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A methodology is introduced where principal component analysis (PCA) and fractal profile description are combined for characterizing and modelling computational rough surfaces for their use in computer-aided-engineering (CAE) processes.
A concept of multiscale modelling of product manufacturing based on integration of three modelling methods currently applied at different scales of length and time: process system modelling, computational fluid dynamics and computational chemistry was presented.
The rapid rise in desktop computing power has enabled relatively easy access to sophisticated applications in molecular modelling, computational chemistry, and machine learning, which have led to a burgeoning of the capability to produce QSARs for large and complex datasets.
Chemoinformatics and Drug Discovery Chemical Information, Patents and Databases Molecular Modelling Computational Materials Science and Nanotechnology.
In this study, the mechanical integrity of advanced multilayer nano-interconnects, as metal/dielectric nano-composites, was investigated using a combination of analytical modelling, computational mechanics and experiments.
As with modelling, computational methods are increasingly able to step up and provide insight where more expensive experimental methods are unable to, with programs such as SIFT (11), Site Directed Mutator (SDM; 12, 13) and PolyPhen (14) and mutant Cutoff Scanning Matrix (mCSM; 15) being developed in recent years.
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This work combines multiple experimental data sets [6], [7], [29] to model computational operations that map onto specific regions of the inferior colliculus.
This results in faster model execution (in comparison to table-driven computations) and allows more flexible model computational structure (multiple time sweeps, indexed loops).
The simulation model, computational techniques, and parallel algorithms are discussed.
These models are: spectral optical model, computational fluid dynamics model and building energy simulation model.
Besides validating proposed models, computational results confirm a better performance of modified NSGA-II versus traditional one.
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