Evaluation of pressure drop effect on COP of single-stage vapor compression refrigeration cycles

Constantino, Matheus; Kanizawa, Fábio Toshio

doi:10.1016/j.tsep.2021.101048

Cited by 5 publications

(2 citation statements)

References 25 publications

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“…This is because the compressor has to work harder to overcome the increased pressure in the condenser and maintain the same level of refrigerant flow. This increased workload leads to higher energy consumption by the compressor [ 26 ].…”

Section: Resultsmentioning

confidence: 99%

Modeling the Energy Consumption of R600a Gas in a Refrigeration System with New Explainable Artificial Intelligence Methods Based on Hybrid Optimization

Akyol,

Das,

Alatas

2023

Biomimetics

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Refrigerant gases, an essential cooling system component, are used in different processes according to their thermophysical properties and energy consumption values. The low global warming potential and energy consumption values of refrigerant gases are primarily preferred in terms of use. Recently, studies on modeling properties such as compressor energy consumption, efficiency coefficient, exergy, and thermophysical properties of refrigerants in refrigeration systems with artificial intelligence methods has become increasingly common. In this study, a hybrid-optimization-based artificial intelligence classification method is applied for the first time to produce explainable, interpretable, and transparent models of compressor energy consumption in a vapor compression refrigeration system operating with R600a refrigerant gas. This methodological innovation obtains models that determine the energy consumption values of R600a gas according to the operating parameters. From these models, the operating conditions with the lowest energy consumption are automatically revealed. The innovative artificial intelligence method applied for the energy consumption value determines the system’s energy consumption according to the operating temperatures and pressures of the evaporator and condenser unit. When the obtained energy consumption model results were compared with the experimental results, it was seen that it had an accuracy of 84.4%. From this explainable artificial intelligence method, which is applied for the first time in the field of refrigerant gas, the most suitable operating conditions that can be achieved based on the minimum, medium, and maximum energy consumption ranges of different refrigerant gases can be determined.

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Section: Resultsmentioning

confidence: 99%

Modeling the Energy Consumption of R600a Gas in a Refrigeration System with New Explainable Artificial Intelligence Methods Based on Hybrid Optimization

Akyol,

Das,

Alatas

2023

Biomimetics

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“…The encouragement of air-conditioning systems driven by renewable energies would effectively cut down the negative effects from consumption of fossil fuels. Vapor compression air-conditioning system is the most popular and widely used airconditioning system, which has a market share of 80% [7,8]. The absorption system adopts environmental friendly refrigerants (like water), fully reflects the concept of green environmental protection.…”

Section: Introductionmentioning

confidence: 99%

A Battery Air-Conditioning System Made from Daily Life Biomass Waste

Wang,

2024

Advances in Transdisciplinary Engineering

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A new green air-conditioning system based on the traditional absorption air-conditioning system is proposed: the system adopts biomass waste and forms a medium cycle with capacitive deionization (CDI) technology. The key to the new system is the electrodes of CDI. In our work, corn cobs, corn stalks, and waste cigarette butts have been used to prepare micro/mesoporous carbon material for electrode fabrication. The resultant material has been characterized by BET. The electrochemical performance has been tested with electrochemical workstation. The COP has been analyzed for the new air-conditioning system with different electrode materials. The results find the suitable conditions for preparing the electrode material with excellent pore structure and higher specific surface area. It has been demonstrated that the corn cobs activated at 800 °C (CBC-800) possess the highest specific surface area of 1201.9 m2 g-1 and the highest electrochemical capacitance of 141.1F g-1 at a scan rate of 5 mV s-1. The results show that the system with LiBr solution has the highest COP, it can approach 6 with a 40 % concentration when CBC-800 is used as carbon electrodes. These results could make the absorption air-conditioning system based on the capacitive deionization method more promising for future application.

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Risk-Based Maintenance Strategies on Fishing Vessel Refrigeration Systems Using Fuzzy-FMEA

Siahaan,

Yaqin,

Priharanto

et al. 2024

J Fail. Anal. and Preven.

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Evaluation of pressure drop effect on COP of single-stage vapor compression refrigeration cycles

Cited by 5 publications

References 25 publications

Modeling the Energy Consumption of R600a Gas in a Refrigeration System with New Explainable Artificial Intelligence Methods Based on Hybrid Optimization

Modeling the Energy Consumption of R600a Gas in a Refrigeration System with New Explainable Artificial Intelligence Methods Based on Hybrid Optimization

A Battery Air-Conditioning System Made from Daily Life Biomass Waste

Risk-Based Maintenance Strategies on Fishing Vessel Refrigeration Systems Using Fuzzy-FMEA

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