Results 121 to 130 of about 268,821 (264)
Knowledge graph, which is a rapidly developing technology, provides strong support in business and engineering. Knowledge graph plays an important role in recommendations and decision-making, while in the electric power industry, there would be more ...
Tianjiao Pu +3 more
doaj +1 more source
What Do Large Language Models Know About Materials?
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer +2 more
wiley +1 more source
Dynamic State Estimation is a crucial task in power systems. Graph Neural Networks have demonstrated significant potential in dynamic state estimation, for power systems by effectively analyzing measurement data and capturing the complex interactions and
Seyed Hamed Haghshenas, Mia Naeini
doaj +1 more source
A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice +2 more
wiley +1 more source
The transient stability assessment (TSA) model based on graph deep learning relies on complete system topology and its characteristics. However, electrical operation data may be missing during the measurement and transmission process, which can lead to a
Chenhao Zhao +3 more
doaj +1 more source
This article presents the NFDI‐MatWerk Ontology (MWO), a Basic Formal Ontology‐based framework for interoperable research data management in materials science and engineering (MSE). Covering consortium structures, research data management resources, services, and instruments, MWO enables semantic integration, Findable, Accessible, Interoperable, and ...
Hossein Beygi Nasrabadi +4 more
wiley +1 more source
Wind Power Forecast Using Multilevel Adaptive Graph Convolution Neural Network
Accurate forecasting of wind power is essential for maintaining the stability and efficiency of power networks as renewable energy sources become more integrated.
Oluwaseun E. Duntoye +2 more
doaj +1 more source
A numerical–experimental framework is developed for characterizing multi‐matrix fiber‐reinforced polymers (MM‐FRPs) combining epoxy and polyurethane matrices. Harmonic bending tests are integrated with finite element model updating (FEMU) to simultaneously identify elastic and viscoelastic material parameters.
Rodrigo M. Dartora +4 more
wiley +1 more source
Enhanced power graph from the power graph of a group
The power graph of a group $G$ is a graph with vertex set $G$, where two distinct vertices $a$ and $b$ are adjacent if one of $a$ and $b$ is a power of the other. Similarly, the enhanced power graph of $G$ is a graph with vertex set $G$, where two distinct vertices are adjacent if they belong to the same cyclic subgroup.
Pote, Amar S., Kadu, Ganesh S.
openaire +2 more sources
Geometry‐driven thermal behavior in wire‐arc additive manufacturing (WAAM) influences microstructural evolution during nonequilibrium solidification of a chemically complex Fe–Cr–Nb–W–Mo–C nanocomposite system. By comparing different deposits configurations, distinct entropy–cooling rate correlations, segregation, and carbide evolution are revealed ...
Blanca Palacios +5 more
wiley +1 more source

