A two-axis mobile measuring system (TAMMS) for high-resolution air velocity analysis in indoor environments

Abstract

The trade-off between cost, time and measurement density often limits experimental acquisition with high spatial resolution of indoor environmental variables, such as air velocity ($V$). This becomes critical when validating HVAC systems, ensuring thermal comfort, and supporting numerical modeling, where standard techniques lack flexibility (point sensors) or require complex configurations (e.g., PIV). This study presents the development and validation of a two-axis mobile measurement system (TAMMS), a device equipped with a point sensor and governed by an adaptive refinement algorithm. The system was tested in a full-scale climate chamber. Measurements were carried out at different air exchange rates ($n$ = 1.5, 3 and $5h^{-1}$) and in three different cross sections by iteratively adjusting the measurement grid with the adaptive algorithm. The high repeatability of the tests was confirmed by uncertainty values of less than 0.2 %. The velocity maps obtained allowed the verification of comfort thresholds in the conventionally occupied zone, highlighting stagnation areas for $n\le 3h^{-1}$ ($V<2cm{s}^{-1}$) and areas of intense variability for $n=5h^{-1}$ ($V_{s}max=23cm{s}^{-1}$). Depending on the flow variability, convergence was obtained with 1–3 iterations, achieving a 96 % reduction in measurement time compared to uniform grids and thus demonstrating the validity of the adaptive algorithm.