A Python code for adjusting periodic soil temperature data

Abstract

This work aims to present a code in Python language for adjusting periodic curves from soil temperature simulation data. We present a methodology to obtain a sinusoidal function using the least squares method that represents the soil temperature of a given locality. The code also uses Newton's method to solve the resulting nonlinear system of equations. Soil temperature simulation data were used in a city in the state of Rio Grande do Sul, Brazil. The results of these curves can help in the study and definition of boundary conditions of new computational models of ground-to-air heat exchangers (TCSA). It is observed that the least squares method is not new , but there is a gap in the literature regarding the presentation of codes for the adjustment of trigonometric functions as presented here.

DOI:https://doi.org/10.56238/sevened2024.003-046