https://repositorio.ufu.br/handle/123456789/19234 2026-04-07T17:03:01Z https://repositorio.ufu.br/handle/123456789/47947 Title: Estudo do comportamento termomecânico de ferramentais de montagem de estruturas aeronáuticas Abstract: The present work investigates the thermomechanical behavior of assembly tooling for flight critical components, focusing on control surfaces and the effects of thermal expansion on product tolerances. The analysis carried out is extremely useful for assembly processes located in thermally uncontrolled environments. Temperature measurements were performed on the assembly jigs of control surfaces from two aircraft during two hot days, including ambient and ceiling temperatures in the hangar where these tools were located. Structural models were developed to perform finite element analyses (FEA), revealing significant displacements in the vertical and transverse directions, directly impacting hinge tolerances and causing assembly delays in the absence of corrective shims. To generalize the analysis, a thermal model based on the Lumped Capacitance Method (LCM) was created to estimate surface temperatures from environmental conditions. The model showed an average error below 10%, and the subsequent structural analyses confirmed the displacement results with a low error and differences between the built models around 0.06 mm, validating the methodology for future evaluations in assembly processes. 2025-11-06T00:00:00Z https://repositorio.ufu.br/handle/123456789/47872 Title: Análise de fadiga em engrenagem planetária do EC225 via simulação computacional Abstract: This study presents the analysis and development of a computational model of the planetary gear located in the Main Gear Box (MGB) of the EC225 Super Puma helicopter, with the objective of mitigating component failures caused by fatigue. Fatigue failures in transmission system components are recurrent due to their exposure to cyclic loads. In this study, the accident involving CHC Flight 241 near Turøy, Norway, was investigated, which occurred as a result of fatigue failure in the planetary gear of the MGB of the EC225 Super Puma. Based on this case, an analysis was conducted and improvements to the component were proposed, employing SolidWorks software for the creation of the Computer-Aided Design (CAD) model and ANSYS software to perform structural fatigue simulations using the Finite Element Method (FEM). Additionally, fatigue criteria and methodologies were examined to support the simulations. Following the study and analysis of the simulations of the gear manufactured from 16NCD13 steel, the original material of the gear, a solution was proposed to enhance the material of the studied component. A comparative evaluation was carried out between the original steel and Maraging 18Ni steel and 300M steel. The simulation results revealed a significant increase in the number of complete life cycles of the component when using Maraging or 300M steel, with Maraging steel demonstrating superior improvement. Through computational analysis and the applied methodologies, this research provides a material enhancement solution for the studied component, contributing to increased reliability and safety in aeronautical engineering projects. 2025-11-27T00:00:00Z https://repositorio.ufu.br/handle/123456789/47462 Title: Integração de Interface Conversacional (Chatbot) a uma Aplicação Web para Gestão de Consultas Médicas 2025-09-29T00:00:00Z https://repositorio.ufu.br/handle/123456789/47330 Title: Predição de Desempenho Termodinâmico em Projeto Conceitual de Motores Aeronáuticos (Off-Design) com Inteligência Artificial Abstract: The technological race for competitiveness and efficient, economic, and environmental soluti ons has been expressly transformed by the implementation of artificial intelligence (AI). In the aerospace sector, the topic is widely discussed in academic and industrial research, planning, ethics, cybersecurity, airworthiness, and certification. In this context, AI is identified as an op portunity to explore its usefulness in conceptual phase projects, specifically in turbofan engines. The general objective of this work is to develop an artificial intelligence meta-model capable of predicting the thermodynamic performance of turbofan engines under off-design conditions, considering critical variables such as thrust, specific fuel consumption, efficiencies, nitrogen oxides (NOx) emissions, turbine inlet temperature, among others. The methodology involved three stages: a thermodynamic on-design project inspired by the GE90 engine and historical success trends; followed by off-design simulations in GasTurb 15 (76 scenarios); and finally, the development of a prediction meta-model using the Gradient Boosting Regressor algorithm in Python, with Mach, altitude, and flight phase as input variables. The results showed high predictive accuracy, surpassing Random Forest and demonstrating good generalization, al though with limitations in some flight phases, indicating the need to expand the database. It is concluded that the approach proved promising as decision support in aerospace propulsion, especially regarding the expansion of analyses in the conceptual phase concomitant with design time reduction, with prospects for future applications in other conceptual design scenarios, cer tification, and sustainability. 2025-09-29T00:00:00Z