Model-Based Systems Engineering Tool-Chain for Automated Parameter Value Selection

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Publications associées (31)

Model-based Systems Engineering Papers Analysis based on Word Cloud Visualization

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With the continuous improvement of system scale and complexity, model-based system engineering (MBSE) is of great importance in the practice of system engineering (SE). MBSE has been widely concerned in industry, especially in the field of complex equipmen ...

IEEE2022

Systematic Literature Review of MBSE Tool-Chains

Dimitrios Kyritsis, Yan Yan, Jinzhi Lu

Currently, the fundamental tenets of systems engineering are supported by a model-based approach to minimize risks and avoid design changes in late development stages. The models are used to formalize, analyze, design, optimize, and verify system developme ...

MDPI2022

A semantic-driven tradespace framework to accelerate aircraft manufacturing system design

Dimitrios Kyritsis, Jinzhi Lu, Xiaochen Zheng

During the design phase of an aircraft manufacturing system, different industrial scenarios need to be evaluated according to key performance indicators to achieve the optimal system performance. It is a highly complex process involving multidisciplinary s ...

SPRINGER2022

Ontology-based system to support industrial system design for aircraft assembly

Dimitrios Kyritsis, Jinzhi Lu, Xiaochen Zheng

The development of an aircraft industrial system is a complex process which faces the challenge of digital discontinuity in multidisciplinary engineering due to various interfaces between different digital tools, leading to extra development time and costs ...

ELSEVIER2022

Contrastive Class-aware Adaptation for Domain Generalization

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Domain generalization (DG) tackles the problem of learning a model that generalizes to data drawn from a target domain that was unseen during training. A major trend in this area consists of learning a domain-invariant representation by minimizing the disc ...

IEEE2022

Bridging the gap between model-driven and data-driven methods in the era of Big Data

Gael Lederrey

Data-driven and model-driven methodologies can be regarded as competitive fields since they tackle similar problems such as prediction. However, these two fields can learn from each other to improve themselves. Indeed, data-driven methodologies have been d ...

EPFL2022

STEPS 4.0: Fast and memory-efficient molecular simulations of neurons at the nanoscale

Felix Schürmann, James Gonzalo King, Christos Kotsalos, Pramod Shivaji Kumbhar, Iain Hepburn, Weiliang Chen, Tristan Mathieu Carel, Samuel Marie A Melchior, Omar Awile, Baudouin Paul Michel Maria Joseph Del Marmol, Alessandro Cattabiani, Giacomo Castiglioni, Nicola Cantarutti

Recent advances in computational neuroscience have demonstrated the usefulness and importance of stochastic, spatial reaction-diffusion simulations. However, ever increasing model complexity renders traditional serial solvers, as well as naive parallel imp ...

FRONTIERS MEDIA SA2022

Combining hypothesis- and data-driven neuroscience modeling in FAIR workflows

Daniel Keller

Modeling in neuroscience occurs at the intersection of different points of view and approaches. Typically, hypothesis-driven modeling brings a question into focus so that a model is constructed to investigate a specific hypothesis about how the system work ...

2022

The DESI N-body Simulation Project - II. Suppressing sample variance with fast simulations

Yu Yu, Andrei Variu, Cheng Zhao, Hanyu Zhang

Dark Energy Spectroscopic Instrument (DESI) will construct a large and precise three-dimensional map of our Universe. The survey effective volume reaches similar to 20 h(-3) Gpc(3). It is a great challenge to prepare high-resolution simulations with a much ...

OXFORD UNIV PRESS2022

Modeling of second-order nonlinear metasurfaces

Olivier Martin, Karim Achouri, Andrei Kiselev

We present a frequency-domain modeling technique for second-order nonlinear metasurfaces. The technique is derived from the generalized sheet transition conditions (GSTCs), which have been so far mostly used for modeling linear metasurfaces. In this work, ...

IOP Publishing Ltd2022

Vision-based Flocking in Aerial Robot Swarms

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Aerial robot swarms have the potential to perform time-critical and dangerous tasks such as disaster response without compromising human safety. However, their reliance on external infrastructure such as global positioning for localization and wireless net ...

EPFL2022

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