Thermal analysis in numerical thermodynamic modeling of solid fuel conversion
Abstract Detailed kinetic models dominate in combustion modeling. However, their application is often complicated by insufficient knowledge of a mechanism and reaction rates for heterophase interactions especially as applied to gasification. The novel approach using thermodynamic model of extreme in...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Kozlov, Alexander [verfasserIn] Svishchev, Denis [verfasserIn] Donskoy, Igor [verfasserIn] Keiko, Alexandre V. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2012 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Journal of thermal analysis and calorimetry - Dordrecht [u.a.] : Springer Science + Business Media B.V., 1969, 109(2012), 3 vom: 19. Aug., Seite 1311-1317 |
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| Übergeordnetes Werk: |
volume:109 ; year:2012 ; number:3 ; day:19 ; month:08 ; pages:1311-1317 |
| Links: |
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| DOI / URN: |
10.1007/s10973-012-2626-6 |
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| Katalog-ID: |
SPR015399931 |
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| 100 | 1 | |a Kozlov, Alexander |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Thermal analysis in numerical thermodynamic modeling of solid fuel conversion |
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| 520 | |a Abstract Detailed kinetic models dominate in combustion modeling. However, their application is often complicated by insufficient knowledge of a mechanism and reaction rates for heterophase interactions especially as applied to gasification. The novel approach using thermodynamic model of extreme intermediate states (MEIS) could make up an efficient alternative. MEIS is strictly deterministic and simple in structure. Along with the search for the final equilibrium, it allows partial equilibria to be found and various macroscopic phenomena to be taken into account, e.g., transport phenomena and kinetic rates. The core problem in MEIS construction is formulation of macrokinetic constrains whose form depends on the problem statement and accessible information on the process. Thermal analysis has been deployed to infer proper constraints for modeling of wooden biomass gasification. The advantage of the method consists in much higher availability of the initial information compared with detailed kinetics. Model results are in good agreement with experiment. | ||
| 650 | 4 | |a Fuel processing |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Thermodynamic modeling |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Macrokinetic constrains |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Biomass gasification |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Thermal analysis |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Svishchev, Denis |e verfasserin |4 aut | |
| 700 | 1 | |a Donskoy, Igor |e verfasserin |4 aut | |
| 700 | 1 | |a Keiko, Alexandre V. |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Journal of thermal analysis and calorimetry |d Dordrecht [u.a.] : Springer Science + Business Media B.V., 1969 |g 109(2012), 3 vom: 19. Aug., Seite 1311-1317 |w (DE-627)315295422 |w (DE-600)2017304-0 |x 1572-8943 |7 nnns |
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10.1007/s10973-012-2626-6 doi (DE-627)SPR015399931 (SPR)s10973-012-2626-6-e DE-627 ger DE-627 rakwb eng 660 ASE 35.00 bkl Kozlov, Alexander verfasserin aut Thermal analysis in numerical thermodynamic modeling of solid fuel conversion 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Detailed kinetic models dominate in combustion modeling. However, their application is often complicated by insufficient knowledge of a mechanism and reaction rates for heterophase interactions especially as applied to gasification. The novel approach using thermodynamic model of extreme intermediate states (MEIS) could make up an efficient alternative. MEIS is strictly deterministic and simple in structure. Along with the search for the final equilibrium, it allows partial equilibria to be found and various macroscopic phenomena to be taken into account, e.g., transport phenomena and kinetic rates. The core problem in MEIS construction is formulation of macrokinetic constrains whose form depends on the problem statement and accessible information on the process. Thermal analysis has been deployed to infer proper constraints for modeling of wooden biomass gasification. The advantage of the method consists in much higher availability of the initial information compared with detailed kinetics. Model results are in good agreement with experiment. Fuel processing (dpeaa)DE-He213 Thermodynamic modeling (dpeaa)DE-He213 Macrokinetic constrains (dpeaa)DE-He213 Biomass gasification (dpeaa)DE-He213 Thermal analysis (dpeaa)DE-He213 Svishchev, Denis verfasserin aut Donskoy, Igor verfasserin aut Keiko, Alexandre V. verfasserin aut Enthalten in Journal of thermal analysis and calorimetry Dordrecht [u.a.] : Springer Science + Business Media B.V., 1969 109(2012), 3 vom: 19. Aug., Seite 1311-1317 (DE-627)315295422 (DE-600)2017304-0 1572-8943 nnns volume:109 year:2012 number:3 day:19 month:08 pages:1311-1317 https://dx.doi.org/10.1007/s10973-012-2626-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA 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_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_120 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_206 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_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_4012 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 35.00 ASE AR 109 2012 3 19 08 1311-1317 |
| spelling |
10.1007/s10973-012-2626-6 doi (DE-627)SPR015399931 (SPR)s10973-012-2626-6-e DE-627 ger DE-627 rakwb eng 660 ASE 35.00 bkl Kozlov, Alexander verfasserin aut Thermal analysis in numerical thermodynamic modeling of solid fuel conversion 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Detailed kinetic models dominate in combustion modeling. However, their application is often complicated by insufficient knowledge of a mechanism and reaction rates for heterophase interactions especially as applied to gasification. The novel approach using thermodynamic model of extreme intermediate states (MEIS) could make up an efficient alternative. MEIS is strictly deterministic and simple in structure. Along with the search for the final equilibrium, it allows partial equilibria to be found and various macroscopic phenomena to be taken into account, e.g., transport phenomena and kinetic rates. The core problem in MEIS construction is formulation of macrokinetic constrains whose form depends on the problem statement and accessible information on the process. Thermal analysis has been deployed to infer proper constraints for modeling of wooden biomass gasification. The advantage of the method consists in much higher availability of the initial information compared with detailed kinetics. Model results are in good agreement with experiment. Fuel processing (dpeaa)DE-He213 Thermodynamic modeling (dpeaa)DE-He213 Macrokinetic constrains (dpeaa)DE-He213 Biomass gasification (dpeaa)DE-He213 Thermal analysis (dpeaa)DE-He213 Svishchev, Denis verfasserin aut Donskoy, Igor verfasserin aut Keiko, Alexandre V. verfasserin aut Enthalten in Journal of thermal analysis and calorimetry Dordrecht [u.a.] : Springer Science + Business Media B.V., 1969 109(2012), 3 vom: 19. Aug., Seite 1311-1317 (DE-627)315295422 (DE-600)2017304-0 1572-8943 nnns volume:109 year:2012 number:3 day:19 month:08 pages:1311-1317 https://dx.doi.org/10.1007/s10973-012-2626-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA 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_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_120 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_206 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_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_4012 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 35.00 ASE AR 109 2012 3 19 08 1311-1317 |
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10.1007/s10973-012-2626-6 doi (DE-627)SPR015399931 (SPR)s10973-012-2626-6-e DE-627 ger DE-627 rakwb eng 660 ASE 35.00 bkl Kozlov, Alexander verfasserin aut Thermal analysis in numerical thermodynamic modeling of solid fuel conversion 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Detailed kinetic models dominate in combustion modeling. However, their application is often complicated by insufficient knowledge of a mechanism and reaction rates for heterophase interactions especially as applied to gasification. The novel approach using thermodynamic model of extreme intermediate states (MEIS) could make up an efficient alternative. MEIS is strictly deterministic and simple in structure. Along with the search for the final equilibrium, it allows partial equilibria to be found and various macroscopic phenomena to be taken into account, e.g., transport phenomena and kinetic rates. The core problem in MEIS construction is formulation of macrokinetic constrains whose form depends on the problem statement and accessible information on the process. Thermal analysis has been deployed to infer proper constraints for modeling of wooden biomass gasification. The advantage of the method consists in much higher availability of the initial information compared with detailed kinetics. Model results are in good agreement with experiment. Fuel processing (dpeaa)DE-He213 Thermodynamic modeling (dpeaa)DE-He213 Macrokinetic constrains (dpeaa)DE-He213 Biomass gasification (dpeaa)DE-He213 Thermal analysis (dpeaa)DE-He213 Svishchev, Denis verfasserin aut Donskoy, Igor verfasserin aut Keiko, Alexandre V. verfasserin aut Enthalten in Journal of thermal analysis and calorimetry Dordrecht [u.a.] : Springer Science + Business Media B.V., 1969 109(2012), 3 vom: 19. Aug., Seite 1311-1317 (DE-627)315295422 (DE-600)2017304-0 1572-8943 nnns volume:109 year:2012 number:3 day:19 month:08 pages:1311-1317 https://dx.doi.org/10.1007/s10973-012-2626-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA 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_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_120 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_206 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_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_4012 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 35.00 ASE AR 109 2012 3 19 08 1311-1317 |
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10.1007/s10973-012-2626-6 doi (DE-627)SPR015399931 (SPR)s10973-012-2626-6-e DE-627 ger DE-627 rakwb eng 660 ASE 35.00 bkl Kozlov, Alexander verfasserin aut Thermal analysis in numerical thermodynamic modeling of solid fuel conversion 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Detailed kinetic models dominate in combustion modeling. However, their application is often complicated by insufficient knowledge of a mechanism and reaction rates for heterophase interactions especially as applied to gasification. The novel approach using thermodynamic model of extreme intermediate states (MEIS) could make up an efficient alternative. MEIS is strictly deterministic and simple in structure. Along with the search for the final equilibrium, it allows partial equilibria to be found and various macroscopic phenomena to be taken into account, e.g., transport phenomena and kinetic rates. The core problem in MEIS construction is formulation of macrokinetic constrains whose form depends on the problem statement and accessible information on the process. Thermal analysis has been deployed to infer proper constraints for modeling of wooden biomass gasification. The advantage of the method consists in much higher availability of the initial information compared with detailed kinetics. Model results are in good agreement with experiment. Fuel processing (dpeaa)DE-He213 Thermodynamic modeling (dpeaa)DE-He213 Macrokinetic constrains (dpeaa)DE-He213 Biomass gasification (dpeaa)DE-He213 Thermal analysis (dpeaa)DE-He213 Svishchev, Denis verfasserin aut Donskoy, Igor verfasserin aut Keiko, Alexandre V. verfasserin aut Enthalten in Journal of thermal analysis and calorimetry Dordrecht [u.a.] : Springer Science + Business Media B.V., 1969 109(2012), 3 vom: 19. Aug., Seite 1311-1317 (DE-627)315295422 (DE-600)2017304-0 1572-8943 nnns volume:109 year:2012 number:3 day:19 month:08 pages:1311-1317 https://dx.doi.org/10.1007/s10973-012-2626-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA 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_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_120 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_206 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_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_4012 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 35.00 ASE AR 109 2012 3 19 08 1311-1317 |
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10.1007/s10973-012-2626-6 doi (DE-627)SPR015399931 (SPR)s10973-012-2626-6-e DE-627 ger DE-627 rakwb eng 660 ASE 35.00 bkl Kozlov, Alexander verfasserin aut Thermal analysis in numerical thermodynamic modeling of solid fuel conversion 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Detailed kinetic models dominate in combustion modeling. However, their application is often complicated by insufficient knowledge of a mechanism and reaction rates for heterophase interactions especially as applied to gasification. The novel approach using thermodynamic model of extreme intermediate states (MEIS) could make up an efficient alternative. MEIS is strictly deterministic and simple in structure. Along with the search for the final equilibrium, it allows partial equilibria to be found and various macroscopic phenomena to be taken into account, e.g., transport phenomena and kinetic rates. The core problem in MEIS construction is formulation of macrokinetic constrains whose form depends on the problem statement and accessible information on the process. Thermal analysis has been deployed to infer proper constraints for modeling of wooden biomass gasification. The advantage of the method consists in much higher availability of the initial information compared with detailed kinetics. Model results are in good agreement with experiment. Fuel processing (dpeaa)DE-He213 Thermodynamic modeling (dpeaa)DE-He213 Macrokinetic constrains (dpeaa)DE-He213 Biomass gasification (dpeaa)DE-He213 Thermal analysis (dpeaa)DE-He213 Svishchev, Denis verfasserin aut Donskoy, Igor verfasserin aut Keiko, Alexandre V. verfasserin aut Enthalten in Journal of thermal analysis and calorimetry Dordrecht [u.a.] : Springer Science + Business Media B.V., 1969 109(2012), 3 vom: 19. Aug., Seite 1311-1317 (DE-627)315295422 (DE-600)2017304-0 1572-8943 nnns volume:109 year:2012 number:3 day:19 month:08 pages:1311-1317 https://dx.doi.org/10.1007/s10973-012-2626-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA 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_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_120 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_206 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_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_4012 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 35.00 ASE AR 109 2012 3 19 08 1311-1317 |
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Enthalten in Journal of thermal analysis and calorimetry 109(2012), 3 vom: 19. Aug., Seite 1311-1317 volume:109 year:2012 number:3 day:19 month:08 pages:1311-1317 |
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Fuel processing Thermodynamic modeling Macrokinetic constrains Biomass gasification Thermal analysis |
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Journal of thermal analysis and calorimetry |
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Kozlov, Alexander @@aut@@ Svishchev, Denis @@aut@@ Donskoy, Igor @@aut@@ Keiko, Alexandre V. @@aut@@ |
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However, their application is often complicated by insufficient knowledge of a mechanism and reaction rates for heterophase interactions especially as applied to gasification. The novel approach using thermodynamic model of extreme intermediate states (MEIS) could make up an efficient alternative. MEIS is strictly deterministic and simple in structure. Along with the search for the final equilibrium, it allows partial equilibria to be found and various macroscopic phenomena to be taken into account, e.g., transport phenomena and kinetic rates. The core problem in MEIS construction is formulation of macrokinetic constrains whose form depends on the problem statement and accessible information on the process. Thermal analysis has been deployed to infer proper constraints for modeling of wooden biomass gasification. The advantage of the method consists in much higher availability of the initial information compared with detailed kinetics. 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Kozlov, Alexander |
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Kozlov, Alexander ddc 660 bkl 35.00 misc Fuel processing misc Thermodynamic modeling misc Macrokinetic constrains misc Biomass gasification misc Thermal analysis Thermal analysis in numerical thermodynamic modeling of solid fuel conversion |
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660 ASE 35.00 bkl Thermal analysis in numerical thermodynamic modeling of solid fuel conversion Fuel processing (dpeaa)DE-He213 Thermodynamic modeling (dpeaa)DE-He213 Macrokinetic constrains (dpeaa)DE-He213 Biomass gasification (dpeaa)DE-He213 Thermal analysis (dpeaa)DE-He213 |
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ddc 660 bkl 35.00 misc Fuel processing misc Thermodynamic modeling misc Macrokinetic constrains misc Biomass gasification misc Thermal analysis |
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thermal analysis in numerical thermodynamic modeling of solid fuel conversion |
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Thermal analysis in numerical thermodynamic modeling of solid fuel conversion |
| abstract |
Abstract Detailed kinetic models dominate in combustion modeling. However, their application is often complicated by insufficient knowledge of a mechanism and reaction rates for heterophase interactions especially as applied to gasification. The novel approach using thermodynamic model of extreme intermediate states (MEIS) could make up an efficient alternative. MEIS is strictly deterministic and simple in structure. Along with the search for the final equilibrium, it allows partial equilibria to be found and various macroscopic phenomena to be taken into account, e.g., transport phenomena and kinetic rates. The core problem in MEIS construction is formulation of macrokinetic constrains whose form depends on the problem statement and accessible information on the process. Thermal analysis has been deployed to infer proper constraints for modeling of wooden biomass gasification. The advantage of the method consists in much higher availability of the initial information compared with detailed kinetics. Model results are in good agreement with experiment. |
| abstractGer |
Abstract Detailed kinetic models dominate in combustion modeling. However, their application is often complicated by insufficient knowledge of a mechanism and reaction rates for heterophase interactions especially as applied to gasification. The novel approach using thermodynamic model of extreme intermediate states (MEIS) could make up an efficient alternative. MEIS is strictly deterministic and simple in structure. Along with the search for the final equilibrium, it allows partial equilibria to be found and various macroscopic phenomena to be taken into account, e.g., transport phenomena and kinetic rates. The core problem in MEIS construction is formulation of macrokinetic constrains whose form depends on the problem statement and accessible information on the process. Thermal analysis has been deployed to infer proper constraints for modeling of wooden biomass gasification. The advantage of the method consists in much higher availability of the initial information compared with detailed kinetics. Model results are in good agreement with experiment. |
| abstract_unstemmed |
Abstract Detailed kinetic models dominate in combustion modeling. However, their application is often complicated by insufficient knowledge of a mechanism and reaction rates for heterophase interactions especially as applied to gasification. The novel approach using thermodynamic model of extreme intermediate states (MEIS) could make up an efficient alternative. MEIS is strictly deterministic and simple in structure. Along with the search for the final equilibrium, it allows partial equilibria to be found and various macroscopic phenomena to be taken into account, e.g., transport phenomena and kinetic rates. The core problem in MEIS construction is formulation of macrokinetic constrains whose form depends on the problem statement and accessible information on the process. Thermal analysis has been deployed to infer proper constraints for modeling of wooden biomass gasification. The advantage of the method consists in much higher availability of the initial information compared with detailed kinetics. Model results are in good agreement with experiment. |
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| container_issue |
3 |
| title_short |
Thermal analysis in numerical thermodynamic modeling of solid fuel conversion |
| url |
https://dx.doi.org/10.1007/s10973-012-2626-6 |
| remote_bool |
true |
| author2 |
Svishchev, Denis Donskoy, Igor Keiko, Alexandre V. |
| author2Str |
Svishchev, Denis Donskoy, Igor Keiko, Alexandre V. |
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| doi_str |
10.1007/s10973-012-2626-6 |
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2024-07-03T15:58:02.384Z |
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| score |
7.3998413 |