Thyroid Imaging

Nucera, Carmelo; Parker, J. Anthony; Parangi, Sareh

doi:10.1007/978-1-84628-881-4_4

Cited by 1 publication

(1 citation statement)

References 93 publications

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“…The primary process of CA production is the electrolysis of brine (NaCl) aqueous solution, which is more environmentally compatible than mercury cell in the past. The electrolysis process has a high electrical energy consumption, and the latest technology in 2022 claim power consumption at 2,000 kWh per metric ton NaOH [4]. Thus, electrical power consumption is the direct operating cost of the CA process and a key factor of production profit.…”

Section: Figure 2 Products Of Chlorine Tree [3]mentioning

confidence: 99%

Parameters optimization in Chlor-Alkali ion-exchange membrane electrolysis process with artificial neural network

Sukantowong

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Since ion-exchange membrane electrolysis cell has developed for producing Chlor-Alkali products. New�higher efficiency and lower consumption�technology are released from licensors yearly, which made the process correlation deviate from the original design. The machine learning�is used with Neural Network Fitting Tool (nftool) in MATLAB. To find a correlation between 5 inputs consisting of current density (CD, KA/m2), operation day (DOL, day), feed brine flow rate (QFB, m3/h), feed caustic flow rate (QHD, m3/h),�cell temperature (T, degC) and one output which is cell voltage (CV, V). Datasets were collected from�the plant information management system exaquantum historian database. The result is shown only on CD as the predictor gives RMSE at 0.0167 V. In 2 predictors, DOL as the second gave RMSE at 0.0065 V, which can conclude that DOL (or clogging factor) has the most impact on CV increasing. In 3 predictors, T as the third gave RMSE at 0.0043 V, from controlled temperature set point change. Developed ANN optimization model can be used to optimize controlled parameters to predict suitable CV after a long run (high DOL) or to compare electrolysis effectiveness by regressing CV for comparing at the same condition.

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Section: Figure 2 Products Of Chlorine Tree [3]mentioning

confidence: 99%

Parameters optimization in Chlor-Alkali ion-exchange membrane electrolysis process with artificial neural network

Sukantowong

View full text Add to dashboard Cite

show abstract

Thyroid Imaging

Cited by 1 publication

References 93 publications

Parameters optimization in Chlor-Alkali ion-exchange membrane electrolysis process with artificial neural network

Parameters optimization in Chlor-Alkali ion-exchange membrane electrolysis process with artificial neural network

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