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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
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
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
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