Temperature Dependency Model in Pressure Measurement for the Motion-Capturing Pressure-Sensitive Paint Method.

Pressure-sensitive paint (PSP) has received significant attention for capturing surface pressure in recent years. One major source of uncertainty in PSP measurements, temperature dependency, stems from the fundamental photophysical process that allows PSP to extract pressure information. The motion-capturing PSP method, which involves two luminophores, is introduced as a method to reduce the measurement uncertainty due to temperature dependency.

Predicting Pressure Sensitivity to Luminophore Content and Paint Thickness of Pressure-Sensitive Paint Using Artificial Neural Network.

An artificial neural network (ANN) was constructed and trained for predicting pressure sensitivity using an experimental dataset consisting of luminophore content and paint thickness as chemical and physical inputs. A data augmentation technique was used to increase the number of data points based on the limited experimental observations. The prediction accuracy of the trained ANN was evaluated by using a metric, mean absolute percentage error.

Novel Superhydrophobic Surface with Solar-Absorptive Material for Improved De-Icing Performance.

Ice accretion is detrimental to numerous industries, including infrastructure, power generation, and aviation applications. Currently, some of the leading de-icing technologies utilize a heating source coupled with a superhydrophobic surface. This superhydrophobic surface reduces the power consumption by the heating element.