Machine learning-based data analysis approaches have been employed to overcome the limitations in accurately analyzing data and to predict the results of the design of Nb-based superalloys. In this study, a database containing the composition of the alloying elements and their room-temperature tensile strengths was prepared based on a previous study. After computing the correlation between the tensile strength at room temperature and the composition, a material science analysis was conducted on the elements with high correlation coefficients. These alloying elements were found to have a significant effect on the variation in the tensile strength of Nb-based alloys at room temperature. Through this process, a model was derived to predict the properties using four machine learning algorithms. The Bayesian ridge regression algorithm proved to be the optimal model when Y, Sc, W, Cr, Mo, Sn, and Ti were used as input features. This study demonstrates the successful application of machine learning techniques to effectively analyze data and predict outcomes, thereby providing valuable insights into the design of Nb-based superalloys.

In this study, we investigated the effects of precipitates and oxide dispersoids on the high-temperature mechanical properties of oxide dispersion-strengthened (ODS) Ni-based super alloys. Two ODS Ni-based super alloy rods with different chemical compositions were fabricated by high-energy milling and hot extrusion process at 1150℃ to investigate the effects of precipitates on high-temperature mechanical properties. Further, the MA6000N alloy is an improvement over the commercial MA6000 alloy, and the KS6000 alloy has the same chemical composition as the MA6000 alloy. The phase and microstructure of Ni-based super alloys were investigated by X-ray diffraction and scanning electron microscopy. It was found that MC carbide precipitates and oxide dispersoids in the ODS Ni-based super alloys developed in this study may effectively improve high-temperature hardness and creep resistance.

Appropriate thermo-mechanical properties of nickel-based superalloys are achieved by heat treatment, which induces precipitation and solid solution hardening; thus, information on the temperature ranges of precipitation and dissolution of the precipitates is essential for the determination of the heat treatment condition. In this study, thermal analyses of nickelbased superalloys were performed by differential scanning calorimetry method under conditions of various heating rates of 5, 10, 20, or 40K/min in a temperature range of 298~1573K. Precipitation and dissolution temperatures were determined by measuring peak temperatures, constructing trend lines, and extrapolating those lines to the zero heating rate to find the exact temperature under isothermal condition. Determined temperatures for the precipitation reactions were 813, 952, and 1062K. Determined onset, peak, and offset temperatures of the first dissolution reaction were 1302, 1388, and 1406K, respectively, and those values of the second dissolution reaction were 1405, 1414, and 1462K. Determined solvus temperature was 1462K. The study showed that it was possible to use a simple method to obtain accurate phase transition temperatures under isothermal condition.

A strain-gradient crystal plasticity constitutive model was developed in order to predict the Hall Petch behavior of a Ni-base polycrystalline superalloy. The constitutive model involves statistically stored dislocation and geometrically necessary dislocation densities, which were incorporated into the Bailey-Hirsch type flow stress equation with six strength interaction coefficients. A strain-gradient term (called slip-system lattice incompatibility) developed by Acharya was used to calculate the geometrically necessary dislocation density. The description of Kocks-Argon-Ashby type thermally activated strain rate was also used to represent the shear rate of an individual slip system. The constitutive model was implemented in a user material subroutine for crystal plasticity finite element method simulations. The grain size dependence of the flow stress (viz., the Hall- Petch behavior) was predicted for a Ni-base polycrystalline superalloy NIMONIC PE16. Simulation results showed that the present constitutive model fairly reasonably predicts 0.2%-offset yield stresses in a limited range of the grain size.

Incoloy 800H, KSA (Kaeri Superalloy)-6, Inconel 600 및 Hastelloy C-276 합금의 용융염에서의 부식거동을 650~850˚C 온도범위에서 조사하였다. LiCl-Li2O혼합용융염에서의 부식은 Li2O에 의한 염기성 용해 기구에 의해 진행되며, 부식속도가 LiCl에서보다 훨씬 빠르게 나타났다. 혼합용융염 LiCl-Li2O에서는 Ni기 합금의 부식속도가 Fe기 합금보다 빠르고, Mo와 W의 함량이 높은 Hastelloy C-276이 가장 빠른 부식속도를 나타내었다. 용융염 LiCl에서는 LiCrO2의 단일 부식층이 형성되고, LiCl-Li2O 혼합용융염에서는 산화물과 Ni의 2상구조의 다공성 부식층이 형성되었다.

초합금의 진공정밀주조시에 진공하에서 용해한 합금을 1000~1700˚C로 가열한 세라믹 주형에 주입하고 난 후, 용탕이 장시간 주형안에 노출됨으로써, 주형의 고온강도가 높아야 하므로 고품위의 주형재를 사용하여 왔으나, 저품위의 값싼 소재를 사용하여 고품위의 주형과 동등한 효과를 갖게 하고자 주형내의 Silica 함량을 조절하였다. 그 결과 SiO2 첨가량이 7.7wt.%일 때, 다른 시험편에 비해 소성강도와 고온강도가 10-55%가량 증가 하였다. 따라서 일반적으로 정밀주조 주형으로 사용하는 용융알루미나와 colloidal silica의 혼합비를 제어하여 단결절 주조용 주형을 개발하였다.

Ni기 초합금은 Co, Cr, Mo, W등의 고용 강화 원소와 AI, Ti, Nb, Ta 등의 γ ' 석출 강화 원소로 구성되어 있다. 초합금의 기계적 성질과 내산화성을 개선하기 위하여 희토류 원소를 재료 내부에 첨가하거나, 코팅 재료로써 사용하고 있다. 이들 희토류 원소는 Al2O3, Cr2O3등의 산화물의 종류에 따라 산화물의 성장 속도와 밀착성에 영향을 미친다. Hf함유 Ni기 초합금 AF115와 AI2O3 함유 MA6000초합금 2종을 이온 코터를 이용, Yttrium 표면개질후, 온도 1273K-1473K에서 고온 산화 수 산호 피막의 성장 속도, 결정립, 내부 구조 및 내박리성에 미치는 Yttrium 의 영향을 조사하였다. AF115와 MA6000 초합금에 Yttrium코팅을 한 결과 내부 산화물의 성장에 현저한 변화가 있었다. Yttrium의 표면 개질에 의하여, AF115의 경우는 AI2O3 주성분의 입계 집중과 Hf의 우선 산확 억제되고, 삼각 형태의 내부 산화물이 plate형으로 변화되었다. MA6000의 경우 AI2O3 주성분의 산화층이Cr2O3주성분의 외부 산화층과AI2O3 주성분의 내부층으로 변화되었다.