Results 61 to 70 of about 150,538 (265)
Randomized Matrix Decompositions Using R
Matrix decompositions are fundamental tools in the area of applied mathematics, statistical computing, and machine learning. In particular, low-rank matrix decompositions are vital, and widely used for data analysis, dimensionality reduction, and data ...
N. Benjamin Erichson +3 more
doaj +1 more source
Phase Field Failure Modeling: Brittle‐Ductile Dual‐Phase Microstructures under Compressive Loading
The approach by Amor and the approach by Miehe and Zhang for asymmetric damage behavior in the phase field method for fracture are compared regarding their fitness for microcrack‐based failure modeling. The comparison is performed for the case of a dual‐phase microstructure with a brittle and a ductile constituent.
Jakob Huber, Jan Torgersen, Ewald Werner
wiley +1 more source
Multimodal Data‐Driven Microstructure Characterization
A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang +4 more
wiley +1 more source
SVD Algorithm in the Application of the MIMO System Model Order Reduction
For linear time invariant high-order system calculation and analysis model is difficult to directly,so we need to study on reduction of the model According to the basic theory of model order reduction Lyapunov equation model order solution to linear time
LU Fang-ming, ZHOU Lin
doaj +1 more source
Creep‐Induced Microstructural Evolution in an A2‐B2 Superalloy
A 27.3Ta‐27.3Mo‐27.3Ti‐8Cr‐10Al (at.%) refractory high‐entropy alloy with precipitation‐strengthened A2‐B2 microstructure was studied by creep tests at 1030°C, which demonstrate a transition in deformation mechanisms in the range of 100–150 MPa applied stress. This is associated with changes in dislocation–precipitate interactions. Relevant deformation
Liu Yang +10 more
wiley +1 more source
This study shows that superalloys used in aircraft engine disks become much more prone to deformation at high temperatures if they have been strained during manufacturing. This effect increases with the level of prior strain but eventually reaches a limit.
Fabio Machado Alves da Fonseca +9 more
wiley +1 more source
On the Iwasawa decomposition of a symplectic matrix
Let \(Sp(n, \mathbb R)=\{S\in SL_{2n}(\mathbb R) : S^tJS=J\}\) be the Lie group of symplectic matrices. The authors present an algorithm for computing the Iwasawa decomposition of a matrix \( Sp(n, \mathbb R)\ni S=KAN\), where \(K\) is compact, \(A\) abelian, and \(N\) nilpotent matrices, via the QR fractorization.
Benzi, Michele, Razouk, Nader
openaire +2 more sources
Relative-Error $CUR$ Matrix Decompositions [PDF]
Many data analysis applications deal with large matrices and involve approximating the matrix using a small number of ``components.'' Typically, these components are linear combinations of the rows and columns of the matrix, and are thus difficult to interpret in terms of the original features of the input data.
Petros Drineas +2 more
openaire +2 more sources
Experiments and thermophysical simulations were conducted to investigate the electron beam powder bed fusion electron beam (PBF‐EB/M) process for the γ′‐strengthened nickel‐based superalloy Inconel 738LC. The results demonstrate the impact of process‐induced microstructural variations on high‐temperature mechanical behavior, providing a basis for ...
Jan Niklas Petenati +11 more
wiley +1 more source
Sparse and Low-Rank Matrix Decompositions [PDF]
Abstract Suppose we are given a matrix that is formed by adding an unknown sparse matrix to an unknown low-rank matrix. Our goal is to decompose the given matrix into its sparse and low-rank components. Such a problem arises in a number of applications in model and system identification, but obtaining an exact solution is NP-hard in general.
Venkat Chandrasekaran +3 more
openaire +3 more sources

