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Gas turbine engines are complex mechanical marvels widely employed in diverse applications such as marine vessels, aircraft, power generation, and pumping facilities. However, their intricate nature renders them susceptible to numerous operational faults, significantly compromising their performance and leading to excessive emissions, consequently incurring stringent penalties from environmental regulatory bodies. Moreover, the deterioration of gas turbine performance is exacerbated by variations in working conditions based on operational settings and environmental conditions. Past studies have focused on certain working conditions that limit effectiveness in real-world applications where operational settings and environmental conditions vary during operations. The influence of these working conditions on the performance of gas turbines also needs to be assessed, as they can lead to different fault patterns resulting in unplanned maintenance, unnecessary maintenance costs, unsafe conditions and stringent penalties. This study uses the Gas Turbine Simulation Program (GSP) to simulate a high-bypass turbofan engine, analyzing the combined effects of operational settings and environmental conditions on engine performance while also incorporating simulations of common gas turbine faults like fouling and erosion in various locations and severities along the gas path. The model's accuracy is confirmed by low Mean Absolute Percentage Errors (MAPE) of 0.004% of thrust at the cycle reference point and 0.15% and 0.28% at 2 km and 7 km altitudes, respectively, demonstrating the model's robustness across varying operational scenarios. In conclusion, this research highlights the significant effects of operational settings and environmental factors on gas turbine performance, particularly impacting specific fuel consumption and thrust. Our findings indicate substantial impacts of operational settings and environmental factors on fuel consumption and thrust. Specifically, compressor fouling and low-pressure turbine erosion increase Nitrogen Oxide (NOx) emissions by 4.5% and 11.1%, while fouling of nozzle guide vanes and high-pressure turbine erosion raise unburnt hydrocarbon (UHC) by 10.0% and 20.2%, and carbon monoxide (CO) by 3.2% and 5.2%, respectively, compared to a healthy engine. These insights highlight the importance of component-specific degradation in influencing gas turbine performance and emissions.
Gas turbine engines are complex mechanical marvels widely employed in diverse applications such as marine vessels, aircraft, power generation, and pumping facilities. However, their intricate nature renders them susceptible to numerous operational faults, significantly compromising their performance and leading to excessive emissions, consequently incurring stringent penalties from environmental regulatory bodies. Moreover, the deterioration of gas turbine performance is exacerbated by variations in working conditions based on operational settings and environmental conditions. Past studies have focused on certain working conditions that limit effectiveness in real-world applications where operational settings and environmental conditions vary during operations. The influence of these working conditions on the performance of gas turbines also needs to be assessed, as they can lead to different fault patterns resulting in unplanned maintenance, unnecessary maintenance costs, unsafe conditions and stringent penalties. This study uses the Gas Turbine Simulation Program (GSP) to simulate a high-bypass turbofan engine, analyzing the combined effects of operational settings and environmental conditions on engine performance while also incorporating simulations of common gas turbine faults like fouling and erosion in various locations and severities along the gas path. The model's accuracy is confirmed by low Mean Absolute Percentage Errors (MAPE) of 0.004% of thrust at the cycle reference point and 0.15% and 0.28% at 2 km and 7 km altitudes, respectively, demonstrating the model's robustness across varying operational scenarios. In conclusion, this research highlights the significant effects of operational settings and environmental factors on gas turbine performance, particularly impacting specific fuel consumption and thrust. Our findings indicate substantial impacts of operational settings and environmental factors on fuel consumption and thrust. Specifically, compressor fouling and low-pressure turbine erosion increase Nitrogen Oxide (NOx) emissions by 4.5% and 11.1%, while fouling of nozzle guide vanes and high-pressure turbine erosion raise unburnt hydrocarbon (UHC) by 10.0% and 20.2%, and carbon monoxide (CO) by 3.2% and 5.2%, respectively, compared to a healthy engine. These insights highlight the importance of component-specific degradation in influencing gas turbine performance and emissions.
This study examines modeling and simulation of the transient thermal behavior of a solar collector adsorber tube. The data used for model setup and validation were taken experimentally during the start-up procedure of a solar collector adsorber tube. ANN models are developed based on the nonlinear autoregressive with exogenous input NARX model and are implemented using the MATLAB® tools including the Neural Network Toolbox TM . It is considered that the data used for model training and validation are experimental data taken during solar collector operation using standard instrumentation. The neural network predictions agreed well with experimental values with mean squared error which are near 0 and the best fit between outputs and targets (R) are very close to 1. These results showed that NARX models (1-12-1 with d1 = 10, d2 = 9 and 35 epochs) can successfully be used to predict thermal performance of the adsorber tube. General TermsNeural networks, training algorithm.
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