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À̸§ °ü¸®ÀÚ waterindustry@hanmail.net ÀÛ¼ºÀÏ 2022.10.27 Á¶È¸¼ö 499
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[½ºÆäÀÎ] ¾Ç½Ã¿À³ª, ¿ª»ïÅõ¸· ¿À¿°¹æÁö ¼Ö·ç¼Ç °³¹ß Âø¼ö

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½ºÆäÀÎÀÇ ±Û·Î¹ú ÀÎÇÁ¶ó¡¤¹°±â¾÷ÀÎ ¾Ç½Ã¿À³ª(ACCIONA)´Â Çؼö ¿ª»ïÅõ¾Ð(SWRO) ´ã¼öÈ­ °øÁ¤¿¡¼­ÀÇ ¿À¿°À» ¹æÁöÇϱâ À§ÇØ  ¡®WITNESS ÇÁ·ÎÁ§Æ®¡¯¸¦ ½ÃÀÛÇß´Ù.  [»çÁøÃâó(Photo source) = ¾Ç½Ã¿À³ª(ACCIONA)]

½ºÆäÀÎÀÇ ±Û·Î¹ú ÀÎÇÁ¶ó¡¤¹°±â¾÷ÀÎ ¾Ç½Ã¿À³ª(ACCIONA)´Â Çؼö ¿ª»ïÅõ¾Ð(SWRO) ´ã¼öÈ­ °øÁ¤¿¡¼­ÀÇ ¿À¿°À» ¹æÁöÇϱâ À§ÇØ ¡®WITNESS ÇÁ·ÎÁ§Æ®¡¯¸¦ ½ÃÀÛÇß´Ù. [»çÁøÃâó(Photo source) = ¾Ç½Ã¿À³ª(ACCIONA)]

 

½ºÆäÀÎÀÇ ±Û·Î¹ú ÀÎÇÁ¶ó¡¤¹°±â¾÷ÀÎ ¾Ç½Ã¿À³ª(ACCIONA)´Â Çõ½Å¿¡ ´ëÇÑ ¾à¼ÓÀÇ ÀÏȯÀ¸·Î ¡®WITNESS ÇÁ·ÎÁ§Æ®¡¯¸¦ ½ÃÀÛÇß´Ù. ÀÌ ÇÁ·ÎÁ§Æ®´Â Çؼö ¿ª»ïÅõ¾Ð ´ã¼öÈ­ °øÁ¤(SWRO desalination processes)¿¡¼­ ¿À¿°À» ÀÏÀ¸Å°´Â ¹°ÁúÀÇ Á¸À縦 ¿¹¹æÀûÀ¸·Î °áÁ¤Çϱâ À§ÇÑ »ý¹°ÇÐÀû ÁöÇ¥¸¦ °³¹ßÇÏ´Â °ÍÀ» ¸ñÇ¥·Î ÇÑ´Ù.


¿ª»ïÅõ¸·ÀÇ ¿À¿°Àº Çؼö ¿ª»ïÅõ¾Ð(SWRO) ´ã¼öÈ­ °øÁ¤À» ´õ¿í ÃÖÀûÈ­Çϱâ À§ÇÑ ÁÖ¿ä Á¦ÇÑ »çÇ× Áß ÇϳªÀÏ »Ó¸¸ ¾Æ´Ï¶ó ÇØ´ç ºÎ¹®ÀÇ Å« °úÁ¦ Áß ÇϳªÀÌ´Ù.


¸·ÀÌ ¿À¿°µÇ¸é ÀÛµ¿ ¾Ð·ÂÀÌ ³ô¾ÆÁ® ¿¡³ÊÁö ¼Òºñ°¡ Áõ°¡ÇÒ »Ó¸¸ ¾Æ´Ï¶ó ÀÛµ¿ÀÌ ´õ º¹ÀâÇØÁö°í Åõ°ú¹°ÀÇ Ç°ÁúÀÌ ÀúÇϵȴÙ.


ÇöÀç ÁöÇ¥´Â ´Ù¾çÇÑ ¿À¿° À¯ÇüÀ» ±¸ºÐÇÒ ¼ö ¾øÀ¸¸ç SDI(Silt Density Index, ½ÇÆ®¹ÐµµÁö¼ö)¿Í °°Àº ´ëÇ¥¼º°ú °ü·ÃÇÏ¿© ÇÑ°è°¡ ÀÖ´Ù(Schippers et al., 2014). ¶ÇÇÑ ÇöÀç »ý¹°ÇÐÀû ÁöÇ¥¿¡´Â ÁÖ¾îÁø Çؼö ¸ÅÆ®¸¯½º(seawater matrix)ÀÇ ¿À¿° °¡´É¼º¿¡ ´ëÇÑ ¿ÏÀüÇÑ °³¿ä¸¦ °®´Â °ÍÀ» ¹æÇØÇÏ´Â ºÒ¿ÏÀüÇϰųª ÆíÇâµÈ ÃøÁ¤ÀÌ Æ÷ÇԵȴÙ(Alhadidi et al., 2012 ; ÀÌÁø¿í(Lee Jin-Wook) et al., 2010).


¿©·¯ Á¤º¸ Ãâó¿¡ µû¸£¸é »ý¹°ÇÐÀû ¿À¿°Àº ´ã¼öÈ­¿¡¼­ ¿ª»ïÅõ¸· ¹®Á¦ÀÇ ÃÖ´ë 10¡­30%¸¦ À¯¹ßÇÒ ¼ö ÀÖÀ¸¸ç, ÀÌ·Î ÀÎÇØ CapEx(ÀÚº»ÁöÃâ) ¹× OpEX(¿î¿ëºñ¿ë)¿¡ °æÁ¦Àû ¿µÇâÀÌ ¹ß»ýÇÒ ¼ö ÀÖ´Ù.


»ý¹°ÇÐÀû ¿À¿°Àº ´ã¼öÈ­¿¡¼­ ¿ª»ïÅõ¸· ¹®Á¦ÀÇ ÃÖ´ë 10¡­30%¸¦ À¯¹ßÇÒ ¼ö ÀÖÀ¸¸ç, ÀÌ·Î ÀÎÇØ CapEx(ÀÚº»ÁöÃâ) ¹× OpEX(¿î¿ëºñ¿ë)¿¡ °æÁ¦Àû ¿µÇâÀÌ ¹ß»ýÇÒ ¼ö ÀÖ´Ù. [»çÁøÃâó(Photo source) = ¾Ç½Ã¿À³ª(ACCIONA)]

»ý¹°ÇÐÀû ¿À¿°Àº ´ã¼öÈ­¿¡¼­ ¿ª»ïÅõ¸· ¹®Á¦ÀÇ ÃÖ´ë 10¡­30%¸¦ À¯¹ßÇÒ ¼ö ÀÖÀ¸¸ç, ÀÌ·Î ÀÎÇØ CapEx(ÀÚº»ÁöÃâ) ¹× OpEX(¿î¿ëºñ¿ë)¿¡ °æÁ¦Àû ¿µÇâÀÌ ¹ß»ýÇÒ ¼ö ÀÖ´Ù. [»çÁøÃâó(Photo source) = ¾Ç½Ã¿À³ª(ACCIONA)]

 

¾Ç½Ã¿À³ª°¡ °³¹ßÇÑ »õ·Î¿î ÁöÇ¥´Â ¿À¿°À» ÃÖ¼ÒÈ­ÇÏ°í ´ã¼öÈ­ °øÁ¤¿¡ ¹ÌÄ¡´Â ¿µÇâÀ» ÃÖ¼ÒÈ­Çϱâ À§ÇØ ´ã¼öÈ­ Ç÷£Æ®ÀÇ ÀÛµ¿ Á¶°ÇÀ» Á¶Á¤Çϱâ À§ÇÑ ¿¹¹æ Áø´ÜÀ» Á¦°øÇÑ´Ù.


¿ª»ïÅõ¾Ð ´Ü°èÀÇ ´Ù¸¥ ÀÛµ¿ ÁöÇ¥¿Í ÇÔ²² WITNESS ÁöÇ¥´Â ÀΰøÁö´É ±â¹Ý ¿À¿° °¡´É¼º ¿¹Ãø µµ±¸¿¡ ÅëÇյǸç, À̴ ȸ»çÀÇ Çõ½Å½Ã¼³, ƯÈ÷ ¹«¸£½Ã¾Æ(Murcia)¿¡ ÀÖ´Â »êÆäµå·Î µ¨ ÇdzªÅ¸¸£ II SWRO(San Pedro del Pinatar II SWRO)ÀÇ ¼±µµ ½ÇÇè °¡¼Ó±â(LEAD ; Leading Experimental Accelerator in Desalination)¿¡¼­ °ËÁõµÈ´Ù.


¸¶Âù°¡Áö·Î ±âº» »ç·Ê ¹öÀü(base case version)ÀÌ °³¹ßµÇ°í ÀÌÈÄ¿¡´Â ÀáÀçÀû ¿À¿° ¼öÁØÀ» ¿¹ÃøÇÒ ¼ö ÀÖ´Â ÀΰøÁö´É µµ±¸(Artificial Intelligence tool)ÀÇ Áõ°­ ¹öÀü(ugmented version)ÀÌ °³¹ßµÈ´Ù.


[¿ø¹®º¸±â]


ACCIONA develops a solution to prevent fouling in reverse osmosis membranes


 

The new biological indicator will be integrated into a predictive tool based on Artificial Intelligence which will allow identifying the potential fouling of the inlet water.

 

ACCIONA , as part of its commitment with innovation, has launched the WITNESS project, which objective is to develop a biological indicator to preventively determine the presence of agents causing fouling in seawater reverse osmosis desalination processes.


Fouling in reverse osmosis membranes is one of the main limitations to further optimise seawater reverse osmosis desalination processes, as well as one of the great challenges for the sector.


The fouling of membranes leads to higher operation pressure and thus and increase of energy consumption, as well as greater complexity in operation and a reduction in the permeate quality.


Current indicators do not allow distinguishing between different fouling types and have limitations regarding representativeness, such as the Silt Density Index (SDI) (Schippers et al., 2014). In addition, current biological indicators include incomplete or biased measurements which prevent from having a complete overview of the fouling potential of a given seawater matrix (Alhadidi et al., 2012; Lee Jin-Wook et al., 2010).


According to several sources of information biological fouling may cause up to 10-30% of the issues in reverse osmosis membranes in desalination, with the economic impact on CapEx and OpEX that this entails.


The new indicator developed by ACCIONA will provide a preventive diagnosis to adjust the operating conditions of the desalination plants, in order to minimize fouling and, therefore, its consequences on the desalination process.


Together with other operation indicators of the reverse osmosis stage, the WITNESS indicator will be integrated into an Artificial Intelligence-based fouling potential prediction tool, which will be validated in the innovation facilities of the company, specifically in its Leading Experimental Accelerator in Desalination (LEAD¢ç), located in the San Pedro del Pinatar II SWRO (Murcia).


Likewise, a base case version will be developed and, afterwards, an augmented version of the Artificial Intelligence tool that will allow to carry out predictive estimations of the potential fouling level.


[Ãâó = FuturENVIRO(https://futurenviro.es/en/acciona-develops-a-solution-to-prevent-fouling-in-reverse-osmosis-membranes/) /2022³â 10¿ù 26ÀÏ]

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