Applied Mathematics and Computational Physics
As faster and more efficient numerical algorithms become available, the understanding of the physics and the mathematical foundation behind these new methods will play an increasingly important role. This Special Issue provides a platform for researchers from both academia and industry to present th...
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| Year of Publication: | 2021 |
| Language: | English |
| Physical Description: | 1 electronic resource (273 p.) |
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| 520 | |a As faster and more efficient numerical algorithms become available, the understanding of the physics and the mathematical foundation behind these new methods will play an increasingly important role. This Special Issue provides a platform for researchers from both academia and industry to present their novel computational methods that have engineering and physics applications. | ||
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| 653 | |a radial basis functions | ||
| 653 | |a finite difference methods | ||
| 653 | |a traveling waves | ||
| 653 | |a non-uniform grids | ||
| 653 | |a chaotic oscillator | ||
| 653 | |a one-step method | ||
| 653 | |a multi-step method | ||
| 653 | |a computer arithmetic | ||
| 653 | |a FPGA | ||
| 653 | |a high strain rate impact | ||
| 653 | |a modeling and simulation | ||
| 653 | |a smoothed particle hydrodynamics | ||
| 653 | |a finite element analysis | ||
| 653 | |a hybrid nanofluid | ||
| 653 | |a heat transfer | ||
| 653 | |a non-isothermal | ||
| 653 | |a shrinking surface | ||
| 653 | |a MHD | ||
| 653 | |a radiation | ||
| 653 | |a multilayer perceptrons | ||
| 653 | |a quaternion neural networks | ||
| 653 | |a metaheuristic optimization | ||
| 653 | |a genetic algorithms | ||
| 653 | |a micropolar fluid | ||
| 653 | |a constricted channel | ||
| 653 | |a MHD pulsatile flow | ||
| 653 | |a strouhal number | ||
| 653 | |a flow pulsation parameter | ||
| 653 | |a multiple integral finite volume method | ||
| 653 | |a finite difference method | ||
| 653 | |a Rosenau-KdV | ||
| 653 | |a conservation | ||
| 653 | |a solvability | ||
| 653 | |a convergence | ||
| 653 | |a transmission electron microscopy (TEM) | ||
| 653 | |a convolutional neural networks (CNN) | ||
| 653 | |a anomaly detection | ||
| 653 | |a principal component analysis (PCA) | ||
| 653 | |a machine learning | ||
| 653 | |a deep learning | ||
| 653 | |a neural networks | ||
| 653 | |a Gallium-Arsenide (GaAs) | ||
| 653 | |a radiation-based flowmeter | ||
| 653 | |a two-phase flow | ||
| 653 | |a feature extraction | ||
| 653 | |a artificial intelligence | ||
| 653 | |a time domain | ||
| 653 | |a Boltzmann equation | ||
| 653 | |a collision integral | ||
| 653 | |a convolutional neural network | ||
| 653 | |a annular regime | ||
| 653 | |a scale layer-independent | ||
| 653 | |a petroleum pipeline | ||
| 653 | |a volume fraction | ||
| 653 | |a dual energy technique | ||
| 653 | |a prescribed heat flux | ||
| 653 | |a similarity solutions | ||
| 653 | |a dual solutions | ||
| 653 | |a stability analysis | ||
| 653 | |a RBF-FD | ||
| 653 | |a node sampling | ||
| 653 | |a lebesgue constant | ||
| 653 | |a complex regions | ||
| 653 | |a finite-difference methods | ||
| 653 | |a data assimilation | ||
| 653 | |a model order reduction | ||
| 653 | |a finite elements analysis | ||
| 653 | |a high dimensional data | ||
| 653 | |a welding | ||
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