Generic flowsheet model for early inventory estimates of industrial microbial processes. II. Downstream processing
To ensure optimal process flowsheet selection it is valuable to conduct environmental and economic comparisons at an early stage of technology selection and process design. However, the data that is needed to perform these studies are not available at this stage of process development. This is also...
Ausführliche Beschreibung
Autor*in: |
K.G. Harding [verfasserIn] S.T.L. Harrison [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
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2016 |
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Übergeordnetes Werk: |
In: South African Journal of Chemical Engineering - Elsevier, 2017, 22(2016), C, Seite 23-33 |
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Übergeordnetes Werk: |
volume:22 ; year:2016 ; number:C ; pages:23-33 |
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DOI / URN: |
10.1016/j.sajce.2016.10.002 |
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Katalog-ID: |
DOAJ002730243 |
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520 | |a To ensure optimal process flowsheet selection it is valuable to conduct environmental and economic comparisons at an early stage of technology selection and process design. However, the data that is needed to perform these studies are not available at this stage of process development. This is also true for bioprocess systems. To overcome the lack of data, the CeBER (Centre for Bioprocess Engineering Research, University of Cape Town) Bioprocess Modeller was developed to provide material and energy values for industrial microbial processes. This paper presents the downstream processing portion of this flowsheet. The model allows for solid–liquid separation, cell disruption, concentration and formulation units as required. The model allows section of appropriate downstream processing units include, amongst others, centrifugation, filtration, precipitation and freeze-drying. At each downstream processing stage, non-reacting and reacting chemicals can be added. The model provides both a material inventory as well as the calculation of the energy input required and waste heat generated. Additionally, the model includes a database of values (including constants, operating conditions and others), drawn from various industrial norms and academic sources. Should specific information not be known, the model selects the most appropriate values based on other decisions made through the model. | ||
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10.1016/j.sajce.2016.10.002 doi (DE-627)DOAJ002730243 (DE-599)DOAJ7a066ee7857c4c8f8b23ca8a13d595df DE-627 ger DE-627 rakwb eng TP155-156 K.G. Harding verfasserin aut Generic flowsheet model for early inventory estimates of industrial microbial processes. II. Downstream processing 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier To ensure optimal process flowsheet selection it is valuable to conduct environmental and economic comparisons at an early stage of technology selection and process design. However, the data that is needed to perform these studies are not available at this stage of process development. This is also true for bioprocess systems. To overcome the lack of data, the CeBER (Centre for Bioprocess Engineering Research, University of Cape Town) Bioprocess Modeller was developed to provide material and energy values for industrial microbial processes. This paper presents the downstream processing portion of this flowsheet. The model allows for solid–liquid separation, cell disruption, concentration and formulation units as required. The model allows section of appropriate downstream processing units include, amongst others, centrifugation, filtration, precipitation and freeze-drying. At each downstream processing stage, non-reacting and reacting chemicals can be added. The model provides both a material inventory as well as the calculation of the energy input required and waste heat generated. Additionally, the model includes a database of values (including constants, operating conditions and others), drawn from various industrial norms and academic sources. Should specific information not be known, the model selects the most appropriate values based on other decisions made through the model. Generic flow sheeting Bioprocess design Modelling Downstream processing CeBER Bioprocess Modeller Penicillin Chemical engineering S.T.L. Harrison verfasserin aut In South African Journal of Chemical Engineering Elsevier, 2017 22(2016), C, Seite 23-33 (DE-627)371099463 (DE-600)2121113-9 10269185 nnns volume:22 year:2016 number:C pages:23-33 https://doi.org/10.1016/j.sajce.2016.10.002 kostenfrei https://doaj.org/article/7a066ee7857c4c8f8b23ca8a13d595df kostenfrei http://www.sciencedirect.com/science/article/pii/S1026918515300196 kostenfrei https://doaj.org/toc/1026-9185 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 22 2016 C 23-33 |
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10.1016/j.sajce.2016.10.002 doi (DE-627)DOAJ002730243 (DE-599)DOAJ7a066ee7857c4c8f8b23ca8a13d595df DE-627 ger DE-627 rakwb eng TP155-156 K.G. Harding verfasserin aut Generic flowsheet model for early inventory estimates of industrial microbial processes. II. Downstream processing 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier To ensure optimal process flowsheet selection it is valuable to conduct environmental and economic comparisons at an early stage of technology selection and process design. However, the data that is needed to perform these studies are not available at this stage of process development. This is also true for bioprocess systems. To overcome the lack of data, the CeBER (Centre for Bioprocess Engineering Research, University of Cape Town) Bioprocess Modeller was developed to provide material and energy values for industrial microbial processes. This paper presents the downstream processing portion of this flowsheet. The model allows for solid–liquid separation, cell disruption, concentration and formulation units as required. The model allows section of appropriate downstream processing units include, amongst others, centrifugation, filtration, precipitation and freeze-drying. At each downstream processing stage, non-reacting and reacting chemicals can be added. The model provides both a material inventory as well as the calculation of the energy input required and waste heat generated. Additionally, the model includes a database of values (including constants, operating conditions and others), drawn from various industrial norms and academic sources. Should specific information not be known, the model selects the most appropriate values based on other decisions made through the model. Generic flow sheeting Bioprocess design Modelling Downstream processing CeBER Bioprocess Modeller Penicillin Chemical engineering S.T.L. Harrison verfasserin aut In South African Journal of Chemical Engineering Elsevier, 2017 22(2016), C, Seite 23-33 (DE-627)371099463 (DE-600)2121113-9 10269185 nnns volume:22 year:2016 number:C pages:23-33 https://doi.org/10.1016/j.sajce.2016.10.002 kostenfrei https://doaj.org/article/7a066ee7857c4c8f8b23ca8a13d595df kostenfrei http://www.sciencedirect.com/science/article/pii/S1026918515300196 kostenfrei https://doaj.org/toc/1026-9185 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 22 2016 C 23-33 |
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K.G. Harding misc TP155-156 misc Generic flow sheeting misc Bioprocess design misc Modelling misc Downstream processing misc CeBER Bioprocess Modeller misc Penicillin misc Chemical engineering Generic flowsheet model for early inventory estimates of industrial microbial processes. II. Downstream processing |
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generic flowsheet model for early inventory estimates of industrial microbial processes. ii. downstream processing |
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Generic flowsheet model for early inventory estimates of industrial microbial processes. II. Downstream processing |
abstract |
To ensure optimal process flowsheet selection it is valuable to conduct environmental and economic comparisons at an early stage of technology selection and process design. However, the data that is needed to perform these studies are not available at this stage of process development. This is also true for bioprocess systems. To overcome the lack of data, the CeBER (Centre for Bioprocess Engineering Research, University of Cape Town) Bioprocess Modeller was developed to provide material and energy values for industrial microbial processes. This paper presents the downstream processing portion of this flowsheet. The model allows for solid–liquid separation, cell disruption, concentration and formulation units as required. The model allows section of appropriate downstream processing units include, amongst others, centrifugation, filtration, precipitation and freeze-drying. At each downstream processing stage, non-reacting and reacting chemicals can be added. The model provides both a material inventory as well as the calculation of the energy input required and waste heat generated. Additionally, the model includes a database of values (including constants, operating conditions and others), drawn from various industrial norms and academic sources. Should specific information not be known, the model selects the most appropriate values based on other decisions made through the model. |
abstractGer |
To ensure optimal process flowsheet selection it is valuable to conduct environmental and economic comparisons at an early stage of technology selection and process design. However, the data that is needed to perform these studies are not available at this stage of process development. This is also true for bioprocess systems. To overcome the lack of data, the CeBER (Centre for Bioprocess Engineering Research, University of Cape Town) Bioprocess Modeller was developed to provide material and energy values for industrial microbial processes. This paper presents the downstream processing portion of this flowsheet. The model allows for solid–liquid separation, cell disruption, concentration and formulation units as required. The model allows section of appropriate downstream processing units include, amongst others, centrifugation, filtration, precipitation and freeze-drying. At each downstream processing stage, non-reacting and reacting chemicals can be added. The model provides both a material inventory as well as the calculation of the energy input required and waste heat generated. Additionally, the model includes a database of values (including constants, operating conditions and others), drawn from various industrial norms and academic sources. Should specific information not be known, the model selects the most appropriate values based on other decisions made through the model. |
abstract_unstemmed |
To ensure optimal process flowsheet selection it is valuable to conduct environmental and economic comparisons at an early stage of technology selection and process design. However, the data that is needed to perform these studies are not available at this stage of process development. This is also true for bioprocess systems. To overcome the lack of data, the CeBER (Centre for Bioprocess Engineering Research, University of Cape Town) Bioprocess Modeller was developed to provide material and energy values for industrial microbial processes. This paper presents the downstream processing portion of this flowsheet. The model allows for solid–liquid separation, cell disruption, concentration and formulation units as required. The model allows section of appropriate downstream processing units include, amongst others, centrifugation, filtration, precipitation and freeze-drying. At each downstream processing stage, non-reacting and reacting chemicals can be added. The model provides both a material inventory as well as the calculation of the energy input required and waste heat generated. Additionally, the model includes a database of values (including constants, operating conditions and others), drawn from various industrial norms and academic sources. Should specific information not be known, the model selects the most appropriate values based on other decisions made through the model. |
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