Results 61 to 70 of about 31,823 (308)
Additive Gaussian Process Regression for Predictive Design of High‐Performance, Printable Silicones
Advanced Engineering Materials, EarlyView.A chemistry‐aware design framework for tuning printable polydimethylsiloxane (PDMS) for vat photopolymerization (VPP) is developed using additive Gaussian process (GP) modeling. Polymer network mechanics informs variable groupings, feasible formulation constraints, and interaction variables.
Roxana Carbonell +3 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.Additive manufacturing provides precise control over the placement of continuous fibres within polymer matrices, enabling customised mechanical performance in composite components. This article explores processing strategies, mechanical testing, and modelling approaches for additive manufactured continuous fibre‐reinforced composites.
Cherian Thomas, Amir Hosein Sakhaei
wiley +1 more source
Detrending And Denoising With Empirical Mode Decompositions
, 2004 Publication in the conference proceedings of EUSIPCO, Viena, Austria ...
Flandrin, Patrick +2 more
openaire +3 more sources
Inspection of Methods of Empirical Mode Decomposition
5th International Conference on Computer Science, Information Technology (CSITEC 2019), 2019 11 pages, 6 figures.
Santander, Roberto Hernández +1 more
openaire +2 more sources
Karl Popper and the Mechanisms of Hydrogen Embrittlement
Advanced Engineering Materials, EarlyView.Representation of the beginning of loss of ductility rather than embrittlement. Small concentrations of hydrogen in a diffusible form within iron are well‐established to harm the mechanical integrity of steels. There are theories that attempt to explain the pernicious role of hydrogen.
H. K. D. H. Bhadeshia
wiley +1 more source
Sparse Reconstruction for Enhancement of the Empirical Mode Decomposition-Based Signal Denoising
IEEE Access, 2020 Effective signal denoising methods are essential for science and engineering. In general, denoising algorithms may be either linear or non-linear. Most of the linear ones are unable to remove the noise from the real-world measurements.
Krzysztof Brzostowski
doaj +1 more source
Journal of Low Frequency Noise, Vibration and Active Control, 2021 Technology that measures bridge responses when a vehicle is crossing over it for structural health monitoring has been under development for approximately a decade.
Feng Xiao +3 more
doaj +1 more source
Improved EMD Using Doubly-Iterative Sifting and High Order Spline Interpolation
, 2008 Empirical mode decomposition (EMD) is a signal analysis method which has received much attention lately due to its application in a number of fields. The main disadvantage of EMD is that it lacks a theoretical analysis and, therefore, our understanding ...
Yannis Kopsinis +4 more
core +1 more source
Signal denoising based on empirical mode decomposition [PDF]
, 2017 The present paper discusses the empirical mode decomposition technique relative to signal denoising, which is often included in signal preprocessing. We provide some basics of the empirical mode decomposition and introduce intrinsic mode functions with ...
Kupriyanov, Mikhail +5 more
core +1 more source
Advanced Engineering Materials, EarlyView.Knowledge‐based atomistic workflows are presented for mechanical and thermodynamic properties. By coupling modular simulations with ontology‐aligned metadata and provenance, Fe case studies on elastic behavior, defects, thermal properties, and Hall–Petch strengthening reveal how FAIR, queryable, and reusable simulation data can be generated. Mechanical
Abril Azócar Guzmán +5 more
wiley +1 more source