BOOK OF ABSTRACTSfiles.iam.metu.edu.tr/beyond2019/booksofabstract_beyond2019.pdf• Çatı cafe (Ac31 at the map) has wide range of options and it is a 2 min walk from the venue. •

BOOK OF ABSTRACTS

Middle East Technical UniversityCulture and Convention Center

Ankara, TurkeySeptember 09–11, 2019

ii BEYOND 2019: Computational Science and Engineering Conference

Institute of Applied Mathematics, Middle East Technical University, 06800 Ankara, Turkey

http://files.iam.met Workshop u.edu.tr/beyond2019http://iam.metu.edu.tr/

Contents

Foreword 1

Venue and Local Info 5

Sponsors 9

Programme 11

Abstracts 17Solving Magnetostatic Problems Using OpenFOAM

Saleh K. Abuhanieh, Hasan U. Akay . . . . . . . . . . . . . . . . . . . . . . . . . 19Turbulence Behind Artificially–Diffused Laminar Solutions

Mustafa Aggul . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20Adjoint based Design Optimization of a Subsonic Intake

Ali Ahmed, İsmail H. Tuncer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21The Instability of Non–Newtonian Boundary Layer Flows over Rough Rotating Disks

Aishah Alqarni, Burhan Alveroğlu, Paul Griffiths, Stephen Garett . . . . . . . . . . 22A High-Order Numerical Method for Solving Nonlinear Singular Boundary Value Problems

Arising in Various Physical ModelSoner Aydınlık, Ahmet Kiriş . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

Biocomputational Platform for Template-Based Protein Docking Prediction Using 3D Ge-ometric DescriptorsRicardo Román-Brenes, Francisco Siles Canales, Paula Gochez . . . . . . . . . . . 24

On the Fracture Surface Morphology under Ductile Plate Tearing at Steady StateŞahin Çelik, Cihan Tekoğlu, Kim Lau Nielsen . . . . . . . . . . . . . . . . . . . . . 26

Analysis of Caching Process in a Line Network via Epidemic ModelsMustafa Kağan Çetin, Meltem Gölgeli . . . . . . . . . . . . . . . . . . . . . . . . 27

Discontinuous Galerkin Methods for Convection Diffusion Equations with Random Coeffi-cientsPelin Çiloğlu, Hamdullah Yücel . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

Modelling Spatio-Temporal Temperature-Mediated Bacteria-Phage InteractionHalil İbrahim Eğilmez, Andrew Yu. Morozov . . . . . . . . . . . . . . . . . . . . . 29

The Time Varied Control of Unsteady MHD EquationsCansu Evcin, Ömür Uğur, Münevver Tezer-Sezgin . . . . . . . . . . . . . . . . . . 30

Computational Modeling of Shrinkage-Induced Cracking in ConcreteMehran Ghasabeh, Serdar Göktepe . . . . . . . . . . . . . . . . . . . . . . . . . . 31

The Impact of Vaccine Skepticism and Migration on the Global Measles OutbreakMeltem Gölgeli . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

iii

iv BEYOND 2019: Computational Science and Engineering Conference

Geometric Design of Gradient Index Lenses via Heuristic Optimization and Full-WaveSimulationsSadri Güler, Özgür Eriş, Özgür Ergül . . . . . . . . . . . . . . . . . . . . . . . . . 34

A Quasi-Incompressible and Quasi-Inextensible Finite Element Implementation of FibrousSoft Biological TissuesOsman Gültekin, Burak Rodoplu, Hüsnü Dal . . . . . . . . . . . . . . . . . . . . . 35

Finite–Parameter Feedback Stabilization of Original Burgers Equations and Burgers’ Equa-tion with Nonlocal NonlinearitiesSerap Gümüş, Varga Kalantarov . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

Uncertainty Modelling of 3D Printed Lattice Structures Using Random FieldOlgun Utku Güngör, Recep Muhammet Görgülüarslan . . . . . . . . . . . . . . . . 37

Heat Transfer of MHD Flow with Variable Viscosity and Hall EffectMerve Gürbüz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

Filtering and Smoothing in Stochastic Modeling of Biological SystemsMerve Haksever, Derya Altıntan, Ömür Uğur . . . . . . . . . . . . . . . . . . . . . 39

Observer Design for the Dynamic Modelling of Arabidopsis Flowering Time Gene Regu-latory NetworkEmrah Haspolat, Benolt Huard, Krishna Busawon . . . . . . . . . . . . . . . . . . 40

Decontaminating Nitrate Containing Groundwater with Pump and Fertilize Application toMaize Farms, But Where? Finite Element Method Utilization with HYDRUS 1DGüray Hatipoğlu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

Computational Electromagnetic Simulations of Zero-Index MaterialsHande İbili, Barışcan Karaosmanoğlu, Özgür Ergül . . . . . . . . . . . . . . . . . 42

Computational Design of Enhanced Plasmonic Nanotraps for Particle Sensing ApplicationsGöktuğ Işıklar, Özgür Ergül . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

Accelerating Electrically Large-Scale Electromagnetic Simulations using Machine Learn-ingBarışcan Karaosmanoğlu, Özgür Ergül . . . . . . . . . . . . . . . . . . . . . . . . 44

Design and Simulations of Nano-Optical Couplers with Genetic Algorithms and MLFMAGökhan Karaova, Özgür Ergül . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

DRBEM Solution of Magnetohydrodynamic Duct Flow under Time-varied Oblique Mag-netic FieldElif Ebren Kaya, Münevver, Tezer-Sezgin . . . . . . . . . . . . . . . . . . . . . . 46

Hybrid Wavelet-Neural Network Models for Multivariate Time Series DataDeniz Kenan Kılıç, Ömür Uğur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

Hyperspectral Target Detection by using Superpixels and Signature Based MethodsMustafa Kütük, Alper Koz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

Reduced Order Modelling of Diffusive Lotka-Volterra EquationsNihan Man, Süleyman Yıldız . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

A Micromechanically based Multi-Scale Constitutive Model for Semi-Crystalline PolymersH. Emre Oktay, Ercan Gürses, Serdar Göktepe . . . . . . . . . . . . . . . . . . . . 51

CFD-based Optimization of Liquid Rocket Fuel InjectionMuhammad Omair, Hasan U. Akay . . . . . . . . . . . . . . . . . . . . . . . . . . 52

Multi-Objective Topology Optimization of Thermal-Fluid Problems using OpenFOAMNiyazi Şenol, Hasan U. Akay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54



BEYOND 2019: Computational Science and Engineering Conference v

Approximation of the Maxwell Eigenvalue Problem using a Residual based Stabilized Fi-nite Element MethodÖnder Türk, Ramon Codina, Daniele Boffi . . . . . . . . . . . . . . . . . . . . . . 56

An Approximation of the MHD Stokes Eigenvalue Problem with the use of ChebyshevSpectral Collocation MethodMünevver Tezer-Sezgin, Önder Türk . . . . . . . . . . . . . . . . . . . . . . . . . 57

Reduced Order Modelling of Coupled Korteweg de Vries EquationsMurat Uzunca, Süleyman Yıldız . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

Computation of a Solution of the Initial Value Problem for Dynamic Motion Equations inQuasicrystalsValery Yakhno . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

Transition to Chaos in Planar Gas Discharge-Semiconductor System in Nitrogen: Effect ofFluid Modelling ApproachCihan Yeşil, Ísmail Rafatov . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

Analysis of Analog Half Center Oscillator and Central Pattern Generator Circuits Employ-ing Memristors in MATLABOsman Zeki Yılmaz, Itır Köymen . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

Speakers 64

Authors 65



vi BEYOND 2019: Computational Science and Engineering Conference



BEYOND 2019: Computational Science and Engineering Conference 1

FOREWORD

Welcome to BEYOND 2019: Computational Science and Engineering Conference, which is a forumfor discussion of basic aspects and new trends in computational science and engineering on the highestlevel of national expertise in Turkey. The first of BEYOND conference was held on October 20-21,2018 in Middle East Technical University. BEYOND 2019 will be held on September 09–11, 2019 inHall A, Culture and Convention Center of Middle East Technical University with over 100 participantsand 38 talks.

Over the past two decades, computational science and engineering (CSE) has become an increas-ingly important part of research in academia, industry, and laboratories. Mathematics-based advancedcomputing is now a prevalent means of discovery and innovation in essentially all areas of science,engineering, technology, and society, and the CSE community is at the core of this transformation.The purpose of this conference is to bring together researchers and scientists from a diversity of sub-disciplines from the fields of computational mathematics and engineering in Turkey. Our aim is tocreate a stimulating atmosphere where researchers can meet and hear about each other’s work, holddiscussions, exchange of ideas and experiences and hopefully initiate future collaborations. The scopeof the conference is quite broad as it aims to bring together scientists from a diversity of subdisciplinesfrom the fields of computational science and engineering such as

• Boundary Element Methods

• Computational Fluid Dynamics

• Computational Mechanics of Solids

• Computational Modeling of Cardiac Electromechanics

• Fast Algorithms for the Solution of Electromagnetics Problems

• Finite Element Discretisation

• GPU Computation

• Mathematical Modelling in Medicine and Biology

• Medical Imagining

• Micro-Architectured Materials

• Micro-Macro Modeling of Rubbery and Glassy Polymers

• Numerical Linear Algebra

• Numerical Optimization

• Parallel Computing

• PDE-Constrained Optimization

• Porous Media and Poroelasticity

• Surface Partial Differential Equations



2 BEYOND 2019: Computational Science and Engineering Conference

• Uncertainty Quantification

We would like to thanks to all the participants with special emphasis to those who will enhance thequality of this workshop with their contributed talks.

Scientific Advisory Committee:

• Hasan Umur Akay, Department of Mechanical Engineering, Atılım University

• Tanıl Ergenç, Department of Mathematics, Atılım University

• Özgür Ergül, Department of Electrical and Electronics Engineering, METU

• Vakur Ertürk, Department of Electrical and Electronics Engineering, Bilkent University

• Nevzat Güneri Gençer, Department of Electrical and Electronics Engineering, METU

• Serdar Göktepe, Department of Civil Engineering, METU

• Ercan Gürses, Department of Aerospace Engineering, METU

• Ali Javili, Department of Mechanical Engineering, Bilkent University

• Murat Manguoğlu, Department of Computer Engineering, METU

• Emre Mengi, Department of Mathematics, Koç University

• Songül Kaya Merdan, Department of Mathematics, METU

• Kerem Pekkan, Department of Mechanical Engineering, Koç University

• Cüneyt Sert, Department of Mechanical Engineering, METU

• Cihan Tekoğlu, Department of Mechanical Engineering, TOBB University of Economics andTechnology

• Önder Türk, Department of Mathematics, Gebze Technical University

• Ömür Uğur, Institute of Applied Mathematics, METU

• Murat Uzunca, Department of Mathematics, Sinop University

• Hamdullah Yücel, Institute of Applied Mathematics, METU

Organizing Committee:

• Özgür Ergül, Department of Electrical and Electronics Engineering, METU

• Serdar Göktepe, Department of Civil Engineering, METU

• Ercan Gürses, Department of Aerospace Engineering, METU




• Murat Manguoğlu, Department of Computer Engineering, METU


Local Organizers:

• Pelin Çiloğlu, Institute of Applied Mathematics, METU

• Mustafa Kütük, Institute of Applied Mathematics, METU

• Eda Oktay, Institute of Applied Mathematics, METU

• Ömür Uğur, Institute of Applied Mathematics, METU

• M. Alp Üreten, Institute of Applied Mathematics, METU





VENUE AND LOCAL INFO

Venue

Congress will be held in Hall A, Culture and Convention Center of Middle East Technical Uni-versity, Ankara, Turkey.

Middle East Technical University (METU) is a leading national university which is internationallyacknowledged and renowned in research, education and public service for society, humanity, and na-ture, in an environment nurturing, creative and critical thinking, innovation, leadership, and universalvalues. There are 107 graduate and 69 doctorate programs available in Graduate Schools of Natu-ral Sciences, Social Sciences, Informatics, Applied Mathematics and Marine Sciences. Marine Sci-ences conducts the academic program studies at İçel-Erdemli. The language of instruction at METUis English. METU School of Foreign Languages takes the initiative to teach English to students atPreparatory School. Owing to the quality academic education that emphasizes merit and excellence inscientific, cultural and intellectual studies as well as owing to the accomplished and qualified METUgraduates, the University has become one of the distinguished and respectable institutions of Turkey.Today, the University is proud to employ about 791 faculty (professors, associate professors etc.), 225academic instructors and 1.273 research assistants. It is a great pleasure to offer education to over28.000 students. The total number of the alumni now is above 120.000.

Institute of Applied Mathematics (IAM) is an interdisciplinary centre fostering various researches andteaching activities in mathematical sciences. A major aim of IAM is to coordinate mathematics-basedresearch at METU and to initiate and undertake collaborative research with industry. The Institute ofApplied Mathematics began functioning in the academic year 2002-03 by offering Master of Science(MSc) degrees in Financial Mathematics, Scientific Computing and Cryptography. The Cryptographydepartment was the only department offering Doctor of Philosophy (PhD) at that time. In the springsemester of the academic year 2004-05, IAM offered PhD in Financial Mathematics and ScientificComputing to cater the growing demands of professionally skilled manpower in Applied Mathemat-ics. IAM consists of four departments (programmes): Actuarial Sciences, Cryptography, FinancialMathematics and Scientific Computing.

Local Info

Food on campus: There are various options at campus:

• Çatı cafe (Ac31 at the map) has wide range of options and it is a 2 min walk from the venue.

• The Social Building (Sosyal Bina, Hc1 at the map) also has somewhat wide range of options,again 2 min walk from the venue.

• There is a small shopping mall on campus across the tennis courts (Çarşı, M1 at the map) whereyou can find various restaurants and fast food places.


http://files.iam.met Workshop u.edu.tr/beyond2019https://www.metu.edu.tr/http://iam.metu.edu.tr/http://iam.metu.edu.tr/


Accommodation at METU

The Organizing Committee has not booked any guest house located inside the campus of Middle EastTechnical University for accommodation of delegates. However, delegates can make booking at

• METU Guest House

• Aysel Sabuncu Guest House

Please, check METU Accommodation (http://stm.metu.edu.tr/) for more information.

Accommodation at Hotels

Hotels close to METU include: Movenpick, JW Marriot Hotel Ankara, Dafne, Holiday Inn, The GreenPark Hotel Ankara, Merya Palace, Bilkent hotel and Conference Center Ankara. These are in a dis-tance between 3 and 4 km from the Metu campus entrance.


http://files.iam.met Workshop u.edu.tr/beyond2019http://stm.metu.edu.tr/http://iam.metu.edu.tr/


SPONSORS

We thank cordially our sponsors for their contributions to BEYOND 2019: Computational Scienceand Engineering Conference.

AP/MTT/EMC/ED Turkey Chapter




PROGRAMME

09 September (Monday Afternoon)

12:00–13:30 Registration and Refreshments

13:30–14:00 Welcoming Remarks

METU SIAM Student Chapter

METU IEEE AP/MTT/EMC/ED Chapter

14:00–15:20 14:00–14:20: Münevver Tezer and Önder Türk, An approximation of theMHD Stokes Eigenvalue Problem with the use of Chebyshev Spectral Collo-cation Method

Chair:HamdullahYücel

14:20–14:40: H. Emre Oktay, Serdar Göktepe and Ercan Gürses, A Microme-chanically based Multi-Scale Constitutive Model for Semi-Crystalline Poly-mers

14:40–15:00: Murat Uzunca and Süleyman Yıldız, Reduced Order Modellingof Coupled Korteweg de Vries Equation

15:00–15:20: Şahin Çelik, Cihan Tekoğlu and Kim Lau Nielsen, On the Frac-ture Surface Morphology under Ductile Plate Tearing at Steady State

15:20–15:40 Coffee Break

15:40–17:00 15:40–16:00: Olgun Utku Güngör and Recep M. Görgülüarslan, UncertaintyModelling of 3D Printed Lattice Structures using Random Field

Chair:MuratUzunca

16:00–16:20: Merve Gürbüz, Heat Transfer of MHD Flow with Variable Vis-cosity and Hall Effect

16:20–16:40: Soner Aydınlık and Ahmet Kiris, A High-Order NumericalMethod for Solving Nonlinear Singular Boundary Value Problems Arising inVarious Physical Model

16:40–17:00: Göktuğ Işıklar and Özgür Ergül, Computational Design of En-hanced Plasmonic Nanotraps for Particle Sensing Applications

17:15–19:00 Welcome Reception: Institute of Applied Mathematics Building




10 September (Tuesday Morning)

09:00 - 10:40 09:00–09:20: Muhammad Omair and Hasan U. Akay, CFD-Based Optimiza-tion of Liquid Rocket Fuel Injection

09:20–09:40: Merve Haksever, Ömür Uğur and Derya Altıntan, Filtering andSmoothing in Stochastic Modelling of Biological Systems

Chair:EmreMengi

09:40–10:00: Gökhan Karaova and Özgür Ergül, Design and Simulations ofNano-Optical Couplers with Genetic Algorithms and MLFMA

10:00–10:20: Önder Türk, Ramon Codina and Daniele Boffi, Approximationof the Maxwell Eigenvalue Problem using a Residual Based Stabilized FiniteElement Method

10:20–10:40: Niyazi Şenol and Hasan U. Akay, Multi-Objective Topology Op-timization of Thermal-Fluid Problems Using OpenFOAM


11:00–12:20 11:00–11:20: Osman Gültekin, Burak Rodoplu and Hüsnü Dal, A Quasi-Incompressible and Quasi-Inextensible Finite Element Implementation of Fi-brous Soft Biological Tissues

Chair:ErcanGürses

11:20–11:40: Pelin Çiloğlu and Hamdullah Yücel, Discontinuous GalerkinMethods for Convection Diffusion Equations with Random Coefficients

11:40–12:00: Mehran Ghasabeh and Serdar Göktepe, Computational Mod-elling of Shrinkage-Induced Cracking in Concrete

12:00–12:20: Mustafa Ağgül, Turbulence Behind Artificially-Diffused Lami-nar Solutions

12:20–14:00 Lunch




10 September (Tuesday Afternoon)

14:00–15:40 14:00–14:20: Halil İbrahim Eğilmez and Andrew Yu Morozov, ModellingSpatio-Temporal Temperature-Mediated Bacteria-Phage Interaction

14:20–14:40: Valery Yakhno, Computation of a Solution of the Initial ValueProblem for Dynamic Motion Equations in Quasicrystals

Chair:SerdarGöktepe

14:40–15:00: Cansu Evcin, Ömür Uğur and Münevver Tezer-Sezgin, TheTime Varied Control of Unsteady MHD Equations

15:00–15:20: Mustafa Kağan Çetin and Meltem Gölgeli, Analysis of CachingProcess in a Line Network via Epidemic Models

15:20–15:40: Cihan Yeşil and İsmail Rafatov, Transition to Chaos in PlanarGas Discharge-Semiconductor System in Nitrogen: Effect of Fluid ModellingApproach


16:00–17:20 16:00–16:20: Mustafa Kütük and Alper Koz, Hyperspectral Target Detectionby using Superpixels and Signature Based Methods

Chair:CansuEvcin

16:20–16:40: Sadri Güler, Özgür Eriş and Özgür Ergül, Geometric Design ofGradient Index Lenses via Heuristic Optimization and Full-Wave Simulations

16:40–17:00: Güray Hatipoğlu, Decontamination Nitrate ContainingGroundwater with Pump and Fertilize Application to Maize Farms, but where?Finite Element Method Utilization with HYDRUS 1D

17:00–17:20: Aishah Alqarni, Burhan Alveroğlu, Paul Griffiths and StephenGarrett, The Instability of Non-Newtonian Boundary-Layer Flows over RoughRotating Disks




11 September (Wednesday Morning)

09:00 - 10:20 09:00–09:20: Emrah Haspolat, Benoit Huard and Krishna Busawon,Observer Design for the Dynamic Modelling of Arabidopsis Flowering TimeGene Regulatory Network

09:20–09:40: Meltem Gölgeli, The Impact of Vaccine Skepticism and Migra-tion on the Global Measles Outbreak

Chair:ÖnderTürk

09:40–10:00: Nihan Akis-Man and Süleyman Yıldız, Reduced Order Mod-elling of Diffusive Lotka-Volterra Equations

10:00–10:20: Ricardo Raman-Brenes and Fracisco Siles, BiocomputationalPlatform for Template-Based Protein Docking Prediction using 3D GeometricDescriptors


10:40–12:20 10:40–11:00: Osman Zeki Yılmaz and Itır Köymen, Analysis of Analog HalfCenter Oscillator and Central Pattern Generator Circuits Employing Memris-tors in MATLAB

Chair:CüneytSert

11:00–11:20: Hande İbili, Barışcan Karaosmanoğlu and Özgür Ergül, Com-putational Electromagnetic Simulations of Zero-Index Materials

11:20–11:40: Saleh Abuhanieh and Hasan U. Akay, Solving MagnetostaticProblems using OpenFOAM

11:40–12:00: Elif Ebren Kaya and Münevver Tezer-Sezgin, DRBEM Solu-tion of Magnetohydrodynamic Duct Flow under Time-Varied Oblique Mag-netic Field

12:00–13:30 Lunch




11 September (Wednesday Afternoon)

13:30–14:50 13:30–13:50: Barışcan Karaosmanoğlu and Özgür Ergül, Accelerating Elec-trically Large-Scale Electromagnetic Simulations using Machine Learning

Chair:ÖmürUğur

13:50–14:10: Deniz Kenan Kılıç and Ömür Uğur, Hybrid Wavelet-Neural Net-work Models for Multivariate Time Series

14:10–14:30: Serap Gümüş and Varga Kalantarov, Finite–Parameter Feed-back Stabilization of Original Burgers Equations and Burgers’ Equation withNonlocal Nonlinearities

14:30–14:50: Ali Ahmed and Ismail H. Tuncer, Adjoint based Design Opti-mization of a Subsonic Intake

14:50–15:30 Closing Remarks

16:00–18:00 Conference Refreshment: Central Ankara, İşçi Blokları, 1536. Sk. No:7, 06520Çankaya/Ankara, self-payment



ABSTRACTS


Solving Magnetostatic Problems Using OpenFOAM

Saleh K. Abuhanieh1, Hasan U. Akay2

1 Atılım University, Ankara, Turkey [email protected] Atılım University, Ankara, Turkey [email protected]

The common computational method for solving electromagnetic problems is FEM. In multi-physicscases where fluid dynamics is involved and FVM is dominating, solving the complete computationalmodel using FVM is more convenient in terms of computational and programming costs. In thispaper, OpenFOAM which is an open-source FVM library is used to develop a solver which can solvemagnetostatic problems for a domain with variable magnetic permeability. To proof the accuracy ofthe developed solver, a benchmark case which has both physical and numerical experiments results inthe literature has been solved and the results were compared.




Turbulence Behind Artificially–Diffused Laminar Solutions

Mustafa Aggul1

1 Department of Mathematics, Hacettepe University, Ankara, [email protected]

Computational fluid dynamics community widely utilizes from artificial viscosity (AV) approxima-tions, which provides somewhat believable results of problems that normally would not be resolvedfeasibly with today’s computational resources. On the other hand, it’s a fact that additional viscos-ity introduced to the system causes over dissipation in all scales that results in underestimation ofthe energy. For this reason, AV approximations are mostly used as a first-step guess for more ac-curacy realizations of multi-step methods. In this talk, a technique that uncovers turbulence behindartificially-diffused laminar solutions will be introduced, and this process will be numerically exem-plified.




Adjoint based Design Optimization of a Subsonic Intake

Ali Ahmed1, İsmail H. Tuncer2

1 Middle East Technical University, Ankara, Turkey, [email protected] Middle East Technical University, Ankara, Turkey [email protected]

The adjoint based CFD optimization of a subsonic intake is done for different objective functions.The subsonic intake is considered to be only a propulsion device however it can have aerodynamiccharacteristic as well. There the engine face pressure recovery factor is the most important objectivefunction but we can also include the drag and develop an optimized shape in form of a submergedintake compared to general pitot-intake. SU2 is a open source CFD tool with built in FFT box forshape optimization and adjoint solver.




The Instability of Non–Newtonian Boundary Layer Flows over RoughRotating Disks

Aishah Alqarni1, Burhan Alveroğlu2, Paul Griffiths3, Stephen Garett4

1 University of Leicester, Leicester, United Kingdom [email protected] Bursa Technical University, Bursa, Turkey [email protected] Coventry University, Coventry, United Kingdom [email protected] University of Leicester, Leicester, United Kingdom [email protected]

We are concerned with the local linear convective instability of the incompressible boundary- layerflows over rough rotating disks for non-Newtonian fluids. Using the Carreau model for a range ofshear-thinning and shear-thickening fluids, we determine, for the first time, steady- flow profiles underthe partial-slip model for surface roughness. The linear stability analyses are described numericallyvia a Chebyshev collocation method in order to investigate the effect of roughness surface with theshear-thinning and shear- thickening fluids on the convective Type I (inviscid cross- flow) and Type II(viscous streamline curvature) modes of instability. It was found that a disk with concentric grooveshas a strongly destabilizing effect, whereas a disk with radial grooves or general isotropic roughnesshas a stabilizing effect on this mode. This is evident in the behaviour of the critical Reynolds numberand growth rates of both Type I (inviscid cross flow) and Type II (viscous streamline curvature) modesof instability. In order to extract possible underlying physical mechanisms behind the effects of rough-ness, and in order to reconfirm the results of the linear stability analysis, an integral energy equationfor three-dimensional disturbances to the undisturbed three-dimensional boundary-layer flow is usedhere.




A High-Order Numerical Method for Solving Nonlinear Singular BoundaryValue Problems Arising in Various Physical Model

Soner Aydınlık1, Ahmet Kiriş2

1 Department of Mathematical Engineering, ITU, İstanbul, Turkey [email protected] Department of Mathematical Engineering, ITU, İstanbul, Turkey [email protected]

Due to singularity, it is not possible to obtain analytical solution for singular boundary value problemin general; moreover, classical numerical methods are not applicable. Therefore, various non-classicalnumerical methods proposed to solve this kind of problems. In this study, a useful technique, Cheby-shev Finite Difference Method (CFDM) is introduced for solving nonlinear singular boundary valueproblems, since the present method is more advantageous for the solution of singular boundary prob-lems than the other methods given in the literature. CFDM is widely used in the literature for thesolution of second-order initial or boundary value problems [1, 2, 3, 4]. Convergence and error anal-ysis of the method are investigated. To show the applicability and efficiency of the presented method,the numerical solutions of four nonlinear singular boundary value problems which appear in appliedscience and engineering are given. Three of these examples arise in the study of thermal explosion(Example 1), steady-state oxygen diffusion in a spherical cell (Example 2) and the equilibrium ofisothermal gas spheres (Example 3). The numerical results show that CFDM is rather efficient andaccurate than the many methods given in the literature, without dividing the domain into the sub inter-vals. Besides, the proposed method does not need any modification for different boundary conditions.

Bibliography

[1] E. M. E. Elbarbary and M. El-Kady, Chebyshev finite difference approximation for the boundary valueproblems, Applied Mathematics and Computation 139(2-3), 513-523, 2003.

[2] A. Saadatmandi and J. A. Farsangi, Chebyshev finite difference method for a nonlinear system of second-order boundary value problems, Applied Mathematics and Computation 192(2), 586-591, 2007.

[3] A. Saadatmandi and M. Dehghan, The numerical solution of problems in calculus of variation using Cheby-shev finite difference method, Physics Letter A. 372(22), 4037-4040, 2008.

[4] S. Aydinlik and A. Kiris A high-order numerical method for solving nonlinear Lane-Emden type equationsarising in astrophysics, Astrophysics and Space Science 363(264), 2018




Biocomputational Platform for Template-Based Protein Docking PredictionUsing 3D Geometric Descriptors

Ricardo Román-Brenes1, Francisco Siles Canales2, Paula Gochez3

1 PRIS-Lab, Ingeniería Eléctrica, Universidad de Costa Rica [email protected] PRIS-Lab, Ingeniería Eléctrica, Universidad de Costa Rica [email protected] PRIS-Lab, Ingeniería Eléctrica, Universidad de Costa Rica [email protected]

Proteins are macromolecules that serve as catalyst for virtually all of the cell’s functions. In order toperform these functions, proteins need to interact with each other to form functional complexes [1].The protein-protein complex structure can be built upon templates. This technique is called template-based protein docking (TBPD). Protein-protein docking (PPD) is an important area of study in molec-ular biology due to its importance in fields like drug discovery or precision medicine. This process canbe done in silico or in vivo. Two general methods exist for in silico PPD: de novo or template based.The computational method is very demanding on CPU resources.

We propose here a computational platform with interchangeable modules to utilize a different setof descriptors, namely 3D geometrical descriptors [2, 3] to clusterize, classify and validate TBPDin order to improve response time of the process. The platform will use annotated data from theDockground project [4] (full structure docking templates v1.1 databank)

The platform will consist of several components. Items can be added to these components program-matically thanks to the use of a well-structured API. Aforesaid components are:

• a set of paired template candidates TC = {(tc00, tc01), (tc10, tc11), (tc20, tc21), . . . , (tcn0, tcn1)}that form a functional complex.

• a set of 3D geometrical feature extraction methods F = {fe0 , fe1 , . . . , fen}, that will generatethe features to be used in the clustering of the Dockground databank. Initially these featureswill be: protein area, protein volume, protein circularity, 3D Zerkine descriptor for the protein[2] and the first 3 PCA components of the protein.

• a set of clustering methods C = {c0, c1, . . . , cn} that will form groups based on the 3D features.All of the candidates TC will be clusterized with each method in order to generate groups. Tobegin with, the clustering methods to be used will be: k-means, x-means, OPTICS and BIRCH.

• a set of classification methods K = {k0, k1, . . . , kn} with which new proteins will be matchedwith subgroups in order to reduce run time. For starters the classifications methods to be usedwill be: SVM, k-nearest neighbors and LDA.

Each component of a set can be used interchangeably so that if for instance c0 does a better job thanc3, the user or programmer can choose which one to use. A parallel and distributed implementation ofthe platform will be done so that multiple methods can be run simultaneously.

The Platform will have at least two modes of operation: databank clusterization and docking predic-tion. For the docking prediction, the normal workflow would be as follows




1. Obtain the PDB files for the 2 proteins that want to be docked, p0 and p1.

2. Choose one or more of the already clusterized databanks generated with the features F extractedfrom TC using C methods.

3. Using the groups generated in the previous step, choose one or more classification methods tofind the best match for p0 and p1 in TC . The similarity of the match will be measured withTM-score [5].

4. The Platform shows, ordered by TM-score, the list of template candidates and the visualizationof both the templates and p0 and p1.

For the databank clusterization, the procedure would be

1. Choose one of the clusterization methods C .

2. Select which databank to use, initially Dockground will be used. This databank will be split,first, in two sets for work and validation, and then the training set will be split in three, fortraining, testing and confirmation.

3. Choose which 3D features from F will be used to perform the clusterization.

4. The Platform shows the results of the clusterization and performs validation using a 10-foldcross-validation against the already annotated entries of the validation set from Dockground.

5. If the user is satisfied with the results, the models will be saved for future use in the dockingprediction.

Aside from the automatization of the process of protein docking, run-time tests will be performed toensure that the Platform behaves well against the current methods for TBPD. The Platform’s parallelimplementation will ensure at least a higher throughput of data

Bibliography

[1] A. Szilagyi and Y. Zhang, Template-based structure modeling of protein–protein interactions, CurrentOpinion in Structural Biology 24, 10–23, 2014.

[2] S. Daberdaku and C. Ferrari, Exploring the potential of 3d zernike descriptors and svm for protein–proteininterface prediction, BMC Bioinformatics 19(1), 35, 2018.

[3] I. Budowski-Tal, Y. Nov, and R. Kolodny, Fragbag, an accurate representation of protein structure, re-trieves structural neighbors from the entire pdb quickly and accurately, Proceedings of the NationalAcademy of Sciences of the United States of America 107(8), 481–3486, 2010.

[4] P. J. Kundrotas, I. Anishchenko, T. Dauzhenka, I. Kotthoff, D. Mnevets, M. M. Copeland, and I. A. Vakser,Dockground: A comprehensive data resource for modeling of protein complexes, Protein Science 27(1),172-181, 2018.

[5] Y. Zhang and J. Skolnick, TM-align: a protein structure alignment algorithm based on the TM-score,Nucleic Acids Research 33(7), 2302–2309, 2005.




On the Fracture Surface Morphology under Ductile Plate Tearing at SteadyState

Şahin Çelik1, Cihan Tekoğlu2, Kim Lau Nielsen3

1 Department of Mechanical Engineering, TOBB University of Economics and Technology, Ankara,Turkey [email protected] Department of Mechanical Engineering, TOBB University of Economics and Technology, Ankara,Turkey [email protected] Department of Mechanical Engineering, Technical University of Denmark, Lyngby, Denmark

[email protected]

Ductile fracture occurs through nucleation, growth and coalescence of voids. The two main mecha-nisms of void nucleation in metals and metal alloys are the brittle cracking of second phase particlesand the decohesion of the interface between the particles and the surrounding matrix. The ease of voidnucleation, which is detrimental for ductility, is therefore closely related to the size, shape, spatial dis-tribution and volume fraction of second phase particles as well as the strength of the particle-matrixinterphase. It is, for example, well established that void nucleation becomes more and more difficultwith decreasing particle size; see e.g. [1]. A direct link between the properties of the particles and thetearing mode (cup-cup, cup-cone, slanted or mixture of the three) of a crack propagating in a ductilemetal is, however, missing in the current literature. In order to shed light on this issue, the authorsof the present abstract have recently investigated the effects of the volume fraction, size and spatialdistribution of spherical particles on the crack morphology in a finite element (FE) framework; see[2]. In the two-dimensional (plane strain) FE framework developed in reference [2], the presence ofparticles are modeled by embedding porous plastic “void nucleation sites” in an otherwise homoge-neous, non-porous matrix. The results showed that a low volume fraction of small particles leads tocup-cup morphology, while a large volume fraction of large particles forces the crack to slant. Thepresent study extends the work in reference [2] by allowing the void nucleation sites to assume el-liptical shapes, and focuses on the effects of the aspect ratio and the orientation of (the long axis ofthe) nucleation sites with respect to the main loading direction. The preliminary results show that thefracture surface has a cup-cup (respectively, slanted) morphology if the nucleation sites are alignedparallel (respectively, perpendicular) to the main loading direction.

The authors gratefully acknowledge the financial support by TÜBİTAK (project no: 315M133).

Bibliography

[1] J. J. Lewandowski, C. Liu and W. H. Hunt, Effects of matrix microstructure and particle distribution onfracture of an aluminum metal matrix composite, Materials Science and Engineering: A 107, 241-255,1989.

[2] C. Tekoğlu and K. L. Nielsen, Effect of damage-related microstructural parameters on plate tearing atsteady state, European Journal of Mechanics–A/Solids 77, 2019.




Analysis of Caching Process in a Line Network via Epidemic Models

Mustafa Kağan Çetin1, Meltem Gölgeli2

1 TOBB University of Economics and Technology, Ankara, [email protected]

2 TOBB University of Economics and Technology, Ankara, Turkey [email protected]

In the earlier aspects of the communication systems, the data was transmitted only from the mainsource to destination point. The rising traffic of internet and video streaming forced the scientists topropose a new technology of data transfer [1]. Caching provides to store frequently accessed data ina memory component known as caches [2]. Thus, the consumers first check the appropriate cacheto access data instead of reaching the primary source, so that they save time and money. There aredifferent ways of implementing cache processes. In this work, we proposed a novel mathematicalmodel explaining the data transmission based on the classical approach of compartmental modelsfor infectious diseases [3]. We consider three separate compartments (consumer(C), producer(P) andrelay(R)) and construct a system of ordinary differential equations for the transmission dynamics ofrequested data. Then, we analyse the model and discuss the local stability of the equilibria. Finally,we support the results by numerical simulations.

Bibliography

[1] G. Xylomenos et al. A survey of information-centric networking research, Communications Surveys Tuto-rials, IEEE, 16(2), 1024–1049, 2014.

[2] E. Bastug, M. Bennis and M. Debbah, Living on the edge: the role of proactive caching in 5G wirelessnetworks, IEEE Communications Magazine 52(8), 82-89, 2014.

[3] W. O. Kermack and A. G. McKendrick, Contributions to the mathematical theory of epidemics, Proceed-ings of the Royal Society of Edinburgh Section A. Mathematics 115, 700–721, 1927.




Discontinuous Galerkin Methods for Convection Diffusion Equations withRandom Coefficients

Pelin Çiloğlu1, Hamdullah Yücel2

1 Institute of Applied Mathematics, METU, Ankara, Turkey [email protected] Institute of Applied Mathematics, METU, Ankara, Turkey [email protected]

Partial differential equations (PDEs) with random input data is one of the most powerful tools to modeloil and gas production as well as groundwater pollution control. However, the information availableon the input data is very limited, which causes high level of uncertainty in approximating the solutionto these problems. To identify the random coefficients, the well–known technique Karhunen Loéve(K–L) expansion has some limitations. K–L expansion approach leads to extremely high dimensionalsystems with Kronecker product structure and only preserves two–point statistics, i.e., mean and vari-ance. To address the limitations of the standard K–L expansion, we propose principal componentanalysis (PCA), i.e., linear and kernel PCA.

This talk concerns a numerical investigation of convection diffusion equation with random input databy using stochastic Galerkin method. Since the local mass conservation plays a crucial role in reser-voir simulations, we use discontinuous Galerkin method for the spatial discretization. To illustratethe efficiency of the proposed approach, we provide some numerical experiments with Gaussian anduniform distributed coefficients.




Modelling Spatio-Temporal Temperature-Mediated Bacteria-PhageInteraction

Halil İbrahim Eğilmez1, Andrew Yu. Morozov2

1 Hitit University, Çorum, Turkey [email protected] University of Leicester, Leicester, UK [email protected]

The pathogenic bacteria Burkholderia pseudomallei is the main cause of the disease Melioidosis whichis currently number three out of the most fatal infections after AIDS and tuberculosis. Bacteria growin water and soil of the endemic areas of South-East Asia and Northern Australia. Via various means(e.g. including human transport) the pathogen can disperse to areas which were initially non-endemic.Currently, it is a growing recognition that bacteriophages (phages) can play an important role in con-trolling the population dynamics of B. pseudomallei and that the variation of the temperature is criticalfor understanding interaction between bacteria and their phages. A parsimonious mathematical modelhas been recently developed to predict dynamics of bacteria and phages in the top surface water. How-ever, bacterial dynamics and their control by phages in the heterogeneous environment (soil) has notbeen addressed so far due to the high complexity if the problem. For example, a number of factorsdetermine the spatial distribution of B. pseudomallei such as the temperature, pH level, precipitation,water content and the nutrients concentration. In this study, we extend the previous works and con-sider the spatio-temporal dynamics of B. pseudomallei in heterogeneous environment (soil). We buildand explore a mathematical model of bacteria-phage interaction in vertically spatial space (soil) ex-ternally forced by daily and seasonal temperature variations. The model is based on reaction-diffusionPDEs. We study the model properties via intensive computer simulations. The simulations use realisticbiological parameters.




The Time Varied Control of Unsteady MHD Equations

Cansu Evcin1, Ömür Uğur2, Münevver Tezer-Sezgin3

1 Department of Mathematics, TNKU, Tekirdağ, Turkey [email protected] Institute of Applied Mathematics, METU, Ankara, Turkey [email protected] Department of Mathematics, METU, Ankara, Turkey [email protected]

Optimal control solution of the unsteady, laminar, fully developed flow of viscous, incompressibleand electrically conducting fluid with time varied coefficients is considered under the effect of aconstant and uniform magnetic field in the direction made an angle with the y–axis. The coupledtime-dependent MHD equations are transformed into the decoupled convection-diffusion type equa-tions with time varied coefficients and are solved by using finite element method (FEM) in space andimplicit Euler in time. FEM solutions are obtained for various values of the Hartmann number and atdifferent time levels.

In this study, we aim to control the unsteady MHD flow by using the time-varied coefficient functionof the problem as control function. In the optimisation, a discretize–then–optimize approach witha gradient based algorithm is followed. Cost function is designed to regain the prescribed velocityand induced magnetic field profiles and also to have a smooth control function with respect to time.Controls are investigated for the regularization parameters included in the cost function. Optimalsolutions are achieved for several states of the flow considering Hartmann number and final time.




Computational Modeling of Shrinkage-Induced Cracking in Concrete

Mehran Ghasabeh1, Serdar Göktepe2

1 Department of Civil Engineering, METU, Ankara, Turkey [email protected] Department of Civil Engineering, METU, Ankara, Turkey [email protected]

Concrete structures, in particular at their early ages, may undergo significant deformations due todrying shrinkage accompanied by the time-dependent creep phenomenon. Therefore, for any concretestructure the accurate estimation of the service life necessitates a sound understanding and quantitativeprediction of creep and shrinkage-induced deformations, and the associated stress concentrations.The latter is greatly affected by durability-related phenomena that start to arise due to initiation ofmicro-cracks as the principal stresses exceed the instant tensile strength of hardening concrete. Thedrying shrinkage-induced localization of tensile stresses results from uneven volume changes due tothe alteration in relative humidity through the loss of evaporable water from the surface of concrete,in contact with generally less humid air.

In this contribution, we develop a coupled constitutive modeling approach that is equipped by robustcomputational framework to address the durability problems that arise from drying shrinkage withinthe three-dimensional framework of poroviscoelasticity. Accordingly, the proposed approach accountsfor the hygro-chemo-mechanical cross coupling effects between the shrinkage-induced strain devel-opment due to the pressure evolution through humidity variations and the stress concentrations inhardening or hardened viscoelastic concrete. To this end, the stress expression is additively decom-posed into the effective stress of viscoelastic concrete skeleton and the pressure developing in pores[1]. The viscoelastic model of the skeleton takes into account short- and long-range creep effectsthrough the well-known micro-prestress theory [2]. The material parameters related with the rigid-ity and strength of concrete are assumed to evolve with the degree of hydration [3]. In the proposedmodel, as opposed to the modeling approaches suggested in the literature, the shrinkage strain is notobtained by using an empirical formula involving the hygromechanical expansion coefficient and thechange in humidity. Instead, we employ a physically motivated approach where the pore pressure isobtained as a function water content that is determined using sorption-desorption [4] equations for agiven value of the local relative humidity. Apart from the the conservation of linear momentum equa-tion, the temporal and spatial variation of the relative humidity is calculated through the Darcy-typetransient continuity equation. The coupled model of poro-viscoelasticity is further supplemented bya crack phase-field model [5, 6] to conduct the crack risk analysis of concrete structures subjected tothe coupled effects. The results obtained using the proposed model are compared with the experimen-tal data involving creep and shrinkage deformations. Additional representative numerical examplesof boundary-value problems are analyzed to validate the predictive capabilities of the proposed threedimensional model.

Bibliography

[1] M. A. Biot, General theory of three-dimensional consolidation, Journal of Applied Physics 12(2), 155–164,1941.

[2] M. Jirasek and P. Havlasek, Microprestress–solidification theory of concrete creep: reformulation and im-provement, Cement and Concrete Research 60, 51–62, 2014.




[3] M. Cervera, J. Oliver and T. Prato, Thermo-chemo-mechanical model for concrete I: Hydration and aging,Journal of Engineering Mechanics 125(9), 1018-1027, 1999.

[4] K. N. Mjörnell, Moisture conditions in high performance concrete, Chalmers University of Technology,Göteborg, 1997.

[5] C. Miehe, F. Welschinger and M. Hofacker, Thermodynamically consistent phase-field models of fracture:Variational principles and multi-field FE implementations, International Journal for Numerical Methods inEngineering 83(10), 1273-1311, 2010.

[6] J. -Y. Wu, A unified phase-field theory for the mechanics of damage and quasi-brittle failure, Journal of theMechanics and Physics of Solids 103, 72–99, 2017.




The Impact of Vaccine Skepticism and Migration on the Global MeaslesOutbreak

Meltem Gölgeli1

1 TOBB University of Economics and Technology, Ankara, Turkey [email protected]

Measles is a highly contagious re-emerging viral infection which especially affects infants and youngchildren. It has been largely eliminated in many developed countries but in 2019, the World HealthOrganization (WHO) reported more than 112163 confirmed cases of measles worldwide includingthe developed countries. Medical researches point out the role of international travel and unauthorizedimmigration on measles outbreaks [1]. The impact of vaccine sceptic parents on the spread of thedisease remains still arguable [2]. Now that the two dose vaccination is the only effective method ofprevention which has been available since 1960s [3]. In this work, we develop a compartmental modelto describe the transmission dynamics of measles under the effect of migration and vaccination. Wederive thresholds for vaccination rates and discuss the control and elimination methods of measles bydetermining the basic reproduction number for the model. Finally, we perform numerical simulationsto support the theoretical results and to consider the optimal vaccination strategies both in migrantsand citizens.

Bibliography

[1] R. A. Bednarczyk, P. A. Rebolledo and S. B. Omer, Assessment of the role of international travel andunauthorized immigration on measles importation to the United States, J Travel Med. 30, 23(3), 2016.

[2] E. Shim, J. J. Grefenstette, S. M. Albert, B. E. Cakouros and D. S. Burke, A game dynamic model forvaccine skeptics and vaccine believers: measles as an example, J Theor Biol. 295, 194-203, 2012.

[3] Y. Hu, Q. Li, S. Luo, L. Luo, X. Qi and S. Xie, Timeliness vaccination of measles containing vaccine andbarriers to vaccination among migrant children in East Chine, PLoS One, 8(8):e73264, 2013.




Geometric Design of Gradient Index Lenses via Heuristic Optimization andFull-Wave Simulations

Sadri Güler1, Özgür Eriş2, Özgür Ergül3

1 Electrical and Electronics Eng., METU, Ankara, Turkey [email protected] Electrical and Electronics Eng., METU, Ankara, Turkey [email protected] Electrical and Electronics Eng., METU, Ankara, Turkey [email protected]

Gradient index lenses are periodic arrangements of dielectric elements and they are commonly usedthanks to their remarkable advantages, such as high power-focusing strength and sub-wavelengththickness (compactness), while being flat structures. In the literature, their design procedures aremainly based on making fundamental geometric assumptions, such as infinity in certain directions,and then designing geometric and material properties of their elements with analytical approaches.While being straightforward, these procedures often lead to designs that do not perform as desiredwhen fabricated, due to natural deviations of realistic samples from the ideal geometries. In this study,we propose a robust design process based on heuristic optimization of geometric properties of gradientindex lenses when they are modeled as realistic three-dimensional structures in full-wave simulations.

For the developed design environment, a parametric modeling algorithm is implemented with thepurpose of flexible and automated computer modeling of gradient index lenses. Parameters of eachelement of the designed structure, such as thickness, periodicity, and element shape, are representedby binary arrays. An efficient implementation of genetic algorithms is employed to optimize elementparameters to achieve desired electromagnetic responses, particularly powerful focusing with min-imized full-width-at-half-maximum values. Each proposed design, which represents a challengingnumerical problem, is analyzed by using a full wave solver based on the electric and magnetic cur-rent combined-field integral equation (JMCFIE) that provides well-conditioned matrix equations. Theconstructed dense matrix equations are solved by using the multilevel fast multipole algorithm bothaccurately and efficiently. Once current expansion coefficients are obtained, electromagnetic responseof each design is found by inspecting near-zone field distributions.

The presentation will include diverse optimization results, as well as the details of the modeling algo-rithm, full-wave solver, and heuristic optimization environment.




A Quasi-Incompressible and Quasi-Inextensible Finite ElementImplementation of Fibrous Soft Biological Tissues

Osman Gültekin1, Burak Rodoplu2, Hüsnü Dal3

1 Department of Mechanical Engineering, METU, Ankara, Turkey [email protected] Department of Mechanical Engineering, METU, Ankara, Turkey2 Department of Mechanical Engineering, METU, Ankara, Turkey [email protected]

Fibrous soft biological tissues exhibit nearly incompressible exponentially stiffening mechanical re-sponse (J–like stress–strain curve), making the development of efficient and robust finite elementformulations at the quasi-incompressible and quasi-inextensible limit particularly important for thenumerical analysis of such materials. The present contribution addresses the quasi–inextensible andquasi–incompressible finite hyperelastic behavior of fibrous tissues such as arterial walls.

The formulation features an additive decomposition of the free energy function into isotropic andanisotropic parts. The unsplit deformation gradient is employed on both parts. While the pressure–dilatation conjugate variables are the cornerstones of the Q1P0 element formulation rendering quasi–incompressibility, similar conjugate pairs, namely the volume averaged fiber stretches and stressesvariables engender the quasi–inextensible behavior of the the material reinforced with a number offiber families, see e.g. [1]. Euler-Lagrange equations and the corresponding Q1P0F0 finite elementformulation are the result of the extended Hu–Washizu variational principle with the respective poten-tial. Following [2] and [3], the numerical implementation exploits the underlying variational structureleading to a canonical symmetric structure.

The numerical performance of the Q1P0F0 element formulation are demonstrated first via series ofdual clamped patch tests where the results are compared with those of Q1 and Q1P0 elements. Amore representative case follows from a three–layered hollow cylinder reinforced with two familiesof fibers subjected to an internal pressure. Results indicate a plausible physical and numerical reasonsin the replacement of all Q1P0 element by the new approach called Q1P0F0.

Bibliography

[1] G. A. Holzapfel, T. C. Gasser and R. W. Ogden, A new constitutive framework for arterial wall mechanicsand a comparative study of material models, J. Elasticity 61, 1-48, 2000.

[2] H. Dal, A quasi-incompressible and quasi-inextensible element formulation for transversely isotropic ma-terials, Int. J. Numer. Meth. Eng. 117, 118-140, 2019.

[3] O. Gültekin, H. Dal and G. A. Holzapfel, On the quasi-incompressible finite element analysis of anisotropichyperelastic materials, Comp. Mech. 63, 443-453, 2019.




Finite–Parameter Feedback Stabilization of Original Burgers Equations andBurgers’ Equation with Nonlocal Nonlinearities

Serap Gümüş1, Varga Kalantarov2

1 Koç University, İstanbul, Turkey [email protected] Koç University, İstanbul, Turkey [email protected]

In this paper, we study the problem of local and global exponential stabilization of original Burgers’equations and the Burgers’ equation with nonlocal nonlinearities by controllers depending on finitelymany parameters. We show that solutions of the controlled equations are steering concrete solution ofthe non-controlled system as t goes to infinity with an exponential rate.




Uncertainty Modelling of 3D Printed Lattice Structures Using Random Field

Olgun Utku Güngör1, Recep Muhammet Görgülüarslan2

1 TOBB University of Economics and Technology, Ankara, Turkey [email protected] TOBB University of Economics and Technology, Ankara, Turkey

[email protected]

Cellular lattice structures (CLS) are highly demanded in many engineering applications and indus-trial components. Due to intrinsically complex network of strut members designed at small scales, thefabrication of these lattice structures is very difficult using conventional manufacturing technologies.Crucial advances in AM technology have provided unprecedented opportunities for producing thesecomplex structures. However, there are different obstacles that arising from AM process. Most impor-tant of these, lattice’s strut diameter varies along its length and built angle. The mechanical propertiesand performance of the lattice structures rely on quantification of these geometric imperfections asso-ciated with AM process. This study focuses on the comparison of various random field models for thegeometric imperfections of lattice struts. The spatial variation of strut diameter is modeled as a set ofrandom fields and represented by Karhunen-Loève expansion. Finally, spatial correlations observedfrom experiments have been compared with commonly used correlation functions.




Heat Transfer of MHD Flow with Variable Viscosity and Hall Effect

Merve Gürbüz1

1 Baskent University, Ankara, Turkey [email protected]

In this study, the heat transfer of steady, electrically conducting fluid under a uniform magnetic fieldis considered. The momentum and energy equations including Hall effect and variable viscosity aresolved by using radial basis function (RBF) approximation for the computational efficiency. The ef-fects of magnetic field, Hall current and viscosity variation on the velocity and temperature of thefluid are analyzed for several values of the Hartmann number (Ha), the Hall parameter (m) and theviscosity parameter (B), respectively. It is found that, as both the Hartmann number and the viscosityparameter increase, the magnitude of the velocity decreases. However, the increase in the Hall pa-rameter increases the magnitude of the axis-velocity. The average Nusselt decreases as the viscosityparameter decreases.




Filtering and Smoothing in Stochastic Modeling of Biological Systems

Merve Haksever1, Derya Altıntan2, Ömür Uğur3

1 Institute of Applied Mathematics, METU, Ankara, Turkey [email protected] Department of Mathematics, Selçuk University, Konya, Turkey [email protected] Institute of Applied Mathematics, METU, Ankara, Turkey [email protected]

Biochemical systems can be represented in terms of mathematical models to predict their future behav-iors. Particularly, time evolution of biochemical reaction systems are described through mathematicalmodels. There are two main approaches to describe time evolution of reaction systems. The first one,deterministic approach, regards the time evolution as a continuous and tractable process and evolvesin time according to set of ordinary differential equations (Reaction-Rate Equations) [1]. The secondone is stochastic approach, regards the time evolution as a random-walk process and characterizedby a single differential-difference equation (Chemical Master Equation) [2]. Obtaining an analyticalsolution for CME is possible for a few cases. Hence, stochastic simulation methods [2] are used tochase the time evolution of stochastic process under consideration.

In general, it is not possible to assess all elements of state vectors for biochemical systems. Hence,some statistical models are used to obtain best estimation. To define methods for estimating the prob-ability distribution of the state of a time-varying system according to indirect measurements, the termfiltering is used. Smoothing also defines estimation methods for the probability distribution of the stateof a time-varying system. Yet, there is a single difference between filtering and smoothing. In filtering,current probability distribution of the state is estimated by using measurements up to that time. Onthe other hand, smoothing is used to estimate the probability distribution of former state of the systembased on all measurements up to given time [3]. In this study, these methods will be explained andwill be applied to biological systems.

This work is supported by the Scientific and Technological Research Council of Turkey (TÜBİTAK)Program no: 3501, Grant no: 11E252

Bibliography

[1] D. J. Wilkinson, Stochastic Modelling for System Biology, Second Edition, CRC Press, 2012.[2] D. T. Gillespie, Stochastic simulation of chemical kinetics, The Annual Review of Physical Chemistry,

2007.[3] A. Doucet, A. Johansen, A tutorial on particle filtering and smoothing: fifteen years later, Handbook of

Nonlinear Filtering, 2009.




Observer Design for the Dynamic Modelling of Arabidopsis Flowering TimeGene Regulatory Network

Emrah Haspolat1, Benolt Huard2, Krishna Busawon3

1 Bilecik Şeyh Edebali University, Bilecik, Turkey [email protected] Northumbria University, Newcastle, United Kingdom [email protected] Northumbria University, Newcastle, United Kingdom

[email protected]

This study deals with the implementation of a high-gain observer design for a nonlinear mathemat-ical model of Arabidopsis Thaliana flowering time gene regulatory network and control its dynamicbehavior. The observer model helps to estimate certain variables which cannot be easily quantified inexperiments by using the measured ones. The behavior of flowering process, which is represented by asystem of three differential equations, and exact time period of the flowering can be controlled with astate feedback control design by tuning up inputs and measuring the desired outputs. Numerical inves-tigations of the observer and controller are performed, and the simulations illustrate the effectivenessof the high-gain observer model developed in our approach.




Decontaminating Nitrate Containing Groundwater with Pump and FertilizeApplication to Maize Farms, But Where? Finite Element Method Utilization

with HYDRUS 1D

Güray Hatipoğlu1

1 Department of Earth System Science, METU, Ankara, Turkey [email protected]

Pump and fertilize process can simultaneously get rid off the nitrate contamination in groundwater aswell as reduce the nitrogen fertilizer requirement of crops. Previously, 5 cities in Turkey were chosen(Eskişehir, Adana, Şanlıurfa, Düzce, and Rize) and using monthly-averaged climatic variables and dif-ferent soil textures the optimum soil type and climate, and as a result the most suitable region to utilizepump and fertilize were found, with Şanlıurfa most promising ([1]). While the monthly-averaged cli-mate variables gave the first insight into where it can be useful, modeling the daily climatic variableswill show more accurate results, as well as permit us to check the significance of precipitation fre-quency etc. over the process. In addition to this fact, soil textures were also modeled homogeneouslyfor the entire modeled region of 120 cm. This, again, can be made more precise using soil profileinformation from literature and databases and utilize finite element discretization to specify eachdominant soil for the entire soil column. To reach these targets, AGRI4CAST database data prod-ucts related to climate variables in entire Europe and Mediterranean region were obtained. Soil profileinformation were obtained from HWSD (Harmonized World Soil Database) which contains 0-30 and30-100 cm soil’s detailed characteristics for the entire world. As previously, HYDRUS 1D software,one of the most preferred groundwater modeling software to simulate unsaturated zone groundwaterflow, was used to discretize finite elements and soil information; then, taking climate variables fromAGRI4CAST database, to model maize fate and nitrate uptake (and consequently nitrate surplus andleaching) throughout pump and fertilize process for 1 year with 1D Richard’s equation. The results ofthis study will illustrate exactly which region, which combinations of the soils, which rain frequencywill result in the optimum nitrogen use efficiency (NUE), nitrate leaching and consequently nitrateremoval from the contaminated groundwater.

Bibliography

[1] Y. G. Hatipoglu and Z. Kurt, Modeling irrigation with nitrate contaminated groundwater, Pamukkale Uni-versity Journal of Engineering Science, doi:10.5505/pajes.2019.38963




Computational Electromagnetic Simulations of Zero-Index Materials

Hande İbili1, Barışcan Karaosmanoğlu2, Özgür Ergül3

1 Electrical and Electronics Eng., METU, Ankara, Turkey [email protected] Electrical and Electronics Eng., METU, Ankara, Turkey [email protected] Electrical and Electronics Eng., METU, Ankara, Turkey [email protected]

In this study, computational analysis of electromagnetic problems involving zero-index (ZI) andnearzero- index (NZI) materials are presented, with the particular focus on the accuracy and effi-ciency of the surface-integral-equation (SIE) formulations. ZI and NZI materials are special structureswith very small refractive index values, resulting in wavelengths locally stretching to infinity. Theirpeculiar characteristics have been useful in diverse applications, such as electromagnetic coupling,electromagnetic tunneling, focusing, and directive antennas. As an expected outcome of these practi-cal applications, full-wave numerical solutions of ZI and NZI structures provide essential informationand have enormous impact on their realizations since even the smallest inaccuracy in simulations maycorrupt the designs. The failure of the conventional SIE formulations when permittivity and/or per-meability values go to zero reveals the need for developing novel SIE formulations for ZI and NZImaterials. In order to mitigate inaccuracy, inefficiency, and instability issues, novel SIE formulationshaving balanced integral-equation operators are presented. In addition, to accelerate iterative solu-tions, the multilevel fast multipole algorithm (MLFMA) is employed [1]. Since standard plane-waveexpansion schemes fail to provide accurate computations for ZI and NZI materials, an approximatediagonalization that was developed for low-frequency problems is used in MLFMA [2]. The resultingimplementation is used to perform fast and accurate iterative solutions of electromagnetic problemsinvolving ZI and NZI materials. The performance of the implementation is demonstrated on bothcanonical and realistic problems.

Bibliography

[1] Ö. Ergül and L. Gürel, The Multilevel Fast Multipole Algorithm (MLFMA) for Solving Large Scale Com-putational Electromagnetics Problems, Wiley-IEEE, 2014.

[2] Ö. Ergül and B. Karaosmanoğlu, Broadband multilevel fast multipole algorithm based on an approximatediagonalization of the Green’s function, IEEE Trans. Antennas Propag. 63(7), 3035–3041, 2015.




Computational Design of Enhanced Plasmonic Nanotraps for Particle SensingApplications

Göktuğ Işıklar1, Özgür Ergül2

1 Department of Electrical and Electronics Engineering, METU, Ankara, [email protected]

2 Department of Electrical and Electronics Engineering, METU, Ankara, [email protected]

Plasmonic nanoholes are ideal structures to detect general variations in macroscopic properties ofsurrounding media (which typically include vast amounts of nanoparticles) thanks to their extraordi-nary nano-optical activities. However, commonly used nanohole structures with circular shapes arenot sufficient to be used in single-particle sensing applications, where the nanoparticles to be detectedare sparse. In this study, we show that generated signal levels of circular nanoholes can significantlybe enhanced with well-designed triangular tips. Specifically, we present computational design andsimulations of bowtie-shaped nanotraps for single-particle sensing applications. Simulations are per-formed by using the multilevel fast multipole algorithm (MLFMA) to obtain the required accurate andfast solutions of electromagnetic scattering problems in the frequency domain. Surface integral equa-tions, which are directly derived from Maxwell’s equations, are used to analyze three-dimensionalstructures. We particularly employ the modified combined tangential formulation (MCTF), which isknown to provide very accurate simulations of plasmonic scatterers [1]. Once the nanotrap geometriesand MCTF are discretized by using the Rao-Wilton-Glisson basis functions, the obtained matrix equa-tions are solved iteratively with the help of MLFMA. Thanks to the efficient and accurate simulations,generated signal level comparisons of nanotrap designs and typical circular nanoholes are rigorouslyperformed for single-particle sensing applications. Shape, position, and electrical properties of differ-ent nanoparticles are investigated in the context of their characterization and identification, towardsmore reliable nano-optical systems for single-particle sensing applications.

Bibliography

[1] B. Karaosmanoğlu, A. Yılmaz and Ö. Ergül, Accurate and efficient analysis of plasmonic structures usingsurface integral equations, IEEE Trans. Antennas Propag. 65(6), 3049-3057, 2017.




Accelerating Electrically Large-Scale Electromagnetic Simulations UsingMachine Learning

Barışcan Karaosmanoğlu1, Özgür Ergül2

1 Electrical and Electronics Eng., METU, Ankara, Turkey [email protected] Electrical and Electronics Eng., METU, Ankara, Turkey [email protected]

Accurate solutions of electrically large three-dimensional electromagnetic scattering problems oftenlead to numerical problems with huge numbers of unknowns. It is possible to use high-frequencytechniques to obtain fast results for the electromagnetic analysis of such large problems. However,these techniques, e.g., physical optics, geometric theory of diffraction, and ray tracing, do not providecontrollable accuracy and they particularly fail for the analysis of complex geometries. In this study,we use surface integral equations for full-wave solutions, which lead to dense matrix equations. Dueto large dimensions of the derived matrix equations, direct solutions cannot be obtained, and hence,iterative techniques are used, where the required matrix-vector multiplications are performed via fastalgorithms, such as the multilevel fast multipole algorithm (MLFMA) [1]. Even though MLFMA per-forms matrix-vector multiplications with O(N logN) computational and memory complexity, whereN is the number of unknowns, the required number of iterations and the solution time for an elec-trically large complex geometry can be at undesirable levels. In this work, we propose the use ofmachine learning (ML) techniques to reduce the required number of iterations and to reduce MLFMAoperations to speed up large-scale electromagnetic simulations.

Excellent performances of different ML techniques have been demonstrated on various applications,such as data classification, resolution improvement, and continuous signal processing. In these appli-cations, ML techniques are not only applied to statistical data but also to underlying physical phe-nomena. Early experiments on the application of ML techniques for electromagnetic simulations havealso shown promising results [2]. In this work, as the first time in the literature, we present the directintegration of ML techniques into an electromagnetic solver in order to accelerate simulations withminimum deterioration on the accuracy. This is achieved by considering electromagnetic interactionsas neural networks and redesigning them by eliminating less critical interactions depending on theproblem. This way, efficient problem-tailored solutions are obtained with the help of ML techniques,which guide and drive the solver with smart interaction reductions. Initial numerical experiments showthat the resulting implementation of MLFMA + ML provide fast simulations, without sacrificing theaccuracy as opposed to high-frequency techniques.

Bibliography

[1] Ö. Ergül and L. Gürel, The Multilevel Fast Multipole Algorithm (MLFMA) for Solving Large Scale Com-putational Electromagnetics Problems, Wiley-IEEE, 2014.

[2] B. Karaosmanoğlu and Ö. Ergül, Error prediction in electromagnetic simulations using machine learning,Proc. IEEE Antennas Propag. Soc. Int. Symp., 2019.




Design and Simulations of Nano-Optical Couplers with Genetic Algorithmsand MLFMA

Gökhan Karaova1, Özgür Ergül2

1 Electrical and Electronics Eng., METU, Ankara, Turkey [email protected] Electrical and Electronics Eng., METU, Ankara, Turkey [email protected]

In this study, novel nano-optical couplers involving well-designed arrays of cubic nanoparticles areproposed for constructing efficient nano-optical networks. The proposed structures are optimized withan in-house implementation of genetic algorithms, while the required electromagnetic simulations areperformed by solving a surface integral equation (SIE), i.e., modified combined tangential formulationMCTF. Solutions of MCTF are accelerated via an in-house implementation of the multilevel fastmultipole algorithm (MLFMA), without sacrificing the accuracy of the results.

Nano-optical couplers that involve array arrangements are used in many nano-optical systems forpower transmission [1], beam steering [2], and nano-optical coupling [3], to name a few. These typesof couplers are made of metals such as Ag and Au, which possess strong plasmonic properties that en-able manipulation of electromagnetic waves at optical frequencies. This study aims to achieve wellde-signed nano-optical couplers that involve Ag particles (nanocubes). Nanocube grids are located atjunction locations of nanowire pairs and they are optimized to control the transmission of electro-magnetic power, i.e., to transfer the electromagnetic power to desired directions while suppressingothers.

Simulating a nano-optical coupler, as described above, can be numerically challenging due to strongplasmonic interactions between nanowires and couplers, and unpredictable behavior of plasmonicwaves. In addition to this, nano-optical couplers are optimized in the presence of nanowires, leadingto large matrix equations to handle, whose solutions are required thousands of times during opti-mization trials. Thanks to MLFMA [4], which is a plane-wave-based acceleration algorithm, iterativesolutions can be obtained both accurately and efficiently. While MLFMA can perform fast solutions,optimization trials are further accelerated via embarrassing parallelism by assigning the evaluation ofindividuals of genetic algorithms to multiple cores.

The obtained nano-optical coupler designs clearly demonstrate the efficiency of the optimizationmechanism, while the results show the effectiveness of the designed couplers for controlling elec-tromagnetic power transmission in nano-optical networks.

Bibliography

[1] A. Altınoklu and Ö. Ergül, Nano-optical couplers for efficient power transmission along sharply bendednanowires, ACES J. 34(2), 228–233, 2019.

[2] A. Altınoklu, N. Razoolzadeh and Ö. Ergül, Design and optimization of two-dimensional nanoarrays forbeam steering, Proc. Int. Applied Computational Electromagnetics Soc. Symp, 2018.

[3] Y. E. Tunçyürek, B. Karaosmanoğlu, and Ö. Ergül, Computational design of optical couplers for bendednanowire transmission lines, ACES J. 32(7), 562–568, 2017.

[4] Ö. Ergül and L. Gürel, The Multilevel Fast Multipole Algorithm (MLFMA) for solving Large-Scale Com-putational Electromagnetics Problems, Wiley-IEEE, 2014.




DRBEM Solution of Magnetohydrodynamic Duct Flow under Time-variedOblique Magnetic Field

Elif Ebren Kaya1, Münevver, Tezer-Sezgin2

1 Middle East Technical University, Ankara, Turkey, [email protected] Middle East Technical University, Ankara, Turkey, [email protected]

The unsteady, laminar, fully developed MHD flow of viscous, incompressible and electrically con-ductin

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