Results 121 to 130 of about 113,421 (265)

Reactive optimal motion planning for a class of holonomic planar agents using reinforcement learning with provable guarantees. [PDF]

Front Robot AI, 2023
Rousseas P, Bechlioulis C, Kyriakopoulos K.   +2 more
europepmc   +1 more source

Precipitation Simulations of the O‐Phase in Ti2AlNb Alloys Processed by Laser Powder Bed Fusion

Advanced Engineering Materials, EarlyView.
Simulated and experimental evolution of the O‐phase volume fraction during postprocessing of a Ti‐21Al‐25Nb (at.%) alloy processed by laser powder bed fusion. With results of sensitivity to input parameters from a thorough and quantified analysis, the interfacial energy matrix/precipitate is the most relevant input parameter for the simulation of the O‐
Silvana Tumminello, Joachim Gussone, Suzana G. Fries, Marcus Rackel, Andreas Stark, Norbert Schell, Jan Haubrich, Guillermo Requena   +7 more
wiley   +1 more source

Modeling Dislocation Cutting of γ′ Precipitates in Ni‐Base Superalloys: Linking Atomistic and Dislocation Dynamics Simulations

Advanced Engineering Materials, EarlyView.
Dislocation cutting of γ′ precipitates in Ni‐based superalloys is investigated by linking atomistic simulations with discrete dislocation dynamics. The critical cutting stress is shown to be governed by the antiphase boundary energy, while line tension effects promote edge‐preferred cutting.
Frédéric Houllé, Siwen Gao, Marc Fivel, Anxin Ma, Daria Smirnova, Sriram Anand, Arun Prakash, Julien Guénolé, Alexander Hartmaier, Erik Bitzek   +9 more
wiley   +1 more source

Cooperative Dynamic Motion Planning for Dual Manipulator Arms Based on RRT*Smart-AD Algorithm. [PDF]

Sensors (Basel), 2023
Long H, Li G, Zhou F, Chen T.
europepmc   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

Triple Junctions as Dislocation‐Like Defects: The Role of Grain Boundary Crystallography Revealed by Experiment and Atomistic Simulation

Advanced Engineering Materials, EarlyView.
Grain boundary triple junctions are an essential ingredient of the microstructure of polycrystalline materials. In this study, a triple junction is observed using atomic‐resolution scanning transmission electron microscopy and characterized. Computer simulations reveal that the junction has a dislocation character that is determined by the joining ...
Tobias Brink, Saba Saood, Peter Schweizer, Jörg Neugebauer, Gerhard Dehm   +4 more
wiley   +1 more source

Benchmarking the utility of maps of dynamics for human-aware motion planning. [PDF]

Front Robot AI, 2022
Swaminathan CS, Kucner TP, Magnusson M, Palmieri L, Molina S, Mannucci A, Pecora F, Lilienthal AJ.   +7 more
europepmc   +1 more source

Microstructure, Thermal Transport, and Dry‐Sliding Tribology of Powder‐Metallurgy Al7075 Composites Reinforced With Sol–Gel‐Derived ZnO–rGO Hybrid Nanoparticles

Advanced Engineering Materials, EarlyView.
Sol–gel‐derived ZnO–rGO hybrid nanoparticles enable Al7075 powder‐metallurgy composites to achieve concurrent gains in hardness and thermal conductivity while markedly lowering friction and wear. The hybrid architecture couples ZnO‐based load support with rGO‐assisted lamellar sliding and heat spreading, revealing a promising route toward lightweight ...
Bunyamin Aksakal, Cevher Kursat Macit, Merve Ayık, Hakan Tutumlu   +3 more
wiley   +1 more source

Safe formation scaling and motion planning for heterogeneous UAV-UGV teams in cluttered environments. [PDF]

Sci Rep
Chen Q, Liu X, Nie W, Liu H, Pang W.
europepmc   +1 more source

A Predictable Obstacle Avoidance Model Based on Geometric Configuration of Redundant Manipulators for Motion Planning. [PDF]

Sensors (Basel), 2023
Ju F, Jin H, Wang B, Zhao J.
europepmc   +1 more source