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Parametric Analysis of a Double Shaft, Batch-Type Paddle Mixer Using the Discrete Element Method (DEM). Processes (Basel) 2023. [DOI: 10.3390/pr11030738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2023] Open
Abstract
To improve the understanding of the mixing performance of double shaft, batch-type paddle mixers, the discrete element method (DEM) in combination with a Plackett–Burman design of experiments simulation plan is used to identify factor significance on the system’s mixing performance. Effects of several factors, including three material properties (particle size, particle density and composition), three operational conditions (initial filling pattern, fill level and impeller rotational speed) and three geometric parameters (paddle size, paddle angle and paddle number), were quantitatively investigated using the relative standard deviation (RSD). Four key performance indicators (KPIs), namely the mixing quality, mixing time, average mixing power and energy required to reach a steady state, were defined to evaluate the performance of the double paddle mixer. The results show that the material property effects are not as significant as those of the operational conditions and geometric parameters. In particular, the geometric parameters were observed to significantly influence the energy consumption, while not affecting the mixing quality and mixing time, showing their potential towards designing more sustainable mixers. Furthermore, the analysis of granular temperature revealed that the centre area between the two paddles has a high diffusivity, which can be correlated to the mixing time.
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Effect of the Mixer Design Parameters on the Performance of a Twin Paddle Blender: A DEM Study. Processes (Basel) 2023. [DOI: 10.3390/pr11030733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2023] Open
Abstract
The design parameters of a mixing system have a major impact on the quality of the final product. Therefore, identifying the optimum parameters of mixing systems is highly relevant to various industrial processes dealing with particulate flows. However, the studies on the influences of the mixer’s design features are still insufficient. In this study, the Discrete Element Method (DEM) is used to examine the impact of paddle angle, width, and gap on the mixing performance of a twin paddle blender. The mixing performance and particle flow are assessed using the relative standard deviation (RSD) mixing index, velocity field, diffusivity coefficient, granular temperature, the force acting on particles, and the mixer’s power consumption. The mixing performance is highest for a paddle angle of 0° at the cost of the highest forces acting on particles. The paddle width is indicated as a critical factor for achieving better mixing quality. In contrast, the powder mixing efficiency and the mixer’s power consumption are not significantly affected by the paddle gap. The results regarding the power consumption denote that the mixer using the paddle angle of 60° has the minimum power consumption. Moreover, increasing the paddle width results in the enhancement of the mixer’s power consumption.
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Zuo Z, Wang J, Gong S, Zhang J. Effect of blade configuration on the mixing process of particles in an intensive mixer. PARTICULATE SCIENCE AND TECHNOLOGY 2023. [DOI: 10.1080/02726351.2023.2177216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/19/2023]
Affiliation(s)
- Zhijian Zuo
- School of Mechanical Engineering, Xiangtan University, Xiangtan, China
| | - Jiajie Wang
- School of Mechanical Engineering, Xiangtan University, Xiangtan, China
| | - Shuguang Gong
- School of Mechanical Engineering, Xiangtan University, Xiangtan, China
| | - Jianping Zhang
- School of Mechanical Engineering, Xiangtan University, Xiangtan, China
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Advanced image analytics to study powder mixing in a novel laboratory scale agitated filter dryer. POWDER TECHNOL 2023. [DOI: 10.1016/j.powtec.2023.118273] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
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5
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Kato Y, Kushimoto K, Ishihara S, Kano J. Development of a method for estimating particles mixing curves in short DEM simulation time. ADV POWDER TECHNOL 2022. [DOI: 10.1016/j.apt.2022.103841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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6
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On POD-based modal analysis in simulations of granular flows. POWDER TECHNOL 2022. [DOI: 10.1016/j.powtec.2022.118058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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7
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Effects of operating conditions and particle properties on mixing performance in an industrial-scale U-shape ribbon mixer. POWDER TECHNOL 2022. [DOI: 10.1016/j.powtec.2022.117933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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Kawashima K, Shirzadi M, Fukasawa T, Fukui K, Tsuru T, Ishigami T. Numerical modeling for particulate flow through realistic microporous structure of microfiltration membrane: Direct numerical simulation coordinated with focused ion beam scanning electron microscopy. POWDER TECHNOL 2022. [DOI: 10.1016/j.powtec.2022.117872] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2022]
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9
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Li S, Duan G, Sakai M. Development of a reduced-order model for large-scale Eulerian–Lagrangian simulations. ADV POWDER TECHNOL 2022. [DOI: 10.1016/j.apt.2022.103632] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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10
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Shi Q, Sakai M. Recent progress on the discrete element method simulations for powder transport systems: A review. ADV POWDER TECHNOL 2022. [DOI: 10.1016/j.apt.2022.103664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
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Gao X, Xie G, Xu Y, Yu Y, Lai Q. Application of a staggered symmetrical spiral groove wheel on a quantitative feeding device and investigation of particle motion characteristics based on DEM. POWDER TECHNOL 2022. [DOI: 10.1016/j.powtec.2022.117650] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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12
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Lu X, Dai B, Yang S. DEM Study of the Effect of Impeller Design on Mixing Performance in a Vertical Mixer. Ind Eng Chem Res 2022. [DOI: 10.1021/acs.iecr.2c00455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Xingfu Lu
- Zhongye Changtian International Engineering Co., Ltd., Changsha 410205, Hunan, China
| | - Bo Dai
- Zhongye Changtian International Engineering Co., Ltd., Changsha 410205, Hunan, China
| | - Shiliang Yang
- State Key Laboratory of Complex Nonferrous Metal Resources Clean Utilization, Kunming University of Science and Technology, Kunming 650093, Yunnan, China
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Arifuzzaman S, Dong K, Zhu H, Zeng Q. DEM study and machine learning model of particle percolation under vibration. ADV POWDER TECHNOL 2022. [DOI: 10.1016/j.apt.2022.103551] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Tiscar J, Boix J, Mallol G, Pérez J, Gilabert F. Design of new industrial mould filling systems for the manufacture of ceramic tiles using a discrete element framework. POWDER TECHNOL 2022. [DOI: 10.1016/j.powtec.2022.117446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Jadidi B, Ebrahimi M, Ein-Mozaffari F, Lohi A. A comprehensive review of the application of DEM in the investigation of batch solid mixers. REV CHEM ENG 2022. [DOI: 10.1515/revce-2021-0049] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Abstract
Powder mixing is a vital operation in a wide range of industries, such as food, pharmaceutical, and cosmetics. Despite the common use of mixing systems in various industries, often due to the complex nature of mixing systems, the effects of operating and design parameters on the mixers’ performance and final blend are not fully known, and therefore optimal parameters are selected through experience or trial and error. Experimental and numerical techniques have been widely used to analyze mixing systems and to gain a detailed understanding of mixing processes. The limitations associated with experimental techniques, however, have made discrete element method (DEM) a valuable complementary tool to obtain comprehensive particle level information about mixing systems. In the present study, the fundamentals of solid-solid mixing, segregation, and characteristics of different types of batch solid mixers are briefly reviewed. Previously published papers related to the application of DEM in studying mixing quality and assessing the influence of operating and design parameters on the mixing performance of various batch mixing systems are summarized in detail. The challenges with regards to the DEM simulation of mixing systems, the available solutions to address those challenges and our recommendations for future simulations of solid mixing are also presented and discussed.
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Affiliation(s)
- Behrooz Jadidi
- Department of Chemical Engineering , Ryerson University , 350 Victoria Street , Toronto M5B 2K3 , Canada
| | - Mohammadreza Ebrahimi
- Department of Chemical Engineering , Ryerson University , 350 Victoria Street , Toronto M5B 2K3 , Canada
| | - Farhad Ein-Mozaffari
- Department of Chemical Engineering , Ryerson University , 350 Victoria Street , Toronto M5B 2K3 , Canada
| | - Ali Lohi
- Department of Chemical Engineering , Ryerson University , 350 Victoria Street , Toronto M5B 2K3 , Canada
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Takaya Y, Xiao Y, Tsunazawa Y, Córdova M, Tokoro C. Mechanochemical degradation treatment of TBBPA: A kinetic approach for predicting the degradation rate constant. ADV POWDER TECHNOL 2022. [DOI: 10.1016/j.apt.2022.103469] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Discrete element simulation for mixing performances and power consumption in a twin-blade planetary mixer with non-cohesive particles. ADV POWDER TECHNOL 2022. [DOI: 10.1016/j.apt.2022.103437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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18
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POD-based identification approach for powder mixing mechanism in Eulerian–Lagrangian simulations. ADV POWDER TECHNOL 2022. [DOI: 10.1016/j.apt.2021.11.016] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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Jadidi B, Ebrahimi M, Ein-Mozaffari F, Lohi A. Mixing performance analysis of non-cohesive particles in a double paddle blender using DEM and experiments. POWDER TECHNOL 2022. [DOI: 10.1016/j.powtec.2022.117122] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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Jin X, Wang S, Shen Y. DEM study of the effect of impeller design on mixing performance in a U-shape ribbon mixer. ADV POWDER TECHNOL 2022. [DOI: 10.1016/j.apt.2021.10.026] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Tsunazawa Y, Soma N, Sakai M. DEM study on identification of mixing mechanisms in a pot blender. ADV POWDER TECHNOL 2022. [DOI: 10.1016/j.apt.2021.10.029] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
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22
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Kosaku Y, Tsunazawa Y, Tokoro C. Investigating the upper limit for applying the coarse grain model in a discrete element method examining mixing processes in a rolling drum. ADV POWDER TECHNOL 2021. [DOI: 10.1016/j.apt.2021.08.039] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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