Indoor Fluid Flow Reconstruction via Temperature Field Simulation
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Solution Overview
Problem
Existing climate control systems in indoor spaces, such as greenhouses, face challenges in accurately measuring and monitoring fluid flow fields due to the high cost and noise susceptibility of traditional sensors, particularly in large areas where air velocities are low.
Innovation Solution
A monitoring system that uses a combination of temperature sensors, a simulation unit, and a Kalman filter-based approach to reconstruct flow fields from temperature measurements, eliminating the need for dedicated flow meters and reducing noise in data, allowing for detailed and accurate assessment of fluid states within indoor spaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional flow sensors (hot-wire anemometry, ultrasonic anemometry, laser Doppler anemometry) are used to measure air flow, then measurement precision of flow field is improved, but device cost increases significantly
Solution Approach 1:
The patent uses temperature field measurements as a proxy/copy to infer flow field characteristics. Instead of directly measuring flow with expensive sensors, the system measures temperature distribution and uses fluid dynamics models to reconstruct flow patterns, thereby achieving flow field measurement without dedicated flow meters
Solution Approach 2:
The patent replaces mechanical/physical flow sensing systems (hot-wire, ultrasonic, laser Doppler) with a thermal-field-based measurement system combined with computational modeling. This substitution uses temperature sensors and simulation algorithms instead of complex flow measurement hardware
2Measurement precision
If traditional flow sensors are used in large indoor spaces, then flow field data accuracy is improved, but noise susceptibility increases
Solution Approach 1:
The system creates a virtual model of the flow field based on temperature measurements, which is less susceptible to noise than direct flow sensing. The reconstruction process using fluid dynamics equations filters out random noise while preserving actual flow patterns
Solution Approach 2:
The system uses iterative reconstruction algorithms that compare predicted temperature fields with actual measurements, adjusting flow field estimates to minimize errors. This feedback mechanism reduces noise by consistently validating measurements against physical laws
3Loss of information
If direct flow measurement methods are used, then flow field information is obtained, but device complexity increases
Solution Approach 1:
The system uses temperature sensors that serve multiple functions: direct temperature measurement and indirect flow field reconstruction. This multi-functionality eliminates the need for separate flow sensors, reducing overall system complexity while maintaining flow information capability
Solution Approach 2:
The patent creates a computational model (virtual copy) of the flow field based on temperature data, avoiding the need for complex physical flow measurement infrastructure. The simulation unit reconstructs flow patterns through algorithmic processing rather than direct sensing
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
This solution enables cost-effective and accurate monitoring of fluid states, including flow fields, in indoor spaces by using temperature sensors and Kalman filter-based methods, reducing computational complexity and noise, thus improving the accuracy of climate control systems.
Implementation Method 1
a plurality of temperature sensors (81a, . . . , 81mT) to provide respective temperature measurement data (yTk) indicative for a temperature field in said indoor space (10)
Implementation Method 2
A monitoring system that uses a combination of temperature sensors, a simulation unit, and a Kalman filter-based approach to reconstruct flow fields from temperature measurements, eliminating the need for dedicated flow meters and reducing noise in data
Data Source
AI summary
A monitoring system for monitoring a state of a fluid in an indoor space including a state of a flow field for said fluid is presented. The system includes an input unit (81), a simulation unit (82), a comparison unit (83) and a state correction unit (84). The input unit (81) comprises a plurality of temperature sensors (81a, 81b, . . . , 81mT) to obtain temperature measurement data indicative for a temperature field in said indoor space. The simulation unit (82) is provided to simulate the fluid in said indoor space according to an indoor climate model to predict a state of the fluid including at least a temperature field and a flow field for the fluid in said indoor space, and has an output to provide a signal indicative for the flow field. The comparison unit (83) is provided to compare the predicted temperature field with the temperature measurement data, and the state correction unit (84) is provided to correct the predicted state of the fluid based on a comparison result of said comparison unit (83). The monitoring system may be part of a climate control system.