Fast Identification of Multiple Indoor Constant Contaminant Sources by Ideal Sensors: A Theoretical Model and Numerical Validation

Abstract

If hazardous contaminants are suddenly released indoors, quickly identifying the pollutants characteristics, such as the locations and emission rates, of the contaminant sources is critical for developing fast and effective response measures. This study presents a theoretical model for quickly identifying the locations and emission rates of multiple constant sources indoors using a single or limited number of ideal sensors. The model combines a linear programming model with an analytical expression of indoor contaminant dispersion that was presented in our previous study. Before the release of contaminants, only a limited number of time-consuming computational fluid dynamics (CFD) simulations need to be conducted to cover a large number of possible scenarios because of the analytical expression integrated into the model. After the release of contaminants, the model can be solved in real-time. Through case studies of sixteen contaminant release scenarios in a three-dimensional office, the effectiveness of the model was numerically demonstrated and validated. The results revealed that the identification accuracy of the presented model was closely related to the sensor layouts and the total sampling time, rather than the sampling interval.

Rapid identification of multiple constantly-released contaminant sources in indoor environments with unknown release time

“…where d 1 and d 2 are the maximum and average absolute relative error between perturbed and exact measurements, respectively; C pert and C exct,i are the ith perturbed and exact measurements, respectively; and M is the number of exact measurements. The SRE indices for performance evaluation were defined as follows [38]:…”

“…To date, most backward and forward methods have shown their applicability in identifying a single indoor contaminant source [17e40]. In contrast, very few studies have discussed the scenarios involving multiple indoor contaminant sources, which are frequent and common in real-world applications [18,38]. In residential or working environments, chemical contaminants are ubiquitous and continuously emitted from building materials, furniture, and equipment.…”

“…In a previous study we presented a theoretical model for quickly identifying the exact locations and emission rates of multiple constant contaminant sources indoors, using ideal sensors [38]. By using an analytical expression of indoor contaminant dispersion, the theoretical model only requires a limited number of CFD simulations.…”

An improved particle swarm optimization method for locating time-varying indoor particle sources

“…The fixed-sensor network method can apply "forward" or "backward" models. A forward model stores all potential release scenarios that are pre-simulated as a database, and then a potential indoor source can be identified by matching the pre-simulated and measured concentrations from an efficient search algorithm such as the Bayesian probability algorithm [5][6][7][8][9] or optimization algorithm [10][11][12][13][14]. By https://doi.org/10.1016/j.buildenv.2018.…”

Inverse identification of the release location, temporal rates, and sensor alarming time of an airborne pollutant source

“…The concentration match may be a simple comparison between the monitored and the predicted concentrations. If the concentration discrepancy is within the prescribed resolution for differentiation, then the source is identified (Cai et al, 2013;Wang et al, 2013). The concentration match can also be correlated with the occurrence probability of a source.…”