Results 71 to 80 of about 42,044 (303)
⁎-freeness in finite tensor products
Advances in Applied Mathematics, 2017 In this paper, we consider the following question and variants thereof: given $\mathbf D:=\big(a_{1;i}\otimes\cdots\otimes a_{K;i}:i\in I\big)$, a collection of elementary tensor non-commutative random variables in the tensor product of probability spaces $(\mathcal A_1\otimes\cdots\otimes\mathcal A_K,ϕ_1\otimes\cdots\otimesϕ_K)$, when is $\mathbf D$ $*
Benoit Collins +1 more
openaire +2 more sources
On the Tensor Product of Composition Algebras
Journal of Algebra, 2001 The authors investigate the tensor product \(C_1\otimes_F C_2\) of two composition algebras \(C_1\) and \(C_2\) over a field \(F\) of characteristic \(\neq 2\). First they consider the Albert forms of these algebras and obtain a necessary and sufficient condition for the similarity of the Albert forms of two algebras each of which is a tensor product ...
Morandi, P.J. +2 more
openaire +4 more sources
Advanced Engineering Materials, EarlyView.This study demonstrates an efficient recycling route for out‐of‐spec AlSi10Mg atomized powders through compaction and arc remelting followed by suction casting. By correlating compaction load, cooling rate, and resulting microstructure, we show that intermediate pressures (50–80 kN) and rapid cooling refine dendrites, reduce porosity, and enhance ...
Mila Christy de Oliveira +4 more
wiley +1 more source
BEST APPROXIMATION IN QUASI TENSOR PRODUCT SPACE AND DIRECT SUM OF LATTICE NORMED SPACES [PDF]
Journal of Algebraic Systems, 2014 We study the theory of best approximation in tensor product and the direct sum of some lattice normed spacesX_{i}. We introduce quasi tensor product space anddiscuss about the relation between tensor product space and thisnew space which we denote it by ...
Mahdi Iranmanesh, Fateme Solimani
doaj +1 more source
A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions
Advanced Engineering Materials, EarlyView.This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice +2 more
wiley +1 more source
Scalability of Tensor Products of Multiple Frames in Hilbert Spaces [PDF]
Sahand Communications in Mathematical AnalysisThis paper studies the scalability of tensor products of several frames, which may come from different Hilbert spaces. Although the scalability of single frames and tensor products of two frames has been explored, the case with more than two frames has ...
Asghar Rahimi +2 more
doaj +1 more source
Advanced Engineering Materials, EarlyView.A numerical–experimental framework is developed for characterizing multi‐matrix fiber‐reinforced polymers (MM‐FRPs) combining epoxy and polyurethane matrices. Harmonic bending tests are integrated with finite element model updating (FEMU) to simultaneously identify elastic and viscoelastic material parameters.
Rodrigo M. Dartora +4 more
wiley +1 more source
Preservation of tensor sum and tensor product
, 2020 . This note deals with preservation of tensor sum and tensor product of Hilbert space operators. Basic operations with tensor sum are presented. The main result addresses to the problem of transferring properties from a pair of operators to their tensor ...
C S Kubrusly, N Levan
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Advanced Engineering Materials, EarlyView.Geometry‐driven thermal behavior in wire‐arc additive manufacturing (WAAM) influences microstructural evolution during nonequilibrium solidification of a chemically complex Fe–Cr–Nb–W–Mo–C nanocomposite system. By comparing different deposits configurations, distinct entropy–cooling rate correlations, segregation, and carbide evolution are revealed ...
Blanca Palacios +5 more
wiley +1 more source
Dynamic Tensor Product Regression
, 2023 In this work, we initiate the study of \emph{Dynamic Tensor Product Regression}. One has matrices $A_1\in \mathbb{R}^{n_1\times d_1},\ldots,A_q\in \mathbb{R}^{n_q\times d_q}$ and a label vector $b\in \mathbb{R}^{n_1\ldots n_q}$, and the goal is to solve ...
Song, Zhao +2 more
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