생물학적 탈질반응에서 하폐수의 C/N비가 충분하지 않거나 유출수의 질소농도를 낮은 수준까지 처리하는 것을 목표로 할 경우에는 외부탄소원의 주입이 요구된다. 본 연구에서 연속회분식반응조의 질산화 반응특성을 잘 파악할 수 있고 무엇보다도 탈질반응의 대상물질인 질산염의 양을 추정할 수 있는 호흡률을 활용하여 탈질공정을 제어하고자 하였다. 호흡률을 측정하여 질산화에 의해 생성된 질산염을 추정할 수 있었으며, 추정치는 반응조내 질산염의 약 90% 정도에 해당되어 비교적 정확하였다. 추정한 질산염의 양에 상응하여 외부탄소원으로 초산염의 주입량을 조절하였으며, 운전결과 질산성 질소당 요구되는 COD는 4.25 mg COD/mg N이 적절하였다. 또한 초산염의 주입에 따라 미생물의 세포내에 유기물로 축적되고 이를 이용한 성장에서 호흡률의 변화가 나타나는 것을 파악할 수 있었다. 연구결과 연속회분식반응조에서 호흡률을 활용하여 초산염의 주입량을 조절함으로써 매우 엄격한 수준의 유출수 질소농도까지 효과적으로 처리할 수 있었다.

This study investigates the thermal expansion characteristics of hydroxyl-terminated polybutadiene(HTPB) based solid propellants, focusing on batch-to-batch variability and accelerated aging effects. Coefficient of thermal expansion(CTE) measurements were conducted using thermomechanical analyzer(TMA) on samples from different manufacturing batches and specimens aged at various temperatures for different durations. Results indicate variations in CTE values between batches, highlighting the significance of manufacturing process control. Accelerated aging experiments reveal minimal systematic changes in CTE, suggesting stability of thermal expansion properties under short-term thermal stress. The overall distribution of CTE values shows concentration within a specific range, indicating consistency in thermal expansion characteristics. These findings provide insights into the thermal behavior of HTPB-based solid propellants, contributing to improved missile design and lifecycle prediction models.

The intensive development of the petrochemical industry globally reflects the necessity of an efficient approach for oily sludge and wastewater. Hence, for the first time, the current study utilized magnetic waxy diesel sludge (MWOPS) to synthesize activated carbon coated with TiO2 particles for the removal of total petroleum hydrocarbons (TPH) and COD from oily petroleum wastewater (OPW). The photocatalyst was characterized using CHNOS, elemental analysis was performed using X-ray fluorescence spectroscopy (XRF), field emission scanning electron microscope (FESEM), high-resolution transmission electron microscope (HR-TEM), X-ray diffraction analysis (XRD), Fourier transform infrared spectrometer (FTIR), Raman, energy dispersive X-ray spectroscopy (EDX), X-ray photoelectron spectroscopy (XPS), MAP thermo-gravimetric analysis/ differential thermo-gravimetric (TGA–DTG), Brunauer–Emmett–Teller (BET), diffuse reflectance spectroscopy (DRS), and vibrating sample magnetometer (VSM). The optimization of synthesized highly porous AC/Fe3O4/TiO2 photocatalyst was conducted considering the impacts of pH, temperature, photocatalyst dosage, and UVA6W exposure time. The results demonstrated the high capacity of the MWOPS with inherent magnetic potential and desired carbon content for the removal of 91% and 93% of TPH and COD, respectively. The optimum conditions for the OPW treatment were obtained at pH 6.5, photocatalyst dosage of 250 mg, temperature of 35 °C, and UVA6W exposure time of 67.5 min. Moreover, the isotherm/kinetic modeling illustrated simultaneous physisorption and chemisorption on heterogeneous and multilayer surfaces. Notably, the adsorption efficiency of the AC/Fe3O4/TiO2 decreased by 4% after five adsorption/desorption cycles. Accordingly, the application of a well-designed pioneering photocatalyst from the MWOPS provides a cost-effective approach for industry manufacturers for oily wastewater treatment.

This study pursues to solve a batch of nonlinear parameter estimation (NPE) problems where a model interpreting the independent and the dependent variables is given and fixed but corresponding data sets vary. Specifically, we assume that the model does not have an explicit form and the discrepancy between a value from a data set and a corresponding value from the model is unknown. Due to the complexity of the problem, one may prefer to use heuristic algorithms rather than gradient-based algorithms, but the performance of the heuristic algorithms depends on their initial settings. In this study, we suggest two schemes to improve the performance of heuristic algorithms to solve the target problem. Most of all, we apply a Bayesian optimization to find the best parameters of the heuristic algorithm for solving the first NPE problem of the batch and apply the parameters of the heuristic algorithm for solving other NPE problems. Besides, we save a list of simulation outputs obtained from the Bayesian optimization and then use the list to construct the initial population set of the heuristic algorithm. The suggested schemes were tested in two simulation studies and were applied to a real example of measuring the critical dimensions of a 2-dimensional high-aspect-ratio structure of a wafer in semiconductor manufacturing.

The important thing in the field of deep learning is to find out the appropriate hyper-parameter for image classification. In this study, the main objective is to investigate the performance of various hyper-parameters in a convolutional neural network model based on the image classification problem. The dataset was obtained from the Kaggle dataset. The experiment was conducted through different hyper-parameters. For this proposal, Stochastic Gradient Descent without momentum (SGD), Adaptive Moment Estimation (Adam), Adagrad, Adamax optimizer, and the number of batch sizes (16, 32, 64, 120), and the number of epochs (50, 100, 150) were considered as hyper-parameters to determine the losses and accuracy of a model. In addition, Binary Cross-entropy Loss Function (BCLF) was used for evaluating the performance of a model. In this study, the VGG16 convolutional neural network was used for image classification. Empirical results demonstrated that a model had minimum losses obtain by Adagrad optimizer in the case of 16 batch sizes and 50 epochs. In addition, the SGD with a 32 batch sizes and 150 epochs and the Adam with a 64 batch sizes and 50 epochs had the best performance based on the loss value during the training process. Interestingly, the accuracy was higher while performing the Adagrad and Adamax optimizer with a 120 batch sizes and 150 epochs. In this study, the Adagrad optimizer with a 120 batch sizes and 150 epochs performed slightly better among those optimizers. In addition, an increasing number of epochs can improve the performance of accuracy. It can help to create a broader scope for further experiments on several datasets to perceive the suitable hyper-parameters for the convolutional neural network. Dataset: https://www.kaggle.com/c/dogs-vs-cats/data

Many small and medium-sized manufacturing companies process various product types to respond different customer orders in a single production line. To improve their productivity, they often apply batch processing while considering various product types, constraints on batch sizes and setups, and due date of each order. This study introduces a batch scheduling heuristic for a production line with multiple product types and different due dates of each order. As the process times vary due to the different batch sizes and product types, a recursive equation is developed based on a flow line model to obtain the upper bound on the completion times with less computational complexity than full computation. The batch scheduling algorithm combines and schedules the orders with same product types into a batch to improve productivity, but within the constraints to match the due dates of the orders. The algorithm incorporates simple and intuitive principles for the purpose of being applied to small and medium companies. To test the algorithm, two case studies are introduced; a high pressure coolant (HPC) manufacturing line and a press process at a plate-type heat exchanger manufacturer. From the case studies, the developed algorithm provides significant improvements in setup frequency and thus convenience of workers and productivity, without violating due dates of each order.

As aeration is an energy-intensive process, its control has become more important to save energy and to meet strict effluent limits. In this study, predictive aeration control based on the respirometric method has been applied to the sequencing batch reactor (SBR) process. The variation of the respiration rate by nitrification was great and obvious, so it could be a very useful parameter for the predictive aeration control. The maximum respiration rate due to nitrification was about 60 mg O2/L‧h and the maximum specific nitrification rate was about 7.5 mg N/g MLVSS‧h. The aeration time of the following cycle of the SBR was daily adjusted in proportion to that which was previously determined based on the sudden decrease of respiration rate at the end of nitrification in the respirometer. The aeration time required for nitrification could be effectively predicted and it was closely related to influent nitrogen loadings. By the predictive aeration control the aerobic period of the SBR has been optimized, and energy saving and enhanced nitrogen removal could be obtained.

Recent focus on wastewater treatment includes energy-saving and renewable energy generation for energy-independence of water infrastructures. Aeration and pumping in biological wastewater removal processes account for nearly 30-60% of the total electricity cost in real wastewater treatment plants. In this study, the performance and microbial characteristics were investigated in sequencing batch reactor under typical oxygen and oxygen limited condition. Under typical DO (7.55±0.99 mg/L) and low DO (0.23±0.08 mg/L) conditions, COD removal was stable over 91 % during SBR operation. Ammonia removal efficiency was reduced from 95.6 % to 89.2 % when DO concentration was dropped sharply. Phosphorus removal efficiency also reached 77% at oxygen-limited condition. The results indicated that removal efficiency both ammonia and phosphorus was influenced by DO condition. Microbial analysis revealed that Proteobacteria and Bacteroidetes at phylum level was dominant in typical DO and low DO conditions and DO concentration did not much affect phylum distribution. Population decrease of genera of nitrifying bacteria(Dokdonella) and Dechloromonas spp. affect removal efficiency of nitrogen and phosphorus at low DO condition.

This paper develops an algorithm to determine the batch size of the batch process in real time for improving production and efficient control of production system with multiple processes and batch processes. It is so important to find the batch size of the batch process, because the variability arising from the batch process in the production system affects the capacity of the production. Specifically, batch size could change system efficiency such as throughput, WIP (Work In Process) in production system, batch formation time and so on. In order to improve the system variability and productivity, real time batch size determined by considering the preparation time and batch formation time according to the number of operation of the batch process. The purpose of the study is to control the WIP by applying CONWIP production system method in the production line and implements an algorithm for a real time batch size decision in a batch process that requires long work preparation time and affects system efficiency. In order to verify the efficiency of the developed algorithm that determine the batch size in a real time, an existed production system with fixed the batch size will be implemented first and determines that batch size in real time considering WIP in queue and average lead time in the current system. To comparing the efficiency of a system with a fixed batch size and a system that determines a batch size in real time, the results are analyzed using three evaluation indexes of lead time, throughput, and average WIP of the queue.

The respirometric technique has been used to analyze the nitrification process in a sequencing batch reactor(SBR) treating municipal wastewater. Especially the profile of the respiration rate very well expressed the reaction characteristics of nitrification. As the nitrification process required a significant amount of oxygen for nitrogen oxidation, the respiration rate due to nitrification was high. The maximum nitrification respiration rate, which was about 50 mg O2/L･h under the period of sufficient nitrification, was related directly to the nitrification reaction rate and showed the nitrifiers activity. The growth rate of nitrifiers is the most critical parameter in the design of the biological nutrient removal systems. On the basis of nitrification kinetics, the maximum specific growth rate of nitrifiers in the SBR was estimated as 0.91 d-1 at 20℃, and the active biomass of nitrifiers was calculated as 23 mg VSS/L and it was about 2% of total biomass.

A사는 발전 플랜트, 오수처리장, 취수, 정수, 배수장, Oil Plant 등 국가 기간 산업현장에서 사용되는 전동 액추에이터를 제조하고 있다. A사가 각 수요처별로 각기 다른 기능을 필요로 하는 Order에 대응하여 제품을 생산하고자 기존의 A사가 적용하고 있는 생산방식인 라인로트생산방식이 가지고 있는 문제점을 파악하여 개선하고자 한다. 본 연구를 통해 시장과 고객의 요구에 유연하게 대응할 수 있도록 다품종 소량생산에 적합한 셀 생산방식으로 변경을 통하여 생산유연화와 생산성향상을 이룰 수 있었다. 이러한 개선을 통하여 다변화하는 고객의 요구에 실시간으로 대응 할 수 있음은 물론이고 생산성향상과 그에 따른 이익창출을 이뤄낼 수 있는 계기가 될 것이다. 또한 A사의 생산 작업자의 업무 능력배양에 긍정적으로 작용하여 일을 하는 재미와 이에 따른 보상의 기대치를 높일 수 있는 계기로 작용하였다.

As the sequencing batch reactor process is a time-oriented system, it has advantages of the flexibility in operation for the biological nutrient removal. Because the sequencing batch reactor is operated in a batch system, respiration rate is more sensitive and obvious than in a continuous system. The variation of respiration rate in the process well represented the characteristics of biological reactions, especially nitrification. The respiration rate dropped rapidly and greatly with the completion of nitrification, and the maximum respiration rate of nitrification showed the activity of nitrifiers. This study suggested a strategy to control the aeration of the sequencing batch reactor based on respirometry. Aeration time of the optimal aerobic period required for nitrification was daily adjusted according to the dynamics of respiration rate. The aeration time was mainly correlated with influent nitrogen loadings. The anoxic period was extended through aeration control facilitating a longer endogenous denitrification reaction time. By respirometric aeration control in the sequencing batch reactor, energy saving and process performance improvement could be achieved.

담체가 투여된 침지형 막결합 연속회분식 반응기(SMSBR)를 사용한 하수의 고도처리에서 담체가 여과성능과 제 거효율에 미치는 영향을 조사하였다. 담체는 반응기 부피 기준으로 10% 투여하였고, 담체와 분말활성탄을 첨가하지 않은 반 응기, 분말활성탄(10 g/L)만을 첨가한 반응기 및 담체와 분말활성탄을 모두 첨가한 반응기를 대조군으로 하였다. COD, T-N 및 T-P에 대한 제거효율은 담체 및 분말활성탄 첨가 유무에 따라 큰 차이가 없었다. 그러나 담체를 첨가하지 않은 경우 막간 차압(TMP)은 급격히 증가하였으나, 담체를 첨가한 경우에 막간차압은 매우 서서히 증가하였다. 담체를 투여한 SMSBR를 사 용하여 하수를 고도처리 할 때, 91일 이상의 운전기간 동안 막 세정 없이 운전이 가능하였다. 담체만을 투여한 경우, 운전 80 일 경과 이후의 COD, T-N 및 T-P 평균 제거율은 각각 95.0, 69.3% 및 51.4%이었다.

We developed leaching kinetics models and a convective mass transfer model for water soluble solid in jujube (Zizyphus jujube) fruits with hot water. Hot-water leaching process was conducted at 90°C for 100 min. The ratio of solvent (volume, mL) to solid (mass, g) was set to varied ratios of 1:6, 1:8, 1:10, and 1:12.5. The mass transfer coefficients (k) were determined based on the 1st- and 2nd-order kinetic models. The amount of solvent influenced the extraction rate and yield. A higher extraction rate and a higher yield were obtained from a lower solvent to solute ratio (1:6, 1:8, 1:10) compared to high ratio (1:12.5). This implies that an appropriate amount of solvent (i.e., water) is necessary to conduct the extraction process of jujube fruit.