Multi-Disciplinary Design Optimization for Large-Scale Reverse Osmosis Systems
Large-scale desalination plants are complex systems with many inter-disciplinary interactions and different levels of subsystem hierarchy. Advanced complex systems design tools have been shown to have a positive impact on design in aerospace and automotive, but have generally not been used in the de...
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| Format: | Article |
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ASME International
2019
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| Online Access: | http://hdl.handle.net/1721.1/120027 https://orcid.org/0000-0001-7891-1187 https://orcid.org/0000-0003-2365-1378 https://orcid.org/0000-0002-7086-5005 https://orcid.org/0000-0002-7776-3423 |
| _version_ | 1826209427465699328 |
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| author | Sharqawy, Mostafa H. Yu, Bo Yang Honda, Tomonori Zubair, Syed M. Yang, Maria C. |
| author2 | Massachusetts Institute of Technology. Department of Mechanical Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Mechanical Engineering Sharqawy, Mostafa H. Yu, Bo Yang Honda, Tomonori Zubair, Syed M. Yang, Maria C. |
| author_sort | Sharqawy, Mostafa H. |
| collection | MIT |
| description | Large-scale desalination plants are complex systems with many inter-disciplinary interactions and different levels of subsystem hierarchy. Advanced complex systems design tools have been shown to have a positive impact on design in aerospace and automotive, but have generally not been used in the design of water systems. This work presents a multi-disciplinary design optimization approach to desalination system design to minimize the total water production cost of a 30,000m3/day capacity reverse osmosis plant situated in the Middle East, with a focus on comparing monolithic with distributed optimization architectures. A hierarchical multi-disciplinary model is constructed to capture the entire system's functional components and subsystem interactions. Three different multi-disciplinary design optimization (MDO) architectures are then compared to find the optimal plant design that minimizes total water cost. The architectures include the monolithic architecture multidisciplinary feasible (MDF), individual disciplinary feasible (IDF) and the distributed architecture analytical target cascading (ATC). The results demonstrate that an MDF architecture was the most efficient for finding the optimal design, while a distributed MDO approach such as analytical target cascading is also a suitable approach for optimal design of desalination plants, but optimization performance may depend on initial conditions. |
| first_indexed | 2024-09-23T14:22:41Z |
| format | Article |
| id | mit-1721.1/120027 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T14:22:41Z |
| publishDate | 2019 |
| publisher | ASME International |
| record_format | dspace |
| spelling | mit-1721.1/1200272022-09-29T09:03:59Z Multi-Disciplinary Design Optimization for Large-Scale Reverse Osmosis Systems Sharqawy, Mostafa H. Yu, Bo Yang Honda, Tomonori Zubair, Syed M. Yang, Maria C. Massachusetts Institute of Technology. Department of Mechanical Engineering Massachusetts Institute of Technology. Institute for Data, Systems, and Society Yu, Bo Yang Honda, Tomonori Zubair, Syed M. Yang, Maria Large-scale desalination plants are complex systems with many inter-disciplinary interactions and different levels of subsystem hierarchy. Advanced complex systems design tools have been shown to have a positive impact on design in aerospace and automotive, but have generally not been used in the design of water systems. This work presents a multi-disciplinary design optimization approach to desalination system design to minimize the total water production cost of a 30,000m3/day capacity reverse osmosis plant situated in the Middle East, with a focus on comparing monolithic with distributed optimization architectures. A hierarchical multi-disciplinary model is constructed to capture the entire system's functional components and subsystem interactions. Three different multi-disciplinary design optimization (MDO) architectures are then compared to find the optimal plant design that minimizes total water cost. The architectures include the monolithic architecture multidisciplinary feasible (MDF), individual disciplinary feasible (IDF) and the distributed architecture analytical target cascading (ATC). The results demonstrate that an MDF architecture was the most efficient for finding the optimal design, while a distributed MDO approach such as analytical target cascading is also a suitable approach for optimal design of desalination plants, but optimization performance may depend on initial conditions. King Fahd University of Petroleum & Minerals (Cneter fo Clean Water and Clean Energy at MIT and KFUPM under project number R13-CW-10) 2019-01-14T18:01:39Z 2019-01-14T18:01:39Z 2014-08 2019-01-14T17:45:03Z Article http://purl.org/eprint/type/ConferencePaper 978-0-7918-4631-5 http://hdl.handle.net/1721.1/120027 Yu, Bo Yang, Tomonori Honda, Syed Zubair, Mostafa H. Sharqawy, and Maria C. Yang. “Multi-Disciplinary Design Optimization for Large-Scale Reverse Osmosis Systems.” Volume 2A: 40th Design Automation Conference (August 17, 2014). https://orcid.org/0000-0001-7891-1187 https://orcid.org/0000-0003-2365-1378 https://orcid.org/0000-0002-7086-5005 https://orcid.org/0000-0002-7776-3423 http://dx.doi.org/10.1115/DETC2014-35032 Volume 2A: 40th Design Automation Conference Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf ASME International ASME |
| spellingShingle | Sharqawy, Mostafa H. Yu, Bo Yang Honda, Tomonori Zubair, Syed M. Yang, Maria C. Multi-Disciplinary Design Optimization for Large-Scale Reverse Osmosis Systems |
| title | Multi-Disciplinary Design Optimization for Large-Scale Reverse Osmosis Systems |
| title_full | Multi-Disciplinary Design Optimization for Large-Scale Reverse Osmosis Systems |
| title_fullStr | Multi-Disciplinary Design Optimization for Large-Scale Reverse Osmosis Systems |
| title_full_unstemmed | Multi-Disciplinary Design Optimization for Large-Scale Reverse Osmosis Systems |
| title_short | Multi-Disciplinary Design Optimization for Large-Scale Reverse Osmosis Systems |
| title_sort | multi disciplinary design optimization for large scale reverse osmosis systems |
| url | http://hdl.handle.net/1721.1/120027 https://orcid.org/0000-0001-7891-1187 https://orcid.org/0000-0003-2365-1378 https://orcid.org/0000-0002-7086-5005 https://orcid.org/0000-0002-7776-3423 |
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