W_xNbMoTa refractory high-entropy alloys with four different tungsten concentrations (x = 0, 0.16, 0.33, 0.53) were fabricated by laser cladding deposition. The crystal structures of W_xNbMoTa alloys are all a single-phase solid solution of the body-centered cubic (BCC) structure. The size of the grains and dendrites are 20 μm and 4 μm on average, due to the rapid solidification characteristics of the laser cladding deposition. These are much smaller sizes than refractory high-entropy alloys fabricated by vacuum arc melting. In terms of integrated mechanical properties, the increase of the tungsten concentration of W_xNbMoTa has led to four results of the Vickers microhardness, i.e., H_v = 459.2 ± 9.7, 476.0 ± 12.9, 485.3 ± 8.7, and 497.6 ± 5.6. As a result, NbMoTa alloy shows a yield strength (σ_b) and compressive strain (ε_p) of 530 Mpa and 8.5% at 1000 °C, leading to better results than traditional refractory alloys such as T-111, C103, and Nb-1Zr, which are commonly used in the aerospace industry.

Ni-based superalloy turbine blades have become indispensable structural parts in modern gas engines. An understanding of the solidification behavior and microstructure formation in directional solidified turbine blades is necessary for improving their high-temperature performance. The multiscale simulation model was developed to simulate the directional solidification process of superalloy turbine blades. The 3D cellular automaton-finite difference (CA-FD) method was used to calculate heat transfer and grain growth on the macroscopic scale, while the phase-field method was developed to simulate dendrite growth on the microscopic scale. Firstly, the evolution of temperature field of an aero-engine blade and a large industrial gas turbine blade was studied under high-rate solidification (HRS) and liquid-metal cooling (LMC) solidification processes. The varying withdrawal velocity was applied to change the curved mushy zone to a flat shape. Secondly, the grain growth in the aero-engine blade was simulated, and the grain structures in the starter block part and the spiral selector part in the HRS process were compared with those in the LMC process. The simulated grain structures were generally in agreement with experimental results. Finally, the dendrite growth in the typical HRS and LMC solidification process was investigated and the simulation results were compared with the experimental results in terms of dendrite morphology and primary dendritic spacing.

The rapid development of numerical modeling techniques has led to more accurate results in modeling metal solidification processes. In this study, the cellular automaton-finite difference (CA-FD) method was used to simulate the directional solidification (DS) process of single crystal (SX) superalloy blade samples. Experiments were carried out to validate the simulation results. Meanwhile, an intelligent model based on fuzzy control theory was built to optimize the complicate DS process. Several key parameters, such as mushy zone width and temperature difference at the cast-mold interface, were recognized as the input variables. The input variables were functioned with the multivariable fuzzy rule to get the output adjustment of withdrawal rate (v) (a key technological parameter). The multivariable fuzzy rule was built, based on the structure feature of casting, such as the relationship between section area, and the delay time of the temperature change response by changing v, and the professional experience of the operator as well. Then, the fuzzy controlling model coupled with CA-FD method could be used to optimize v in real-time during the manufacturing process. The optimized process was proven to be more flexible and adaptive for a steady and stray-grain free DS process.

Grain selection is an important process in single crystal turbine blades manufacturing. Selector structure is a control factor of grain selection, as well as directional solidification (DS). In this study, the grain selection and structure design of the spiral selector were investigated through experimentation and simulation. A heat transfer model and a 3D microstructure growth model were established based on the Cellular automaton-Finite difference (CA-FD) method for the grain selector. Consequently, the temperature field, the microstructure and the grain orientation distribution were simulated and further verified. The average error of the temperature result was less than 1.5%. The grain selection mechanisms were further analyzed and validated through simulations. The structural design specifications of the selector were suggested based on the two grain selection effects. The structural parameters of the spiral selector, namely, the spiral tunnel diameter (d_w), the spiral pitch (h_b) and the spiral diameter (h_s), were studied and the design criteria of these parameters were proposed. The experimental and simulation results demonstrated that the improved selector could accurately and efficiently produce a single crystal structure.

In current research, many researchers propose analytical expressions for calculating the packing structure of spherical particles such as DN Model, Compact Model and NLS criterion et al. However, there is still a question that has not been well explained yet. That is: What is the core factors affecting the thermal conductivity of particles? In this paper, based on the coupled discrete element-finite difference (DE-FD) method and spherical aluminum powder, the relationship between the parameters and the thermal conductivity of the powder ( ETC _p ) is studied. It is found that the key factor that can described the change trend of ETC _p more accurately is not the materials of the powder but the average contact area between particles ( a _ave ) which also have a close nonlinear relationship with the average particle size d ₅₀ . Based on this results, the expression for calculating the ETC _p of the sphere metal powder is successfully reduced to only one main parameter d ₅₀ and an efficient calculation model is proposed which can applicate both in room and high temperature and the corresponding error is less than 20.9% in room temperature. Therefore, in this study, based on the core factors analyzation, a fast calculation model of ETC _p is proposed, which has a certain guiding significance in the field of thermal field simulation.

The particle accumulation structure is commonly found in diverse engineering fields, including additive manufacturing powder, powder metallurgy, advanced reactor, grain storage and catalyst bed. The relative thermal conductivity of such structure is an important parameter to study the heat transfer behavior of the accumulation. In the study, the key factors affecting on the thermal conductivity of the powder is analyzed. Based on the results, the expression for calculating the thermal conductivity of the sphere metal powder is successfully reduced to only one parameter d₅₀ and an efficient calculation model is proposed which can applicate both in room and high temperature. Meanwhile, the corresponding error is less than 20.9% in room temperature and 50% in high temperature.