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  • Research
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  • SE²A - Sustainable and Energy-Efficient Aviation
  • Research
  • ICA B "Flight Physics and Vehicle Systems"
Logo Sustainable and Energy Efficient Aviation of TU Braunschweig
B4.2 - Consistent Multilevel Model Coupling and Knowledge Representation in Multidisciplinary Analysis and Design
  • ICA B "Flight Physics and Vehicle Systems"
    • B5.2 - Application of physics-based finite-element tools in stiffness tailored structures for cryogenic hydrogen storage for improved mechanical and thermo-mechanical response
    • B4.2 - Consistent Multilevel Model Coupling and Knowledge Representation in Multidisciplinary Analysis and Design
    • B4.1- Collaborative Multidisciplinary Structural Design and Thermal Management for Electric Aircraft
    • B3.5 - Production technologies for hybrid suction designs - Bonding of micro-perforated sheets for hybrid laminar flow control suction panels
    • B3.2 - Advancing the additive xHLFC suction panel concept towards wind-tunnel readiness
    • B3.1 - Protective, multifunctional suction shells for hybrid laminar flow control: Design, integration, simulation and testing
    • B2.5 - EverScale - Enhancement and verification of load alleviation technologies by subscale flight testing
    • B2.4- Hybrid load alleviation by fluidic/reversed control and nonlinear structures
    • B2.3 - ARGO2 - Integrated design of control methods for stability of elastic aircraft
    • B1.9 - Validation of turbulent boundary layer-induced sound transmission through a fuselage section
    • B1.8 - Wind-tunnel experiments of advanced design of swept-wing with suction surfaces
    • B1.7 - Extension of Correlation-based Transition Transport Models for Laminar Aircraft Design
    • B1.6 - Effective Design Methods and Design Exploration for Laminar Wing and Fuselage
    • B1.5 - Sensitivities of Laminar Suction Boundary Layers for Large Reynolds Numbers
    • B1.3- Physics of broadband noise of sound sources from installed propulsors
    • JRG-B1 - Physics of Laminar Wing and Fuselage
    • JRG-B2 - Flow Physics of Load Reduction
    • B1.1 - Propeller and wing aerodynamics of distributed propulsion
    • B1.2 - Aerodynamic analysis of partly embedded boundary layer ingesting propulsors
    • B1.3 - Fast non empiric prediction of propulsion installation related noise
    • B1.4 - Transition Prediction and Design of Hybrid Laminar Flow Control on Blended Wing Bodies Based on 3D Parabolized Stability Equations
    • B2.1 - Load reduction potential of nonlinear stiffness and damping technologies
    • B2.2 - Structural technologies enabling load alleviation
    • B2.3 - Active load Reduction for enabling a 1-G wing using fOrward-looking and distributed sensors (ARGO)
    • B2.4 - Morphing structures for the 1g-wing
    • B3.1 - Global and Local Design Methodology for Laminar Flow Control
    • B3.2 - Process simulation and multiscale manufacturing of suction panels for laminar flow control
    • B3.3 - Thin Plies in Application for Next Generation Aircraft (TANGA)
    • B3.4 - New methods for failure and fatigue analysis of suction panels for laminar flow control
    • B5.1 - ADEMAO: Aircraft Design Engine based on Multidisciplinary Analysis and Optimization
    • JRG-B5 - Long-Range Aircraft Configurations and Technology Analyses
    • JRP - Permeation assessment for cryogenic applications by means of Fiber Bragg Grating sensors
    • ⯇ back to research

B4.2 - Consistent Multilevel Model Coupling and Knowledge Representation in Multidisciplinary Analysis and Design

Project B4-2 addresses, in close collaboration with B4.1, the simulation-based design of a skin heat exchanger. The heat rejection system serves as a prototype for unexplored design configurations in new electric aircraft, which covers multiple and coupled disciplines as well as complex physics, data structures and models. 

We present new ideas for coupling multi-disciplinary data on different fidelity levels and for analysing the propagation of errors and uncertainties in coupled problems. Moreover, semantic knowledge representations will be used to impose a semantic structure on the data and the models, which enables a more principled coupling. Further, we will take first steps to explicitly make knowledge design through advanced knowledge representations and explainable AI, which is important in view of the growing modeling complexity and which shall assist designers in the future. 

Multidisciplinary Design Optimization

Figure describes the cooperative workflow with various internal and external solver with different fidelity models. The solvers are coupled by CoSimAPP and Master Geometry

Finding more efficient solutions of complex multidiscipline problems requires not only coupling different physical aspects into one system, but as well different models, solvers and even teams or departments. To enable the use of well-suited, individual, solution techniques for each specific discipline and fidelity, a partitioned solution approach is mandatory, which solves the coupled problem by dedicated coupling algorithms and mappings between the individual solvers. This stands in contrast to so-called monolithic solution approaches where the whole multidisciplinary coupled problem is formulated as a single large coupled discrete system. Essentially, the monolithic approach is often seen as more robust but at the same time unable to deal with a multi-code environment, which is the standard case in industry-level multidisciplinary analysis and design workflows. This flexibility of realizing mixed-fidelity and coupled physics simulations by various solvers requires a consistent formulation of the coupling conditions and the orchestration of the overall simulation workflow with a so-called geometry master model and mapping operators between the diverse simulation tools are key requirements. The master model is achieved here by a B-Rep CAD representation, with multiple coupled and trimmed NURBS patches as shape description. Moreover, the different methods for CAD-integrated simulation are a suitable methodological basis, amongst them the so-called Isogeometric Analysis (IGA) with its extension to real-world B-Rep models of complex geometries, the Isogeometric B-Rep Analysis (IBRA).

The project studies the possibility of realizing a co-simulation framework, which enables efficient and simple cooperation solution, and where various teams can efficiently integrate their models and codes to solve aforementioned complex problems.

Uncertainty Quantification

Uncertainty quantification (UQ) is of particular importance in multidisciplinary systems. Different scales and coupling effects between disciplines often amplify existing uncertainties. Furthermore, the complexity makes it difficult for developers to correctly assess the significance of results based on experience alone.

Multi-fidelity approaches are particularly suitable for uncertainty quantification in multiphysics systems. Since high-resolution simulations in aviation are often very computationally intensive, low-cost surrogate models are constructed and used simultaneously with the full order models. Subsequently, the variable fidelity models of the sub-disciplines are coupled in a modular way for uncertainty analysis.

Knowledge representation

Figure schematically represent the connection between the engineering terms, that are used in the simulation and its link to the available open knowledge data, that describes the used terms.

During development, knowledge might be lost between projects, even between iterations within the same project. Engineers especially can benefit from the fact that human knowledge can be represented and stored with semantic technologies, specifically knowledge graphs and ontologies. These can list an individual airplane that might carry you on your next flight, as well as its model, its design series and the development behind that. Simultaniously, this can extend down to each single screw and rivet used, both again in class that an engineer requires for this task and individual entity that a mechanic places to fullfill it. However, the current status quo in engineering knowledge representation lacks behind it's potential in the usage of state-of-the-art semantic technologies and the interoperability they provide.

With this project, we aim to utilize this potential by integrating knowledge graphs into the KRATOS-based design workflow. Knowledge required and produced by simulations in multi-fidelity multidisciplinary design steps can be seamingly formalised and alligned to be interoperable at all times. We increase the efficiency of knowledge transfer between systems and projects by formalising the knowledge assisted by tools and their access to large-scale knowledge graphs like WikiData. By removing the need for redundant knowledge specification, founding our progress on a literature survey on prior knowledge and it's representation in aerospace enginnering, we are heading to more sustainable knowledge flow, wherin each contributor simultaniously benefits from and beneficiates to the grander knowledge base.

Project Details

Memebers

Institut für Statik und Dynamik

Prof. Dr.-Ing. Roland Wüchner (PI)

 

Ihar Antonau, M.Sc.

Dr.-Ing. Suneth Warnakulasuriya

Institut für Akustik und Dynamik

Prof. Dr.-Ing. Ulrich Römer (PI)

 

Susanna Baars, M.Sc.

TIB

Prof. Dr. Sören Auer (PI)

 

Tim Wittenborg, M.Sc.

Dr. Ildar Baimuratov

Student Projects

Master Thesis Projects

Viral Chheda, "Fluid Structure Interaction with Uncertainty Quantification", 2023

 

 

Project Management

Prof. Dr.-Ing. Roland Wüchner
Institut für Statik und Dynamik, TU Braunschweig
r.wüchner@tu-braunschweig.de

 

Prof. Dr.-Ing. Ulrich Römer
Institut für Akustik und Dynamik, TU Braunschweig
u.roemer@tu-braunschweig.de

Prof. Dr. Sören Auer
TIB, L3S Research Center, Leibniz Universität Hannover
soeren.auer@tib.eu

Intitutions

Institut für Statik und Dynamik, Technische Universität Braunschweig, Beethovenstraße 5, 38106 Braunschweig

 

Institut für Akustik und Dynamik, Technische Universität Braunschweig, Langer Kamp 19, 38106 Braunschweig

Data Science & Digital Libraries Research Group, German National Library of Science and Technology (TIB), Welfengarten 1 B, 30167 Hannover

 

 

 

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Cluster of Excellence SE²A –
Sustainable and Energy-Efficient Aviation
Technische Universität Braunschweig
Hermann-Blenk-Str. 42
38108 Braunschweig

se2a(at)tu-braunschweig.de
+49 531 391 66661

 

 

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