Multiscale modeling of woven composites by deep learning neural networks and its application in design optimization
Due to complex yarn geometries and multiscale nature, it is very challenging to predict
mechanical properties and strength constants of woven composites in an accuracy and …
mechanical properties and strength constants of woven composites in an accuracy and …
Life assessment of thermomechanical fatigue in a woven SiC/SiC ceramic matrix composite with an environmental barrier coating at elevated temperature
In this work, the tension–tension fatigue behavior of a woven SiC/SiC ceramic matrix
composite with an environmental barrier coating is investigated under elevated …
composite with an environmental barrier coating is investigated under elevated …
[HTML][HTML] High-temperature transient-induced thermomechanical damage of fiber-reinforced ceramic-matrix composites in supersonic wind tunnel
J Wang, Z Yang, R Yang, J Jiao, L Yue… - Composites Part A: Applied …, 2024 - Elsevier
This article is based on the supersonic directly connected wind tunnel. Through a specially
designed experimental chamber, combined with infrared temperature measurement, high …
designed experimental chamber, combined with infrared temperature measurement, high …
Multi deep learning-based stochastic microstructure reconstruction and high-fidelity micromechanics simulation of time-dependent ceramic matrix composite response
MH Hamza, A Chattopadhyay - Composite Structures, 2024 - Elsevier
A multi deep learning-based framework is developed for efficient, automated microstructure
reconstruction and generation of stochastic representative volume elements (SRVEs) with …
reconstruction and generation of stochastic representative volume elements (SRVEs) with …
Surrogate-Assisted Differential Evolution for Wave Energy Converters Optimization
In the aftermath of the successes in wind and solar energy, wave energy has emerged as an
exceptionally promising renewable resource. A pivotal aspect of wave energy development …
exceptionally promising renewable resource. A pivotal aspect of wave energy development …
A physics-informed long short-term memory (LSTM) model for estimating ammonia emissions from dairy manure during storage
Manure management on dairy farms impacts how farmers maximize its value as fertilizer,
reduce operating costs, and minimize environmental pollution potential. A persistent …
reduce operating costs, and minimize environmental pollution potential. A persistent …
Integrating machine learning into process-based modeling to predict the ammonia loss from stored slurry dairy manure
Effective manure storage management on dairy farms is crucial for maximizing its value as
fertilizer, reducing costs, and minimizing environmental pollution. However, manure nitrogen …
fertilizer, reducing costs, and minimizing environmental pollution. However, manure nitrogen …
Integrating Machine Learning Into Process-Based Modeling to Predict Ammonia Losses From Stored Liquid Dairy Manure
RAK Genedy - 2023 - vtechworks.lib.vt.edu
Storing manure on dairy farms is essential for maximizing its fertilizer value, reducing
management costs, and minimizing potential environmental pollution challenges. However …
management costs, and minimizing potential environmental pollution challenges. However …