Hierarchical component-wise models for enhanced stress analysis and health monitoring of composites structures

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Refined 1D finite elements for thin-walled curved structures

This paper presents numerical results on the static and dynamic analysis of thinwalled, composite structures. The results are obtained via 1D finite elements based on refined beam theories. The Carrera Unified Formulation (CUF) is employed to build the refined theories. In the CUF framework, structural models can be obtained using expansions of the unknown variables along the cross-section of the beam. Any expansion type can be employed; for instance, polynomial, exponential, harmonic, etc.. Moreover, the order of the expansion can be set as an input, and chosen via a convergence analysis. Such features stem from the use of a few fundamental nuclei to obtain the governing equations and the finite element matrices. The formal expressions of the nuclei are independent of the order and the type of the expansion. 1D CUF models can provide 3D-like accuracies with low computational cost. Moreover, nonclassical effects, such as warping, can be dealt with straightforwardly. This paper shows the latest extension of 1D CUF models. Legendre polynomials are employed as expansion functions of the displacement variables. The use of Legendre polynomials allows the parametrization of the cross-section geometry to tackle complex geometries, such as curved boundaries. The Principle of Virtual Displacements (PVD) is employed to obtain the finite element matrices. Various structural configurations are considered, including composite, thin-walled, curved structures. The results are compared with those from literature and 3D finite element models

Bias Estimation for Evaluation of ATC surveillance systems

This paper describes an off-line bias estimation and correction system for air traffic control related sensors, used in a newly developed Eurocontrol tool for the assessment of ATC surveillance systems. Current bias estimation algorithms are mainly focused in radar sensors, but the installation of new sensors (especially automatic dependent surveillance-broadcast and wide area multilateration) demands the extension of those procedures. In this paper bias estimation architecture is designed, based on error models for all those sensors. The error models described rely on the physics of the measurement process. The results of these bias estimation methods will be exemplified with simulated data

Air traffic generation for new terminal area air traffic management concepts design and evaluation

This paper describes two systems that can be used to obtain realistic random traffic samples in a terminal area: a real traffic analyser and a synthetic traffic generator. These two systems allow the air traffic management (ATM) engineer to gain insight on the traffic structure of the area under analysis, and allow obtaining realistic traffic samples enabling the evaluation of new operational concepts, the validation or system performance measurement after procedure changes, the analysis of ATM performance under forecasted future traffic changes, etc. Together with the design of the system, the work provides insight of user interfaces and describes the potential uses of such tools in an integrated ATM system

Capturing the Severity and Impairment Associated With Depression: The Overall Depression Severity and Impairment Scale (ODSIS) Validation in a Spanish Clinical Sample

Background: The Overall Depression Severity and Impairment Scale (ODSIS) is a self-report scale designed to evaluate the severity and functional impairment associated with depression. Objective: This study evaluated the psychometric properties of the online version of the ODSIS in Spanish outpatients with depression and anxiety disorders. Method: Patients with a main diagnosis of a depressive (n = 283) or anxiety disorder (n = 191) and a mean age of 38.15 (SD = 12.06) were evaluated with a clinical diagnostic interview and measures assessing depression, anxiety, positive and negative affect, and quality of life. Factorial structure, internal consistency, convergent, and discriminant validity and cutoff scores were analyzed. Results: Consistent with previous validations of the instrument, Confirmatory Factor Analysis showed a unidimensional factor structure. Furthermore, the results obtained supported the internal consistency and construct validity of the ODSIS scores. A score of 5 was found to meet the criteria used in this study for the optimal cutoff score. Conclusion: The results obtained in this study show that the Spanish version of the ODSIS delivered online is an adequate tool to assess the depression-related severity and impairment in a brief and easy fashion