Multiphysics Modeling of Microwave Heating of a Frozen Heterogeneous Meal Rotating on a Turntable

Lau

Food and Bioproducts Processing

et al. 2017

Self Cite

A multiphysics model that coupled electric fields and heat transfer was developed to simulate the radio frequency (RF) heating of food moving on a conveyor belt. A discrete moving step approach was used in the simulation. The total power absorption increased considerably during the entry of the sample into the RF system, remained stable when the sample was fully covered by the top and bottom electrodes, and decreased when the sample moved out of the system. Edge and corner heating was observed from the power absorption distribution and electric field distribution. The model was validated by heating a rectangular container of wheat kernels moving on a conveyor belt in a RF system (27.12 MHz, 6 kW). The predicted spatial temperatures in top, middle, and bottom layers showed less than 3.5 °C lower prediction than the experimental result. The measured anode current showed a good linear correlation with the predicted total power absorption. The optimum number of discrete moving steps was determined to be nine for accurate temperature prediction with total conveyor belt movement distance of 1.13 m which is equivalent to optimize step size of 0.1256 m/step (0.3 m for entry and exit, respectively, and 0.53 m for fully covered by electrodes) at speed of 14.23 m h-1. The movement of food product could help improve the heating uniformity of RF heating process.

Section: Introductionmentioning

confidence: 99%

Modeling radio frequency heating of food moving on a conveyor belt

Lau

Food and Bioproducts Processing

et al. 2017

Self Cite

“…2(c). Earlier research [30,41,44,45] work have showed an agreement of maximum rise in transient temperature at the central core region during continuous microwave heating. Therefore, it will be interesting and of direct utilities to understand the temperature distribution and thermal containment behavior of tissue phantom infused with dielectric nanoparticles compared to tissue without nanoparticles (W.N.P).…”

Section: Thermal Efficacy Of Nanoparticle Mediated Microwave Heatingmentioning

confidence: 81%

Thermal Response of Dielectric Nanoparticle Infused Tissue Phantoms during Microwave Assisted Hyperthermia

Kumar¹,

Dhar²,

Paul³

2020

Preprint

Hyperthermia has been in use for many years; as a potential alternative modality for cancer treatment. In this paper, an experimental investigation of microwave assisted thermal heating (MWATH) of tissue phantom using a domestic microwave oven has been reported. Computer simulations using finite element method based tools was also carried out to support the experimental observations and probe insight on the thermal transport aspects deep within the tissue phantom. A good agreement between predicted and measured temperature were achieved. Furthermore, experiments were conducted to investigate the efficacy of dielectric nanoparticles viz. alumina (Al 2 O 3 ) and titanium oxide (TiO 2 ) during the MWATH of nanoparticle infused tumor phantoms. A deep seated tumor injected with nanoparticle solution was specifically mimicked in the experiments. Interesting results were obtained in terms of spatiotemporal thermal history of the nanoparticle infused tissue

“…The conclusion could help properly determine the most significant parameters for a reliable model. Another porous material heating model by Pitchai et al [ 49 ] that simulated the rotational microwave heating of a heterogeneous sample (lasagna) was developed and validated. The heterogeneous lasagna sample with 6 layers, composed of meat sauce, pasta, ricotta cheese, pasta, meat sauce, and pasta from top to bottom layer, was used as a model food.…”

Section: Mechanistic Modelsmentioning

confidence: 99%

“…In addition to thermal profiles, in models that simulate the heating process of foods with high moisture or in small volume size, where the mass transfer can make a great difference to the final results, the moisture change due to the microwave power should also be validated. The total moisture loss [ 3 , 46 , 49 , 50 , 67 , 72 , 73 ] and/or transient point moisture content [ 74 ] have been measured for validation. Besides, the pressure generated due to moisture evaporation was also measured for validation [ 46 ].…”

Section: Mechanistic Modelsmentioning

confidence: 99%

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

Yang

2021

Foods

Self Cite

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.