Article
Engineering, Chemical
Jiaxing Zhu, Cong Jing, Lin Hao, Hongyuan Wei
Summary: The extractive dividing-wall column (E-DWC) can enhance the sustainability and safety of chemical processes, but operational and control issues are major obstacles. This study investigates interaction behavior in E-DWC, emphasizing the need for additional control freedom and proposing an intermediate heating strategy for improving controllability.
SEPARATION AND PURIFICATION TECHNOLOGY
(2021)
Article
Engineering, Chemical
Ruan de Villiers, Hendrik A. Kooijman, Ross Taylor
Summary: Reactive Dividing Wall Column (RDWC) modelling has gained significant attention due to its potential for energy and capital cost savings. Most simulations involve decomposing RDWCs into reactive and non-reactive column sections, leading to time-consuming and difficult convergences. In this study, an equation-based parallel column model (PCM) is used to rapidly model an RDWC as a single unit, demonstrating excellent numerical performance and validity for reproducing conventionally modelled RDWCs.
CHEMICAL ENGINEERING RESEARCH & DESIGN
(2023)
Article
Engineering, Chemical
Guoxuan Li, Shengli Liu, Gangqiang Yu, Chengna Dai, Zhigang Lei
Summary: The study focuses on process intensification by combining ionic liquids-based mixed entrainers and DWC technology, showing high energy efficiency, low economy cost and a promising industrial application prospect.
SEPARATION AND PURIFICATION TECHNOLOGY
(2021)
Article
Energy & Fuels
Zhongfeng Geng, Ke Zhang, Yuzhu Yang, Hao Gong, Minhua Zhang
Summary: This study proposes an extractive distillation intensified hydrolysis process to completely hydrolyze methyl acetate. By using acetic acid as an extractant, impurity components can be avoided and the process can be simplified. Under the optimum conditions, methyl acetate can be almost completely hydrolyzed, and the purity of the produced crude acetic acid and methanol is also improved.
CHEMICAL ENGINEERING AND PROCESSING-PROCESS INTENSIFICATION
(2022)
Article
Engineering, Chemical
Qiliang Ye, Yule Wang, Hui Pan, Wenyong Zhou, Peiqing Yuan
Summary: The focus of this study is to investigate the use of an extractive dividing wall column (EDWC) with N, N-dimethylacetamide (DMAC) as the entrainer for separating azeotropic mixtures of dipropyl ether and 1-propyl alcohol. The results show that this method is more economically attractive compared to conventional extractive distillation and pressure swing distillation. Additionally, the study finds that a control structure with the vapor split ratio as the manipulated variable has better dynamic control performance when facing feed flow rate and composition disturbances.
Article
Engineering, Chemical
Dian Ning Chia, Fanyi Duanmu, Eva Sorensen
Summary: The separation of azeotropic mixtures is often energy intensive. This study compares different intensification methods, such as dividing wall columns and hybrid distillation-membrane processes, and finds that the distillation followed by pervaporation then by distillation (D-P-D) and hybrid dividing wall column (H-DWC) structures have lower total annualized costs due to smaller membrane area requirements.
CHEMICAL ENGINEERING RESEARCH & DESIGN
(2023)
Article
Engineering, Chemical
Cong Jing, Jiaxing Zhu, Leping Dang, Hongyuan Wei
Summary: The energy-efficient E-DWC-HI process is proposed for separating DCM-MeOH mixture, and it is found that variable vapor split by adjusting pressures on both sides of the dividing wall can stabilize product purities.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2021)
Article
Engineering, Environmental
Jian Zhai, Xiaoqing Sun, Siqi Huang, Hongfei Xie, Xin Chen
Summary: Inherently safer design during the preliminary design stage is crucial for reducing potential risks and accidents in new process design. However, little attention has been given to incorporating inherent safety assessment into the technoevaluation of heat-integrated extractive dividing wall column processes. This paper proposes a systematic methodology for designing energy-efficient extractive dividing wall column processes by utilizing heat pump and feed preheating techniques. The results demonstrate significant reductions in energy consumption, annual cost, and CO2 emissions, as well as improved thermodynamic efficiency compared to conventional designs.
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
(2023)
Article
Engineering, Chemical
Jiyan Liu, Jianlin Yan, Wenshuo Liu, Jie Kong, Yang Wu, Xinnong Li, Lanyi Sun
Summary: This study optimized the reactive-extractive dividing wall column (REDWC) and REDWC with feed preheating process using a multi-objective genetic algorithm, for the separation of ethyl acetate/ethanol/water ternary azeotropic mixture. Additionally, new configurations combining Organic Rankine cycles (ORCs) were proposed to significantly reduce TAC and CO2 emissions.
SEPARATION AND PURIFICATION TECHNOLOGY
(2022)
Article
Energy & Fuels
Qiaoting He, Qiao Li, Yunfei Tan, Lichun Dong, Zemin Feng
Summary: This paper improves the process of separating the azeotropic mixture of methanol and trimethoxysilane through multi-objective optimization and proposes a heat pump assisted EDWC process. The optimal solution is obtained by considering criteria such as total annual cost, carbon emission, and thermodynamic efficiency.
CHEMICAL ENGINEERING AND PROCESSING-PROCESS INTENSIFICATION
(2022)
Review
Engineering, Chemical
Natalie J. Czarnecki, Scott A. Owens, R. Bruce Eldridge
Summary: Extractive distillation (ED) can be combined with divided wall column (DWC) schemes to separate azeotropic mixtures within one column shell. Traditional extractive divided wall columns (EDWCs) have the dividing wall placed at the top of the column, eliminating the common rectifying section. This review covers the design schemes, entrainer selection process, simulation design methods, and control schemes for EDWCs. There is an emphasis on the 33 azeotropic systems that have been separated using EDWCs. Successful case studies and ongoing research challenges are highlighted in the review. As with switching from conventional distillation schemes to a DWC, the motivation to use EDWCs over ED is economic savings and environmental benefits.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2023)
Article
Engineering, Chemical
Zhishan Zhang, Xiaoxiao Zhao, Xiuyu Zhu, Min Li, Zhun Ma, Jun Gao
Summary: Several new extractive distillation configurations using ionic liquid as extractant are proposed, with EDWC scheme being the best option due to its benefits in reducing costs and CO2 emissions as compared to conventional CED process. The optimization method used is practical for designing complex distillation systems.
SEPARATION AND PURIFICATION TECHNOLOGY
(2021)
Article
Engineering, Chemical
Jiaxing Zhu, Cong Jing, Lin Hao, Hongyuan Wei
Summary: This article proposes a systematic method to study the application of vapor recompression assisted extractive dividing-wall column (EDWC-VRC) and evaluates several configurations through multi-criteria assessment, ultimately finding configurations with better economic and environmental performance.
SEPARATION AND PURIFICATION TECHNOLOGY
(2022)
Article
Engineering, Chemical
Aejin Lee, Yus Donald Chaniago, Juli Ayu Ningtyas, Hosanna Uwitonze, Hankwon Lim
Summary: This study uses optimal extractive distillation and extractive dividing wall column to recover waste solvent, and multi-objective optimization using genetic algorithm is conducted by linking Aspen Plus and MATLAB. The optimized cases are compared in terms of energy, economic, and environmental parameters, and it is found that the extractive dividing wall column can achieve potential energy savings of 26.29%, total annual cost savings of 24.15%, and an exergy efficiency of 21.02%. Optimization can significantly reduce exergy losses associated with the number of trays, while dividing wall column can significantly reduce exergy losses associated with remixing. Further, multi-objective optimization using a genetic algorithm and a range of populations provides various results for process selection.
SEPARATION AND PURIFICATION TECHNOLOGY
(2023)
Article
Thermodynamics
Hongru Zhang, Shuai Wang, Jiaxuan Tang, Ningning Li, Yanan Li, Peizhe Cui, Yinglong Wang, Shiqing Zheng, Zhaoyou Zhu, Yixin Ma
Summary: This study investigates the separation mechanism of chemicals using thermodynamics and molecular dynamics theory, and reduces energy consumption by utilizing extractive dividing-wall column and pervaporation technologies. The optimized processes show improved performance in terms of TAC and CO2 emissions compared to the basic processes.
Article
Engineering, Chemical
Yingjie Ma, Jie Li
Summary: In this study, two robust homotopy continuation enhanced branch and bound (HCBB) algorithms are proposed for solving large-scale strongly nonlinear and nonconvex mixed-integer nonlinear programming (MINLP) models. The computational results demonstrate that the proposed algorithms can find the optimal solutions while other algorithms fail or find worse solutions.
Article
Energy & Fuels
Wanrong Wang, Yingjie Ma, Azadeh Maroufmashat, Nan Zhang, Jie Li, Xin Xiao
Summary: This study focuses on hydrogen production using solar thermal chemistry, utilizing optimization design and machine learning techniques to reduce production costs and CO2 emissions, resulting in a reduction of around 17.2% in the cost of hydrogen production.
Article
Thermodynamics
Nikolaos Rakovitis, Dan Li, Nan Zhang, Jie Li, Liping Zhang, Xin Xiao
Summary: In this work, a novel mathematical formulation is developed for the energy-efficient flexible job-shop scheduling problem using an improved time representation method. A grouping-based decomposition approach is proposed to efficiently solve large-scale problems and generate good feasible solutions with reduced energy consumption in significantly less computational time. The proposed model outperforms existing models by achieving up to 13.5% energy savings and up to 43.1% less energy consumption compared to existing algorithms.
Article
Thermodynamics
Zheng Chu, Nan Zhang, Robin Smith
Summary: Organic Rankine Cycle (ORC) is a promising technology for utilizing industrial low-grade waste heat, but the existing integration methods are insufficient. This study proposes a model-based methodology for the indirect integration of multi-parallel ORCs and validates its application through two case studies. The results show that using multi-parallel ORCs instead of a single ORC can effectively decrease the overall annualized cost.
Article
Chemistry, Multidisciplinary
Zhaoqing Wang, Dungang Gu, Jiaqi Lu, Nan Zhang, Yang Liu, Guanghui Li
Summary: A novel mixed-integer linear programming model is proposed in this paper for scheduling the batch operation of a wastewater treatment plant under time-of-use electricity pricing. By optimizing the start time and end time of each treatment task, the electricity cost can be minimized to the greatest extent, without changing the treatment capacity or the treatment process.
Article
Engineering, Chemical
Dan Li, Nikolaos Rakovitis, Taicheng Zheng, Yueting Pan, Jie Li, Giorgos Kopanos
Summary: In this study, two novel unit-specific event-based mixed-integer linear programming models are developed for scheduling multipurpose batch plants. The introduction of indirect and direct material transfer allows for rigorous sequencing and alignment of tasks in different units. The computational results show that the proposed models require fewer event points in many cases to achieve optimality compared to existing unit-specific event-based models. The best variant developed outperforms existing models with a maximum improvement of 67% in objective values and significantly reduces computational effort in some cases.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2022)
Article
Engineering, Chemical
Xi Cheng, Yangyanbing Liao, Zhao Lei, Jie Li, Xiaolei Fan, Xin Xiao
Summary: In this work, a multi-scale design framework of MOF-based membrane separation for CO2/CH4 mixture is proposed, which integrates molecular simulation, machine learning, and process modeling and simulation. The adsorption isotherms, permeability, and selectivity of a MOF-based membrane (IRMOF-1) for CO2/CH4 separation are evaluated using molecular simulation. Prediction models of adsorption capacity and self-diffusivity are established using machine learning methods, and then integrated with membrane separation process modeling. Case studies demonstrate the feasibility and superiority of the proposed integrated framework.
JOURNAL OF MEMBRANE SCIENCE
(2023)
Article
Engineering, Environmental
Na Xue, Jiaqi Lu, Dungang Gu, Yuhang Lou, Yuan Yuan, Guanghui Li, Shogo Kumagai, Yuko Saito, Toshiaki Yoshioka, Nan Zhang
Summary: Low-carbon water production technologies are crucial for sustainable development and mitigating climate change. However, many advanced water treatment processes lack comprehensive assessments of their greenhouse gas emissions. This case study focuses on electrodialysis (ED), an electricity-driven desalination technology, and assesses its carbon footprint in various applications. The study highlights the significant impact of power consumption on GHG emissions and recommends optimizing process design and operation to reduce energy consumption. The findings also underscore the importance of reducing GHG emissions in module production and disposal.
Article
Engineering, Chemical
Dinghao Li, Jingde Wang, Wei Sun, Nan Zhang
Summary: This paper proposes a novel matrix non-structural model for heat exchanger networks (HEN), which improves the flexibility and efficiency of searching feasible solutions.
Article
Multidisciplinary Sciences
Jiaqi Lu, Jing Tang, Rui Shan, Guanghui Li, Pinhua Rao, Nan Zhang
Summary: Solar photovoltaics (PVs) installation is predicted to increase 20-fold by 2050. However, the production process of PV panels generates significant greenhouse gas emissions, which vary depending on the grid emissions. A dynamic life cycle assessment (LCA) model was developed to evaluate the carbon footprint of PV panels manufactured and installed in the United States. The estimated state-level carbon footprint of solar electricity in 2050 is significantly lower than the comparison benchmark, indicating the potential for a carbon-neutral energy system.
Article
Engineering, Environmental
Ruilan Wei, Hui Wang, Longbo Jiang, Jinjuan Yang, Wenqin Li, Xingzhong Yuan, Hou Wang, Jie Liang, Yaoning Chen, Yuanqing Bu
Summary: In this study, a novel highly dispersed cobalt single-atom loaded carbon nitride catalyst was prepared via a molecular self-assembly strategy. The catalyst exhibited effective removal of sulfamethoxazole through peroxymonosulfate activation. The catalytic pathway and the variations in toxicity were also investigated.
CHEMICAL ENGINEERING JOURNAL
(2023)
Review
Green & Sustainable Science & Technology
Shuhao Zhang, Nan Zhang
Summary: This paper introduces the recent development in integrated green hydrogen polygeneration, summarizing theoretical concepts, design types, and recent developments related to the integration of Alkaline Electrolysis (AE), Proton Exchange Membrane Electrolysis (PEME), and the Solid Oxide Electrolysis Cell (SOEC). The study evaluates the efficiency and economic impact of green hydrogen production integrated with different energy sources, storage, and power cycles. The state-of-the-art method for hydrogen production is the Solid Oxide Electrolysis Cell (SOEC) which shows over 10% efficiency improvement compared to commercially applied methods (AE and PEME).
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Engineering, Chemical
Lixiao Ye, Nan Zhang, Guanghui Li, Dungang Gu, Jiaqi Lu, Yuhang Lou
Summary: This paper proposes a design methodology based on the GA-BP model to improve design efficiency, minimize reliance on experience, and obtain the best design solution. It establishes a distillation column surrogate model using the back propagation neural network technique and optimizes the design solution using a Genetic Algorithm with the minimum Total Annual Cost (TAC) as the objective function. The proposed method is verified with a propylene distillation column and achieves a 6.1% reduction in TAC and a 27.13 kgCO(2)/t reduction in carbon emission compared to the original design.
