Optimization of operational parameters of pneumatic system for ballast tank sediment reduction with experimental and ANN applications

Ceren Bilgin Güney

doi:10.1016/j.oceaneng.2022.111927

Optimization of operational parameters of pneumatic system for ballast tank sediment reduction with experimental and ANN applications

Ceren Bilgin Güney

Department of Shipbuilding and Ocean Engineering

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

Abstract

The studies show that ballast tank sediments pose several problems, including the continuing risk of invasive and pathogenic species transfer. Moreover, Regulation B.5 of The IMO's BWM convention states “ships should be designed and constructed with a view to minimize the uptake and undesirable entrapment of Sediments, facilitate removal of Sediments”. The purpose of the study is to investigate the effectiveness of the pneumatic system for reducing the amount of accumulated sediment under different operating conditions and determine an optimal operating condition for the pneumatic system. The experimental study has demonstrated that there are complex relationships and interactions among initial air pressure, run number, and run time in terms of reducing sediment accumulation. The overall results of this study show that sediment reduction occurs at rates ranging from ∼4% to ∼29% in sets completed under different operating conditions. Even though the total amount of the sediment was reduced in all conditions at different rates, it is figured out that the sediment amount increased in some locations within the tank. However, when operated under optimal conditions suggested by the ANN application, the sediment reduction occurred at a rate of ∼29% and there was no local increase detected throughout the tank model.

Original language	English
Article number	111927
Journal	Ocean Engineering
Volume	259
DOIs	https://doi.org/10.1016/j.oceaneng.2022.111927
Publication status	Published - 1 Sept 2022

Bibliographical note

Publisher Copyright:
© 2022 Elsevier Ltd

Funding

This study was funded by Scientific Research Projects Coordination Unit ( BAP ) at Istanbul Technical University (Project Number:41718) and conducted within the continuation of the work done by Bilgin Güney et al. ( Bilgin Güney et al., 2020 ). In their preliminary studies, they determined the mid-section of the double bottom tank closer to the center girder is the most susceptible area for sediment accumulation ( Bilgin Güney et al., 2017, 2018b ) and they have developed a pneumatic system for air injection along the center girder. The purpose of the present study is to investigate the effectiveness of the pneumatic system under different operating conditions and to determine an optimal operating condition for the pneumatic system with experimental and Artificial Neural Network (ANN) applications. This study was funded by Scientific Research Projects Coordination Unit (BAP) at Istanbul Technical University (Project Number:41718) and conducted within the continuation of the work done by Bilgin Güney et al. ( Bilgin Güney et al., 2020). In their preliminary studies, they determined the mid-section of the double bottom tank closer to the center girder is the most susceptible area for sediment accumulation ( Bilgin Güney et al., 2017, 2018b) and they have developed a pneumatic system for air injection along the center girder. The purpose of the present study is to investigate the effectiveness of the pneumatic system under different operating conditions and to determine an optimal operating condition for the pneumatic system with experimental and Artificial Neural Network (ANN) applications.The overall work was concluded generally in three stages (Fig. 1). The experimental studies were carried out in the first and third stages of the study, and the Artificial Neural Networks (ANN) application was conducted in the second stage. Within the scope of the study, the ANN approach was used as a supporting tool to determine the optimal conditions of the pneumatic system to obtain the best sediment reduction rate.The only constraint here is that the number of data is limited. However, the study is not an ANN study. The ANN approach is only used as a supporting tool for experimental study to define an optimum working condition. Considering that each data set needs 14 days period to be experimentally created, the time and resources needed to improve the data set would exceed the purpose of the study.This study was funded by Scientific Research Projects Coordination Unit (BAP) at Istanbul Technical University (Project No:41718). The experiments were conducted with the system built within the “Conceptual Ballast Tank Design for Reducing Sediment Accumulation” project which was supported by the Scientific and Technical Research Council of Turkey (TUBITAK) with Grant No: 115Y740. The author would like to thank Assoc. Prof. Dr. Devrim Bülent Danışman for sharing his valuable expertise on ANN modeling. This study was funded by Scientific Research Projects Coordination Unit ( BAP ) at Istanbul Technical University (Project No:41718). The experiments were conducted with the system built within the “Conceptual Ballast Tank Design for Reducing Sediment Accumulation” project which was supported by the Scientific and Technical Research Council of Turkey (TUBITAK) with Grant No: 115Y740. The author would like to thank Assoc. Prof. Dr. Devrim Bülent Danışman for sharing his valuable expertise on ANN modeling.

Funders	Funder number
Artificial Neural Network
Artificial Neural Networks
Scientific Research Projects Coordination Unit
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu	115Y740
Istanbul Teknik Üniversitesi

Keywords

ANN
Ballast tank
Invasive species
Pneumatic system
Sediment reduction

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.oceaneng.2022.111927

Cite this

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title = "Optimization of operational parameters of pneumatic system for ballast tank sediment reduction with experimental and ANN applications",

abstract = "The studies show that ballast tank sediments pose several problems, including the continuing risk of invasive and pathogenic species transfer. Moreover, Regulation B.5 of The IMO's BWM convention states “ships should be designed and constructed with a view to minimize the uptake and undesirable entrapment of Sediments, facilitate removal of Sediments”. The purpose of the study is to investigate the effectiveness of the pneumatic system for reducing the amount of accumulated sediment under different operating conditions and determine an optimal operating condition for the pneumatic system. The experimental study has demonstrated that there are complex relationships and interactions among initial air pressure, run number, and run time in terms of reducing sediment accumulation. The overall results of this study show that sediment reduction occurs at rates ranging from ∼4% to ∼29% in sets completed under different operating conditions. Even though the total amount of the sediment was reduced in all conditions at different rates, it is figured out that the sediment amount increased in some locations within the tank. However, when operated under optimal conditions suggested by the ANN application, the sediment reduction occurred at a rate of ∼29% and there was no local increase detected throughout the tank model.",

keywords = "ANN, Ballast tank, Invasive species, Pneumatic system, Sediment reduction",

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doi = "10.1016/j.oceaneng.2022.111927",

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AB - The studies show that ballast tank sediments pose several problems, including the continuing risk of invasive and pathogenic species transfer. Moreover, Regulation B.5 of The IMO's BWM convention states “ships should be designed and constructed with a view to minimize the uptake and undesirable entrapment of Sediments, facilitate removal of Sediments”. The purpose of the study is to investigate the effectiveness of the pneumatic system for reducing the amount of accumulated sediment under different operating conditions and determine an optimal operating condition for the pneumatic system. The experimental study has demonstrated that there are complex relationships and interactions among initial air pressure, run number, and run time in terms of reducing sediment accumulation. The overall results of this study show that sediment reduction occurs at rates ranging from ∼4% to ∼29% in sets completed under different operating conditions. Even though the total amount of the sediment was reduced in all conditions at different rates, it is figured out that the sediment amount increased in some locations within the tank. However, when operated under optimal conditions suggested by the ANN application, the sediment reduction occurred at a rate of ∼29% and there was no local increase detected throughout the tank model.

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Optimization of operational parameters of pneumatic system for ballast tank sediment reduction with experimental and ANN applications

Abstract

Bibliographical note

Funding

Keywords

UN SDGs

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