• Title/Summary/Keyword: industrial column

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Recovery of Trichloroethylene Removal Efficiency through Short-term Toluene Feeding in a Biofilter Enriched with Pseudomonas putida F1

  • Jung In-Gyung;Park Ok-Hyun;Woo Hae-Jin;Park Chang-Ho
    • Biotechnology and Bioprocess Engineering:BBE
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    • v.10 no.1
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    • pp.34-39
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    • 2005
  • Trichloroethylene (TCE) is an environmental contaminant provoking genetic mutation and damages to liver and central nerve system even at low concentrations. A practical scheme is reported using toluene as a primary substrate to revitalize the biofilter column for an extended period of TCE degradation. The rate of trichloroethylene (TCE) degradation by Pseudomonas putida F1 at $25^{\circ}C$ decreased exponentially with time, without toluene feeding to a biofilter column ($11\;cm\;I.D.{\times}95\;cm$ height). The rate of decrease was 2.5 times faster at a TCE concentration of $970\;{\mu}g/L$ compared to a TCE concentration of $110\;{\mu}g/L$. The TCE itself was not toxic to the cells, but the metabolic intermediates of the TCE degradation were apparently responsible for the decrease in the TCE degradation rate. A short-term (2 h) supply of toluene ($2,200\;{\mu}g/L$) at an empty bed residence time (EBRT) of 6.4 min recovered the relative column activity by $43\%$ when the TCE removal efficiency at the time of toluene feeding was $58\%$. The recovery of the TCE removal efficiency increased at higher incoming toluene concentrations and longer toluene supply durations according to the Monod type of kinetic expressions. A longer duration ($1.4{\sim}2.4$ times) of toluene supply increased the recovery of the TCE removal efficiency by $20\%$ for the same toluene load.

Computer Simulation and Optimization Study on the Pressure-Swing Distillation of 1-propanol-benzene Mixture (1-프로판올과 벤젠 혼합물의 압력변환 증류공정을 통한 전산모사 및 공정 최적화)

  • Park, Hoey Kyung;Cho, Jungho
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.6
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    • pp.88-97
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    • 2018
  • Computer modeling and optimization works have been performed for the separation of the binary mixture of 1-propanol and benzene through a pressure-swing distillation. PRO/II with PRIVISION V10.0 at Schneider Electric company and NRTL liquid activity coefficient model were utilized. The sum of the total reboiler heat duties of the low-high and high-low pressure column configurations were compared. To minimize the utility consumptions, low column, and high column to obtain pure benzene at the top, the number of theoretical stages and optimal feed tray locations for each distillation column were determined and the reflux ratios for each distillation column were also adjusted. As a result of the optimization works, the sum of the total reboiler heat duties for the high-low and low-high pressure configurations were $3.10{\times}10^6kcal/h$ and $2.75{\times}10^6kcal/h$, respectively. In the case where heat integration was applied to low-high pressure configurations, 57.36 % of the total reboiler heat duties could be saved compared to the high-low pressure configurations.

Remote Health Monitoring of Parkinson's Disease Severity Using Signomial Regression Model (파킨슨병 원격 진단을 위한 Signomial 회귀 모형)

  • Jeong, Young-Seon;Lee, Chung-Mok;Kim, Nor-Man;Lee, Kyung-Sik
    • IE interfaces
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    • v.23 no.4
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    • pp.365-371
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    • 2010
  • In this study, we propose a novel remote health monitoring system to accurately predict Parkinson's disease severity using a signomial regression method. In order to characterize the Parkinson's disease severity, sixteen biomedical voice measurements associated with symptoms of the Parkinson's disease, are used to develop the telemonitoring model for early detection of the Parkinson's disease. The proposed approach could be utilized for not only prediction purposes, but also interpretation purposes in practice, providing an explicit description of the resulting function in the original input space. Compared to the accuracy performance with the existing methods, the proposed algorithm produces less error rate for predicting Parkinson's disease severity.

Studies on the Separation of Immunoglobulin and Immunological Response from Korean Native Cattle (한우초유중 Ig의 분리 ${\cdot}$ 정제 및 면역 반응에 관한 연구)

  • Baick, Seung-Cheon;Kim, Yong-Hwi;Shin, Je-Ho;Yu, Je-Hyeon
    • Journal of Dairy Science and Biotechnology
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    • v.15 no.1
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    • pp.1-9
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    • 1997
  • This study was conducted to efficiently separate the Ig from Korean native cattle colostrum and to utilize them as an immunogen for the production of antibodies aginst rabbit. The results obtained were as follows : 1. About 84% of Ig G could be separated from Korean native cattle colostrum by·gel filtration using Superose 12 column on HPLC. The separation profile of Korean native cattle colostral immunoglobulin was similar that of Holstein colostral Ig. 2. Separation of Korean native cattle colostral Ig by anion exchange chromatography using Mono Q column on HPLC was poor resolution chromatographic pattern. 3. Hi-Trap Protein G column showed better results than the Protein A Sepharose CL-4B column in the Ig G binding capacity from Korean native cattle colostral Ig. 4. Protein G Sepharose Fast Flow system resulted in higher Ig g binding capacity as the industrial size scale-up approach. 5. Sufficient titer reaction of antibody to Korean native cattle colostral Ig G was confirmed by ELISA.

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Determination of Phthalate Metabolites in Human Serum and Urine as Biomarkers for Phthalate Exposure Using Column-Switching LC-MS/MS

  • Jeong, Jee-Yeon;Lee, Ji-Hyun;Kim, Eun-Young;Kim, Pan-Gyi;Kho, Young-Lim
    • Safety and Health at Work
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    • v.2 no.1
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    • pp.57-64
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    • 2011
  • Objectives: Although phthalates like dibutyl phthalate (DBP) and di-2-ethylhexyl phthalate (DEHP) are commonly used as plasticizers and their metabolites are especially suspected of reproductive toxicity, little is known about occupational exposure to those phthalates. The aim of this study was to assess the utility of measuring the metabolite concentrations of DBP and DEHP in serum and urine samples as an indicator of occupational exposure to those phthalates. Methods: Phthalate metabolites were analyzed by using column-switching high-performance liquid chromatography tandem mass spectrometry (LC-MS/MS). Results: We detected phthalate metabolites in serum and urine matrices at approximately 10-fold lower than the limit of detection of those metabolites in the same matrix by LC-MS/MS without column switching, which was sufficient to evaluate concentrations of phthalate metabolites for industrial workers and the general population. Conclusion: The accuracy and precision of the analytical method indicate that urinary metabolite determination can be a more acceptable biomarker for studying phthalate exposure and adverse health outcomes.

Shear behavior of RC interior joints with beams of different depths under cyclic loading

  • Xi, Kailin;Xing, Guohua;Wu, Tao;Liu, Boquan
    • Earthquakes and Structures
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    • v.15 no.2
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    • pp.145-153
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    • 2018
  • Extensive reinforced concrete interior beam-column joints with beams of different depths have been used in large industrial buildings and tall building structures under the demand of craft or function. The seismic behavior of the joint, particularly the relationship between deformation and strength in the core region of these eccentric reinforced concrete beam-column joints, has rarely been investigated. This paper performed a theoretical study on the effects of geometric features on the shear strength of the reinforced concrete interior beam-column joints with beams of different depths, which was critical factor in seismic behavior. A new model was developed to analyze the relationship between the shear strength and deformation based on the Equivalent Strut Mechanism (ESM), which combined the truss model and the diagonal strut model. Additionally, this paper developed a simplified calculation method to estimate the shear strength of these type eccentric joints. The accuracy of the model was verified as the modifying analysis data fitted to the test results, which was a loading test of 6 eccentric joints conducted previously.

A Study on Compressive Strength of Centrally-Loaded Steel Columns at Elevated Temperatures (중심축 하중을 받는 고온상태 강재기둥의 압축강도에 관한 연구)

  • Yoon, Jong Hwi;Lee, Chy Hyoung;Yoon, Sung Kee
    • Journal of Korean Society of Steel Construction
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    • v.28 no.4
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    • pp.253-261
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    • 2016
  • In order to evaluate compressive strength of centrally-loaded steel column at elevated temperature, new FE analysis techniques and assumptions of model were applied in this study. It also includes comparison with the existing studies, and a new design equation for centrally-loaded steel column at elevated temperature was proposed. The proposed equation was the most accurate of the three design equations(EC3, AISC, proposed equation) when comparing with the coefficient of determination on the simulated results and test results.

Purification of Cephalosporin C Produced by Cephalosporium acrernoniurn (Cephalosporium acremonium 변이주가 생성하는 Cephalosporin C의 정제)

  • 이헌주;손영선;안동호;김현수;현형환
    • Microbiology and Biotechnology Letters
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    • v.20 no.2
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    • pp.178-182
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    • 1992
  • For an industrial-scale purification and production of cephalosporin C from a culture broth of Ceplzalos#mium nmemonium CSA-2.8A3 mutant, ultrafiltration, column chromatography, reverse osmosis, and spray drying were empolyed. Above 90% of yield and high purity of cephalosporin C were obtained through WA-30, HP-20, XAD-2000 and SK-1B column chromatographies. Especially, in the tendom operation of the columns, the recovery yield was increased up to 96%. The purified cephalosporin C was stable at $4^{\circ}C$ and in acidic condition, while it was unstable at room temperature and in alkaline condition at pH above 8.0. Cephalosporin C powder or a final product prepared by spray drying contained 85.554 of sodium cephalosporin C, 6.3%' of water, 4.63% of free $Na^+$ ions. and traces of metal ions.

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Assessing pollutants' migration through saturated soil column

  • Smita Bhushan Patil;Hemant Sharad Chore;Vishwas Abhimanyu Sawant
    • Membrane and Water Treatment
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    • v.14 no.2
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    • pp.95-106
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    • 2023
  • In the developing country like India, groundwater is the main sources for household, irrigation and industrial use. Its contamination poses hydro-geological and environmental concern. The hazardous waste sites such as landfills can lead to contamination of ground water. The contaminants existing at such sites can eventually find ingress down through the soil and into the groundwater in case of leakage. It is necessary to understand the process of migration of pollutants through sub-surface porous medium for avoiding health risks. On this backdrop, the present paper investigates the behavior of pollutants' migration through porous media. The laboratory experiments were carried out on a soil-column model that represents porous media. Two different types of soils (standard sand and red soil) were considered as the media. Further, two different solutes, i.e., non-reactive and reactive, were used. The experimental results are simulated through numerical modeling. The percentage variation in the experimental and numerical results is found to be in the range of 0.75- 11.23 % and 0.84 - 1.26% in case of standard sand and red soil, respectively. While a close agreement is observed in most of the breakthrough curves obtained experimentally and numerically, good agreement is seen in either result in one case.

Prediction of Distillation Column Temperature Using Machine Learning and Data Preprocessing (머신 러닝과 데이터 전처리를 활용한 증류탑 온도 예측)

  • Lee, Yechan;Choi, Yeongryeol;Cho, Hyungtae;Kim, Junghwan
    • Korean Chemical Engineering Research
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    • v.59 no.2
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    • pp.191-199
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    • 2021
  • A distillation column, which is a main facility of the chemical process, separates the desired product from a mixture by using the difference of boiling points. The distillation process requires the optimization and the prediction of operation because it consumes much energy. The target process of this study is difficult to operate efficiently because the composition of feed flow is not steady according to the supplier. To deal with this problem, we could develop a data-driven model to predict operating conditions. However, data preprocessing is essential to improve the predictive performance of the model because the raw data contains outlier and noise. In this study, after optimizing the predictive model based long-short term memory (LSTM) and Random forest (RF), we used a low-pass filter and one-class support vector machine for data preprocessing and compared predictive performance according to the method and range of the preprocessing. The performance of the predictive model and the effect of the preprocessing is compared by using R2 and RMSE. In the case of LSTM, R2 increased from 0.791 to 0.977 by 23.5%, and RMSE decreased from 0.132 to 0.029 by 78.0%. In the case of RF, R2 increased from 0.767 to 0.938 by 22.3%, and RMSE decreased from 0.140 to 0.050 by 64.3%.