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Refinado por: Base de dados/Biblioteca: BACON - Mir@bel - GLOBAL_LIBRESACCES remover assunto: Physics, Condensed Matter remover Physical Sciences remover Materials Science, Multidisciplinary remover
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1
Machine Learning Techniques in Concrete Mix Design
Machine Learning Techniques in Concrete Mix Design
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Machine Learning Techniques in Concrete Mix Design

Ziolkowski, Patryk ; Niedostatkiewicz, Maciej

Materials, 2019-04, Vol.12 (8), p.1256 [Periódico revisado por pares]

Switzerland: MDPI AG

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2
Prediction and Sensitivity Analysis of Bubble Dissolution Time in 3D Selective Laser Sintering Using Ensemble Decision Trees
Prediction and Sensitivity Analysis of Bubble Dissolution Time in 3D Selective Laser Sintering Using Ensemble Decision Trees
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Prediction and Sensitivity Analysis of Bubble Dissolution Time in 3D Selective Laser Sintering Using Ensemble Decision Trees

Ly, Hai-Bang ; Monteiro, Eric ; Le, Tien-Thinh ; Le, Vuong Minh ; Dal, Morgan ; Regnier, Gilles ; Pham, Binh Thai

Materials, 2019-05, Vol.12 (9), p.1544 [Periódico revisado por pares]

Switzerland: MDPI AG

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3
Comparison of Grain-Growth Mean-Field Models Regarding Predicted Grain Size Distributions
Comparison of Grain-Growth Mean-Field Models Regarding Predicted Grain Size Distributions
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Comparison of Grain-Growth Mean-Field Models Regarding Predicted Grain Size Distributions

Roth, Marion ; Flipon, Baptiste ; Bozzolo, Nathalie ; Bernacki, Marc

Materials, 2023-10, Vol.16 (20), p.6761 [Periódico revisado por pares]

Basel: MDPI AG

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4
Simulation of Continuous Dynamic Recrystallization Using a Level-Set Method
Simulation of Continuous Dynamic Recrystallization Using a Level-Set Method
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Simulation of Continuous Dynamic Recrystallization Using a Level-Set Method

Grand, Victor ; Flipon, Baptiste ; Gaillac, Alexis ; Bernacki, Marc

Materials, 2022-11, Vol.15 (23), p.8547 [Periódico revisado por pares]

Switzerland: MDPI AG

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5
Nettle, a Long-Known Fiber Plant with New Perspectives
Nettle, a Long-Known Fiber Plant with New Perspectives
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Nettle, a Long-Known Fiber Plant with New Perspectives

Viotti, Chloé ; Albrecht, Katharina ; Amaducci, Stefano ; Bardos, Paul ; Bertheau, Coralie ; Blaudez, Damien ; Bothe, Lea ; Cazaux, David ; Ferrarini, Andrea ; Govilas, Jason ; Gusovius, Hans-Jörg ; Jeannin, Thomas ; Lühr, Carsten ; Müssig, Jörg ; Pilla, Marcello ; Placet, Vincent ; Puschenreiter, Markus ; Tognacchini, Alice ; Yung, Loïc ; Chalot, Michel

Materials, 2022-06, Vol.15 (12), p.4288 [Periódico revisado por pares]

Basel: MDPI AG

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6
Comparative Study and Limits of Different Level-Set Formulations for the Modeling of Anisotropic Grain Growth
Comparative Study and Limits of Different Level-Set Formulations for the Modeling of Anisotropic Grain Growth
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Comparative Study and Limits of Different Level-Set Formulations for the Modeling of Anisotropic Grain Growth

Murgas, Brayan ; Florez, Sebastian ; Bozzolo, Nathalie ; Fausty, Julien ; Bernacki, Marc

Materials, 2021-07, Vol.14 (14), p.3883 [Periódico revisado por pares]

Basel: MDPI AG

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7
A New Method to Predict Damage to Composite Structures Using Convolutional Neural Networks
A New Method to Predict Damage to Composite Structures Using Convolutional Neural Networks
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A New Method to Predict Damage to Composite Structures Using Convolutional Neural Networks

Mezeix, Laurent ; Rivas, Ainhoa Soldevila ; Relandeau, Antonin ; Bouvet, Christophe

Materials, 2023-11, Vol.16 (22), p.7213 [Periódico revisado por pares]

Basel: MDPI AG

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8
Prediction of the Compressive Strength of Waste-Based Concretes Using Artificial Neural Network
Prediction of the Compressive Strength of Waste-Based Concretes Using Artificial Neural Network
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Prediction of the Compressive Strength of Waste-Based Concretes Using Artificial Neural Network

Amar, Mouhamadou ; Benzerzour, Mahfoud ; Zentar, Rachid ; Abriak, Nor-Edine

Materials, 2022-10, Vol.15 (20), p.7045 [Periódico revisado por pares]

Basel: MDPI AG

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9
A 2D Front-Tracking Lagrangian Model for the Modeling of Anisotropic Grain Growth
A 2D Front-Tracking Lagrangian Model for the Modeling of Anisotropic Grain Growth
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A 2D Front-Tracking Lagrangian Model for the Modeling of Anisotropic Grain Growth

Florez, Sebastian ; Fausty, Julien ; Alvarado, Karen ; Murgas, Brayan ; Bernacki, Marc

Materials, 2021-07, Vol.14 (15), p.4219 [Periódico revisado por pares]

Switzerland: MDPI AG

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10
Analysis of the Usability of Iron Ore Ultra-Fines for Hydrogen-Based Fluidized Bed Direct Reduction-A Review
Analysis of the Usability of Iron Ore Ultra-Fines for Hydrogen-Based Fluidized Bed Direct Reduction-A Review
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Analysis of the Usability of Iron Ore Ultra-Fines for Hydrogen-Based Fluidized Bed Direct Reduction-A Review

Wolfinger, Thomas ; Spreitzer, Daniel ; Schenk, Johannes

Materials, 2022-04, Vol.15 (7), p.2687 [Periódico revisado por pares]

Switzerland: MDPI AG

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