Statistical Technique in Gas Dispersion Modeling Based on Linear Interpolation

At the head of a plume, the spiral surge algorithm surged into the low concentration area, and then spiral back to the origin of the surge before receiving another "odor hit". The area of the gas source was expected to be appearing as a series of small distances between the locations where the robot senses consecutive "odor hits".However, this approach highly relied on sufficiently constant and strong airflow where the anemometer is required throughout the work. The Goodness of the technique is tested using some performance indicators such as means absolute error (MAE), normalized absolute error (NAE), root mean square error (RMSE), prediction accuracy (PA), coefficient of determination (R2) and index of agreement (d2). In industry the mapping is done manually by the engineers with complete personal protective equipment (PPE) to collect data manually at site or by using complex and expensive computer programs to do the data prediction, mapping and modeling. [...]in this study, a simple gas distribution modeling technique is being introduced. 2.Research Method Interpolation is a mathematical technique that can be used to fill blanks in the dataset. [...]both lines are having same slope, m and this applies to all lines that are falling between those two lines which m is mathematically defined as: ... [...]percentage difference between calculated and collected data can be figured out and suitability in using Linear Interpolation techniques can be defined. By considering 5% to 7% gas detector acceptance error by sensor manufacturer recommendation, 93% accuracy is highly acceptable. 4.Conclusion From this...