Marcelo Santiago de Sousa
Universidade Federal de Itajubá
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Featured researches published by Marcelo Santiago de Sousa.
Archive | 2016
Sebastião Simões da Cunha; Marcelo Santiago de Sousa; Danilo Pereira Roque; Alexandre C. B. Ramos; Pedro Fernandes
In this paper we seek to present the mathematical model relating to flight dynamics of a rotary-wing aircraft. The procedure starts by linearizing the translational and rotational dynamics and rotational kinematic equations of motion based on perturbation theory. Some procedures are simplified and are implemented here, due to the complex modeling process. The second step is to obtain the linear form, which is fundamental in order to describe the stability and response of the small movements of the helicopter around a specific attitude. Finally, the dynamic behavior of two helicopters (AS355-F2 Squirrel and BO105-S123) was simulated employing MATLAB Simulink v7.6 (2008) [1]. The input data, status and control derivatives from an existing helicopter were employed. It is noteworthy that the linearized model developed here is valid for applications where a deeper representation of the aircraft is not required.
Archive | 2018
Pedro Fernandes; Alexandre C. B. Ramos; Danilo Pereira Roque; Marcelo Santiago de Sousa
This paper presents a method for time series forecasting based on pattern recognition. As the system receives samples of time series, each of them representing one variable from the set of variables that describe the behavior of an application model, these samples are evaluated using a PCA algorithm, where each sample is represented by a feature vector. Different feature vectors (each of them representing a different sample of a particular case) are compared for pattern recognition. Once this sequence of steps is well performed, it’s possible to estimate time series for different states between those represented by the previously analyzed samples. As an example for application of this method, a case study is presented for some variables under specific flight conditions. The chosen application for this case study, helicopter flight dynamics is a relevant study, for it can be used, for example, to provide precise data to a flight simulator, which implies in an important issue for pilot training, and subsequently, this type of application may help reducing the probability of pilots faults in real flight missions. To demonstrate the applicability of the method, this paper shows results obtained when the system generated forecasts for flight dynamics variables in a specific scenario of initial conditions and while the helicopter performed a maneuver of response to collective command. Finally, some considerations are made about the work shown in this paper as the results, discussions and conclusions are presented.
Archive | 2018
Pedro FernandesJr.; Alexandre C. B. Ramos; Danilo Pereira Roque; Marcelo Santiago de Sousa
This paper presents a method for the development of artificial neural networks (ANN) that consists in the use of a search space algorithm to adjust the components of an ANN’s initial structure, based on the performance obtained by different network configurations. Also, it is possible to represent an ANN’s structure as a genetic sequence, which enables directly loading a corresponding genetic sequence to instantly generate and run a previously trained ANN. This paper also shows some results obtained by different ANNs developed by this method, which demonstrate its features by analyzing its accuracy and trueness. As an example for application of this method, a case study is presented for a specific flight simulation, using data obtained from a helicopter’s flight dynamics simulator for ANN training. Helicopter flight dynamics is a relevant study, for it can be used, for example, to provide precise data to a flight simulator, which implies in an important issue for pilot training, and subsequently, this type of application may help reducing the probability of pilot’s faults in a real flight mission. Finally, some considerations are made about the work shown in this paper as the results, discussions and conclusions are presented.
International Journal of Industrial and Systems Engineering | 2017
Marcelo Santiago de Sousa; Felipe Martins Torres; Ariosto Bretanha Jorge
The use of system theoretic accident model and processes (STAMP) is presented in this work in order to increase the efficiency in a production system. The motivation for this research is the possibility to apply STAMP together with the Lean philosophy and tools, to eliminate wastes in a production system. The main contribution of this study is based on the application of the methodology STAMP (commonly used for safety/security analyses and identification of accident causes) as a management tool. Besides assisting Lean on the wastes elimination, STAMP can help the process of taking decisions in a company. The results obtained and presented in this work show that STAMP methodology has the potential to be used together with the Lean approach, allowing the acquisition of more information than in the case where only Lean was used.
XXXVIII Iberian-Latin American Congress on Computational Methods in Engineering | 2017
Nycolas de Lima Santos; Sebastião Simões da Cunha; Marcelo Santiago de Sousa; Rafaella Barrêto Campos
Revista Interdisciplinar de Pesquisa em Engenharia - RIPE | 2017
Rafaella Barrêto Campos; Sebastião Simões da Cunha Júnior; Marcelo Santiago de Sousa; Nycolas de Lima Santos; Caue da Silva Camilo
Procceedings of the 24th ABCM International Congress of Mechanical Engineering | 2017
Rodrigo Zanatta; Marcelo Santiago de Sousa; Sebastião Simões da Cunha
AIAA Modeling and Simulation Technologies Conference | 2017
Adson A. de Paula; Fabricio M. Porto; Marcelo Santiago de Sousa
AIAA Modeling and Simulation Technologies Conference | 2017
Marcelo Santiago de Sousa; Adson A. de Paula; Fabricio M. Porto; Sebastião Simões da Cunha Júnior
55th AIAA Aerospace Sciences Meeting | 2017
Adson A. de Paula; Fabricio M. Porto; Marcelo Santiago de Sousa