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Optimization of the Morphological Parameters of a Metal Foam for the Highest Sound Absorption Coefficient Using Local Search Algorithm

Jafari Mohammad Javad, Khavanin Ali, Ebadzadeh Touraj, Fazlali Mahmood, Sharak Mohsen Niknam, Madvari Rohollah Fallah

Archives of Acoustics

2020

Vol. 45, No. 3

487--497

Due to its unique features, the metal foam is considered as one of the newest acoustic absorbents. It is a navel approach determining the structural properties of sound absorbent to predict its acoustical behavior. Unfortunately, direct measurements of these parameters are often difficult. Currently, there have been acoustic models showing the relationship between absorbent morphology and sound absorption coefficient (SAC). By optimizing the effective parameters on the SAC, the maximum SAC at each frequency can be obtained. In this study, using the Benchmarking method, the model presented by Lu was validated in MATLAB coding software. Then, the local search algorithm (LSA) method was used to optimize the metal foam morphology parameters. The optimized parameters had three factors, including porosity, pore size, and metal foam pore opening size. The optimization was applied to a broad band of frequency ranging from 500 to 8000 Hz. The predicted values were in accordance with benchmark data resulted from Lu model. The optimal range of the parameters including porosity of 50 to 95%, pore size of 0.09 to 4.55 mm, and pore opening size of 0.06 to 0.4 mm were applied to obtain the highest SAC for the frequency range of 500 to 800 Hz. The optimal amount of pore opening size was 0.1 mm in most frequencies to have the highest SAC. It was concluded that the proposed method of the LSA could optimize the parameters affecting the SAC according to the Lu model. The presented method can be a reliable guide for optimizing microstructure parameters of metal foam to increase the SAC at any frequency and can be used to make optimized metal foam.

Ship Collision Avoidance by Distributed Tabu Search

Kim D., Hirayama K., Okimoto M.

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

2015

Vol. 9, no. 1

23--29

More than 90% of world trade is transported by sea. The size and speed of ships is rapidly increasing in order to boost economic efficiency. If ships collide, the damage and cost can be astronomical. It is very difficult for officers to ascertain routes that will avoid collisions, especially when multiple ships travel the same waters. There are several ways to prevent ship collisions, such as lookouts, radar, and VHF radio. More advanced methodologies, such as ship domain, fuzzy theory, and genetic algorithm, have been proposed. These methods work well in one-on-one situations, but are more difficult to apply in multiple-ship situations. Therefore, we proposed the Distributed Local Search Algorithm (DLSA) to avoid ship collisions as a precedent study. DLSA is a distributed algorithm in which multiple ships communicate with each other within a certain area. DLSA computes collision risk based on the information received from neighboring ships. However, DLSA suffers from Quasi-Local Minimum (QLM), which prevents a ship from changing course even when a collision risk arises. In our study, we developed the Distributed Tabu Search Algorithm (DTSA). DTSA uses a tabu list to escape from QLM that also exploits a modified cost function and enlarged domain of next-intended courses to increase its efficiency. We conducted experiments to compare the performance of DLSA and DTSA. The results showed that DTSA outperformed DLSA.