In this study, we investigated the performance and reliability of commercial corrosion sensors for monitoring the integrity of piping systems in various fluid environments as an alternative to ultrasonic transducers. To this end, we investigated pipes’ wall-thinning using commercial electrical resistance (ER), linear polarization resistance (LPR), and ultrasonic transducer (UT) sensors under various operating environments. A pilot-scale closed-loop test bed was built to simulate a real pipeline flow situation, from which the sensor data were collected and analyzed. Experimental results indicate that, in the case of the LPR sensor, it is challenging to accurately measure the corrosion rate when a specific measure exceeds the threshold in a severe corrosion environment. In contrast, the ER sensor could measure metal loss under all conditions and reflect the corresponding characteristics. The metal loss (about 0.25 mm) of the real pipe after the experiment was confirmed to be equal to the metal loss (0.254 mm) measured by the sensor. Furthermore, the regression analysis revealed a high correlation between the results obtained from the ER and UT sensors. Thus, evaluating the remaining thickness of the piping system using the commercial ER sensor is deemed to be effective and reliable.

In this study, a model was proposed to predict the corrosion rate (Mils per Year, MPY) of carbon steel in a 3.5% NaCl solution, with the objective of comparing the effectiveness of a commercial LPR sensor against traditional electrochemical methods, using potentiostat-based LPR techniques. The primary factors considered in the experiments were temperature, flow velocity, and pH, tested through a full factorial design to identify the most influential variables. Statistical analysis showed that temperature and flow velocity had a significant effect on corrosion rate, with their interaction having the most substantial impact. In contrast, pH had no statistically significant influence within the tested conditions, likely due to the dominant effects of temperature and flow velocity in the high-salinity environment. The MPY data were validated through Tafel plots, immersion coupon tests, and other electrochemical techniques to confirm the reliability of the measurements. A regression model trained on 54 MPY data points demonstrated high accuracy, achieving a coefficient of determination (R²) of 0.9733. The model also provided reliable predictions for factor combinations excluded from the training dataset. Additionally, scenario-based evaluations highlighted the model’s performance under simulated operating conditions, while revealing challenges related to sensor contamination during long-term use. These findings emphasize the potential of commercial LPR sensors as effective tools for real-time corrosion monitoring and demonstrate the utility of the regression model in marine environments.

In this study, the optimization of the operational parameters for a single proton exchange membrane fuel cell (PEMFC) was carried out using the Taguchi method and orthogonal array. The operating parameters were H₂ stoichiometry, air stoichiometry, cell temperature, and back pressure of the anode∙cathode, each with three levels. The performance of the PEMFC, operated according to the L₉ orthogonal arrangement, was evaluated through I–V curves at a step-up current loading ranging from 0.1 to 0.7 A/cm². The results indicated that the anode∙cathode back pressure had the greatest sensitivity to the output voltage compared to the other operating parameters. Increasing the back pressure resulted in higher current output densities at higher values than those applied in the orthogonal arrangement. As the back pressure increased, the output voltage tended to increase at each current density. However, for operating conditions above 150 kPa, the improvement in cell performance was either not significant or tended to decrease. Therefore, it can be concluded that the Taguchi method and orthogonal array are effective tools for selecting the optimal operating conditions for PEMFC.