Application of POD reduced-order algorithm on data-driven modeling of rod bundle

Kang, Huilun; Tian, Zhilong; Chen, Guangliang; Li, Lei; Wang, Tianyu

doi:10.1016/j.net.2021.07.010

Cited by 18 publications

(6 citation statements)

References 32 publications

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“…The test data is the temperature when M = 350 and 1,100, which are not included Frontiers in Energy Research frontiersin.org 07 Chen et al 10.3389/fenrg.2023.1155294 in the snapshot matrix. The shape of the input vector is (1,7) and the number of nodes in the three hidden layers are 100, 32, and 5 with activation functions of Tanh, Tanh, and Linear, respectively. The batch size is 8 and epoch is 100, loss function is the mean square error, optimizer is ADAM, and learning rate is 0.001.…”

Section: Case 2: Multiple Time-varying Boundarymentioning

confidence: 99%

Numerical and Experimental Studies on Small/Micro Nuclear Reactors

2024

Frontiers Research Topics

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Frontiers is more than just an open access publisher of scholarly articles: it is a pioneering approach to the world of academia, radically improving the way scholarly research is managed. The grand vision of Frontiers is a world where all people have an equal opportunity to seek, share and generate knowledge. Frontiers provides immediate and permanent online open access to all its publications, but this alone is not enough to realize our grand goals. Frontiers journal seriesThe Frontiers journal series is a multi-tier and interdisciplinary set of openaccess, online journals, promising a paradigm shift from the current review, selection and dissemination processes in academic publishing. All Frontiers journals are driven by researchers for researchers; therefore, they constitute a service to the scholarly community. At the same time, the Frontiers journal series operates on a revolutionary invention, the tiered publishing system, initially addressing specific communities of scholars, and gradually climbing up to broader public understanding, thus serving the interests of the lay society, too. Dedication to qualityEach Frontiers article is a landmark of the highest quality, thanks to genuinely collaborative interactions between authors and review editors, who include some of the world's best academicians. Research must be certified by peers before entering a stream of knowledge that may eventually reach the public -and shape society; therefore, Frontiers only applies the most rigorous and unbiased reviews. Frontiers revolutionizes research publishing by freely delivering the most outstanding research, evaluated with no bias from both the academic and social point of view. By applying the most advanced information technologies, Frontiers is catapulting scholarly publishing into a new generation. What are Frontiers Research Topics?Frontiers Research Topics are very popular trademarks of the Frontiers journals series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area.

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Section: Case 2: Multiple Time-varying Boundarymentioning

confidence: 99%

Numerical and Experimental Studies on Small/Micro Nuclear Reactors

2024

Frontiers Research Topics

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“…Kang et al [55] proposed a reduced-order model based on a machine-learning approach and proper orthogonal decomposition (POD) to reduce the calculation time of the Navier-Stokes equations in the CFD method. They applied the proposed method to reconstruct the rod bundle flow field.…”

Section: Cfdmentioning

confidence: 99%

Heat Transfer Coefficient Distribution—A Review of Calculation Methods

Duda

2023

Energies

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Determination of the heat transfer coefficient (HTC) distribution is important during the design and operation of many devices in microelectronics, construction, the car industry, drilling, the power industry and research on nuclear fusion. The first part of the manuscript shows works describing how a change in the coefficient affects the operation of devices. Next, various methods of determining the coefficient are presented. The most common method to determine the HTC is the use of Newton’s law of cooling. If this method cannot be applied directly, there are other methods that can be found in the open literature. They use analytical formulations, the lumped thermal capacity assumption, the 1D unsteady heat conduction equation for a semi-infinite wall, the fin model, energy conservation and the analogy between heat and mass transfer. The HTC distribution can also be calculated by means of computational fluid dynamics (CFD) modelling if all boundary conditions with fluid and solid properties are known. Often, the surface on which the HTC is to be determined is not accessible for any measuring sensors, or their installation might disturb the analysed phenomenon. It also happens that calculations using direct or CFD methods cannot be performed due to the lack of required boundary conditions or sufficiently proven models to analyse the considered physical phenomena. Too long a calculation time needed by CFD tools may also be problematic if the method should be used in the online mode. One way to solve the above problem is to assume an unknown boundary condition and include additional information from the sensors located at a certain distance from the investigated surface. The problem defined in this way can be solved by inverse methods. The aim of the paper is to show the current state of knowledge regarding the importance of the heat transfer coefficient and the variety of methods that can be used for its determination.

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“…Among them, the jet has a significant influence on the internal flow field of natural gas, which makes the flow field structure more complex, and it is necessary to reduce the order of the flow field to extract a smooth feature structure from several datasets. Proper orthogonal decomposition (POD) can be employed to effectively reduce the dimensionality of intricate high-dimensional systems [29]. Currently, the POD method is also widely used in the field of computational fluid dynamics.…”

Section: Introductionmentioning

confidence: 99%

Vortex of a Symmetric Jet Structure in a Natural Gas Pipeline via Proper Orthogonal Decomposition

Li,

Lu,

Zhao

et al. 2024

Processes

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The impact of particle addition jets on the flow field in natural gas pipelines was investigated, and the structural information of the flow field at different flow velocities in a symmetric jet flow was analyzed via numerical simulation. The results of coherent structures in the high-pressure natural gas pipeline reveal vortex structures of varying sizes both upstream and downstream of the jet flow. To determine the spatial distribution of the main vortex structures in the flow field, proper orthogonal decomposition (POD) mode analysis was performed on the unsteady numerical results. Moreover, the detailed spatial characteristics of the coherent vortex structures represented by each mode were obtained. The results indicate that the large-scale vortex structures within the pipeline are balanced and stable, with their energy increasing as the jet flow velocity increases. Additionally, higher-order modes exhibit significant shedding of small-scale vortex structures downstream of the jet flow. In this research, coherent structures present in symmetric particle addition jets are provided, offering theoretical support for future investigations on the distribution of particle image velocimetry (PIV) flowmeters.

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Application of POD reduced-order algorithm on data-driven modeling of rod bundle

Cited by 18 publications

References 32 publications

Numerical and Experimental Studies on Small/Micro Nuclear Reactors

Numerical and Experimental Studies on Small/Micro Nuclear Reactors

Heat Transfer Coefficient Distribution—A Review of Calculation Methods

Vortex of a Symmetric Jet Structure in a Natural Gas Pipeline via Proper Orthogonal Decomposition

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