The power demand from gas turbines in electrical grids is becoming more dynamic due to the rising demand for power generation from renewable energy sources. Therefore, including the transient data in the fault diagnostic process is important when the steady-state data are limited and if some component faults are more observable in the transient condition than in the steady-state condition. This study analyses the transient behaviour of a three-shaft industrial gas turbine engine in clean and degraded conditions with consideration of the secondary air system and variable inlet guide vane effects. Different gas path faults are simulated to demonstrate how magnified the transient measurement deviations are compared with the steady-state measurement deviations. The results show that some of the key measurement deviations are considerably higher in the transient mode than in the steady state. This confirms the importance of considering transient measurements for early fault detection and more accurate diagnostic solutions.
This research aims to investigate the effects of seawater parameters like salinity, pH, and temperature on the external corrosion behaviour and microhardness of offshore oil and gas carbon steel pipes. The immersion tests were performed for 28 days following ASTM G-1 standards, simulating controlled artificial marine environments with varying pH levels, salinities, and temperatures. Besides, Field emission scanning electron microscopy (FESEM) analysis is performed to study the corrosion morphology. Additionally, a Vickers microhardness tester was used for microhardness analysis. The results revealed that an increase in salinity from 33.18 to 61.10 ppt can reduce the corrosion rate by 28%. In contrast, variations in seawater pH have a significant effect on corrosion rate, with a pH decrease from 8.50 to 7 causing a 42.54% increase in corrosion rate. However, the temperature of seawater was found to be the most prominent parameter, resulting in a 76.13% increase in corrosion rate and a 10.99% reduction in the microhardness of offshore pipelines. Moreover, the response surface methodology (RSM) modelling is used to determine the optimal seawater parameters for carbon steel pipes. Furthermore, the desirability factor for these parameters was 0.999, and the experimental validation displays a good agreement with predicted model values, with around 4.65% error for corrosion rate and 1.36% error for microhardness.
The increasing demand for cement has substantially affected the environment, and its manufacturing requires substantial energy usage. However, most countries in the world recently encountered a significant energy problem. So, researchers are exploring the use of agricultural and industrial waste resources with cementitious characteristics to minimize cement manufacturing, cut energy consumption, and contribute to environmental protection. Therefore, this research is performed on roller compacted concrete (RCC) reinforced with 5%, 10%, 15%, and 20% of corn cob ash (CCA) as substitution material with different percentage of cement and 0.25%, 0.50%, 0.75%, and 1% of jute fibre (JF) together for determining the mechanical properties and embodied carbon (EC) by applying response surface methodology (RSM) modelling. The cubical samples were prepared to achieve the targeted strength about 30 MPa at 28 days and then obtained mix proportions were employed for all combinations at various water-cement ratios to maintain roller-compacted concrete's zero slump. Results showed that at 0.50% JF and 10% CCA, the flexural strength, splitting tensile strength and compressive strengths, and modulus of elasticity of RCC obtained were 5.3 MPa, 3.8 MPa, 32.88 MPa, and 33.11 GPa at 28 days, respectively. Besides, the embodied carbon of RCC is recoded reducing with combined addition of different levels of JF and CCA as compared to control mixture. In addition, the generation of response prediction algorithms was performed using analysis of variance (ANOVA) at a threshold of significance of 95%. The coefficient of determination (R2) readings for the statistical models ranged from 96 to 99%. It is observed that the use of 0.50% of JF along with 10% of CCA as cementitious constituent in RCC provides best outcomes. Therefore, this method is a superior choice for the construction industry.