본 연구에서는 3D 프린팅 FDM 방식의 적층 방향에 따라 기계적 물성이 달라지는 이방성 특성을 확인하고 이를 이용하여 위상 최 적설계를 수행하였다. 벤치마크 문제인 자동차 현가장치 부품 중 하나인 로어 컨트롤 암에 대하여 밀도법 기반 위상 최적설계를 수행 하였으며, 외부 하중과 이방성 특성에 따라 위상 최적결과가 다르게 나타나는 것을 확인하였다. 이를 이용하여 최적화된 모델에 대하 여 3D 프린터로 적층 방향을 달리하여 2가지 시험품을 제작하였으며 인장시험을 수행하였다. 시험시 3D 비접촉 변형률 측정기를 이 용하여 변형률을 구하였으며 이를 CAE 응답해석으로 얻은 변형률과 비교한 결과가 정량 및 정성적으로 일치하는 것을 확인하였다. 3D 프린팅 적층 방향을 고려한 위상 최적모델의 인장 실험 결과를 통해 해당 최적설계 방법론의 유효성을 검증하였다.

In this present investigation, machinability studies on novel aluminum composite with hybrid reinforcements of copper-coated 4% carbon fibers (CFs) and 3% nanoclay in AA6026 matrix fabricated by compocasting method is performed. Step drill bit and multifaceted drill bit are used by adopting central composite design (CCD) in response surface methodology (RSM). The outcomes show that, with a rise in rotational speed surface irregularities, resultant force and material removal rate (MRR) intensifies, and with the additional rise in rotational speed, all the outputs decrease considerably. High MRR, resultant cutting force, and surface roughness are obtained with multifaceted carbide drills, compared with a step drill. Desirability function is used to maximize the MRR and minimize the resultant cutting forces considering the constant surface roughness of 3 μm. The optimal values are rotational speed of 1285 rpm, feed rate of 60 mm/min with the step drill bit, producing an MRR of 0.0439 kg/sec and a resultant cutting force of 185.818 N. The second-order empirical models are developed for outputs, which are fed into the non-traditional metaheuristic Evaporation Rate-based Water Cycle Algorithm (ER-WCA) therefore the lower objective value is achieved with step drill of 51.7421. It is found that using a step drill the machinability performance of this hybrid nanocomposite is well improved than the machining with other drill bits. This composite fulfills the norms of 2000/53/CE-ELV European environmental directives.

As the decommissioning of nuclear power plants increases, there is an increasing interest in the amounts of radioactive waste. Especially, the radiation dose limit for packaging of radioactive wastes shall not exceed 2 mSv·h−1 and 0.1 mSv·h−1 on contact and at 2 m, respectively in South Korea. The DEMplus provides various environmental geometry and all properties such as materials, absorptions, and reflections and the estimation of the radiation dose rates is based on the radiation interactions of the designed 3D geometry model. With the consideration of the radiation dose rate by using DEMplus and its strategy of packaging plan, the radiation shielding was optimized and estimated in this paper. The modular shielded containers (MSC) with shielding inserted were used for radioactive wastes that require shielded packaging. In order to verify the accuracy of the estimated radiation dose rate by using DEMplus, the estimated results were compared with those obtained using MicroShield. The trends of the estimated radiation dose rates using DEMplus and the estimation of MicroShield were similar to each other. The results of this study demonstrated the feasibility of using DEMplus as a means of estimating the radiation dose limit in packaging plan of the radioactive waste.

Waste that contains or is contaminated with radionuclides arises from a number of activities involving the use of radioactive material. Such activities include the operation and decommissioning of nuclear facilities; the use of radionuclides in medicine, industry, agriculture, research and education. Radioactive waste must be safely disposed in a radioactive waste repository for the protection of public health and the environment. In order to safely dispose of radioactive waste in a repository, it is important to derive an optimal predisposal management scenario because radioactive waste must be processed (i.e. processing (pretreatment, treatment and conditioning), storage and transport) for satisfying waste acceptance criteria (WAC). Optimal scenario of predisposal management of radioactive waste is derived for considering the balancing of exposures of workers and/or those of members of the public, the short term and long term risk implications of different waste management strategies, the technological options available and the costs. However, existing studies for deriving the optimal scenario of predisposal management of radioactive waste have evaluated only the radiation dose of workers and public within given scenarios using fixed value, or have derived optimal single process (i.e. decontamination) of predisposal management using Multi-Attribute Decision Making (MADM) methodology. In this study, optimal predisposal management scenario is derived by evaluating exposures of workers using system dynamics (SD) technique. Radiation dose assessment SD model was modeled using VENSIM® code developed by VENTANA systems Inc.. SD Model has the advantage of being able to respond flexibly when decision makers want to change input data and it has the advantage of being able to track dynamically changing phenomena and visually confirm interdependence. After that, based on the SD model derived from this study, evaluations of exposures of public, cost, and technicality will be added to be utilized when establishing an optimal scenario of predisposal management of radioactive waste considering multi attribute.

During decommissioning of a nuclear power plant, a large amount of radioactive waste is produced, and it is known to cost more than 300 billion won to dispose the waste. To reduce the disposal cost, it is essential to minimize the number of radioactive waste drums, which can be achieved by detecting and removing hotspot contaminations in the radioactive waste drums. Therefore, a Compton CT system for radioactive waste monitoring is under development, which provides the images of both the internal structure of the drum and the radioactive hotspot(s) in the drum. Based on the acquired information, the activity of hotspots can be estimated. The performance of the system is affected by various geometry factors. Therefore, it is essential to determine optimal configuration by evaluating the effects of the factors on the performance of the system. In the present study, we determined the optimum value of the factors and then predicted the performance of the optimized system by using a simulator based on the Geant4 Monte Carlo simulation. For optimization, the factors were evaluated in terms of structural similarity index measure (SSIM) and measurement time. The considered factors were the activity of the CT source, source to object distance (SOD), object to detector distance (ODD), and projection angle. The simulation result showed that the activities of the CT sources were determined as 23 mCi for 137Cs and 9.6 mCi for 60Co. The optimal SOD and ODD were 180 cm and 40 cm, respectively. The optimal projection angle was evaluated as 4° since it achieves the SSIM of 0.95 faster than other projection angles. With the optimized parameters, the performance of the system was evaluated using the IAEA gamma CT standard phantom containing a hotspot of 137Cs (7.02 μCi). The Compton image was reconstructed using the back-projection algorithm, and the CT image was reconstructed using the filtered back-projection algorithm. The result showed that the location of the hotspot in the Compton image was well identified at the true position. The acquired CT image also well represented the internal structure of the phantom, and the estimated mean linear attenuation coefficient value (μ= 0.0789 cm−1) of the phantom was close to the true value (μ= 0.0752 cm−1). In addition, the hotspot activity estimated by combining the information of the Compton image and CT image was 8.06 μCi. Hence, it was found that the Compton CT system provides essential information for radioactive waste drums.

Multiple sorptive sites on natural illitic clays (e.g., frayed edge [FES], type II [TS], and planar sites [PS]) play an important role to diverse 137Cs immobilization in soil and aquifer environments. This study investigated the Cs sorption capabilities of 10 natural illitic clays at ranged Cs concentrations (1 ×10−7 to 1×10−3 mol·L−1) under various competing potassium concentration (distilled water to 1×10−1 mol·L−1). Additionally, multisite cation exchange model was performed to evaluate the best-fit sorption model and optimize the sorption capacities and affinities of multiple sorptive sites for Cs. Here, the experimental Cs sorption isotherms varied among 10 illtic clays, indicating different sorption capacities of Cs on illitic clays. The best-fit sorption model exhibited that variable Cs sorption of 10 illitic clays was significantly related to the sorption capacities at the FES (1.76 × 10−5 to 1.12×10−4 eq·kg−1), TS (1.59×10−3 to 9.76×10−3 eq·kg−1), and PS (2.14×10−2 to 1.51×10−1 eq·kg−1), respectively. The FES predominantly contributed to Cs sorption at low aqueous concentrations, whereas the TS and PS sorbed Cs at high concentrations. These sorption capabilities of multiple sorptive sites were correlated to illite contents and crystallinity of illitic clays, implicating that such parameters could be key factors to predict the Cs sorption for natural illitic clays in soil and aquifer environments. Finally, 1-D transport simulations represented that the severe Cs retardation occurred at low Cs concentration, implying that the FES predominantly affected to Cs transport in actual radioactive contamination sites (i.e., where low Cs concentration prevails), compared to the TS and/or PS.

In this study, stiffness evaluation was conducted on the main member, front cross member, and rear cross member, which are three components of sub-frame for SUVs (sports utility vehicles), through mode analysis. As for the design variables used in the analysis, the maximum frequency was examined by varying the width and height of each of the three parts into four types. Of course, the weight at this time is minimized, and the mode is set as a constraint that only bending occurs and no distortion occurs. As a result of the analysis, the member affecting the 1st mode was the rear cross member, and the member having the greatest influence on the 2nd mode was the front cross member. In addition, the member with the greatest influence on the 3rd mode appeared as the rear cross member, indicating that this part had the greatest effect on the bending stiffness.

최근에는 경량화 문제에 대한 합리적인 솔루션을 제공하고 유용한 개념설계를 제공할 수 있는 다중 재료 구조 위상최적화가 더욱 중요해지고 있다. 기존의 MMTO(Multi-Material Topology Optimization)의 경우 후보 물질의 수가 증가할수록 설계변수의 수도 증가 하고, 결과적으로 계산 시간이 크게 증가한다. 따라서 PSM(Phase Section Method)과 같은 단일 설계변수를 갖는 MMTO가 제안되었 다. 본 연구는 조성비가 면적이나 부피비를 나타내지 못하고, 설계변수가 목표치에 충분히 집중되지 않고, 특정 재료가 요구량보다 적 게 생성되는 PSM의 세 가지 주요 제한점을 고려하여 이를 개선하는데 중점을 둔다. 이러한 한계를 극복하기 위해 재정의된 조성비와 더 나은 수렴을 위한 조정된 매개변수를 제안한다. 제안된 수정 사항의 유효성을 2차원 및 3차원 수치 예제를 통해 검증한다.

In this paper, a method of reducing the weight of vehicle wheels through topology optimization by finite element method is proposed. Recently, various environmental pollution caused by the operation of vehicles is gradually increasing, and this has a great correlation with the fuel efficiency of the vehicle. Therefore, it is required to reduce the weight of the vehicle to increase fuel efficiency. Among them, the vehicle's wheels are a key part of vehicle acceleration and braking, and passenger safety. Because the shape of the wheels is different, various effects such as reduced fuel economy and reduced airpower occur as well as aesthetic factors. The stiffness of the wheels plays an important role in transmitting the vehicle's power to the tires and braking. In this study, to reduce weight while satisfying the stiffness value, we propose to use topology optimization to design an arbitrary shape according to the number of spokes on the wheel.

고품질의 아가콩 음료개발을 위해 반응표면분석법에 의한 추출조건을 최적화 하였다. 아가콩 의 최적 볶음조건은 250 ℃, 30분으로 설정하였다. 추출시간, 추출온도에 따른 아가콩의 품질지표인 pH, 색도 및 이소플라본 함량은 1% 이내에서의 유의적인 영향을 미치는 것으로 나타났다. 추출온도와 추출시간이 길어질수록 이소플라본 함량은 높은 것으로 나타났다. 반응표면분석의 이소플라본 추출 공정 최적화 결과 추출온도는 99.5 ℃, 추출시간은 1.7 h으로 나타났으며, 이 조건에서 이소플라본의 최적 수 율은 10.63 μg/mL로 예측되었다.

본 논문에서는 구조물의 좌굴 온도와 좌굴 형상을 제어하는 새로운 크기 최적화 방법에 대해서 소개한다. 구조적 안정성 관점에서 구조물의 좌굴 온도와 좌굴 형상을 예측하는 것은 중요한 주제 중 하나이다. 이를 공학적인 직관을 통해 예측하고 최적화된 구조 설계 를 하는 것은 너무나 어려운 과제이다. 이러한 한계점을 해결하기 위해 본 연구에서는 유한요소 시뮬레이션과 치수 최적 설계 방식의 조합을 제안한다. 구조물의 좌굴 온도와 좌굴 형상이 구조물의 두께에 영향을 받는다는 생각에서 착안해 설계 변수를 구조물의 노드 의 두께 값으로 설정했다. 좌굴 온도 값과 좌굴 형상을 목적 함수로 정해진 부피 값을 제약 조건으로 두었다. 치수 최적 설계를 통해 원 하는 좌굴 온도와 좌굴 형상을 유도하기 위한 최적의 두께 분포를 결정할 수 있다. 제안된 치수 최적 설계의 타당성은 본 논문의 다양 한 직사각형 복합 구조물 예제들을 사용해서 검증하였다.

An endemic plant to South Korea, Sedum zokuriense Nakai, has medical and floricultural potential and is of ecological importance. Today, many species under the genus Sedum are used as green-roofing systems, sold as ornamental plants, and studied for breeding programs. As such, optimization studies should be conducted to identify key environmental and cultivation factors that would affect their survival and vegetative growth. In this study, shading levels (50%, 65%, 80%, 95%, and 98%), potting mixes (decomposed granite, fertilizer-amended media, perlite, river sand, burnt husk, and vermiculite), and fertilization rates [(control, 0 ppm), 500, 750, 1,000, and 2,000 ppm] were investigated and the responses of S. zokuriense in terms of their survival rate, plant growth and development, CIELAB color reading, and chlorophyll content under greenhouse conditions. Results showed that these stonecrop species are shade-loving and thrive in low-light conditions. Although the fertilizer use had minimal impacts, growing plants at 65% shading, planted with RS:VL:PL (6:2:2, v/v/v) potting media have substantially produced a high survival rate in propagation using stem cuttings. Furthermore, this allowed plants to be established while supporting high vegetative growth, green and healthy plants with high chlorophyll content.

This paper is a study to improve the energy harvesting output of a TENG(Triboelectric nanogenerator) driven by wind power using fine PTFE(Polytetrafluoroethylene) flakes. The structure of the nanogenerator was manufactured in the cylindrical structure, Al(Aluminium) was attached to the inner wall of the cylinder and the PTFE flakes were rotated by the wind inside the cylinder. The number of contact and separation motions was increased as there are multiple PTFE flakes, resulting in improvement of the harvesting output. Through this, it was evaluated to the energy harvesting output characteristics according to the change in the number of PTFE flakes. Up to the optimum, the energy collection efficiency shows the linear correlation with the increase in PTFE flakes and decreases after that. As the PTFE flakes are more than the optimum, the lowering in the harvesting output is induced by obstructing the flow of wind inside the cylinder.

The process optimization of directed energy deposition (DED) has become imperative in the manufacture of reliable products. However, an energy-density-based approach without a sufficient powder feed rate hinders the attainment of an appropriate processing window for DED-processed materials. Optimizing the processing of DEDprocessed Ti-6Al- 4V alloys using energy per unit area (Eeff) and powder deposition density (PDDeff) as parameters helps overcome this problem in the present work. The experimental results show a lack of fusion, complete melting, and overmelting regions, which can be differentiated using energy per unit mass as a measure. Moreover, the optimized processing window (Eeff = 44~47 J/mm2 and PDDeff = 0.002~0.0025 g/mm2) is located within the complete melting region. This result shows that the Eeff and PDDeff-based processing optimization methodology is effective for estimating the properties of DED-processed materials.

In this paper, a GAN-based data augmentation method is proposed for topology optimization. In machine learning techniques, a total amount of dataset determines the accuracy and robustness of the trained neural network architectures, especially, supervised learning networks. Because the insufficient data tends to lead to overfitting or underfitting of the architectures, a data augmentation method is need to increase the amount of data for reducing overfitting when training a machine learning model. In this study, the Ganerative Adversarial Network (GAN) is used to augment the topology optimization dataset. The produced dataset has been compared with the original dataset.