Optimization of Weight Reduction in Power Transmission Systems Using Bio-Inspired Algorithms and Composite Materials

Traditional optimization approaches for power transmission systems often optimize gear and shaft designs separately, rely on conventional materials, and face challenges handling mixed-variable problems involving discrete and continuous variables. These limitations hinder the potential for significant weight reduction and performance improvements in modern mechanical systems. This research presents an innovative optimization approach for reducing the gear pitch in a power transmission system comprising a shaft with two gears. By employing bio-inspired metaheuristic algorithms and utilizing materials common in additive manufacturing and composite materials, the study aims to minimize system weight while ensuring mechanical integrity. The optimization integrates gear and shaft design variables, accurately models mechanical constraints through penalty functions, and leverages the unique properties of advanced materials to enhance performance. In this work, we developed an integrated optimization model that overcomes the limitations of previous studies by combining advanced materials with bio-inspired algorithms to achieve significant weight reduction in gear systems. This approach effectively addresses the complexities of mixed-variable optimization and mechanical constraints, providing a practical and innovative solution for modern engineering applications.

Authors

Institutions

Publication Details

Journal
Coatings
Published
2024-12-18
DOI
https://doi.org/10.3390/coatings14121586
Citations
1
Primary Topic
Advanced Machining and Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.21

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimization of Weight Reduction in Power Transmission Systems Using Bio-Inspired Algorithms and Composite Materials

Vanessa Botero-Gómez, Daniel Sanín-Villa, Miguel Ángel Rodriguez-Cabal
1 citations
Coatings
Advanced Machining and Optimization Techniques
0.21
article

Optimization of Weight Reduction in Power Transmission Systems Using Bio-Inspired Algorithms and Composite Materials

Vanessa Botero-Gómez, Daniel Sanín-Villa, Miguel Ángel Rodriguez-Cabal
article en
1 citations

Abstract

Traditional optimization approaches for power transmission systems often optimize gear and shaft designs separately, rely on conventional materials, and face challenges handling mixed-variable problems involving discrete and continuous variables. These limitations hinder the potential for significant weight reduction and performance improvements in modern mechanical systems. This research presents an innovative optimization approach for reducing the gear pitch in a power transmission system comprising a shaft with two gears. By employing bio-inspired metaheuristic algorithms and utilizing materials common in additive manufacturing and composite materials, the study aims to minimize system weight while ensuring mechanical integrity. The optimization integrates gear and shaft design variables, accurately models mechanical constraints through penalty functions, and leverages the unique properties of advanced materials to enhance performance. In this work, we developed an integrated optimization model that overcomes the limitations of previous studies by combining advanced materials with bio-inspired algorithms to achieve significant weight reduction in gear systems. This approach effectively addresses the complexities of mixed-variable optimization and mechanical constraints, providing a practical and innovative solution for modern engineering applications.

CoatingsVol. 14(12)
Instituto Tecnológico Metropolitano (CO), Universidad EAFIT (CO)
Universidad EAFIT, Instituto Tecnológico Metropolitano
Affordable and clean energy
Openalex Percentile: Top 45%
Advanced Machining and Optimization Techniques
0.21
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.