Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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Naji, M.
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Publications (22/22 displayed)

  • 2024Aeroelastic Tailoring of a Strut-Braced Wing for a Medium Range Aircraft1citations
  • 2023Optimization Framework of a Ram Air Inlet Composite Morphing Flap1citations
  • 2022Application of Aeroelastic Tailoring for Load Alleviation on a Flying Demonstrator Wing †7citations
  • 2022Assessment of an Increased-Fidelity Aeroelastic Experiment for Free Flying Wing Response to Gust Excitationcitations
  • 2022Aeroelastic Wing Demonstrator with a Distributed and Decentralized Control Architecture1citations
  • 2022An aeroelastic optimisation framework for manufacturable variable stiffness composite wings including critical gust loads9citations
  • 2021Development and testing of an active trailing edge morphing demonstrator for a rotary wing1citations
  • 2021Skin Panel Optimization of the Common Research Model Wing using Sandwich Composites4citations
  • 2021Aeroelastic optimisation of manufacturable tow-steered composite wings with cruise shape constraint and gust loads1citations
  • 2021Developing the Model Reduction Framework in High Frame Rate Visual Tracking Environmentcitations
  • 2020Static and dynamic aeroelastic tailoring with composite blending and manoeuvre load alleviation23citations
  • 2020Ground Testing of the FLEXOP Demonstrator Aircraft12citations
  • 2019Aeroelastic optimization of composite wings including fatigue loading requirements18citations
  • 2018FLEXOP – Application of aeroelastic tailoring to a flying demonstrator wingcitations
  • 2018Aeroelastic optimization of composite wings subjected to fatigue loads2citations
  • 2017Aeroelastic Design of Blended Composite Structures Using Lamination Parameters15citations
  • 2017Aeroelastic tailoring for static and dynamic loads with blending constraintscitations
  • 2016Aeroelastic Optimization of Variable Stiffness Composite Wing with Blending Constraints9citations
  • 2016A Conceptual Development of a Shape Memory Alloy Actuated Variable Camber Morphing Wingcitations
  • 2016Derivation and application of blending constraints in lamination parameter space for composite optimisation39citations
  • 2015Special Issuecitations
  • 2015Development and Testing of an Unconventional Morphing Wing Concept with Variable Chord and Cambercitations

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Sodja, Jurij
8 / 8 shared
Córcoles, Xavier Carrillo
2 / 2 shared
Krüger, Wolf R.
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Meddaikar, Yasser M.
1 / 2 shared
Dillinger, Johannes
3 / 6 shared
Wang, Xuerui
1 / 1 shared
Mkhoyan, Tigran
2 / 2 shared
Peeters, Daniël
2 / 7 shared
Wang, Zhijun
2 / 2 shared
Zahoor, Yasir
1 / 1 shared
Voskuijl, Mark
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Meddaikar, Yasser
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Silva, Gustavo
1 / 2 shared
Fassah, Abdul Abdul Rozak Rivai
1 / 1 shared
De Visser, Cornelis
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Bettebghor, Dimitri
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Bordogna, Marco Tito
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Lancelot, Paul
3 / 5 shared
Vanek, Balin
1 / 1 shared
Nagy, Mihaly
1 / 1 shared
Toth, Szabolcs
1 / 1 shared
Gyulai, László
1 / 1 shared
Teubl, Daniel
1 / 1 shared
Roessler, Christian
1 / 1 shared
Rajpal, D.
1 / 3 shared
Kassapoglou, Christos
2 / 6 shared
Rajpal, Darwin
1 / 1 shared
Macquart, Terence
2 / 21 shared
Werter, Noud
2 / 3 shared
Bettebghor, D.
1 / 1 shared
Ferreira, J. P.
1 / 2 shared
Macquart, Tbmj
1 / 1 shared
Bordogna, Mt
1 / 2 shared
Martinez, Marcias
1 / 3 shared
Keidel, Dominic
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Ermanni, P.
1 / 12 shared
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Co-Authors (by relevance)

  • Sodja, Jurij
  • Córcoles, Xavier Carrillo
  • Krüger, Wolf R.
  • Meddaikar, Yasser M.
  • Dillinger, Johannes
  • Wang, Xuerui
  • Mkhoyan, Tigran
  • Peeters, Daniël
  • Wang, Zhijun
  • Zahoor, Yasir
  • Voskuijl, Mark
  • Meddaikar, Yasser
  • Silva, Gustavo
  • Fassah, Abdul Abdul Rozak Rivai
  • De Visser, Cornelis
  • Bettebghor, Dimitri
  • Bordogna, Marco Tito
  • Lancelot, Paul
  • Vanek, Balin
  • Nagy, Mihaly
  • Toth, Szabolcs
  • Gyulai, László
  • Teubl, Daniel
  • Roessler, Christian
  • Rajpal, D.
  • Kassapoglou, Christos
  • Rajpal, Darwin
  • Macquart, Terence
  • Werter, Noud
  • Bettebghor, D.
  • Ferreira, J. P.
  • Macquart, Tbmj
  • Bordogna, Mt
  • Martinez, Marcias
  • Keidel, Dominic
  • Ermanni, P.
OrganizationsLocationPeople

document

Developing the Model Reduction Framework in High Frame Rate Visual Tracking Environment

  • Fassah, Abdul Abdul Rozak Rivai
  • De Visser, Cornelis
  • Breuker, Roeland De
  • Mkhoyan, Tigran
Abstract

The developments in the field of aerospace materials and structures allow the more light weight air vehicles. However, the aircraft body, particularly wing, can deform more appreciably due to the occurrence of flow separation and flutter. Therefore, active control is necessary in order to maintain structural integrity. One of the proposed control methods uses visual tracking for structural state estimation, which reduces complexity in terms of hardware and data processing requirements compared to the conventional method using inertial measurement units and gyroscopes. However, the wing displacement measurement involves a high number of states to estimate. An idea is to implement a model reduction method to be implemented as a mathematical model of the aeroelastic wing to quicken the state estimation process. The proposed method of model reduction by using Modified Frequency-Limited Model Reduction (MFLMR) method by Gugercin and Antoulas (2004) is then augmented with the application of singular perturbation step and validated with simulation in stochastic Gaussian gust regimes for two wing models. The effect of additional singular perturbation step is presented. The results show that the proposed MFLMR method with singular perturbation prevails to replicate the true values in the simulated condition with different wing models in both time domain and frequency domain with smaller error autocorrelation. Further analysis is recommended to be focused on the implementation of the proposed model reduction method to the state and parameter estimation in order to maintain the high sample rate that can be attained by using the controller scheme with visual tracking.

Topics
  • impedance spectroscopy
  • simulation