콘크리트 구조물은 노후화에 따른 균열 발생으로 내구성이 저하되며, 유지보수 과정에서 경제적 비용이 발생한다. 이를 해결 하기 위해 박테리아를 이용한 자가치유 기술이 주목받고 있으나, 기존의 캡슐화 및 펠릿화 공정은 높은 제작 비용이 발생한다. 본 연구에서는 지속 가능한 폐기물 자원인 골재 분말(BAP) 내 Hydroxyaptite(HAp)를 박테리아의 보호 담체 및 반응 촉진제로 활용 하여 자가치유 효율을 최적화하고자 하였다. BAP의 혼입 조건에 따른 균열 치유 특성을 평가하였으며, SEM, EDS 및 XRD 분석을 통해 박테리아의 생체광물화에 의한   및 HAp 생성 여부와 미세구조적 치유 메커니즘을 규명하였다. 연구 결과, BAP는 박테리 아의 생존성을 확보함과 동시에 치유 성능을 유의미하게 향상시키는 것으로 나타났다. 본 연구는 BAP 용 자가치유 콘크리트의 최적 배합 도출을 통해 유지 보수 비용 절감 및 구조물 장수명화를 위한 기초 자료를 제공할 것으로 기대된다.

This study proposes a distributed integrated control architecture based on Direct Digital Control(DDC) as an alternative to conventional centralized Distributed Control System(DCS) structures for a Canadian oil sands pilot plant, and theoretically analyzes its control characteristics and operational optimization potential. The target process consists of production and circulation, separation, water treatment, partial upgrading, and utility systems, and exhibits complex characteristics such as multiphase flow, high viscosity, time delay, strong coupling, and operation under extreme environmental conditions. In this study, an integrated control architecture combining independent DDC nodes for each process unit with a supervisory control layer is presented. A control model considering the coupling relationships among production, separation, water treatment, and upgrading processes is formulated, along with an objective function for energy optimization. Furthermore, through literature-based comparison and system architecture analysis, it is demonstrated that the DDC-based structure is suitable for oil sands pilot plants in terms of responsiveness, scalability, fault isolation, and energy efficiency.

In electric vehicles, lightweight design is an important development objective for improving energy efficiency. Seat frame materials that are important for weight reduction use steel. In this study, weight optimization analysis was conducted by applying Almag, an aluminu-magnesium alloy material that offers excellent weight reduction while maintaining structural strength, to the seat frame. First, key stiffness members among the seat components were identified. Static strength analysis and natural frequency analysis were then performed on the steel seat frame. Based on the analysis results, a static optimization analysis was carried out for the application of the Almag material to achieve displacement levels equivalent to the static strength analysis. In addition, a dynamic optimization analysis was performed to maximize the natural frequency. Through these analyses, the optimal thicknesses of the seat back and cushion frame were determined.

This study investigates the superior predictive performance of a DeepGBM model (combining boosting and deep learning) for identifying metabolic syndrome in the Korean adult population using KNHANES data. DeepGBM consistently showed superior performance compared to established algorithms. Feature prioritization revealed waist circumference and fasting glucose as critical predictors. This research demonstrates the potential of integrating advanced machine learning with public health data to improve early detection.

전 세계적인 물 부족 심화로 상수관망의 효율적 운영 및 유지보수(O&M) 중요성이 커지고 있다. 특히 정확한 수압 예측은 잠재적 문제의 사전 감지와 대응에 필수적이다. 이에 본 연구는 전처리된 데이터를 활용하여 현장 적용성이 높은 수압 예측 모델을 개발하는 것을 목표로 하였다. 이를 위해 8개 블록시스템(DMA)의 10분 단위 시계열 데이터와 4종류의 딥러닝 모델(LSTM, GRU, CNN-LSTM, CNN-GRU)을 활용하였으며, optuna를 통해 하이퍼파라미터를 최적화하고 배치 정규화 등을 적용해 학습 안정성을 확보하였다. 평가 결과, CNN-GRU 모델이 가장 우수한 성능을 나타냈다. 해당 모델을 기반으로 입력 조건에 따른 성능을 비교한 결과, 단변수 대비 다변수 입력 조건에서 예측 정확도가 향상됨을 확인하였다. 또한, 10분 선행 시점에서 최고 신뢰도(R2 0.9678, RMSE 0.0375)를 기록했으며, 지속성 모델의 성능이 점진적으로 하락하여 상대적인 저점을 형성하는 7시간 및 17시간 선행 시점에서 CNN-GRU 모델은 지속성 모델 대비 RMSE 기준 각각 48.0% 및 42.1%의 오차 개선을 달성하였다. 결론적으로, 본 연구에서 제안하는 전처리 및 하이퍼파라미터 통합 최적화 프로세스는 DMA별로 상이한 운영 환경에서도 안정적인 예측 성능을 확보할 수 있음을 입증하였다. 이는 현장 엔지니어의 데이터 분석 및 의사결정을 지원함으로써, 상수관망의 안정적인 운영과 유지보수 효율성 향상에 기여할 수 있을 것으로 기대된다.

To achieve competitive design, it is essential to develop an optimization method that ensures both high customer satisfaction and robustness for products with multiple criteria. While several studies have proposed optimization methods that integrate TOPSIS with Taguchi method or desirability function, no single study has yet combined all three methods into a unified optimization framework. Therefore, this study proposes an integrated optimization method that combines TOPSIS, Taguchi method and desirability function. The overall process of proposed method is based on the TOPSIS framework. To incorporate Taguchi method and desirability function into TOPSIS, we propose using desirability function for normalization, replacing the traditional vector normalization used in standard TOPSIS. In addition, Signal-to-Noise(S/N) ratios are calculated to evaluate the degree of customer satisfaction. To demonstrate the effectiveness of the proposed method, a hypothetical example is generated under specific conditions, and the resulting rankings are compared with those derived using the original TOPSIS approach. The comparison revealed that the rankings of design alternatives differed between the original TOPSIS and the proposed method. This difference is attributed to the influence of the desirability function’s threshold points, the specific type of desirability function applied (from Kano’s perspective), and the Taguchi S/N ratio used to assess satisfaction levels. These factors enabled a more nuanced evaluation of customer satisfaction and robustness, thereby validating the effectiveness of the proposed optimization method.

Betulin, a pentacyclic triterpenoid, abundantly accumulated in Inonotus obliquus (chaga mushroom), exhibits strong anti-inflammatory, antioxidant, anticancer, and wound-healing properties. However, its extraction remains challenging due to its poor solubility and thermal sensitivity. In this study, we optimized ultrasound-assisted extraction (UAE) using response surface methodology (RSM) to maximize simultaneous betulin and antioxidant compound recovery from I. obliquus. We evaluated three extraction variables (i.e., time, temperature, and ethanol concentration) using a three-factor, five-level design. All quadratic models were significant (p < 0.05), with R² values ranging from 0.83 to 0.93 and prediction errors remaining below 5 %, thereby confirming strong model reliability. Multi-response optimization using a superimposed response plot identified 92.08 % ethanol, 42.56 min, and 62.19 °C as a narrow optimal region, in which all responses simultaneously met the desired criteria. Under these conditions, extraction was predicted to yield high phenolic content (2.58 mg GAE/g DM), increased flavonoid levels (0.57 mg QE/ g DM), strong DPPH radical-scavenging activity (87.49 % DSA), and a betulin content of 2.00 mg/g DM. In contrast, low ethanol concentrations, excessive heating, or prolonged extraction times resulted in reduced yields due to the oxidative or thermal degradation of the bioactive constituents. Overall, the optimized extraction conditions emphasize the importance of controlling solvent polarity and balancing the temperature and time parameters to prevent thermolabile compound decomposition. These results provide a reproducible and eco-efficient framework for large-scale antioxidant constituent extraction from I. obliquus.

In laser powder bed fusion (L-PBF), a metal powder–based additive manufacturing process, pure titanium powders rely on expensive gas-atomized spherical powders, which poses a significant limitation of material cost. In contrast, non-spherical titanium powders are more cost-effective but their application in L-PBF is restricted their use due to poor flow property and high oxygen content. In this study, a powder mixing strategy with spherical titanium and hydrophobic SiO2 nanoparticle is proposed to improve the flowability and process stability of non-spherical Ti powders. After evaluating flow properties at various mixing ratios, a spherical-to-non-spherical Ti ratio of 4:6 was selected, with SiO2 nanoparticles added during mixing. The uniform distribution of oxide nanoparticles on the powder surfaces was confirmed by SEM and EDS. A maximum relative density of 99.7% was shown by specimens made with L-PBF under various processing parameters. The specimens obtained a tensile strength of 762.6 ± 3.8 MPa and an elongation of 22.1 ± 0.7% at a volumetric energy density of 71.4 J/mm³. This study demonstrates the application of low-cost non-spherical Ti powders in L-PBF is feasible and presents an effective way to simultaneously increase process stability and economic efficiency in titanium additive manufacturing.

영구자석 선형 전동기인 VCM(Voice coil motor)은 직접 구동 방식의 액츄에이터로 기어나 변속장치가 필요 없어 높은 정밀도 를 가지고 구조적인 특성상 기계적 마찰이 적어 소음이 발생하지 않는 장점을 가지고 있다. 아울러 회전운동을 직선 운동으로 변환하기 위한 별도의 장치가 필요하지 않고, 구동부가 가벼워 응답속도가 빠른 특징이 있다. 본 연구에서는 이러한 VCM을 다양한 산업 분야에 적용하기 위한 기초연구로 VCM의 속도제어를 위해 PSO(Pariticle swarm optimization) 기법을 적용하여 제어기의 유용성 평가를 위한 수 치 시뮬레이션을 수행하였다. 제어계는 전류와 속도 제어를 위한 이중 루프로 구성하였고, 각각의 제어 루프에는 PI 제어기를 적용하여 속도 목표치에 추종하는 출력값을 얻기 위한 제어기를 설계하였다. 제어기 파라미터 추정에는 PSO기법을 적용하였고, 제어기의 유용성 을 검증하기 위해 주파수 영역에서의 모델매칭기법을 적용한 제어 기법과의 제어 결과를 비교하였다. 두 가지 제어 기법은 MATLAB을 이용하여 수치 시뮬레이션을 수행했고, 제어 결과는 IAEU(Integral of absolute error units) 평가 지수를 이용하여 비교하였다. 수치 시뮬레 이션 결과 제안한 제어 기법의 유용성을 확인할 수 있었다.

본 연구에서는 고속선 선형설계의 효율성과 재현성을 향상시키기 위하여 선형 최적설계 자동화 기법을 제안하였다. 고속선에 서는 조파저항의 영향이 크고, 선형의 미세한 형상 변화가 저항 성능에 비선형적으로 작용해 경험 기반 설계에 한계가 있으므로, 이를 개 선하고자 다중단계 최적화와 ADAMS 알고리즘을 적용하여 복잡한 설계공간에서도 안정적인 탐색과 수렴성을 확보하고자 하였다. 선형 변경은 가우시안 구적법으로 국부 변형을 매끄럽게 제어하고자 하였으며, 목적함수인 조파저항을 구하기 위하여 포텐셜 기반 패널법을 적용하였다. 또한 민감도 분석을 통해 설계변수를 체계적으로 선정하고 변수 범위를 합리적으로 설정함으로써 비현실적 선형 생성과 최 적해 발산을 방지했다. R/V Athena 선형(Fn=0.45) 적용 결과, 배수량 변화는 거의 없으면서 조파저항은 유의미하게 감소했고, 최적화 전 과 정에서 선형의 기하학적 안정성도 확인되었다.

This study of a high-entropy alloy (HEA) explored two strategies to simultaneously satisfy two mechanical properties, ultimate tensile strength (UTS) and total elongation. The first strategy used inverse design based on a conditional variational autoencoder (CVAE), and the second employed multi-objective Bayesian optimization. Using a dataset of 501 literature-based HEAs, three models were trained with alloy composition and experimental conditions as inputs. Among these, extreme gradient boosting (XGBoost) exhibited the highest predictive performance for both properties and was selected as the final prediction model. CVAE was employed to generate 1,000 new samples from the latent space under the condition that both UTS and total elongation exceeded their mean values. Of these, 310 physically feasible compositions were validated using the XGBoost model, and approximately 17.7 % satisfied the target properties. Next, expected hypervolume improvement (EHVI)-based Bayesian optimization, beginning with 130 initial compositions that demonstrated superior properties, proposed five recommended candidates. These samples were found to differ in compositional characteristics from the existing dataset, which can be interpreted as exploration driven by the uncertainty of the probabilistic machine learning model. The candidate compositions generated by both methods were predicted by the XGBoost model to have the potential to achieve the target properties.

식품매개 감염은 여전히 세계 공중보건의 중대한 위협 이다. 특히 저산성 통조림 및 레토르트 제품에서 내열성 포자를 형성하는 Clostridium botulinum에 의해 부각되며, 해당 미생물의 생장·독소 생성 가능성을 확실히 차단하는 열처리 공정 설계가 필수적이다. 증기-공기혼합 레토르트 는 과압 상태에서 증기와 공기를 혼합하여 가열하는 방식 으로, 공기의 낮은 열전달계수로 인해 ‘콜드 스팟(cold spot)’이 형성될 위험이 있다. 따라서, 본 연구는 증기-공 기혼합(air-steam) 레토르트의 공정 최적화를 위해 95oC 및 121oC 조건에서 다지점(대차 상·중·하부 12지점/트레이별 5구간)으로 정량 평가하고, 적재밀도(12, 18, 28개), 스팀 공급량(100, 90, 80%), 가압(0.3-0.7 및 1.3-1.7 kgf/cm2)이 균일가열성과 살균값(F₀)에 미치는 영향을 분석하였다. 기 준 온도계 대비 최대 편차는 ΔT=1.1oC로 IFTPS 허용범위 이내였으나, 냉점(cold spot)은 일관되게 하부(D3_d)에서 확인되었고, 과적재(28개) 시 CUT 지연과 온도편차 확대 가 발생하였다. 스팀공급 저하(특히 80%)와 저가압(0.3 또 는 1.3 kgf/cm2)은 목표온도 미도달·분산 증가를 야기했으 며, 이는 냉점의 F₀ 유의 저하로 연결되었다(예: 121oC에 서 스팀 100% 대비 80% 조건의 D3_d F₀ 16.729.01). 반면, 충분한 스팀품질·환기(venting)와 적정 가압(1.5-1.7 kgf/cm²) 유지 시 공간적 균일성과 목표 F₀ 확보가 용이하였다. 결과적으로 레토르트 운전의 핵심 관리포인트는 적 정 적재·트레이 통기성 확보, 주증기 공급능력 및 노즐 스 케일 관리, 벤팅·순환 성능 검증, 공정단계별 정밀 압력제 어이며, HD에서 HP 순의 검증체계를 통해 냉점 기준으 로 과살균을 최소화하면서 규제수준의 상업적 멸균을 보 장할 수 있음을 제시한다. 본 연구는 산업현장에서 적용 가능한 운영 프로토콜을 제안함으로써 레토르트 열살균 공정의 품질·안전 관리에 실증적 근거를 제공한다.

The slow cathodic oxygen reduction rate (ORR) of microbial fuel cells (MFCs) is still one of the main bottlenecks in its industrialization. As an ORR catalyst, metal oxides are expected to significantly enhance ORR efficiency by providing active sites, regulating reaction pathways, and enhancing stability. In this paper, four bimetallic oxide catalysts, CuO/Co3O4, CuO/ MnO2, CuO/NiO, and CuO/Fe2O3, were synthesized by sol–gel method, and their structural characteristics were characterized. The results showed that CuO/Co3O4 exhibited the largest specific surface area and optimized pore structure, and the synergistic effect of Cu and Co significantly improved the electrochemical performance. As the cathode catalyst of MFCs, CuO/Co3O4 shows high ORR catalytic activity, low charge transfer resistance, and good stability. In MFCs application, CuO/ Co3O4 catalyst achieved the maximum power density of 227 mW m− 2. In the five-cycle test, the output voltage is stable at about 240 mV, and the COD removal rate reaches 91.9%, which shows great application potential in wastewater treatment.

The loss of soil available nutrients may affect soil quality and crop growth. Biochar can form a multi-level fixed network because of its rich pore structure and surface functional groups, which can effectively fix available nutrients in soil and maintain nutrient utilization rate. Because it is difficult to directly prepare biochar materials with good adsorption characteristics through experimental results. This study employed an XGBoost machine learning prediction model to determine the optimal nutrient-rich biochar preparation conditions. The R2 value ranged from 0.97 to 0.99. The results indicated that specific surface area was the primary factor influencing ammonium nitrogen adsorption, with a feature importance of 56.13%. Production conditions (hydrothermal temperature and time) significantly affected the adsorption of nitrate nitrogen and available phosphorus, with feature importances of 75.91% and 81.54%, respectively. Mean pore diameter was negatively correlated with potassium ion adsorption characteristics. Biochar prepared under hydrothermal conditions at 202.50–251.25 °C for 3 h exhibited favorable adsorption characteristics for multiple soil available nutrients. This study provides new insights into biochar’s application in the field of soil nutrient adsorption through data analysis. It is helpful to avoid the waste in the process of energy utilization from biomass to biochar.

The rapid expansion of the fast fashion industry has led to a dramatic increase in textile waste, posing significant environmental and systemic challenges. Although approximately 95% of discarded clothing is technically recyclable, current recycling system remains inefficient due to fragmented collection, manual sorting, limited recycling capabilities, and a lack of integrated data management. This study investigates the structural limitations of Korea’s waste clothing recycling system and proposes optimization strategies grounded in circular economy principles. These strategies, if implemented, have the potential to significantly improve the efficiency and effectiveness of Korea’s textile waste recycling system. Through a comparative analysis of international models― including government-led Extended Producer Responsibility (EPR) systems, digital platform-based collection services, and brand-driven recycling initiatives―the study identifies key bottlenecks in Korea’s current system. The findings highlight the need for a unified and monitored collection infrastructure, the deployment of AI-based automated sorting technologies, and the development of fiber-to-fiber (F2F) recycling processes supported by standardized classification codes and centralized databases. Furthermore, the study emphasizes the importance of real-time data integration across all stages of the recycling chain to enable transparent tracking and performance evaluation. Drawing on successful PET bottle recycling cases, the research outlines a roadmap for transitioning Korea’s textile waste management to a scalable, sustainable circular economy. The study concludes by calling for robust institutional support, legal clarity, and most importantly, cross-sector collaboration. This collaboration is crucial to ensure effective implementation of EPR and long-term resource circulation, and it will require the collective efforts of environmental policymakers, waste management professionals, industry stakeholders, and researchers.

Camellia japonica L. is highly valued for its ornamental and industrial applications. However, existing limitations in conventional seed and cutting propagation necessitate the development of a stable and efficient mass propagation system. This study systemically optimized each critical stage of in vitro culture—including shoot and root development, multiple shoot induction, rooting, and acclimatization —and quantitatively assessed the overall efficiency using integrated indices. Shoot growth was most vigorous on Woody Plant Medium (WPM) without the addition of indole-3-butyric acid (IBA), while root development was notably promoted by Murashige and Skoog (MS) medium supplemented with IBA. The highest number of multiple shoots was produced using basal explants cultured on MS medium containing 0.5 mg/L thidiazuron (TDZ), yielding an average of 2.67 shoots per explant. Optimal root induction was observed following a 15-min pulse treatment with 500 mg/L IBA (producing 24,33 roots), whereas the root elongation was maximized by a 5-min treatment with 1000 mg/L IBA (2.10 cm). Acclimatization successfully resulted in 100% survival in both tested substrates (A: peat moss, perlite, and cocopeat mixed in a 3:1:1 ratio; B: peat moss, perlite, and vermiculite mixed in a 1:1:1 ratio), with substrate B promoting a greater increase in plant height. Normalized growth parameters were averaged to calculate the Camellia Micropropagation Index (CMI). Integrated analysis identified the most efficient treatments as: WPM without IBA (shoot growth), MS with IBA (root growth), MS + 0.5 mg/L TDZ with basal explants (multiple shoots), 1000 mg/L IBA for 5 min (rooting), and substrate B (acclimatization). Despite these optimal conditions, considerable variation within treatments suggests that further fine-tuning or long-term evaluation is necessary to improve reliability. These findings provide a robust guideline for establishing a successful in vitro mass micropropagation system for C. japonica.

본 논문에서는 기어 소음 및 진동 저감을 위해 베이지안 최적화 기법을 이용하여 기어 전달오차를 최소화하는 최적설계 기법을 제 안하였다. 이는 기어의 형상에 큰 영향을 받는다. 기존의 ISO 6336과 AGMA 2101 기반의 전달오차 해석은 기어 형상과 물림률을 충 분히 반영하지 못하며, 유한요소해석은 정확도가 높으나 세밀한 요소망과 접촉 비선형 해석으로 인해 계산 비용이 매우 크다는 한계 가 있다. 본 연구에서는 물림률을 고려한 유한요소 간소화모델을 구성하여 비교적 적은 샘플로 정확한 확률 모델을 만들 수 있는 가우 시안 프로세스 기반 대리모델과, 여기서 얻어진 기대치 개선값을 바탕으로 새로운 최적점을 탐색하였다. 제안된 기법의 결과를 유전 자 알고리즘 기법과 비교하여 유효성을 검증하였다.