Sensitivity and Dependence analysis are used to filter non-informative design parameters in the study, ranking the informative ones with respect to their influence on the given response function and selecting parameters that provide the best approximation. As a result, it ensures time and resource saving on experiments and smarter decision-making based on the detailed knowledge of the design space. Adaptive DoE with Uniform, Maximum Variance and Integrated Mean Squared Errors Gain - Maximum Variance criteria.ĭesign of Experiments allows controlling the process of surrogate modeling via adaptive sampling plan, which benefits the quality of approximation.Composite, D-optimal, IV-optimal, Box Behnken.Sequential techniques ( Random, Halton, Sobol, Faure sequences).Batch techniques (Random, Full-Factorial, Latin hypercube sampling, Optimal LHS).Design of Experimentsĭesign of Experiments includes the following techniques: Optimization", en.wikipedia.Design of Experiments allows exploring design space using as small number of observations as possible, enables reliable surrogate-based optimization and generates a training sample for building an accurate approximation model. Wikipedia, "List of optimization software", en./wiki/ List_of_optimization_software, "Design, simulation and optimization of a slotted waveguide array withĬentral feed and low sidelobes", IEEE-APS Simulation to design resonant cavity antennas", Int. Of external MATLAB-based optimization with full-wave
#Cst microwave studio wikipedia software
(VBA in CST MWSĮt al., "Antenna design explorer: a GUI software tool for efficientĪntenna design optimization", Loughborough Antenna Propagat. ( LAPC), 2017Īutomation of UHF RFID tag antenna using a genetic algorithm linked with MWS CST", IEEE 4th Int. " MATLAB-based multi-objective optimization ofīroadband circularly polarized antennas", Loughborough Antenna Propagat. Symp., 2014 Simultaneous optimization of gain and returnĭesign by Simulation-Driven Optimization, Springer, 2014 Of antenna structures in multi-dimensional design spaces", IEEE APS Int. Koziel et al., "EM-driven multi-objective optimization 2007 PSO applied to aperiodic antenna arrays Optimization for antenna designs: real-number, binary, single-objective and multiobjective implementations", IEEE Trans. Rahmat-Samii, "Advances in particle swarm "Evaluation of genetic algorithms, particle swarm optimization, andįirefly algorithms in antenna design", 13th Int. "Seven bands loop antenna optimized by using particle swarm optimizationĪlgorithm", Int. Appl., 2007 Matlab optimization + CST Studio EM "Solution of the antenna placement problem by means of global optimizationĮt al., "Novel coplanar ultra-wideband antennas designed by global Gain [ P r : power radiated from the antennaĮt al., "Virtual prototyping of diplexers by using CST Studio", 15th V – : voltage (electric field) reflected from the V + : voltage (electric field) incident on the antenna
Primary Antenna Parameters To Be Optimized Simulation engine: MATLAB, commercial, in-houseĥ. Optimizer calculates the most effective placement of decoupling capacitors Optimizer for printed circuit board (PCB) design, the Decap
Parameters, systems without a good initial model Good for complex problem domains with relatively few PSO (particle swarm optimization): Global Through multiple generations with random parameter mutation. GA (genetic algorithm): Evolutionary approach. Good for problems with sensitivity information Builds a linear model on primary data in a General optimizer for complex problem domains CMS-ES (covariance matrix adaptation evolutionary strategy): the mostĬomplicated of the global optimizers. Risk of converging to a local minimum rather than the best overall Optimization methods: Evolutionary algorithm Targets of optimization: Performance vs frequency of maximum, gainįlatness, front-to-back ratio, standing wave ratio Optimization parameters: Wire length, wire diameter, wire spacing Radiation pattern, Lower left = Diagonal plane cross-polarized radiation pattern,Ģ) LPDA (log periodic dipole array) Maximum variation range in a single iteration:įigure: Upper left = H-plane radiation pattern, Upper right = E-plane The problem has one maximum and one minimum. The problem hasįigure: A two-parameter optimization problem. Several dimensions to obtain the best design.įigure: A two-parameter optimization problem.
#Cst microwave studio wikipedia manual
Manual antenna design: Adjust a few antenna dimensions and obtain good
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