In order to predict the process window of laser powder bed fusion (LPBF) for printing metallic components, the calculation of volumetric energy density (VED) has been widely calculated for controlling process parameters. However, because it is assumed that the process parameters contribute equally to heat input, the VED still has limitation for predicting the process window of LPBF-processed materials. In this study, an explainable machine learning (xML) approach was adopted to predict and understand the contribution of each process parameter to defect evolution in Ti alloys in the LPBF process. Various ML models were trained, and the Shapley additive explanation method was adopted to quantify the importance of each process parameter. This study can offer effective guidelines for fine-tuning process parameters to fabricate high-quality products using LPBF.

The emergence of ferrous-medium entropy alloys (FeMEAs) with excellent tensile properties represents a potential direction for designing alloys based on metastable engineering. In this study, an FeMEA is successfully fabricated using laser powder bed fusion (LPBF), a metal additive manufacturing technology. Tensile tests are conducted on the LPBF-processed FeMEA at room temperature and cryogenic temperatures (77 K). At 77 K, the LPBF-processed FeMEA exhibits high yield strength and excellent ultimate tensile strength through active deformation-induced martensitic transformation. Furthermore, due to the low stability of the face-centered cubic (FCC) phase of the LPBFprocessed FeMEA based on nano-scale solute heterogeneity, stress-induced martensitic transformation occurs, accompanied by the appearance of a yield point phenomenon during cryogenic tensile deformation. This study elucidates the origin of the yield point phenomenon and deformation behavior of the FeMEA at 77 K.

Although the Ti–6Al–4V alloy has been used in the aircraft industry owing to its excellent mechanical properties and low density, the low formability of the alloy hinders broadening its applications. Recently, laser-powder bed fusion (L-PBF) has become a novel process for overcoming the limitations of the alloy (i.e., low formability), owing to the high degree of design freedom for the geometry of products having outstanding performance used in hightech applications. In this study, to investigate the effect of bulk shape on the microstructure and mechanical properties of L-PBFed Ti-6Al-4V alloys, two types of samples are fabricated using L-PBF: thick and thin samples. The thick sample exhibits lower strength and higher ductility than the thin sample owing to the larger grain size and lower residual dislocation density of the thick sample because of the heat input during the L-PBF process.

Because magnets fabricated using Nd-Fe-B exhibit excellent magnetic properties, this novel material is used in various high-tech industries. However, because of the brittleness and low formability of Nd-Fe-B magnets, the design freedom of shapes for improving the performance is limited based on conventional tooling and postprocessing. Laserpowder bed fusion (L-PBF), the most famous additive manufacturing (AM) technique, has recently emerged as a novel process for producing geometrically complex shapes of Nd-Fe-B parts owing to its high precision and good spatial resolution. However, because of the repeated thermal shock applied to the materials during L-PBF, it is difficult to fabricate a dense Nd-Fe-B magnet. In this study, a high-density (>96%) Nd-Fe-B magnet is successfully fabricated by minimizing the thermal residual stress caused by substrate heating during L-PBF.

Several previous simulation studies using various geochemical models have been carried out in several major analogue sites. The cases are beneficial when these studies provided the possibility of testing the geochemical models to be used to describe the migration of radionuclides in a future radioactive waste repository system. It was possible to interpret the complex transport behaviour of radionuclides such as uranium and thorium in an environment. We organize major natural analogue study sites from the previous literatures that provided information on the general geochemistry of the sites, in terms of groundwater composition and mineralogy. Also, we calculated aqueous speciation and the solid phases most likely to control their solubilities. The results obtained from the previous studies and this study vary depending on the tools used and on the conceptual models followed. Also, the results differed from the actual measured concentrations of trace metals or radionuclide analogues. The results obtained from these tests identify the main mathematical limitations of available geochemical models. However, the modelling results using a geochemical code with the thermodynamic database simulated well the observed behaviour of radionuclides, especially to identify the dominant processes controlling actinide mobilization and fixation. It was a useful outcome in terms of building confidence on the current geochemical tools to predict the concentrations of radionuclide analogues once the major geochemical characteristics were known. This study allows improving specific aspects of geochemical modelling using major natural analogue sites.

Metal three-dimensional (3D) printing is an important emerging processing method in powder metallurgy. There are many successful applications of additive manufacturing. However, processing parameters such as laser power and scan speed must be manually optimized despite the development of artificial intelligence. Automatic calibration using information in an additive manufacturing database is desirable. In this study, 15 commercial pure titanium samples are processed under different conditions, and the 3D pore structures are characterized by X-ray tomography. These samples are easily classified into three categories, unmelted, well melted, or overmelted, depending on the laser energy density. Using more than 10,000 projected images for each category, convolutional neural networks are applied, and almost perfect classification of these samples is obtained. This result demonstrates that machine learning methods based on X-ray tomography can be helpful to automatically identify more suitable processing parameters.

본 연구의 목적은 전후진 자동변속기가 장착된 트랙터의 변속 충격을 모사하기 위한 시뮬레이션 모델에 적용될 비례 제어 밸브의 전류 제어 모델을 개발하는 것이다. 전류 제어 모델을 개발하기 위하여 시험 장치를 구성하여 밸브의 정특성 시험과 계단 응답 시험을 수행하였으며, 시험 결과를 토대로 전류 제어 모델을 검증하였다. 비례 제어 밸브의 전류 제어 모델은 밸브의 전류-압력 선도, PID 제어기, 펄스폭변조 신호 발생기와 밸브 모델로 구성하였다. 전류 제어 모델에 사용된 데이터는 시험을 통하여 도출된 값과 대상 트랙터에 적용된 값을 사용하였다. 전류 제어 모델 검증을 위해 계단 입력 신호에 대하여 전류 특성 시험을 수행하였고, 실제 전류 시험 결과와 시뮬레이션 결과를 비교하였다. 시험 결과와 시뮬레이션 결과에 대한 전류 특성을 비교해 보면, 상승 시간 오차는 0.0074초, 첨두치 시간의 오차는 0.0065초, 오버슈트 오차는 0.06%로 나타났다. 따라서 개발된 비례 제어 밸브의 전류 제어 모델은 실제 제어기의 전류 제어 특성을 제대로 반영할 수 있으며, 추후 변속 충격 모사를 위한 트랙터 시뮬레이션 모델에서 비례 제어 밸브의 전류 제어 모델로 사용될 수 있을 것으로 판단된다.

The convergence of artificial intelligence with smart factories or smart mechanical systems has been actively studied to maximize the efficiency and safety. Despite the high improvement of artificial neural networks, their application in the manufacturing industry has been difficult due to limitations in obtaining meaningful data from factories or mechanical systems. Accordingly, there have been active studies on manufacturing components with sensor integration allowing them to generate important data from themselves. Additive manufacturing enables the fabrication of a net shaped product with various materials including plastic, metal, or ceramic parts. With the principle of layer-bylayer adhesion of material, there has been active research to utilize this multi-step manufacturing process, such as changing the material at a certain step of adhesion or adding sensor components in the middle of the additive manufacturing process. Particularly for smart parts manufacturing, researchers have attempted to embed sensors or integrated circuit boards within a three-dimensional component during the additive manufacturing process. While most of the sensor embedding additive manufacturing was based on polymer material, there have also been studies on sensor integration within metal or ceramic materials. This study reviews the additive manufacturing technology for sensor integration into plastic, ceramic, and metal materials.

H13 tool steels are widely used as metallic mold materials due to their high hardness and thermal stability. Recently, many studies are undertaken to satisfy the demands for manufacturing the complex shape of the mold using a 3D printing technique. It is reported that the mechanical properties of 3D printed materials are lower than those of commercial forged alloys owing to micropores. In this study, we investigate the effect of microstructures and defects on mechanical properties in the 3D printed H13 tool steels. H13 tool steel is fabricated using a selective laser melting(SLM) process with a scan speed of 200 mm/ s and a layer thickness of 25 μm. Microstructures are observed and porosities are measured by optical and scanning electron microscopy in the X-, Y-, and Z-directions with various the build heights. Tiny keyhole type pores are observed with a porosity of 0.4%, which shows the lowest porosity in the center region. The measured Vickers hardness is around 550 HV and the yield and tensile strength are 1400 and 1700 MPa, respectively. The tensile properties are predicted using two empirical equations through the measured values of the Vickers hardness. The prediction of tensile strength has high accuracy with the experimental data of the 3D printed H13 tool steel. The effects of porosities and unmelted powders on mechanical properties are also elucidated by the metallic fractography analysis to understand tensile and fracture behavior.

In this study, two types of SKD61 tool-steel samples are built by a selective laser melting (SLM) process using the different laser scan speeds. The characteristics of two kinds of SKD61 tool-steel powders used in the SLM process are evaluated. Commercial SKD61 tool-steel power has a flowability of 16.68 sec/50 g and its Hausner ratio is calculated to be 1.25 by apparent and tapped density. Also, the fabricated SKD61 tool steel powder fabricated by a gas atomization process has a flowability of 21.3 sec/50 g and its Hausner ratio is calculated to be 1.18. Therefore, we confirmed that the two powders used in this study have excellent flowability. Samples are fabricated to measure mechanical properties. The highest densities of the SKD61 tool-steel samples, fabricated under the same conditions, are 7.734 g/cm³ (using commercial SKD61 powder) and 7.652 g/cm3 (using fabricated SKD61 powder), measured with Archimedes method. Hardness is measured by Rockwell hardness testing equipment 5 times and the highest hardnesses of the samples are 54.56 HRC (commercial powder) and 52.62 HRC (fabricated powder). Also, the measured tensile strengths are approximately 1,721 MPa (commercial SKD61 powder) and 1,552 MPa (fabricated SKD61 powder), respectively.

A cold-work tool steel powder is used to fabricate 3-dimensional objects by selective laser melting using a high-pressure gas atomization process. The spherical powder particles form continuous carbide networks among the austenite matrix and its decomposition products. The carbides comprise Nb-rich MC and Mo-rich M2C. In the SLM process, the process parameters such as the laser power (90 W), layer thickness (25 μm), and hatch spacing (80 μm) are kept fixed, while the scan speed is changed from 50 mm/s to 4000 mm/s. At a low scan speed of 50 mm/s, spherical cavities develop due to over melting, while they are substantially reduced on increasing the speed to 2000 mm/s. The carbide network spacing decreases with increasing speed. At an excessively high speed of 4000 mm/s, long and irregularly shaped cavities are developed due to incomplete melting. The influence of the scan pattern is examined, for which 1 × 1 mm2 blocks constituting a processing layer are irradiated in a random sequence. This island-type pattern exhibits the same effect as that of a low scan speed. Post processing of an object using hot isostatic pressing leads to a great reduction in the porosity but causes coarsening of the microstructure.

In this study, H13 tool steel sculptures are built by a metal 3D printing process at various laser scan speeds. The properties of commercial H13 tool steel powders are confirmed for the metal 3D printing process used: powder bed fusion (PBF), which is a selective laser melting (SLM) process. Commercial H13 powder has an excellent flowability of 16.68 s/50 g with a Hausner ratio of 1.25 and a density of 7.68 g/cm3. The sculptures are built with dimensions of 10 × 10 × 10 mm3 in size using commercial H13 tool steel powder. The density measured by the Archimedes method is 7.64 g/cm3, similar to the powder density of 7.68 g/cm3. The hardness is measured by Rockwell hardness equipment 5 times to obtain a mean value of 54.28 HRC. The optimum process conditions in order to build the sculptures are a laser power of 90 W, a layer thickness of 25 μm, an overlap of 30%, and a laser scan speed of 200 mm/s.

Selective laser melting (SLM) can produce a layer of a metal powder and then fabricate a three-dimensional structure by a layer-by-layer method. Each layer consists of several lines of molten metal. Laser parameters and thermal properties of the materials affect the geometric characteristics of the melt pool such as its height, depth, and width. The geometrical characteristics of the melt pool are determined herein by optical microscopy and three-dimensional bulk structures are fabricated to investigate the relationship between them. Powders of the commercially available Fe-based tool steel AISI H13 and Ni-based superalloy Inconel 738LC are used to investigate the effect of material properties. Only the scan speed is controlled to change the laser parameters. The laser power and hatch space are maintained throughout the study. Laser of a higher energy density is seen to melt a wider and deeper range of powder and substrate; however, it does not correspond with the most highly densified three-dimensional structure. H13 shows the highest density at a laser scan speed of 200 mm/s whereas Inconel 738LC shows the highest density at 600 mm/s.

The effect of seasonal wind on the tidal circulation in Jeju harbor was examined by using a numerical shallow water model. A finite element for analyzing shallow water flow is presented. The Galerkin method is employed for spatial discretization. Two step explicit finite element scheme is used to discretize the time function, which has advantage in problems treating large numbers of elements and unsteady state. The numerical simulation is compared with three cases; Case 1 does not consider the effect of wind, Case 2 and Case 3 consider the effect of summer and winter seasonal wind, respectively. According to result considering effect of seasonal wind, velocity of current vector shows slightly stronger than that of case 1 in the flow field. It can be concluded that the present method is a useful and effective tool in tidal current analysis.