基于数字双胞胎的智能仓库热环境模拟与自动控制优化

Key Points

• The research aims to develop a digital twin model for simulating and optimizing the thermal environment of a warehouse.
• Constructed a digital twin model incorporating geometric, physical, and behavioral characteristics.
• Conducted multi-condition simulation experiments with 96 monitoring points.
• Monitored thermal conditions over a 72-hour period in a specified warehouse area.
• Achieved a mean temperature simulation error of 0.21°C.
• 87% of monitoring points had an error of ±0.3°C.
• Significant negative correlation between humidity and temperature (coefficient -0.76).
• Cardboard packaging increased local humidity by 8% while absorbing 5% moisture by weight.