnan Tan, Kamil Çağatay Bayındır, Ömer Karal, Saeed Golestan, Josep M. Guerrero

Publikováno v: Energies, Vol 15, Iss 18, p 6641 (2022)

Power quality (PQ) problems, including voltage sag, flicker, and harmonics, are the main concerns for the grid operator. Among these disturbances, voltage sag, which affects the sensitive loads in the interconnected system, is a crucial problem in th

Externí odkaz: https://doaj.org/article/c05025b1755f45d596a478c366a68570

Zobrazit plný text záznamu

Plný text ve formátu HTML

Akademický článek

Implementation of Voltage Sag Relative Location and Fault Type Identification Algorithm Using Real-Time Distribution System Data

Autor: Yunus Yalman, Tayfun Uyanık, Adnan Tan, Kamil Çağatay Bayındır, Yacine Terriche, Chun-Lien Su, Josep M. Guerrero

Publikováno v: Mathematics, Vol 10, Iss 19, p 3537 (2022)

One of the common power quality (PQ) problems in transmission and distribution systems is the voltage sag that affects the sensitive loads. Losses and problems caused by the voltage sag in the power system can be reduced by correctly determining the

Externí odkaz: https://doaj.org/article/c6eb971343124a7e800219d8406f130a

Zobrazit plný text záznamu

Plný text ve formátu HTML

Akademický článek

Thermoelectric Generators as an Alternative Energy Source in Shipboard Microgrids

Autor: Tayfun Uyanık, Emir Ejder, Yasin Arslanoğlu, Yunus Yalman, Yacine Terriche, Chun-Lien Su, Josep M. Guerrero

Publikováno v: Energies, Vol 15, Iss 12, p 4248 (2022)

In recent years, the usage potential of alternative energy sources has been gaining importance to increase the efficiency of ships within the scope of the obligations brought by international maritime regulations. The possibility of using alternative

Externí odkaz: https://doaj.org/article/0b703a574e8d4423b32bc2e1182cf21d

Zobrazit plný text záznamu

Plný text ve formátu HTML

APPLICATION OF MACHINE LEARNING METHODS FOR PREDICTION OF SEAFARER SAFETY PERCEPTION

Autor: Birgul Arslanoglu, Gizem Elidolu, Tayfun Uyanık

Publikováno v: International Journal of Maritime Engineering. 164:269-282

Purpose - This study aims to predict seafarer safety perceptions and evaluate their feedbacks in order to understand the human factor on ship’s safety. Design/methodology/approach - A questionnaire survey has been conducted with 304 seafarers' part

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::3fa3517f90848b4ed73552f999b5a53b
https://doi.org/10.5750/ijme.v164ia3.725

Zobrazit plný text záznamu