Sentence examples for computational simulations for from inspiring English sources
Computational simulations for steady and unsteady cases generally agreed with their experimental counterparts.
The present experimental data are cross-referenced with computational simulations for identification of the major vortices in the flow.
Further validation concerning the quality of atomic mobilities is conducted with computational simulations for diffusion couples, the results of which are compared with experimental data.
The review highlights the importance of a combination of experimental data and computational simulations for the design of an optimal delivery system.
This study demonstrates a pathway of materials search based on computational simulations for proper media that can hold hydrogen at ambient conditions through physisorption.
Further validation concerning the quality of atomic mobilities is conducted with computational simulations for diffusion couples annealed at 1573 K for 50 h, the results of which are compared with experimental data.
High fidelity 3D computational simulation for gas liquid two-phase flow is getting important to simulate various thermal hydraulic phenomena in nuclear related components.
The direct computational simulation for multiple microdischarges is presently beyond our reach, thus the essential physics may be better understood on the framework of physics-based modeling.
Computational simulation for predicting mechanical properties of carbon nanotubes (CNTs) has been adopted as a powerful tool relative to the experimental difficulty.
Molecularly imprinted polymers (MIPs) were designed using computational simulation for the synthesis of high affinity synthetic receptors to be used for drug recognition and detection in combination with optical based biosensors.
The computational simulation for weather, seasonal, climate, and environment forecast of ever-increasing range of geophysical phenomena contributes enormously to understand and predict the complex processes in the Earth system, with close relation between the sophistication of prediction models and the availability of computational power [1].
