Artificial Neural Network (ANN) Approach to Predict Tensile Properties of Longitudinally Placed Fiber Reinforced Polymeric Composites including Interphase
Machine Learning has become prevalent nowadays for predicting data on the mechanical properties of various materials and is widely used in various polymeric applications. In the present study, Artificial Neural Network (ANN), a computational tool is used to predict the elastic modulus of a composite...
Saved in:
| Main Authors: | Sagar Chokshi, Piyush Gohil, Vijay Parmar, Vijaykumar Chaudhary |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Semnan University
2025-08-01
|
| Series: | Mechanics of Advanced Composite Structures |
| Subjects: | |
| Online Access: | https://macs.semnan.ac.ir/article_8980_187576ddf606902249196f9627a8584b.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Experimental investigation and prediction of wear behavior of cotton fiber polyester composites
by: Hiral H. Parikh, et al.
Published: (2017-05-01) -
Preparation of Unsaturated Polyester Nanocomposites and Studying Their Mechanical Properties Using some Inorganic Additives
by: Baghdad Science Journal
Published: (2016-06-01) -
Viscoelastic and Thermal Characterization of a Composite Material Based on Unsaturated Polyester Resin Reinforced with Perlite
by: Dehas Ouided, et al.
Published: (2024-12-01) -
Recent Progress in Fiber Reinforced Polymer Hybrid Composites and Its Challenges-A Comprehensive Review
by: C. M. Mohanraj, et al.
Published: (2025-12-01) -
Experimental study on mechanical properties for a three-phase polymer composite reinforced by glass fibers and titanium oxide particles
by: Nguyen Dinh Duc, et al.
Published: (2011-06-01)