Science – Society – Technology
From: A machine learning approach for mapping the very shallow theoretical geothermal potential
Symbol | Unit | Description |
---|---|---|
\(\alpha\) | (\(\text {m}^{2}\,\text {s}^{-1}\)) | Thermal diffusivity |
\(\gamma _{d}\) | (g/\(\text {cm}^{3}\)) | Dry (bulk) density |
\(\gamma _{s}\) | (g/\(\text {cm}^{3}\)) | Particle density |
\(\gamma _{w}\) | (g/\(\text {cm}^{3}\)) | Water density |
\(\lambda\) | (\(\text {W K}^{-1}\,\text {m}^{-1}\)) | Thermal conductivity |
\(\rho\) | (\(\Omega\) m) | Electrical resistivity |
\(\omega\) | (\(\text {s}^{-1}\)) | Angular frequency of one period in Fourier series |
\(a_{n}\) | (–) | First Fourier coefficient for the nth harmonics |
\(b_{n}\) | (–) | Second Fourier coefficient for the nth harmonics |
\(c_{v}\) | (\(\text {J m}^{-3}\,\text {K}^{-1}\)) | Volumetric heat capacity |
D | (m) | Damping depth |
e | (–) | Void ratio |
F | (%) | Percentage sum of sand and gravel fractions in the soil |
\(h_{i}\) | (m) | Width of soil strata i |
\(I_{1},...,I_{10}\) | (–) | Possible fraction intervals for soil texture variables |
\(M_{s}\) | (g) | Mass of solid soil in ground |
\(M_{w}\) | (g) | Mass of water in ground |
n | (–) | Harmonics index in Fourier series |
\(n_{p}\) | (–) | Porosity |
\(R_{n}\) | (–) | Amplitude of nth harmonic of Fourier series solution for T |
Sd, St, Cl | (%) | Sand, silt, and clay fraction percentage in soil |
\(S_{r}\) | (%) | Saturation degree |
t | (s) | Time |
T | (\(^{\circ }\)C) | Shallow ground temperature |
\(T_{0}\) | (\(^{\circ }\)C) | Average ground surface temperature over a year |
\(V_{a}\) | (\(\text {m}^{3}\)) | Volume of air in ground |
\(V_{s}\) | (\(\text {m}^{3}\)) | Volume of solid soil in ground |
\(V_{T}\) | (\(\text {m}^{3}\)) | Total volume of ground |
\(V_{v}\) | (\(\text {m}^{3}\)) | Volume of void in ground |
\(V_{w}\) | (\(\text {m}^{3}\)) | Volume of water in ground |
w | (%) | Gravimetric water content |
z | (m) | Ground depth |