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SLAWOMIR KOZIEL, ASSOCIATE PROF. | STANISLAV OGURTSOV, POSTDOC SCHOOL OF SCIENCE AND ENGINEERING | RU LECTURE MARATHON COMPUTATIONALLY EFFICIENT SIMULATION-DRIVEN DESIGN TECHNIQUES FOR MICROWAVE ENGINEERING

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  • SLAWOMIR KOZIEL, ASSOCIATE PROF. | STANISLAV OGURTSOV, POSTDOCSCHOOL OF SCIENCE AND ENGINEERING | RU LECTURE MARATHON

    COMPUTATIONALLY EFFICIENT SIMULATION-DRIVEN DESIGN TECHNIQUES FOR MICROWAVE ENGINEERING

  • www.hr.is

    Challenges of Simulation-Driven Microwave Design

    Contemporary microwave engineering relies more and more on CPU-intensive electromagnetic simulations

    Accurate evaluation of typical components can be very time consuming: from several minutes to many hours per simulation

    Typical microwave components: filters, SICs, LTCC, and antennas

    Computationally Efficient Simulation-Driven Design Techniques for Microwave Engineering | Koziel/Ogurtsov

  • www.hr.is

    Challenges of Simulation-Driven Microwave Design

    Traditional design methods that employ EM solver in an optimization loop are impractical due to:• High computational cost of EM simulation• Poor analytical properties of EM-based objective functions • Lack of sensitivity information or sensitivity expensive to compute

    Traditional approach: EM solver directly employed in the optimization loop:=> High CPU cost=> Fails to find satisfactory

    design

    Computationally Efficient Simulation-Driven Design Techniques for Microwave Engineering | Koziel/Ogurtsov

  • www.hr.is

    Surrogate-Based Microwave Design

    Computationally efficient simulation-driven design can be realized using physically-based surrogate models

    Key components: • High-fidelity (fine) model: CPU-intensive

    EM-simulated microwave structure• Low-fidelity (coarse) model: low-cost but

    physically-based representation (e.g., equivalent circuit)

    Coarse model is very fastbut usually lacks accuracy;To serve as a surrogate, it has to be corrected

    SurrogateModel

    Coarse Model Correction

    Computationally Efficient Simulation-Driven Design Techniques for Microwave Engineering | Koziel/Ogurtsov

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    Traditional approach Surrogate-Based

    Computationally Efficient Simulation-Driven Design Techniques for Microwave Engineering | Koziel/Ogurtsov

    Surrogate-Based Microwave Design

    Surrogate-based design replaces direct optimization of the fine model by iterative re-optimization and updating of the surrogate:

  • www.hr.is

    Surrogate-Based Microwave Design: Space Mapping

    Probably the most successful surrogate-based design technique in microwave engineering is space mapping (SM)

    Coarse model correction methods used by SM:(a) Domain distortion (input SM) (b) Response distortion (output SM)

    (c) Exploiting physically-based (d) Exploiting free parametersdegrees of freedom (implicit SM) (frequency SM)

    Example of combined SMsurrogate model:

    Computationally Efficient Simulation-Driven Design Techniques for Microwave Engineering | Koziel/Ogurtsov

  • www.hr.is

    Example: Design of Microstrip Hairpin Filter

    Fine model: Simulation time 17 hours per design!

    Coarse model: Equivalent circuit – simulation time less than 0.1 s

    S1

    εr

    H

    S2

    L1

    L2

    La

    L3 L4

    2LcLbS2

    S1LbLa

    L4L3

    L2

    L1

    Computationally Efficient Simulation-Driven Design Techniques for Microwave Engineering | Koziel/Ogurtsov

  • www.hr.is

    Example: Design of Microstrip Hairpin Filter

    Traditional design methods fail for this example

    Space Mapping: Optimal design obtained after 5 EM simulations!

    Initial responses and design specifications Responses of the optimized filter

    Computationally Efficient Simulation-Driven Design Techniques for Microwave Engineering | Koziel/Ogurtsov

  • www.hr.is

    Simulation-Based Tuning

    Design process can be performed in an even more efficient way using the concept of tuning

    Simulation-based tuning is an invasive technique, where the structure under consideration is “cut” and the circuit-based tuning components are inserted

    The resulting surrogate (“tuning” model)is very fast and yet accurate as it containsthe “image” of the fine model at the initial design

    Bρ=∇ Do

    0=∇ Bo

    ω +D J

    jω∇× =−E

    ED ε=

    HB μ=

    j∇× =H

    Computationally Efficient Simulation-Driven Design Techniques for Microwave Engineering | Koziel/Ogurtsov

  • www.hr.is

    Example: Chebyshev Filter

    Chebyshev filter geometry

    Fine model with places for inserting the tuning ports

    Tuningmodel

    L3

    Input Output

    W1

    L4

    S2

    S1

    S2

    L5L1

    L2

    W

    W

    WW

    1

    34

    56

    1112

    1314

    1516

    1718

    78

    91019

    20

    21 22 23 24

    25 26 27 28

    2

    S1

    Computationally Efficient Simulation-Driven Design Techniques for Microwave Engineering | Koziel/Ogurtsov

  • www.hr.is

    Example: Chebyshev FilterThe coarse (dashed line) and fine model (solid line) response at the initial design:

    Fine model response after one (!) iteration of the tuning-based optimization algorithm:

    Computationally Efficient Simulation-Driven Design Techniques for Microwave Engineering | Koziel/Ogurtsov

  • www.hr.is

    Engineering Optimization & Modeling Center (EOMC)

    EOMC develops surrogate-based techniques for computationally expensive real-world engineering design problems

    Applications: microwave/RF engineering, aerospace design, aeroacoustics, hydrodynamics, oil industry

    Website: http://www.ru.is/kennarar/koziel/eoml_index.html

    Computationally Efficient Simulation-Driven Design Techniques for Microwave Engineering | Koziel/Ogurtsov

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