Evaluation of Elastic Filament Velocimetry (EFV) Sensor in Ventilation Systems: An Experimental Study

Athanasia Keli (), Samira Rahnama, Göran Hultmark, Marcus Hultmark and Alireza Afshari ()
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Athanasia Keli: Department of the Built Environment, Aalborg University, 2450 København, Denmark
Samira Rahnama: Department of the Built Environment, Aalborg University, 2450 København, Denmark
Göran Hultmark: Department of the Built Environment, Aalborg University, 2450 København, Denmark
Marcus Hultmark: Department of Mechanical and Aerospace Engineering, Princeton University, Princeton, NJ 08544, USA
Alireza Afshari: Department of the Built Environment, Aalborg University, 2450 København, Denmark

Sustainability, 2023, vol. 15, issue 3, 1-14

Abstract: Determination of airflow rates is an inevitable part of the energy-efficient control of ventilation systems. To achieve efficient control, the flowmeters used must be suitably accurate and create minimum disturbance to the airflow. In this study, we evaluate the quantitative performance characteristics of an innovative micro-electromechanical systems (MEMS) flowmeter, a so-called Elastic Filament Velocimetry (EFV), in ventilation ducts. Two versions of the EFV-sensor, i.e., an 11-nanoribbon and a 22-nanoribbon variety, were evaluated in laboratory studies. The results indicate that the 11-nanoribbon sensor is more suitable for air velocity measurements in ducts than the 22-nanoribbon sensor. The 11-nanoribbon sensor can measure air velocities from 0.3 m/s. The maximum variation of the sensor-output is 3% for velocities over 0.5 m/s. Calibration models have been developed for the 11-nanoribbon sensor. The error due to model calibration is lower than ±5% for velocities over 0.6 m/s. Moreover, laboratory studies were performed to investigate the airflow disturbance in a duct system due to the EFV sensor. The results were compared with the corresponding disturbance caused by two different types of self-averaging probes. At a bulk velocity of 3 m/s, the self-averaging probes introduced a greater pressure drop by at least 50% compared to the EFV-sensor.

Keywords: EFV-sensor; MEMS airflow sensor; air velocity measurements; flow disturbance; ventilation systems (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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