Investigation of the temporal and spatial flow features within the high‐shear mixer by modal decomposition techniques

Zhao, Shuchun; Li, Wei; Zhang, Jinli

doi:10.1002/aic.17967

Cited by 5 publications

(2 citation statements)

References 30 publications

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“…Researchers have used the C3D model on many models to extract the dynamic features of the video and achieved some results, but because C3D uses the traditional 3D convolution, which easily triggers the problem of the excessive amount of model parameters and the long video processing time In order to alleviate the above problems, this paper adopts the P3D network structure to extract the dynamic information of the video, and the core idea of P3D is to replace the original 3×3×3 convolution with 1×1×3 convolution of the 2D spatial convolution and 3×3×1 convolution of the one-dimensional temporal convolution [17].…”

Section: Dynamic Feature Extractionmentioning

confidence: 99%

Research on the Innovative Path of Ideological and Political Education in Colleges and Universities in the Context of Deep Learning

Cao

2023

Applied Mathematics and Nonlinear Sciences

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To construct an automatic question-and-answer system for Civics, a neural network and a self-attention mechanism are combined in this paper. Through the input layer of the neural network, the model remembers the semantic information of the Civics text that has been processed. Dynamic feature extraction is used to categorize and classify Civics questions in the system and determine the type of questions. The GLU network is used to predict the answers to the Civics and Politics questions, and the predicted results are normalized by combining the Softmax function, and the category with the highest probability is selected as the answer. The main mode of teaching afterward was to combine the automatic question-and-answer system with teaching. The results show that in the question and answer system, the highest accuracy rate is the practical cognition type of questions, with the accuracy rate fluctuating in the range of (0.8-0.9), and the accuracy rate of truth type and method type of questions fluctuates up and down in the range of 0.7. The percentage of students in the high marking stage increased by 0.1. In Civic Behavior, students’ patriotism increased by 0.15, and spirituality increased by 0.3.

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Section: Dynamic Feature Extractionmentioning

confidence: 99%

Research on the Innovative Path of Ideological and Political Education in Colleges and Universities in the Context of Deep Learning

Cao

2023

Applied Mathematics and Nonlinear Sciences

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“…In the case of periodic or quasi‐periodic flows, the DMD mode exhibits similarities to the POD mode. These two methods can be employed for comparative analysis when dealing with intricate flow phenomena 16–18 . Lamotte et al 19 conducted experimental research on the flow characteristics induced by a Rushton turbine, utilizing PIV technology.…”

Section: Introductionmentioning

confidence: 99%

Flow stirred by open turbine: A modal analysis of multiscale flow characteristics

Jin,

Bu,

Fan

et al. 2024

Asia-Pacific J Chem Eng

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The turbulence observed in the stirred tank is a result of the superposition of flows at different scales, each exerting various influences on the operational processes. To understand the flow characteristics associated with stirring, this paper undertakes particle image velocimetry (PIV) experimental research on an unbaffled tank stirred by an open turbine featuring four distinct blade deflection angles. The flow field in the unbaffled tank manifests as a double‐circulation flow pattern; however, it is worth noting that the blade deflection angle exerts a significant impact on the stirring process. Specifically, when the blade deflection angle reached 90°, the flow discharge aligned closely with the radial direction, accompanied by pronounced fluctuations in the high‐velocity region. The Lagrangian coherent structures (LCS) formed were subsequently extracted and subjected to finite‐time Lyapunov exponent (FTLE) analysis. Notably, a more regular wake pattern emerged in proximity to the blade tip, while a larger scale flow structure persisted along the flow direction. To systematically analyze the flow field stirred by the open turbine, modal analysis was employed. By reconstructing the flow field based on the principle of 50% energy content, the decomposition of flows at different scales was achieved. The turbulent kinetic energy (TKE) generated by the various scale flows was subsequently calculated, revealing that the high TKE values primarily originate from the large‐scale flow structure. Conversely, the TKE generated by the small‐scale flow exhibits a uniform distribution across different regions. Notably, in regions characterized by higher velocities, the peak TKE associated with the small‐scale flow also manifests; however, it is significantly smaller in magnitude compared to that generated by the original flow or the large‐scale flow.

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CFD simulation of an axial discharge rotor-stator mixer: LES versus RANS predictions

Minnick,

Janz,

Calabrese

2023

Chemical Engineering Research and Design

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Investigation of the temporal and spatial flow features within the high‐shear mixer by modal decomposition techniques

Cited by 5 publications

References 30 publications

Research on the Innovative Path of Ideological and Political Education in Colleges and Universities in the Context of Deep Learning

Research on the Innovative Path of Ideological and Political Education in Colleges and Universities in the Context of Deep Learning

Flow stirred by open turbine: A modal analysis of multiscale flow characteristics

CFD simulation of an axial discharge rotor-stator mixer: LES versus RANS predictions

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