• Title/Summary/Keyword: Salinity error

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Optimizatio of Processing Conditions for Smoked Eggs Aging and Pressurizing Techniques (숙성 및 가압 방식에 의한 훈제 계란의 제조 공정 최적화)

  • Kim, Jin-Gon;Hwang, Yong-Il;Kwon, Sang-Chul
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.6
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    • pp.375-380
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    • 2017
  • This study assessed the technology to minimize the discoloration to reduce the defect rate and penetrate the curing solution through the egg shells to produce quality smoked eggs that meet the preference of consumers. The discoloration refers to the defects on the colors of egg shells due to overheated smoking fluids, causing the eggs to be discarded. The manufacturing process was prepared by the manufacturer of the regular smoked egg manufacturing process. A preliminary study found that the preferred salinity of smoked eggs was 1.67~2.00% and the major processing factors have been set to maintain the optimal salinity of smoked eggs and an industrially attainable minimum defect rate below 3%. When the eggs were aged at $50^{\circ}C$ for 96 hours to produce the smoked eggs, the discoloration rate was 0%. When the circulatory dipping method was applied, 3.00% salinity was achieved after 8 hours. When the eggs were smoked at that time, the salinity was 1.67%. With a $2.07kg/cm^2$ pressure, 3.33% salinity was achieved after 4 hours and 2.00% salinity was achieved when the smoked eggs were produced. To identify the most efficient pressurizing method, 0.52, 1.55, 1.86, 2.07, 2.38, 2.58, and $3.62kg/cm^2$ were applied, the discoloration rate was 2.2% after 4 hours under a $2.07kg/cm^2$ pressure. The aging and pressurized method is considered to be the basis for reducing the manufacturing time and decreasing the rate of error during the smoked eggs process.

Design of optimal PID controller for the reverse osmosis using teacher-learner-based-optimization

  • Rathore, Natwar S.;Singh, V.P.
    • Membrane and Water Treatment
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    • v.9 no.2
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    • pp.129-136
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    • 2018
  • In this contribution, the control of multivariable reverse osmosis (RO) desalination plant using proportional-integral-derivative (PID) controllers is presented. First, feed-forward compensators are designed using simplified decoupling method and then the PID controllers are tuned for flux (flow-rate) and conductivity (salinity). The tuning of PID controllers is accomplished by minimization of the integral of squared error (ISE). The ISEs are minimized using a recently proposed algorithm named as teacher-learner-based-optimization (TLBO). TLBO algorithm is used due to being simple and being free from algorithm-specific parameters. A comparative analysis is carried out to prove the supremacy of TLBO algorithm over other state-of-art algorithms like particle swarm optimization (PSO), artificial bee colony (ABC) and differential evolution (DE). The simulation results and comparisons show that the purposed method performs better in terms of performance and can successfully be applied for tuning of PID controllers for RO desalination plants.

Analysis of the temporal stratification variation pattern in Mikawa Bay, Japan (일본 미카와만의 시간적인 성층변화 양상 분석)

  • Cho, Hong-Yeon;Cho, Bong-Sik
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.22 no.3
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    • pp.171-180
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    • 2010
  • Analysis on the temporal variation of the stratification is carried out by using the continuous water temperature and salinity data observed in the coastal monitoring buoy in Mikawa Bay, Japan. The main analysis results are as follows. The stratification pattern have an obvious and dominant 1-year period variation and the occurrence frequency (days) are exponentially decreased as the stratification intensity (SI) defined as the density difference between surface and bottom layers linearly increases. The frequency distribution function of the SI is presumably close to the log-normal function type or exponential function type. From the water temperature and salinity scatter diagram analysis, the line and loop type patterns are shown in the bottom and surface layers, respectively. In addition, the analysis of the SI estimation show that the error bound in case of using the weekly-monitoring data is about 4.45 times greater than that in case of using the continuous (daily) monitoring data.

Analysis of Hydraulic Characteristics of Yeongsan River and Estuary Using EFDC Model (EFDC-NIER 모델을 이용한 영산강 하구 물흐름 특성 분석)

  • Shin, Chang Min;Kim, Darae;Song, Yongsik
    • Journal of Korean Society on Water Environment
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    • v.35 no.6
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    • pp.580-588
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    • 2019
  • The flow of the middle and downstream of the Yeongsan River is stagnant by two weirs of Seungchon and Juksan and the estuary dam and maintained in freshwater. In this study, the Environmental Fluid Dynamics Code-National Institute of Environment Research(EFDC-NIER) model was applied to the Yeongsan River to simulate water flow, temperature, and salinity stratification. The EFDC-NIER model is an improved model which can simulate multi-functional weirs operation, multiple algal species, and the vertical movement mechanism of algal based on the EFDC model. The simulation results for the water level, water temperature, velocity, and salinity reproduced the observed values well. The mean absolute error(MAE) of the model calibration in the annual variations of the water level was 0.1-0.3 m, water temperature was 0.8-1.7 ℃, velocity was 4.5-7.1 cm/sec, and salinity was 1.5 psu, respectively. In the case of scenario simulation for the full opening of the estuary dam, the water level of the estuary dam was directly impacted by the tide so it was predicted to rise - 1.35 m to 0.2 m on average sea level. The velocity was also predicted to increase from 2.7 cm/sec to 50.8 cm/sec, and the flow rate to increase from 53 ㎥/sec to 5,322 ㎥/sec.

Modeling of Suspended Solids and Sea Surface Salinity in Hong Kong using Aqua/MODIS Satellite Images

  • Wong, Man-Sing;Lee, Kwon-Ho;Kim, Young-Joon;Nichol, Janet Elizabeth;Li, Zhangqing;Emerson, Nick
    • Korean Journal of Remote Sensing
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    • v.23 no.3
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    • pp.161-169
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    • 2007
  • A study was conducted in the Hong Kong with the aim of deriving an algorithm for the retrieval of suspended sediment (SS) and sea surface salinity (SSS) concentrations from Aqua/MODIS level 1B reflectance data with 250m and 500m spatial resolutions. 'In-situ' measurements of SS and SSS were also compared with coincident MODIS spectral reflectance measurements over the ocean surface. This is the first study of SSS modeling in Southeast Asia using earth observation satellite images. Three analysis techniques such as multiple regression, linear regression, and principal component analysis (PCA) were performed on the MODIS data and the 'in-situ' measurement datasets of the SS and SSS. Correlation coefficients by each analysis method shows that the best correlation results are multiple regression from the 500m spatial resolution MODIS images, $R^2$= 0.82 for SS and $R^2$ = 0.81 for SSS. The Root Mean Square Error (RMSE) between satellite and 'in-situ' data are 0.92mg/L for SS and 1.63psu for SSS, respectively. These suggest that 500m spatial resolution MODIS data are suitable for water quality modeling in the study area. Furthermore, the application of these models to MODIS images of the Hong Kong and Pearl River Delta (PRO) Region are able to accurately reproduce the spatial distribution map of the high turbidity with realistic SS concentrations.

A Study on Characteristics and Equivalent Circuit Model of Underwater Wireless Power Transfer System by Salinity (염도에 따른 수중 무선전력전송 시스템 특성 및 등가모델 연구)

  • Lee, Jeong-Geon;Kang, Wonshil;Ku, Hyunchul
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.29 no.11
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    • pp.851-856
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    • 2018
  • In this study, we analyze the characteristics of wireless power transfer(WPT) based on magnetic resonance in an underwater environment and propose an equivalent model suitable for underwater WPT. The proposed underwater WPT equivalent model is constructed by expanding the free-space WPT T-model reflecting characteristics change according to media. Considering the water salinity, we propose a method to extract the parameters of the proposed model based on the S parameters. To verify the proposed model, a 6.78-MHz underwater WPT system was constructed and compared with the predicted power transfer efficiency of the model. As a result, it was confirmed that the proposed model predicts the variation of characteristics with an average error of less than 3 %.

The Determination of TRC using an Electrochemical Method (II: Pt electrode) (전기화학적 방법의 TRC(Total residual chlorine) 측정 연구(II: Pt전극 이용))

  • Lee, JunCheol;Pak, DaeWon
    • Journal of Korean Society on Water Environment
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    • v.30 no.3
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    • pp.304-310
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    • 2014
  • The conventional methods for total residual chlorine such as iodometry and DPD colorimetric can cause secondary pollution due to additional agents, also have a wide error range. As for alternative, electrochemical method can measure TRC(Total residual chlorine), and is not required as additional agents, also very suitable for using the fields of ballast water because test time is relatively fast. Therefore, this study was investigated for changing charge by agitation, salt concentration, and temperature change. Charge showed differences based on changes of reduction peak with or without agitation. In contrast, TRC and charge were well correlated in constant agitation speed. As TRC and charge were analyzed with high correlations in constant salinity and temperature of ocean, thereby conductivity was firstly measured, and charge had high correlation for TRC in spite of changing salinity and temperature Pt electrode revealed high reliability ($r^2=0.960$) because it was rarely effected by TRC, On the other hand, Au electrode appeared inadequate ($r^2=0.767$) to use sensor in less than 1.0 ppm of TRC. For high accuracy and detection of TRC, Pt and Au electrodes for test time were, respectively, 14 and 22 seconds. As a result, Pt electrode was more valuable than Au electrode in terms of response time.

Prediction of Salinity of Nakdong River Estuary Using Deep Learning Algorithm (LSTM) for Time Series Analysis (시계열 분석 딥러닝 알고리즘을 적용한 낙동강 하굿둑 염분 예측)

  • Woo, Joung Woon;Kim, Yeon Joong;Yoon, Jong Sung
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.34 no.4
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    • pp.128-134
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    • 2022
  • Nakdong river estuary is being operated with the goal of expanding the period of seawater inflow from this year to 2022 every month and creating a brackish water area within 15 km of the upstream of the river bank. In this study, the deep learning algorithm Long Short-Term Memory (LSTM) was applied to predict the salinity of the Nakdong Bridge (about 5 km upstream of the river bank) for the purpose of rapid decision making for the target brackish water zone and prevention of salt water damage. Input data were constructed to reflect the temporal and spatial characteristics of the Nakdong River estuary, such as the amount of discharge from Changnyeong and Hamanbo, and an optimal model was constructed in consideration of the hydraulic characteristics of the Nakdong River Estuary by changing the degree according to the sequence length. For prediction accuracy, statistical analysis was performed using the coefficient of determination (R-squred) and RMSE (root mean square error). When the sequence length was 12, the R-squred 0.997 and RMSE 0.122 were the highest, and the prior prediction time showed a high degree of R-squred 0.93 or more until the 12-hour interval.

A Capacitance Wavestaff for the Use near Surf Zone (쇄파역에서의 사용을 위한 주상 파고계 제작)

  • Oh, Im Sang;Lee, Young Ro
    • 한국해양학회지
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    • v.23 no.2
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    • pp.53-61
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    • 1988
  • A capacitance wavestaff system was devised, which is suitable for the wave measurement near to surf zone. Laboratory tests show that the performance of the wavestaff is not significantly affected by the sea water characteristics such as temperature and salinity, and output signals of the wavestaff are linearly proportional to sea surface elevations. The major error source of the wavestaff system is the improper setting of the wavestaff in field experiment.

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Estimation of High Resolution Sea Surface Salinity Using Multi Satellite Data and Machine Learning (다종 위성자료와 기계학습을 이용한 고해상도 표층 염분 추정)

  • Sung, Taejun;Sim, Seongmun;Jang, Eunna;Im, Jungho
    • Korean Journal of Remote Sensing
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    • v.38 no.5_2
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    • pp.747-763
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    • 2022
  • Ocean salinity affects ocean circulation on a global scale and low salinity water around coastal areas often has an impact on aquaculture and fisheries. Microwave satellite sensors (e.g., Soil Moisture Active Passive [SMAP]) have provided sea surface salinity (SSS) based on the dielectric characteristics of water associated with SSS and sea surface temperature (SST). In this study, a Light Gradient Boosting Machine (LGBM)-based model for generating high resolution SSS from Geostationary Ocean Color Imager (GOCI) data was proposed, having machine learning-based improved SMAP SSS by Jang et al. (2022) as reference data (SMAP SSS (Jang)). Three schemes with different input variables were tested, and scheme 3 with all variables including Multi-scale Ultra-high Resolution SST yielded the best performance (coefficient of determination = 0.60, root mean square error = 0.91 psu). The proposed LGBM-based GOCI SSS had a similar spatiotemporal pattern with SMAP SSS (Jang), with much higher spatial resolution even in coastal areas, where SMAP SSS (Jang) was not available. In addition, when tested for the great flood occurred in Southern China in August 2020, GOCI SSS well simulated the spatial and temporal change of Changjiang Diluted Water. This research provided a potential that optical satellite data can be used to generate high resolution SSS associated with the improved microwave-based SSS especially in coastal areas.