Computational approach for membrane desalination system development

Along with surging population growth, the rapid pace of urbanization and industrialization were observed in many developing economies, resulting in a burst in water demand. As predicted by the World Bank Group, by 2030, the world would face a 30% of water shortage if the current trend on demand and...

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Main Author: Mo, Zijing
Other Authors: She Qianhong
Format: Thesis-Doctor of Philosophy
Language:English
Published: Nanyang Technological University 2024
Subjects:
Online Access:https://hdl.handle.net/10356/181806
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Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-181806
record_format dspace
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering
Reverse osmosis (RO)
System optimizations
Optimization and machine learning
Water treatment technology
Energy efficiency
Dynamic simulation
Brine resource recovery
Sustainable desalination
Semi-closed reverse osmosis
Closed-circuit reverse osmosis
spellingShingle Engineering
Reverse osmosis (RO)
System optimizations
Optimization and machine learning
Water treatment technology
Energy efficiency
Dynamic simulation
Brine resource recovery
Sustainable desalination
Semi-closed reverse osmosis
Closed-circuit reverse osmosis
Mo, Zijing
Computational approach for membrane desalination system development
description Along with surging population growth, the rapid pace of urbanization and industrialization were observed in many developing economies, resulting in a burst in water demand. As predicted by the World Bank Group, by 2030, the world would face a 30% of water shortage if the current trend on demand and supply-side remain unchanged. Therefore, an increased amount of resources should be devoted to the strategic options that can close the gap between water supply and demand. While RO is the most viable solution to closing such gap, it remains energy intensive which hurdle its wide application. The primary objective of this study is to improve energy efficiency in reverse osmosis (RO) designs for desalination, focusing on economically feasible solutions. Despite advancements in alternative RO designs, concerns persist, hindering their widespread adoption. This study addresses these concerns and knowledge gaps to optimize RO system configurations and reduce energy consumption. The study begins with a comprehensive investigation of existing alternative RO designs, highlighting their features, advantages, and disadvantages as delineated in Chapter 2. While some designs, such as Multiple-Stage RO (MSRO), exhibit superior performance in theoretical scenarios, they come with practical hurdles, such as reduced energy recovery efficiency and increased capital costs. Mixing effects compromising efficiency are observed in other designs like Batch RO (BRO), Closed-Circuit RO (CCRO), and CaptuRO. Hybrid RO processes, specifically Split-Feed Osmotically Assisted RO (SF-OARO) and Low-Salt-Rejection RO (LSRRO), show promise in reducing applied pressure for high salinity, higher recovery desalination applications. However, they introduce extra complexities and inefficiencies such as mixing and internal concentration polarization. Chapters 3, 4, 5, and 6 delve into the system optimization of RO designs. Chapter 3 focuses on the efficient hybrid RO design, SF-OARO. Operating parameters are optimized to reduce energy consumption, emphasizing its advantage in high-recovery Brine Volume Minimization (BVM) scenarios. An 18% energy saving and 4.1% cost savings are observed with SF-OARO compared to conventional SSRO at 65% recovery. Despite its superior performance at high recovery, OARO still lacks the ability to reduce overall energy consumption in the typical recovery range (50%) due to significant mixing and ICP effects. To explore potential RO solutions with reduced energy consumption, this study revisits standalone rather than hybrid RO designs due to their simpler transport processes and the avoidance of ICP. An existing advanced RO solution, CCRO, is investigated in Chapter 4, which consists of the more studied closed-loop (CL) period and the less focused plug-flow (PF) period. A time-dependent finite-difference model is developed to comprehensively assess the energy consumption of CCRO. The results indicate that, although varying the applied pressure helps reduce the energy consumption of CCRO compared to conventional designs, intrinsic inefficiencies during the PF period, which were overlooked in previous studies, compromise its practical efficiency. Therefore, compared to a 25% (0.41 kWh/m³) energy saving indicated by theoretical estimation, a reduced saving of 6% (0.15 kWh/m³) is observed by the model for practical CCRO compared to SSRO. To circumvent the intrinsic inefficiencies in existing RO alternatives, a novel Single-Staged Multiple Cycle RO, Semi-Closed Reverse Osmosis (SCRO), is introduced in Chapters 5 and 6. SCRO balances economic practicability and energy efficiency, avoiding over-pressurization without requiring additional stages. Featuring a concise design and flexible operation, SCRO demonstrates promising results in mitigating over-pressurization and outperforms other tested RO processes in low-energy desalination. Results indicate a theoretical 32% (0.53 kWh/m³) and module-wise 9% (0.15 kWh/m³) energy saving with SCRO compared to SSRO, outperforming other RO designs To accurately assess and optimize energy consumption, simulation methods, including both hard and soft computational approaches, are employed. The findings presented in this study offer valuable insights into enhancing RO energy efficiency, paving the way for more sustainable and economically viable desalination processes.
author2 She Qianhong
author_facet She Qianhong
Mo, Zijing
format Thesis-Doctor of Philosophy
author Mo, Zijing
author_sort Mo, Zijing
title Computational approach for membrane desalination system development
title_short Computational approach for membrane desalination system development
title_full Computational approach for membrane desalination system development
title_fullStr Computational approach for membrane desalination system development
title_full_unstemmed Computational approach for membrane desalination system development
title_sort computational approach for membrane desalination system development
publisher Nanyang Technological University
publishDate 2024
url https://hdl.handle.net/10356/181806
_version_ 1823108723198918656
spelling sg-ntu-dr.10356-1818062025-02-03T03:24:17Z Computational approach for membrane desalination system development Mo, Zijing She Qianhong Interdisciplinary Graduate School (IGS) Nanyang Environment and Water Research Institute QHSHE@ntu.edu.sg Engineering Reverse osmosis (RO) System optimizations Optimization and machine learning Water treatment technology Energy efficiency Dynamic simulation Brine resource recovery Sustainable desalination Semi-closed reverse osmosis Closed-circuit reverse osmosis Along with surging population growth, the rapid pace of urbanization and industrialization were observed in many developing economies, resulting in a burst in water demand. As predicted by the World Bank Group, by 2030, the world would face a 30% of water shortage if the current trend on demand and supply-side remain unchanged. Therefore, an increased amount of resources should be devoted to the strategic options that can close the gap between water supply and demand. While RO is the most viable solution to closing such gap, it remains energy intensive which hurdle its wide application. The primary objective of this study is to improve energy efficiency in reverse osmosis (RO) designs for desalination, focusing on economically feasible solutions. Despite advancements in alternative RO designs, concerns persist, hindering their widespread adoption. This study addresses these concerns and knowledge gaps to optimize RO system configurations and reduce energy consumption. The study begins with a comprehensive investigation of existing alternative RO designs, highlighting their features, advantages, and disadvantages as delineated in Chapter 2. While some designs, such as Multiple-Stage RO (MSRO), exhibit superior performance in theoretical scenarios, they come with practical hurdles, such as reduced energy recovery efficiency and increased capital costs. Mixing effects compromising efficiency are observed in other designs like Batch RO (BRO), Closed-Circuit RO (CCRO), and CaptuRO. Hybrid RO processes, specifically Split-Feed Osmotically Assisted RO (SF-OARO) and Low-Salt-Rejection RO (LSRRO), show promise in reducing applied pressure for high salinity, higher recovery desalination applications. However, they introduce extra complexities and inefficiencies such as mixing and internal concentration polarization. Chapters 3, 4, 5, and 6 delve into the system optimization of RO designs. Chapter 3 focuses on the efficient hybrid RO design, SF-OARO. Operating parameters are optimized to reduce energy consumption, emphasizing its advantage in high-recovery Brine Volume Minimization (BVM) scenarios. An 18% energy saving and 4.1% cost savings are observed with SF-OARO compared to conventional SSRO at 65% recovery. Despite its superior performance at high recovery, OARO still lacks the ability to reduce overall energy consumption in the typical recovery range (50%) due to significant mixing and ICP effects. To explore potential RO solutions with reduced energy consumption, this study revisits standalone rather than hybrid RO designs due to their simpler transport processes and the avoidance of ICP. An existing advanced RO solution, CCRO, is investigated in Chapter 4, which consists of the more studied closed-loop (CL) period and the less focused plug-flow (PF) period. A time-dependent finite-difference model is developed to comprehensively assess the energy consumption of CCRO. The results indicate that, although varying the applied pressure helps reduce the energy consumption of CCRO compared to conventional designs, intrinsic inefficiencies during the PF period, which were overlooked in previous studies, compromise its practical efficiency. Therefore, compared to a 25% (0.41 kWh/m³) energy saving indicated by theoretical estimation, a reduced saving of 6% (0.15 kWh/m³) is observed by the model for practical CCRO compared to SSRO. To circumvent the intrinsic inefficiencies in existing RO alternatives, a novel Single-Staged Multiple Cycle RO, Semi-Closed Reverse Osmosis (SCRO), is introduced in Chapters 5 and 6. SCRO balances economic practicability and energy efficiency, avoiding over-pressurization without requiring additional stages. Featuring a concise design and flexible operation, SCRO demonstrates promising results in mitigating over-pressurization and outperforms other tested RO processes in low-energy desalination. Results indicate a theoretical 32% (0.53 kWh/m³) and module-wise 9% (0.15 kWh/m³) energy saving with SCRO compared to SSRO, outperforming other RO designs To accurately assess and optimize energy consumption, simulation methods, including both hard and soft computational approaches, are employed. The findings presented in this study offer valuable insights into enhancing RO energy efficiency, paving the way for more sustainable and economically viable desalination processes. Doctor of Philosophy 2024-12-19T11:21:32Z 2024-12-19T11:21:32Z 2024 Thesis-Doctor of Philosophy Mo, Z. (2024). Computational approach for membrane desalination system development. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/181806 https://hdl.handle.net/10356/181806 10.32657/10356/181806 en This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). application/pdf Nanyang Technological University