Results 101 to 110 of about 186,255 (315)
Grand Challenges in Computational Physics
Frontiers in Physics, 2013 Kay eHamacher
doaj +3 more sources
A Knowledge‐Based Approach for Understanding and Managing Additive Manufacturing Data
Advanced Engineering Materials, EarlyView.Additive manufacturing processes generate a large amount of data. Effectively managing, understanding, and retrieving information from this data remains a major challenge. Therefore, we propose an ontology‐based approach to integrate heterogeneous data, enable semantic queries, and support decision‐making.
Mina Abd Nikooie Pour +5 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.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
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
Physics Data Management Tools for Monte Carlo Transport: Computational Evolutions and Benchmarks
, 2010 The development of a package for the management of physics data is described: its design, implementation and computational benchmarks. This package improves the data management tools originally developed for Geant4 physics models based on the EADL, EEDL ...
Moneta, Lorenzo +9 more
core +1 more source
Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization
Advanced Engineering Materials, EarlyView.Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier +17 more
wiley +1 more source
Multimodal Data‐Driven Microstructure Characterization
Advanced Engineering Materials, EarlyView.A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang +4 more
wiley +1 more source
Machine learning (ML) offers a diverse array of tools and architectures for transforming data from simulations and experiments into explainable science, thereby augmenting domain knowledge.
Reza, Maryam, Faraji, Farbod
core +1 more source
A comparative study of immersed-boundary interpolation methods for a flow around a stationary cylinder at low Reynolds number [PDF]
, 2013 The accuracy and computational efficiency of various interpolation methods for the implementation of non grid-confirming boundaries is assessed. The aim of the research is to select an interpolation method that is both efficient and sufficiently accurate
Wissink, J +5 more
core
Advanced Engineering Materials, EarlyView.We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang +2 more
wiley +1 more source