Results 61 to 70 of about 45,297 (262)

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

Relating Random Vector and Random Finite Set Estimation in Navigation, Mapping, and Tracking [PDF]

IEEE Transactions on Signal Processing, 2017
Navigation, mapping, and tracking are state estimation problems relevant to a wide range of applications. These problems have traditionally been formulated using random vectors in stochastic filtering, smoothing, or optimization-based approaches. Alternatively, the problems can be formulated using random finite sets, which offer a more robust solution ...
Keith Yu Kit Leung, Felipe Inostroza, Martin Adams   +2 more
openaire   +4 more sources

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

Tracking Multiple Marine Ships via Multiple Sensors with Unknown Backgrounds

Sensors, 2019
In multitarget tracking, knowledge of the backgrounds plays a crucial role in the accuracy of the tracker. Clutter and detection probability are the two essential background parameters which are usually assumed to be known constants although they are, in
Cong-Thanh Do, Tran Thien Dat Nguyen, Weifeng Liu   +2 more
doaj   +1 more source

Parameter estimation and tracking algorithm for resolvable group targets based on GLMB filter and RLS algorithm

EURASIP Journal on Advances in Signal Processing, 2022
Current resolvable group targets tracking algorithms can only track a small number of group targets assuming the standard deviation vectors (SDVs) are known. Based on generalized labeled multi-Bernoulli filter, this paper first proposes a serial tracking
Weifeng Liu, Zhi Zhao, Qiliang Liu, Zhangming Peng   +3 more
doaj   +1 more source

Influence of Scan Strategies in Electron Beam Powder Bed Fusion on Solidification, Microstructure, and High‐Temperature Compressive Properties of γ′‐Strengthened Inconel 738LC

Advanced Engineering Materials, EarlyView.
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, Karthik Kumar Banku, Prasanth Bondi, Ivan Zhirnov, Yangyiwei Yang, Gordon Schmidt, Jürgen Christen, Georg Hasemann, Manja Krüger, Bai‐Xiang Xu, Bilal Gökce, Silja‐Katharina Rittinghaus   +11 more
wiley   +1 more source

Adaptive Target Birth Intensity Multi-Bernoulli Filter with Noise-Based Threshold

Sensors, 2019
Adaptively modeling the target birth intensity while maintaining the filtering efficiency is a challenging issue in multi-target tracking (MTT). Generally, the target birth probability is predefined as a constant and only the target birth density is ...
Xiaolong Hu, Hongbing Ji, Long Liu
doaj   +1 more source

New AI‐Assisted Approach for Expanding the Solution Space: Application to Lattice Structure Design

Advanced Engineering Materials, EarlyView.
This work introduces an innovative framework for designing structured materials by ex panding the design space through reparameterization of qualitative variables into continuous structural descriptors. Combined with machine‐learning‐based prediction and multi‐objective optimization, the approach enables the discovery of novel lattice architectures ...
G. H. Gahimbare, Y. Beideler, D. Chune, R. De Guio, T. Roland, H. Chibane   +5 more
wiley   +1 more source

High‐Resolution Corrosion Fingerprinting of Alloy Libraries via Microdroplet Spectroelectrochemistry

Advanced Engineering Materials, EarlyView.
Ionic‐liquid microdroplet spectroelectrochemistry enables stable, localized electrochemical measurements over extended timescales. By coupling impedance spectroscopy, wetting analysis, finite‐element simulations, and operando Raman spectroscopy, it disentangles geometrical and electrochemical effects, opening new opportunities for rapid corrosion ...
Ekaterina Kurchavova, Oumaïma Gharbi, Mireille Turmine, Vincent Vivier   +3 more
wiley   +1 more source

Multi-Channel Speech Enhancement Using Labelled Random Finite Sets and a Neural Beamformer in Cocktail Party Scenario

Applied Sciences
In this research, a multi-channel target speech enhancement scheme is proposed that is based on deep learning (DL) architecture and assisted by multi-source tracking using a labeled random finite set (RFS) framework.
Jayanta Datta, Ali Dehghan Firoozabadi, David Zabala-Blanco, Francisco R. Castillo-Soria   +3 more
doaj   +1 more source