Results 111 to 120 of about 7,885 (219)
Physics-constrained transformer for wind power forecasting. [PDF]
Wang D, Luo Q, Gao J, Zhang D, Chen Y.
europepmc +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
A robust multi-location evaluation of a machine learning framework for wind power forecasting. [PDF]
Ali U +7 more
europepmc +1 more source
Phase‐field simulations coupled with dislocation‐density‐based crystal plasticity modeling reproduce γ′ rafting behavior in single‐crystal Ni‐based superalloys under varied loading conditions. The model captures both macroscopic creep and microscopic morphology evolution, with results matching high‐temperature creep experiments.
Micheal Younan +5 more
wiley +1 more source
An Uncertainty-Aware Temporal Transformer for Probabilistic Interval Modeling in Wind Power Forecasting. [PDF]
Sun S +6 more
europepmc +1 more source
Karl Popper and the Mechanisms of Hydrogen Embrittlement
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
Fast-powerformer achieves accurate and memory-efficient mid-term wind power forecasting. [PDF]
Zhu M, Li Z, Lin Q, Ding L.
europepmc +1 more source
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch +3 more
wiley +1 more source
Enhanced Dhole Optimization Algorithm for hyperparameter tuning of a TCN-BiGRU-MHA hybrid architecture for wind power forecasting. [PDF]
Lale T.
europepmc +1 more source
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

