Numerical Assessment of Plenums Intersected by Four Baffles Using the Boundary Element Method, Genetic Algorithm, and Neural Networks. (December 2013)
- Record Type:
- Journal Article
- Title:
- Numerical Assessment of Plenums Intersected by Four Baffles Using the Boundary Element Method, Genetic Algorithm, and Neural Networks. (December 2013)
- Main Title:
- Numerical Assessment of Plenums Intersected by Four Baffles Using the Boundary Element Method, Genetic Algorithm, and Neural Networks
- Authors:
- Chiu, Min-Chie
Chang, Ying-Chun - Abstract:
- There has been much research on partitioned plenums in the industrial field. However, maximum noise reduction of a plenum within a constrained space, which frequently occurs in engineering problems, has been neglected. Therefore, the optimum design of multi-chamber plenums becomes essential. In this paper, five-chamber plenums intersected by four baffles within a fixed space are assessed. In order to select the appropriate design parameter sets used in the shape optimization of a five-chamber plenum, three kinds of design parameter sets (Case I: L 1 * and L 2 *; Case II: L 1 ** and L 2 **; Case III: L 1 ***, L 2 ***, and L 3 ***) are proposed. In order to simplify the shape optimization of plenums intersected by multiple baffles, a simplified objective function (OBJ) is established by linking the boundary element model (BEM, developed using SYSNOISE) with a polynomial neural network fitted with a series of real data - input design data (baffle dimensions) and output data approximated by BEM data in advance. Before optimization is performed, accuracy of the boundary element method (BEM) for a one-chamber and three-chamber plenum is checked using analytical and experimental data and found to be accurate. To assess the optimal plenums, a genetic algorithm (GA) is adopted. Consequently, optimal results reveal that the depths of the two upper baffles and the two lower baffles play essential roles in minimizing the noise level of the lower frequencies (400∼800 Hz). Moreover, theThere has been much research on partitioned plenums in the industrial field. However, maximum noise reduction of a plenum within a constrained space, which frequently occurs in engineering problems, has been neglected. Therefore, the optimum design of multi-chamber plenums becomes essential. In this paper, five-chamber plenums intersected by four baffles within a fixed space are assessed. In order to select the appropriate design parameter sets used in the shape optimization of a five-chamber plenum, three kinds of design parameter sets (Case I: L 1 * and L 2 *; Case II: L 1 ** and L 2 **; Case III: L 1 ***, L 2 ***, and L 3 ***) are proposed. In order to simplify the shape optimization of plenums intersected by multiple baffles, a simplified objective function (OBJ) is established by linking the boundary element model (BEM, developed using SYSNOISE) with a polynomial neural network fitted with a series of real data - input design data (baffle dimensions) and output data approximated by BEM data in advance. Before optimization is performed, accuracy of the boundary element method (BEM) for a one-chamber and three-chamber plenum is checked using analytical and experimental data and found to be accurate. To assess the optimal plenums, a genetic algorithm (GA) is adopted. Consequently, optimal results reveal that the depths of the two upper baffles and the two lower baffles play essential roles in minimizing the noise level of the lower frequencies (400∼800 Hz). Moreover, the horizontal span of the baffles will influence the acoustical performance of the higher frequencies (1200 Hz and above). … (more)
- Is Part Of:
- Noise & vibration worldwide. Volume 44:Number 11(2013)
- Journal:
- Noise & vibration worldwide
- Issue:
- Volume 44:Number 11(2013)
- Issue Display:
- Volume 44, Issue 11 (2013)
- Year:
- 2013
- Volume:
- 44
- Issue:
- 11
- Issue Sort Value:
- 2013-0044-0011-0000
- Page Start:
- 25
- Page End:
- 44
- Publication Date:
- 2013-12
- Subjects:
- boundary element method -- genetic algorithm -- group method of data handling -- intersected baffle -- polynomial neural network model -- optimization
Noise control -- Periodicals
Damping (Mechanics) -- Periodicals
Soundproofing -- Periodicals
Damping (Mechanics)
Noise control
Soundproofing
Periodicals
620.205 - Journal URLs:
- http://multi-science.metapress.com/content/121511/ ↗
http://nvw.sagepub.com/ ↗
http://www.multi-science.co.uk/ ↗
http://www.ingenta.com/journals/browse/mscp/nvww ↗ - DOI:
- 10.1260/0957-4565.44.11.25 ↗
- Languages:
- English
- ISSNs:
- 0957-4565
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
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