https://repositorio.ufu.br/handle/123456789/5466 2026-08-02T07:20:39Z 2026-08-02T07:20:39Z https://repositorio.ufu.br/handle/123456789/49169 2026-07-31T06:23:51Z 2026-07-21T00:00:00Z

Title: Comportamento de revestimentos de ferramentas de corte no fresamento do Inconel 718 Abstract: This study aimed to investigate the influence of different coatings applied to solid carbide end mills in the end milling of Inconel 718, a nickel-based superalloy characterized by high mechanical strength and low machinability. Three commercial coatings (ALCRONA EVO® (AlCrN), TISAFLEX® (AlTiN/TiSiXN), and LATUMA® (AlTiN)) were evaluated, in addition to an uncoated condition, under different combinations of cutting speed (50 and 80 m/min) and feed per tooth (0.035 and 0.070 mm/tooth). The experimental tests included the analysis of tool life, surface roughness, cutting temperature, cutting forces, and chip morphology. Tool life was determined based on a maximum flank wear criterion of 0.3 mm and expressed in terms of volume of material removed. Surface roughness was evaluated using the Ra parameter, temperature was measured by infrared thermography under dry conditions, and cutting forces were monitored using a piezoelectric rotating dynamometer. Chip morphology was qualitatively analyzed using optical microscopy. The results showed that tool performance was significantly influenced by the coating, with TISAFLEX® exhibiting the best performance and longest tool life, while the uncoated tool showed the poorest results. Feed per tooth was identified as the most influential parameter, leading to reduced tool life and increased surface roughness (Ra) and cutting forces. Temperature measurements presented relatively low values, attributed to the short cutting length, although an increasing trend was observed along the cutting pass. The chips exhibited similar geometry across the evaluated conditions, being more influenced by the cutting parameters than by the coating. Overall, the results demonstrate that the proper combination of coating and cutting parameters is essential to improve the milling of Inconel 718, contributing to enhance the tool life and surface quality.

2026-07-21T00:00:00Z https://repositorio.ufu.br/handle/123456789/49158 2026-07-30T06:25:27Z 2026-02-26T00:00:00Z

Title: Aplicação de redes neurais convolucionais a imagens de modelos térmicos para a estimativa de tamanho e posição de inclusões que simulam tumores mamários Abstract: Breast cancer is the most prevalent and deadly neoplasm among women worldwide, highlighting the urgent need for early detection strategies that are accurate, safe, and accessible. Mammography, while the gold standard, has limitations, including repeated radiation exposure, reduced sensitivity in dense breasts, and reliance on expert interpretation, while ultrasound and magnetic resonance imaging increase cost and complexity. Infrared thermography emerges as a non-invasive, low-cost, and radiation-free alternative, but visual inspection alone lacks the sensitivity to detect deep or small tumors. In this context, machine learning methods have shown promise in extracting subtle thermal patterns beyond human perception. This study implements and trains convolutional neural networks in Python using the Tensorflow library to learn the position and diameter of a spherical inclusion in thermal models, using steady-state temperature maps generated through finite element simulations in Ansys Mechanical. The methodology is applied to two thermal models: i) parallelepiped: simulating an experiment performed on a silicon parallelepiped with inclusions of spheres heated by thermal resistors, the neural network trained with 270 matrices (27x39) achieved an accuracy of 99.10% and a sensitivity of 98.10%, and was able to correctly predict the position and diameter of the inclusion when applied to an experimental thermogram. ii) anatomical model: simulating metabolically active tumor tissue immersed in anatomical breast geometry representing healthy breast tissue, the neural network trained with 965 matrices (50x50) achieved an accuracy of 97.63% and a sensitivity of 95.62%. These results demonstrate that a neural network can reliably learn geometric and physical characteristics related to inclusions (which simulate the presence of tumors) from low-resolution thermal data, indicating the feasibility of using artificial intelligence applied to thermal images for tumor detection.

2026-02-26T00:00:00Z https://repositorio.ufu.br/handle/123456789/49122 2026-07-28T06:21:53Z 2026-06-16T00:00:00Z

Title: Revisão e proposta de estratégia de controle de movimento para um gerador linear a ímã permanente movido a pistão livre para regime permanente Abstract: This work investigates motion control in a free-piston linear generator (FPLG), with the objective of regulating electromagnetic energy extraction in order to ensure stable operation within mechanical limits and adequate performance in electrical power generation. For this purpose, the system is modeled as a combustion-excited mass–spring oscillator in which the electromagnetic force is represented as an equivalent damping proportional to the piston velocity, considering an electrical architecture composed of passive three-phase rectification followed by a DC–DC boost converter. Three control strategies are developed and evaluated under the same modeling and excitation conditions: (i) proportional–integral control with peak displacement detection, (ii) control based on the mechanical energy of the cycle, and (iii) nonlinear model predictive control (NMPC). The comparison is carried out in terms of piston stroke, oscillatory regime stability, energy balance, and DC power delivered to the load. The results show that PI control with peak detection achieves good steady-state performance, but with higher latency under disturbances; the mechanical-energy-based control regulates energy extraction throughout the oscillation cycle, contributing to stroke containment and robustness to combustion variations; and NMPC enables explicit handling of operational constraints, at the cost of increased command modulation and lower uniformity of the electrical power in the considered architecture. It is concluded that the strategies present different trade-offs between mechanical stability, robustness, and energy utilization, providing a comparative basis for controller design in FPLGs.

2026-06-16T00:00:00Z https://repositorio.ufu.br/handle/123456789/49042 2026-07-25T06:28:00Z 2026-07-02T00:00:00Z

Title: Projeto e maximização de desempenho de um reator de gaseificação com sistema de craqueamento de alcatrão Abstract: Aiming to meet global greenhouse gas emission reduction targets, solutions related to wasteto- energy recovery have gained prominence for enabling the monetization of an environmental liability. Among the available methods to achieve this purpose, the gasification process stands out due to the versatility of the generated synthesis gas (syngas), which can be applied in thermal and electrical power generation, as well as the production of hydrogen and other synthetic fuels. To carry out this process, the reactor must ensure a controlled atmosphere where the waste is thermally conditioned. Aiming to increase system efficiency, the design and the fluid dynamics and structural simulations were conducted using Siemens NX, Ansys Fluent, ANSYS Rocky, and MATLAB software. The objective was to design an optimized gasifier capable of mitigating condensable tar by increasing the filtration efficiency and the average gas residence time inside it. To this end, a computational study was performed through fluid dynamics simulations of high-temperature (800 °C) cyclones connected in series inside the reactor. For these simulations, several geometric alterations that dictate the behavior of these cyclones were tested, namely: pressure drop, filtration efficiency, and average residence time. These variables present a trade-off among themselves, which must be balanced to allow the formation of a clean syngas. Once the cyclone configuration was determined, a recirculation system for gas and filtered particles operating under the Venturi effect was added to its base. This mechanism considerably increased the filtration efficiency of the cyclones by scaling up their cut-off diameter, allowing them to capture nanometric particles, with the cyclone combination showing an overall efficiency of 100%. Furthermore, it extended the gas residence time inside the gasifier to 40.6 seconds, which, according to the scientific literature, contributes to mitigating condensable tar in the reactor. Additionally, a thermal study was conducted for modeling the outer shell, along with kinematic and structural simulations for developing an inspection door. Finally, a simulation of the behavior of the internal components subjected to a pressure of 0,2 bar and a temperature of 800 °C was carried out, identifying stress concentration points and displacements that could affect the structural integrity of the reactor.

2026-07-02T00:00:00Z