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We demonstrate the performance of the multiphysics algorithm by solving a number of buoyant flow problems.
The filter gains will be given for both full-order and reduced-order filters by solving a number of LMIs.
The dynamics of the system are modelled by solving a number of system mass and energy balances, as well as a population balance equation.
The efficacy of the overall scheme for the time-domain modeling of electrically large, and computationally challenging, problems is illustrated by solving a number of plane as well as non-plane waveguide problems.
In the method, the state of the system is determined by solving a number of decoupled problems and, as a result, implementation of the method is computationally efficient even when the dimension of the system is large.
The numerical results, obtained by solving a number of optimal control problems, are arranged into contour plots, characterized by different and well-defined behaviors depending on the value of the initial spacecraft propulsive acceleration, the final orbit radius, and the thruster's specific impulse.
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The designed schemes are evaluated by solving a numbers of BVPs for the PFDE and comparing with standard results.
These generating methods specialize either in finding multiple Pareto-optimal solutions in a single simulation run or specialize in maintaining a good diversity by systematically solving a number of scalarizing problems.
Feasible solutions can be obtained by solving a finite number of linear matrix inequalities (LMIs) embedded within a genetic algorithm (GA).
Here a modified genetic algorithm using quasi-random sequences in the initial population is tested by solving a large number of continuous benchmark problems from the literature.
By leveraging network flow optimization algorithms, we discover a few expressed transcripts among the exponential number of candidates by solving a problem with a number of variables polynomial in n.
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by solving a parameter-dependent
by solving a difference
by solving a linear
by solving a missile
by solving a benchmark
by solving a test
by solving a series
by solving a revenue
by solving a time-dependent
by solving a set
by solving a min-max
by solving a delay-dependent
by solving a literature
by solving a sequence
by solving a sub-problem
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com