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In the current design work, turbine performance requirements are getting higher and higher, and turbine blade design needs multiple rounds of iterative optimization. Three-dimensional turbine optimization involves multiple parameters, and 3D simulation takes a long time. Machine learning methods can make full use of historically accumulated data to train high-precision data models, which can greatly reduce turbine blade performance evaluation time and improve optimization efficiency. Based on the data model, the advanced intelligent combinatorial optimization technology can effectively reduce the number of iterations, find the better model faster, and improve the optimization calculation efficiency. Based on the different cooling parts of turbine blades and machine learning, this research explores the potential of implementing different machine learning algorithms in the field of turbine cooling design. [ABSTRACT FROM AUTHOR]

Phosphoric acid-activated biochar has been proven to be a promising adsorbent for pollutant removal in an aqueous solution. It is urgent to understand how surface adsorption and intra-particle diffusion synergistically contribute to the adsorption kinetic process of dyes. In this work, we prepared a series of PPC adsorbents (PPCs) from red-pulp pomelo peel under different pyrolysis temperatures (150–350 °C), which have a broad specific surface area range from 3.065 m2/g to 1274.577 m2/g. The active sites on the surface of PPCs have shown specific change laws of decreasing hydroxyl groups and increasing phosphate ester groups occurring as the pyrolysis temperature rises. Both reaction models (PFO and PSO models) and diffusion models (intra-particle diffusion models) have been applied to simulate the adsorption experimental data to verify the hypothesis deduced from the Elovich model. PPC-300 exhibits the highest adsorption capacity of MB (423 mg/g) under given conditions. Due to its large quantities of active sites on the external and internal surfaces (1274.577 m2/g), a fast adsorption equilibrium can be achieved within 60 min (with an initial MB concentration of 100 ppm). PPC-300 and PPC-350 also exhibit an intra-particle-diffusion-controlled adsorption kinetic process with a low initial MB concentration (100 ppm) or at the very beginning and final stage of adsorption with a high initial MB concentration (300 ppm) at 40 °C, considering that the diffusion is likely hindered by adsorbate molecules through internal pore channels at the middle stage of adsorption in these cases. [ABSTRACT FROM AUTHOR]