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eg. and we take the hit of repeated evaluation of gnabar_hh.
The discrete equations are linearized using finite differences and the Jacobian is computed using repeated evaluation of the residuals.
and not only do we take the hit of repeated evaluation of gnabar_hh but the statement must be interpreted each time.
This stochastic sampling requires repeated evaluation of system model response and corresponds to the computationally most intensive part of the algorithm.
Like the reliability-based design optimization (RBDO), the NRBDO application for practical engineering structure is hindered by the huge computational effort involved in the repeated evaluation of non-probabilistic constraints.
Designing control systems using multiobjective genetic algorithms can lead to a substantial computational load as a result of the repeated evaluation of the multiple objectives and the population-based nature of the search.
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Analog circuit synthesis ofen requires repeated evaluations of circuit under design to reach the final design goals.
Repeated evaluations of expensive computer models in applications such as design optimization and uncertainty quantification can be computationally infeasible.
Conventionally, this requires repeated evaluations of the failure probability for different values of the design parameters, which is a direct but computationally expensive task.
Topology optimization problem requires repeated evaluations of the objective function and design sensitivity in the design domain with various density distributions.
Computational challenges in this construction arise from the need for repeated evaluations of the forward model (e.g., in the context of Markov chain Monte Carlo) and are compounded by high dimensionality of the posterior.
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