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Documents publiés en "2022"

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Nombre de documents: 8

B

Beaudry, G., Pasquier, P., Marcotte, D., & Zarrella, A. (2022). Flow rate control in standing column wells: A flexible solution for reducing the energy use and peak power demand of the built environment. Applied Energy, 313, 14 pages. Lien externe

D

De Castro, B., Marcotte, D., Chopard, A., Plante, B., & Benzaazoua, M. (2022). Technical note adaptation of Pierre's Gy theory of sampling for polished section preparation geared towards automated mineralogical analysis. Minerals Engineering, 187, 107795 (5 pages). Lien externe

Dion, G., Pasquier, P., & Marcotte, D. (2022). Deconvolution of experimental thermal response test data to recover short-term g-function. Geothermics, 100, 102302 (13 pages). Lien externe

Dion, G., Pasquier, P., Beaudry, G., & Marcotte, D. (décembre 2022). Stationary and non-stationary deconvolution to recover long-term transfer functions [Communication écrite]. International Ground Source Heat Pump Association annual Conference, Las vegas, NV, USA. Lien externe

L

Lauzon, D., & Marcotte, D. (juin 2022). On a constructive spectral method for conditioning pluriGaussian simulations to boreholes observations and indirect data. Application to aquifer models [Affiche]. 14th International Conference on Geostatistics for Environmental Applications (GeoEnv 2022)#, Parma, Italia (1 page). Lien externe

Lauzon, D., & Marcotte, D. (2022). Statistical comparison of variogram-based inversion methods for to indirect data. Computers & Geosciences, 160, 105032 (15 pages). Lien externe

M

Mery, N., & Marcotte, D. (2022). Assessment of Recoverable Resource Uncertainty in Multivariate Deposits Through a Simple Machine Learning Technique Trained Using Geostatistical Simulations. Natural Resources Research, 31(2), 767-783. Lien externe

Mery, N., & Marcotte, D. (2022). Quantifying Mineral Resources and Their Uncertainty Using Two Existing Machine Learning Methods. Mathematical Geosciences, 54(2), 363-387. Lien externe

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