A Mathematical Model of Membrane Gas Separation with Energy Transfer by Molecules of Gas Flowing in a Channel to Molecules Penetrating this Channel from the Adjacent Channel

Szwast, Maciej; Szwast, Zbigniew

doi:10.1515/cpe-2015-0012

Cited by 6 publications

(4 citation statements)

References 9 publications

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“…Additionally, to abstract the packaging of different fruits and vegetables [107]. This type of model works on four ideal flow patterns for a mixed gas module including co-current flow, cross flow, counter-current flow, and perfect mixing [108][109][110].…”

Section: Application Of Mathematical Modeling Techniques In the Postharvest Supply Chain Of Fruits And Vegetablesmentioning

confidence: 99%

Recent Advances in Reducing Food Losses in the Supply Chain of Fresh Agricultural Produce

et al. 2020

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Fruits and vegetables are highly nutritious agricultural produce with tremendous human health benefits. They are also highly perishable and as such are easily susceptible to spoilage, leading to a reduction in quality attributes and induced food loss. Cold chain technologies have over the years been employed to reduce the quality loss of fruits and vegetables from farm to fork. However, a high amount of losses (≈50%) still occur during the packaging, pre-cooling, transportation, and storage of these fresh agricultural produce. This study highlights the current state-of-the-art of various advanced tools employed to reducing the quality loss of fruits and vegetables during the packaging, storage, and transportation cold chain operations, including the application of imaging technology, spectroscopy, multi-sensors, electronic nose, radio frequency identification, printed sensors, acoustic impulse response, and mathematical models. It is shown that computer vision, hyperspectral imaging, multispectral imaging, spectroscopy, X-ray imaging, and mathematical models are well established in monitoring and optimizing process parameters that affect food quality attributes during cold chain operations. We also identified the Internet of Things (IoT) and virtual representation models of a particular fresh produce (digital twins) as emerging technologies that can help monitor and control the uncharted quality evolution during its postharvest life. These advances can help diagnose and take measures against potential problems affecting the quality of fresh produce in the supply chains. Plausible future pathways to further develop these emerging technologies and help in the significant reduction of food losses in the supply chain of fresh produce are discussed. Future research should be directed towards integrating IoT and digital twins for multiple shipments in order to intensify real-time monitoring of the cold chain environmental conditions, and the eventual optimization of the postharvest supply chains. This study gives promising insight towards the use of advanced technologies in reducing losses in the postharvest supply chain of fruits and vegetables.

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Section: Application Of Mathematical Modeling Techniques In the Postharvest Supply Chain Of Fruits And Vegetablesmentioning

confidence: 99%

Recent Advances in Reducing Food Losses in the Supply Chain of Fresh Agricultural Produce

et al. 2020

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“…Regardless of the scope of the practical research, in industry, agriculture (in the case presented, aerodynamic separation), medicine, or environmental protection, following a set of experimental determinations, it is advisable to design a mathematical equation, thus generating equations with which they can be tracked, analyzed, and optimized [27][28][29][30][31][32][33][34][35].…”

Section: Introductionmentioning

confidence: 99%

Extraction of Mathematical Correlations Applied in the Aerodynamic Separation of Solid Particles

et al. 2022

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This article describes the methodology used to identify the mathematical equation that describes the correlations between the input and output parameters of an experiment. As a technological process, aerodynamic separation was chosen to represent the behavior of a solid particle within an ascending vertical airflow. The experimental data were used to identify two parameters, namely the average linear velocity and the angular velocity. The Table Curve 3D program was used to develop a mathematical equation describing the dependence between the input parameters (the shape and size of the solid particle, as well as the velocity of the airflow) and the monitored parameters. A pyramid-type analysis (following a filtering system, a general equation was determined from a large number of equations that characterize an experimental set mathematically) was designed in order to determine a single mathematical equation that describes the correlation between the input variables and those obtained as accurately as possible. The determination of the mathematical equation started with the number of equations generated by the Table Curve 3D program; then, the equations with a correlation coefficient greater than 0.85 were chosen; and finally, the common equations were identified. Respecting the working methodology, one equation was identified, which has for the average linear velocity, a correlation coefficient r2 of between 0.88-0.99 and 0.86–0.99 for the angular velocity.

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“…Following a set of experimental determinations, it is advisable to design a mathematical model, thus generating equations with which they can be tracking, analysed and optimized different industrial processes [27][28][29][30][31][32][33][34][35][36][37][38][39][40][41].…”

Section: Introductionmentioning

confidence: 99%

Identify the Mathematical Models Generated by the Table Curve 3 D Program

Moșneguțu¹,

Panainte-Lehăduș²,

Nedeff³

et al. 2022

Preprint

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This article describes the methodology used to identify the mathematical model that describes the correlations between the input parameters of an experiment and the parameters being followed. As a technological process, the aerodynamic separation was chosen, respectively, the behavior of a solid particle within an ascending vertical airflow. The experimental data obtained were used to identify two parameters, the average linear velocity, and the angular velocity, and through the Table Curve 3D program was developed a mathematical model which describes the dependence between the input parameters (the shape and size of the solid particle and the velocity of the airflow) and the monitored parameters. In order to determine a single mathematical equation that describes as accurately as possible the correlation between the input variables and those obtained, a pyramid-type analysis was designed. The determination of the mathematical equation started from the number of equations generated by the Table Curve 3D program, then the equations with a correlation coefficient greater than 0.85 were chosen, and finally, the common equations were identified. Respecting the working methodology was identified one equation which has for the average linear velocity a correlation coefficient r2 between 0.88-0.99 and 0.86-0.99 for the angular velocity.

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A Mathematical Model of Membrane Gas Separation with Energy Transfer by Molecules of Gas Flowing in a Channel to Molecules Penetrating this Channel from the Adjacent Channel

Cited by 6 publications

References 9 publications

Recent Advances in Reducing Food Losses in the Supply Chain of Fresh Agricultural Produce

Recent Advances in Reducing Food Losses in the Supply Chain of Fresh Agricultural Produce

Extraction of Mathematical Correlations Applied in the Aerodynamic Separation of Solid Particles

Identify the Mathematical Models Generated by the Table Curve 3 D Program

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