首页|期刊导航|华中科技大学学报(自然科学版)|通风管道过滤器微波灭菌系统的灭菌性能预测

通风管道过滤器微波灭菌系统的灭菌性能预测OA

Disinfection performance prediction for ventilation duct filter microwave disinfection system

中文摘要英文摘要

针对微波灭菌过程的复杂性,提出一种基于温度的灭菌性能预测方法.首先,建立复合过滤器在微波场下的温升特性数值模型,得到复合过滤器在微波场下的温升过程;然后,结合灭菌率与温度的关系模型,实现对通风管道过滤器微波灭菌系统的灭菌性能预测;最后,依据实测数据对数值模型的有效性和准确性进行了验证.结果表明:当微波功率分别为600W和400W时,复合过滤器上各测点的平均温度最终稳定值模拟值与实测值的平均绝对误差分别为0.9℃和2.4℃;根据模拟温度与实测温度预测计算的灭菌率的平均绝对误差分别为0.2%和1.2%;所建立的数值模型对复合过滤器在微波场下的温升过程具有较高的模拟精度,实现了对通风管道过滤器微波灭菌性能的可靠预测.

Aiming at the complexity of the microwave disinfection process,a temperature-based predictive method for disinfection performance was proposed.First,a temperature rise characteristics numerical model of the composite filter under micro wave field was established to obtain its heating process.Then,by combining the relationship model between disinfection rate and temperature,the disinfection performance of the ventilation duct filter micro wave disinfection system was predicted.Finally,the validity and accuracy of the numerical model were verified based on the experimental data.Results show that when the microwave power is 600 W and 400 W,the average absolute errors between the simulated and measured final steady-state temperatures at each measurement point on the composite filter are 0.9℃ and 2.4℃,respectively,and the average absolute errors of the predicted disinfection rates from simulated and measured temperatures are 0.2%and 1.2%,respectively.The established numerical model demonstrates high simulation accuracy for the temperature rise process of the composite filter under microwave field,thereby enabling reliable prediction of the microwave disinfection performance of ventilation duct filters.

张源;王飞飞;徐新华;张浩然

华中科技大学环境科学与工程学院,湖北 武汉 430074华中科技大学环境科学与工程学院,湖北 武汉 430074华中科技大学环境科学与工程学院,湖北 武汉 430074大连船舶重工集团有限公司,辽宁 大连 116083

资源环境

室内空气品质微生物污染通风空调系统微波灭菌数值预测模型

indoor air qualitymicrobial contaminationventilation and air-conditioning systemmicro wave disinfectionnumerical prediction model

《华中科技大学学报(自然科学版)》 2026 (4)

143-147,5

国家自然科学基金资助项目(52508117)湖北省科技计划资助项目(2025BCB033).

10.13245/j.hust.259995

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