An acoustic transmitter can be located by having multiple static microphones. These microphones are synchronized and measure the time differences of arrival (TDoA). Usually, the positions of the microphones are assumed to be known in advance. However, in practice, this means they have to be manually measured, which is a cumbersome job and is prone to errors. In this paper, we present two novel approaches which do not require manual measurement of the receiver positions. The first method uses an inertial measurement unit (IMU), in addition to the acoustic transmitter, to estimate the positions of the receivers. By using an IMU as an additional source of information, the non-convex optimizers are less likely to fall into local minima. Consequently, the success rate is increased and measurements with large errors have less influence on the final estimation. The second method we present in this paper consists of using machine learning to learn the TDoA signatures of certain regions of the localization area. By doing this, the target can be located without knowing where the microphones are and whether the received signals are in line-of-sight or not. We use an artificial neural network and random forest classification for this purpose.

The low cycle fatigue (LCF) behavior and fatigue crack growth rates (da/dN) of alloy IN718 were studied in detail at 360,550 and 650 "C, including the cycle stress-strain behavior, Massing effect, the LCF lives expressed by plastic strain energy and fatigue crack growth rates. In addition, the effect of hold time on da/dN was also discussed. The experimental results show that the da/dN is increased with the temperature increased. The effect of hold time on da/dN is very significant at 650°C, while it is a little below 550%.

Tea pollen is rich in nutritional and bioactive compounds; however, the pollen wall limits their release. In this study, we explored the effects of freeze–thaw processing (FT), a combination of enzymatic hydrolysis and ultrasonication (EHUS) and superfine grinding (SG) on the wall disruption, antioxidant activity, sensory qualities and nutrients in tea pollen. SG‐treated pollen had the highest broken‐wall ratio (100%), followed by EHUS (79.14%), while FT‐treated pollen displayed the lowest ratio (59.86%). Release of nutrient compounds, including polyphenols, flavonoids, carbohydrates, total free amino acids, proteins and theanine, increased after treatment with the three wall‐disruption methods compared with untreated samples. Moreover, levels of epigallocatechin gallate (EGCG), epigallocatechin (EGC), catechin gallate (CG) and gallocatechin gallate (GCG) were higher following EHUS or SG than in untreated or FT‐treated tea pollen. EGCG was the most potent catechin involved in antioxidant activity of tea pollen, making major contributions to the significant improvement of antioxidant activity in SG‐ and EHUS‐treated groups. Additionally, the overall sensory qualities of tea were lower after treatment with the three wall‐disruption methods compared with untreated samples. In summary, SG and EHUS treatment had greater effects on cell wall disruption, nutrient release and antioxidant activity in tea pollen.

The fatigue crack growth rates of alloy 718 ~were studied in detail at 550 and 650°C to offer the data for design selected and life estimated of turbine disk. In addition, to simulate the takeoff-cruisedescent operation condition of air engine, and to study the effect of creep on fatigue crack growth rate at high temperature, the effect of hold time at peak load on fatigue crack growth rate has been studied also.

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