Hot Corrosion Resistant Laser Coatings in Diesel Engine

publishedVersionNon peer reviewe

Heat Transfer Through Plasma-Sprayed Thermal Barrier Coatings in Gas Turbines: A Review of Recent Work

A review is presented of how heat transfer takes place in plasma-sprayed (zirconia-based) thermal barrier coatings (TBCs) during operation of gas turbines. These characteristics of TBCs are naturally of central importance to their function. Current state-of-the-art TBCs have relatively high levels of porosity (~15%) and the pore architecture (i.e., its morphology, connectivity, and scale) has a strong influence on the heat flow. Contributions from convective, conductive, and radiative heat transfer are considered, under a range of operating conditions, and the characteristics are illustrated with experimental data and modeling predictions. In fact, convective heat flow within TBCs usually makes a negligible contribution to the overall heat transfer through the coating, although what might be described as convection can be important if there are gross through-thickness defects such as segmentation cracks. Radiative heat transfer, on the other hand, can be significant within TBCs, depending on temperature and radiation scattering lengths, which in turn are sensitive to the grain structure and the pore architecture. Under most conditions of current interest, conductive heat transfer is largely predominant. However, it is not only conduction through solid ceramic that is important. Depending on the pore architecture, conduction through gas in the pores can play a significant role, particularly at the high gas pressures typically acting in gas turbines (although rarely applied in laboratory measurements of conductivity). The durability of the pore structure under service conditions is also of importance, and this review covers some recent work on how the pore architecture, and hence the conductivity, is affected by sintering phenomena. Some information is presented concerning the areas in which research and development work needs to be focussed if improvements in coating performance are to be achieved

Evaluation of walking activity and gait to identify physical and mental fatigue in neurodegenerative and immune disorders: preliminary insights from the IDEA-FAST feasibility study

\ua9 The Author(s) 2024. Background: Many individuals with neurodegenerative (NDD) and immune-mediated inflammatory disorders (IMID) experience debilitating fatigue. Currently, assessments of fatigue rely on patient reported outcomes (PROs), which are subjective and prone to recall biases. Wearable devices, however, provide objective and reliable estimates of gait, an essential component of health, and may present objective evidence of fatigue. This study explored the relationships between gait characteristics derived from an inertial measurement unit (IMU) and patient-reported fatigue in the IDEA-FAST feasibility study. Methods: Participants with IMIDs and NDDs (Parkinson\u27s disease (PD), Huntington\u27s disease (HD), rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), primary Sjogren’s syndrome (PSS), and inflammatory bowel disease (IBD)) wore a lower-back IMU continuously for up to 10 days at home. Concurrently, participants completed PROs (physical fatigue (PF) and mental fatigue (MF)) up to four times a day. Macro (volume, variability, pattern, and acceleration vector magnitude) and micro (pace, rhythm, variability, asymmetry, and postural control) gait characteristics were extracted from the accelerometer data. The associations of these measures with the PROs were evaluated using a generalised linear mixed-effects model (GLMM) and binary classification with machine learning. Results: Data were recorded from 72 participants: PD = 13, HD = 9, RA = 12, SLE = 9, PSS = 14, IBD = 15. For the GLMM, the variability of the non-walking bouts length (in seconds) with PF returned the highest conditional R2, 0.165, and with MF the highest marginal R2, 0.0018. For the machine learning classifiers, the highest accuracy of the current analysis was returned by the micro gait characteristics with an intrasubject cross validation method and MF as 56.90% (precision = 43.9%, recall = 51.4%). Overall, the acceleration vector magnitude, bout length variation, postural control, and gait rhythm were the most interesting characteristics for future analysis. Conclusions: Counterintuitively, the outcomes indicate that there is a weak relationship between typical gait measures and abnormal fatigue. However, factors such as the COVID-19 pandemic may have impacted gait behaviours. Therefore, further investigations with a larger cohort are required to fully understand the relationship between gait and abnormal fatigue