Research on neutron-induced fission product yields of^(232)Th is crucial for understanding the competition between symmetric and asymmetric fission in actinide nuclei.However,obtaining complete isotopic yield distribu...Research on neutron-induced fission product yields of^(232)Th is crucial for understanding the competition between symmetric and asymmetric fission in actinide nuclei.However,obtaining complete isotopic yield distributions over a wide range of neutron energies remains a challenge.In this study,a Bayesian neural network model was developed to predict the independent(IND)and cumulative fission yields of^(232)Th under neutron irradiation at various incident energies.To address the limited availability of experimental data for the analysis of IND mass distributions,we substituted mass-number-based yields with the yields of specific isotopes.Furthermore,physical phenomena or quantities,such as the odd-even effect and isospin,were introduced as constraints to enhance the physical consistency of the predictions.The impact of these constraints was evaluated using mass-chain yield distributions and their dependence on energy.Incorporating physical constraints significantly improves the prediction accuracy,yielding more reliable and physically meaningful fission yield data for nuclear physics and reactor design applications.展开更多
Alkaline pretreatment(AL)and air mixing(air)both have the potential to improve anaerobic co-digestion(Co-AD)of poultry litter with wheat straw for methane production.In this study,the effects of the combination of AL(...Alkaline pretreatment(AL)and air mixing(air)both have the potential to improve anaerobic co-digestion(Co-AD)of poultry litter with wheat straw for methane production.In this study,the effects of the combination of AL(pH 12 for 12 h)and air mixing(12 mL·d^(−1))on the Co-AD process were investigated.The substrate hydrolysis was enhanced by AL,with soluble chemical oxygen demand increased by 4.59 times and volatile fatty acids increased by 5.04 times.The cumulative methane yield in the group of Co-AD by AL integrated with air(Co-(AL+air)),being 287 mL·(g VS_(added))^(−1),was improved by 46.7%compared to the control.The cone model was found the best in simulating the methane yield kinetics with R^(2)≥0.9979 and root mean square prediction error(rMSPE)≤3.50.Co-(AL+air)had a larger hydrolysis constant k(0.14 d^(−1))and a shorter lag phaseλ(0.99 d)than the control(k=0.12 d^(−1),λ=2.06 d).The digestate improved the removal of total solids and total volatile solids by 2.0 and 2.3 times,respectively.AL facilitated substrate degradation,while air can enrich the microbial activity,together enhancing the methane generation.The results show that AL+air can be applied as an effective method to improve methane production from the Co-AD process.展开更多
基金supported by the National Natural Science Foundation of China(Nos.12247126 and 12375123)Henan Postdoctoral Foundation(No.HN2024013)the Natural Science Foundation of Henan Province(No.242300421048)。
文摘Research on neutron-induced fission product yields of^(232)Th is crucial for understanding the competition between symmetric and asymmetric fission in actinide nuclei.However,obtaining complete isotopic yield distributions over a wide range of neutron energies remains a challenge.In this study,a Bayesian neural network model was developed to predict the independent(IND)and cumulative fission yields of^(232)Th under neutron irradiation at various incident energies.To address the limited availability of experimental data for the analysis of IND mass distributions,we substituted mass-number-based yields with the yields of specific isotopes.Furthermore,physical phenomena or quantities,such as the odd-even effect and isospin,were introduced as constraints to enhance the physical consistency of the predictions.The impact of these constraints was evaluated using mass-chain yield distributions and their dependence on energy.Incorporating physical constraints significantly improves the prediction accuracy,yielding more reliable and physically meaningful fission yield data for nuclear physics and reactor design applications.
基金funded by USDA/NIFA/AFRI Applied Science and Foundational Program(2019-67021-29945)the authors want to show appreciation for the financial support provided by the United States Department of Agriculture.
文摘Alkaline pretreatment(AL)and air mixing(air)both have the potential to improve anaerobic co-digestion(Co-AD)of poultry litter with wheat straw for methane production.In this study,the effects of the combination of AL(pH 12 for 12 h)and air mixing(12 mL·d^(−1))on the Co-AD process were investigated.The substrate hydrolysis was enhanced by AL,with soluble chemical oxygen demand increased by 4.59 times and volatile fatty acids increased by 5.04 times.The cumulative methane yield in the group of Co-AD by AL integrated with air(Co-(AL+air)),being 287 mL·(g VS_(added))^(−1),was improved by 46.7%compared to the control.The cone model was found the best in simulating the methane yield kinetics with R^(2)≥0.9979 and root mean square prediction error(rMSPE)≤3.50.Co-(AL+air)had a larger hydrolysis constant k(0.14 d^(−1))and a shorter lag phaseλ(0.99 d)than the control(k=0.12 d^(−1),λ=2.06 d).The digestate improved the removal of total solids and total volatile solids by 2.0 and 2.3 times,respectively.AL facilitated substrate degradation,while air can enrich the microbial activity,together enhancing the methane generation.The results show that AL+air can be applied as an effective method to improve methane production from the Co-AD process.
