Your English writing platform
Discover LudwigSuggestions(5)
Exact(60)
The power model is capable of predicting the ultimate capacity of the connection.
The model is capable of predicting pressure and rate for every layer within the system.
Moreover, it is capable of predicting gateway link disconnections, increasing the total amount of delivered data.
The model is capable of predicting fractional formation of FAME XX c) at other operating conditions.
The latter is capable of predicting the experimental collapse load and overall behaviour quite accurately.
The model is capable of predicting the experimentally observed enhanced hardening of small grain sized materials.
The proposed degradation model is capable of predicting the degradation index with high degree of accuracy.
Moreover, by converting this model into an electrical circuit, it is capable of predicting thermal conductivity.
The paper demonstrates that a non-linear pushover analysis is capable of predicting collapse.
The model is capable of predicting the microstructure, texture, and kinetics.
This method is capable of predicting the farfield noise from non-linear nearfield flow quantities.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com