HVAC Infection Control Using Dynamic Quanta and Temperature Models
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Solution Overview
Problem
Existing HVAC systems face challenges in maintaining occupant comfort and disinfection while minimizing expenses, as they often require manual adjustments that can inadvertently affect other environmental conditions and are costly when not optimized correctly.
Innovation Solution
A heating, ventilation, and air conditioning (HVAC) system with a controller that uses dynamic temperature and infectious quanta models to determine infection probability and generate control decisions for airside equipment, optimizing disinfection and airflow while integrating disinfection lighting and filters to provide clean air effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If building equipment is operated to change environmental conditions for occupant comfort and disinfection, then disinfection level and occupant comfort are improved, but expenses and energy consumption increase
Solution Approach 1:
The system dynamically adjusts HVAC equipment operation based on real-time environmental conditions, occupancy levels, and infection risk assessments. Control parameters such as airflow rates, temperature setpoints, and disinfection intensities are continuously optimized to maintain adequate disinfection while minimizing energy consumption, rather than operating at fixed high levels throughout.
Solution Approach 2:
The system changes operational parameters of building equipment based on varying conditions. When infection risk is low or occupancy is minimal, the system reduces disinfection intensity and adjusts environmental parameters, thereby maintaining reliability while reducing energy consumption during periods when full disinfection capacity is not required.
2Reliability
If building equipment is operated to change environmental conditions for occupant comfort and disinfection, then disinfection level and occupant comfort are improved, but expenses increase
Solution Approach 1:
The system incorporates feedback mechanisms that continuously monitor environmental conditions, occupancy patterns, and equipment performance. This feedback enables the control system to adjust operations in real-time, optimizing the balance between disinfection effectiveness and operational expenses by reducing equipment runtime and intensity when full capacity is not needed.
Solution Approach 2:
The system transitions from static, high-level operation to dynamic, condition-based operation. By continuously adapting equipment settings based on actual building conditions and infection risk assessments, the system maintains adequate disinfection levels while minimizing unnecessary energy expenditure and operational costs.
3Ease of operation
If manual adjustments are made by occupants to change environmental conditions, then individual comfort is improved, but other environmental conditions are adversely affected and expenses increase
Solution Approach 1:
The system introduces an intelligent control intermediary that manages environmental adjustments. Instead of allowing direct manual adjustments that may compromise overall environmental stability, the control system mediates between individual comfort requests and building-wide environmental requirements, making optimized adjustments that maintain both comfort and stability.
Solution Approach 2:
The system uses feedback mechanisms to monitor the impact of environmental adjustments in real-time. When occupants request changes, the control system evaluates these requests against building-wide environmental targets and makes coordinated adjustments across multiple parameters to maintain overall environmental stability while accommodating individual comfort needs.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system efficiently maintains occupant comfort and disinfection while reducing costs by optimizing HVAC operations based on real-time data, ensuring effective disinfection and comfortable conditions without excessive energy consumption.
Implementation Method 1
one or more filters configured to filter the clean air before it is provided to the one or more building zones
Implementation Method 2
disinfection lighting operable to disinfect the clean air before it is provided to the one or more building zones
Data Source
AI summary
A heating, ventilation, or air conditioning (HVAC) system for one or more building zones includes airside HVAC equipment operable to provide clean air to the one or more building zones and a controller. The controller is configured to obtain a dynamic temperature model and a dynamic infectious quanta model for the one or more building zones, determine an infection probability, and generate control decisions for the airside HVAC equipment using the dynamic temperature model, the dynamic infectious quanta model, and the infection probability.