Computational technologies in materials science
著者
書誌事項
Computational technologies in materials science
（Science, technology, and management series / series editor, J. Paulo Davim）
CRC Press, 2022
- : hbk
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注記
Includes bibliographical references and index
Other editors : Parveen Singla, Ashutosh Nandi, J. Paulo Davim
内容説明・目次
内容説明
* Covers material testing and development using computational intelligence
* Highlights the technologies to integrate computational intelligence and materials sciences
* Discusses how computational tools can generate new materials with advanced applications
* Details case studies and detailed applications
* Investigates challenges in developing and using computational intelligence in materials science * Analyzes historic changes that are taking place in designing of materials
目次
Chapter 1 Fabrication and Characterization of Materials Chapter 2 Application to Advanced Materials Simulation Chapter 3 Molecular Dynamics Simulations for Structural Characterization and Property Prediction of Materials Chapter 4 Desirability Approach-Based Optimization of Process Parameters in Turning of Aluminum Matrix Composites Chapter 5 Spark Plasma-Induced Combustion Synthesis, Densification, and Characterization of Nanostructured Magnesium Silicide for Mid Temperature Energy Conversion Energy Harvesting Application Chapter 6 The Role of Computational Intelligence in Materials Science: An Overview Chapter 7 Characterization Techniques for Composites using AI and Machine Learning Techniques Chapter 8 Experimental Evaluation on Tribological Behavior of TiO2 Reinforced Polyamide Composites Validated by Taguchi and Machine Learning Methods Chapter 9 Prediction of Compressive Strength of SCC-Containing Metakaolin and Rice Husk Ash Using Machine Learning Algorithms Chapter 10 Predicting Compressive Strength of Concrete Matrix Using Engineered Cementitious Composites: A Comparative Study between ANN and RF Models Chapter 11 Estimation of Marshall Stability of Asphalt Concrete Mix Using Neural Network and M5P Tree
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