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Finally, I show how the different lattice configurations were obtained and list their parameters.
Optimal design configurations were obtained representing the best tradeoff between antagonistic objectives, i.e. the so-called non-dominant solutions.
Three optimal configurations were obtained by the Multi-Object Genetic Algorithm based on Genetic Aggregation response surface.
Optimized interface configurations were obtained by minimization of the total internal energy with respect to relative translation states of the adjoining grains and relaxations of all atomic positions.
For each consumer virtual panel, sample and descriptor configurations were obtained using Correspondence Analysis and the concordance between them and the reference configurations (obtained with all the consumers) were computed using the regression vector (RV) coefficient.
All of the parameters needed to draw these configurations were obtained from the Japan Seismic Hazard Information Station (J-Shis) site of the National Research Institute for Earth Science and Disaster Prevention (NIED, 2010).
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Non-trivial configurations are obtained involving modest solution times.
The moment rotation curves of the joint configurations are obtained from the corresponding simulations.
The most efficient configurations are obtained by lowering the air flow rate of the condenser fan.
Symbolic expressions for two different families of isotropic configurations are obtained.
The results of both types of generator configurations are obtained and compared.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com