Prediction of void fraction and minimum fluidization velocity of a binary mixture of particles: Bed material and fuel particles

For operational control and design of a fluidized bed reactor containing different types of solid particles, the bed void fraction and minimum fluidization velocity are vital parameters. This paper demonstrates a method for predicting the void fraction and minimum fluidization velocity of different...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Agu, Cornelius Emeka [verfasserIn] Pfeifer, Christoph [verfasserIn] Moldestad, Britt M.E. [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Schlagwörter:	Binary mixture Biomass Void fraction Segregation Fluidized bed

Übergeordnetes Werk:	Enthalten in: Powder technology - Amsterdam [u.a.] : Elsevier Science, 1967, 349, Seite 99-107
Übergeordnetes Werk:	volume:349 ; pages:99-107

DOI / URN:	10.1016/j.powtec.2019.03.027

Katalog-ID:	ELV002120550

Internformat


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245	1	0	\|a Prediction of void fraction and minimum fluidization velocity of a binary mixture of particles: Bed material and fuel particles
264		1	\|c 2019
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520			\|a For operational control and design of a fluidized bed reactor containing different types of solid particles, the bed void fraction and minimum fluidization velocity are vital parameters. This paper demonstrates a method for predicting the void fraction and minimum fluidization velocity of different binary mixtures of particles with improved accuracy. A new model for predicting the void fraction is presented. This model is non-linear and continuous, and it is developed by introducing a packing factor and establishing a mass balance between the solid phases in the packing environment. The results show that the model can accurately predict the void fraction of a binary mixture where the particles are well mixed, partially mixed or segregated. Using this void fraction model and the Ergun equation of pressure drop, the minimum fluidization velocity can be predicted with mean errors of 15.2% for a mixture of two inert materials and 7.0% for a mixture of biomass and inert particles.
650		4	\|a Binary mixture
650		4	\|a Biomass
650		4	\|a Void fraction
650		4	\|a Segregation
650		4	\|a Fluidized bed
700	1		\|a Pfeifer, Christoph \|e verfasserin \|4 aut
700	1		\|a Moldestad, Britt M.E. \|e verfasserin \|4 aut
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matchkey_str	article:00325910:2019----::rdcinfodrcinnmnmmliiaineoiyfbnrmxuefatce
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publishDate	2019
allfields	10.1016/j.powtec.2019.03.027 doi (DE-627)ELV002120550 (ELSEVIER)S0032-5910(19)30194-9 DE-627 ger DE-627 rda eng 660 DE-600 58.10 bkl 52.77 bkl Agu, Cornelius Emeka verfasserin (orcid)0000-0002-5339-9794 aut Prediction of void fraction and minimum fluidization velocity of a binary mixture of particles: Bed material and fuel particles 2019 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier For operational control and design of a fluidized bed reactor containing different types of solid particles, the bed void fraction and minimum fluidization velocity are vital parameters. This paper demonstrates a method for predicting the void fraction and minimum fluidization velocity of different binary mixtures of particles with improved accuracy. A new model for predicting the void fraction is presented. This model is non-linear and continuous, and it is developed by introducing a packing factor and establishing a mass balance between the solid phases in the packing environment. The results show that the model can accurately predict the void fraction of a binary mixture where the particles are well mixed, partially mixed or segregated. Using this void fraction model and the Ergun equation of pressure drop, the minimum fluidization velocity can be predicted with mean errors of 15.2% for a mixture of two inert materials and 7.0% for a mixture of biomass and inert particles. Binary mixture Biomass Void fraction Segregation Fluidized bed Pfeifer, Christoph verfasserin aut Moldestad, Britt M.E. verfasserin aut Enthalten in Powder technology Amsterdam [u.a.] : Elsevier Science, 1967 349, Seite 99-107 Online-Ressource (DE-627)320599019 (DE-600)2019938-7 (DE-576)098474278 0032-5910 nnns volume:349 pages:99-107 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 58.10 Verfahrenstechnik: Allgemeines 52.77 Urformen AR 349 99-107
spelling	10.1016/j.powtec.2019.03.027 doi (DE-627)ELV002120550 (ELSEVIER)S0032-5910(19)30194-9 DE-627 ger DE-627 rda eng 660 DE-600 58.10 bkl 52.77 bkl Agu, Cornelius Emeka verfasserin (orcid)0000-0002-5339-9794 aut Prediction of void fraction and minimum fluidization velocity of a binary mixture of particles: Bed material and fuel particles 2019 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier For operational control and design of a fluidized bed reactor containing different types of solid particles, the bed void fraction and minimum fluidization velocity are vital parameters. This paper demonstrates a method for predicting the void fraction and minimum fluidization velocity of different binary mixtures of particles with improved accuracy. A new model for predicting the void fraction is presented. This model is non-linear and continuous, and it is developed by introducing a packing factor and establishing a mass balance between the solid phases in the packing environment. The results show that the model can accurately predict the void fraction of a binary mixture where the particles are well mixed, partially mixed or segregated. Using this void fraction model and the Ergun equation of pressure drop, the minimum fluidization velocity can be predicted with mean errors of 15.2% for a mixture of two inert materials and 7.0% for a mixture of biomass and inert particles. Binary mixture Biomass Void fraction Segregation Fluidized bed Pfeifer, Christoph verfasserin aut Moldestad, Britt M.E. verfasserin aut Enthalten in Powder technology Amsterdam [u.a.] : Elsevier Science, 1967 349, Seite 99-107 Online-Ressource (DE-627)320599019 (DE-600)2019938-7 (DE-576)098474278 0032-5910 nnns volume:349 pages:99-107 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 58.10 Verfahrenstechnik: Allgemeines 52.77 Urformen AR 349 99-107
allfields_unstemmed	10.1016/j.powtec.2019.03.027 doi (DE-627)ELV002120550 (ELSEVIER)S0032-5910(19)30194-9 DE-627 ger DE-627 rda eng 660 DE-600 58.10 bkl 52.77 bkl Agu, Cornelius Emeka verfasserin (orcid)0000-0002-5339-9794 aut Prediction of void fraction and minimum fluidization velocity of a binary mixture of particles: Bed material and fuel particles 2019 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier For operational control and design of a fluidized bed reactor containing different types of solid particles, the bed void fraction and minimum fluidization velocity are vital parameters. This paper demonstrates a method for predicting the void fraction and minimum fluidization velocity of different binary mixtures of particles with improved accuracy. A new model for predicting the void fraction is presented. This model is non-linear and continuous, and it is developed by introducing a packing factor and establishing a mass balance between the solid phases in the packing environment. The results show that the model can accurately predict the void fraction of a binary mixture where the particles are well mixed, partially mixed or segregated. Using this void fraction model and the Ergun equation of pressure drop, the minimum fluidization velocity can be predicted with mean errors of 15.2% for a mixture of two inert materials and 7.0% for a mixture of biomass and inert particles. Binary mixture Biomass Void fraction Segregation Fluidized bed Pfeifer, Christoph verfasserin aut Moldestad, Britt M.E. verfasserin aut Enthalten in Powder technology Amsterdam [u.a.] : Elsevier Science, 1967 349, Seite 99-107 Online-Ressource (DE-627)320599019 (DE-600)2019938-7 (DE-576)098474278 0032-5910 nnns volume:349 pages:99-107 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 58.10 Verfahrenstechnik: Allgemeines 52.77 Urformen AR 349 99-107
allfieldsGer	10.1016/j.powtec.2019.03.027 doi (DE-627)ELV002120550 (ELSEVIER)S0032-5910(19)30194-9 DE-627 ger DE-627 rda eng 660 DE-600 58.10 bkl 52.77 bkl Agu, Cornelius Emeka verfasserin (orcid)0000-0002-5339-9794 aut Prediction of void fraction and minimum fluidization velocity of a binary mixture of particles: Bed material and fuel particles 2019 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier For operational control and design of a fluidized bed reactor containing different types of solid particles, the bed void fraction and minimum fluidization velocity are vital parameters. This paper demonstrates a method for predicting the void fraction and minimum fluidization velocity of different binary mixtures of particles with improved accuracy. A new model for predicting the void fraction is presented. This model is non-linear and continuous, and it is developed by introducing a packing factor and establishing a mass balance between the solid phases in the packing environment. The results show that the model can accurately predict the void fraction of a binary mixture where the particles are well mixed, partially mixed or segregated. Using this void fraction model and the Ergun equation of pressure drop, the minimum fluidization velocity can be predicted with mean errors of 15.2% for a mixture of two inert materials and 7.0% for a mixture of biomass and inert particles. Binary mixture Biomass Void fraction Segregation Fluidized bed Pfeifer, Christoph verfasserin aut Moldestad, Britt M.E. verfasserin aut Enthalten in Powder technology Amsterdam [u.a.] : Elsevier Science, 1967 349, Seite 99-107 Online-Ressource (DE-627)320599019 (DE-600)2019938-7 (DE-576)098474278 0032-5910 nnns volume:349 pages:99-107 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 58.10 Verfahrenstechnik: Allgemeines 52.77 Urformen AR 349 99-107
allfieldsSound	10.1016/j.powtec.2019.03.027 doi (DE-627)ELV002120550 (ELSEVIER)S0032-5910(19)30194-9 DE-627 ger DE-627 rda eng 660 DE-600 58.10 bkl 52.77 bkl Agu, Cornelius Emeka verfasserin (orcid)0000-0002-5339-9794 aut Prediction of void fraction and minimum fluidization velocity of a binary mixture of particles: Bed material and fuel particles 2019 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier For operational control and design of a fluidized bed reactor containing different types of solid particles, the bed void fraction and minimum fluidization velocity are vital parameters. This paper demonstrates a method for predicting the void fraction and minimum fluidization velocity of different binary mixtures of particles with improved accuracy. A new model for predicting the void fraction is presented. This model is non-linear and continuous, and it is developed by introducing a packing factor and establishing a mass balance between the solid phases in the packing environment. The results show that the model can accurately predict the void fraction of a binary mixture where the particles are well mixed, partially mixed or segregated. Using this void fraction model and the Ergun equation of pressure drop, the minimum fluidization velocity can be predicted with mean errors of 15.2% for a mixture of two inert materials and 7.0% for a mixture of biomass and inert particles. Binary mixture Biomass Void fraction Segregation Fluidized bed Pfeifer, Christoph verfasserin aut Moldestad, Britt M.E. verfasserin aut Enthalten in Powder technology Amsterdam [u.a.] : Elsevier Science, 1967 349, Seite 99-107 Online-Ressource (DE-627)320599019 (DE-600)2019938-7 (DE-576)098474278 0032-5910 nnns volume:349 pages:99-107 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 58.10 Verfahrenstechnik: Allgemeines 52.77 Urformen AR 349 99-107
language	English
source	Enthalten in Powder technology 349, Seite 99-107 volume:349 pages:99-107
sourceStr	Enthalten in Powder technology 349, Seite 99-107 volume:349 pages:99-107
format_phy_str_mv	Article
bklname	Verfahrenstechnik: Allgemeines Urformen
institution	findex.gbv.de
topic_facet	Binary mixture Biomass Void fraction Segregation Fluidized bed
dewey-raw	660
isfreeaccess_bool	false
container_title	Powder technology
authorswithroles_txt_mv	Agu, Cornelius Emeka @@aut@@ Pfeifer, Christoph @@aut@@ Moldestad, Britt M.E. @@aut@@
publishDateDaySort_date	2019-01-01T00:00:00Z
hierarchy_top_id	320599019
dewey-sort	3660
id	ELV002120550
language_de	englisch
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author	Agu, Cornelius Emeka
spellingShingle	Agu, Cornelius Emeka ddc 660 bkl 58.10 bkl 52.77 misc Binary mixture misc Biomass misc Void fraction misc Segregation misc Fluidized bed Prediction of void fraction and minimum fluidization velocity of a binary mixture of particles: Bed material and fuel particles
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topic_title	660 DE-600 58.10 bkl 52.77 bkl Prediction of void fraction and minimum fluidization velocity of a binary mixture of particles: Bed material and fuel particles Binary mixture Biomass Void fraction Segregation Fluidized bed
topic	ddc 660 bkl 58.10 bkl 52.77 misc Binary mixture misc Biomass misc Void fraction misc Segregation misc Fluidized bed
topic_unstemmed	ddc 660 bkl 58.10 bkl 52.77 misc Binary mixture misc Biomass misc Void fraction misc Segregation misc Fluidized bed
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title	Prediction of void fraction and minimum fluidization velocity of a binary mixture of particles: Bed material and fuel particles
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title_full	Prediction of void fraction and minimum fluidization velocity of a binary mixture of particles: Bed material and fuel particles
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author_browse	Agu, Cornelius Emeka Pfeifer, Christoph Moldestad, Britt M.E.
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title_sort	prediction of void fraction and minimum fluidization velocity of a binary mixture of particles: bed material and fuel particles
title_auth	Prediction of void fraction and minimum fluidization velocity of a binary mixture of particles: Bed material and fuel particles
abstract	For operational control and design of a fluidized bed reactor containing different types of solid particles, the bed void fraction and minimum fluidization velocity are vital parameters. This paper demonstrates a method for predicting the void fraction and minimum fluidization velocity of different binary mixtures of particles with improved accuracy. A new model for predicting the void fraction is presented. This model is non-linear and continuous, and it is developed by introducing a packing factor and establishing a mass balance between the solid phases in the packing environment. The results show that the model can accurately predict the void fraction of a binary mixture where the particles are well mixed, partially mixed or segregated. Using this void fraction model and the Ergun equation of pressure drop, the minimum fluidization velocity can be predicted with mean errors of 15.2% for a mixture of two inert materials and 7.0% for a mixture of biomass and inert particles.
abstractGer	For operational control and design of a fluidized bed reactor containing different types of solid particles, the bed void fraction and minimum fluidization velocity are vital parameters. This paper demonstrates a method for predicting the void fraction and minimum fluidization velocity of different binary mixtures of particles with improved accuracy. A new model for predicting the void fraction is presented. This model is non-linear and continuous, and it is developed by introducing a packing factor and establishing a mass balance between the solid phases in the packing environment. The results show that the model can accurately predict the void fraction of a binary mixture where the particles are well mixed, partially mixed or segregated. Using this void fraction model and the Ergun equation of pressure drop, the minimum fluidization velocity can be predicted with mean errors of 15.2% for a mixture of two inert materials and 7.0% for a mixture of biomass and inert particles.
abstract_unstemmed	For operational control and design of a fluidized bed reactor containing different types of solid particles, the bed void fraction and minimum fluidization velocity are vital parameters. This paper demonstrates a method for predicting the void fraction and minimum fluidization velocity of different binary mixtures of particles with improved accuracy. A new model for predicting the void fraction is presented. This model is non-linear and continuous, and it is developed by introducing a packing factor and establishing a mass balance between the solid phases in the packing environment. The results show that the model can accurately predict the void fraction of a binary mixture where the particles are well mixed, partially mixed or segregated. Using this void fraction model and the Ergun equation of pressure drop, the minimum fluidization velocity can be predicted with mean errors of 15.2% for a mixture of two inert materials and 7.0% for a mixture of biomass and inert particles.
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title_short	Prediction of void fraction and minimum fluidization velocity of a binary mixture of particles: Bed material and fuel particles
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up_date	2024-07-06T23:41:03.299Z
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Prediction of void fraction and minimum fluidization velocity of a binary mixture of particles: Bed material and fuel particles

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