Propeller Optimization in Marine Power Systems: Exploring Its Contribution and Correlation with Renewable Energy Solutions
Abstract
:1. Introduction
1.1. Problem Background
1.2. Energy Efficiency and GHG Reduction in Shipping
2. Materials and Methods
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- Optimized propeller design reduces vibrations;
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- Vibration reduction enhances propeller efficiency and decreases fuel consumption;
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- Propeller optimization reduces greenhouse gas (GHG) emissions from shipping.
3. Propeller Optimization—Case Study
3.1. Prop Scan System
3.2. Measurements and Data Collection
4. Results after Optimization of the Ship Propeller
5. Comparing Photovoltaic Panels Application, Wind Application, and Propeller Optimization
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Author/Authors and Year | Title | Effect on Energy Efficiency |
---|---|---|
Lee et al., 2010 [18] | Performance optimization of marine propellers | Method for improving wide chord tip (WCT) propeller efficiency by more than 2% |
Blasques et al., 2010 [20] | Hydro-elastic analysis and optimization of a composite marine propeller | The design and optimization of a flexible composite marine propeller results in a 1.25% reduction in fuel consumption |
Knutsson, Larsson, 2011 [25] | Large Area Propellers | Potential of propeller adjustments for efficiency enhancement |
Vetma et al., 2012 [22] | Optimization of marine propellers with constant pitch | Optimizing marine propellers using Prop Scan increased ship speed, while fuel consumption decreased |
Lützen, Kristensen, 2012 [12] | A Model for Prediction of Propulsion Power and Emissions: Tankers and Bulk Carriers | A new model for prediction of the propulsion power of ships |
Kristensen, Lützen, 2012 [13] | Existing Design Trends for Tankers and Bulk Carriers: Design Changes for Improvement of the EEDI in the Future | Analysis showed that the design trend of bulk carriers and tankers has moved in the wrong direction from an energy-saving point of view |
Vesting et al., 2013 [16] | Parameter Influence Analysis in Propeller Optimisation | Propeller optimization process |
Taheri, Mazaheri, 2013 [19] | Hydrodynamic Optimization of Marine Propeller Using Gradient and Non-Gradient-based Algorithms | Optimization of marine propellers using gradient and non-gradient-based algorithms revealed a nearly 13% increase in efficiency and a nearly 15% drop in torque coefficient for the first propeller, as well as a nearly 10% increase in efficiency for the later propeller |
Faitar, Novac, 2016 [8] | A new approach on the upgrade of energetic system based on green energy | Comparative analysis of the EEDI and EEOI |
Ančić et al., 2018 [9] | Energy efficiency of ro-ro passenger ships with integrated power systems | Energy efficiency of ro-ro passenger ships with IPS |
El Geneidy et al., 2018 [11] | Increasing energy efficiency in passenger ships by novel energy conservation measures | Increasing energy efficiency in passenger ships |
Zaccone et al., 2018 [15] | Ship voyage optimization for safe and energy-efficient navigation: A dynamic programming approach | Ship voyage optimization method, aiming to select the optimal path and speed on the basis of weather forecast maps in accordance with a minimum fuel consumption |
Radonja et al., 2019 [14] | Methodological approach on optimizing the speed of navigation to reduce fuel consumption and increase energy efficiency of the cruising ship | Fuel savings can be achieved by optimizing cruising speeds during travel |
Litwin et al., 2019 [5] | Experimental Research on the Energy Efficiency of a Parallel Hybrid Drive for an Inland Ship | Energy efficiency improvements of a parallel hybrid drive |
Roshan et al., 2020 [17] | Hull–propeller interaction for planing boats: a numerical study | Propellers have a significant impact on a vessel’s performance, leading to an increase in trim angle and a decrease in resistance |
He et al., 2021 [7] | Two-phase energy efficiency optimization for ships using parallel hybrid electric propulsion system | Two-phase energy efficiency optimization for ships using parallel hybrid electric propulsion system reduces energy consumption by between 2.60% and 9.86% |
The maritime executive, 2021 [23] | No name | Redesigned propeller blades increase fuel efficiency by up to 22% |
Ammar, Seddiek, 2021 [10] | Evaluation of the environmental and economic impacts of electric propulsion systems onboard ships: case study passenger vessel | Gas turbine electric and steam propulsion systems demonstrate higher energy efficiency compared to Diesel engines, boasting improvements of 9.3% and 27.55% |
Elkafas, Shouman, 2022 [6] | A Study of the Performance of Ship Diesel-Electric Propulsion Systems From an Environmental, Energy Efficiency, and Economic Perspective | The suggested electric propulsion system reduced emission rates compared to the conventional system, showing decreases of 10% for carbon dioxide, 21% for nitrogen oxides, and 88% for sulfur dioxide emissions. |
Doijode et al., 2022 [27] | A machine learning approach for propeller design and optimization | Challenges in propeller design and computational demands |
Hamed, 2022 [24] | Multi-objective optimization method of trimaran hull form for resistance reduction and propeller intake flow improvement | Trimaran hull form optimization outcomes reveal a 13.3% decrease in resistance and a 7.58% enhancement in wake coefficient for the obtained hull form |
Yin et al., 2023 [26] | Improve Ship Propeller Efficiency via Optimum Design of Propeller Boss Cap Fins | Optimization of propeller boss cap with fins provided an efficiency improvement of 0.728 percentage points |
Gypa et al., 2023 [29] | Propeller optimization by interactive genetic algorithms and machine learning | Difficulties in blade design optimization |
Pitch | Class | ||||
---|---|---|---|---|---|
S | I | II | III | ||
Local pitch | Pitch of one portion of one blade | ±1.5% | ±2% | ±3% | - |
Section pitch | Average pitch of one radius of one blade | ±1% | ±1.5% | ±2% | ±5% |
Blade pitch | Pitch of single blade | ±0.75% | ±1% | ±1.5% | ±4% |
Propeller pitch | Average pitch of all blades | ±0.5% | ±0.75% | ±1% | ±3% |
Year built | 1993 |
Length of hull | 116.00 m |
Breadth | 18.90 m |
Draft | 5.140 m |
Gross tonnage | 9487 |
Propulsion type | Diesel engine × 2 |
Manufacturer | MAN, Augsburg, Germany |
Model | MAN 8L |
Total power | 1750.00 kW × 2 |
Before Optimization—Class 2 | |||
---|---|---|---|
Revolutions per Minute (RPM) | 380 (±1) | Measurement Error | |
Course | 86° | 266° | ±1° |
Speed (knots) | 14.25 | 14.62 | ±0.02 |
Average speed in both directions (knots) | 14.43 | ±0.05 | |
Consumption (Lh) | 876.2 | 906.3 | ±0.4 |
Average consumption in both directions (L/h) | 891.3 | ±0.8 |
Ro-Ro Passenger Ship Vibration Measurement at 380 min−1 (Average of Both Directions) | |||
---|---|---|---|
Direction | X [m/s2] (Up-Down) | Y [m/s2] (Port-Starboard) | Z [m/s2] (Bow-Stern) |
RMS exp | 0.02130 | 0.02402 | 0.03447 |
RMS lin | 0.09295 | 0.07887 | 0.1399 |
Peak | 0.06951 | 0.07820 | 0.2477 |
Peak-Peak | 0.1667 | 0.1444 | 0.2320 |
Min | −0.09295 | −0.07888 | −0.1399 |
Max | 0.07371 | 0.07032 | 0.1077 |
Average | −0.000434 | −0.00002019 | −0.002849 |
Vibration spectrum (maximum amplitude) | |||
X peak | 0.1017@ [7 Hz] | ||
Y peak | 0.02108 @ [31 Hz] | ||
Z peak | 0.03088 @ [7Hz] |
After Optimization—Class S | |||
---|---|---|---|
Revolutions per Minute (RPM) | 380 (±1) | Measurement Error | |
Course | 185° | 5° | ±1° |
Speed (knots) | 14.71 | 14.54 | ±0.02 |
Average speed in both directions (knots) | 14.63 | ±0.05 | |
Consumption (L/h) | 865.2 | 892.1 | ±0.4 |
Average consumption in both directions (L/h) | 878.7 | ±0.8 |
Ro-Ro Passenger Ship Vibration Measurement at 380 min−1 (Average of Both Directions) | |||
---|---|---|---|
Direction | X [m/s2] (Up-Down) | Y [m/s2] (Port-Starboard) | Z [m/s2] (Bow-Stern) |
RMS exp | 0.02448 | 0.02310 | 0.036866 |
RMS lin | 0.02435 | 0.01968 | 0.1050 |
Peak | 0.074526 | 0.06702 | 0.2000 |
Peak-Peak | 0.1464 | 0.1275 | 0.1623 |
Min | −0.07188 | −0.06702 | −0.09495 |
Max | 0.074526 | 0.06754 | 0.1051 |
Average | −0.0006371 | −0.0003775 | 0.001191 |
Vibration spectrum (maximum amplitude) | |||
X peak | 0.0211 @ [7 Hz] | ||
Y peak | 0.01024 @ [12,5 Hz] | ||
Z peak | 0.03296 @ [7 Hz] |
Solar Power Application | Wind Power Application | Propeller Optimization on Ships | |
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Share and Cite
Bacalja Bašić, B.; Krčum, M.; Jurić, Z. Propeller Optimization in Marine Power Systems: Exploring Its Contribution and Correlation with Renewable Energy Solutions. J. Mar. Sci. Eng. 2024, 12, 843. https://doi.org/10.3390/jmse12050843
Bacalja Bašić B, Krčum M, Jurić Z. Propeller Optimization in Marine Power Systems: Exploring Its Contribution and Correlation with Renewable Energy Solutions. Journal of Marine Science and Engineering. 2024; 12(5):843. https://doi.org/10.3390/jmse12050843
Chicago/Turabian StyleBacalja Bašić, Bruna, Maja Krčum, and Zdeslav Jurić. 2024. "Propeller Optimization in Marine Power Systems: Exploring Its Contribution and Correlation with Renewable Energy Solutions" Journal of Marine Science and Engineering 12, no. 5: 843. https://doi.org/10.3390/jmse12050843
APA StyleBacalja Bašić, B., Krčum, M., & Jurić, Z. (2024). Propeller Optimization in Marine Power Systems: Exploring Its Contribution and Correlation with Renewable Energy Solutions. Journal of Marine Science and Engineering, 12(5), 843. https://doi.org/10.3390/jmse12050843