Results 121 to 130 of about 1,196,266 (277)
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
A simplified thermoplastic pultrusion model is developed to predict thermal fields in glass fiber/polyethylene terephthalate (GF/PET) composites with reduced computational cost. By combining effective material homogenization, validation against literature data, and Gaussian‐process‐based optimization, the study reveals how heating limits, pulling speed,
Elder Soares +3 more
wiley +1 more source
Learning graph based individual intrinsic reward for multi-agent reinforcement learning
Designing a reward function is a critical challenge in reinforcement learning. However, as environments become more complex and tasks grow more difficult, designing a reward function that drives optimal behavior becomes increasingly challenging.
Seokhun Ju +6 more
doaj +1 more source
The impact of intrinsic rewards on exploration in Reinforcement Learning
Abstract One of the open challenges in Reinforcement Learning (RL) is the hard exploration problem in sparse reward environments. Various types of intrinsic rewards have been proposed to address this challenge by pushing toward diversity.
Aya Kayal +2 more
openaire +2 more sources
Copper‐based composites enhanced with carbon feature convenient mechanical properties and favorable electric conductivity. Processing via deformation and thermomechanical treatments can introduce advantageous microstructures further enhancing their performance. Herein, copper–graphene powder‐based composites are directly consolidated via rotary swaging
Radim Kocich +3 more
wiley +1 more source
Optimistic Online LQR via Intrinsic Rewards
Optimism in the face of uncertainty is a popular approach to balance exploration and exploitation in reinforcement learning. Here, we consider the online linear quadratic regulator (LQR) problem, i.e., to learn the LQR corresponding to an unknown linear dynamical system by adapting the control policy online based on closed-loop data collected during ...
Marcell Bartos +5 more
openaire +2 more sources
A two‐dimensional multiscale finite element analysis framework was established for the first‐generation MoSiBTiC alloy, and the mechanical and fracture‐related parameters of the constituent phases were calibrated through experiments and simulations. The framework provides a basis for analyzing crack propagation behavior in its complex microstructure ...
Junfeng Du +4 more
wiley +1 more source
A Lightweight Procedural Layer for Hybrid Experimental–Computational Workflows in Materials Science
We unveil a prototype hybrid‐workflow framework that fuses automatedcomputation with hands‐on experiments. Built atop pyiron, a lightweight, parameterized layer translates procedure descriptions into executable manual steps, syncing instrument settings, human interventions, and data capture in real‐time today.
Steffen Brinckmann +8 more
wiley +1 more source
Creep Properties and Deformation Mechanism of Additively Manufactured NiAl‐CrMo Composites
Additively manufactured NiAl‐CrMo composites contain numerous interfaces and cell boundaries that control their creep response. At 700°C under high applied stress, creep is dominated by dislocation‐controlled power‐law mechanisms. At 800°C–900°C and lower stresses, creep is primarily diffusion‐controlled along cell boundaries.
Jan Vollhüter +9 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

