厌氧消化1号模型(Anaerobic Digestion Model No.1,ADM1)量化表达了厌氧发酵过程中各类物质的转化过程,在研究和咨询领域获得了广泛的发展和应用,但ADM1并没有过多考虑物理化学过程,这些物化过程虽然并不直接经由微生物发生,但它们却可...厌氧消化1号模型(Anaerobic Digestion Model No.1,ADM1)量化表达了厌氧发酵过程中各类物质的转化过程,在研究和咨询领域获得了广泛的发展和应用,但ADM1并没有过多考虑物理化学过程,这些物化过程虽然并不直接经由微生物发生,但它们却可以影响生化过程。通过建立ADM1气液转换模型,并基于生物甲烷潜力(BMP)测试建立液相气体浓度变化映射函数,将多元隐性模型转化为k_(L)a的显性模型,基于对k_(L)a参数的实时测算,对序批式投料的CSTR反应器搅拌装置设置变频激励机制,提高气液转换效率,促进沼气的快速逸出。经撬装CSTR中试设备连续实验测试,该智能控制模型相比传统运行方式容积产气率提升15.5%,对提升规模化沼气工程的生产效率具有显著的指导和应用价值。基于边云协同的智能控制为规模化生物燃气项目的智慧管控提供了全新的技术范式。展开更多
The Anaerobic Digestion Model No.1(ADM1)has been modified to include enhanced kinetic parameters,which more precisely simulate methane production during the anaerobic digestion of diverse organic solid wastes.Calibrat...The Anaerobic Digestion Model No.1(ADM1)has been modified to include enhanced kinetic parameters,which more precisely simulate methane production during the anaerobic digestion of diverse organic solid wastes.Calibration and validation of the model were achieved using experimental data from batch fermentation processes.Simulations of the updated ADM1 were conducted using AQUASIM 2.0 software.Sensitivity analysis helped identify and assess the most critical kinetic parameters affecting biogas production.Key parameters such as the microorganism decay constant(d^(-1)),disintegration rate constant(d^(-1)),Monod maximum specific substrate uptake rate(gCOD/gVSS·d),and half⁃saturation constants were found to significantly influence biogas yield.The optimal values for these parameters were identified as 0.03,6.07,3.64,and 0.27,respectively.These optimized values were validated through batch experiments.The modified ADM1 successfully predicted methane production,achieving R2 values greater than 0.8 in all validation trials.Key methanogens,Methanosarcina and Methanosaeta,were identified,and their enrichment during mixed fermentation of various organic solid wastes indicated enhanced methane production via aceticlastic methanogenesis.The microbial characterization and simulations using the modified ADM1 model supported each other.展开更多
Anaerobic acidogenic fermentation with high-solid sludge is a promising method for volatile fatty acid（VFA） production to realize resource recovery. In this study, to model inhibition by free ammonia in high-solid s...Anaerobic acidogenic fermentation with high-solid sludge is a promising method for volatile fatty acid（VFA） production to realize resource recovery. In this study, to model inhibition by free ammonia in high-solid sludge fermentation, the anaerobic digestion model No. 1（ADM1） was modified to simulate the VFA generation in batch, semicontinuous and full scale sludge. The ADM1 was operated on the platform AQUASIM 2.0.Three kinds of inhibition forms, e.g., simple inhibition, Monod and non-inhibition forms,were integrated into the ADM1 and tested with the real experimental data for batch and semi-continuous fermentation, respectively. The improved particle swarm optimization technique was used for kinetic parameter estimation using the software MATLAB 7.0. In the modified ADM1, the Ksof acetate is 0.025, the km,acis 12.51, and the KI_NH3is 0.02,respectively. The results showed that the simple inhibition model could simulate the VFA generation accurately while the Monod model was the better inhibition kinetics form in semi-continuous fermentation at pH 10.0. Finally, the modified ADM1 could successfully describe the VFA generation and ammonia accumulation in a 30 m^3full-scale sludge fermentation reactor, indicating that the developed model can be applicable in high-solid sludge anaerobic fermentation.展开更多
Mathematical modeling of anaerobic digestion is a powerful tool to predict gas yields and optimize the process.The Anaerobic Digestion Model No.1(ADM1)is a widely implemented model for this purpose.However,modeling fu...Mathematical modeling of anaerobic digestion is a powerful tool to predict gas yields and optimize the process.The Anaerobic Digestion Model No.1(ADM1)is a widely implemented model for this purpose.However,modeling full-scale biogas plants is challenging due to the extensive substrate and parameter characterization required.This study describes the modification of the ADM1 through a simplification of individual process phases,characteristic components and required parameters.Consequently,the ability of the simplified model to simulate the co-digestion of grass silage and cattle slurry was evaluated using data from a full-scale biogas plant.The impacts of substrate composition(crude carbohydrate,protein and lipid concentration)and variability of carbohydrate degradability on simulation results were assessed to identify the most influential parameters.Results indicated that the simplified version was able to depict biogas and biomethane production with average model efficiencies,according to the Nash-Sutcliffe efficiency(NSE)coefficient,of 0.70 and 0.67,respectively,and was comparable to the original ADM1(average model efficiencies of 0.71 and 0.63,respectively).The variability of crude carbohydrate,protein and lipid concentration did not significantly impact biogas and biomethane output for the data sets explored.In contrast,carbohydrate degradability seemed to explain much more of the variability in the biogas and methane production.Thus,the application of simplified models provides a reliable basis for the process simulation and optimization of full-scale agricultural biogas plants.展开更多
文摘厌氧消化1号模型(Anaerobic Digestion Model No.1,ADM1)量化表达了厌氧发酵过程中各类物质的转化过程,在研究和咨询领域获得了广泛的发展和应用,但ADM1并没有过多考虑物理化学过程,这些物化过程虽然并不直接经由微生物发生,但它们却可以影响生化过程。通过建立ADM1气液转换模型,并基于生物甲烷潜力(BMP)测试建立液相气体浓度变化映射函数,将多元隐性模型转化为k_(L)a的显性模型,基于对k_(L)a参数的实时测算,对序批式投料的CSTR反应器搅拌装置设置变频激励机制,提高气液转换效率,促进沼气的快速逸出。经撬装CSTR中试设备连续实验测试,该智能控制模型相比传统运行方式容积产气率提升15.5%,对提升规模化沼气工程的生产效率具有显著的指导和应用价值。基于边云协同的智能控制为规模化生物燃气项目的智慧管控提供了全新的技术范式。
基金Sponsored by Power China Eco-Environment Group Technology Project (Grant No.ST-ZB-ZC-JY-JS-2022-25)Heilongjiang Key Research and Development Program (Grant No.GA21C025)+1 种基金Technological Project of Heilongjiang Province"the open competition mechanism to select the best candidates"Foundation of National Local Joint Engineering Research Center for Biomass Energy Development and Utilization (Grant No.2021B006).
文摘The Anaerobic Digestion Model No.1(ADM1)has been modified to include enhanced kinetic parameters,which more precisely simulate methane production during the anaerobic digestion of diverse organic solid wastes.Calibration and validation of the model were achieved using experimental data from batch fermentation processes.Simulations of the updated ADM1 were conducted using AQUASIM 2.0 software.Sensitivity analysis helped identify and assess the most critical kinetic parameters affecting biogas production.Key parameters such as the microorganism decay constant(d^(-1)),disintegration rate constant(d^(-1)),Monod maximum specific substrate uptake rate(gCOD/gVSS·d),and half⁃saturation constants were found to significantly influence biogas yield.The optimal values for these parameters were identified as 0.03,6.07,3.64,and 0.27,respectively.These optimized values were validated through batch experiments.The modified ADM1 successfully predicted methane production,achieving R2 values greater than 0.8 in all validation trials.Key methanogens,Methanosarcina and Methanosaeta,were identified,and their enrichment during mixed fermentation of various organic solid wastes indicated enhanced methane production via aceticlastic methanogenesis.The microbial characterization and simulations using the modified ADM1 model supported each other.
基金supported by the Joint Innovative R&D Program of University and Industry(No.BY2014023-03)National Key Technology R&D Program of the Ministry of Scienceand Technology(No.2014BAD24B03-02)
文摘Anaerobic acidogenic fermentation with high-solid sludge is a promising method for volatile fatty acid（VFA） production to realize resource recovery. In this study, to model inhibition by free ammonia in high-solid sludge fermentation, the anaerobic digestion model No. 1（ADM1） was modified to simulate the VFA generation in batch, semicontinuous and full scale sludge. The ADM1 was operated on the platform AQUASIM 2.0.Three kinds of inhibition forms, e.g., simple inhibition, Monod and non-inhibition forms,were integrated into the ADM1 and tested with the real experimental data for batch and semi-continuous fermentation, respectively. The improved particle swarm optimization technique was used for kinetic parameter estimation using the software MATLAB 7.0. In the modified ADM1, the Ksof acetate is 0.025, the km,acis 12.51, and the KI_NH3is 0.02,respectively. The results showed that the simple inhibition model could simulate the VFA generation accurately while the Monod model was the better inhibition kinetics form in semi-continuous fermentation at pH 10.0. Finally, the modified ADM1 could successfully describe the VFA generation and ammonia accumulation in a 30 m^3full-scale sludge fermentation reactor, indicating that the developed model can be applicable in high-solid sludge anaerobic fermentation.
基金the Teagasc Walsh Scholarship Programme(Ireland)(Ref:2021010).The input of Dr.Ciara Beausang and Dr.J J Lenehan in the study concept and design is acknowledged.
文摘Mathematical modeling of anaerobic digestion is a powerful tool to predict gas yields and optimize the process.The Anaerobic Digestion Model No.1(ADM1)is a widely implemented model for this purpose.However,modeling full-scale biogas plants is challenging due to the extensive substrate and parameter characterization required.This study describes the modification of the ADM1 through a simplification of individual process phases,characteristic components and required parameters.Consequently,the ability of the simplified model to simulate the co-digestion of grass silage and cattle slurry was evaluated using data from a full-scale biogas plant.The impacts of substrate composition(crude carbohydrate,protein and lipid concentration)and variability of carbohydrate degradability on simulation results were assessed to identify the most influential parameters.Results indicated that the simplified version was able to depict biogas and biomethane production with average model efficiencies,according to the Nash-Sutcliffe efficiency(NSE)coefficient,of 0.70 and 0.67,respectively,and was comparable to the original ADM1(average model efficiencies of 0.71 and 0.63,respectively).The variability of crude carbohydrate,protein and lipid concentration did not significantly impact biogas and biomethane output for the data sets explored.In contrast,carbohydrate degradability seemed to explain much more of the variability in the biogas and methane production.Thus,the application of simplified models provides a reliable basis for the process simulation and optimization of full-scale agricultural biogas plants.
