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Article
Publication date: 16 September 2013

Carlos Páscoa, Nelson Ferreira and José Tribolet

The aim of this article is to: provide an overview of the role of organizational simulators as essential tools to assess, at early stages of the planning phase, organizational…

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Abstract

Purpose

The aim of this article is to: provide an overview of the role of organizational simulators as essential tools to assess, at early stages of the planning phase, organizational objectives and strategy; propose recommendations on how to advance the subject area in terms of research and development; demonstrate that aeronautical concepts can be applied in the organizational context.

Design/methodology/approach

The article refers concepts and theories related with the subject and presents a methodology for social investigation, which was used in this research.

Findings

Organizational simulators have a fundamental role in organizational self-awareness because they help to control the organization's vital parameters, in a proactive manner, considering the creation of different scenarios that allow, beforehand, a predictive assessment.

Research limitations/implications

The research provides empirical evidence of use in the operational domain of the Portuguese Air Force and also an example of the valuable collaboration between real operations use and academia research. It also offers an insight, by using the metaphor “Flying the Organization”, on how flying concepts can be applied in the organizational context.

Practical implications

The research lab was done using Microsoft Excel in what was related to the simulator development. All relevant data was gathered from organization's information systems (IS) and inserted into Microsoft Excel. Future implementations should be integrated with the organization's IS.

Originality/value

This article contributes to the “state of art” of organizational simulators by providing a real case and provides both the entrepreneurial and academia communities for conducting future actions within this subject. The article also provides value to organizational management actors on how organizational simulators can be applied.

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Article
Publication date: 7 March 2016

Jakson Augusto Leger Monteiro, José C. Páscoa and Carlos M. Xisto

Cycloidal rotors, also known as cyclogyros, are horizontal axis rotary-wing machines with potential for Vertical Take-Off and Landing aircraft applications. The paper aims to…

419

Abstract

Purpose

Cycloidal rotors, also known as cyclogyros, are horizontal axis rotary-wing machines with potential for Vertical Take-Off and Landing aircraft applications. The paper aims to devise and validate a new semi-empirical analytical model that is capable of assisting in the structural and aerodynamic design of cyclogyros.

Design/methodology/approach

The analytical model comprises a purely analytical kinematic sub-component that is used for analyzing the structural feasibility of the rotor. Several geometrical parameters are assessed, e.g. the oscillation schedule of the blades as a function of the properties of the pitching mechanical system. The dynamic sub-component of the model is used for estimating the rotor thrust production and power consumption. This sub-component is semi-empirical and uses a calibration function that was devised using the available experimental data.

Findings

For a set of initial conditions and geometrical parameters, the model is capable of providing a real animation of the cyclogyro operation. It is shown that the motion of the blades does not comply with the requirements of a perfect cycloidal curve. The study concerning the simulation of the virtual camber effect on the drum blades, with and without the pitch effect, shows that the virtual camber strongly depends on the chord-to-radius ratio and on the aircraft advance velocity.

Originality/value

A new analytical model capable of assisting in the geometrical and aerodynamic design of cyclogyros is here proposed. The model is capable of providing approximate estimations of the cyclogyro thrust production and power consumption under operating design conditions.

Details

Aircraft Engineering and Aerospace Technology: An International Journal, vol. 88 no. 2
Type: Research Article
ISSN: 1748-8842

Keywords

Available. Content available
Article
Publication date: 16 September 2013

Joao Varajao

1080

Abstract

Details

The Learning Organization, vol. 20 no. 6
Type: Research Article
ISSN: 0969-6474

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Article
Publication date: 30 July 2024

Ananthajit Ajaya Kumar and Ashwani Assam

Deep-learning techniques are recently gaining a lot of importance in the field of turbulence. This study focuses on addressing the problem of data imbalance to improve the…

52

Abstract

Purpose

Deep-learning techniques are recently gaining a lot of importance in the field of turbulence. This study focuses on addressing the problem of data imbalance to improve the performance of an existing deep learning neural network to infer the Reynolds-averaged Navier–Stokes solution, proposed by Thuerey et al. (2020), in the cases of airfoils with high wake formation behind them. The model is based on a U-Net architecture, which calculates pressure and velocity solutions for fluid flow around an airfoil.

Design/methodology/approach

In this work, we propose various methods for training the model on selectively generated data with different distributions, which would be representative of the under-performing test samples. The property we chose for selectively generating data was the fraction of negative x-velocity in the domain. We have used Grad-CAM to compare the layer activations of different models trained using the proposed methods.

Findings

We observed that using our methods, the average performance on the samples with high wake formation (i.e. flow over airfoils at high angle of attack) has improved. Using one of the proposed methods, an average performance improvement of 15.65% was observed for samples of unknown airfoils compared to a similar model trained using the original method.

Originality/value

This work demonstrates the use of imbalanced learning in the field of fluid mechanics. The performance of the model is improved by giving significance to the distribution of the training data without changes to the model architecture.

Details

Engineering Computations, vol. 41 no. 7
Type: Research Article
ISSN: 0264-4401

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