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Analytical techniques are used to minimise the computational requirements of the model.
To minimise the computational effort it is suggested that an initial "near optimum" shape be used.
The model uses simplified loading functions in order to minimise the computational time required to obtain the numerical solution.
We investigate two clustering strategies, serial and parallel clustering, that allow to effectively exploit the solvent process design interactions to minimise the computational demands of the process synthesis stage.
The model is designed in such a way as to minimise the computational burden, while maintaining a full, joint representation of the probability density function of the precipitation process.
The main goal of this study was avoid such extended tails of large force errors and to minimise the computational effort at a given force accuracy.
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A hybrid finite element mesh, containing both shell and solid elements was proposed as the solution to minimising the computational resources required.
We determine good design for the coupling of patches by comparing the macroscale predictions from patch dynamics with the emergent macroscale on the entire domain, thus minimising the computational error of the multiscale modelling.
Furthermore, based upon this efficient implementation, we analyse which spectral/hp discretisation (which specific combination of mesh-size h and polynomial order P) minimises the computational cost to solve an elliptic problem up to a predefined level of accuracy.
In this paper a Confidence Interval Convergence Test (CICT) method is presented that minimises the computational burden required to demonstrate that a model design has passed/failed by calculating a CI for the population 95th percentile time, τP, rather than simply relying on τS determined from an arbitrary sample of 500 simulations as specified in the current guidelines.
In addition to this base non-rigid registration method, we have incorporated several other features to increase the accuracy of the result whilst minimising the computational time needed.
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