Corn stover dry matter loss effects variability for biofuel conversion facility and technology sustainability. This research seeks to understand the dynamic mechanisms of the thermal system, organic matter loss, and microbial heat generation in corn stover storage operations through system dynamics, a mathematical modeling approach, and response analysis to improve the system performance. This study considers epistemic uncertainties including cardinal temperatures of microbial respiratory activity, specific degradation rate, heat evolution per unit substrate degraded, and thermal conductivity in corn stover storage reactors. These uncertainties were managed through calibration, a process of improving the agreement between the computational and benchmark experimental results by adjusting the parameters of the model. Model calibration successfully predicted the temperature of the system as quantified by the mean absolute error, 0.6°C, relative to the experimental work. The model and experimental dry matter loss after 30 days of storage were 5.1% and 4.9 ± 0.28%. The model was further validated using additional experimental results to ensure that the model accurately represented the system. Model validation obtained a temperature mean absolute relative error of 0.9 ± 0.3°C and dry matter loss relative error of 3.1 ± 1.5%. This study presents a robust prediction of corn stover storage temperature and demonstrates that an understanding of carbon sources, microbial communities, and lag-phase evolution in bi-phasic growth are essential for the prediction of organic matter preservation in corn stover storage systems under environment’s variation.

中文翻译：

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好氧玉米秸秆储存反应器中微生物热量和有机物损失：使用集总参数动力学公式的模型验证和预测方法

玉米秸秆干物质损失影响生物燃料转化设施和技术可持续性的可变性。本研究旨在通过系统动力学、数学建模方法和响应分析来了解玉米秸秆储存操作中热系统、有机物损失和微生物产热的动态机制，以提高系统性能。本研究考虑了认知不确定性，包括微生物呼吸活动的基本温度、特定降解率、每单位降解基质的热量释放以及玉米秸秆储存反应器的热导率。这些不确定性是通过校准来管理的，校准是通过调整模型参数来提高计算和基准实验结果之间一致性的过程。模型校准成功地预测了系统的温度，由相对于实验工作的平均绝对误差 0.6°C 量化。储存 30 天后模型和实验干物质损失分别为 5.1% 和 4.9 ± 0.28%。使用额外的实验结果进一步验证了该模型，以确保该模型准确地代表了系统。模型验证获得的温度平均绝对相对误差为 0.9 ± 0.3°C，干物质损失相对误差为 3.1 ± 1.5%。本研究提供了对玉米秸秆储存温度的可靠预测，并表明了解碳源、微生物群落和双相生长中的滞后期演化对于预测环境变化下玉米秸秆储存系统中的有机质保存至关重要.