Work

Optimization of an NH3-H2O Absorption Cooling System Using an Inverted Multivariate Function with Neural Networks and PSO

Year: 2026

Type: article

Abstract: Absorption systems offer a practical alternative to traditional compression systems, especially when low-grade heat sources are available. Their applications range from vaccine preservation to space conditioning, making performance optimization essential. This study employed a multivariate inverse artificial neural network with multiple parameters (ANNim-mp) to simultaneously enhance the cooling load and coefficient of performance in an experimental single-effect ammonia–water absorption cooling system. Optimization was carried out using particle swarm optimization. The results showed significant performance improvements: up to 100% in cooling load and 97% in COP when optimizing two variables. With four-variable optimization, improvements reached 98.7% and 106.7%, respectively. These results demonstrate the strong potential of the ANNim-mp approach in enhancing the efficiency of absorption cooling systems.

Source: Processes

DOI: 10.3390/pr14010177

Authors: Ulises Cruz-Jacobo, Roberto Agustin Conde-Gutiérrez, Wilfrido Rivera, Darío Colorado, José Camilo Jiménez-García

Institutions: Universidad Autónoma del Estado de Morelos, Universidad Veracruzana, Universidad Nacional Autónoma de México

Language: English

Topic: Refrigeration and Air Conditioning Technologies

Subfield: Mechanical Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Climate action

Open Access status: gold

Estimated APC paid: $2,896