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The purpose of this paper is to present the result of calculations that were performed to estimate the structural weight of the passenger aircraft using novel technological solution. Mass penalty resulting from the installation of the fuselage boundary layer ingestion device was needed in the CENTRELINE project to be able to estimate the real benefits of the applied technology.

This paper focusses on the finite element analysis (FEA) of the fuselage and wing primary load-carrying structures. Masses obtained in these analyses were used as an input for the total structural mass calculation based on semi-empirical equations.

Combining FEA with semi-empirical equations makes it possible to estimate the mass of structures at an early technology readiness level and gives the possibility of obtaining more accurate results than those obtained using only empirical formulas. The applied methodology allows estimating the mass in case of using unusual structural solutions, which are not covered by formulas available in the literature.

Accurate structural mass estimation is possible at an earlier design stage of the project based on the presented methodology, which allows for easier and less costly changes in designed aircrafts.

The presented methodology is an original method of mass estimation based on a two-track approach. The analytical formulas available in the literature have worked well for aeroplanes of conventional design, but thanks to the connection with FEA presented in this paper, it is possible to estimate the structure mass of aeroplanes using unconventional technological solutions.

This paper aims to introduce a non-invasive and convenient method to detect a life-threatening disease called aortic dissection. A Bayesian inference based on enhanced multi-sensors impedance cardiography (ICG) method has been applied to classify signals from healthy and sick patients.

A 3D numerical model consisting of simplified organ geometries is used to simulate the electrical impedance changes in the ICG-relevant domain of the human torso. The Bayesian probability theory is used for detecting an aortic dissection, which provides information about the probabilities for both cases, a dissected and a healthy aorta. Thus, the reliability and the uncertainty of the disease identification are found by this method and may indicate further diagnostic clarification.

The Bayesian classification shows that the enhanced multi-sensors ICG is more reliable in detecting aortic dissection than conventional ICG. Bayesian probability theory allows a rigorous quantification of all uncertainties to draw reliable conclusions for the medical treatment of aortic dissection.

This paper presents a non-invasive and reliable method based on a numerical simulation that could be beneficial for the medical management of aortic dissection patients. With this method, clinicians would be able to monitor the patient’s status and make better decisions in the treatment procedure of each patient.

The purpose of this paper is to present the status of the on-going development of the new computerized environment for aircraft synthesis and integrated optimization methods (CEASIOM) and to compare results of different aerodynamic tools. The concurrent design of aircraft is an extremely interdisciplinary activity incorporating simultaneous consideration of complex, tightly coupled systems, functions and requirements. The design task is to achieve an optimal integration of all components into an efficient, robust and reliable aircraft with high performance that can be manufactured with low technical and financial risks, and has an affordable life-cycle cost.

CEASIOM (www.ceasiom.com) is a framework that integrates discipline-specific tools like computer-aided design, mesh generation, computational fluid dynamics (CFD), stability and control analysis and structural analysis, all for the purpose of aircraft conceptual design.

A new CEASIOM version is under development within EU Project AGILE (www.agile-project.eu), by adopting the CPACS XML data-format for representation of all design data pertaining to the aircraft under development.

Results obtained from different methods have been compared and analyzed. Some differences have been observed; however, they are mainly due to the different physical modelizations that are used by each of these methods.

This paper summarizes the current status of the development of the new CEASIOM software, in particular for the following modules: CPACS file visualizer and editor CPACSupdater (Matlab) Automatic unstructured (Euler) & hybrid (RANS) mesh generation by sumo Multi-fidelity CFD solvers: Digital Datcom (Empirical), Tornado (VLM), Edge-Euler & SU2-Euler, Edge-RANS & SU2-RANS Data fusion tool: aerodynamic coefficients fusion from variable fidelity CFD tools above to compile complete aero-table for flight analysis and simulation.