scholarly journals Mechanistic and Machine Learning Modeling of Microwave Heating Process in Domestic Ovens: A Review

Foods ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 2029
Author(s):  
Ran Yang ◽  
Jiajia Chen

The domestic microwave oven has been popularly used at home in heating foods for its rapid heating rate and high power efficiency. However, non-uniform heating by microwave is the major drawback that can lead to severe food safety and quality issues. In order to alleviate this problem, modeling of microwave heating process in domestic ovens has been employed to simulate and understand the complicated interactions between microwaves and food products. This paper extensively reviews the mechanistic models with different geometric dimensions and physics/kinetics that simulated the microwave heating process. The model implementation and validation strategies related to the model accuracy and efficiency are also discussed. With the emergence of the machine learning technique, this paper also discusses the recent development of hybrid models that integrate machine learning with mechanistic models in improving microwave heating performance. Besides, pure machine learning models using only experimental data as input are also covered. Further research is needed to improve the model accuracy, efficiency, and ease of use to enable the industrial application of the models in the development of microwave systems and food products.

Processes ◽  
2018 ◽  
Vol 6 (9) ◽  
pp. 142 ◽  
Author(s):  
Weiquan Ma ◽  
Tao Hong ◽  
Tian Xie ◽  
Fengxia Wang ◽  
Bin Luo ◽  
...  

Oleic acid needs to be heated when it is utilized for biodiesel production, but, as a low-loss solution, oleic acid is difficult to heat by microwave. An efficient heating method for oleic acid is designed. A high loss material porous media is placed in a quartz tube, and a microwave directly heats the porous medium of the high loss material. The oleic acid flows through the pores of porous media so that the oleic acid exchanges heat during this process and rapid heating of oleic acid is achieved. A coupling model, based on the finite element method, is used to analyze the microwave heating process. The multiphysics model is based on a single mode cavity operating at 2450 MHz. An elaborate experimental system is developed to validate the multiphysics model through temperature measurements carried out for different flow velocities of oleic acid and different microwave power levels. The computational results are in good agreement with the experimental data. Based on the validated model, the effects of different sizes, porosities, and materials on microwave heating efficiency are analyzed.


2013 ◽  
Vol 58 (3) ◽  
pp. 919-922 ◽  
Author(s):  
K. Granat ◽  
B. Opyd ◽  
D. Nowak ◽  
M. Stachowicz ◽  
G. Jaworski

Abstract The paper describes preliminary examinations on establishing usefulness criteria of foundry tooling materials in the microwave heating technology. Presented are measurement results of permittivity and loss tangent that determine behaviour of the materials in electromagnetic field. The measurements were carried-out in a waveguide resonant cavity that permits precise determination the above-mentioned parameters by perturbation technique. Examined were five different materials designed for use in foundry tooling. Determined was the loss factor that permits evaluating usefulness of materials in microwave heating technology. It was demonstrated that the selected plastics meet the basic criterion that is transparency for electromagnetic radiation.


2018 ◽  
Vol 15 (1) ◽  
pp. 47-55
Author(s):  
Xuebing Li ◽  
Haifen Yang ◽  
Ning Wang ◽  
Tijian Sun ◽  
Wei Bian ◽  
...  

Background: Morin has many pharmacological functions including antioxidant, anticancer, anti-inflammatory, and antibacterial effects. It is commonly used in the treatment of antiviral infection, gastropathy, coronary heart disease and hepatitis B in clinic. However, researches have shown that morin is likely to show prooxidative effects on the cells when the amount of treatment is at high dose, leading to the decrease of intracellular ATP levels and the increase of necrosis process. Therefore, it is necessary to determine the concentration of morin in biologic samples. Method: Novel water-soluble and green nitrogen and sulfur co-doped carbon dots (NSCDs) were prepared by a microwave heating process with citric acid and L-cysteine. The fluorescence spectra were collected at an excitation wavelength of 350 nm when solutions of NSCDs were mixed with various concentrations of morin. Results: The as-prepared NSCDs were characterized by transmission electron microscopy, X-ray diffraction and X-ray photoelectron spectroscopy. The fluorescence intensity of NSCDs decreased significantly with the increase of morin concentration. The fluorescence intensity of NSCDs displayed a linear response to morin in the concentration 0.10-30 μM with a low detection limit of 56 nM. The proposed fluorescent probe was applied to analysis of morin in human body fluids with recoveries of 98.0-102%. Conclusion: NSCDs were prepared by a microwave heating process. The present analytical method is sensitive to morin. The quenching process between NSCDs and morin is attributed to the static quenching. In addition, the cellular toxicity on HeLa cells indicated that the as-prepared NSCDs fluorescent probe does not show obvious cytotoxicity in cell imaging. Our proposed method possibly opens up a rapid and nontoxic way for preparing heteroatom doped carbon dots with a broad application prospect.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
William Greig Mitchell ◽  
Edward Christopher Dee ◽  
Leo Anthony Celi

AbstractCho et al. report deep learning model accuracy for tilted myopic disc detection in a South Korean population. Here we explore the importance of generalisability of machine learning (ML) in healthcare, and we emphasise that recurrent underrepresentation of data-poor regions may inadvertently perpetuate global health inequity.Creating meaningful ML systems is contingent on understanding how, when, and why different ML models work in different settings. While we echo the need for the diversification of ML datasets, such a worthy effort would take time and does not obviate uses of presently available datasets if conclusions are validated and re-calibrated for different groups prior to implementation.The importance of external ML model validation on diverse populations should be highlighted where possible – especially for models built with single-centre data.


2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Zhigang Li ◽  
Xiaoming Zhang ◽  
Yuichi Sugai ◽  
Jiren Wang ◽  
Kyuro Sasaki

Combustion and gasification properties of pulverized coal and char have been investigated experimentally under the conditions of high temperature gradient of order 200°C·s−1by a CO2gas laser beam and CO2-rich atmospheres with 5% and 10% O2. The laser heating makes a more ideal experimental condition compared with previous studies with a TG-DTA, because it is able to minimize effects of coal oxidation and combustion by rapid heating process like radiative heat transfer condition. The experimental results indicated that coal weight reduction ratio to gases followed the Arrhenius equation with increasing coal temperature; further which were increased around 5% with adding H2O in CO2-rich atmosphere. In addition, coal-water mixtures with different water/coal mass ratio were used in order to investigate roles of water vapor in the process of coal gasification and combustion. Furthermore, char-water mixtures with different water/char mass ratio were also measured in order to discuss the generation ratio of CO/CO2, and specified that the source of Hydrocarbons is volatile matter from coal. Moreover, it was confirmed that generations of CO and Hydrocarbons gases are mainly dependent on coal temperature and O2concentration, and they are stimulated at temperature over 1000°C in the CO2-rich atmosphere.


2020 ◽  
Vol 39 (1) ◽  
pp. 54-62
Author(s):  
Hua Chen ◽  
Junjiang Chen ◽  
Weijun Wang ◽  
Huan Lin

AbstractThe multimode resonant cavity is the most common cavity. The material often shows on selective heating performance during the heating process due to the effect of microwave heating having a closely relationship with the electromagnetism parameters. This paper is based on finite difference time domain method (FDTD) to establish the electromagnetic-thermal model. The electromagnetic sensitivity property parameters of sodium chloride including relative dielectric constant, loss angle tangent and water content of sodium chloride is studied during the heating and drying process. The heating rate and the electric field distribution of sodium chloride, at the different water content, were simulated with the electromagnetic characteristic parameters changing. The results show that with the electromagnetic sensitivity property parameters varying, the electric field strength, heating rate and steady-state temperature of the heating material will all have a variety in the cavity. Some measures are proposed to improve the heating efficiency and ensure the stability of the microwave heating system in the industrial application.


2021 ◽  
Vol 45 (4) ◽  
Author(s):  
Stefanie Jauk ◽  
Diether Kramer ◽  
Alexander Avian ◽  
Andrea Berghold ◽  
Werner Leodolter ◽  
...  

AbstractEarly identification of patients with life-threatening risks such as delirium is crucial in order to initiate preventive actions as quickly as possible. Despite intense research on machine learning for the prediction of clinical outcomes, the acceptance of the integration of such complex models in clinical routine remains unclear. The aim of this study was to evaluate user acceptance of an already implemented machine learning-based application predicting the risk of delirium for in-patients. We applied a mixed methods design to collect opinions and concerns from health care professionals including physicians and nurses who regularly used the application. The evaluation was framed by the Technology Acceptance Model assessing perceived ease of use, perceived usefulness, actual system use and output quality of the application. Questionnaire results from 47 nurses and physicians as well as qualitative results of four expert group meetings rated the overall usefulness of the delirium prediction positively. For healthcare professionals, the visualization and presented information was understandable, the application was easy to use and the additional information for delirium management was appreciated. The application did not increase their workload, but the actual system use was still low during the pilot study. Our study provides insights into the user acceptance of a machine learning-based application supporting delirium management in hospitals. In order to improve quality and safety in healthcare, computerized decision support should predict actionable events and be highly accepted by users.


2017 ◽  
Vol 42 (2) ◽  
pp. e13468
Author(s):  
Pu Guang Yi ◽  
Pu Cheng Xi ◽  
Jun Wang ◽  
Song Chun Fang

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