A Heat and Mass Transfer Model for Predicting the Drying of Beef During Biltong Processing Using Infrared-Assisted Hot Air Drying
Purpose The aim of this study was to develop a coupled heat and mass transfer model to predict the temperature and moisture content of beef during biltong processing using infrared-assisted hot air drying (IRHAD). Methods The developed model was implemented and solved using Ansys Fluent CFD software...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Muga, F. C. [verfasserIn] Marenya, M. O. [verfasserIn] Workneh, T. S. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021 |
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| Schlagwörter: |
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| Anmerkung: |
© The Korean Society for Agricultural Machinery 2021 |
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| Übergeordnetes Werk: |
Enthalten in: Journal of Biosystems Engineering - Singapore : Springer Singapore, 2004, 46(2021), 3 vom: Sept., Seite 273-285 |
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| Übergeordnetes Werk: |
volume:46 ; year:2021 ; number:3 ; month:09 ; pages:273-285 |
| Links: |
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| DOI / URN: |
10.1007/s42853-021-00105-x |
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| Katalog-ID: |
SPR045235899 |
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| 100 | 1 | |a Muga, F. C. |e verfasserin |4 aut | |
| 245 | 1 | 2 | |a A Heat and Mass Transfer Model for Predicting the Drying of Beef During Biltong Processing Using Infrared-Assisted Hot Air Drying |
| 264 | 1 | |c 2021 | |
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| 520 | |a Purpose The aim of this study was to develop a coupled heat and mass transfer model to predict the temperature and moisture content of beef during biltong processing using infrared-assisted hot air drying (IRHAD). Methods The developed model was implemented and solved using Ansys Fluent CFD software. Drying experiments conducted using an infrared-assisted hot air dryer were used to determine the moisture diffusivity, and the heat and mass transfer coefficients used in the model. The experiments were done at an infrared emitter power level of 750 W; drying air temperature of 30, 35, and 40 °C; and velocity of 1.5 and 2.5 m $ s^{−1} $. Results The simulation slightly overpredicted the temperature in the first hour of drying and underpredicted the temperature towards the end of the drying period. Consequently, the predicted moisture ratio (MR) was underpredicted at the onset of drying and agreed with the experimental values towards the end of the drying period. The simulation results were validated using a new set of experimental results, and the suitability of the model assessed using the $ R^{2} $ (0.9790 for temperature and 0.9579 for MR) and RMSE (1.99 for temperature and 0.0698 for MR). Conclusion The model can guide the application of IRHAD in the processing of biltong and forms a theoretical basis for analysing the application of IRHAD to other food and biobased products. | ||
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| 700 | 1 | |a Marenya, M. O. |e verfasserin |4 aut | |
| 700 | 1 | |a Workneh, T. S. |e verfasserin |4 aut | |
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10.1007/s42853-021-00105-x doi (DE-627)SPR045235899 (SPR)s42853-021-00105-x-e DE-627 ger DE-627 rakwb eng Muga, F. C. verfasserin aut A Heat and Mass Transfer Model for Predicting the Drying of Beef During Biltong Processing Using Infrared-Assisted Hot Air Drying 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Korean Society for Agricultural Machinery 2021 Purpose The aim of this study was to develop a coupled heat and mass transfer model to predict the temperature and moisture content of beef during biltong processing using infrared-assisted hot air drying (IRHAD). Methods The developed model was implemented and solved using Ansys Fluent CFD software. Drying experiments conducted using an infrared-assisted hot air dryer were used to determine the moisture diffusivity, and the heat and mass transfer coefficients used in the model. The experiments were done at an infrared emitter power level of 750 W; drying air temperature of 30, 35, and 40 °C; and velocity of 1.5 and 2.5 m $ s^{−1} $. Results The simulation slightly overpredicted the temperature in the first hour of drying and underpredicted the temperature towards the end of the drying period. Consequently, the predicted moisture ratio (MR) was underpredicted at the onset of drying and agreed with the experimental values towards the end of the drying period. The simulation results were validated using a new set of experimental results, and the suitability of the model assessed using the $ R^{2} $ (0.9790 for temperature and 0.9579 for MR) and RMSE (1.99 for temperature and 0.0698 for MR). Conclusion The model can guide the application of IRHAD in the processing of biltong and forms a theoretical basis for analysing the application of IRHAD to other food and biobased products. Ansys fluent (dpeaa)DE-He213 Biltong (dpeaa)DE-He213 Computerised fluid dynamics (dpeaa)DE-He213 Heat transfer (dpeaa)DE-He213 Mass transfer (dpeaa)DE-He213 Modelling (dpeaa)DE-He213 Marenya, M. O. verfasserin aut Workneh, T. S. verfasserin aut Enthalten in Journal of Biosystems Engineering Singapore : Springer Singapore, 2004 46(2021), 3 vom: Sept., Seite 273-285 (DE-627)166529633X (DE-600)2972001-1 2234-1862 nnns volume:46 year:2021 number:3 month:09 pages:273-285 https://dx.doi.org/10.1007/s42853-021-00105-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 46 2021 3 09 273-285 |
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10.1007/s42853-021-00105-x doi (DE-627)SPR045235899 (SPR)s42853-021-00105-x-e DE-627 ger DE-627 rakwb eng Muga, F. C. verfasserin aut A Heat and Mass Transfer Model for Predicting the Drying of Beef During Biltong Processing Using Infrared-Assisted Hot Air Drying 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Korean Society for Agricultural Machinery 2021 Purpose The aim of this study was to develop a coupled heat and mass transfer model to predict the temperature and moisture content of beef during biltong processing using infrared-assisted hot air drying (IRHAD). Methods The developed model was implemented and solved using Ansys Fluent CFD software. Drying experiments conducted using an infrared-assisted hot air dryer were used to determine the moisture diffusivity, and the heat and mass transfer coefficients used in the model. The experiments were done at an infrared emitter power level of 750 W; drying air temperature of 30, 35, and 40 °C; and velocity of 1.5 and 2.5 m $ s^{−1} $. Results The simulation slightly overpredicted the temperature in the first hour of drying and underpredicted the temperature towards the end of the drying period. Consequently, the predicted moisture ratio (MR) was underpredicted at the onset of drying and agreed with the experimental values towards the end of the drying period. The simulation results were validated using a new set of experimental results, and the suitability of the model assessed using the $ R^{2} $ (0.9790 for temperature and 0.9579 for MR) and RMSE (1.99 for temperature and 0.0698 for MR). Conclusion The model can guide the application of IRHAD in the processing of biltong and forms a theoretical basis for analysing the application of IRHAD to other food and biobased products. Ansys fluent (dpeaa)DE-He213 Biltong (dpeaa)DE-He213 Computerised fluid dynamics (dpeaa)DE-He213 Heat transfer (dpeaa)DE-He213 Mass transfer (dpeaa)DE-He213 Modelling (dpeaa)DE-He213 Marenya, M. O. verfasserin aut Workneh, T. S. verfasserin aut Enthalten in Journal of Biosystems Engineering Singapore : Springer Singapore, 2004 46(2021), 3 vom: Sept., Seite 273-285 (DE-627)166529633X (DE-600)2972001-1 2234-1862 nnns volume:46 year:2021 number:3 month:09 pages:273-285 https://dx.doi.org/10.1007/s42853-021-00105-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 46 2021 3 09 273-285 |
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10.1007/s42853-021-00105-x doi (DE-627)SPR045235899 (SPR)s42853-021-00105-x-e DE-627 ger DE-627 rakwb eng Muga, F. C. verfasserin aut A Heat and Mass Transfer Model for Predicting the Drying of Beef During Biltong Processing Using Infrared-Assisted Hot Air Drying 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Korean Society for Agricultural Machinery 2021 Purpose The aim of this study was to develop a coupled heat and mass transfer model to predict the temperature and moisture content of beef during biltong processing using infrared-assisted hot air drying (IRHAD). Methods The developed model was implemented and solved using Ansys Fluent CFD software. Drying experiments conducted using an infrared-assisted hot air dryer were used to determine the moisture diffusivity, and the heat and mass transfer coefficients used in the model. The experiments were done at an infrared emitter power level of 750 W; drying air temperature of 30, 35, and 40 °C; and velocity of 1.5 and 2.5 m $ s^{−1} $. Results The simulation slightly overpredicted the temperature in the first hour of drying and underpredicted the temperature towards the end of the drying period. Consequently, the predicted moisture ratio (MR) was underpredicted at the onset of drying and agreed with the experimental values towards the end of the drying period. The simulation results were validated using a new set of experimental results, and the suitability of the model assessed using the $ R^{2} $ (0.9790 for temperature and 0.9579 for MR) and RMSE (1.99 for temperature and 0.0698 for MR). Conclusion The model can guide the application of IRHAD in the processing of biltong and forms a theoretical basis for analysing the application of IRHAD to other food and biobased products. Ansys fluent (dpeaa)DE-He213 Biltong (dpeaa)DE-He213 Computerised fluid dynamics (dpeaa)DE-He213 Heat transfer (dpeaa)DE-He213 Mass transfer (dpeaa)DE-He213 Modelling (dpeaa)DE-He213 Marenya, M. O. verfasserin aut Workneh, T. S. verfasserin aut Enthalten in Journal of Biosystems Engineering Singapore : Springer Singapore, 2004 46(2021), 3 vom: Sept., Seite 273-285 (DE-627)166529633X (DE-600)2972001-1 2234-1862 nnns volume:46 year:2021 number:3 month:09 pages:273-285 https://dx.doi.org/10.1007/s42853-021-00105-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 46 2021 3 09 273-285 |
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10.1007/s42853-021-00105-x doi (DE-627)SPR045235899 (SPR)s42853-021-00105-x-e DE-627 ger DE-627 rakwb eng Muga, F. C. verfasserin aut A Heat and Mass Transfer Model for Predicting the Drying of Beef During Biltong Processing Using Infrared-Assisted Hot Air Drying 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Korean Society for Agricultural Machinery 2021 Purpose The aim of this study was to develop a coupled heat and mass transfer model to predict the temperature and moisture content of beef during biltong processing using infrared-assisted hot air drying (IRHAD). Methods The developed model was implemented and solved using Ansys Fluent CFD software. Drying experiments conducted using an infrared-assisted hot air dryer were used to determine the moisture diffusivity, and the heat and mass transfer coefficients used in the model. The experiments were done at an infrared emitter power level of 750 W; drying air temperature of 30, 35, and 40 °C; and velocity of 1.5 and 2.5 m $ s^{−1} $. Results The simulation slightly overpredicted the temperature in the first hour of drying and underpredicted the temperature towards the end of the drying period. Consequently, the predicted moisture ratio (MR) was underpredicted at the onset of drying and agreed with the experimental values towards the end of the drying period. The simulation results were validated using a new set of experimental results, and the suitability of the model assessed using the $ R^{2} $ (0.9790 for temperature and 0.9579 for MR) and RMSE (1.99 for temperature and 0.0698 for MR). Conclusion The model can guide the application of IRHAD in the processing of biltong and forms a theoretical basis for analysing the application of IRHAD to other food and biobased products. Ansys fluent (dpeaa)DE-He213 Biltong (dpeaa)DE-He213 Computerised fluid dynamics (dpeaa)DE-He213 Heat transfer (dpeaa)DE-He213 Mass transfer (dpeaa)DE-He213 Modelling (dpeaa)DE-He213 Marenya, M. O. verfasserin aut Workneh, T. S. verfasserin aut Enthalten in Journal of Biosystems Engineering Singapore : Springer Singapore, 2004 46(2021), 3 vom: Sept., Seite 273-285 (DE-627)166529633X (DE-600)2972001-1 2234-1862 nnns volume:46 year:2021 number:3 month:09 pages:273-285 https://dx.doi.org/10.1007/s42853-021-00105-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 46 2021 3 09 273-285 |
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10.1007/s42853-021-00105-x doi (DE-627)SPR045235899 (SPR)s42853-021-00105-x-e DE-627 ger DE-627 rakwb eng Muga, F. C. verfasserin aut A Heat and Mass Transfer Model for Predicting the Drying of Beef During Biltong Processing Using Infrared-Assisted Hot Air Drying 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Korean Society for Agricultural Machinery 2021 Purpose The aim of this study was to develop a coupled heat and mass transfer model to predict the temperature and moisture content of beef during biltong processing using infrared-assisted hot air drying (IRHAD). Methods The developed model was implemented and solved using Ansys Fluent CFD software. Drying experiments conducted using an infrared-assisted hot air dryer were used to determine the moisture diffusivity, and the heat and mass transfer coefficients used in the model. The experiments were done at an infrared emitter power level of 750 W; drying air temperature of 30, 35, and 40 °C; and velocity of 1.5 and 2.5 m $ s^{−1} $. Results The simulation slightly overpredicted the temperature in the first hour of drying and underpredicted the temperature towards the end of the drying period. Consequently, the predicted moisture ratio (MR) was underpredicted at the onset of drying and agreed with the experimental values towards the end of the drying period. The simulation results were validated using a new set of experimental results, and the suitability of the model assessed using the $ R^{2} $ (0.9790 for temperature and 0.9579 for MR) and RMSE (1.99 for temperature and 0.0698 for MR). Conclusion The model can guide the application of IRHAD in the processing of biltong and forms a theoretical basis for analysing the application of IRHAD to other food and biobased products. Ansys fluent (dpeaa)DE-He213 Biltong (dpeaa)DE-He213 Computerised fluid dynamics (dpeaa)DE-He213 Heat transfer (dpeaa)DE-He213 Mass transfer (dpeaa)DE-He213 Modelling (dpeaa)DE-He213 Marenya, M. O. verfasserin aut Workneh, T. S. verfasserin aut Enthalten in Journal of Biosystems Engineering Singapore : Springer Singapore, 2004 46(2021), 3 vom: Sept., Seite 273-285 (DE-627)166529633X (DE-600)2972001-1 2234-1862 nnns volume:46 year:2021 number:3 month:09 pages:273-285 https://dx.doi.org/10.1007/s42853-021-00105-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 46 2021 3 09 273-285 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">SPR045235899</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20211007064918.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">211007s2021 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s42853-021-00105-x</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR045235899</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s42853-021-00105-x-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Muga, F. C.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="2"><subfield code="a">A Heat and Mass Transfer Model for Predicting the Drying of Beef During Biltong Processing Using Infrared-Assisted Hot Air Drying</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2021</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Korean Society for Agricultural Machinery 2021</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Purpose The aim of this study was to develop a coupled heat and mass transfer model to predict the temperature and moisture content of beef during biltong processing using infrared-assisted hot air drying (IRHAD). Methods The developed model was implemented and solved using Ansys Fluent CFD software. Drying experiments conducted using an infrared-assisted hot air dryer were used to determine the moisture diffusivity, and the heat and mass transfer coefficients used in the model. The experiments were done at an infrared emitter power level of 750 W; drying air temperature of 30, 35, and 40 °C; and velocity of 1.5 and 2.5 m $ s^{−1} $. Results The simulation slightly overpredicted the temperature in the first hour of drying and underpredicted the temperature towards the end of the drying period. Consequently, the predicted moisture ratio (MR) was underpredicted at the onset of drying and agreed with the experimental values towards the end of the drying period. The simulation results were validated using a new set of experimental results, and the suitability of the model assessed using the $ R^{2} $ (0.9790 for temperature and 0.9579 for MR) and RMSE (1.99 for temperature and 0.0698 for MR). 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Muga, F. C. |
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Muga, F. C. misc Ansys fluent misc Biltong misc Computerised fluid dynamics misc Heat transfer misc Mass transfer misc Modelling A Heat and Mass Transfer Model for Predicting the Drying of Beef During Biltong Processing Using Infrared-Assisted Hot Air Drying |
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A Heat and Mass Transfer Model for Predicting the Drying of Beef During Biltong Processing Using Infrared-Assisted Hot Air Drying Ansys fluent (dpeaa)DE-He213 Biltong (dpeaa)DE-He213 Computerised fluid dynamics (dpeaa)DE-He213 Heat transfer (dpeaa)DE-He213 Mass transfer (dpeaa)DE-He213 Modelling (dpeaa)DE-He213 |
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misc Ansys fluent misc Biltong misc Computerised fluid dynamics misc Heat transfer misc Mass transfer misc Modelling |
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A Heat and Mass Transfer Model for Predicting the Drying of Beef During Biltong Processing Using Infrared-Assisted Hot Air Drying |
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A Heat and Mass Transfer Model for Predicting the Drying of Beef During Biltong Processing Using Infrared-Assisted Hot Air Drying |
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Muga, F. C. Marenya, M. O. Workneh, T. S. |
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heat and mass transfer model for predicting the drying of beef during biltong processing using infrared-assisted hot air drying |
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A Heat and Mass Transfer Model for Predicting the Drying of Beef During Biltong Processing Using Infrared-Assisted Hot Air Drying |
| abstract |
Purpose The aim of this study was to develop a coupled heat and mass transfer model to predict the temperature and moisture content of beef during biltong processing using infrared-assisted hot air drying (IRHAD). Methods The developed model was implemented and solved using Ansys Fluent CFD software. Drying experiments conducted using an infrared-assisted hot air dryer were used to determine the moisture diffusivity, and the heat and mass transfer coefficients used in the model. The experiments were done at an infrared emitter power level of 750 W; drying air temperature of 30, 35, and 40 °C; and velocity of 1.5 and 2.5 m $ s^{−1} $. Results The simulation slightly overpredicted the temperature in the first hour of drying and underpredicted the temperature towards the end of the drying period. Consequently, the predicted moisture ratio (MR) was underpredicted at the onset of drying and agreed with the experimental values towards the end of the drying period. The simulation results were validated using a new set of experimental results, and the suitability of the model assessed using the $ R^{2} $ (0.9790 for temperature and 0.9579 for MR) and RMSE (1.99 for temperature and 0.0698 for MR). Conclusion The model can guide the application of IRHAD in the processing of biltong and forms a theoretical basis for analysing the application of IRHAD to other food and biobased products. © The Korean Society for Agricultural Machinery 2021 |
| abstractGer |
Purpose The aim of this study was to develop a coupled heat and mass transfer model to predict the temperature and moisture content of beef during biltong processing using infrared-assisted hot air drying (IRHAD). Methods The developed model was implemented and solved using Ansys Fluent CFD software. Drying experiments conducted using an infrared-assisted hot air dryer were used to determine the moisture diffusivity, and the heat and mass transfer coefficients used in the model. The experiments were done at an infrared emitter power level of 750 W; drying air temperature of 30, 35, and 40 °C; and velocity of 1.5 and 2.5 m $ s^{−1} $. Results The simulation slightly overpredicted the temperature in the first hour of drying and underpredicted the temperature towards the end of the drying period. Consequently, the predicted moisture ratio (MR) was underpredicted at the onset of drying and agreed with the experimental values towards the end of the drying period. The simulation results were validated using a new set of experimental results, and the suitability of the model assessed using the $ R^{2} $ (0.9790 for temperature and 0.9579 for MR) and RMSE (1.99 for temperature and 0.0698 for MR). Conclusion The model can guide the application of IRHAD in the processing of biltong and forms a theoretical basis for analysing the application of IRHAD to other food and biobased products. © The Korean Society for Agricultural Machinery 2021 |
| abstract_unstemmed |
Purpose The aim of this study was to develop a coupled heat and mass transfer model to predict the temperature and moisture content of beef during biltong processing using infrared-assisted hot air drying (IRHAD). Methods The developed model was implemented and solved using Ansys Fluent CFD software. Drying experiments conducted using an infrared-assisted hot air dryer were used to determine the moisture diffusivity, and the heat and mass transfer coefficients used in the model. The experiments were done at an infrared emitter power level of 750 W; drying air temperature of 30, 35, and 40 °C; and velocity of 1.5 and 2.5 m $ s^{−1} $. Results The simulation slightly overpredicted the temperature in the first hour of drying and underpredicted the temperature towards the end of the drying period. Consequently, the predicted moisture ratio (MR) was underpredicted at the onset of drying and agreed with the experimental values towards the end of the drying period. The simulation results were validated using a new set of experimental results, and the suitability of the model assessed using the $ R^{2} $ (0.9790 for temperature and 0.9579 for MR) and RMSE (1.99 for temperature and 0.0698 for MR). Conclusion The model can guide the application of IRHAD in the processing of biltong and forms a theoretical basis for analysing the application of IRHAD to other food and biobased products. © The Korean Society for Agricultural Machinery 2021 |
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| title_short |
A Heat and Mass Transfer Model for Predicting the Drying of Beef During Biltong Processing Using Infrared-Assisted Hot Air Drying |
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https://dx.doi.org/10.1007/s42853-021-00105-x |
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Marenya, M. O. Workneh, T. S. |
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10.1007/s42853-021-00105-x |
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2024-07-03T14:40:38.633Z |
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| score |
7.402112 |