Analysis of the Effect of Inlet Velocity on Cooling Speed in a Refrigerated Container using CFD simulations

Budiyanto, Muhammad Arif; Suheriyanto, Nadhilah

doi:10.37934/cfdl.12.12.5562

Cited by 9 publications

(6 citation statements)

References 21 publications

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“…6 to 8 present the temperature values for the outdoor and indoor temperature obtained via the data logger during the over-all five-day period and the artificial neural network predictions for the indoor temperature. The study has shown that there need to conserve energy consumption by using a PU roofing system, which is in line with the study of [23][24][25]. The authors surveyed the alternative application of nanoparticles in increasing the cooling rate within the house environment for human comforts.…”

Section: Results Of Ann Prediction Analysis Of Pu-al Roofing Systemsupporting

confidence: 67%

Prediction and Performance Investigation of Polyurethane Foam as Thermal Insulation Material for Roofing Sheet Using Artificial Neural Network

Essien

Bolu

Okokpujie

et al. 2021

ARFMTS

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The prediction and application of Polyurethane Foam in developing roofing sheets cannot be over-emphasized when considering the environmental changes coursed by thermal radiation. This paper presents an artificial neural network application to model and predict the indoor temperature resistance of polyurethane (PU) roofing in residential buildings. The study employed a data logger to measure the indoor and outdoor temperatures for three simulation environments (i.e., morning, afternoon, and evening) for two hours each. Furthermore, the authors employed the Levenberg-Marquardt algorithm to transform and predict the indoor temperature obtained in the residential building's polyurethane roofing house. The result shows that the PU roofing system could absorb the heat and reduce the house model's temperature with 6.9% in the morning, afternoon 15.8%, and 6.8% in the evening when compared with the temperature outdoor environment. The ANN was also able to train, test, and validate the experimental temperature results with 92.86%, 93.92%, and 95%, respectively. The mean square error and a testing error occurs at 0.1707 and 0.1689. Therefore, this study concluded that ANN's application in predicting the thermal insulation material such as the PU roofing system is highly efficient and will increase the manufacturer's performance evaluation. It has also created significant awareness of the community in employing the PU roofing system for residential buildings, which will reduce the rate of energy consumption in buildings.

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Section: Results Of Ann Prediction Analysis Of Pu-al Roofing Systemsupporting

confidence: 67%

Prediction and Performance Investigation of Polyurethane Foam as Thermal Insulation Material for Roofing Sheet Using Artificial Neural Network

Essien

Bolu

Okokpujie

et al. 2021

ARFMTS

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“…Table 5 summarizes all the data from the thermal analysis. Inlet velocity influence on the temperature was neglected although results shown inlet velocity speed affects the cooling [19]. While epoxy is supposedly thermally resilient, grey cast iron had shown better results than carbon fibre in terms of the manifold and air temperature.…”

Section: Thermal Analysismentioning

confidence: 99%

Intake Manifold Material Selection and Fluid Flow Analysis for Formula Society of Automotive Engineers (FSAE) Race Car

Halim

Rahman

Adom

et al. 2023

CFDL

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The Formula SAE competition is organised for students who want to design and build a Formula-style race car. To limit the car's performance for safety and to encourage problem-solving skills, a 20mm restrictor was installed between the carburetor and the intake manifold to reduce air intake. When airflow is restricted, a bottleneck effect occurs, and less air is supplied to the engine for combustion, lowering engine efficiency. The goal of this project is to find a solution to this problem within the rules' limitations. This is accomplished by selecting an intake manifold that provides the best uniform distribution through each outlet and selecting a material that can withstand engine stress and vibrations while maintaining a relatively low temperature to ensure consistent velocity and pressure. Computational Fluid Dynamics (CFD) software is used to analyse the design's fluid flow, static, and thermal analysis, and the results are compared for each design. The best design and material will be used on the Universiti Malaysia Perlis Automotive Racing Team (UniART) race car

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“…In the application of the CFD method on reefer containers [17,18], there are several aspects that need to be considered, one of which is the placement of the skipjack tuna which is formed in packages on pallets. Another thing that needs to be considered is the area inside the pallet fish packaging to the wall requires a perfect arrangement, this aims to avoid cells or tilted arrangements.…”

Section: Introductionmentioning

confidence: 99%

Airflow Distribution Analysis of Reefer Container with Skipjack Tuna Load using Computational Fluid Dynamics

Muhammad Arif Budiyanto,

Muhammad Bukhari Robbani,

Gerry Liston Putra

et al. 2023

CFDL

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In the transportation of skipjack tuna to various destination countries, it is crucial to ensure that the skipjack tuna persists and remains of high quality. This study aims to analyse the airflow distribution inside the reefer container with the cargo load of skipjack tuna. The analysis carries out the computational fluid dynamics method to obtain appropriate airflow settings and investigate the temperature distribution inside reefer containers. The designed reefer container is 40ft with detailed structural variables of the T-bar and flat floor. The simulation result shows reefer containers that use the T-bar floor provide offer a thorough airflow distribution to cooling pallet stacks with full load conditions. The finding of the simulation results is the airflow rate of 5 m/s and the inlet temperature of -6°C will provide optimal cooling distribution.

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Analysis of the Effect of Inlet Velocity on Cooling Speed in a Refrigerated Container using CFD simulations

Cited by 9 publications

References 21 publications

Prediction and Performance Investigation of Polyurethane Foam as Thermal Insulation Material for Roofing Sheet Using Artificial Neural Network

Prediction and Performance Investigation of Polyurethane Foam as Thermal Insulation Material for Roofing Sheet Using Artificial Neural Network

Intake Manifold Material Selection and Fluid Flow Analysis for Formula Society of Automotive Engineers (FSAE) Race Car

Airflow Distribution Analysis of Reefer Container with Skipjack Tuna Load using Computational Fluid Dynamics

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