If radioactive plumes are released outside due to loss of containment building integrity during a nuclear power plant accident, these materials might travel with the wind, affecting both the surrounding environment and neighboring countries. In China, most nuclear power plants are located on the eastern coast. Consequently, a radioactive plume generated during an accident could negatively impact even the western part of the Korean Peninsula due to westerly winds. To detect such problems early, respond quickly, and protect residents, a system that can monitor aerial radiation under normal conditions is needed. Additionally, a detection system that can operate in real-time in an emergencies conditions is required. The current method for aerial radiation measurement takes environmental radiation data from a monitoring post 1.5 m above the ground and converts it to altitude. To measure actual aerial radiation, an expansive area is surveyed by aircraft. However, this approach is both time-consuming and expensive. Thus, to monitor radioactive plumes influenced by environmental factors like wind, we need a radiation detector that can gauge both radioactivity and directionality. In this study, we developed a radiation detector capable of assessing both the radioactivity and directionality of a radioactive plume and conducted its performance evaluation. We miniaturized the radiation detector using a CZT (Cadmium Zinc Telluride) sensor, enabling its mounting on unmanned aerial vehicles like drones. It is configured with multi-channels to measure directionality of a radioactive plumes. For performance evaluation, we positioned two-channel CZT sensors at 90 degrees and measured the energy spectrum for angle and distance using a disk-type radioactive isotope. Using this method, we compared and analyzed the directionality performance of the multi-channel radiation detector. We also confirmed its capability to discern specific radioactivity information and nuclide types in actual radioactive plumes. Our future research direction involves mounting the multi-channel radiation detector on a drone. We aim to gather actual aerial radiation data from sensors positioned in various directions.

KHNP is conducting research to decommission Wolsong Unit 1 Calandria. Establishment of preparation and dismantlement processes, conceptual design of equipment and temporary radiation protection facilities, and waste management are being established. In particular, the ALARA plan is to be established by performing exposure dose evaluation for workers. This study aims to deal with the methodology of evaluating exposure dose based on the calandria dismantling process. The preparation process consists of bringing in and installing tooling and devices, and removing interference facilities to secure work space. The main source term for the preparation process is the calandria structure itself and crud of feeders. In the case of the dismantlement process, a structure with a shape that changes according to the process was modeled as a radiation source. It is intended to estimate the exposure dose by selecting the number of workers, time, and location required for each process in the radiation field evaluated according to the preparation and dismantlement process. In addition, it is also conducting an evaluation of the impact on dust generated by cutting operations and the human impact of C-14, H-3, which are specialized nuclides for heavy water reactors. KHNP is conducting an exposure dose evaluation based on a process based on the preparation and dismantlement process for decommissioning Calandria through computation code analysis. If additional worker protection measures are deemed necessary through dose evaluation according to this methodology, the process is improved to prepare for the dismantling of worker safety priorities.

Heavy water primary system decontamination technology is essential to reduce worker exposure and improve safety during maintenance and decommissioning of nuclear facilities. Advanced decontamination technology development aims to secure controlled decontamination technologies that can reduce the cost of radiation exposure and dramatically reduce the amount of secondary waste generated when decontaminating large equipment and large-area facilities. We conducted a study to identify candidate corrosion inhibitors through the literature and analyze the degree of corrosion of carbon steel samples. Countries with advanced nuclear technology have developed chemical decontamination technology for the entire nuclear power generation system and applied it to the dismantling and maintenance of nuclear power plants. In the decontamination process, the corrosion oxide film must be removed. If the base metal is corroded by the decontaminant in this process, additional secondary waste is generated and treatment costs increase. Therefore, it is necessary to develop a corrosion inhibitor that inhibits the corrosion of the carbon steel base metal in the decontamination process to generate a secondary waste liquid that is favorable for waste reduction and treatment. In this presentation, a study was conducted to analyze the extent of corrosion on a carbon steel base material and identify candidate materials for corrosion inhibition testing. Samples were analyzed using optical microscopy and EPMA analysis to determine the thickness of the corroded oxide film. EPMA analysis also allowed us to map the elemental distribution of the carbon steel corrosion layer, which we plan to quantify in the future. The candidate materials for organic-based corrosion inhibitor were also selected based on their inhibition mechanism; having high electronegative elements for coordinate covalent bonding at metal surface and hydrophobic nonpolar group for preventing access of corrosive substances.The selection of candidate materials for corrosion inhibition testing was based on the mechanism of the corrosion inhibitor. Organic-based corrosion inhibitors are adsorbed by donor-acceptor interactions between metal surfaces and highly electronegative elements. Corrosion can also be inhibited by arranging hydrophobic nonpolar groups on metal surfaces in the solution direction to prevent access of corrosive substances.

The domestic Pressurized Heavy Water Reactor (PWHR) nuclear power plant, Wolsong Unit 1, was permanently shut down on December 24, 2019. However, research on decommissioning has mainly focused on Pressurized Water Reactors (PWRs), with a notable absence of both domestic and international experience in the decommissioning of PHWRs. If proper business management such as radiation safety and waste is not performed, it can lead to increased business risks and costs in decommissioning. Therefore, the assessment of waste volume and cost, which provide fundamental data for the nuclear decommissioning process, is a crucial technical requirement before initiating the actual decommissioning of Wolsong Unit 1. Decommissioning radiation-contaminated structures and facilities presents significant challenges due to high radiation levels, making it difficult for workers to access these areas. Therefore, technology development should precede decommissioning process assessments and safety evaluations, facilitating the derivation of optimal decommissioning procedures and ensuring worker safety while enhancing the efficiency of decommissioning operations. In this study, we have developed a program to estimate decommissioning waste amounts for PHWRs, building upon prior research on PWR decommissioning projects while accounting for the specific design characteristics of PHWRs. To evaluate the amount of radioactive waste generated during decommissioning, we considered the characteristics of radioactive waste, disposal methods, packaging container specifications, and the criteria for the transfer of radioactive waste to disposal operators. Based on the derived algorithm, we conducted a detailed design and implemented the program. The proposed program is based on 3D modeling of the decommissioning components and the calculation of the Work Difficulty Factor (WDF), which is used to determine the time weighting factors for each task. Program users can select the cutting and packaging conditions for decommissioning components, estimate waste amount based on the chosen decommissioning method, and calculate costs using time weighting factors. It can be applied not only to PHWRs, but also to PWRs and non-nuclear fields, providing a flexible tool for optimizing decommissioning process.

Nuclear facilities present the important task related to the migration and retention of radioactive contaminants such as cesium (Cs), strontium (Sr), and cobalt (Co) for unexpected events in various environmental conditions. The distribution coefficient (Kd) is important factor for understanding these contaminants mobility, influenced by environmental variables. This study focusses the prediction of Kd values for radionuclides within solid phase groups through the application of machine-learning models trained on experimental data and open source data from Japan atomic energy agency. Three machine-learning models, such as the convolutional neural network, artificial neural network, and random forest, were trained for prediction model of the distribution coefficient (Kd). Fourteen input variables drawn from the database and experimental data, including parameters such as initial concentration, solid-phase characteristics, and solution conditions, served as the basis for model training. To enhance model performance, these variables underwent preprocessing steps involving normalization and log transformation. The performances of the models were evaluated using the coefficient of determination. These results showed that the environmental media, initial radionuclide concentration, solid phase properties, and solution conditions were significant variables for Kd prediction. These models accurately predict Kd values for different environmental conditions and can assess the environmental risk by analyzing the behavior of radionuclides in solid phase groups. The results of this study can improve safety analyses and longterm risk assessments related to waste disposal and prevent potential hazards and sources of contamination in the surrounding environment.

Structural stability of a waste form can be provided by the waste form itself (steel components, etc.), by processing the waste to a stable form (solidification, etc.), or by emplacing the waste in a container or structure that provides stability (HICs or engineered structure, etc.). The waste or container should be resistant to degradation caused by radiation effects. In accordance with the requirements for the domestic waste acceptance criteria, irradiation testing of solidified waste forms containing spent resin should be conducted on specimens exposed to a dose of 1.0E+6 Gy and other material 1.0E+7 Gy. Expected cumulative dose over 300 years is about 1.770E+6 Gy for spent resin and 0.770E+6 Gy for dried concentrated waste generated from NPPs generally. According to NRC Waste Form Technical Position, to ensure that spent resins will not undergo adverse degradation effects from radiation, resins should not be generated having loadings that will produce greater than 1E+6 Gy total accumulated dose. If it necessary to load resins higher than 1E+6 Gy, it should be demonstrated that the resin will not undergo radiation degradation at the proposed higher loading. This is the recommended maximum activity level for organic resins based on evidence that while a measurable amount of damage to the resin will occur at 1E+6 Gy, the amount of damage will have negligible effect on disposal site safety. Cementitious materials are not affected by gamma radiation to in excess of 1E+6 Gy. Therefore, for cement-stabilized waste forms, irradiation qualification testing need not be conducted unless the waste forms contain spent resins or other organic media or the expected cumulative dose on waste forms containing other materials is greater than 1E+7 Gy. Testing should be performed on specimens exposed to IE+6 Gy or the expected maximum dose greater than 1E+6 Gy for waste forms that contain ion exchange resins or other organic media or the expected maximum dose greater than 1E+7 Gy for other waste forms. This is suggestion as a review result that requirement for irradiation testing of solidified waste forms has something to be revise in detail and definitively.

The increasing accumulation of spent nuclear fuel has raised interest in High-Level Waste (HLW) repositories. For example, Sweden is under construction of the KBS-3 repository. To ensure the safety of such HLW repository, various countries have been developing assessment models. In the Republic of Korea, the Korea Atomic Energy Research Institute has been developing on the AKRS model. However, traditional safety assessment models have not considered the fracture growth in the far-field host rock as a function of time. As repository safety assessments guarantee safety for million years, sustained stress naturally leads to the progressive growth of fractures as time goes on. Therefore, it becomes essential to account for fracture growth in the surrounding host rock. To address this, our study proposes a new coupling scheme between the Fracture growth model and the radionuclide transport model. That coupling scheme consists of the Cubic Law model as a fracture growth function and the GoldSim code which is a commercial software for radionuclide transport calculations. The model that adopting such fracture growth functions showed an increase of up to 15% in the release of radionuclide compared to traditional assessment models. our observations indicated that crack growth as a function of time led to an increase in hydraulic conductivity that allowed more radionuclide transport. Notably, these findings show the significance of adopting fracture growth models as a critical element in evaluating the safety of nuclear waste repositories.

The development of advanced nuclear facilities is progressing rapidly around the world. Newly designed facilities have differences in structure and operation from existing nuclear facilities, so Safeguards by Design (SBD), which applies safeguards at the design stage, is important. To this end, designers should consider the safeguardability of nuclear facilities when designing the system. Safeguardability represents a measure of the ease of safeguards, and representative evaluation methodologies are Facility Safeguardability Analysis (FSA) and Safeguardability Check-List (SCL). Those two have limitations in the quantification of safeguardability. Accordingly, in this study, the Safeguardability Evaluation Method (SEM), which has clear evaluation criteria based on engineering formulas, was developed. Nuclear Material Accountancy (NMA), a key element of Safeguards, requires the Material Balance Area (MBA) of the target facility and performs Material Balance Evaluation (MBE) based on the quantitative evaluation of nuclear materials entering or leaving the MBA. In this study, about 10 factors related to NMA were developed, including MBA, Key Measurement Point (KMP), Uncertainty of a detector, Radiation signatures, and MUF (Material Unaccounted For). For example, one of the factors, MUF is used in MBA to determine diversion through analysis of unquantified nuclear materials and refers to the difference between Book Inventory and Physical Inventory, as well as errors occurring during the process in bulk facilities, errors in measurement, or intentional use of nuclear materials. This occurs in situations such as attempted diversion, and accurate MUF evaluation is essential for solid Safeguards implementation. MUF can be evaluated using the following formula (MUF=(PB+X-Y)-PE). The IAEA’s Safeguards achievement conditions (MUF < SQ) should be met. Considering this, MUF-related factors were developed as follows. (􀜵􀜧􀜯 = 1 − 􀯆􀯎􀮿 􀯌􀯊 ) In this way, about 10 factors were developed and described in the text. This factors is expected to serve as an important factor in evaluating the safeguardability of NMA, and in the future, safeguardability factors related to Containment & Surveillance (C&S) and Design Information Verification (DIV) will be additionally developed to conduct a comprehensive safeguardability evaluation of the target facility. This methodology can significantly enhance safeguardability during the design stage of nuclear facilities.

As the demand for nuclear power increases as a means to achieve carbon neutrality, concerns about nuclear proliferation have also grown. Consequently, significant researches have conducted to enhance nuclear non-proliferation resistance. Among these research, nuclear material attractiveness is a methodology used to evaluate how appealing a particular material is for potential use in nuclear weapons, based on the characteristics of that material. Existing nuclear material attractiveness assessments focused on materials like U, Pu, and TRU, which could be directly used in the production of nuclear weapons. However, these assessments did not consider how the properties of nuclear materials change throughout the nuclear fuel cycle, with each facility process. This study assumed a scenario of the nuclear fuel cycle of graphite reduction reactors and analyzed including enrichment facilities and PUREX. This study used the FOM (Figure-Of-Merit) method developed by LANL (Los Alamos National Laboratory) for evaluating the nuclear material attractiveness. The FOM formula consists of three parameters such as critical mass, heat content, and dose The critical mass of targe materials and the dose evaluation were conducted using the Monte Carlo N-Particle code. The heat content was calculated using the ORIGEN code embedded in the Scale code. In particular, if U-238 is dominant in the facility’s materials, such as mining and refining facilities, and critical mass evaluation is unpractical. Therefore, 1SQ (Significant Quantity) of that uranium was assumed as the critical mass value for the FOM evaluation, even though 1SQ is not identical to the critical mass As a result of this study, the attractiveness of Pu produced by PUREX among all nuclear fuel cycle facilities was 2.7616, which was the most attractive to be diverted to nuclear weapons. Through this study, it was shown that the proliferation risk of the nuclear facilities in the nuclear fuel cycle and risk of diversion among those facilities.

기후변화와 세계시장 개방에 따른 외래 및 돌발해충의 종류는 다양해지고 밀도는 지속적으로 증가하고 있지 만 발생 실태에 관한 자료는 미흡하다. 본 연구는 경남지역 돌발 및 남방계 해충의 발생과 피해조사를 위해 미국선 녀벌레, 썩덩나무노린재, 담배거세미나방 등 3종을 경남 18시·군에서 조사하였다. 미국선녀벌레는 약충기(6월), 성충기(9월) 조사를 진행하였고, 길이가 50cm 이상되는 가지의 밑동에서 위쪽으로 50cm 내 개체를 육안조사하 였다. 썩덩나무노린재는 콩 개화기(7월), 등숙기(9월) 조사를 진행하였고 지점당 집합페로몬 트랩 1개를 설치하 고 1주 후 채집된 마리 수를 조사하였다. 담배거세미나방은 성페로몬 트랩 1개를 설치한 뒤 1주 후 채집된 마리 수를 조사하였다. 미국선녀벌레는 의령, 함안, 함양 등에서 발생이 많았고, 전년대비 발생이 소폭 감소하였다. 썩덩나무노린재는 합천, 밀양, 함양 등에서 발생이 많았고, 담배거세미나방은 전시군에서 발생이 확인되었으 며, 특히 함양, 산청, 사천, 고성 등에서 밀도가 높았다.

최근 기후변화에 따라 아열대 작물 재배가 증가하면서 경남지역 망고 재배면적도 크게 증가하고 있다. 하지만 망고에 발생하는 병해충 발생 정보가 부족하여 2022년부터 현재까지 경남지역에 있는 망고농장을 조사하였으 며, 그 결과 병해 6종, 해충 8종 발생을 확인하였다. 특히 경남지역 망고 포장에서 꽃노랑총채벌레, 대만총채벌레, 볼록총채벌레 등의 발생을 확인하였고, 통영, 함안, 밀양 등에서 총채벌레류에 의한 피해가 발생하였다. 많은 농가에서 총채벌레류 방제를 위해 화학농약에 의존하고 있으나 총채벌레는 반복적인 약제 노출시 빠른 세대 진전으로 인해 저항성 발달이 쉽기때문에 방제에 어려움을 겪고 있다. 이러한 문제를 해결하고자 색상별 끈끈이 트랩의 총채벌레류 유인효과를 확인하였으며, 꽃노랑총채벌레는 노랑, 주황, 연두, 대만총채벌레는 빨강, 노랑, 파랑, 볼록총채벌레는 파랑, 노랑, 빨강 순으로 유인효과가 높은 것을 확인하였다.

Until now, in case of Palaearctic region, only one species, Nesendaeus monochrous in this genus was recorded from China. but the biology and life cycle are not clearly known, yet. This species collected from the bud of Glochidion chodoense in Korea for the first time and closely related to Heterochyromera imerodeus Kojima & Morimoto which was recorded only in Japan,. But Nesendaeus monochrous is easily distinguishable from H. imerodeus by the relatively longer elytra with bisinuately round apices. Heterochyromera imerodeus Kojima & Morimoto can be found from Eurya emarginata and Glochidion obovatum in Japan. So, this two species are closely related each other and need more taxonomic study about the generic synonymy or changing the generic position.

The repeated use of biocidal products, including household insecticides and disinfectants, has led people to seek safer alternatives, such as light traps, ultrasound generators, or repellent lamps. By appearances, these physical/non-chemical alternatives seem appealing to many consumers and are gaining more attention. However, unlike biocidal products, these alternatives are not subject to mandatory approval and registration processes, and no standards for efficacy and safety are in place. Given the increasing numbers of insect traps on the market, there is an urgent need to investigate their efficacy. In the present study, we examined the attraction activity of ten commercially available insect trap products. They varied in size, structure, trapping methods (fan or sticky pad), and attractants. Their efficacies were assessed under both laboratory condition (1.8m x 1.8m x 1.8m) and semi-field room condition (4m x 6m x 2m). Ul*****APTM demonstrated the highest capture rate (%), leading us to further study the role of its attractant. Notably, the capture rate increased by 28.9% when the CO2 attractant was used, displaying statistical differences (P = 0.032). For practical application in the field, consumer acceptance and satisfaction were monitored using 20 participants. The potential of insect traps as viable alternatives to biocidal products is discussed.

모기는 감염병을 매개하는 종으로 전염병 확산 억제를 위해서는 개체수의 감시와 정확한 예측이 필요하다. 본 연구에서는 모기 개체수 및 기상 및 현장 자료를 활용해 모기 개체수 머신러닝 모델을 개발하였다. 모기 개체수는 디지털 모기 측정기(Digital Mosquito Monitoring System, DMS)의 2015 년~2022년의 5월~10월의 자료를 활용하였다. 기상 자료는 기온, 강수량, 풍속, 습도를 사용하였으며, 현장 조사 자료는 현장을 명목척도와 서열척도로 나누어 기록하여, 명목 척도의 경우 원핫 인코딩으 로 변환해 수치화하여 사용하였다. 분석에 사용된 머신러닝 모델은 Artificial Neural Network, Random Forest, Gradient Boosting Machine, Support Vector Machine이며 성능지표로 R2, RMSE를 사용하였다. 연구 결과, Gradient Boosting 모델이 R2 0.4, RMSE 22.45로 가장 좋은 성능을 나타냈다. 현장 조사 자료 를 분석에 활용하였을 때 R2는 증가하였고, RMSE는 감소하였다. 본 연구 결과 모기 개체수에 현장 조사 자료가 예측 정확도를 향상시킬 수 있음을 확인하였다.

This study was conducted to determine the appropriate seeding dates by verifying the difference in winter survival and productivity of alfalfa according to fall sowing dates in the central area of South Korea. The experiment was conducted for 2 years (2020 and 2021) at the field in the Department of Animal Resources Development, NIAS located in Cheonan. Sowing dates started from September 18 to November 8 with 10 days of intervals during 2020 and 2021; SO1 (September 18), SO2 (September 28), SO3 (October 8), SO4 (October 18), SO5 (October 28), and SO6 (November 8). After sowing, the winter survival rate was measured in the spring of the following year, and the dry matter yield was measured by harvesting at 10% flowering and harvesting five times a year. SO6 failed to winter survival, and SO5 also had a lower winter survival rate than SO1~4 (p<0.05). The average annual dry matter yield of alfalfa linearly decreased with delaying sowing dates (p<0.05). The feed value did not differ in the same year by delaying the sowing date in the same year. These results suggest that sowing date should be started before October 18 to increase winter survival and productivity of alfalfa in the central area of South Korea.

This study was aimed to isolate bacterial inoculants producing chitinase and evaluate their application effects on corn silage. Four corn silages were collected from four beef cattle farms to serve as the sources of bacterial inoculants. All isolates were tested against Fusarium graminearum head blight fungus MHGNU F132 to confirm their antifungal effects. The enzyme activities (carboxylesterase and chitinase) were also measured to isolate the bacterial inoculant. Based on the activities of anti-head blight fungus, carboxylesterase, and chitinase, L. buchneri L11-1 and L. paracasei L9-3 were subjected to silage production. Corn forage (cv. Gwangpyeongok) was ensiled into a 10 L mini silo (5 kg) in quadruplication for 90 days. A 2 × 2 factorial design consists of F. graminearum contamination at 1.0104 cfu/g (UCT (no contamination) vs. CT (contamination)) and inoculant application at 2.1 × 105 cfu/g (CON (no inoculant) vs. INO (inoculant)) used in this study. After 90 days of ensiling, the contents of CP, NDF, and ADF increased (p<0.05) by F. graminearum contamination, while IVDMD, acetate, and aerobic stability decreased (p<0.05). Meanwhile, aerobic stability decreased (p<0.05) by inoculant application. There were interaction effects (p<0.05) on IVNDFD, NH3-N, LAB, and yeast, which were highest in UCT-INO, UCT-CON, CT-INO, and CT-CON & INO, respectively. In conclusion, this study found that mold contamination could negatively impact silage quality, but isolated inoculants had limited effects on IVNDFD and yeast.

Buckwheat (Fagopyrum esculentum), which is a traditional Korean crop, has been known as a health food due to its rich nutrition. This study was conducted to evaluate the change in flavonoid content of flowers and seeds during post-flowering growth of Korean tartary buckwheat variety ‘Hwanggeummiso’, with the aim of providing basic data for the development of functional food and feed additive. Tartary buckwheat took 69 and 99 days from the sowing date to reach the flowering and maturity stages, respectively. As a result of examining the flavonoid components of each part of tartary buckwheat, chlorogenic acid, rutin, and isoquercitrin of flowers increased from the flowering period on 22 May (0 days after flowering) to 42 days after flowering, while quercetin increased until 21 days after flowering and then decreased thereafter. In seeds, chlorogenic acid, rutin, and isoquercitrin were most abundant at the time of seed-bearing on 14 days after flowering, and showed a decreasing tendency thereafter. On the other hand, quercetin showed a tendency to increase until 21 days after flowering and then decrease. Overall, the flavonoid content was higher in flowers than in seeds, with rutin being particularly prominent. Based on this, the possibility as food materials and feed additives was confirmed using buckwheat produced in Korea.

Although the proportion of coal-fired power generation is decreasing, efficient operating technology is needed to continuously invest in facilities and reduce maintenance costs until it is abolished. Boilers, one of the main facilities of power plants, operate for a long time in harsh environments of high temperature and high pressure. In addition, damage due to deterioration is likely to occur depending on the fuel and tube material used. It is very important to judge soundness because damage caused by deterioration adversely affects facility operation. Previously, replication method was used to analyze the progress of deterioration. In the replication method, pre-treatment such as chemical treatment is performed on the boiler tube in the field, the area is reproduced by attaching a film, and the replicated film is determined by an expert in the laboratory with an expensive microscope. However, this method involves substantial costs and time requirements, as well as the possibility of human errors. To address these issues, we developed a mobile health assessment system in this research. Since it is detachable and takes images in real time, this system enables swift evaluations across a broad range and facilitates the assessment of preprocessing quality. In addition, it was intended to reduce existing human mistakes by developing a degradation classification algorithm using the merger cluster method.

With the recent advent of Metaverse, the character industry that reflects the characteristics of users' faces is drawing attention. there is a hassle that users have to select face components such as eyes, nose, and mouth one by one. In this paper, we propose a diffusion-based model that automatically generates characters from content human photographs. Our model generates user artistic characters by reflecting content information such as face angle, direction, and shape of a content human photo. In particular, our model automatically analyzes detailed information such as glasses and whiskers from content photo images and reflects them in artistic characters generated. Our network generates the final character through a three-step: diffusion process, UNet, and denoising processes. We use image encoders and CLIP encoders for the connection between style and input data. In the diffusion process, a collection of noise vectors is gradually added to a style vector to enable lossless learning of the detailed styles. All input values except for the style images are vectorized with CLIP encoders and then learned with noise style vectors in the UNet. Subsequently, noise is removed from the vectors through the UNet to obtain the artistic character image. We demonstrate our performance by comparing the results of other models with our results. Our method reflects content information without loss and generates natural high-definition characters.

There are many types of foam molding methods. The most commonly used methods are the pressure foaming method, in which foam resin is mixed with a foaming agent at high temperature and high pressure, and the normal pressure foaming method, which foams at high temperature without pressure. The polymer resins used for foaming have different viscosities. For foaming under normal pressure, they need to be designed and analyzed for optimal foaming conditions, to obtain resins with low melt-viscosity or a narrow optimal viscosity range. This study investigated how changes in viscosity, molding temperature, and cross-link foaming conditions affected the characteristics of the molded foam, prepared by blending rubber polymer with biodegradable resin. The morphologies of cross sections and the cell structures of the normal pressure foam were investigated by SEM analysis. Properties were also studied according to cross-link/foaming conditions and torque. Also, the correlation between foaming characteristics was studied by analyzing tensile strength and elongation, which are mechanical properties of foaming composites.