A prognostic approach based on a MISO (multiple inputs and single output) fuzzy logic model was introduced to estimate the pressure difference across a gas turbine (GT) filter house in a heavy-duty power generation system. For modelling and simulation of clogging of the GT filter house, nine real-time process variables (ambient temperature, humidity, ambient pressure, GT produced load, inlet guide vane position, airflow rate, wind speed, wind direction and PM10 dust concentration) were fuzzified using a graphical user interface within the framework of an artificial intelligence-based methodology. The results revealed that the proposed fuzzy logic model produced very small deviations and showed a superior predictive performance than the conventional multiple regression methodology, with a very high determination coefficient of 0.974. A complicated dynamic process, such as clogging phenomenonin heavy-duty GT system, was successfully modelled due to high capability of the fuzzy logic-based prognostic approach in capturing the nonlinear interactions.

Directional fluid transport is critical for water, energy, and biomedical applications, including passive fog harvesting. The unique shape gradient of conical structures can induce capillary pressure and drive the self-propulsion of droplets as the droplets settle on wettable sharp cones and move toward the cone base as they grow. In this work, we achieve passive droplet transport by fabricating conical spikes with sawtooth and imbricated (reversed-sawtooth) surface structures via high-resolution 3D printing. Fog harvesting experiments on various spikes indicate that the sawtooth structure exhibits the most efficient droplet mobilization toward the spike base, while the imbricated surface structure promotes isolated droplet formation with delayed transport and the smooth spikes would keep droplets stationary unless coalescences occur. Further droplet motion analysis reveals that the flat surface with imbricated structure exerts 3.5 times more hysteresis force than the sawtooth one under dry conditions and nearly twice under wet conditions. During fog harvesting, microdroplets in fog fill the teeth gaps along the water-wet sawtooth spike, and the resulting big barrel droplet exhibits a series of stop-and-go motions when it continues growing. Our quantitative analysis reveals that the interplay between the capillary and hysteresis forces is responsible for the droplet self-propulsion. Our experiments with the conical sawtooth spike array further demonstrate that the fog water harvesting rate with 10 μm teeth spacing is twice that with 20 μm spacing and triple that with 40 μm spacing.

Mini-channel heatsinks have proven useful in removing high heat fluxes from microelectronic devices. However, further miniaturization of electronic devices requires significant enhancement in the mini-channel heatsinks’ thermohydraulic characteristics, which depend greatly on the coolant and geometrical configuration of the channel. Therefore, the current study explores the potential of mini-channel heatsinks’ using different coolants (water, nanofluid and supercritical carbon dioxide) and various channel configurations. The effect of various channel configurations on the thermohydraulic characteristics of the mini-channel heat sinks is evaluated numerically for different coolants employing three flow rates (17 g/s, 34 g/s and 50 g/s). Hence, the effects of fin height, spacing and thickness, and mass flow rate on the overall heat transfer coefficient (CHT) and pressure drop (ΔP) are reported for the abovementioned coolants. It is found that increasing the mass flow rate increases both the CHT and ΔP. It is also noted that increasing the fin height and spacing decreases both the CHT and ΔP, as opposed to increasing the thickness, which causes both the CHT and ΔP to increase. Among the three coolants used, the sCO₂ shows superior performance compared to the water and nanofluid and this based on higher CHT and lower ΔP. Moreover, the performance evaluation criterion (PEC) for the sCO₂ is higher than that for the water and nanofluid by 53% at 17 g/s flow rate and 243% at 50 g/s flow rate.