Relying on machine learning methods for predicting hydrogen solubility in different alcoholic solvents
There are high demands for reliable hydrogen-alcohol phase equilibria in separation and conversion-related industrial processes. Since experimental measurements cannot be directly included in the computer-aided handling of these processes, this study utilizes various computational techniques for est...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Zhou, Zongming [verfasserIn] |
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E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022transfer abstract |
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| Umfang: |
11 |
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| Übergeordnetes Werk: |
Enthalten in: External auditory canal: Inferior, posterior-inferior, and anterior canal wall overhangs - Dedhia, Kavita ELSEVIER, 2018, official journal of the International Association for Hydrogen Energy, New York, NY [u.a.] |
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| Übergeordnetes Werk: |
volume:47 ; year:2022 ; number:9 ; day:29 ; month:01 ; pages:5817-5827 ; extent:11 |
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| DOI / URN: |
10.1016/j.ijhydene.2021.11.121 |
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| 245 | 1 | 0 | |a Relying on machine learning methods for predicting hydrogen solubility in different alcoholic solvents |
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| 520 | |a There are high demands for reliable hydrogen-alcohol phase equilibria in separation and conversion-related industrial processes. Since experimental measurements cannot be directly included in the computer-aided handling of these processes, this study utilizes various computational techniques for estimating hydrogen solubility in seven alcoholic solvents (methanol, ethanol, 1-propanol, 2-propanol, allyl alcohol, 1-butanol, and furfuryl alcohol). Ranking analysis shows that the adaptive-neuro fuzzy inference system having genfis2 (ANFIS2) is the best choice for this purpose. The model predictions are in excellent agreement with the 194 laboratory measurements (RAD = 3.32%, MSE = 6.9 × 10−4, and R2 = 0.998896). Statistical uncertainty analysis confirms that the ANFIS2 model is superior to the previously proposed equations of state and empirical correlations in the literature. Simulation results confirm that 1-butanol and furfuryl alcohol has the highest and lowest hydrogen absorption tendency, respectively. Furthermore, the ANFIS2 justifies that the solubility of hydrogen in all alcohols obeys Henry's law and decreases by decreasing temperature and pressure. | ||
| 520 | |a There are high demands for reliable hydrogen-alcohol phase equilibria in separation and conversion-related industrial processes. Since experimental measurements cannot be directly included in the computer-aided handling of these processes, this study utilizes various computational techniques for estimating hydrogen solubility in seven alcoholic solvents (methanol, ethanol, 1-propanol, 2-propanol, allyl alcohol, 1-butanol, and furfuryl alcohol). Ranking analysis shows that the adaptive-neuro fuzzy inference system having genfis2 (ANFIS2) is the best choice for this purpose. The model predictions are in excellent agreement with the 194 laboratory measurements (RAD = 3.32%, MSE = 6.9 × 10−4, and R2 = 0.998896). Statistical uncertainty analysis confirms that the ANFIS2 model is superior to the previously proposed equations of state and empirical correlations in the literature. Simulation results confirm that 1-butanol and furfuryl alcohol has the highest and lowest hydrogen absorption tendency, respectively. Furthermore, the ANFIS2 justifies that the solubility of hydrogen in all alcohols obeys Henry's law and decreases by decreasing temperature and pressure. | ||
| 650 | 7 | |a Computational modeling |2 Elsevier | |
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| 700 | 1 | |a Kamrani, Elham |4 oth | |
| 700 | 1 | |a Anqi, Ali E. |4 oth | |
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10.1016/j.ijhydene.2021.11.121 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001658.pica (DE-627)ELV056638876 (ELSEVIER)S0360-3199(21)04508-0 DE-627 ger DE-627 rakwb eng 610 VZ 44.94 bkl Zhou, Zongming verfasserin aut Relying on machine learning methods for predicting hydrogen solubility in different alcoholic solvents 2022transfer abstract 11 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier There are high demands for reliable hydrogen-alcohol phase equilibria in separation and conversion-related industrial processes. Since experimental measurements cannot be directly included in the computer-aided handling of these processes, this study utilizes various computational techniques for estimating hydrogen solubility in seven alcoholic solvents (methanol, ethanol, 1-propanol, 2-propanol, allyl alcohol, 1-butanol, and furfuryl alcohol). Ranking analysis shows that the adaptive-neuro fuzzy inference system having genfis2 (ANFIS2) is the best choice for this purpose. The model predictions are in excellent agreement with the 194 laboratory measurements (RAD = 3.32%, MSE = 6.9 × 10−4, and R2 = 0.998896). Statistical uncertainty analysis confirms that the ANFIS2 model is superior to the previously proposed equations of state and empirical correlations in the literature. Simulation results confirm that 1-butanol and furfuryl alcohol has the highest and lowest hydrogen absorption tendency, respectively. Furthermore, the ANFIS2 justifies that the solubility of hydrogen in all alcohols obeys Henry's law and decreases by decreasing temperature and pressure. There are high demands for reliable hydrogen-alcohol phase equilibria in separation and conversion-related industrial processes. Since experimental measurements cannot be directly included in the computer-aided handling of these processes, this study utilizes various computational techniques for estimating hydrogen solubility in seven alcoholic solvents (methanol, ethanol, 1-propanol, 2-propanol, allyl alcohol, 1-butanol, and furfuryl alcohol). Ranking analysis shows that the adaptive-neuro fuzzy inference system having genfis2 (ANFIS2) is the best choice for this purpose. The model predictions are in excellent agreement with the 194 laboratory measurements (RAD = 3.32%, MSE = 6.9 × 10−4, and R2 = 0.998896). Statistical uncertainty analysis confirms that the ANFIS2 model is superior to the previously proposed equations of state and empirical correlations in the literature. Simulation results confirm that 1-butanol and furfuryl alcohol has the highest and lowest hydrogen absorption tendency, respectively. Furthermore, the ANFIS2 justifies that the solubility of hydrogen in all alcohols obeys Henry's law and decreases by decreasing temperature and pressure. Computational modeling Elsevier Adaptive-neuro fuzzy inference system Elsevier Phase equilibria Elsevier Hydrogen-alcohol mixtures Elsevier Henry law Elsevier Nourani, Pejman oth Karimi, Mehdi oth Kamrani, Elham oth Anqi, Ali E. oth Enthalten in Elsevier Dedhia, Kavita ELSEVIER External auditory canal: Inferior, posterior-inferior, and anterior canal wall overhangs 2018 official journal of the International Association for Hydrogen Energy New York, NY [u.a.] (DE-627)ELV000127019 volume:47 year:2022 number:9 day:29 month:01 pages:5817-5827 extent:11 https://doi.org/10.1016/j.ijhydene.2021.11.121 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.94 Hals-Nasen-Ohrenheilkunde VZ AR 47 2022 9 29 0129 5817-5827 11 |
| spelling |
10.1016/j.ijhydene.2021.11.121 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001658.pica (DE-627)ELV056638876 (ELSEVIER)S0360-3199(21)04508-0 DE-627 ger DE-627 rakwb eng 610 VZ 44.94 bkl Zhou, Zongming verfasserin aut Relying on machine learning methods for predicting hydrogen solubility in different alcoholic solvents 2022transfer abstract 11 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier There are high demands for reliable hydrogen-alcohol phase equilibria in separation and conversion-related industrial processes. Since experimental measurements cannot be directly included in the computer-aided handling of these processes, this study utilizes various computational techniques for estimating hydrogen solubility in seven alcoholic solvents (methanol, ethanol, 1-propanol, 2-propanol, allyl alcohol, 1-butanol, and furfuryl alcohol). Ranking analysis shows that the adaptive-neuro fuzzy inference system having genfis2 (ANFIS2) is the best choice for this purpose. The model predictions are in excellent agreement with the 194 laboratory measurements (RAD = 3.32%, MSE = 6.9 × 10−4, and R2 = 0.998896). Statistical uncertainty analysis confirms that the ANFIS2 model is superior to the previously proposed equations of state and empirical correlations in the literature. Simulation results confirm that 1-butanol and furfuryl alcohol has the highest and lowest hydrogen absorption tendency, respectively. Furthermore, the ANFIS2 justifies that the solubility of hydrogen in all alcohols obeys Henry's law and decreases by decreasing temperature and pressure. There are high demands for reliable hydrogen-alcohol phase equilibria in separation and conversion-related industrial processes. Since experimental measurements cannot be directly included in the computer-aided handling of these processes, this study utilizes various computational techniques for estimating hydrogen solubility in seven alcoholic solvents (methanol, ethanol, 1-propanol, 2-propanol, allyl alcohol, 1-butanol, and furfuryl alcohol). Ranking analysis shows that the adaptive-neuro fuzzy inference system having genfis2 (ANFIS2) is the best choice for this purpose. The model predictions are in excellent agreement with the 194 laboratory measurements (RAD = 3.32%, MSE = 6.9 × 10−4, and R2 = 0.998896). Statistical uncertainty analysis confirms that the ANFIS2 model is superior to the previously proposed equations of state and empirical correlations in the literature. Simulation results confirm that 1-butanol and furfuryl alcohol has the highest and lowest hydrogen absorption tendency, respectively. Furthermore, the ANFIS2 justifies that the solubility of hydrogen in all alcohols obeys Henry's law and decreases by decreasing temperature and pressure. Computational modeling Elsevier Adaptive-neuro fuzzy inference system Elsevier Phase equilibria Elsevier Hydrogen-alcohol mixtures Elsevier Henry law Elsevier Nourani, Pejman oth Karimi, Mehdi oth Kamrani, Elham oth Anqi, Ali E. oth Enthalten in Elsevier Dedhia, Kavita ELSEVIER External auditory canal: Inferior, posterior-inferior, and anterior canal wall overhangs 2018 official journal of the International Association for Hydrogen Energy New York, NY [u.a.] (DE-627)ELV000127019 volume:47 year:2022 number:9 day:29 month:01 pages:5817-5827 extent:11 https://doi.org/10.1016/j.ijhydene.2021.11.121 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.94 Hals-Nasen-Ohrenheilkunde VZ AR 47 2022 9 29 0129 5817-5827 11 |
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10.1016/j.ijhydene.2021.11.121 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001658.pica (DE-627)ELV056638876 (ELSEVIER)S0360-3199(21)04508-0 DE-627 ger DE-627 rakwb eng 610 VZ 44.94 bkl Zhou, Zongming verfasserin aut Relying on machine learning methods for predicting hydrogen solubility in different alcoholic solvents 2022transfer abstract 11 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier There are high demands for reliable hydrogen-alcohol phase equilibria in separation and conversion-related industrial processes. Since experimental measurements cannot be directly included in the computer-aided handling of these processes, this study utilizes various computational techniques for estimating hydrogen solubility in seven alcoholic solvents (methanol, ethanol, 1-propanol, 2-propanol, allyl alcohol, 1-butanol, and furfuryl alcohol). Ranking analysis shows that the adaptive-neuro fuzzy inference system having genfis2 (ANFIS2) is the best choice for this purpose. The model predictions are in excellent agreement with the 194 laboratory measurements (RAD = 3.32%, MSE = 6.9 × 10−4, and R2 = 0.998896). Statistical uncertainty analysis confirms that the ANFIS2 model is superior to the previously proposed equations of state and empirical correlations in the literature. Simulation results confirm that 1-butanol and furfuryl alcohol has the highest and lowest hydrogen absorption tendency, respectively. Furthermore, the ANFIS2 justifies that the solubility of hydrogen in all alcohols obeys Henry's law and decreases by decreasing temperature and pressure. There are high demands for reliable hydrogen-alcohol phase equilibria in separation and conversion-related industrial processes. Since experimental measurements cannot be directly included in the computer-aided handling of these processes, this study utilizes various computational techniques for estimating hydrogen solubility in seven alcoholic solvents (methanol, ethanol, 1-propanol, 2-propanol, allyl alcohol, 1-butanol, and furfuryl alcohol). Ranking analysis shows that the adaptive-neuro fuzzy inference system having genfis2 (ANFIS2) is the best choice for this purpose. The model predictions are in excellent agreement with the 194 laboratory measurements (RAD = 3.32%, MSE = 6.9 × 10−4, and R2 = 0.998896). Statistical uncertainty analysis confirms that the ANFIS2 model is superior to the previously proposed equations of state and empirical correlations in the literature. Simulation results confirm that 1-butanol and furfuryl alcohol has the highest and lowest hydrogen absorption tendency, respectively. Furthermore, the ANFIS2 justifies that the solubility of hydrogen in all alcohols obeys Henry's law and decreases by decreasing temperature and pressure. Computational modeling Elsevier Adaptive-neuro fuzzy inference system Elsevier Phase equilibria Elsevier Hydrogen-alcohol mixtures Elsevier Henry law Elsevier Nourani, Pejman oth Karimi, Mehdi oth Kamrani, Elham oth Anqi, Ali E. oth Enthalten in Elsevier Dedhia, Kavita ELSEVIER External auditory canal: Inferior, posterior-inferior, and anterior canal wall overhangs 2018 official journal of the International Association for Hydrogen Energy New York, NY [u.a.] (DE-627)ELV000127019 volume:47 year:2022 number:9 day:29 month:01 pages:5817-5827 extent:11 https://doi.org/10.1016/j.ijhydene.2021.11.121 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.94 Hals-Nasen-Ohrenheilkunde VZ AR 47 2022 9 29 0129 5817-5827 11 |
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10.1016/j.ijhydene.2021.11.121 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001658.pica (DE-627)ELV056638876 (ELSEVIER)S0360-3199(21)04508-0 DE-627 ger DE-627 rakwb eng 610 VZ 44.94 bkl Zhou, Zongming verfasserin aut Relying on machine learning methods for predicting hydrogen solubility in different alcoholic solvents 2022transfer abstract 11 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier There are high demands for reliable hydrogen-alcohol phase equilibria in separation and conversion-related industrial processes. Since experimental measurements cannot be directly included in the computer-aided handling of these processes, this study utilizes various computational techniques for estimating hydrogen solubility in seven alcoholic solvents (methanol, ethanol, 1-propanol, 2-propanol, allyl alcohol, 1-butanol, and furfuryl alcohol). Ranking analysis shows that the adaptive-neuro fuzzy inference system having genfis2 (ANFIS2) is the best choice for this purpose. The model predictions are in excellent agreement with the 194 laboratory measurements (RAD = 3.32%, MSE = 6.9 × 10−4, and R2 = 0.998896). Statistical uncertainty analysis confirms that the ANFIS2 model is superior to the previously proposed equations of state and empirical correlations in the literature. Simulation results confirm that 1-butanol and furfuryl alcohol has the highest and lowest hydrogen absorption tendency, respectively. Furthermore, the ANFIS2 justifies that the solubility of hydrogen in all alcohols obeys Henry's law and decreases by decreasing temperature and pressure. There are high demands for reliable hydrogen-alcohol phase equilibria in separation and conversion-related industrial processes. Since experimental measurements cannot be directly included in the computer-aided handling of these processes, this study utilizes various computational techniques for estimating hydrogen solubility in seven alcoholic solvents (methanol, ethanol, 1-propanol, 2-propanol, allyl alcohol, 1-butanol, and furfuryl alcohol). Ranking analysis shows that the adaptive-neuro fuzzy inference system having genfis2 (ANFIS2) is the best choice for this purpose. The model predictions are in excellent agreement with the 194 laboratory measurements (RAD = 3.32%, MSE = 6.9 × 10−4, and R2 = 0.998896). Statistical uncertainty analysis confirms that the ANFIS2 model is superior to the previously proposed equations of state and empirical correlations in the literature. Simulation results confirm that 1-butanol and furfuryl alcohol has the highest and lowest hydrogen absorption tendency, respectively. Furthermore, the ANFIS2 justifies that the solubility of hydrogen in all alcohols obeys Henry's law and decreases by decreasing temperature and pressure. Computational modeling Elsevier Adaptive-neuro fuzzy inference system Elsevier Phase equilibria Elsevier Hydrogen-alcohol mixtures Elsevier Henry law Elsevier Nourani, Pejman oth Karimi, Mehdi oth Kamrani, Elham oth Anqi, Ali E. oth Enthalten in Elsevier Dedhia, Kavita ELSEVIER External auditory canal: Inferior, posterior-inferior, and anterior canal wall overhangs 2018 official journal of the International Association for Hydrogen Energy New York, NY [u.a.] (DE-627)ELV000127019 volume:47 year:2022 number:9 day:29 month:01 pages:5817-5827 extent:11 https://doi.org/10.1016/j.ijhydene.2021.11.121 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.94 Hals-Nasen-Ohrenheilkunde VZ AR 47 2022 9 29 0129 5817-5827 11 |
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10.1016/j.ijhydene.2021.11.121 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001658.pica (DE-627)ELV056638876 (ELSEVIER)S0360-3199(21)04508-0 DE-627 ger DE-627 rakwb eng 610 VZ 44.94 bkl Zhou, Zongming verfasserin aut Relying on machine learning methods for predicting hydrogen solubility in different alcoholic solvents 2022transfer abstract 11 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier There are high demands for reliable hydrogen-alcohol phase equilibria in separation and conversion-related industrial processes. Since experimental measurements cannot be directly included in the computer-aided handling of these processes, this study utilizes various computational techniques for estimating hydrogen solubility in seven alcoholic solvents (methanol, ethanol, 1-propanol, 2-propanol, allyl alcohol, 1-butanol, and furfuryl alcohol). Ranking analysis shows that the adaptive-neuro fuzzy inference system having genfis2 (ANFIS2) is the best choice for this purpose. The model predictions are in excellent agreement with the 194 laboratory measurements (RAD = 3.32%, MSE = 6.9 × 10−4, and R2 = 0.998896). Statistical uncertainty analysis confirms that the ANFIS2 model is superior to the previously proposed equations of state and empirical correlations in the literature. Simulation results confirm that 1-butanol and furfuryl alcohol has the highest and lowest hydrogen absorption tendency, respectively. Furthermore, the ANFIS2 justifies that the solubility of hydrogen in all alcohols obeys Henry's law and decreases by decreasing temperature and pressure. There are high demands for reliable hydrogen-alcohol phase equilibria in separation and conversion-related industrial processes. Since experimental measurements cannot be directly included in the computer-aided handling of these processes, this study utilizes various computational techniques for estimating hydrogen solubility in seven alcoholic solvents (methanol, ethanol, 1-propanol, 2-propanol, allyl alcohol, 1-butanol, and furfuryl alcohol). Ranking analysis shows that the adaptive-neuro fuzzy inference system having genfis2 (ANFIS2) is the best choice for this purpose. The model predictions are in excellent agreement with the 194 laboratory measurements (RAD = 3.32%, MSE = 6.9 × 10−4, and R2 = 0.998896). Statistical uncertainty analysis confirms that the ANFIS2 model is superior to the previously proposed equations of state and empirical correlations in the literature. Simulation results confirm that 1-butanol and furfuryl alcohol has the highest and lowest hydrogen absorption tendency, respectively. Furthermore, the ANFIS2 justifies that the solubility of hydrogen in all alcohols obeys Henry's law and decreases by decreasing temperature and pressure. Computational modeling Elsevier Adaptive-neuro fuzzy inference system Elsevier Phase equilibria Elsevier Hydrogen-alcohol mixtures Elsevier Henry law Elsevier Nourani, Pejman oth Karimi, Mehdi oth Kamrani, Elham oth Anqi, Ali E. oth Enthalten in Elsevier Dedhia, Kavita ELSEVIER External auditory canal: Inferior, posterior-inferior, and anterior canal wall overhangs 2018 official journal of the International Association for Hydrogen Energy New York, NY [u.a.] (DE-627)ELV000127019 volume:47 year:2022 number:9 day:29 month:01 pages:5817-5827 extent:11 https://doi.org/10.1016/j.ijhydene.2021.11.121 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.94 Hals-Nasen-Ohrenheilkunde VZ AR 47 2022 9 29 0129 5817-5827 11 |
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Enthalten in External auditory canal: Inferior, posterior-inferior, and anterior canal wall overhangs New York, NY [u.a.] volume:47 year:2022 number:9 day:29 month:01 pages:5817-5827 extent:11 |
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Enthalten in External auditory canal: Inferior, posterior-inferior, and anterior canal wall overhangs New York, NY [u.a.] volume:47 year:2022 number:9 day:29 month:01 pages:5817-5827 extent:11 |
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relying on machine learning methods for predicting hydrogen solubility in different alcoholic solvents |
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Relying on machine learning methods for predicting hydrogen solubility in different alcoholic solvents |
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There are high demands for reliable hydrogen-alcohol phase equilibria in separation and conversion-related industrial processes. Since experimental measurements cannot be directly included in the computer-aided handling of these processes, this study utilizes various computational techniques for estimating hydrogen solubility in seven alcoholic solvents (methanol, ethanol, 1-propanol, 2-propanol, allyl alcohol, 1-butanol, and furfuryl alcohol). Ranking analysis shows that the adaptive-neuro fuzzy inference system having genfis2 (ANFIS2) is the best choice for this purpose. The model predictions are in excellent agreement with the 194 laboratory measurements (RAD = 3.32%, MSE = 6.9 × 10−4, and R2 = 0.998896). Statistical uncertainty analysis confirms that the ANFIS2 model is superior to the previously proposed equations of state and empirical correlations in the literature. Simulation results confirm that 1-butanol and furfuryl alcohol has the highest and lowest hydrogen absorption tendency, respectively. Furthermore, the ANFIS2 justifies that the solubility of hydrogen in all alcohols obeys Henry's law and decreases by decreasing temperature and pressure. |
| abstractGer |
There are high demands for reliable hydrogen-alcohol phase equilibria in separation and conversion-related industrial processes. Since experimental measurements cannot be directly included in the computer-aided handling of these processes, this study utilizes various computational techniques for estimating hydrogen solubility in seven alcoholic solvents (methanol, ethanol, 1-propanol, 2-propanol, allyl alcohol, 1-butanol, and furfuryl alcohol). Ranking analysis shows that the adaptive-neuro fuzzy inference system having genfis2 (ANFIS2) is the best choice for this purpose. The model predictions are in excellent agreement with the 194 laboratory measurements (RAD = 3.32%, MSE = 6.9 × 10−4, and R2 = 0.998896). Statistical uncertainty analysis confirms that the ANFIS2 model is superior to the previously proposed equations of state and empirical correlations in the literature. Simulation results confirm that 1-butanol and furfuryl alcohol has the highest and lowest hydrogen absorption tendency, respectively. Furthermore, the ANFIS2 justifies that the solubility of hydrogen in all alcohols obeys Henry's law and decreases by decreasing temperature and pressure. |
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There are high demands for reliable hydrogen-alcohol phase equilibria in separation and conversion-related industrial processes. Since experimental measurements cannot be directly included in the computer-aided handling of these processes, this study utilizes various computational techniques for estimating hydrogen solubility in seven alcoholic solvents (methanol, ethanol, 1-propanol, 2-propanol, allyl alcohol, 1-butanol, and furfuryl alcohol). Ranking analysis shows that the adaptive-neuro fuzzy inference system having genfis2 (ANFIS2) is the best choice for this purpose. The model predictions are in excellent agreement with the 194 laboratory measurements (RAD = 3.32%, MSE = 6.9 × 10−4, and R2 = 0.998896). Statistical uncertainty analysis confirms that the ANFIS2 model is superior to the previously proposed equations of state and empirical correlations in the literature. Simulation results confirm that 1-butanol and furfuryl alcohol has the highest and lowest hydrogen absorption tendency, respectively. Furthermore, the ANFIS2 justifies that the solubility of hydrogen in all alcohols obeys Henry's law and decreases by decreasing temperature and pressure. |
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Nourani, Pejman Karimi, Mehdi Kamrani, Elham Anqi, Ali E. |
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