Aditya Putranto

Modeling of Drying of Food Materials with Thickness of Several Centimeters by the Reaction Engineering Approach (REA)

Food materials are highly perishable. Drying is necessary to restrict biological and chemical activity to extend shelf life. A good drying model is useful for design of a better dryer, evaluation of dryer performance, prediction of product quality, and optimization. The reaction engineering approach (REA) is a simple-lumped parameter model revealed to be accurate and robust to model drying of various thin layers or small objects. Modeling drying behavior of different sizes is essential for a good drying model, yet it is still very challenging, even for a traditional diffusion-based model, which requires several sets of experiments to generate the diffusivity function. The REA is implemented in this study, for the first time, to model drying of rather thick samples of food materials. An approximate spatial distribution of sample temperature is introduced and combined with the REA to model drying kinetics. Results have indicated that the REA can model both moisture content and temperature profiles. The accuracy and effectiveness of the REA to model drying of thick samples of food materials are revealed in this study. This has extended the application of REA substantially. The application of the REA is currently not restricted for thin layesr or small objects but also for thick samples.

Simple, Accurate and Robust Modeling of Various Systems of Drying of Foods and Biomaterials: A Demonstration of the Feasibility of the Reaction Engineering Approach (REA)

A simple and effective drying model is desirable for evaluation of dryer performance, optimization, and evaluation of product quality. It should be able to model the phenomena of the drying process and yet be favorable for quick decision-making in industries. Ideally, it should require a minimum number of experiments to generate the parameters. Reaction engineering approach (REA) has been shown for many years to be an alternative model for convective air drying of various dairy products. In this paper, a demonstration of the flexibilities of the REA is given for modeling various systems of drying of foods and biomaterials, including convective drying of grain, fruit tissues, and biomaterials as well as intermittent drying of grain and fruit tissues. While the results are accurate, the modeling itself has still proven to be simple. These exercises are very encouraging and have set up a good foundation for a wider range of applications in the near future.

Drying and Denaturation Kinetics of Whey Protein Isolate (WPI) During Convective Air Drying Process

The denaturation and drying kinetics of whey protein isolate (WPI) in a convective drying (CD) environment was measured using single droplet drying experiments. The moisture content and temperature histories during drying of WPI droplets were predicted using reaction kinetics–based models. The denaturation kinetics of WPI in the CD process was predicted using first-order reaction kinetics considering the denaturation rate constant to be moisture content and temperature dependent. Single droplets of WPI (10% [w/v], 2.0 ± 0.1 mm initial diameter) were used throughout these experiments. The drying experiments were carried out at two temperatures (65 and 80°C) at a constant air velocity (0.5 m/s) for 600 s. The extent and nature of the denaturation of WPI during the CD was compared with those in isothermal heat treatments (IHT) at the same medium temperatures. The denaturation of WPI was 68.31% in convective air drying at 65°C and 600 s and it was 10.79% in the IHT at the same temperature and time. The stress due to dehydration and the exposure time were found to be responsible for the denaturation of WPI in the CD process and long exposure time was found to be responsible for its denaturation in the IHT process. At the media temperature of 80°C, the denaturation loss of WPI was 90.00 and 68.73% in IHT and CD processes, respectively. Both the thermal (moist heat) and dehydration stresses were found to be responsible for denaturation of WPI during CD process and very high thermal stress was found to be responsible for denaturation of WPI during the IHT. There was good agreement between the experimental and reaction engineering approach (REA)-predicted moisture content and temperature histories. The experimental moisture content and temperature histories were followed by the respective REA predictions within 6.5% (R 2 = 0.995) and 3% (R 2 = 0.981) errors, respectively. The denaturation kinetics of WPI during CD was predicted well (R 2 = 0.95 – 0.98; average error = 6.5 ± 0.5%) by a first-order reaction kinetics model.

Roasting of Barley and Coffee Modeled Using the Lumped-Reaction Engineering Approach (L-REA)

Roasting is a complex process of simultaneous heat and mass transfer involving water removal as well as color and flavor changes. In this study, the lumped-reaction engineering approach (L-REA) was implemented to model roasting of barley and coffee. The approach was able to capture the details of the process kinetics and the predictions matched the experimental data well. Benchmarks against the diffusion-based model indicated that the L-REA yielded comparable or even better results. As such, the L-REA approach can be adopted for simulation of the roasting process and optimization or model-based control strategies.

Modeling Intermittent Drying of Wood under Rapidly Varying Temperature and Humidity Conditions with the Lumped Reaction Engineering Approach (L-REA)

For improving product quality and minimizing energy consumption during drying, intermittent drying is often recommended. The mathematical models that are used to describe intermittent drying are usually transport phenomena based, complex models. In this study, the lumped reaction engineering approach (L-REA) is implemented to model wood drying under rapid periodically changed drying air temperature and humidity with high number of cycles of intermittency. The equilibrium activation energy (ΔE v,b ), an important parameter for REA approach, is evaluated according to the corresponding drying air temperature and humidity in each drying section. The results of modeling suggest the L-REA works well with the experimental data. The simplicity of the L-REA is obvious and is hoped to be used in an industrial setting more readily. The L-REA can be used for sustainable processing in industries to assist in energy audit and management.

Modeling of high-temperature treatment of wood using the reaction engineering approach (REA)

A simple and accurate model of high-temperature treatment of wood can assist in the process design and the evaluation of performance of equipment. The high-temperature treatment of wood is essentially a drying process under linearly-increased gas temperature up to final temperature of 220-230°C which is a challenging process to model. This study is aimed to assess the applicability and accuracy of the reaction engineering approach (REA) to model the heat treatment of wood. In order to describe the process using the REA, the maximum activation energy (ΔE(v,b)) is evaluated according to the corresponding external conditions during the heat treatment. Results indicate that the REA coupled with the heat balance describes both moisture content and temperature profiles during the heat treatment very well. A good agreement towards the experimental data is indicated. It has also been shown that the current model is highly comparable in accuracy with the complex models.

Examining the Suitability of the Reaction Engineering Approach (REA) to Modeling Local Evaporation/Condensation Rates of Materials with Various Thicknesses

The reaction engineering approach (REA) is examined here to investigate its suitability as the local evaporation rate to be used in multiphase drying. For this purpose, REA is first implemented to model the convective drying of materials with various thicknesses. The relative activation energy, as the fingerprint of REA, generated from one size of a material is used to model the convective drying of the same material with different thicknesses. Because the results indicate that REA parameters can model the drying of materials with various thicknesses, REA can be scaled down to describe the local evaporation rate (at the microscale as affected by local composition and temperature). The relative activation energy is used to describe the global drying rate in modeling the local evaporation rate. REA is combined with a system of equations of conservation of heat and mass transfer in order to yield the spatial reaction engineering approach (S-REA) as a nonequilibrium multiphase drying model. By using S-REA, the spatial profiles of moisture content, concentration of water vapor, temperature, and local evaporation rate can be generated, which can assist in comprehending the transport phenomena.

The Relative Activation Energy of Food Materials: Important Parameters to Describe Drying Kinetics

An effective drying model should be accurate and require a small number of experiments to generate the parameters. The relative activation energy of various food materials, important drying kinetic properties used in the reaction engineering approach, is evaluated and summarized. The reaction engineering approach is then implemented to model the global and local drying rates of food materials. By using the relative activation energy, the reaction engineering approach describes the (R2 higher than 0.99) global drying rate of food materials well. The reaction engineering approach can be coupled with a set of equations of conservation of heat and mass transfer to model the local drying rate of food materials. The relative activation energy is indeed proven to be accurate to model the local drying rate. While the predictions are accurate, the reaction engineering approach is very effective in generating the drying parameters since the relative activation energy can be generated from one accurate drying run. Different drying conditions of the same material with similar initial moisture content would result in the similar relative activation energies. The drying kinetics parameters generated here are readily used for design of new equipment, evaluating the performance of existing dryers, and monitoring the product quality.

Microwave drying at various conditions modeled using the reaction engineering approach

ABSTRACT One of the most significant process intensification schemes in drying is microwave drying. Modeling the process of microwave drying is very useful. The lumped reaction engineering approach (REA) is now coupled with appropriate equations for modeling microwave heating. Here, a slight modification of the equilibrium activation energy is needed since the product temperature is higher than the ambient temperature. Unlike the diffusion-based approach, the REA drying parameters were generated from minimum number of drying runs. It has been found that the modifications lead to excellent agreements between the predicted and experimental data. The results of modeling match well with the experimental data. The overall model is accurate to describe the moisture content and temperature profiles. Comparisons with the diffusion-based approach indicate that the REA can achieve comparable or even better agreement toward the experimental data. This exercise has demonstrated that a simple combination of the lumped reaction engineering approach and the microwave energy absorption is versatile in predicting the microwave drying process accurately; thus, this worked example will be illustrative for future needed studies.

Application of the reaction engineering approach (REA) for modeling of the convective drying of onion

ABSTRACT In this study, the drying of thin layers of the “Violet de Galmi” onion (a variety mainly grown in West Africa) is presented in this article, along with the reaction engineering approach (REA) modeling for a comprehensive understanding of the drying kinetics. The experiments were conducted on a lab-scale dryer to form thin layer of cylindrical onion slice. By performing this experiment, the standard activation energy is evaluated and modeled. The model is validated by simulating the drying rates under various drying conditions. The comparison of simulation and experimental data is found to be satisfactory. This approach allows the determination of the internal characteristics of the onion for the further studies such as design of solar dryer for onion.