Results 61 to 70 of about 666,598 (288)

Higher-order Galilean contractions

Nuclear Physics B, 2019
A Galilean contraction is a way to construct Galilean conformal algebras from a pair of infinite-dimensional conformal algebras, or equivalently, a method for contracting tensor products of vertex algebras.
Jørgen Rasmussen, Christopher Raymond
doaj   +1 more source

From Nature to Engineering: Mortar Volume and Interfacial Mechanics in Bioinspired Ceramics

Advanced Engineering Materials, EarlyView.
Inspired by natural armors like nacre, this study explores how varying the volume fraction of the soft mortar layer impacts the interfacial strength and toughness of bioinspired ceramics. Experimental and computational analysis reveals that higher mortar volumes increase energy dissipation but reduce interfacial stiffness, offering insights for ...
Ehsan Azad, Hamidreza Yazdani Sarvestani, Behnam Ashrafi, Farjad Shadmehri, Mehdi Hojjati   +4 more
wiley   +1 more source

A Simulative Approach for the Prediction of Mesoscale Residual Stress Fields in Solution‐Strengthened Ferritic Ductile Iron

Advanced Engineering Materials, EarlyView.
This study presents a 3D representative volume element‐based simulation approach to predict mesoscopic residual stress and strain fields in silicon solid solution‐strengthened ductile cast iron. By modeling phase transformation kinetics with an enhanced Johnson–Mehl–Avrami–Kolmogorov model, the effects of varying cooling rates on residual stresses are ...
Lutz Horbach, Oliver Schenk, Valérian Iss, Ali Rajaei, Jiali Zhang, Felix Weber, Christoph Broeckmann   +6 more
wiley   +1 more source

BlockBP decoder for the surface code

Physical Review Research
We present a new decoder for the surface code, which combines the accuracy of the tensor-network decoders with the efficiency and parallelism of the belief-propagation algorithm.
Aviad Kaufmann, Itai Arad
doaj   +1 more source

Axially Symmetric-dS Solution in Teleparallel f(T) Gravity Theories

Advances in High Energy Physics, 2015
We apply a tetrad field with six unknown functions to Einstein field equations. Exact vacuum solution, which represents axially symmetric-dS spacetime, is derived.
Gamal G. L. Nashed
doaj   +1 more source

Residual Stress States in Microstructurally Graded PBF–LB/M Austenitic Steel Components

Advanced Engineering Materials, EarlyView.
This study examines microstructurally graded 316L rectangular tube profiles fabricated via PBF–LB/M using a dual‐laser system. A 1 kW top‐hat and a 400 W Gaussian laser create distinct grain sizes and crystallographic texture. Mechanical properties are linked to microstructural evolution driven by processing conditions.
Nico Möller, Florian Loebich, Thomas Wegener, Julia Richter, Jens Gibmeier, Thomas Niendorf   +5 more
wiley   +1 more source

Tensor networks for p-spin models

Frontiers in Physics
We introduce a tensor network algorithm for the solution of p-spin models. We show that bond compression through rank-revealing decompositions performed during the tensor network contraction resolves logical redundancies in the system exactly and is thus
Benjamin Lanthier, Jeremy Côté, Stefanos Kourtis   +2 more
doaj   +1 more source

A Comprehensive Review of Additive Manufacturing for Space Applications: Materials, Advances, Challenges, and Future Directions

Advanced Engineering Materials, EarlyView.
Additive manufacturing (AM) transforms space hardware by enabling lightweight, high‐performance, and on‐demand production. This review outlines AM processes—powder bed fusion (PBF), directed energy deposition (DED), binder jetting (BJ), sheet lamination (SL), and material extrusion (ME)—applied to propulsion, satellite structures, and thermal devices ...
Stelios K. Georgantzinos, Eleni Papadopoulou, Grigorios Kostopoulos, Stefanos Voulgaris, Alexandra Tseni, Panteleimon Bakalis, Maria Gkara, Chara C. Mitropoulou, Nikos D. Lagaros   +8 more
wiley   +1 more source

Differentiable Programming Tensor Networks

Physical Review X, 2019
Differentiable programming is a fresh programming paradigm which composes parameterized algorithmic components and optimizes them using gradient search. The concept emerges from deep learning but is not limited to training neural networks. We present the
Hai-Jun Liao, Jin-Guo Liu, Lei Wang, Tao Xiang   +3 more
doaj   +1 more source

Optimizing Laser Ablation of Stainless Steels for Volume Removal and Surface Quality Using Burst of Pulses

Advanced Engineering Materials, EarlyView.
This study explores the ablation efficiency and surface quality of laser‐treated stainless steel alloys (AISI 304, AISI 420, and AISI 316Ti) using an ultrashort pulsed laser and varying burst parameters (MHz, GHz, and Bi‐burst). Both ablation rates and surface quality parameters are determined, including isotropy surface roughness values, highlighting ...
Dirk Obergfell, Bahman Azarhoushang, Andrés Fabián Lasagni   +2 more
wiley   +1 more source