Engenharia Mecânica
URI permanente desta comunidadehttps://repositorio.fei.edu.br/handle/FEI/23
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Resultados da Pesquisa
- Optimal coordination strategy to form and dissolve truck platoons on a highway stretch(2022) DE SOUZA MENDES, A.; Fabrizio Leonardi; DE TOLEDO FLEURY, A.© 2022, The Author(s), under exclusive licence to The Brazilian Society of Mechanical Sciences and Engineering.This paper presents a coordination strategy to optimally form and dissolve N-truck platoons on a highway stretch. Truck platooning, a set of trucks driving with small inter-vehicle distances, can benefit the transportation sector by reducing the overall fuel consumption and greenhouse gas emissions while increasing traffic throughput. However, different itineraries and delivery time restrictions may limit the opportunities to from platoons on a large scale. Therefore, a coordination strategy must be capable of merging scattered trucks and splitting the platoon considering the constraints from each participant to avoid penalties. To address this issue, an optimization problem is formulated to provide optimal speed profiles for an unlimited number of trucks during the merging, platooning and splitting phases of the coordination. An equivalent single stretch representation is presented to simplify complex road networks using appropriate merging and splitting constraints. The resulting optimal speed profiles are presented for 2, 3 and 10 trucks highlighting the capability to handle different desired traveling speeds without compromising the itinerary of each truck and allowing the overtake of trucks directly in the optimization problem. Sensitivity analyses are used to investigate the savings potential according to the main parameters of the coordination. Finally, the proposed algorithm is evaluated in a simulation study using validated vehicle and consumption models with real road topography data. In a 100 km Brazilian highway stretch, scenarios with two and three scattered trucks with substantial initial separation distances are evaluated and present energy efficient maneuvers under the proposed coordination strategy.
- Thermodynamic analysis and optimization of a multi-stage compression system for CO2 injection unit: NSGA-II and gradient-based methods(2021-10-10) ALLAHYARZADEH-BIDGOLI, A.; DE MELO, P. E. B.; DEZAN, D. J.; SALTARA, F.; SALVIANO, O.; YANAGIHARA, J. I.© 2021, The Brazilian Society of Mechanical Sciences and Engineering.The injection of CO2 into oil reservoirs is used by the oil and gas industry for enhanced oil recovery (EOR) and/or the reduction of environmental impact. The compression systems used for this task work with CO2 in supercritical conditions, and the equipment used is energy intensive. The application of an optimization procedure designed to find the optimum operating conditions leads to reduced energy consumption, lower exergy destruction, and reduced CO2 emissions. First, this work presents two thermodynamic models to estimate the amount of power necessary for a multi-stage CO2 compression system in floating production storage and offloading (FPSO) using accurate polytropic relationships and equations of state. Second, a thermodynamic analysis using the first and second laws of thermodynamics is conducted to identify possible improvements in energy consumption and the sources of the compression unit’s irreversibilities. In the final step, optimization procedures, using two methods with different approaches, are implemented to minimize the total power consumption. As the number of stages and the pressure drop between them influence the total power required by the compressors, these are considered as the input parameters used to obtain the inlet pressure at each stage. Three different compositions with variations in CO2 content, i.e., pure CO2, pure CH 4, and 70% CO2 + 30% CH 4, are also investigated as three different operating scenarios. The optimal configurations and pressure ratios result in a reduction in power consumption of up to 9.65%, mitigation of CO2 emissions by up to 1.95 t/h, and savings in exergy loss of up to 23.9%, when compared with conventional operating conditions.
- Optimized network structure for full-synchronization(2009-06-05) Carareto R.; Orsatti F. M.; Piqueira J.R.C.A network of Kuramoto oscillators with different natural frequencies is optimized for enhanced synchronizability. All node inputs are normalized by the node connectivity and some important properties of the network structure are determined in this case: (i) optimized networks present a strong anti-correlation between natural frequencies of adjacent nodes; (ii) this anti-correlation should be as high as possible since the average path length between nodes is maintained as small as in random networks; and (iii) high anti-correlation is obtained without any relation between nodes natural frequencies and the degree of connectivity. We also propose a network construction model with which it is shown that high anti-correlation and small average paths may be achieved by randomly rewiring a fraction of the links of a totally anti-correlated network, and that these networks present optimal synchronization properties. © 2008 Elsevier B.V. All rights reserved.
- MQL Strategies Applied in Ti-6Al-4V Alloy Milling-Comparative Analysis between Experimental Design and Artificial Neural Networks(2020-08-30) PASCHOALINOTO, NELSON WILSON; BATALHA, GILMAR FERREIRA; Ed Claudio Bordinassi; FERRER, JORGE ANTONIO GILES; LIMA FILHO, ADERVAL FERREIRA DE; RIBEIRO, GLEICY DE L. X.; CARDOSO, CRISTIANOThis paper presents a study of the Ti-6Al-4V alloy milling under different lubrication conditions, using the minimum quantity lubrication approach. The chosen material is widely used in the industry due to its properties, although they present difficulties in terms of their machinability. A minimum quantity lubrication (MQL) prototype valve was built for this purpose, and machining followed a previously defined experimental design with three lubrication strategies. Speed, feed rate, and the depth of cut were considered as independent variables. As design-dependent variables, cutting forces, torque, and roughness were considered. The desirability optimization function was used in order to obtain the best input data indications, in order to minimize cutting and roughness efforts. Supervised artificial neural networks of the multilayer perceptron type were created and tested, and their responses were compared statistically to the results of the factorial design. It was noted that the variables that most influenced the machining-dependent variables were the feed rate and the depth of cut. A lower roughness value was achieved with MQL only with the use of cutting fluid with graphite. Statistical analysis demonstrated that artificial neural network and the experimental design predict similar results.
- Searching for strategies to reduce the mechanical demands of the sit-to-stand task with a muscle-actuated optimal control model(2016) Bobbert M.F.; Kistemaker D.A.; Vaz M.A.; Marko Ackermann© 2016Background The sit-to-stand task, which involves rising unassisted from sitting on a chair to standing, is important in daily life. Many people with muscle weakness, reduced range of motion or loading-related pain in a particular joint have difficulty performing the task. How should a person suffering from such impairment best perform the sit-to-stand task and, in the case of pain in a particular joint, with reduced loading of that joint? Methods We developed a musculoskeletal model with reference parameter values based on properties of healthy strong subjects. The model's muscle stimulation-time input was optimized using direct collocation to find strategies that yielded successful sit-to-stand task performance with minimum ‘control effort’ for the reference set and modified sets of parameter values, and with constraints on tibiofemoral compression force. Findings The sit-to-stand task could be performed successfully and realistically by the reference model, by a model with isometric knee extensor forces reduced to 40% of reference, by a model with isometric forces of all muscles reduced to 45% of reference, and by the reference model with the tibiofemoral compression force constrained during optimization to 65% of the peak value in the reference condition. Interpretation The strategies found by the model in conditions other than reference could be interpreted well on the basis of cost function and task biomechanics. The question remains whether it is feasible to teach patients with musculoskeletal impairments or joint pain to perform the sit-to-stand task according to strategies that are optimal according to the simulation model.