Applying CFD in the Analysis of Heavy Oil/Water Separation Process via Hydrocyclone

The choice of favorable regions for wind turbine installations is an important process and should be worked methodically. Among the models of the movement of air masses forecast, we can highlight those who work with computational fluid mechanics, where the Navier-Stokes and conservative are resolved and able to fulfill this request. Turbulence is the most difficult phenomenon to comprehend in studying the atmospheric boundary layer (ABL).It can be described as fluctuations in the flow field in space and time. The process of formation and development of turbulence is complex, since it is three dimensional, transient and has multiple scales. Moreover, it can cause significant effects on flow characteristics. When the fluid inertia forces become significant, if compared with the viscous forces, turbulence occurs and it comes in a high Reynolds number. In this paper, turbulence models based on RANS of the software Ansys CFX 11 were tested on hybrid unstructured meshes, and the results compared with experimental data on the size of the recirculation of air and velocity profiles in an elevation in the 2D triangular shape obtained by Arya and Shipman (1981) and Lee and Park (1997). Three more efficient models were tested in the fields of computing of real and complex terrain, showing good agreement with experimental data. A escolha de regiões favoráveis para instalações de turbinas eólicas é um processo importante e deve ser trabalhado metodicamente. Entre os modelos de previsão do movimento de massas de ar, pode-se destacar os que trabalham com a mecânica dos fluidos computacional, onde as equações de Navier-Stokes e conservativas são resolvidas e capazes de atender tal solicitação. No entanto a turbulência é o fenômeno difícil de compreensão no estudo da camada limite atmosférica, para aplicação de potencial eólico de uma região. Ela pode ser descrita como sendo flutuações no campo de escoamento no espaço e no tempo. O processo de formação e desenvolvimento de uma turbulência é complexo, uma vez que ela é tridimensional, transiente e possui várias escalas. Além disso, ela pode causar efeitos significativos nas características do escoamento. Quando as forças de inércia do fluido tornam-se significantes, se comparadas com as forças viscosas, ocorre à turbulência e ela apresenta-se em um elevado número de Reynolds. Neste trabalho, os modelos de turbulência baseados em RANS e de Tensões de Reynolds do software Ansys CFX 14 foram testados em malhas hibridas não estruturadas e seus resultados comparados com dados experimentais do tamanho da recirculação do ar e perfis de velocidade em uma elevação 2D na forma triangular obtidos por Arya and Shipman (1981) e Lee and Park (1997). Três modelos mais eficientes foram testados em domínios computacionais de terrenos complexos e reais, mostrando boa concordância com dados experimentais.

Anais do Congresso Internacional de Engenharia Mecânica e Industrial (2764-4294) - Differential Parametric Sensitivity Analysis Of The Cell Temperature In Photovoltaic Modules

Anais do Congresso Internacional de Engenharia Mecânica e Industrial (2764-4294) - Estudo Numérico Do Escoamento Bifásico Óleo-Água, Aplicado Em Duto Horizontal Utilizando A Técnica “Core Annular Flow”

Combined-cycle gas turbine (CCGT) power plants play an important role in reducing greenhouse gas emissions while maintaining high thermal efficiency. Accurate thermodynamic models are essential for evaluating plant performance under different operating conditions and supporting improvements in energy resource management. This study presents a Python-based thermodynamic model of an isolated natural gas-fired CCGT power plant, applied to 1027 steady-state operating points recorded over one month of operation. The model integrates energy, exergy, and exergoeconomic analyses based on the Specific Exergy Costing (SPECO) methodology to assess plant operation with and without supplementary firing. The model was validated against the measured steam production, with a mean absolute percentage error of 2.8%. The proposed methodology enables the evaluation of component efficiencies, exergy destruction, cost formation, and the influence of different operating modes on electricity production. The plant achieved median gross first- and second-law efficiencies of 46.6% and 44.6%, respectively (45.1% and 43.2% on a net basis). The combustion chamber exhibited the highest exergy destruction in both operating modes, while the supplementary burner became one of the major sources of irreversibility when supplementary firing was activated. The specific exergy cost of electricity decreased from about 21.0 to 14.2 $/GJ as the electrical output increased from 11.3 to 20.9 MW, with a median of 16.47 $/GJ in the period. The supplementary burner presented the highest relative cost difference (median of 1.06), whereas the combustion chamber had the highest exergy destruction rate and cost rate of exergy destruction. The proposed model provides a flexible and reproducible framework for evaluating CCGT power plants and can support operational assessment and decision-making aimed at improving thermodynamic and economic performance.

The photovoltaic (PV) solar energy sector has expanded rapidly in response to the urgent need to diversify the global electrical matrix. The efficiency of silicon-based PV modules depends on several factors, with cell operating temperature being one of the most critical. High temperatures reduce open-circuit voltage and energy yield, making accurate thermal-electrical modeling essential. The main objective of this work is to develop a robust thermoelectrical model, and based on its results, perform a detailed parametric sensitivity analysis to understand how the input variables influence the output variables of interest, namely, the cell temperature and efficiency. The model integrates thermal and electrical phenomena in a multi-physics approach. The thermal component is one-dimensional and transient, accounting for heat conduction across module layers, internal generation in cells and glass, and radiative and convective exchanges at both surfaces. The electrical component uses the single-diode model to reproduce current-voltage (I-V) characteristics. A transient differential sensitivity analysis identifies the parameters most affecting cell temperature. Sensitivity coefficients are evaluated over a simulated day to capture dynamic effects. Results show that ambient air temperature, solar irradiation on the tilted plane and open-circuit voltage exert the greatest influence, requiring precise determination to improve model reliability. Conversely, parameters with low sensitivity, such as glass thermal conductivity, are less critical, enabling simplifications without sacrificing accuracy. This systematic approach enhances the predictive capability of PV performance modeling, supporting both accurate system simulations and informed design decisions.