Journal ArticleDOI
Microstructural material database for self-consistent clustering analysis of elastoplastic strain softening materials
Reads0
Chats0
TLDR
In this article, a stable micro-damage homogenization algorithm is presented which removes the material instability issues in the microstructure with representative volume elements (RVE) that are not sensitive to size when computing the homogenized stress-strain response.About:
This article is published in Computer Methods in Applied Mechanics and Engineering.The article was published on 2018-03-01. It has received 115 citations till now. The article focuses on the topics: Multiscale modeling & Cluster analysis.read more
Citations
More filters
Journal ArticleDOI
A deep material network for multiscale topology learning and accelerated nonlinear modeling of heterogeneous materials
TL;DR: By discovering a proper topological representation of RVE with fewer degrees of freedom, this intelligent material model is believed to open new possibilities of high-fidelity efficient concurrent simulations for a large-scale heterogeneous structure.
Journal ArticleDOI
Artificial intelligence and machine learning in design of mechanical materials
TL;DR: The applications in mechanical property prediction, materials design and computational methods using ML-based approaches are summarized, followed by perspectives on opportunities and open challenges in this emerging and exciting field.
Journal ArticleDOI
Virtual, Digital and Hybrid Twins: A New Paradigm in Data-Based Engineering and Engineered Data
TL;DR: Not only data serve to enrich physically-based models, but also modeling and simulation viewpoints, which could allow us to perform a tremendous leap forward, by replacing big-data-based habits by the incipient smart-data paradigm.
Journal ArticleDOI
Machine learning for metal additive manufacturing: predicting temperature and melt pool fluid dynamics using physics-informed neural networks
TL;DR: In this article, a physics-informed neural network (PINN) framework was proposed to predict the temperature and melt pool dynamics during metal additive manufacturing (AM) processes with only a moderate amount of labeled data sets.
References
More filters
Some methods for classification and analysis of multivariate observations
TL;DR: The k-means algorithm as mentioned in this paper partitions an N-dimensional population into k sets on the basis of a sample, which is a generalization of the ordinary sample mean, and it is shown to give partitions which are reasonably efficient in the sense of within-class variance.
Book
Data Mining: Practical Machine Learning Tools and Techniques
TL;DR: This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining.
Proceedings Article
A density-based algorithm for discovering clusters a density-based algorithm for discovering clusters in large spatial databases with noise
TL;DR: In this paper, a density-based notion of clusters is proposed to discover clusters of arbitrary shape, which can be used for class identification in large spatial databases and is shown to be more efficient than the well-known algorithm CLAR-ANS.
Reference EntryDOI
Principal Component Analysis
TL;DR: Principal component analysis (PCA) as discussed by the authors replaces the p original variables by a smaller number, q, of derived variables, the principal components, which are linear combinations of the original variables.
Proceedings Article
A density-based algorithm for discovering clusters in large spatial Databases with Noise
TL;DR: DBSCAN, a new clustering algorithm relying on a density-based notion of clusters which is designed to discover clusters of arbitrary shape, is presented which requires only one input parameter and supports the user in determining an appropriate value for it.
Related Papers (5)
A numerical method for computing the overall response of nonlinear composites with complex microstructure
Hervé Moulinec,Pierre Suquet +1 more